From c93947be9db0d1c6eafb5f93b37628645ad3c261 Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Tue, 8 Nov 2022 14:59:05 +0000
Subject: [PATCH 01/28] [WIP] Reformating Unet

---
 .../networks/nets/diffusion_model_unet.py     | 608 +++++++++---------
 1 file changed, 309 insertions(+), 299 deletions(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index c78a4ca7..9003a9bf 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -10,7 +10,6 @@
 # limitations under the License.
 
 import math
-from abc import abstractmethod
 from typing import Optional, Sequence, Tuple
 
 import torch
@@ -165,6 +164,15 @@ def forward(self, x: torch.Tensor, context: Optional[torch.Tensor] = None) -> to
         return x
 
 
+def zero_module(module: nn.Module) -> nn.Module:
+    """
+    Zero out the parameters of a module and return it.
+    """
+    for p in module.parameters():
+        p.detach().zero_()
+    return module
+
+
 class SpatialTransformer(nn.Module):
     """
     Transformer block for image-like data. First, project the input (aka embedding) and reshape to b, t, d. Then apply
@@ -259,61 +267,6 @@ def forward(self, x: torch.Tensor, context: Optional[torch.Tensor] = None) -> to
         return x + x_in
 
 
-def timestep_embedding(timesteps: int, dim: int, max_period: int = 10000) -> torch.Tensor:
-    """
-    This matches the implementation in Denoising Diffusion Probabilistic Models: Create sinusoidal timestep embeddings.
-
-    Args:
-        timesteps: a 1-D Tensor of N indices, one per batch element.
-        dim: the dimension of the output.
-        max_period: controls the minimum frequency of the embeddings.
-    """
-    half = dim // 2
-    freqs = torch.exp(-math.log(max_period) * torch.arange(start=0, end=half, dtype=torch.float32) / half).to(
-        device=timesteps.device
-    )
-    args = timesteps[:, None].float() * freqs[None]
-    embedding = torch.cat([torch.cos(args), torch.sin(args)], dim=-1)
-    if dim % 2:
-        embedding = torch.cat([embedding, torch.zeros_like(embedding[:, :1])], dim=-1)
-
-    return embedding
-
-
-def zero_module(module: nn.Module) -> nn.Module:
-    """
-    Zero out the parameters of a module and return it.
-    """
-    for p in module.parameters():
-        p.detach().zero_()
-    return module
-
-
-class TimestepBlock(nn.Module):
-    @abstractmethod
-    def forward(self, x: torch.Tensor, emb: torch.Tensor):
-        """
-        Apply the module to `x` given `emb` timestep embeddings.
-        """
-
-
-class TimestepEmbedSequential(nn.Sequential, TimestepBlock):
-    """
-    A sequential module that passes timestep embeddings to the children that
-    support it as an extra input.
-    """
-
-    def forward(self, x: torch.Tensor, emb: torch.Tensor, context: Optional[torch.Tensor] = None) -> torch.Tensor:
-        for layer in self:
-            if isinstance(layer, TimestepBlock):
-                x = layer(x, emb)
-            elif isinstance(layer, SpatialTransformer):
-                x = layer(x, context)
-            else:
-                x = layer(x)
-        return x
-
-
 class QKVAttentionLegacy(nn.Module):
     """
     A qkv attention mechanism.
@@ -338,8 +291,6 @@ def forward(self, qkv: torch.Tensor) -> torch.Tensor:
         return a.reshape(bs, -1, length)
 
 
-# TODO: Check if could use MONAI's SABlock instead.
-# https://github.com/Project-MONAI/MONAI/blob/1516ca758090dd8ed2890b64554a77f681a0e224/monai/networks/blocks/selfattention.py#L20
 class AttentionBlock(nn.Module):
     """
     An attention block.
@@ -384,6 +335,31 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
         return (x + h).reshape(b, c, *spatial)
 
 
+def get_timestep_embedding(timesteps: int, embedding_dim: int, max_period: int = 10000) -> torch.Tensor:
+    """
+    This matches the implementation in Denoising Diffusion Probabilistic Models: Create sinusoidal timestep embeddings.
+
+    Args:
+        timesteps: a 1-D Tensor of N indices, one per batch element.
+        embedding_dim: the dimension of the output.
+        max_period: controls the minimum frequency of the embeddings.
+    """
+    assert len(timesteps.shape) == 1, "Timesteps should be a 1d-array"
+
+    half_dim = embedding_dim // 2
+    exponent = -math.log(max_period) * torch.arange(start=0, end=half_dim, dtype=torch.float32, device=timesteps.device)
+    freqs = torch.exp(exponent / half_dim)
+
+    args = timesteps[:, None].float() * freqs[None, :]
+    embedding = torch.cat([torch.cos(args), torch.sin(args)], dim=-1)
+
+    # zero pad
+    if embedding_dim % 2 == 1:
+        embedding = torch.nn.functional.pad(embedding, (0, 1, 0, 0))
+
+    return embedding
+
+
 class Downsample(nn.Module):
     """
     Downsampling layer.
@@ -472,18 +448,16 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
         return x
 
 
-class ResBlock(TimestepBlock):
+class ResnetBlock(nn.Module):
     """
     Residual block with timestep conditioning.
 
     Args:
         spatial_dims: The number of spatial dimensions.
-        channels: number of input channels
-        emb_channels: number of timestep embedding  channels
-        dropout: dropout probability to use.
+        in_channels: number of input channels
+        temb_channels: number of timestep embedding  channels
         out_channels: number of output channels.
         use_conv: if True uses Convolution instead of Identity in skip connection.
-        use_scale_shift_norm: if True, performs a scale-shift normalization.
         up: if True, performs upsampling.
         down: if True, performs downsampling.
         norm_num_groups: number of groups for the group normalization.
@@ -493,31 +467,27 @@ class ResBlock(TimestepBlock):
     def __init__(
         self,
         spatial_dims: int,
-        channels: int,
-        emb_channels: int,
-        dropout: float = 0.0,
+        in_channels: int,
+        temb_channels: int,
         out_channels: Optional[int] = None,
         use_conv: bool = False,
-        use_scale_shift_norm: bool = False,
         up: bool = False,
         down: bool = False,
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
     ) -> None:
         super().__init__()
-        self.channels = channels
-        self.emb_channels = emb_channels
-        self.dropout = dropout
-        self.out_channels = out_channels or channels
+        self.channels = in_channels
+        self.emb_channels = temb_channels
+        self.out_channels = out_channels or in_channels
         self.use_conv = use_conv
-        self.use_scale_shift_norm = use_scale_shift_norm
 
         self.in_layers = nn.Sequential(
-            nn.GroupNorm(num_groups=norm_num_groups, num_channels=channels, eps=norm_eps, affine=True),
+            nn.GroupNorm(num_groups=norm_num_groups, num_channels=in_channels, eps=norm_eps, affine=True),
             nn.SiLU(),
             Convolution(
                 spatial_dims=spatial_dims,
-                in_channels=channels,
+                in_channels=in_channels,
                 out_channels=self.out_channels,
                 strides=1,
                 kernel_size=3,
@@ -529,25 +499,24 @@ def __init__(
         self.updown = up or down
 
         if up:
-            self.h_upd = Upsample(spatial_dims, channels, False)
-            self.x_upd = Upsample(spatial_dims, channels, False)
+            self.h_upd = Upsample(spatial_dims, in_channels, False)
+            self.x_upd = Upsample(spatial_dims, in_channels, False)
         elif down:
-            self.h_upd = Downsample(spatial_dims, channels, False)
-            self.x_upd = Downsample(spatial_dims, channels, False)
+            self.h_upd = Downsample(spatial_dims, in_channels, False)
+            self.x_upd = Downsample(spatial_dims, in_channels, False)
         else:
             self.h_upd = self.x_upd = nn.Identity()
 
         self.emb_layers = nn.Sequential(
             nn.SiLU(),
             nn.Linear(
-                emb_channels,
-                2 * self.out_channels if use_scale_shift_norm else self.out_channels,
+                temb_channels,
+                self.out_channels,
             ),
         )
         self.out_layers = nn.Sequential(
             nn.GroupNorm(num_groups=norm_num_groups, num_channels=self.out_channels, eps=norm_eps, affine=True),
             nn.SiLU(),
-            nn.Dropout(p=dropout),
             zero_module(
                 Convolution(
                     spatial_dims=spatial_dims,
@@ -561,12 +530,12 @@ def __init__(
             ),
         )
 
-        if self.out_channels == channels:
+        if self.out_channels == in_channels:
             self.skip_connection = nn.Identity()
         elif use_conv:
             self.skip_connection = Convolution(
                 spatial_dims=spatial_dims,
-                in_channels=channels,
+                in_channels=in_channels,
                 out_channels=self.out_channels,
                 strides=1,
                 kernel_size=3,
@@ -577,7 +546,7 @@ def __init__(
         else:
             self.skip_connection = Convolution(
                 spatial_dims=spatial_dims,
-                in_channels=channels,
+                in_channels=in_channels,
                 out_channels=self.out_channels,
                 strides=1,
                 kernel_size=1,
@@ -597,14 +566,9 @@ def forward(self, x: torch.Tensor, emb: torch.Tensor) -> torch.Tensor:
         emb_out = self.emb_layers(emb).type(h.dtype)
         while len(emb_out.shape) < len(h.shape):
             emb_out = emb_out[..., None]
-        if self.use_scale_shift_norm:
-            out_norm, out_rest = self.out_layers[0], self.out_layers[1:]
-            scale, shift = torch.chunk(emb_out, 2, dim=1)
-            h = out_norm(h) * (1 + scale) + shift
-            h = out_rest(h)
-        else:
-            h = h + emb_out
-            h = self.out_layers(h)
+
+        h = h + emb_out
+        h = self.out_layers(h)
         return self.skip_connection(x) + h
 
 
@@ -632,8 +596,163 @@ def get_attention_parameters(
     return dim_head, num_heads
 
 
-# TODO: Replace TimestepEmbedSequential by using an approach similar to huggingface diffusers
-#  https://github.com/huggingface/diffusers/blob/2d35f6733a2d698e8917896071444a5923993ae7/src/diffusers/models/unet_2d.py#L38
+class DownBlock(nn.Module):
+    def __init__(
+        self,
+        spatial_dims: int,
+        in_channels: int,
+        out_channels: int,
+        temb_channels: int,
+        num_res_blocks: int = 1,
+        norm_eps: float = 1e-6,
+        norm_num_groups: int = 32,
+        add_downsample=True,
+        downsample_padding=1,
+    ):
+        super().__init__()
+        resnets = []
+
+        for i in range(num_res_blocks):
+            in_channels = in_channels if i == 0 else out_channels
+            resnets.append(
+                ResnetBlock(
+                    spatial_dims=spatial_dims,
+                    in_channels=in_channels,
+                    out_channels=out_channels,
+                    temb_channels=temb_channels,
+                    norm_num_groups=norm_num_groups,
+                    norm_eps=norm_eps,
+                )
+            )
+
+        self.resnets = nn.ModuleList(resnets)
+
+        if add_downsample:
+            self.downsampler = Downsample(
+                spatial_dims=spatial_dims,
+                channels=out_channels,
+                use_conv=True,
+                out_channels=out_channels,
+                padding=downsample_padding,
+            )
+        else:
+            self.downsampler = None
+
+    def forward(self, hidden_states: torch.Tensor, temb: torch.Tensor) -> Tuple[torch.Tensor, Tuple]:
+        output_states = ()
+
+        for resnet in self.resnets:
+            hidden_states = resnet(hidden_states, temb)
+            output_states += (hidden_states,)
+
+        if self.downsampler is not None:
+            hidden_states = self.downsampler(hidden_states)
+            output_states += (hidden_states,)
+
+        return hidden_states, output_states
+
+
+class MidBlock(nn.Module):
+    def __init__(
+        self,
+        spatial_dims: int,
+        in_channels: int,
+        temb_channels: int,
+        norm_num_groups: int = 32,
+        norm_eps: float = 1e-6,
+        num_heads=1,
+        num_head_channels=1,
+    ):
+        super().__init__()
+
+        self.resnet_1 = ResnetBlock(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            out_channels=in_channels,
+            temb_channels=temb_channels,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+        )
+
+        self.attention = AttentionBlock(
+            channels=in_channels,
+            num_heads=num_heads,
+            num_head_channels=num_head_channels,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+        )
+        self.resnet_2 = ResnetBlock(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            out_channels=in_channels,
+            temb_channels=temb_channels,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+        )
+
+    def forward(self, hidden_states, temb=None):
+        hidden_states = self.resnet_1(hidden_states, temb)
+        hidden_states = self.attention(hidden_states)
+        hidden_states = self.resnet_2(hidden_states, temb)
+
+        return hidden_states
+
+
+class UpBlock(nn.Module):
+    def __init__(
+        self,
+        spatial_dims: int,
+        in_channels: int,
+        prev_output_channel: int,
+        out_channels: int,
+        temb_channels: int,
+        num_res_blocks: int = 1,
+        norm_eps: float = 1e-6,
+        norm_num_groups: int = 32,
+        add_upsample=True,
+    ):
+        super().__init__()
+        resnets = []
+
+        for i in range(num_res_blocks):
+            res_skip_channels = in_channels if (i == num_res_blocks - 1) else out_channels
+            resnet_in_channels = prev_output_channel if i == 0 else out_channels
+
+            resnets.append(
+                ResnetBlock(
+                    spatial_dims=spatial_dims,
+                    in_channels=resnet_in_channels + res_skip_channels,
+                    out_channels=out_channels,
+                    temb_channels=temb_channels,
+                    norm_num_groups=norm_num_groups,
+                    norm_eps=norm_eps,
+                )
+            )
+
+        self.resnets = nn.ModuleList(resnets)
+
+        if add_upsample:
+            self.upsampler = Upsample(
+                spatial_dims=spatial_dims, channels=out_channels, use_conv=True, out_channels=out_channels
+            )
+        else:
+            self.upsampler = None
+
+    def forward(self, hidden_states, res_hidden_states_tuple, temb=None):
+        for resnet in self.resnets:
+            # pop res hidden states
+            res_hidden_states = res_hidden_states_tuple[-1]
+            res_hidden_states_tuple = res_hidden_states_tuple[:-1]
+            hidden_states = torch.cat([hidden_states, res_hidden_states], dim=1)
+
+            hidden_states = resnet(hidden_states, temb)
+
+        if self.upsampler is not None:
+            hidden_states = self.upsampler(hidden_states)
+
+        return hidden_states
+
+
 class DiffusionModelUNet(nn.Module):
     """
     Unet network with timestep embedding and attention mechanisms for conditioning based on
@@ -647,11 +766,8 @@ class DiffusionModelUNet(nn.Module):
         out_channels: number of output channels.
         num_res_blocks: number of residual blocks (see ResBlock) per level.
         attention_resolutions: list of levels to add attention.
-        channel_mult: list of channel multipliers.
         num_heads: number of attention heads.
         num_head_channels: number of channels in each head.
-        use_scale_shift_norm:  if True, performs a scale-shift normalization in ResBlocks.
-        resblock_updown: if True, use ResBlocks to perform upsampling or downsampling.
         norm_num_groups: number of groups for the normalization.
         norm_eps: epsilon for the normalization.
         use_spatial_transformer: if True add spatial transformers to perform conditioning.
@@ -664,15 +780,12 @@ def __init__(
         self,
         spatial_dims: int,
         in_channels: int,
-        model_channels: int,
         out_channels: int,
         num_res_blocks: int,
-        attention_resolutions: Sequence[int],
-        channel_mult: Sequence[int] = (1, 2, 4, 8),
+        attention_resolutions: Sequence[int] = (False, False, True, True),
+        block_out_channels: Sequence[int] = (32, 64, 64, 64),
         num_heads: int = -1,
         num_head_channels: int = -1,
-        use_scale_shift_norm: bool = False,
-        resblock_updown: bool = False,
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
         use_spatial_transformer: bool = False,
@@ -695,219 +808,103 @@ def __init__(
             raise ValueError("DiffusionModelUNet expects that either num_heads or num_head_channels has to be set.")
 
         # The number of channels should be multiple of num_groups
-        if (model_channels % norm_num_groups) != 0:
-            raise ValueError("DiffusionModelUNet expects model_channels being multiple of norm_num_groups")
+        # if (model_channels % norm_num_groups) != 0:
+        #     raise ValueError("DiffusionModelUNet expects model_channels being multiple of norm_num_groups")
 
         self.in_channels = in_channels
-        self.model_channels = model_channels
+        self.block_out_channels = block_out_channels
         self.out_channels = out_channels
         self.num_res_blocks = num_res_blocks
         self.attention_resolutions = attention_resolutions
-        self.channel_mult = channel_mult
         self.num_heads = num_heads
         self.num_head_channels = num_head_channels
 
-        time_embed_dim = model_channels * 4
+        # input
+        self.conv_in = Convolution(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            out_channels=block_out_channels[0],
+            strides=1,
+            kernel_size=3,
+            padding=1,
+            conv_only=True,
+        )
+
+        # time
+        time_embed_dim = block_out_channels[0] * 4
         self.time_embed = nn.Sequential(
-            nn.Linear(model_channels, time_embed_dim),
+            nn.Linear(block_out_channels[0], time_embed_dim),
             nn.SiLU(),
             nn.Linear(time_embed_dim, time_embed_dim),
         )
 
-        self.input_blocks = nn.ModuleList(
-            [
-                TimestepEmbedSequential(
-                    Convolution(
-                        spatial_dims=spatial_dims,
-                        in_channels=in_channels,
-                        out_channels=model_channels,
-                        strides=1,
-                        kernel_size=3,
-                        padding=1,
-                        conv_only=True,
-                    )
-                )
-            ]
-        )
-        self._feature_size = model_channels
-        input_block_chans = [model_channels]
-        ch = model_channels
-        ds = 1
-        for level, mult in enumerate(channel_mult):
-            for _ in range(num_res_blocks):
-                layers = [
-                    ResBlock(
-                        spatial_dims=spatial_dims,
-                        channels=ch,
-                        emb_channels=time_embed_dim,
-                        out_channels=mult * model_channels,
-                        use_scale_shift_norm=use_scale_shift_norm,
-                        norm_num_groups=norm_num_groups,
-                        norm_eps=norm_eps,
-                    )
-                ]
-                ch = mult * model_channels
-                if ds in attention_resolutions:
-                    dim_head, num_heads = get_attention_parameters(
-                        ch, num_head_channels, num_heads, legacy, use_spatial_transformer
-                    )
-
-                    layers.append(
-                        AttentionBlock(
-                            ch,
-                            num_heads=num_heads,
-                            num_head_channels=dim_head,
-                            norm_num_groups=norm_num_groups,
-                            norm_eps=norm_eps,
-                        )
-                        if not use_spatial_transformer
-                        else SpatialTransformer(
-                            spatial_dims=spatial_dims,
-                            in_channels=ch,
-                            n_heads=num_heads,
-                            d_head=dim_head,
-                            depth=transformer_depth,
-                            norm_num_groups=norm_num_groups,
-                            norm_eps=norm_eps,
-                            context_dim=context_dim,
-                        )
-                    )
-                self.input_blocks.append(TimestepEmbedSequential(*layers))
-                self._feature_size += ch
-                input_block_chans.append(ch)
-            if level != len(channel_mult) - 1:
-                out_ch = ch
-                self.input_blocks.append(
-                    TimestepEmbedSequential(
-                        ResBlock(
-                            spatial_dims=spatial_dims,
-                            channels=ch,
-                            emb_channels=time_embed_dim,
-                            out_channels=out_ch,
-                            use_scale_shift_norm=use_scale_shift_norm,
-                            down=True,
-                            norm_num_groups=norm_num_groups,
-                            norm_eps=norm_eps,
-                        )
-                        if resblock_updown
-                        else Downsample(spatial_dims=spatial_dims, channels=ch, use_conv=True, out_channels=out_ch)
-                    )
-                )
-                ch = out_ch
-                input_block_chans.append(ch)
-                ds *= 2
-                self._feature_size += ch
+        # down
+        self.down_blocks = nn.ModuleList([])
+        output_channel = block_out_channels[0]
+        for i in range(len(block_out_channels)):
+            input_channel = output_channel
+            output_channel = block_out_channels[i]
+            is_final_block = i == len(block_out_channels) - 1
 
-        dim_head, num_heads = get_attention_parameters(
-            ch, num_head_channels, num_heads, legacy, use_spatial_transformer
-        )
-
-        self.middle_block = TimestepEmbedSequential(
-            ResBlock(
+            down_block = DownBlock(
                 spatial_dims=spatial_dims,
-                channels=ch,
-                emb_channels=time_embed_dim,
-                use_scale_shift_norm=use_scale_shift_norm,
-                norm_num_groups=norm_num_groups,
-                norm_eps=norm_eps,
-            ),
-            AttentionBlock(
-                ch,
-                num_heads=num_heads,
-                num_head_channels=dim_head,
+                in_channels=input_channel,
+                out_channels=output_channel,
+                temb_channels=time_embed_dim,
+                num_res_blocks=num_res_blocks,
                 norm_num_groups=norm_num_groups,
                 norm_eps=norm_eps,
+                add_downsample=not is_final_block,
             )
-            if not use_spatial_transformer
-            else SpatialTransformer(
-                spatial_dims=spatial_dims,
-                in_channels=ch,
-                n_heads=num_heads,
-                d_head=dim_head,
-                depth=transformer_depth,
-                norm_num_groups=norm_num_groups,
-                norm_eps=norm_eps,
-                context_dim=context_dim,
-            ),
-            ResBlock(
+            self.down_blocks.append(down_block)
+
+        # mid
+        dim_head, num_heads = get_attention_parameters(
+            block_out_channels[-1], num_head_channels, num_heads, legacy, use_spatial_transformer
+        )
+        self.middle_block = MidBlock(
+            spatial_dims=spatial_dims,
+            in_channels=block_out_channels[-1],
+            temb_channels=time_embed_dim,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+            num_heads=num_heads,
+            num_head_channels=dim_head,
+        )
+
+        # up
+        self.up_blocks = nn.ModuleList([])
+        reversed_block_out_channels = list(reversed(block_out_channels))
+        output_channel = reversed_block_out_channels[0]
+        for i in range(len(reversed_block_out_channels)):
+            prev_output_channel = output_channel
+            output_channel = reversed_block_out_channels[i]
+            input_channel = reversed_block_out_channels[min(i + 1, len(block_out_channels) - 1)]
+
+            is_final_block = i == len(block_out_channels) - 1
+
+            up_block = UpBlock(
                 spatial_dims=spatial_dims,
-                channels=ch,
-                emb_channels=time_embed_dim,
-                use_scale_shift_norm=use_scale_shift_norm,
+                in_channels=input_channel,
+                prev_output_channel=prev_output_channel,
+                out_channels=output_channel,
+                temb_channels=time_embed_dim,
+                num_res_blocks=num_res_blocks + 1,
                 norm_num_groups=norm_num_groups,
                 norm_eps=norm_eps,
-            ),
-        )
-        self._feature_size += ch
-
-        self.output_blocks = nn.ModuleList([])
-        for level, mult in list(enumerate(channel_mult))[::-1]:
-            for i in range(num_res_blocks + 1):
-                ich = input_block_chans.pop()
-                layers = [
-                    ResBlock(
-                        spatial_dims=spatial_dims,
-                        channels=ch + ich,
-                        emb_channels=time_embed_dim,
-                        out_channels=model_channels * mult,
-                        use_scale_shift_norm=use_scale_shift_norm,
-                        norm_num_groups=norm_num_groups,
-                        norm_eps=norm_eps,
-                    )
-                ]
-                ch = model_channels * mult
-                if ds in attention_resolutions:
-                    dim_head, num_heads = get_attention_parameters(
-                        ch, num_head_channels, num_heads, legacy, use_spatial_transformer
-                    )
-
-                    layers.append(
-                        AttentionBlock(
-                            ch,
-                            num_heads=num_heads,
-                            num_head_channels=dim_head,
-                            norm_num_groups=norm_num_groups,
-                            norm_eps=norm_eps,
-                        )
-                        if not use_spatial_transformer
-                        else SpatialTransformer(
-                            spatial_dims=spatial_dims,
-                            in_channels=ch,
-                            n_heads=num_heads,
-                            d_head=dim_head,
-                            depth=transformer_depth,
-                            norm_num_groups=norm_num_groups,
-                            norm_eps=norm_eps,
-                            context_dim=context_dim,
-                        )
-                    )
-                if level and i == num_res_blocks:
-                    out_ch = ch
-                    layers.append(
-                        ResBlock(
-                            spatial_dims=spatial_dims,
-                            channels=ch,
-                            emb_channels=time_embed_dim,
-                            out_channels=out_ch,
-                            use_scale_shift_norm=use_scale_shift_norm,
-                            up=True,
-                            norm_num_groups=norm_num_groups,
-                            norm_eps=norm_eps,
-                        )
-                        if resblock_updown
-                        else Upsample(spatial_dims=spatial_dims, channels=ch, use_conv=True, out_channels=out_ch)
-                    )
-                    ds //= 2
-                self.output_blocks.append(TimestepEmbedSequential(*layers))
-                self._feature_size += ch
+                add_upsample=not is_final_block,
+            )
+            self.up_blocks.append(up_block)
+            prev_output_channel = output_channel
 
+        # out
         self.out = nn.Sequential(
-            nn.GroupNorm(num_groups=norm_num_groups, num_channels=ch, eps=norm_eps, affine=True),
+            nn.GroupNorm(num_groups=norm_num_groups, num_channels=block_out_channels[0], eps=norm_eps, affine=True),
             nn.SiLU(),
             zero_module(
                 Convolution(
                     spatial_dims=spatial_dims,
-                    in_channels=model_channels,
+                    in_channels=block_out_channels[0],
                     out_channels=out_channels,
                     strides=1,
                     kernel_size=3,
@@ -929,17 +926,30 @@ def forward(
             timesteps: timestep tensor (N,)
             context: context tensor (N, 1, ContextDim)
         """
-        hs = []
-        t_emb = timestep_embedding(timesteps, self.model_channels)
+        # 1. time
+        t_emb = get_timestep_embedding(timesteps, self.block_out_channels[0])
         emb = self.time_embed(t_emb)
 
-        h = x
-        for module in self.input_blocks:
-            h = module(h, emb, context)
-            hs.append(h)
-        h = self.middle_block(h, emb, context)
-        for module in self.output_blocks:
-            h = torch.cat([h, hs.pop()], dim=1)
-            h = module(h, emb, context)
+        # 2. initial convolution
+        h = self.conv_in(x)
+
+        # 3. down
+        down_block_res_samples = (h,)
+        for downsample_block in self.down_blocks:
+            h, res_samples = downsample_block(hidden_states=h, temb=emb)
+            down_block_res_samples += res_samples
+
+        # 4. mid
+        h = self.middle_block(h, emb)
+
+        # 5. up
+        for upsample_block in self.up_blocks:
+            res_samples = down_block_res_samples[-len(upsample_block.resnets) :]
+            down_block_res_samples = down_block_res_samples[: -len(upsample_block.resnets)]
+
+            h = upsample_block(h, res_samples, emb)
+
+        # 6. output block
+        h = self.out(h)
 
-        return self.out(h)
+        return h

From fd6b953ec529edf14decdcd2b62c0152789d3bfd Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Tue, 8 Nov 2022 17:58:17 +0000
Subject: [PATCH 02/28] [WIP] Reformating Unet (#53)

---
 .../networks/nets/diffusion_model_unet.py     | 337 +++++++++++++-----
 generative/utils/__init__.py                  |  12 -
 generative/utils/misc.py                      |  30 --
 tests/test_diffusion_model_unet.py            | 173 +++++----
 4 files changed, 335 insertions(+), 217 deletions(-)
 delete mode 100644 generative/utils/__init__.py
 delete mode 100644 generative/utils/misc.py

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index 9003a9bf..95d00de4 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -19,8 +19,6 @@
 from monai.networks.layers.factories import Pool
 from torch import einsum, nn
 
-from generative.utils.misc import default
-
 __all__ = ["DiffusionModelUNet"]
 
 
@@ -59,8 +57,7 @@ def __init__(
     ) -> None:
         super().__init__()
         inner_dim = int(dim * mult)
-        # TODO: Try to remove default usage
-        dim_out = default(dim_out, dim)
+        dim_out = dim_out if dim_out is not None else dim
         project_in = nn.Sequential(nn.Linear(dim, inner_dim), nn.GELU()) if not glu else GEGLU(dim, inner_dim)
 
         self.net = nn.Sequential(project_in, nn.Dropout(dropout), nn.Linear(inner_dim, dim_out))
@@ -91,8 +88,7 @@ def __init__(
     ) -> None:
         super().__init__()
         inner_dim = dim_head * heads
-        # TODO: Try to remove default usage
-        context_dim = default(context_dim, query_dim)
+        context_dim = context_dim if context_dim is not None else query_dim
 
         self.scale = dim_head**-0.5
         self.heads = heads
@@ -107,8 +103,7 @@ def forward(self, x: torch.Tensor, context: Optional[torch.Tensor] = None) -> to
         h = self.heads
 
         q = self.to_q(x)
-        # TODO: Try to remove default usage
-        context = default(context, x)
+        context = context if context is not None else x
         k = self.to_k(context)
         v = self.to_v(context)
 
@@ -573,7 +568,7 @@ def forward(self, x: torch.Tensor, emb: torch.Tensor) -> torch.Tensor:
 
 
 def get_attention_parameters(
-    ch: int, num_head_channels: int, num_heads: int, legacy: bool, use_spatial_transformer: bool
+    ch: int, num_head_channels: int, num_heads: int, legacy: bool, with_conditioning: bool
 ) -> Tuple[int, int]:
     """
     Get the number of attention heads and their dimensions depending on the model parameters.
@@ -583,7 +578,7 @@ def get_attention_parameters(
         num_head_channels: number of channels in each head.
         num_heads: number of attention heads.
         legacy: if True, use legacy way to compute dim_head for attention blocks.
-        use_spatial_transformer: if true together with legacy, use ch // num_heads as head dimension.
+        with_conditioning: if true together with legacy, use ch // num_heads as head dimension.
 
     """
     if num_head_channels == -1:
@@ -592,7 +587,7 @@ def get_attention_parameters(
         num_heads = ch // num_head_channels
         dim_head = num_head_channels
     if legacy:
-        dim_head = ch // num_heads if use_spatial_transformer else num_head_channels
+        dim_head = ch // num_heads if with_conditioning else num_head_channels
     return dim_head, num_heads
 
 
@@ -604,13 +599,21 @@ def __init__(
         out_channels: int,
         temb_channels: int,
         num_res_blocks: int = 1,
-        norm_eps: float = 1e-6,
         norm_num_groups: int = 32,
-        add_downsample=True,
-        downsample_padding=1,
+        norm_eps: float = 1e-6,
+        add_downsample: bool = True,
+        downsample_padding: int = 1,
+        with_attn: bool = False,
+        with_cross_attn: bool = False,
+        num_heads: int = 1,
+        num_head_channels: int = 1,
+        transformer_num_layers: int = 1,
+        cross_attention_dim: Optional[int] = None,
     ):
         super().__init__()
         resnets = []
+        attentions = []
+        cross_attentions = []
 
         for i in range(num_res_blocks):
             in_channels = in_channels if i == 0 else out_channels
@@ -624,8 +627,33 @@ def __init__(
                     norm_eps=norm_eps,
                 )
             )
+            if with_attn:
+                attentions.append(
+                    AttentionBlock(
+                        channels=out_channels,
+                        num_heads=num_heads,
+                        num_head_channels=num_head_channels,
+                        norm_num_groups=norm_num_groups,
+                        norm_eps=norm_eps,
+                    )
+                )
+            if with_cross_attn:
+                cross_attentions.append(
+                    SpatialTransformer(
+                        spatial_dims=spatial_dims,
+                        in_channels=out_channels,
+                        n_heads=num_heads,
+                        d_head=num_head_channels,
+                        depth=transformer_num_layers,
+                        norm_num_groups=norm_num_groups,
+                        norm_eps=norm_eps,
+                        context_dim=cross_attention_dim,
+                    )
+                )
 
         self.resnets = nn.ModuleList(resnets)
+        self.attentions = nn.ModuleList(attentions)
+        self.cross_attentions = nn.ModuleList(cross_attentions)
 
         if add_downsample:
             self.downsampler = Downsample(
@@ -638,11 +666,18 @@ def __init__(
         else:
             self.downsampler = None
 
-    def forward(self, hidden_states: torch.Tensor, temb: torch.Tensor) -> Tuple[torch.Tensor, Tuple]:
+    def forward(self, hidden_states: torch.Tensor, temb: torch.Tensor, context=None) -> Tuple[torch.Tensor, Tuple]:
         output_states = ()
 
-        for resnet in self.resnets:
-            hidden_states = resnet(hidden_states, temb)
+        for i in range(len(self.resnets)):
+            hidden_states = self.resnets[i](hidden_states, temb)
+
+            if len(self.attentions) != 0:
+                hidden_states = self.attentions[i](hidden_states)
+
+            if len(self.cross_attentions) != 0:
+                hidden_states = self.cross_attentions[i](hidden_states, context=context)
+
             output_states += (hidden_states,)
 
         if self.downsampler is not None:
@@ -660,10 +695,15 @@ def __init__(
         temb_channels: int,
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
-        num_heads=1,
-        num_head_channels=1,
+        with_cross_attn: bool = False,
+        num_heads: int = 1,
+        num_head_channels: int = 1,
+        transformer_num_layers: int = 1,
+        cross_attention_dim: Optional[int] = None,
     ):
         super().__init__()
+        attentions = []
+        cross_attentions = []
 
         self.resnet_1 = ResnetBlock(
             spatial_dims=spatial_dims,
@@ -673,14 +713,31 @@ def __init__(
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
         )
+        if with_cross_attn:
+            cross_attentions.append(
+                SpatialTransformer(
+                    spatial_dims=spatial_dims,
+                    in_channels=in_channels,
+                    n_heads=num_heads,
+                    d_head=num_head_channels,
+                    depth=transformer_num_layers,
+                    norm_num_groups=norm_num_groups,
+                    norm_eps=norm_eps,
+                    context_dim=cross_attention_dim,
+                )
+            )
+
+        else:
+            attentions.append(
+                AttentionBlock(
+                    channels=in_channels,
+                    num_heads=num_heads,
+                    num_head_channels=num_head_channels,
+                    norm_num_groups=norm_num_groups,
+                    norm_eps=norm_eps,
+                )
+            )
 
-        self.attention = AttentionBlock(
-            channels=in_channels,
-            num_heads=num_heads,
-            num_head_channels=num_head_channels,
-            norm_num_groups=norm_num_groups,
-            norm_eps=norm_eps,
-        )
         self.resnet_2 = ResnetBlock(
             spatial_dims=spatial_dims,
             in_channels=in_channels,
@@ -690,9 +747,18 @@ def __init__(
             norm_eps=norm_eps,
         )
 
-    def forward(self, hidden_states, temb=None):
+        self.attentions = nn.ModuleList(attentions)
+        self.cross_attentions = nn.ModuleList(cross_attentions)
+
+    def forward(self, hidden_states, temb=None, context=None):
         hidden_states = self.resnet_1(hidden_states, temb)
-        hidden_states = self.attention(hidden_states)
+
+        if len(self.attentions) != 0:
+            hidden_states = self.attentions(hidden_states)
+
+        if len(self.cross_attentions) != 0:
+            hidden_states = self.cross_attentions(hidden_states, context=context)
+
         hidden_states = self.resnet_2(hidden_states, temb)
 
         return hidden_states
@@ -707,12 +773,20 @@ def __init__(
         out_channels: int,
         temb_channels: int,
         num_res_blocks: int = 1,
-        norm_eps: float = 1e-6,
         norm_num_groups: int = 32,
-        add_upsample=True,
+        norm_eps: float = 1e-6,
+        add_upsample: bool = True,
+        with_attn: bool = False,
+        with_cross_attn: bool = False,
+        num_heads: int = 1,
+        num_head_channels: int = 1,
+        transformer_num_layers: int = 1,
+        cross_attention_dim: Optional[int] = None,
     ):
         super().__init__()
         resnets = []
+        attentions = []
+        cross_attentions = []
 
         for i in range(num_res_blocks):
             res_skip_channels = in_channels if (i == num_res_blocks - 1) else out_channels
@@ -728,8 +802,33 @@ def __init__(
                     norm_eps=norm_eps,
                 )
             )
+            if with_attn:
+                attentions.append(
+                    AttentionBlock(
+                        channels=out_channels,
+                        num_heads=num_heads,
+                        num_head_channels=num_head_channels,
+                        norm_num_groups=norm_num_groups,
+                        norm_eps=norm_eps,
+                    )
+                )
+            if with_cross_attn:
+                cross_attentions.append(
+                    SpatialTransformer(
+                        spatial_dims=spatial_dims,
+                        in_channels=out_channels,
+                        n_heads=num_heads,
+                        d_head=num_head_channels,
+                        norm_num_groups=norm_num_groups,
+                        norm_eps=norm_eps,
+                        depth=transformer_num_layers,
+                        context_dim=cross_attention_dim,
+                    )
+                )
 
         self.resnets = nn.ModuleList(resnets)
+        self.attentions = nn.ModuleList(attentions)
+        self.cross_attentions = nn.ModuleList(cross_attentions)
 
         if add_upsample:
             self.upsampler = Upsample(
@@ -738,14 +837,20 @@ def __init__(
         else:
             self.upsampler = None
 
-    def forward(self, hidden_states, res_hidden_states_tuple, temb=None):
-        for resnet in self.resnets:
+    def forward(self, hidden_states, res_hidden_states_tuple, temb=None, context=None):
+        for i in range(len(self.resnets)):
             # pop res hidden states
             res_hidden_states = res_hidden_states_tuple[-1]
             res_hidden_states_tuple = res_hidden_states_tuple[:-1]
             hidden_states = torch.cat([hidden_states, res_hidden_states], dim=1)
 
-            hidden_states = resnet(hidden_states, temb)
+            hidden_states = self.resnets[i](hidden_states, temb)
+
+            if len(self.attentions) != 0:
+                hidden_states = self.attentions[i](hidden_states)
+
+            if len(self.cross_attentions) != 0:
+                hidden_states = self.cross_attentions[i](hidden_states, context=context)
 
         if self.upsampler is not None:
             hidden_states = self.upsampler(hidden_states)
@@ -762,18 +867,18 @@ class DiffusionModelUNet(nn.Module):
     Args:
         spatial_dims: number of spatial dimensions.
         in_channels: number of input channels.
-        model_channels:
         out_channels: number of output channels.
         num_res_blocks: number of residual blocks (see ResBlock) per level.
-        attention_resolutions: list of levels to add attention.
-        num_heads: number of attention heads.
-        num_head_channels: number of channels in each head.
+        block_out_channels:
+        attention_levels: list of levels to add attention.
         norm_num_groups: number of groups for the normalization.
         norm_eps: epsilon for the normalization.
-        use_spatial_transformer: if True add spatial transformers to perform conditioning.
-        transformer_depth: number of layers of Transformer blocks to use.
-        context_dim: number of context dimensions to use.
+        num_heads: number of attention heads.
+        num_head_channels: number of channels in each head.
         legacy: if True, use legacy way to compute dim_head for attention blocks.
+        with_conditioning: if True add spatial transformers to perform conditioning.
+        transformer_num_layers: number of layers of Transformer blocks to use.
+        context_dim: number of context dimensions to use.
     """
 
     def __init__(
@@ -782,40 +887,40 @@ def __init__(
         in_channels: int,
         out_channels: int,
         num_res_blocks: int,
-        attention_resolutions: Sequence[int] = (False, False, True, True),
         block_out_channels: Sequence[int] = (32, 64, 64, 64),
-        num_heads: int = -1,
-        num_head_channels: int = -1,
+        attention_levels: Sequence[bool] = (False, False, True, True),
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
-        use_spatial_transformer: bool = False,
-        transformer_depth: int = 1,
-        context_dim: Optional[int] = None,
+        num_heads: int = -1,
+        num_head_channels: int = -1,
         legacy: bool = True,
+        with_conditioning: bool = False,
+        transformer_num_layers: int = 1,
+        context_dim: Optional[int] = None,
     ) -> None:
         super().__init__()
-        if use_spatial_transformer is True and context_dim is None:
+        if with_conditioning is True and context_dim is None:
             raise ValueError(
                 (
                     "DiffusionModelUNet expects dimension of the cross-attention conditioning (context_dim) when using "
-                    "use_spatial_transformer."
+                    "with_conditioning."
                 )
             )
-        if context_dim is not None and use_spatial_transformer is False:
+        if context_dim is not None and with_conditioning is False:
             raise ValueError("DiffusionModelUNet expects use_spatial_transformer=True when specifying the context_dim.")
 
         if num_heads == -1 and num_head_channels == -1:
             raise ValueError("DiffusionModelUNet expects that either num_heads or num_head_channels has to be set.")
 
         # The number of channels should be multiple of num_groups
-        # if (model_channels % norm_num_groups) != 0:
-        #     raise ValueError("DiffusionModelUNet expects model_channels being multiple of norm_num_groups")
+        if any((out_channel % norm_num_groups) != 0 for out_channel in block_out_channels):
+            raise ValueError("DiffusionModelUNet expects all block_out_channels being multiple of norm_num_groups")
 
         self.in_channels = in_channels
         self.block_out_channels = block_out_channels
         self.out_channels = out_channels
         self.num_res_blocks = num_res_blocks
-        self.attention_resolutions = attention_resolutions
+        self.attention_levels = attention_levels
         self.num_heads = num_heads
         self.num_head_channels = num_head_channels
 
@@ -846,35 +951,72 @@ def __init__(
             output_channel = block_out_channels[i]
             is_final_block = i == len(block_out_channels) - 1
 
-            down_block = DownBlock(
-                spatial_dims=spatial_dims,
-                in_channels=input_channel,
-                out_channels=output_channel,
-                temb_channels=time_embed_dim,
-                num_res_blocks=num_res_blocks,
-                norm_num_groups=norm_num_groups,
-                norm_eps=norm_eps,
-                add_downsample=not is_final_block,
-            )
+            if attention_levels[i]:
+                dim_head, num_heads = get_attention_parameters(
+                    input_channel, num_head_channels, num_heads, legacy, with_conditioning
+                )
+
+                down_block = DownBlock(
+                    spatial_dims=spatial_dims,
+                    in_channels=input_channel,
+                    out_channels=output_channel,
+                    temb_channels=time_embed_dim,
+                    num_res_blocks=num_res_blocks,
+                    norm_num_groups=norm_num_groups,
+                    norm_eps=norm_eps,
+                    add_downsample=not is_final_block,
+                    with_attn=not with_conditioning,
+                    with_cross_attn=with_conditioning,
+                    num_heads=num_heads,
+                    num_head_channels=dim_head,
+                    transformer_num_layers=transformer_num_layers,
+                    cross_attention_dim=context_dim,
+                )
+            else:
+                down_block = DownBlock(
+                    spatial_dims=spatial_dims,
+                    in_channels=input_channel,
+                    out_channels=output_channel,
+                    temb_channels=time_embed_dim,
+                    num_res_blocks=num_res_blocks,
+                    norm_num_groups=norm_num_groups,
+                    norm_eps=norm_eps,
+                    add_downsample=not is_final_block,
+                )
             self.down_blocks.append(down_block)
 
         # mid
         dim_head, num_heads = get_attention_parameters(
-            block_out_channels[-1], num_head_channels, num_heads, legacy, use_spatial_transformer
-        )
-        self.middle_block = MidBlock(
-            spatial_dims=spatial_dims,
-            in_channels=block_out_channels[-1],
-            temb_channels=time_embed_dim,
-            norm_num_groups=norm_num_groups,
-            norm_eps=norm_eps,
-            num_heads=num_heads,
-            num_head_channels=dim_head,
+            block_out_channels[-1], num_head_channels, num_heads, legacy, with_conditioning
         )
+        if with_conditioning:
+            self.middle_block = MidBlock(
+                spatial_dims=spatial_dims,
+                in_channels=block_out_channels[-1],
+                temb_channels=time_embed_dim,
+                norm_num_groups=norm_num_groups,
+                norm_eps=norm_eps,
+                with_cross_attn=True,
+                num_heads=num_heads,
+                num_head_channels=dim_head,
+                transformer_num_layers=transformer_num_layers,
+                cross_attention_dim=context_dim,
+            )
+        else:
+            self.middle_block = MidBlock(
+                spatial_dims=spatial_dims,
+                in_channels=block_out_channels[-1],
+                temb_channels=time_embed_dim,
+                norm_num_groups=norm_num_groups,
+                norm_eps=norm_eps,
+                num_heads=num_heads,
+                num_head_channels=dim_head,
+            )
 
         # up
         self.up_blocks = nn.ModuleList([])
         reversed_block_out_channels = list(reversed(block_out_channels))
+        reversed_attention_levels = list(reversed(attention_levels))
         output_channel = reversed_block_out_channels[0]
         for i in range(len(reversed_block_out_channels)):
             prev_output_channel = output_channel
@@ -883,17 +1025,40 @@ def __init__(
 
             is_final_block = i == len(block_out_channels) - 1
 
-            up_block = UpBlock(
-                spatial_dims=spatial_dims,
-                in_channels=input_channel,
-                prev_output_channel=prev_output_channel,
-                out_channels=output_channel,
-                temb_channels=time_embed_dim,
-                num_res_blocks=num_res_blocks + 1,
-                norm_num_groups=norm_num_groups,
-                norm_eps=norm_eps,
-                add_upsample=not is_final_block,
-            )
+            if reversed_attention_levels[i]:
+                dim_head, num_heads = get_attention_parameters(
+                    output_channel, num_head_channels, num_heads, legacy, with_conditioning
+                )
+
+                up_block = UpBlock(
+                    spatial_dims=spatial_dims,
+                    in_channels=input_channel,
+                    prev_output_channel=prev_output_channel,
+                    out_channels=output_channel,
+                    temb_channels=time_embed_dim,
+                    num_res_blocks=num_res_blocks + 1,
+                    norm_num_groups=norm_num_groups,
+                    norm_eps=norm_eps,
+                    add_upsample=not is_final_block,
+                    with_attn=not with_conditioning,
+                    with_cross_attn=with_conditioning,
+                    num_heads=num_heads,
+                    num_head_channels=dim_head,
+                    transformer_num_layers=transformer_num_layers,
+                    cross_attention_dim=context_dim,
+                )
+            else:
+                up_block = UpBlock(
+                    spatial_dims=spatial_dims,
+                    in_channels=input_channel,
+                    prev_output_channel=prev_output_channel,
+                    out_channels=output_channel,
+                    temb_channels=time_embed_dim,
+                    num_res_blocks=num_res_blocks + 1,
+                    norm_num_groups=norm_num_groups,
+                    norm_eps=norm_eps,
+                    add_upsample=not is_final_block,
+                )
             self.up_blocks.append(up_block)
             prev_output_channel = output_channel
 
@@ -936,18 +1101,18 @@ def forward(
         # 3. down
         down_block_res_samples = (h,)
         for downsample_block in self.down_blocks:
-            h, res_samples = downsample_block(hidden_states=h, temb=emb)
+            h, res_samples = downsample_block(hidden_states=h, temb=emb, context=context)
             down_block_res_samples += res_samples
 
         # 4. mid
-        h = self.middle_block(h, emb)
+        h = self.middle_block(hidden_states=h, temb=emb, context=context)
 
         # 5. up
         for upsample_block in self.up_blocks:
             res_samples = down_block_res_samples[-len(upsample_block.resnets) :]
             down_block_res_samples = down_block_res_samples[: -len(upsample_block.resnets)]
 
-            h = upsample_block(h, res_samples, emb)
+            h = upsample_block(hidden_states=h, res_hidden_states_tuple=res_samples, temb=emb, context=context)
 
         # 6. output block
         h = self.out(h)
diff --git a/generative/utils/__init__.py b/generative/utils/__init__.py
deleted file mode 100644
index cd51d099..00000000
--- a/generative/utils/__init__.py
+++ /dev/null
@@ -1,12 +0,0 @@
-# Copyright (c) MONAI Consortium
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#     http://www.apache.org/licenses/LICENSE-2.0
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from .misc import default, exists, extract
diff --git a/generative/utils/misc.py b/generative/utils/misc.py
deleted file mode 100644
index bef9b5e4..00000000
--- a/generative/utils/misc.py
+++ /dev/null
@@ -1,30 +0,0 @@
-# Copyright (c) MONAI Consortium
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#     http://www.apache.org/licenses/LICENSE-2.0
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-from inspect import isfunction
-
-__all__ = ["exists", "default", "extract"]
-
-
-def exists(x):
-    return x is not None
-
-
-def default(val, d):
-    if exists(val):
-        return val
-    return d() if isfunction(d) else d
-
-
-def extract(a, t, x_shape):
-    b, *_ = t.shape
-    out = a.gather(-1, t)
-    return out.reshape(b, *((1,) * (len(x_shape) - 1)))
diff --git a/tests/test_diffusion_model_unet.py b/tests/test_diffusion_model_unet.py
index daa0894a..69151adb 100644
--- a/tests/test_diffusion_model_unet.py
+++ b/tests/test_diffusion_model_unet.py
@@ -25,39 +25,39 @@
         {
             "spatial_dims": 2,
             "in_channels": 1,
-            "model_channels": 32,
             "out_channels": 1,
             "num_res_blocks": 1,
-            "attention_resolutions": [16, 8],
-            "channel_mult": [1, 1, 1, 1],
+            "block_out_channels": (16, 16, 16),
+            "attention_levels": (False, False, True),
             "num_heads": 1,
+            "norm_num_groups": 16,
         },
     ],
     [
         {
             "spatial_dims": 2,
             "in_channels": 1,
-            "model_channels": 32,
             "out_channels": 1,
             "num_res_blocks": 1,
-            "attention_resolutions": [16, 8],
-            "channel_mult": [1, 1, 1, 1],
+            "block_out_channels": (16, 16, 16),
+            "attention_levels": (False, False, True),
             "num_heads": -1,
             "num_head_channels": 1,
+            "norm_num_groups": 16,
         },
     ],
     [
         {
             "spatial_dims": 2,
             "in_channels": 1,
-            "model_channels": 32,
             "out_channels": 1,
             "num_res_blocks": 1,
-            "attention_resolutions": [16, 8],
-            "channel_mult": [1, 1, 1, 1],
+            "block_out_channels": (16, 16, 16),
+            "attention_levels": (False, False, True),
             "num_heads": 4,
             "num_head_channels": 2,
             "legacy": False,
+            "norm_num_groups": 16,
         },
     ],
 ]
@@ -67,42 +67,39 @@
         {
             "spatial_dims": 3,
             "in_channels": 1,
-            "model_channels": 16,
             "out_channels": 1,
             "num_res_blocks": 1,
-            "attention_resolutions": [16, 8],
-            "channel_mult": [1, 1, 1, 1],
+            "block_out_channels": (8, 8, 8),
+            "attention_levels": (False, False, True),
             "num_heads": 1,
-            "norm_num_groups": 16,
+            "norm_num_groups": 4,
         },
     ],
     [
         {
             "spatial_dims": 3,
             "in_channels": 1,
-            "model_channels": 16,
             "out_channels": 1,
             "num_res_blocks": 1,
-            "attention_resolutions": [16, 8],
-            "channel_mult": [1, 1, 1, 1],
+            "block_out_channels": (8, 8, 8),
+            "attention_levels": (False, False, True),
             "num_heads": -1,
             "num_head_channels": 1,
-            "norm_num_groups": 16,
+            "norm_num_groups": 4,
         },
     ],
     [
         {
             "spatial_dims": 3,
             "in_channels": 1,
-            "model_channels": 16,
             "out_channels": 1,
             "num_res_blocks": 1,
-            "attention_resolutions": [16, 8],
-            "channel_mult": [1, 1, 1, 1],
+            "block_out_channels": (8, 8, 8),
+            "attention_levels": (False, False, True),
             "num_heads": 1,
             "num_head_channels": 1,
             "legacy": False,
-            "norm_num_groups": 16,
+            "norm_num_groups": 4,
         },
     ],
 ]
@@ -113,8 +110,8 @@ class TestDiffusionModelUNet2D(unittest.TestCase):
     def test_shape_unconditioned_models(self, input_param):
         net = DiffusionModelUNet(**input_param)
         with eval_mode(net):
-            result = net.forward(torch.rand((1, 1, 32, 64)), torch.randint(0, 1000, (1,)).long())
-            self.assertEqual(result.shape, (1, 1, 32, 64))
+            result = net.forward(torch.rand((1, 1, 16, 16)), torch.randint(0, 1000, (1,)).long())
+            self.assertEqual(result.shape, (1, 1, 16, 16))
 
     def test_shape_with_different_in_channel_out_channel(self):
         in_channels = 6
@@ -122,29 +119,29 @@ def test_shape_with_different_in_channel_out_channel(self):
         net = DiffusionModelUNet(
             spatial_dims=2,
             in_channels=in_channels,
-            model_channels=32,
             out_channels=out_channels,
             num_res_blocks=1,
-            attention_resolutions=[16, 8],
-            channel_mult=[1, 1, 1, 1],
+            block_out_channels=(16, 16, 16),
+            attention_levels=(False, False, True),
             num_heads=1,
+            norm_num_groups=16,
         )
         with eval_mode(net):
-            result = net.forward(torch.rand((1, in_channels, 64, 64)), torch.randint(0, 1000, (1,)).long())
-            self.assertEqual(result.shape, (1, out_channels, 64, 64))
+            result = net.forward(torch.rand((1, in_channels, 16, 16)), torch.randint(0, 1000, (1,)).long())
+            self.assertEqual(result.shape, (1, out_channels, 16, 16))
 
     def test_attention_heads_not_declared(self):
         with self.assertRaises(ValueError):
             DiffusionModelUNet(
                 spatial_dims=2,
                 in_channels=3,
-                model_channels=32,
                 out_channels=3,
                 num_res_blocks=1,
-                attention_resolutions=[16, 8],
-                channel_mult=[1, 1, 1, 1],
+                block_out_channels=(16, 16, 16),
+                attention_levels=(False, False, True),
                 num_heads=-1,
                 num_head_channels=-1,
+                norm_num_groups=16,
             )
 
     def test_model_channels_not_multiple_of_norm_num_group(self):
@@ -152,11 +149,10 @@ def test_model_channels_not_multiple_of_norm_num_group(self):
             DiffusionModelUNet(
                 spatial_dims=2,
                 in_channels=3,
-                model_channels=40,
                 out_channels=3,
                 num_res_blocks=1,
-                attention_resolutions=[16, 8],
-                channel_mult=[1, 1, 1, 1],
+                block_out_channels=(8, 8, 40),
+                attention_levels=(False, False, True),
                 norm_num_groups=32,
             )
 
@@ -164,23 +160,23 @@ def test_shape_conditioned_models(self):
         net = DiffusionModelUNet(
             spatial_dims=2,
             in_channels=1,
-            model_channels=32,
             out_channels=1,
             num_res_blocks=1,
-            attention_resolutions=[16, 8],
-            channel_mult=[1, 1, 1, 1],
+            block_out_channels=(16, 16, 16),
+            attention_levels=(False, False, True),
             num_heads=1,
-            use_spatial_transformer=True,
-            transformer_depth=1,
+            with_conditioning=True,
+            transformer_num_layers=1,
             context_dim=3,
+            norm_num_groups=16,
         )
         with eval_mode(net):
             result = net.forward(
-                x=torch.rand((1, 1, 32, 64)),
+                x=torch.rand((1, 1, 16, 32)),
                 timesteps=torch.randint(0, 1000, (1,)).long(),
                 context=torch.rand((1, 1, 3)),
             )
-            self.assertEqual(result.shape, (1, 1, 32, 64))
+            self.assertEqual(result.shape, (1, 1, 16, 32))
 
     # TODO: Fix problem with torchscript
     # def test_script_unconditioned_models(self):
@@ -213,54 +209,53 @@ def test_shape_conditioned_models(self):
     #     )
 
 
-class TestDiffusionModelUNet3D(unittest.TestCase):
-    @parameterized.expand(UNCOND_CASES_3D)
-    def test_shape_unconditioned_models(self, input_param):
-        net = DiffusionModelUNet(**input_param)
-        with eval_mode(net):
-            result = net.forward(torch.rand((1, 1, 16, 32, 48)), torch.randint(0, 1000, (1,)).long())
-            self.assertEqual(result.shape, (1, 1, 16, 32, 48))
-
-    def test_shape_with_different_in_channel_out_channel(self):
-        in_channels = 6
-        out_channels = 3
-        net = DiffusionModelUNet(
-            spatial_dims=3,
-            in_channels=in_channels,
-            model_channels=16,
-            out_channels=out_channels,
-            num_res_blocks=1,
-            attention_resolutions=[16, 8],
-            channel_mult=[1, 1, 1, 1],
-            num_heads=1,
-            norm_num_groups=16,
-        )
-        with eval_mode(net):
-            result = net.forward(torch.rand((1, in_channels, 16, 32, 48)), torch.randint(0, 1000, (1,)).long())
-            self.assertEqual(result.shape, (1, out_channels, 16, 32, 48))
-
-    def test_shape_conditioned_models(self):
-        net = DiffusionModelUNet(
-            spatial_dims=3,
-            in_channels=1,
-            model_channels=16,
-            out_channels=1,
-            num_res_blocks=1,
-            attention_resolutions=[16, 8],
-            channel_mult=[1, 1, 1, 1],
-            num_heads=1,
-            norm_num_groups=16,
-            use_spatial_transformer=True,
-            transformer_depth=1,
-            context_dim=3,
-        )
-        with eval_mode(net):
-            result = net.forward(
-                x=torch.rand((1, 1, 16, 32, 48)),
-                timesteps=torch.randint(0, 1000, (1,)).long(),
-                context=torch.rand((1, 1, 3)),
-            )
-            self.assertEqual(result.shape, (1, 1, 16, 32, 48))
+#
+# class TestDiffusionModelUNet3D(unittest.TestCase):
+#     @parameterized.expand(UNCOND_CASES_3D)
+#     def test_shape_unconditioned_models(self, input_param):
+#         net = DiffusionModelUNet(**input_param)
+#         with eval_mode(net):
+#             result = net.forward(torch.rand((1, 1, 16, 32, 48)), torch.randint(0, 1000, (1,)).long())
+#             self.assertEqual(result.shape, (1, 1, 16, 32, 48))
+#
+#     def test_shape_with_different_in_channel_out_channel(self):
+#         in_channels = 6
+#         out_channels = 3
+#         net = DiffusionModelUNet(
+#             spatial_dims=3,
+#             in_channels=in_channels,
+#             out_channels=out_channels,
+#             num_res_blocks=1,
+#             block_out_channels=(16, 16, 16, 16),
+#             attention_levels=(False, False, True, True),
+#             num_heads=1,
+#             norm_num_groups=16,
+#         )
+#         with eval_mode(net):
+#             result = net.forward(torch.rand((1, in_channels, 16, 32, 48)), torch.randint(0, 1000, (1,)).long())
+#             self.assertEqual(result.shape, (1, out_channels, 16, 32, 48))
+#
+#     def test_shape_conditioned_models(self):
+#         net = DiffusionModelUNet(
+#             spatial_dims=3,
+#             in_channels=1,
+#             out_channels=1,
+#             num_res_blocks=1,
+#             block_out_channels=(16, 16, 16, 16),
+#             attention_levels=(False, False, True, True),
+#             num_heads=1,
+#             norm_num_groups=16,
+#             with_conditioning=True,
+#             transformer_num_layers=1,
+#             context_dim=3,
+#         )
+#         with eval_mode(net):
+#             result = net.forward(
+#                 x=torch.rand((1, 1, 16, 32, 48)),
+#                 timesteps=torch.randint(0, 1000, (1,)).long(),
+#                 context=torch.rand((1, 1, 3)),
+#             )
+#             self.assertEqual(result.shape, (1, 1, 16, 32, 48))
 
 
 if __name__ == "__main__":

From 80a6bc755658a2f27da395aeab16cd4c9e757ba0 Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Tue, 8 Nov 2022 23:50:26 +0000
Subject: [PATCH 03/28] [WIP] Reformating Unet (#53)

---
 .../networks/nets/diffusion_model_unet.py     | 902 +++++++++++++-----
 tests/test_diffusion_model_unet.py            | 124 ++-
 2 files changed, 706 insertions(+), 320 deletions(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index 95d00de4..8d1ce53a 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -9,6 +9,26 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+# =========================================================================
+# Adapted from https://github.com/huggingface/diffusers
+# which has the following license:
+# https://github.com/huggingface/diffusers/blob/main/LICENSE
+
+# Copyright 2022 UC Berkeley Team and The HuggingFace Team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# =========================================================================
+
 import math
 from typing import Optional, Sequence, Tuple
 
@@ -330,7 +350,7 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
         return (x + h).reshape(b, c, *spatial)
 
 
-def get_timestep_embedding(timesteps: int, embedding_dim: int, max_period: int = 10000) -> torch.Tensor:
+def get_timestep_embedding(timesteps: torch.Tensor, embedding_dim: int, max_period: int = 10000) -> torch.Tensor:
     """
     This matches the implementation in Denoising Diffusion Probabilistic Models: Create sinusoidal timestep embeddings.
 
@@ -408,8 +428,8 @@ class Upsample(nn.Module):
         channels: number of input channels
         use_conv: if True uses Convolution instead of Pool average to perform downsampling.
         out_channels: number of output channels.
-        padding: controls the amount of implicit zero-paddings on both sides for padding number of points
-            for each dimension.
+        padding: controls the amount of implicit zero-paddings on both sides for padding number of points for each
+            dimension.
     """
 
     def __init__(
@@ -437,7 +457,7 @@ def __init__(
 
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         assert x.shape[1] == self.channels
-        x = F.interpolate(x, scale_factor=2, mode="nearest")
+        x = F.interpolate(x, scale_factor=2.0, mode="nearest")
         if self.use_conv:
             x = self.conv(x)
         return x
@@ -452,7 +472,6 @@ class ResnetBlock(nn.Module):
         in_channels: number of input channels
         temb_channels: number of timestep embedding  channels
         out_channels: number of output channels.
-        use_conv: if True uses Convolution instead of Identity in skip connection.
         up: if True, performs upsampling.
         down: if True, performs downsampling.
         norm_num_groups: number of groups for the group normalization.
@@ -465,79 +484,57 @@ def __init__(
         in_channels: int,
         temb_channels: int,
         out_channels: Optional[int] = None,
-        use_conv: bool = False,
         up: bool = False,
         down: bool = False,
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
     ) -> None:
         super().__init__()
+        self.spatial_dims = spatial_dims
         self.channels = in_channels
         self.emb_channels = temb_channels
         self.out_channels = out_channels or in_channels
-        self.use_conv = use_conv
+        self.up = up
+        self.down = down
 
-        self.in_layers = nn.Sequential(
-            nn.GroupNorm(num_groups=norm_num_groups, num_channels=in_channels, eps=norm_eps, affine=True),
-            nn.SiLU(),
-            Convolution(
-                spatial_dims=spatial_dims,
-                in_channels=in_channels,
-                out_channels=self.out_channels,
-                strides=1,
-                kernel_size=3,
-                padding=1,
-                conv_only=True,
-            ),
+        self.norm1 = nn.GroupNorm(num_groups=norm_num_groups, num_channels=in_channels, eps=norm_eps, affine=True)
+        self.nonlinearity = nn.SiLU()
+        self.conv1 = Convolution(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            out_channels=self.out_channels,
+            strides=1,
+            kernel_size=3,
+            padding=1,
+            conv_only=True,
         )
 
-        self.updown = up or down
-
-        if up:
-            self.h_upd = Upsample(spatial_dims, in_channels, False)
-            self.x_upd = Upsample(spatial_dims, in_channels, False)
+        self.upsample = self.downsample = None
+        if self.up:
+            self.upsample = Upsample(spatial_dims, in_channels, use_conv=False)
         elif down:
-            self.h_upd = Downsample(spatial_dims, in_channels, False)
-            self.x_upd = Downsample(spatial_dims, in_channels, False)
-        else:
-            self.h_upd = self.x_upd = nn.Identity()
+            self.downsample = Downsample(spatial_dims, in_channels, use_conv=False)
 
-        self.emb_layers = nn.Sequential(
-            nn.SiLU(),
-            nn.Linear(
-                temb_channels,
-                self.out_channels,
-            ),
-        )
-        self.out_layers = nn.Sequential(
-            nn.GroupNorm(num_groups=norm_num_groups, num_channels=self.out_channels, eps=norm_eps, affine=True),
-            nn.SiLU(),
-            zero_module(
-                Convolution(
-                    spatial_dims=spatial_dims,
-                    in_channels=self.out_channels,
-                    out_channels=self.out_channels,
-                    strides=1,
-                    kernel_size=3,
-                    padding=1,
-                    conv_only=True,
-                )
-            ),
+        self.time_emb_proj = nn.Linear(
+            temb_channels,
+            self.out_channels,
         )
 
-        if self.out_channels == in_channels:
-            self.skip_connection = nn.Identity()
-        elif use_conv:
-            self.skip_connection = Convolution(
+        self.norm2 = nn.GroupNorm(num_groups=norm_num_groups, num_channels=self.out_channels, eps=norm_eps, affine=True)
+        self.conv2 = zero_module(
+            Convolution(
                 spatial_dims=spatial_dims,
-                in_channels=in_channels,
+                in_channels=self.out_channels,
                 out_channels=self.out_channels,
                 strides=1,
                 kernel_size=3,
                 padding=1,
                 conv_only=True,
             )
+        )
 
+        if self.out_channels == in_channels:
+            self.skip_connection = nn.Identity()
         else:
             self.skip_connection = Convolution(
                 spatial_dims=spatial_dims,
@@ -550,20 +547,32 @@ def __init__(
             )
 
     def forward(self, x: torch.Tensor, emb: torch.Tensor) -> torch.Tensor:
-        if self.updown:
-            in_rest, in_conv = self.in_layers[:-1], self.in_layers[-1]
-            h = in_rest(x)
-            h = self.h_upd(h)
-            x = self.x_upd(x)
-            h = in_conv(h)
-        else:
-            h = self.in_layers(x)
-        emb_out = self.emb_layers(emb).type(h.dtype)
-        while len(emb_out.shape) < len(h.shape):
-            emb_out = emb_out[..., None]
+        h = x
+        h = self.norm1(h)
+        h = self.nonlinearity(h)
+
+        if self.upsample is not None:
+            if h.shape[0] >= 64:
+                x = x.contiguous()
+                h = h.contiguous()
+            x = self.upsample(x)
+            h = self.upsample(h)
+        elif self.downsample is not None:
+            x = self.downsample(x)
+            h = self.downsample(h)
+
+        h = self.conv1(h)
+
+        if self.spatial_dims == 2:
+            temb = self.time_emb_proj(self.nonlinearity(emb))[:, :, None, None]
+        if self.spatial_dims == 3:
+            temb = self.time_emb_proj(self.nonlinearity(emb))[:, :, None, None, None]
+        h = h + temb
+
+        h = self.norm2(h)
+        h = self.nonlinearity(h)
+        h = self.conv2(h)
 
-        h = h + emb_out
-        h = self.out_layers(h)
         return self.skip_connection(x) + h
 
 
@@ -574,7 +583,7 @@ def get_attention_parameters(
     Get the number of attention heads and their dimensions depending on the model parameters.
 
     Args:
-        ch:
+        ch: number of channels.
         num_head_channels: number of channels in each head.
         num_heads: number of attention heads.
         legacy: if True, use legacy way to compute dim_head for attention blocks.
@@ -603,17 +612,70 @@ def __init__(
         norm_eps: float = 1e-6,
         add_downsample: bool = True,
         downsample_padding: int = 1,
-        with_attn: bool = False,
-        with_cross_attn: bool = False,
+    ) -> None:
+        super().__init__()
+        resnets = []
+
+        for i in range(num_res_blocks):
+            in_channels = in_channels if i == 0 else out_channels
+            resnets.append(
+                ResnetBlock(
+                    spatial_dims=spatial_dims,
+                    in_channels=in_channels,
+                    out_channels=out_channels,
+                    temb_channels=temb_channels,
+                    norm_num_groups=norm_num_groups,
+                    norm_eps=norm_eps,
+                )
+            )
+
+        self.resnets = nn.ModuleList(resnets)
+
+        if add_downsample:
+            self.downsampler = Downsample(
+                spatial_dims=spatial_dims,
+                channels=out_channels,
+                use_conv=True,
+                out_channels=out_channels,
+                padding=downsample_padding,
+            )
+        else:
+            self.downsampler = None
+
+    def forward(
+        self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
+    ) -> Tuple[torch.Tensor, Tuple[torch.Tensor, ...]]:
+        output_states = ()
+
+        for resnet in self.resnets:
+            hidden_states = resnet(hidden_states, temb)
+            output_states += (hidden_states,)
+
+        if self.downsampler is not None:
+            hidden_states = self.downsampler(hidden_states)
+            output_states += (hidden_states,)
+
+        return hidden_states, output_states
+
+
+class AttnDownBlock(nn.Module):
+    def __init__(
+        self,
+        spatial_dims: int,
+        in_channels: int,
+        out_channels: int,
+        temb_channels: int,
+        num_res_blocks: int = 1,
+        norm_num_groups: int = 32,
+        norm_eps: float = 1e-6,
+        add_downsample: bool = True,
+        downsample_padding: int = 1,
         num_heads: int = 1,
         num_head_channels: int = 1,
-        transformer_num_layers: int = 1,
-        cross_attention_dim: Optional[int] = None,
-    ):
+    ) -> None:
         super().__init__()
         resnets = []
         attentions = []
-        cross_attentions = []
 
         for i in range(num_res_blocks):
             in_channels = in_channels if i == 0 else out_channels
@@ -627,33 +689,18 @@ def __init__(
                     norm_eps=norm_eps,
                 )
             )
-            if with_attn:
-                attentions.append(
-                    AttentionBlock(
-                        channels=out_channels,
-                        num_heads=num_heads,
-                        num_head_channels=num_head_channels,
-                        norm_num_groups=norm_num_groups,
-                        norm_eps=norm_eps,
-                    )
-                )
-            if with_cross_attn:
-                cross_attentions.append(
-                    SpatialTransformer(
-                        spatial_dims=spatial_dims,
-                        in_channels=out_channels,
-                        n_heads=num_heads,
-                        d_head=num_head_channels,
-                        depth=transformer_num_layers,
-                        norm_num_groups=norm_num_groups,
-                        norm_eps=norm_eps,
-                        context_dim=cross_attention_dim,
-                    )
+            attentions.append(
+                AttentionBlock(
+                    channels=out_channels,
+                    num_heads=num_heads,
+                    num_head_channels=num_head_channels,
+                    norm_num_groups=norm_num_groups,
+                    norm_eps=norm_eps,
                 )
+            )
 
         self.resnets = nn.ModuleList(resnets)
         self.attentions = nn.ModuleList(attentions)
-        self.cross_attentions = nn.ModuleList(cross_attentions)
 
         if add_downsample:
             self.downsampler = Downsample(
@@ -666,18 +713,92 @@ def __init__(
         else:
             self.downsampler = None
 
-    def forward(self, hidden_states: torch.Tensor, temb: torch.Tensor, context=None) -> Tuple[torch.Tensor, Tuple]:
+    def forward(
+        self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
+    ) -> Tuple[torch.Tensor, Tuple[torch.Tensor, ...]]:
         output_states = ()
 
-        for i in range(len(self.resnets)):
-            hidden_states = self.resnets[i](hidden_states, temb)
+        for resnet, attn in zip(self.resnets, self.attentions):
+            hidden_states = resnet(hidden_states, temb)
+            hidden_states = attn(hidden_states)
+            output_states += (hidden_states,)
 
-            if len(self.attentions) != 0:
-                hidden_states = self.attentions[i](hidden_states)
+        if self.downsampler is not None:
+            hidden_states = self.downsampler(hidden_states)
+            output_states += (hidden_states,)
+
+        return hidden_states, output_states
+
+
+class CrossAttnDownBlock(nn.Module):
+    def __init__(
+        self,
+        spatial_dims: int,
+        in_channels: int,
+        out_channels: int,
+        temb_channels: int,
+        num_res_blocks: int = 1,
+        norm_num_groups: int = 32,
+        norm_eps: float = 1e-6,
+        add_downsample: bool = True,
+        downsample_padding: int = 1,
+        num_heads: int = 1,
+        num_head_channels: int = 1,
+        transformer_num_layers: int = 1,
+        cross_attention_dim: Optional[int] = None,
+    ) -> None:
+        super().__init__()
+        resnets = []
+        attentions = []
+
+        for i in range(num_res_blocks):
+            in_channels = in_channels if i == 0 else out_channels
+            resnets.append(
+                ResnetBlock(
+                    spatial_dims=spatial_dims,
+                    in_channels=in_channels,
+                    out_channels=out_channels,
+                    temb_channels=temb_channels,
+                    norm_num_groups=norm_num_groups,
+                    norm_eps=norm_eps,
+                )
+            )
+
+            attentions.append(
+                SpatialTransformer(
+                    spatial_dims=spatial_dims,
+                    in_channels=out_channels,
+                    n_heads=num_heads,
+                    d_head=num_head_channels,
+                    depth=transformer_num_layers,
+                    norm_num_groups=norm_num_groups,
+                    norm_eps=norm_eps,
+                    context_dim=cross_attention_dim,
+                )
+            )
+
+        self.resnets = nn.ModuleList(resnets)
+        self.attentions = nn.ModuleList(attentions)
+
+        if add_downsample:
+            self.downsampler = Downsample(
+                spatial_dims=spatial_dims,
+                channels=out_channels,
+                use_conv=True,
+                out_channels=out_channels,
+                padding=downsample_padding,
+            )
+        else:
+            self.downsampler = None
 
-            if len(self.cross_attentions) != 0:
-                hidden_states = self.cross_attentions[i](hidden_states, context=context)
+    def forward(
+        self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
+    ) -> Tuple[torch.Tensor, Tuple[torch.Tensor, ...]]:
+        output_states = ()
 
+        for resnet, attn in zip(self.resnets, self.attentions):
+            hidden_states = resnet(hidden_states, temb)
+            hidden_states = attn(hidden_states, context=context)
             output_states += (hidden_states,)
 
         if self.downsampler is not None:
@@ -687,7 +808,56 @@ def forward(self, hidden_states: torch.Tensor, temb: torch.Tensor, context=None)
         return hidden_states, output_states
 
 
-class MidBlock(nn.Module):
+class AttnMidBlock(nn.Module):
+    def __init__(
+        self,
+        spatial_dims: int,
+        in_channels: int,
+        temb_channels: int,
+        norm_num_groups: int = 32,
+        norm_eps: float = 1e-6,
+        num_heads: int = 1,
+        num_head_channels: int = 1,
+    ) -> None:
+        super().__init__()
+        self.attention = None
+
+        self.resnet_1 = ResnetBlock(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            out_channels=in_channels,
+            temb_channels=temb_channels,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+        )
+        self.attention = AttentionBlock(
+            channels=in_channels,
+            num_heads=num_heads,
+            num_head_channels=num_head_channels,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+        )
+
+        self.resnet_2 = ResnetBlock(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            out_channels=in_channels,
+            temb_channels=temb_channels,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+        )
+
+    def forward(
+        self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
+    ) -> torch.Tensor:
+        hidden_states = self.resnet_1(hidden_states, temb)
+        hidden_states = self.attention(hidden_states)
+        hidden_states = self.resnet_2(hidden_states, temb)
+
+        return hidden_states
+
+
+class CrossAttnMidBlock(nn.Module):
     def __init__(
         self,
         spatial_dims: int,
@@ -695,15 +865,13 @@ def __init__(
         temb_channels: int,
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
-        with_cross_attn: bool = False,
         num_heads: int = 1,
         num_head_channels: int = 1,
         transformer_num_layers: int = 1,
         cross_attention_dim: Optional[int] = None,
-    ):
+    ) -> None:
         super().__init__()
-        attentions = []
-        cross_attentions = []
+        self.attention = None
 
         self.resnet_1 = ResnetBlock(
             spatial_dims=spatial_dims,
@@ -713,24 +881,132 @@ def __init__(
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
         )
-        if with_cross_attn:
-            cross_attentions.append(
-                SpatialTransformer(
+        self.attention = SpatialTransformer(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            n_heads=num_heads,
+            d_head=num_head_channels,
+            depth=transformer_num_layers,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+            context_dim=cross_attention_dim,
+        )
+        self.resnet_2 = ResnetBlock(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            out_channels=in_channels,
+            temb_channels=temb_channels,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+        )
+
+    def forward(
+        self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
+    ) -> torch.Tensor:
+        hidden_states = self.resnet_1(hidden_states, temb)
+        hidden_states = self.attention(hidden_states, context=context)
+        hidden_states = self.resnet_2(hidden_states, temb)
+
+        return hidden_states
+
+
+class UpBlock(nn.Module):
+    def __init__(
+        self,
+        spatial_dims: int,
+        in_channels: int,
+        prev_output_channel: int,
+        out_channels: int,
+        temb_channels: int,
+        num_res_blocks: int = 1,
+        norm_num_groups: int = 32,
+        norm_eps: float = 1e-6,
+        add_upsample: bool = True,
+    ) -> None:
+        super().__init__()
+        resnets = []
+
+        for i in range(num_res_blocks):
+            res_skip_channels = in_channels if (i == num_res_blocks - 1) else out_channels
+            resnet_in_channels = prev_output_channel if i == 0 else out_channels
+
+            resnets.append(
+                ResnetBlock(
                     spatial_dims=spatial_dims,
-                    in_channels=in_channels,
-                    n_heads=num_heads,
-                    d_head=num_head_channels,
-                    depth=transformer_num_layers,
+                    in_channels=resnet_in_channels + res_skip_channels,
+                    out_channels=out_channels,
+                    temb_channels=temb_channels,
                     norm_num_groups=norm_num_groups,
                     norm_eps=norm_eps,
-                    context_dim=cross_attention_dim,
                 )
             )
 
+        self.resnets = nn.ModuleList(resnets)
+
+        if add_upsample:
+            self.upsampler = Upsample(
+                spatial_dims=spatial_dims, channels=out_channels, use_conv=True, out_channels=out_channels
+            )
         else:
+            self.upsampler = None
+
+    def forward(
+        self,
+        hidden_states: torch.Tensor,
+        res_hidden_states_tuple: torch.Tensor,
+        temb: torch.Tensor,
+        context: Optional[torch.Tensor] = None,
+    ) -> torch.Tensor:
+        for i, resnet in enumerate(self.resnets):
+            # pop res hidden states
+            res_hidden_states = res_hidden_states_tuple[-1]
+            res_hidden_states_tuple = res_hidden_states_tuple[:-1]
+            hidden_states = torch.cat([hidden_states, res_hidden_states], dim=1)
+
+            hidden_states = resnet(hidden_states, temb)
+
+        if self.upsampler is not None:
+            hidden_states = self.upsampler(hidden_states)
+
+        return hidden_states
+
+
+class AttnUpBlock(nn.Module):
+    def __init__(
+        self,
+        spatial_dims: int,
+        in_channels: int,
+        prev_output_channel: int,
+        out_channels: int,
+        temb_channels: int,
+        num_res_blocks: int = 1,
+        norm_num_groups: int = 32,
+        norm_eps: float = 1e-6,
+        add_upsample: bool = True,
+        num_heads: int = 1,
+        num_head_channels: int = 1,
+    ) -> None:
+        super().__init__()
+        resnets = []
+        attentions = []
+
+        for i in range(num_res_blocks):
+            res_skip_channels = in_channels if (i == num_res_blocks - 1) else out_channels
+            resnet_in_channels = prev_output_channel if i == 0 else out_channels
+
+            resnets.append(
+                ResnetBlock(
+                    spatial_dims=spatial_dims,
+                    in_channels=resnet_in_channels + res_skip_channels,
+                    out_channels=out_channels,
+                    temb_channels=temb_channels,
+                    norm_num_groups=norm_num_groups,
+                    norm_eps=norm_eps,
+                )
+            )
             attentions.append(
                 AttentionBlock(
-                    channels=in_channels,
+                    channels=out_channels,
                     num_heads=num_heads,
                     num_head_channels=num_head_channels,
                     norm_num_groups=norm_num_groups,
@@ -738,33 +1014,39 @@ def __init__(
                 )
             )
 
-        self.resnet_2 = ResnetBlock(
-            spatial_dims=spatial_dims,
-            in_channels=in_channels,
-            out_channels=in_channels,
-            temb_channels=temb_channels,
-            norm_num_groups=norm_num_groups,
-            norm_eps=norm_eps,
-        )
-
+        self.resnets = nn.ModuleList(resnets)
         self.attentions = nn.ModuleList(attentions)
-        self.cross_attentions = nn.ModuleList(cross_attentions)
 
-    def forward(self, hidden_states, temb=None, context=None):
-        hidden_states = self.resnet_1(hidden_states, temb)
+        if add_upsample:
+            self.upsampler = Upsample(
+                spatial_dims=spatial_dims, channels=out_channels, use_conv=True, out_channels=out_channels
+            )
+        else:
+            self.upsampler = None
 
-        if len(self.attentions) != 0:
-            hidden_states = self.attentions(hidden_states)
+    def forward(
+        self,
+        hidden_states: torch.Tensor,
+        res_hidden_states_tuple: torch.Tensor,
+        temb: torch.Tensor,
+        context: Optional[torch.Tensor] = None,
+    ) -> torch.Tensor:
+        for resnet, attn in zip(self.resnets, self.attentions):
+            # pop res hidden states
+            res_hidden_states = res_hidden_states_tuple[-1]
+            res_hidden_states_tuple = res_hidden_states_tuple[:-1]
+            hidden_states = torch.cat([hidden_states, res_hidden_states], dim=1)
 
-        if len(self.cross_attentions) != 0:
-            hidden_states = self.cross_attentions(hidden_states, context=context)
+            hidden_states = resnet(hidden_states, temb)
+            hidden_states = attn(hidden_states)
 
-        hidden_states = self.resnet_2(hidden_states, temb)
+        if self.upsampler is not None:
+            hidden_states = self.upsampler(hidden_states)
 
         return hidden_states
 
 
-class UpBlock(nn.Module):
+class CrossAttnUpBlock(nn.Module):
     def __init__(
         self,
         spatial_dims: int,
@@ -776,17 +1058,14 @@ def __init__(
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
         add_upsample: bool = True,
-        with_attn: bool = False,
-        with_cross_attn: bool = False,
         num_heads: int = 1,
         num_head_channels: int = 1,
         transformer_num_layers: int = 1,
         cross_attention_dim: Optional[int] = None,
-    ):
+    ) -> None:
         super().__init__()
         resnets = []
         attentions = []
-        cross_attentions = []
 
         for i in range(num_res_blocks):
             res_skip_channels = in_channels if (i == num_res_blocks - 1) else out_channels
@@ -802,33 +1081,21 @@ def __init__(
                     norm_eps=norm_eps,
                 )
             )
-            if with_attn:
-                attentions.append(
-                    AttentionBlock(
-                        channels=out_channels,
-                        num_heads=num_heads,
-                        num_head_channels=num_head_channels,
-                        norm_num_groups=norm_num_groups,
-                        norm_eps=norm_eps,
-                    )
-                )
-            if with_cross_attn:
-                cross_attentions.append(
-                    SpatialTransformer(
-                        spatial_dims=spatial_dims,
-                        in_channels=out_channels,
-                        n_heads=num_heads,
-                        d_head=num_head_channels,
-                        norm_num_groups=norm_num_groups,
-                        norm_eps=norm_eps,
-                        depth=transformer_num_layers,
-                        context_dim=cross_attention_dim,
-                    )
+            attentions.append(
+                SpatialTransformer(
+                    spatial_dims=spatial_dims,
+                    in_channels=out_channels,
+                    n_heads=num_heads,
+                    d_head=num_head_channels,
+                    norm_num_groups=norm_num_groups,
+                    norm_eps=norm_eps,
+                    depth=transformer_num_layers,
+                    context_dim=cross_attention_dim,
                 )
+            )
 
         self.resnets = nn.ModuleList(resnets)
         self.attentions = nn.ModuleList(attentions)
-        self.cross_attentions = nn.ModuleList(cross_attentions)
 
         if add_upsample:
             self.upsampler = Upsample(
@@ -837,20 +1104,21 @@ def __init__(
         else:
             self.upsampler = None
 
-    def forward(self, hidden_states, res_hidden_states_tuple, temb=None, context=None):
-        for i in range(len(self.resnets)):
+    def forward(
+        self,
+        hidden_states: torch.Tensor,
+        res_hidden_states_tuple: torch.Tensor,
+        temb: torch.Tensor,
+        context: Optional[torch.Tensor] = None,
+    ) -> torch.Tensor:
+        for resnet, attn in zip(self.resnets, self.attentions):
             # pop res hidden states
             res_hidden_states = res_hidden_states_tuple[-1]
             res_hidden_states_tuple = res_hidden_states_tuple[:-1]
             hidden_states = torch.cat([hidden_states, res_hidden_states], dim=1)
 
-            hidden_states = self.resnets[i](hidden_states, temb)
-
-            if len(self.attentions) != 0:
-                hidden_states = self.attentions[i](hidden_states)
-
-            if len(self.cross_attentions) != 0:
-                hidden_states = self.cross_attentions[i](hidden_states, context=context)
+            hidden_states = resnet(hidden_states, temb)
+            hidden_states = attn(hidden_states, context=context)
 
         if self.upsampler is not None:
             hidden_states = self.upsampler(hidden_states)
@@ -858,6 +1126,160 @@ def forward(self, hidden_states, res_hidden_states_tuple, temb=None, context=Non
         return hidden_states
 
 
+def get_down_block(
+    spatial_dims: int,
+    in_channels: int,
+    out_channels: int,
+    temb_channels: int,
+    num_res_blocks: int,
+    norm_num_groups: int,
+    norm_eps: float,
+    add_downsample: bool,
+    with_attn: bool,
+    with_cross_attn: bool,
+    num_heads: int,
+    num_head_channels: int,
+    transformer_num_layers: int,
+    cross_attention_dim: Optional[int],
+) -> nn.Module:
+    if with_attn:
+        return AttnDownBlock(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            out_channels=out_channels,
+            temb_channels=temb_channels,
+            num_res_blocks=num_res_blocks,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+            add_downsample=add_downsample,
+            num_heads=num_heads,
+            num_head_channels=num_head_channels,
+        )
+    elif with_cross_attn:
+        return CrossAttnDownBlock(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            out_channels=out_channels,
+            temb_channels=temb_channels,
+            num_res_blocks=num_res_blocks,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+            add_downsample=add_downsample,
+            num_heads=num_heads,
+            num_head_channels=num_head_channels,
+            transformer_num_layers=transformer_num_layers,
+            cross_attention_dim=cross_attention_dim,
+        )
+    else:
+        return DownBlock(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            out_channels=out_channels,
+            temb_channels=temb_channels,
+            num_res_blocks=num_res_blocks,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+            add_downsample=add_downsample,
+        )
+
+
+def get_mid_block(
+    spatial_dims: int,
+    in_channels: int,
+    temb_channels: int,
+    norm_num_groups: int,
+    norm_eps: float,
+    with_conditioning: bool,
+    num_heads: int,
+    num_head_channels: int,
+    transformer_num_layers: int,
+    cross_attention_dim: Optional[int],
+) -> nn.Module:
+    if with_conditioning:
+        return CrossAttnMidBlock(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            temb_channels=temb_channels,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+            num_heads=num_heads,
+            num_head_channels=num_head_channels,
+            transformer_num_layers=transformer_num_layers,
+            cross_attention_dim=cross_attention_dim,
+        )
+    else:
+        return AttnMidBlock(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            temb_channels=temb_channels,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+            num_heads=num_heads,
+            num_head_channels=num_head_channels,
+        )
+
+
+def get_up_block(
+    spatial_dims: int,
+    in_channels: int,
+    prev_output_channel: int,
+    out_channels: int,
+    temb_channels: int,
+    num_res_blocks: int,
+    norm_num_groups: int,
+    norm_eps: float,
+    add_upsample: bool,
+    with_attn: bool,
+    with_cross_attn: bool,
+    num_heads: int,
+    num_head_channels: int,
+    transformer_num_layers: int,
+    cross_attention_dim: Optional[int],
+) -> nn.Module:
+    if with_attn:
+        return AttnUpBlock(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            prev_output_channel=prev_output_channel,
+            out_channels=out_channels,
+            temb_channels=temb_channels,
+            num_res_blocks=num_res_blocks,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+            add_upsample=add_upsample,
+            num_heads=num_heads,
+            num_head_channels=num_head_channels,
+        )
+    elif with_cross_attn:
+        return CrossAttnUpBlock(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            prev_output_channel=prev_output_channel,
+            out_channels=out_channels,
+            temb_channels=temb_channels,
+            num_res_blocks=num_res_blocks,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+            add_upsample=add_upsample,
+            num_heads=num_heads,
+            num_head_channels=num_head_channels,
+            transformer_num_layers=transformer_num_layers,
+            cross_attention_dim=cross_attention_dim,
+        )
+    else:
+        return UpBlock(
+            spatial_dims=spatial_dims,
+            in_channels=in_channels,
+            prev_output_channel=prev_output_channel,
+            out_channels=out_channels,
+            temb_channels=temb_channels,
+            num_res_blocks=num_res_blocks,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+            add_upsample=add_upsample,
+        )
+
+
 class DiffusionModelUNet(nn.Module):
     """
     Unet network with timestep embedding and attention mechanisms for conditioning based on
@@ -869,7 +1291,7 @@ class DiffusionModelUNet(nn.Module):
         in_channels: number of input channels.
         out_channels: number of output channels.
         num_res_blocks: number of residual blocks (see ResBlock) per level.
-        block_out_channels:
+        block_out_channels: TODO
         attention_levels: list of levels to add attention.
         norm_num_groups: number of groups for the normalization.
         norm_eps: epsilon for the normalization.
@@ -951,67 +1373,45 @@ def __init__(
             output_channel = block_out_channels[i]
             is_final_block = i == len(block_out_channels) - 1
 
-            if attention_levels[i]:
-                dim_head, num_heads = get_attention_parameters(
-                    input_channel, num_head_channels, num_heads, legacy, with_conditioning
-                )
-
-                down_block = DownBlock(
-                    spatial_dims=spatial_dims,
-                    in_channels=input_channel,
-                    out_channels=output_channel,
-                    temb_channels=time_embed_dim,
-                    num_res_blocks=num_res_blocks,
-                    norm_num_groups=norm_num_groups,
-                    norm_eps=norm_eps,
-                    add_downsample=not is_final_block,
-                    with_attn=not with_conditioning,
-                    with_cross_attn=with_conditioning,
-                    num_heads=num_heads,
-                    num_head_channels=dim_head,
-                    transformer_num_layers=transformer_num_layers,
-                    cross_attention_dim=context_dim,
-                )
-            else:
-                down_block = DownBlock(
-                    spatial_dims=spatial_dims,
-                    in_channels=input_channel,
-                    out_channels=output_channel,
-                    temb_channels=time_embed_dim,
-                    num_res_blocks=num_res_blocks,
-                    norm_num_groups=norm_num_groups,
-                    norm_eps=norm_eps,
-                    add_downsample=not is_final_block,
-                )
-            self.down_blocks.append(down_block)
+            dim_head, num_heads = get_attention_parameters(
+                input_channel, num_head_channels, num_heads, legacy, with_conditioning
+            )
 
-        # mid
-        dim_head, num_heads = get_attention_parameters(
-            block_out_channels[-1], num_head_channels, num_heads, legacy, with_conditioning
-        )
-        if with_conditioning:
-            self.middle_block = MidBlock(
+            down_block = get_down_block(
                 spatial_dims=spatial_dims,
-                in_channels=block_out_channels[-1],
+                in_channels=input_channel,
+                out_channels=output_channel,
                 temb_channels=time_embed_dim,
+                num_res_blocks=num_res_blocks,
                 norm_num_groups=norm_num_groups,
                 norm_eps=norm_eps,
-                with_cross_attn=True,
+                add_downsample=not is_final_block,
+                with_attn=(attention_levels and not with_conditioning),
+                with_cross_attn=(attention_levels and with_conditioning),
                 num_heads=num_heads,
                 num_head_channels=dim_head,
                 transformer_num_layers=transformer_num_layers,
                 cross_attention_dim=context_dim,
             )
-        else:
-            self.middle_block = MidBlock(
-                spatial_dims=spatial_dims,
-                in_channels=block_out_channels[-1],
-                temb_channels=time_embed_dim,
-                norm_num_groups=norm_num_groups,
-                norm_eps=norm_eps,
-                num_heads=num_heads,
-                num_head_channels=dim_head,
-            )
+
+            self.down_blocks.append(down_block)
+
+        # mid
+        dim_head, num_heads = get_attention_parameters(
+            block_out_channels[-1], num_head_channels, num_heads, legacy, with_conditioning
+        )
+        self.middle_block = get_mid_block(
+            spatial_dims=spatial_dims,
+            in_channels=block_out_channels[-1],
+            temb_channels=time_embed_dim,
+            norm_num_groups=norm_num_groups,
+            norm_eps=norm_eps,
+            with_conditioning=with_conditioning,
+            num_heads=num_heads,
+            num_head_channels=dim_head,
+            transformer_num_layers=transformer_num_layers,
+            cross_attention_dim=context_dim,
+        )
 
         # up
         self.up_blocks = nn.ModuleList([])
@@ -1025,40 +1425,28 @@ def __init__(
 
             is_final_block = i == len(block_out_channels) - 1
 
-            if reversed_attention_levels[i]:
-                dim_head, num_heads = get_attention_parameters(
-                    output_channel, num_head_channels, num_heads, legacy, with_conditioning
-                )
+            dim_head, num_heads = get_attention_parameters(
+                output_channel, num_head_channels, num_heads, legacy, with_conditioning
+            )
+
+            up_block = get_up_block(
+                spatial_dims=spatial_dims,
+                in_channels=input_channel,
+                prev_output_channel=prev_output_channel,
+                out_channels=output_channel,
+                temb_channels=time_embed_dim,
+                num_res_blocks=num_res_blocks + 1,
+                norm_num_groups=norm_num_groups,
+                norm_eps=norm_eps,
+                add_upsample=not is_final_block,
+                with_attn=(reversed_attention_levels[i] and not with_conditioning),
+                with_cross_attn=(reversed_attention_levels[i] and with_conditioning),
+                num_heads=num_heads,
+                num_head_channels=dim_head,
+                transformer_num_layers=transformer_num_layers,
+                cross_attention_dim=context_dim,
+            )
 
-                up_block = UpBlock(
-                    spatial_dims=spatial_dims,
-                    in_channels=input_channel,
-                    prev_output_channel=prev_output_channel,
-                    out_channels=output_channel,
-                    temb_channels=time_embed_dim,
-                    num_res_blocks=num_res_blocks + 1,
-                    norm_num_groups=norm_num_groups,
-                    norm_eps=norm_eps,
-                    add_upsample=not is_final_block,
-                    with_attn=not with_conditioning,
-                    with_cross_attn=with_conditioning,
-                    num_heads=num_heads,
-                    num_head_channels=dim_head,
-                    transformer_num_layers=transformer_num_layers,
-                    cross_attention_dim=context_dim,
-                )
-            else:
-                up_block = UpBlock(
-                    spatial_dims=spatial_dims,
-                    in_channels=input_channel,
-                    prev_output_channel=prev_output_channel,
-                    out_channels=output_channel,
-                    temb_channels=time_embed_dim,
-                    num_res_blocks=num_res_blocks + 1,
-                    norm_num_groups=norm_num_groups,
-                    norm_eps=norm_eps,
-                    add_upsample=not is_final_block,
-                )
             self.up_blocks.append(up_block)
             prev_output_channel = output_channel
 
diff --git a/tests/test_diffusion_model_unet.py b/tests/test_diffusion_model_unet.py
index 69151adb..eb9902d8 100644
--- a/tests/test_diffusion_model_unet.py
+++ b/tests/test_diffusion_model_unet.py
@@ -27,10 +27,10 @@
             "in_channels": 1,
             "out_channels": 1,
             "num_res_blocks": 1,
-            "block_out_channels": (16, 16, 16),
+            "block_out_channels": (8, 8, 8),
             "attention_levels": (False, False, True),
             "num_heads": 1,
-            "norm_num_groups": 16,
+            "norm_num_groups": 8,
         },
     ],
     [
@@ -39,11 +39,11 @@
             "in_channels": 1,
             "out_channels": 1,
             "num_res_blocks": 1,
-            "block_out_channels": (16, 16, 16),
+            "block_out_channels": (8, 8, 8),
             "attention_levels": (False, False, True),
             "num_heads": -1,
             "num_head_channels": 1,
-            "norm_num_groups": 16,
+            "norm_num_groups": 8,
         },
     ],
     [
@@ -52,12 +52,12 @@
             "in_channels": 1,
             "out_channels": 1,
             "num_res_blocks": 1,
-            "block_out_channels": (16, 16, 16),
+            "block_out_channels": (8, 8, 8),
             "attention_levels": (False, False, True),
             "num_heads": 4,
             "num_head_channels": 2,
             "legacy": False,
-            "norm_num_groups": 16,
+            "norm_num_groups": 8,
         },
     ],
 ]
@@ -121,10 +121,10 @@ def test_shape_with_different_in_channel_out_channel(self):
             in_channels=in_channels,
             out_channels=out_channels,
             num_res_blocks=1,
-            block_out_channels=(16, 16, 16),
+            block_out_channels=(8, 8, 8),
             attention_levels=(False, False, True),
             num_heads=1,
-            norm_num_groups=16,
+            norm_num_groups=8,
         )
         with eval_mode(net):
             result = net.forward(torch.rand((1, in_channels, 16, 16)), torch.randint(0, 1000, (1,)).long())
@@ -137,11 +137,11 @@ def test_attention_heads_not_declared(self):
                 in_channels=3,
                 out_channels=3,
                 num_res_blocks=1,
-                block_out_channels=(16, 16, 16),
+                block_out_channels=(8, 8, 8),
                 attention_levels=(False, False, True),
                 num_heads=-1,
                 num_head_channels=-1,
-                norm_num_groups=16,
+                norm_num_groups=8,
             )
 
     def test_model_channels_not_multiple_of_norm_num_group(self):
@@ -151,9 +151,9 @@ def test_model_channels_not_multiple_of_norm_num_group(self):
                 in_channels=3,
                 out_channels=3,
                 num_res_blocks=1,
-                block_out_channels=(8, 8, 40),
+                block_out_channels=(8, 8, 24),
                 attention_levels=(False, False, True),
-                norm_num_groups=32,
+                norm_num_groups=16,
             )
 
     def test_shape_conditioned_models(self):
@@ -162,13 +162,13 @@ def test_shape_conditioned_models(self):
             in_channels=1,
             out_channels=1,
             num_res_blocks=1,
-            block_out_channels=(16, 16, 16),
+            block_out_channels=(8, 8, 8),
             attention_levels=(False, False, True),
             num_heads=1,
             with_conditioning=True,
             transformer_num_layers=1,
             context_dim=3,
-            norm_num_groups=16,
+            norm_num_groups=8,
         )
         with eval_mode(net):
             result = net.forward(
@@ -178,11 +178,10 @@ def test_shape_conditioned_models(self):
             )
             self.assertEqual(result.shape, (1, 1, 16, 32))
 
-    # TODO: Fix problem with torchscript
     # def test_script_unconditioned_models(self):
     #     input_param = UNCOND_CASES_2D[0][0]
     #     net = DiffusionModelUNet(**input_param)
-    #     test_script_save(net, {"x": torch.rand((1, 1, 32, 64)), "timesteps": torch.randint(0, 1000, (1,)).long()})
+    #     test_script_save(net, {"x": torch.rand((1, 1, 16, 16)), "timesteps": torch.randint(0, 1000, (1,)).long()})
 
     # TODO: Fix problem with torchscript
     # def test_script_conditioned_models(self):
@@ -209,53 +208,52 @@ def test_shape_conditioned_models(self):
     #     )
 
 
-#
-# class TestDiffusionModelUNet3D(unittest.TestCase):
-#     @parameterized.expand(UNCOND_CASES_3D)
-#     def test_shape_unconditioned_models(self, input_param):
-#         net = DiffusionModelUNet(**input_param)
-#         with eval_mode(net):
-#             result = net.forward(torch.rand((1, 1, 16, 32, 48)), torch.randint(0, 1000, (1,)).long())
-#             self.assertEqual(result.shape, (1, 1, 16, 32, 48))
-#
-#     def test_shape_with_different_in_channel_out_channel(self):
-#         in_channels = 6
-#         out_channels = 3
-#         net = DiffusionModelUNet(
-#             spatial_dims=3,
-#             in_channels=in_channels,
-#             out_channels=out_channels,
-#             num_res_blocks=1,
-#             block_out_channels=(16, 16, 16, 16),
-#             attention_levels=(False, False, True, True),
-#             num_heads=1,
-#             norm_num_groups=16,
-#         )
-#         with eval_mode(net):
-#             result = net.forward(torch.rand((1, in_channels, 16, 32, 48)), torch.randint(0, 1000, (1,)).long())
-#             self.assertEqual(result.shape, (1, out_channels, 16, 32, 48))
-#
-#     def test_shape_conditioned_models(self):
-#         net = DiffusionModelUNet(
-#             spatial_dims=3,
-#             in_channels=1,
-#             out_channels=1,
-#             num_res_blocks=1,
-#             block_out_channels=(16, 16, 16, 16),
-#             attention_levels=(False, False, True, True),
-#             num_heads=1,
-#             norm_num_groups=16,
-#             with_conditioning=True,
-#             transformer_num_layers=1,
-#             context_dim=3,
-#         )
-#         with eval_mode(net):
-#             result = net.forward(
-#                 x=torch.rand((1, 1, 16, 32, 48)),
-#                 timesteps=torch.randint(0, 1000, (1,)).long(),
-#                 context=torch.rand((1, 1, 3)),
-#             )
-#             self.assertEqual(result.shape, (1, 1, 16, 32, 48))
+class TestDiffusionModelUNet3D(unittest.TestCase):
+    @parameterized.expand(UNCOND_CASES_3D)
+    def test_shape_unconditioned_models(self, input_param):
+        net = DiffusionModelUNet(**input_param)
+        with eval_mode(net):
+            result = net.forward(torch.rand((1, 1, 16, 16, 16)), torch.randint(0, 1000, (1,)).long())
+            self.assertEqual(result.shape, (1, 1, 16, 16, 16))
+
+    def test_shape_with_different_in_channel_out_channel(self):
+        in_channels = 6
+        out_channels = 3
+        net = DiffusionModelUNet(
+            spatial_dims=3,
+            in_channels=in_channels,
+            out_channels=out_channels,
+            num_res_blocks=1,
+            block_out_channels=(8, 8, 8),
+            attention_levels=(False, False, True),
+            num_heads=1,
+            norm_num_groups=4,
+        )
+        with eval_mode(net):
+            result = net.forward(torch.rand((1, in_channels, 16, 16, 16)), torch.randint(0, 1000, (1,)).long())
+            self.assertEqual(result.shape, (1, out_channels, 16, 16, 16))
+
+    def test_shape_conditioned_models(self):
+        net = DiffusionModelUNet(
+            spatial_dims=3,
+            in_channels=1,
+            out_channels=1,
+            num_res_blocks=1,
+            block_out_channels=(16, 16, 16),
+            attention_levels=(False, False, True),
+            num_heads=1,
+            norm_num_groups=16,
+            with_conditioning=True,
+            transformer_num_layers=1,
+            context_dim=3,
+        )
+        with eval_mode(net):
+            result = net.forward(
+                x=torch.rand((1, 1, 16, 16, 16)),
+                timesteps=torch.randint(0, 1000, (1,)).long(),
+                context=torch.rand((1, 1, 3)),
+            )
+            self.assertEqual(result.shape, (1, 1, 16, 16, 16))
 
 
 if __name__ == "__main__":

From 80de3f7a8400e0fbd509d7c21640a78ddded8d42 Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Tue, 8 Nov 2022 23:54:34 +0000
Subject: [PATCH 04/28] [WIP] Reformating Unet (#53)

---
 generative/networks/nets/diffusion_model_unet.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index 8d1ce53a..ca361eb5 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -1291,7 +1291,7 @@ class DiffusionModelUNet(nn.Module):
         in_channels: number of input channels.
         out_channels: number of output channels.
         num_res_blocks: number of residual blocks (see ResBlock) per level.
-        block_out_channels: TODO
+        block_out_channels: tuple of block output channels.
         attention_levels: list of levels to add attention.
         norm_num_groups: number of groups for the normalization.
         norm_eps: epsilon for the normalization.

From 26b5403167c36540edd793a18f8250ad5d3aa9d7 Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Wed, 9 Nov 2022 00:00:02 +0000
Subject: [PATCH 05/28] [WIP] Reformating Unet (#53)

---
 .../networks/nets/diffusion_model_unet.py     |  2 +-
 tests/test_diffusion_model_unet.py            | 26 ++++++++++++-------
 2 files changed, 18 insertions(+), 10 deletions(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index ca361eb5..05e55b2f 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -565,7 +565,7 @@ def forward(self, x: torch.Tensor, emb: torch.Tensor) -> torch.Tensor:
 
         if self.spatial_dims == 2:
             temb = self.time_emb_proj(self.nonlinearity(emb))[:, :, None, None]
-        if self.spatial_dims == 3:
+        else:
             temb = self.time_emb_proj(self.nonlinearity(emb))[:, :, None, None, None]
         h = h + temb
 
diff --git a/tests/test_diffusion_model_unet.py b/tests/test_diffusion_model_unet.py
index eb9902d8..f82a172c 100644
--- a/tests/test_diffusion_model_unet.py
+++ b/tests/test_diffusion_model_unet.py
@@ -178,30 +178,38 @@ def test_shape_conditioned_models(self):
             )
             self.assertEqual(result.shape, (1, 1, 16, 32))
 
+    # TODO: Fix problem with torchscript
     # def test_script_unconditioned_models(self):
-    #     input_param = UNCOND_CASES_2D[0][0]
-    #     net = DiffusionModelUNet(**input_param)
+    #     net = DiffusionModelUNet(
+    #     spatial_dims= 2,
+    #     in_channels= 1,
+    #     out_channels= 1,
+    #     num_res_blocks= 1,
+    #     block_out_channels= (8, 8, 8),
+    #     attention_levels= (False, False, True),
+    #     num_heads= 1,
+    #     norm_num_groups= 8,
+    #     )
     #     test_script_save(net, {"x": torch.rand((1, 1, 16, 16)), "timesteps": torch.randint(0, 1000, (1,)).long()})
 
-    # TODO: Fix problem with torchscript
     # def test_script_conditioned_models(self):
     #     net = DiffusionModelUNet(
     #         spatial_dims=2,
     #         in_channels=1,
-    #         model_channels=32,
     #         out_channels=1,
     #         num_res_blocks=1,
-    #         attention_resolutions=[16, 8],
-    #         channel_mult=[1, 1, 1, 1],
+    #         block_out_channels=(8, 8, 8),
+    #         attention_levels=(False, False, True),
     #         num_heads=1,
-    #         use_spatial_transformer=True,
-    #         transformer_depth=1,
+    #         norm_num_groups=8,
+    #         with_conditioning=True,
+    #         transformer_num_layers=1,
     #         context_dim=3,
     #     )
     #     test_script_save(
     #         net,
     #         {
-    #             "x": torch.rand((1, 1, 32, 64)),
+    #             "x": torch.rand((1, 1, 16, 16)),
     #             "timesteps": torch.randint(0, 1000, (1,)).long(),
     #             "context": torch.rand((1, 1, 3)),
     #         },

From 9841294003bf103c9b1e78024f0a7fa798648a26 Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Wed, 9 Nov 2022 00:15:25 +0000
Subject: [PATCH 06/28] [WIP] Reformating Unet (#53)

---
 .../networks/nets/diffusion_model_unet.py     | 37 +++++++++++++------
 1 file changed, 26 insertions(+), 11 deletions(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index 05e55b2f..18ba95be 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -119,23 +119,38 @@ def __init__(
 
         self.to_out = nn.Sequential(nn.Linear(inner_dim, query_dim), nn.Dropout(dropout))
 
-    def forward(self, x: torch.Tensor, context: Optional[torch.Tensor] = None) -> torch.Tensor:
-        h = self.heads
+    def reshape_heads_to_batch_dim(self, x: torch.Tensor) -> torch.Tensor:
+        batch_size, seq_len, dim = x.shape
+        head_size = self.heads
+        x = x.reshape(batch_size, seq_len, head_size, dim // head_size)
+        x = x.permute(0, 2, 1, 3).reshape(batch_size * head_size, seq_len, dim // head_size)
+        return x
 
-        q = self.to_q(x)
+    def reshape_batch_dim_to_heads(self, x: torch.Tensor) -> torch.Tensor:
+        batch_size, seq_len, dim = x.shape
+        head_size = self.heads
+        x = x.reshape(batch_size // head_size, head_size, seq_len, dim)
+        x = x.permute(0, 2, 1, 3).reshape(batch_size // head_size, seq_len, dim * head_size)
+        return x
+
+    def forward(self, x: torch.Tensor, context: Optional[torch.Tensor] = None) -> torch.Tensor:
+        query = self.to_q(x)
         context = context if context is not None else x
-        k = self.to_k(context)
-        v = self.to_v(context)
+        key = self.to_k(context)
+        value = self.to_v(context)
 
-        q, k, v = map(lambda t: rearrange(t, "b n (h d) -> (b h) n d", h=h), (q, k, v))
+        # TODO: make use of xformers to improve attention speed
+        query = self.reshape_heads_to_batch_dim(query)
+        key = self.reshape_heads_to_batch_dim(key)
+        value = self.reshape_heads_to_batch_dim(value)
 
-        sim = einsum("b i d, b j d -> b i j", q, k) * self.scale
+        attention_scores = einsum("b i d, b j d -> b i j", query, key) * self.scale
 
-        attn = sim.softmax(dim=-1)
+        attention_probs = attention_scores.softmax(dim=-1)
 
-        out = einsum("b i j, b j d -> b i d", attn, v)
-        out = rearrange(out, "(b h) n d -> b n (h d)", h=h)
-        return self.to_out(out)
+        hidden_states = einsum("b i j, b j d -> b i d", attention_probs, value)
+        hidden_states = self.reshape_batch_dim_to_heads(hidden_states)
+        return self.to_out(hidden_states)
 
 
 class BasicTransformerBlock(nn.Module):

From fb550375f5c3c10639a7bfe6255dea12530582da Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Wed, 9 Nov 2022 18:10:27 +0000
Subject: [PATCH 07/28] Fix typo with attentions and rerun tutorial (#53)

---
 .../networks/nets/diffusion_model_unet.py     |   4 +-
 .../generative/2d_ddpm/2d_ddpm_tutorial.ipynb | 157 +++++++++---------
 .../generative/2d_ddpm/2d_ddpm_tutorial.py    |   5 +-
 3 files changed, 82 insertions(+), 84 deletions(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index 18ba95be..037cfa8c 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -1401,8 +1401,8 @@ def __init__(
                 norm_num_groups=norm_num_groups,
                 norm_eps=norm_eps,
                 add_downsample=not is_final_block,
-                with_attn=(attention_levels and not with_conditioning),
-                with_cross_attn=(attention_levels and with_conditioning),
+                with_attn=(attention_levels[i] and not with_conditioning),
+                with_cross_attn=(attention_levels[i] and with_conditioning),
                 num_heads=num_heads,
                 num_head_channels=dim_head,
                 transformer_num_layers=transformer_num_layers,
diff --git a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb
index b15ffff2..e2c4e8c3 100644
--- a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb
+++ b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb
@@ -36,7 +36,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -129,7 +129,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/tmp/tmpyooav2vj\n"
+      "/tmp/tmps65jg_gf\n"
      ]
     }
    ],
@@ -174,9 +174,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-07 23:56:04,346 - INFO - Downloaded: /tmp/tmpyooav2vj/MedNIST.tar.gz\n",
-      "2022-11-07 23:56:04,418 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
-      "2022-11-07 23:56:04,418 - INFO - Writing into directory: /tmp/tmpyooav2vj.\n"
+      "2022-11-09 17:30:58,066 - INFO - Downloaded: /tmp/tmps65jg_gf/MedNIST.tar.gz\n",
+      "2022-11-09 17:30:58,136 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
+      "2022-11-09 17:30:58,137 - INFO - Writing into directory: /tmp/tmps65jg_gf.\n"
      ]
     }
    ],
@@ -206,7 +206,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1775.27it/s]\n"
+      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1723.26it/s]\n"
      ]
     }
    ],
@@ -240,16 +240,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-07 23:56:27,056 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
-      "2022-11-07 23:56:27,057 - INFO - File exists: /tmp/tmpyooav2vj/MedNIST.tar.gz, skipped downloading.\n",
-      "2022-11-07 23:56:27,057 - INFO - Non-empty folder exists in /tmp/tmpyooav2vj/MedNIST, skipped extracting.\n"
+      "2022-11-09 17:31:20,695 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
+      "2022-11-09 17:31:20,696 - INFO - File exists: /tmp/tmps65jg_gf/MedNIST.tar.gz, skipped downloading.\n",
+      "2022-11-09 17:31:20,696 - INFO - Non-empty folder exists in /tmp/tmps65jg_gf/MedNIST, skipped extracting.\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1789.02it/s]\n"
+      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1781.72it/s]\n"
      ]
     }
    ],
@@ -332,10 +332,9 @@
     "    spatial_dims=2,\n",
     "    in_channels=1,\n",
     "    out_channels=1,\n",
-    "    model_channels=64,\n",
-    "    attention_resolutions=[2, 4],\n",
+    "    block_out_channels=(64, 128, 128),\n",
+    "    attention_levels=(False, False, True),\n",
     "    num_res_blocks=1,\n",
-    "    channel_mult=[1, 2, 2],\n",
     "    num_heads=1,\n",
     ")\n",
     "model.to(device)\n",
@@ -366,16 +365,16 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 0: 100%|████████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.863]\n",
-      "Epoch 1: 100%|████████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.568]\n",
-      "Epoch 2: 100%|████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.343]\n",
-      "Epoch 3: 100%|██████████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.2]\n",
-      "Epoch 4: 100%|████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.117]\n"
+      "Epoch 0: 100%|████████████| 63/63 [00:30<00:00,  2.09it/s, loss=0.863]\n",
+      "Epoch 1: 100%|████████████| 63/63 [00:29<00:00,  2.11it/s, loss=0.566]\n",
+      "Epoch 2: 100%|████████████| 63/63 [00:30<00:00,  2.10it/s, loss=0.341]\n",
+      "Epoch 3: 100%|████████████| 63/63 [00:30<00:00,  2.09it/s, loss=0.198]\n",
+      "Epoch 4: 100%|████████████| 63/63 [00:30<00:00,  2.08it/s, loss=0.115]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -387,16 +386,16 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 5: 100%|████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.068]\n",
-      "Epoch 6: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0405]\n",
-      "Epoch 7: 100%|███████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0266]\n",
-      "Epoch 8: 100%|█████████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.02]\n",
-      "Epoch 9: 100%|███████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0161]\n"
+      "Epoch 5: 100%|████████████| 63/63 [00:30<00:00,  2.08it/s, loss=0.067]\n",
+      "Epoch 6: 100%|███████████| 63/63 [00:30<00:00,  2.04it/s, loss=0.0399]\n",
+      "Epoch 7: 100%|███████████| 63/63 [00:31<00:00,  2.03it/s, loss=0.0263]\n",
+      "Epoch 8: 100%|█████████████| 63/63 [00:31<00:00,  2.01it/s, loss=0.02]\n",
+      "Epoch 9: 100%|███████████| 63/63 [00:30<00:00,  2.04it/s, loss=0.0163]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -408,16 +407,16 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 10: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0154]\n",
-      "Epoch 11: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0145]\n",
-      "Epoch 12: 100%|██████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0136]\n",
-      "Epoch 13: 100%|██████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0134]\n",
-      "Epoch 14: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0131]\n"
+      "Epoch 10: 100%|██████████| 63/63 [00:30<00:00,  2.06it/s, loss=0.0156]\n",
+      "Epoch 11: 100%|██████████| 63/63 [00:30<00:00,  2.06it/s, loss=0.0145]\n",
+      "Epoch 12: 100%|██████████| 63/63 [00:30<00:00,  2.05it/s, loss=0.0137]\n",
+      "Epoch 13: 100%|██████████| 63/63 [00:30<00:00,  2.04it/s, loss=0.0135]\n",
+      "Epoch 14: 100%|███████████| 63/63 [00:31<00:00,  2.03it/s, loss=0.013]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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8+uuv6PV62O/3uY073EvR6/XCjrCrqyusVisMBgOsVitcX1+HECSNNrFlaocqriPeG4/HGAwG+O6779Dr9QJzAl8NpyzLgtV+PH6NXKEU9hioyCVShhH422ohLz0xXyyf2HjYdJ4Et8EjvM862dCyIqqkjmMiNjWb7W9P1Si+Wq/XmE6n2O/3wV+oE6DRaARpRB/fcrkMRkqWZdGytL56jeqZUcW1Wg13d3fYbrc4Pz8PWyHb7XbOgl+tVmg2m5jNZgD8UwpS5fKa99v+LzL0vOuelLOQyivXpo1NnNg3kD82pIgqGSZ2B5XFeVp5/e1VNtaJ+/0+rGhwJWO1WoXdYKpu6/V6cOe8e/cOm80mHIExn8+xXC6RZVlwdtvVF1sPSsHFYoHPnz9jNpuh1WphNBrh6uoqWMyECbVa7dESH0OkdLWCeVssZdWy13/a1/Z/LF3M+InhUi3XY1rvvqpnT3JayztFlQ5EKitiLbN5g03yVIY6hBmuTpVMkEw1TWlJHHd+fo79fo/b21vM53Pc3d0B+BqiNZvNcuu/3mSg0fHbb7+h3W6j1WphNpvl9vcyYmU4HIbdaZSKi8UCi8Uit+Ro3Rpst43HK6OSlXk9RrRSy3s2lb/NKyUtvbK1bc++286TdkUqWCum97Vx3uyjtKLBQF8d/YaUap1OB+v1GvV6HZ1OB7XawwFBdOlwTZhMst1uMZ/Pc4GXdhWC9TocDsF1M5lMUK9/3VpJA6nZbKLX6+H8/DysMff7/bCys1qtgmuHPsWYumZ5MSqSlDavlMFhLfBYWh0rT+Xqs/q8aoAy9OSg1pSFXNTAVJ5kNjIQD+npdrvo9Xphr8V4PEa/38e7d+/Q6XRwdnaGdruN8XgccOLbt28xn8/x8eNHLJdLfP78Gev1OmrAkPb7Pe7u7kJY12w2wx/+8AcMBgM0Gg0MBgMcj8cwOXj8xnw+Dw51qmjiXD0Txq4y2GU2lSwpyefBnBiDqAbQkC4dJ8tQMUkaM8BoqD07JoyR7ZjYb49iHWvTEMPREiURN1KFH4/HgNeoylutVvA5Mhghy7KgKjTkSaUR60VjjAeCM7rmcDgEpzXxKXEr60vXTafTCdKh2Wzmop/tWrzXf8SSRZitiOzzlmljlLoXK0fxbxGdZJioea6i3Vs/9H7HxLuWpdcZRnV/f49arRas406ng/l8Hpis1+vhcDiE+zyb5ezsLFi3q9UquFgmkwlWqxVms1lQ0bY+ZBbGILbb7SAFyVSEAupKoop++/Yt1us1bm9vsd1ukWUZttttwIz8qJSkle71TeydLF6/eQzrQQ5rzNg8ON42nXot1G3DCVc2mqaSn7CseCWVmaVVZ/LxeAw7w1gv4CEaZrFYhM5QR3e73c6pUa528FuZQfPVstm52+02BLpS4trYPyBvJPT7/YBBiSm5E07dX7qaY7dash5VrOr/FaUwaBFVkoTK9SxYO6WMyngOxiTeIK5jFHan0wmO6zdv3mA8HqPb7WI4HKLf7+P8/By73Q7D4TAs9S2XS9ze3gZpeHt76wJrWsq6ZKdLhPbAcJUglMj7/R4XFxdB2qmRtdvtAkalup/P54FRFUt6UtIzNlJjaK9ZreYZi9442w/wsN7/PzmL5n9BsQ6liia+4gpKr9fDbrcLrhv6Eev1eji1gMCZ1nStVgudZg8EYtl0zwAP1jullvc2AzImnydU4Noz1RUZkEaXMiOZFXjAxhpSpuRZxCnBoHXVtJq3ved923y07c/OhLQirbUEPLbqPKbxrLrU/aLrJA7ofD4PhshyuQTwVUVfXFzgeDwG1w2xbKPRCBJyOBzi7du3WC6X+P3vf4/1eh1221ECkQnJ2BpjqH4xxc0kDXPiMiUNFGVKMjbD09rtdrDw1+s11us1lstl0ALWmLEaxzKJnSh2HPQZlehsn7c5SvPRQBNu0ShDlSOri6wpz1r21EcKyxRZzEqUEAT2HDgyCQ0ZNSrYoQxYJa3Xa1xdXWGxWKDb7QYG2G63j9QLgyUsFvSCROlgV5VG6c32Kgbk6fuU7lyjZpCGRpUrbrSGn4clWV5sNcMbC2uc2H0oqi24cEAfbRkqzYScsd4GnxQVpfXcNKeqerpqqEp53MV6vUa328VkMsmtsvCVCtppvV4P2+02GBJcZaEW0LAte7IpGUn3elhpwKBYzzWjG5EoNbk+Tot6NBphvV6HpUhKRuJkXbONCQz+1/rbvcR08qsEBB6fOUPMyzV9Yu8//vGPzy8JyYSpjGPM81xSz8vTPsu13Pl8jnq9jslkEuITGSP4u9/9Dt1uF5eXl8F1w0huOqCpHnmylZ7fQlVIBzfrQmOG6prqSYkMy3rrmjafb7fbOB6POQxLHEs/JV0+k8kkGGhq5dt+V2KeelA6tUSn03kUNscx0rhChSDD4TAYgOPxGBcXF/jTn/70Mst22iExTOf5AD0/VMpPWERlJTGBPaUFl/f4Ab4aDMBXuEEXjkoGDgp/c/WGRgWQx0asHyUSGdXiKf2mqqbjnf/VF6tp6dKh9GPQhh5mZOtjiUyoG7yUKfWULs1DGZXPkAn7/T4GgwHOzs7w7t27l8GEutWSFdNOss5q3rNqiXgmhhdTVNUXRXXcaDQwn89DQAKX9igRz8/PcXl5icPhgG63G44IGQ6HOe+/RuXYfS0k9TkST3LA+CHGtGr5cDiEKCLdxsB+I/NzzzR3JGpgbsoIUcyq9dATYDUd68Q2sN8YdU7/K+EM9+e8CBOeIrGs34mNUxwY+xTVo6oa133HZB61UOnbGo1GYZupSgOrgrR9Vjuk2mCNOwX3XBCgPzKGlSkpldFpzCjTWetV2wIg+C/JhBbL6oRn2k6ng/F4HFai7D5xnnrGfdxlqPJ7TCyxcexEj6FqtVqQBKysdS3QcasSwB6IZOtTRHYQmT/XjtfrNZrNJu7v7wNmvLu7Q7/fx3fffYdutxuiZjhYHGgOiDISpbvGE9IfyQFl21Q962Adj8fcWrPd5M/vwWCAw+EQHOZUx8DD1gdCDuZrtyxQsrEtNMyoAehu4QYzTky+64Tr9HyWY8ejXMpqrRc9JFNnLkW/fRu59UtxgNQiPYU0PwsPdF2TZdCq7XQ62Gw2YeM7B5ODpz5R+1JCzZeuFA+iaF20vkqaj424UYlLlc4JQtI1bTWC6AJSJiRjkfl0UxdPp1DVrQJFrWMKEh3nMnTSRifrB1NMqAYMRfpgMAjHarBy1vdETKMzlgxCh7G6MNR9oHXg4LIO9gwZDgaZRvNiQGqn08Hd3R263S7evHkTYgZ5UBMHj3tdeNAk8+ZhnEyjPkCNtKaxxI99c5KeKKt9pmmspNQ+0f+cLKpymQ+PIdbDqEajETqdTpCEajGr+4ZlWLdOFTpp33HM2lIGYDpWno5hdgQryo7X16Oqn4trtWRG+ujYWMVnAHIMrIPMfNUAsHWn+mu32wEXAl8taEoUqiBtBycbpantJ9ZZvQtWErKvgLwUVMmn/aaSnM+TEbhCo/7Mer0epJ31a9KYaDabgQmHw2HwIlDyKRNrn5fhjxRVXju2M82LrGElNByeQFX3Z2haG/pjO5xYS8uzUk8lgxcgoEtdmi9JVQ7rRUzHQAl6Cbgqw/aRYbTuOmD9fj+0QevpWbP6zmHb93r4O/uY3+qC0rGgBBsOh+G3GoYcFxooqnJthFBqzHXiexozRpWZ0KqEWCEKuglwe71e7ngNNkglgw6eOn0Vc/FDJqMUUwnIUCvuY+YymDKeqnfWyaoqjwkpVTnJiMlYX8XAvEaVTZxIx7ftR5VcOrjAg4Vqo3zIaI1GI0Sc62oI752dneXOZNTy9LDQ2Jgq3LJjzevEhOzXMm6aSurYLtlZaaakldIN7VYdW/eNdigtafVdad6eVFMGJTOuVqtwuoOqZWtIkHnUiUsrUbeeatuA/DnXqpY1Pw2gYD+oH45tAB4CV5WJ+Kx1oVicp/5Idb/ovm3Wzbq7dEkyBbm86/y2zvgyVGnfsUcxLKDqM8uy4D/SwbGdptJDra/Y7NSZZrESabVahYPCJ5NJiEDRxX8dTAXZjUYjYCRdxqLEJfNZfKr1ARDaTuCvwRDsI+anBgoNHMV5tjxiOeur5LYG4jzFe+x7NdoUh1t4oGOq11JuuxdhQmulxUCpV3HiMh48xI5lRZUJqe7Y6SmrnM8AyOXF/2oY0d1Cn5pKU6/T+SwH0Eocu/gfc7EAeUe5xZ3apzoJyIyclMpoWiYxnOJj9UNqf1mpq/GJZELbf0Xa7jmoUjyh4inbgUD+9HadLRx0SiSqBlV7FktxEHStUpkOyM92q4I4yJRiOkCsD5/T08D0AEy1KK3BotJDHfAWJjCv+XyOWq0WHOV0EusLqhU/0hlMFaoGhaZh37BcRmErdGI9NTqbY8r28prCDoVICgFSBgfvpewFS5Wc1So1PN+VVoQDwAYytk8duOw8HWCVMLyuRoANoScuUyvRTgQdEJUEhAIaUGqPAuZqgaoxMpyuntCAUMMp5g6y/lT2mQ64tlEnoOJEK5HZl6qyrVZST4K6w3SZUCVcTN3GqKp7Bjjh4HR2irpESLyuA64WK2eeDpw6OC22IsNptAaNBF7ju3xpEXLZSSWGOllZL+BBQpDZiZs0DdujC/TMz1rFutxomZqTRYG7MrcyE6UR8+J/Or914itWZVtoBFlppu1iHRg2RoPEi55RI8hT0ZZRy3hPlCoHMFjJ5/1WJ6t1zvI6G21nvcVFOlAqbYiNFOQzvfqq1HflLSVpndUSBfIYSo0mZQSVSmot6xKWdcBr2SxXcZ5ORHX8q5HGfvSwm4fXPeZRQ8vmZ8fbquIYD1RRw6TK8YSpxvG/qm0ypJU+Gnhp81L3DfAQDTKdTnMhRWQMXXhXa1axloUIwIOa5tIU32PCMrQtuhWU0pxwghOK+JFhUbxHiWb9mbY/2R6u1aq7SPuF/WndLNqXiuGsWiZ5e4aofWy+nlvN2gSWN8pSZUzIQmwF7DU7I3jNrlJUIYJ7AnX17HNFhmfOENRzYOkyAvJSnSq81+sFC5pMq4aIWu26t4R9U6vVwkRQY4gMpxvb1Y/Jb+CBcTTAVKW9HVztS534rLv1s2palke3EJ9LOautJI0JH3uviE5eMbGgW9Ut/3sMF8MRZYjP6FosJQIZg697UB+bjWtTCdhsNgNWJZPybBlVQWR6dZEog9br9bAyo1tNdXCBB8NJo3fUP8h02sesM/A4cJjPKozg86rqNU9+axtimq0KnfrcSUyoINxaWwAeMaKtoNdQO0tjxAH0HKf8JqNY61Gd3/V6PYSlr9frcMIXrWbLhJ1OJ0g3ddlonbgbbrPZ5MLkdc1cMdfxeAxn4ZCUwT0cbvuak9GTYJ7/UvNVYy3W71quLnHqM1Uc0x49S1Crl1a/Y6D5VPLqwv9W+ip+Yh34smllSmtR2vap1OKKi50A1sgA8kEc6gNl3taFo4yh7iCd8LZPvf7R32UklFXXnsZ6KvaLUaU9Jl6lPGawqtkCWc0nxZQx1a0uBcvgyoz2Wb6eVevE0C01DNRKtVY28yT+tOWyr5S5lAn5bQNLSWTg4/GYc7ITbqgVq/2kElb9kIpdbZ97DK2aTe+lxuepVNlPaHFfiuwAVZWCZVRzmbQK2oF8YABXb6huNZTfukQA5NxFzNsOnD3ISKN96KyPuUKsM97ib8tYKVhjVagdi7IMdgqzlWFiUqVlOwXUtuNJMbxnY9CeQy2n8qF0UIxIKce4uqurq3B40tXVVdi0o5JKTxI4Ho9hGY3/afFaQw1AjonJTGoJ04BR/yOlsUo3jdhRC1rTsD5qkfMUWzuRtE88HKkTINXvikutIcUyrMHkUWVMGMOGlqwlpteZ30uRlSgAcqsndN8MBoOwh4K+Qmu80M2jkpB7TrTTNURM62F9dbourqpfXTLKCOwrlbjaj9ZZTbLPeKrYw45Wa3gUe04/NpopRZWZUK1jryHAY9CsWIZkg1k9lVFGXbA+urRFCUaHNX/bkCYeNTwajcKZhWo0NBoPgaCM1OZRF/ryRT5jVzz0QCWuM1MqqYFCjElLnisydjuDOrA1uEPzIXbV/rS7FtXdk1Ln1hK2eNuOOTUBpTA1RxE9ad9xGUzoWVQxqWpFepE1RgbUaBICfzJKt9vFYDAIm7YpCZvNr3uMufWAL1fUDmZ+3LVWqz1s9dQN8joBdJmRoWt0VgN4pBrpsFYGZhplHpavBpOWpcuT1iizatOutnhj6gkCO27K6DquumZehk5+37H11tvKxT50XXhYRP16wOMtACQ7IGQWlXIqCVXyKbNoWBjzZT2YH7c+NhoPJ2RRClHCsc0MoWIbKGnIqLasWi2/TZTE87cZCKFtZ/mxMH1dHiXj6wTy1poVLqjVbSGAN7aaTvf0aLRUEZ3EhBZjeEyoM4kNVNBtATAxkobSs0NszJsX9kVQz62KavnytWDD4fBRvmow6WCRcSlFgYdoGxs1Y091ZRs5CTgp2I9A3geo+1YYdKuqjfVVuGEZykosHrapE8su/VmsymvA4+27SpaRtf66wezZJaFWsEp6qhfOXF3OUrVCY4EDp0tY2iEaIaPrrFTDeqhRrVbLMWG/338EB6wVrZKk2Xw4aV8DDlRK8b/FshxYTgbiPLbFunm0ncxDA0zJgHyGGJOqVevNOuthTBpiZrElJ5T2jWU+lZIqkJQBdWcjpXkZqrT53bN2LSmjKl7TCBN2PAeq0WhgPB6HIzd0Y442XtXT8XjMGQfcLcZnyDidTicEN+i2S6pKDgoHVoMcNPpFB5d1Z4S27tNQRmX7m81mkMLsOw9+kHnJfNyXQkbhBFZjw6pRPdSdARl8npvNKAw4gbVPKdV1stjlRrqk9Ghl9gv7TN8xWESVo2g8a5i/PdymxoPtcOAB46gUVN8Z87B4k8966omDzQ7ivhYyiJ4TQyakVKEEGQwGQTrQyGAIl7ZP+4b9oP5CTjQypV5jvdlO9pPtL4UQ6hJSdWrVI8tTHK51U+mu+NgzGFUyUuXSAmZeCh94HN+zM2Hs4EWtoLXCgPw5NBqVrGqYBkWv18tJQkpNtbSoYhXz6Xqr7jvmNk9dKwYe9ssQv1i/HMule6derwfpolsMFKsBCBa6vqCHkkUNM0psnkxB9xAxMScjJyhJlw5ZLich+5n7eJTR2W495JMBt+xH72g4lsFJzfZkWZZTxUxHTbJYLHB9ff38hknMZC96RrEDnb4aUEBiGkosHUBvW6K6A7RuZDC11LhywOc1lk9jA1Wy6NmD9Xo9hwGt4WWlk3oQ7KRVQ8BOTCv9PAxu89QJbaW0ahHtN2oIlV4qiTUf5q1jQjVM4aM4led8c493Gap8Fo31I+k9xY0cDEpQnnnCQSfuIXOycYpVdHlMG2sDDNS3ZjcbERsxn8Ph4WwbHVjin1arFd5TQsxpNzmpGlaDgedKk8npo1SJTYbTt0x5x3aQeXSw+bHLiuzXw+EQLHpVm3zRkOJgPRKF+bBNQD6Il6c+WOtdN0kdDodwuPt8PsenT58eLdU+mQmVigwTz39EIlgGHva4koEUq1C860y2EovEjgLy+0IItLXDtROZHztccSPTMF8tMybdVDJwYvD1Znbr6Gg0CvBDo7BtP1u3GLGe+kjpH2Sb2A7tf4sHVRuof1GPVWH7eZ9MyP6kFmJavtV0Pp+HgwbKUOXzCWNqwhscMhEbyyM5rO+KHcdvaw2Gypo4O8U9CtxVGhIbqoWrg6kOa10NqdVqgYFYJsuI1Z37UxiVo5ap7ikmFqYU7Ha7uQlIKGD3oai7i1ha66R9vV6v8fnz5yCdmd/x+HX/N6WkDYlT/56qdI4f68fJvN1uAw7Vs38mk8nzGyaqhj0mjOEPMoa6JzS9WrT2o1ajdrRafbofhJ3IgSAT2kFg/XXvBtUgQ/tHoxEAhKN4VcKSAa1Vy2VArkUrLlRfH9um7ivCFDKQMmHMyNNoau1HMs10OsVmswkvj2T7aWSpSuV4eYfB8zqhBl0y8/kcm80Gs9kMy+Uyt1pCCFCGTmLCmBmvZBlSVSTvA8jNRAus7fKdF2tnJbOqIVUhWgdNq9KFTu/BYICrqyv0+31cXFzkXjPBVyWoH5M4jRE5xH92EIEH7UApulwu0W63A37lxFEiQ+iKku43Zv77/R7T6RTT6RSTyQRZlmGz2SDLspwE033RNljZYlAePE/MTkbb7/eB8fQ1aFT1Fnen6OTjgmNMqAyh/j3PoPH+JytrmNBKW0vWr2ilOAeAqk2Z8M2bN4EJdXspX0NG9wolS61Ww3A4DGc164RS6aZYVieSWqn8sFwg7/hXBzYnF91C0+kU19fXmE6nQVJlWZaTXGQya/GzH8l8u90uvHiSklCZ2Fs1IiPaiZQc19IphbSDdXCrMNQppOo0pvotgyrj8boOPn12g8EAw+EQo9EoLO9pe3XFgNKMHc0JQActpZyqJ95T9amGjtbVYk6tK9urkowScLlcYjqdYrFYBIahVGId9M1PyixqtBwOh/BmrMVikXufHpA3XqzxoXUrS5VdNFZlxhjP4j9PUup/K1k1nTJbUeMoHXRQLYOqemNI19XVFUajEd6+fRvUrDrfyRR0RXAAlEEnk0nAe61WC4vFIryWTCWDlXJ2YujaufoVWW9KX2WWT58+YTabIcuy8EJG4uHpdIrVahUkmkoyOuzJtIvFIkhN+4Yo7WPgcYiY9ntZVQw84VWzKSojEWNMqfdPka4E8lb9q5rjYOtJDbq3xC4t2klA/5nFpRws5sOzEe0yHlW0h6PVYaz4DHgcnkVLl1IuyzIsl8sgCWezWWBCGii6tqxGBiUk8R2tXSvVLP7WNsUgVxFVZkLPOi4q1KtcmQoX5WuZJPWcqkkyCd/oxAhrumTU8iRWUxW82WxykTEcAA6glqkObTK4wgLWyfoAqe4oicjUagDQmNntdvj8+TNms1kwTLIsw5cvX7BYLPDly5fcscmLxSIwnQ1Y0HVgi6m9MfTSqEejDL2IJCS9BEY8FXuqP89awnoOoG5MUoOBnWr3HetEWK1WjwC5ulVYf+bL/54BxzwVY1GKERLQuGDoFKUgHcZ0ndAgoeqlX89KOZaldfD8wmX6P6bhPKoUylVUYJElHMOGVZiqyC3kOb3JBPomona7je+//z4X4s+lQjLGfv/1LZ+6NkvnN/Cw4qMGk13J0XNz1Kmu2EnrzLpynZ2Si1LMukLu7++x2WxwfX2N+XyOm5sbXF9fI8uy4Kymn5AuIKpZlXgpbeWNgbUN7EcXAYroxSShh8n4nWLOU4kMoBuA7FEc3L5J1Xt+fh7ez0ZjhKTrz9rplCg64Yjv7IumNbyMkpPqWRlX+0itYTKpXYJTJsyyLBgdfPkj3SrqWtFnbdusBNZxi5FlRB2HF1XHKSmnjYlhMlthL58UWQyoqpWSjD6/brebCxBQCUO1y7c0MU9alGoMsD36cka1LtUSZPCsGjzMg+8uplHAfNUBrZHfmlY30/MencifP3/GYrHAzc0NsizD7e0tbm5usFwug2WuLhU1rrxxsIZcbIw8oVJFBSs9acUklkZ/Wx+Yl7YMaafwmysYrVYr7Hyjqh0MBoER6UDWZb96/euBSDwSTpei7GSjS4RWpK4gaDt5EFKv1wvrwepfJDNbIiPS+U3JRWZl3RQm0PK+u7vDfD7H7e0tsizD3d1dcMlYy9xGgKv69MYtNr5qWMXGKpaHRydZx97Hq4jes7MqNctiZF0snU4nrF7o67C4qUmtXc2D0lNBOh26VFkcKEo9SkANCmW4PAeE68w0ILrdbhh0PeC9Xq+H5T1uwCd2pMSyy2nKjMR7i8UCv/zyCxaLBSaTSXDTZFkW6hkbNzumZRin7L0XU8fWD6Rq6LnIdoSqJlXBuoR2fn4etnPyu9PphJUPi4HIAPV6PfdaC425oz+Oy1a66mAdvCrll8tliEekBGZeahwRCozH4/AhTGDcJXGjrrmv12vMZjPc3Nzg73//O+bzOX799deACe37Way0i6naGE63/z3BEjNQXoQJLWZ4qiFRpUw2VFcPiPXoWqFRoAdUKvNpnlSJ6ujligEHkYvzXEGg9NNYPDVQarVasGBpVGjAK4N3vbrr2TNqGZPxaXxMJhN8+fIl4D5OHutYjq2jP9d46JgoWdVelp71LJqqmC9lkdnZRkxH46Pf72M8HuPs7CxIPu5V4cYiVUc6kwnY7+7uwnoqP/T13d/f5yJGbLCsagLmzYjsxWIRnOCcDHQ4U0KenZ2FCB3GL9J/SPjAZTjivPfv3+Of//xncESr35B9b/GeTpIYg8SYKzaeVvp54/X/jbO6iMq4ZihR1KDQ3Xlc3dDlNqvCWRYZgoaIvnJMmVAjRuwKgtZbtYK1aokRNciAbfH2kSgWpOXLtef7+/vwYaCCSm6PyWKGYJFRcQp5wqMKVd78nmIcz9hI+QdJMWCsOLBerweXy2g0Cns0qIZp+dqjL9QXRqaaTCbhXXdUZzZMiSsSWhevnhYnAw9qvt1u56KNGQjL0yIA5AIi6JT+9OlTMDqm0yk+ffqEm5ubEKal7iFOzpTbJdbX3tjFyMOItk+0L14sgKGqJWufKSPeU/nZyGKN/iXZAANr6XKwKWlWq1X4aFobZ5eaePaeF5qvUdk2JAtA2Ku7WCxwf3+P2WyGyWSC+/t73N3d4e7uLtTbRnnbPrWS2qvzU8gzak7xdpCedFywVirV6DKVK+oYVWXKhOpEVoagQcHB1Qjg+XyeW8ineo5NHNu+olnO08B42hePn+MpDJwQui8jyzJcX19jsVjg48eP4TvLMtzc3ASM6uFR24e2r5XpT6GY5ex9c4z0yJIiOtk6thRTt7HrsbS8Z11CvK+YipKOFqnuY6GBwQV8Bmhq7JzGBabqpJ1ZRs2oBcyVE/oF2S61wrncxlWP6+vrEIJFv99yuczVUSdEDPKk4IPtc4+sZC1Kz/u6T6gMVQ5q1cqVTRMDyLG8PPDM2a8fxX3cbK1Sj6sbekagVblFTGXjE1PECTIej3F+fo7Ly0tcXl5iOBzi4uIiHM7UarWCFGQYfpZlgem4+nFzcxO2UVJSe+ovpg7Vs2D/exjPjlUZ0vyU6bzomxidvPldr+n/IiaLWXCxTlGyLiJ+7/f74KydTCa5t73r5vcyZFWXBzNibaMaOjs7w7t373B2dobz83OMRqOwV4VGCV1Dk8kkWLwMPLi5uQl7d3UzPZmc9VQvQIqxvN92YnlpvfxiRo3u/Uml9ejZ1HEsfYqsyk1ZbarCuNO/Xq8HlXp/fx9ULlc0rJvmFIoxnJcvlwp1TzGd0XbVRttC5mMQqq5+qAXsSeQidRpjtpQw8QwOe88rq8guiNFJu+1OsZLtc971lCo5Hh9WOuwm+PV6jZubmyABuTpBaaFn4Hj18/BOrKPtMwDCKs3V1RWGwyHOz8+DQcK1bDIdQ7oIFabTaVgF+eWXXwJTasAp8ZVaxboFwXOXsL4qJa2U91Szx+TWMPPggP1dhZ6kjmPpqroGYgxpGYQ4js5kkq7nWmBehoowXxEwtwd7qjNaJ4P1CWr8H91FelCRx1ixOpShMsZFGUhVppwqz5RmQkofb4OOpZQUsf8t/lCjw6ann48br220MPDwXmKvzJQFXzRBbEQ0rzNyh2vBNp5Qz3LRANNff/0Vk8kEnz59wsePH8N2TZV2doOU1rUKg7DO1nDQ+7H8WY9YubGxZuhZGXqWZbvYbH0qHvPKITYEHk5WLSrHqvkUHipLVG80RvRwT5WIDN0nM1HaaQS07vmIqbaY8WHbZ+voTf5T21yFiH3LUGVntQf2ixguJn30Xgy7eB2m4e5FqsOzpkk24NTm4+ErpuEJDJ1OB1dXV+h2u7i4uMi9F+X8/BwXFxfBcFqtVvjvf/+L+XyODx8+hI3qdCHZsmIYVSei3ve0hz5b1g2TUv8pj4Ytt+zS3ZPeYxJLlwK6qWeUEVNWc8yQeWrdy5CqZz3Fq9frhZ17jKymiibT8JgOBiJMJpOcNFdIUqVdyhSnQKVU/h7DpaRpkbfDo9JMyPAiYjBLsY4oqmzK92T/W+aLdbhVZWXqZKWOTWP9YJ1OJ+xXpgTkIUrqpqH/77fffsN8Pg/7g2ezWe70LSAv4cuQleKxNBbP2faVHQObX4w8SZ2iyoaJxS22gqnB9ygm5bx7mqaM+i9jDcZmrFXv9uwYLsVR/TK+kSqaElDP62NQwnw+D9hQ62q3X6bqU4XKbNeN/S/zjKUXs44tJioDhsuq4rLl23KK0sUwlf1vn7FSg2n2+32wfHlEHI+D6/V6GA6HGA6HgaG45DaZTHB9fZ0zRFSjxDBpqv1lyJN43nfsvpdf2TKrqP3Kr5BgQWX9apbK+qCsiyB2z+brpYlJO++ZmKuC68zcYNXv93F2dhZO8+J+l9FoFAIOVqsVbm5ucHt7i19//TWEaekyohohHsMU4d8UQ5W55uXnjV9Z46QqAwInrphoQR4TpZi1bAXVWPGuPzd5VrEyB53ODEKg4aGHquuiPR3Tk8kkqGAGV8SsVq8PtH4x0J+S+GXb/Vx9ykn1IupYgzxrtccnBJSRjrayet1zS6QihYvUfhnmjQ2eGgdkLDLbaDTC5eUlxuNx2NtsmZGqezKZ4Oeff8ZkMsGHDx9wPB4fMatKHq89VurEJrVndHjS00rdMpiwiuBIrfTEqPRuFM/K0uuxSqdUwFNmXxXc6T3r4TCvjiQ930ZfdqOnuJL5eCwbMWDR+c2W6bzfZZ6tmrYMRDmVXgQTqotCVQ7vAT7A5vVYJYtcKZ5E81R1kSSO1cN7npJe20qfoFrEl5eXufcec5/yv//9b/znP//B+/fv8dNPP+WOi+O6sk6EFO4ro7pTONvTQEV4WeullnUZnM10L3IgUgyw81oRDjx1hsWePdV6LKsmrMqyktDu9ONmesY23t3dYTabPTr2wwP+nkvp1P56CmZOPVclz6parpJh8hT1GcNcRemUPEsypr7KqFh9RvPVD9d+uSJCScjXSjAw9Xg84v7+HsvlEv/617/w008/hZB83QQf64MUbIlZ0Fr/lKRM4cbYt6aLLaN6woiY90UkYZGIr0qnunhiacuk9xhX/1spz04l5tO9zrplkxE9ejjR7e0tgMfvPIkdE5yqX8ogKbqm92LYPcaAsWup37GyUlR5xaSsyC5islN2gKUsutgAVsnXu97v90PIPt/JTGY8Hr+GlzEM/+PHj2FdmHhKjx1W69G2J4UHtY0pI1ClpZXwMazOe/ptKTUBPAlddQxKM6EVr97A6/8iaRYb+JRUS80+L58q5A0w1TANES7P6WGYlIBZluHDhw+4v79HlmXheTKrXR+2EteT6GUmW+zZVL+k+q6M4VJ0vSqddCpXlWeAl4lieUq6lDThf3VAU6LpS2y22y2ur6+x2Wxwe3sb3vfB1RA9IN0zPCyd2rexfMtINisF9Zrm50nkIqpiIFU+BkQ7NNapZZjPc0sU4R7NN9ZRVWa5zdsaJBqkypAtHtuWZRl+++03LJdLfPz4MfgGN5vNIwnoSSmvLSlm9YwC4PFrHJQ04MIrl//LSLUivKj3VPKXocqR1VrpU6RjLD/7u+yzVctKkZ0Q/K8+Q33jkX1xTYzhWHZR21KTrqxRULatloomKL+rGDPPHlltK5UyBmLg11ZUXQ+aVp9VKsJLNk1s8Irqq6c62HeP8LyY6XSKDx8+YL1eP3qLpufOik1ar6/s9k6v3fa7SGqlfmv5tr62LA/Lem3VA+SL6MnLdrbCtkFlZm3svi2zzOwuIxnKSEQyk32HCMOzeHClvg+Ez+nnFEpJm6JnWP+i36l8UwxY9OwpVNk6ttadN2O9/Q8kz6qzacvgO5ufl0cRdknlxzbc3t6G1zH0+31kWRY2p/OQdZvfqQPkTWRPG8T6zRsLL08bQBH7Tk0Gq8H0/ou5aGIYwIpw65+KpU1dL4ONyuCrFJYixfIhuNa3N3G/ME/14mGYVVTPc1AVy7MMpRjOu6fPPQedvNHJw4Qpi1mfS/1PUVUpeUonaZuIAbllkxvsmY6RM2W8AGXa/dRBtpM1pQlUIhKHatoUlvQwoX6qLNkBTzgk89QB9kR3kWqMpS2SjKnnvGc0DV0fDECo1WqP3napMZVeHlq2ZQyvrl5byvSTLbcKprRMGEsfy59Ml2pbEZ18SKYeOGR9XRb36XNlZntMslRtZFE+ZRhYlxd1yU2fYRrFyynyYEyqvkwTw9Ekbyw0fy89tyx4k0T7yZOuZD7v9bwvcnC63ZSjrylNDbY2IDXYmo+H52xaj6r64bSs2MApg9g3YOrAFD3Pe3bDfVUG9CSOZ5WnoJEdFx6vrPdS5VJy6svL9W1ZVU9DqxzAoA3hDCpqLDvKXvful8FXXtpYaJjWLRY04Ul0S3b/iM2fv21fWKzF/zHpo2ljzOClSfWf1kE/9q0IMfVtVbU+qxJR07zIikmv1wsF1Ov13ClYdM7a0zm9QWU6fa9wKi3vAQ8HBCkOSzGmShyNcbN56BvWbb6WEbzOtQcYMXJaHd0xyWili5Zl9zp7adgmlUSWUfRlPXxG18W9+D87efkSIW0Dg3gVjuhr2cpSZReNzh47QHbWx05q0LTaAGU6O7N4jeJeJUkZDJmSIilp9FRK5eOVn1KB+t+Og2VaZUrFbpYJyXxW0+nktcJAx0PVuI5LpT46Vn3ilV7pmam8CfNKr/RC9MqEr/TN6ZUJX+mb0ysTvtI3p1cmfKVvTq9M+ErfnF6Z8JW+Ob0y4St9c3plwlf65vT/ANZRE4E2DP8hAAAAAElFTkSuQmCC\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -429,16 +428,16 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 15: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0126]\n",
-      "Epoch 16: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.013]\n",
-      "Epoch 17: 100%|██████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0124]\n",
-      "Epoch 18: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0119]\n",
-      "Epoch 19: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0125]\n"
+      "Epoch 15: 100%|██████████| 63/63 [00:30<00:00,  2.05it/s, loss=0.0129]\n",
+      "Epoch 16: 100%|██████████| 63/63 [00:30<00:00,  2.05it/s, loss=0.0132]\n",
+      "Epoch 17: 100%|██████████| 63/63 [00:30<00:00,  2.03it/s, loss=0.0123]\n",
+      "Epoch 18: 100%|██████████| 63/63 [00:31<00:00,  2.01it/s, loss=0.0121]\n",
+      "Epoch 19: 100%|██████████| 63/63 [00:31<00:00,  2.02it/s, loss=0.0126]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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owCExq1l0A8ja4g6BD4TzsHQ7nY5zZAOYyLTh1XudTkfO57NMp1MHNuQC8lpn1E3Xz9dfXCerriHjBJNov99LlmUuOoQ0Nq0KlRl/sZxXt6EOR20sqRWVwH/oe0mSuO3RILJ4QQ8GFtYpr7UFKKFUgzPu9/vCbxgL0C0BCvy2uBEDFvfneS5pmsrj46OMx2PZ7/fO54brOR2MxTPCgbvdzn3YLbLdbp17CJze2gKYv5ks3Yvvw5oVcGM2QDg1jaVPGQfk/z6d21fXq7poQqQ5EfQ7OEzh8mDxiUrDmIEI50ag09hgAcjAiQDG7XYrh8NB0jQt+MWYG6FTcYzLhz8Q1jLEPurZ6/VcVCVJEtnv925DS+hgXLc0TeVwODjjReRp+Sn3mf6N5/m4i+++x8dHl1WOD7igFuEAIYO/zAjS9dPl8XNfVByjsZiBsMTwVku4N+Aohm8Oyx/BLRFKw4BjwRKvkAMIOZkVoSpsx4YNhxC281nb4NDg0hg4cFN8wHXG47FTK+BLBAjxGY1GbkdW1m+zLHOTCdyRORZP6CbGI6TXMWA0ePmeMos3Vp/VdBUQckfCMoPO1e/3XYYK/G84jkU/p9PJLWCHqGagsuhFUgJ0L3DL1Wol2+1WNpuNrNdrORwODowc++Vvfga+GYSYQNBtp9OpnM9nB7TBYFAwTLC0AGVw/TabjdtAc7VaSZ7nslqtHFC126Sq1ck6pE+/Y6Dxt9YhtQHFz9DP47rGArFWxCRG4ecO4ARRkadll3DFICqBzYEAQnyDC8I6BUCsmQnxiSWU8Pnlee6SVhH/xbUAIaxgqA28W6q2JnkAB4OBAxru7ff7jtNx+5nTs+WN7YQh1gF8veovdmCtcYLLyRKxljeBgRc7Ca7qoilDt9UodCA4AKITSZI4Kxk7D4DbIZEAAfheryeHw8G5GJD/h8FkdwpHDfI8d5biarWS3W4ni8XCOZc5sA/qdrvO8MCzUR5Ay7osb4qeJIlMJhNnFOEDnRBOcT3YiNakaSqfP3+W3W4n9/f37h5IEnaCaw5k6ZLWWGEy+XZ2YMBZwNMGicUpq+qDIg2J47IHojPQgVrHgDXM26OBWz4+ProlkeCEfC+MGg6xoROwQxcMBhgSIuIGmeO+eBUswMjcVvvU8M3+Pt5rGsfhiAcAfKv4zuezTCYTp6qAW+u9Fvk+7ksNCF0+/9YAihlDJh8YrfMxdNH7jn3XWA3ThgDcBQABu2ygd0Ff3Gw20u12ZbPZyHg8ltlsJtPp1DmTuTwRcQ5lZMbAcMC2H/f3985gYZHHhhE+zCkxOfI8FxFxk4PTwaDnwh0zGAzkeDy65FjoiCgfgGe1YTgcSp7n8vXrV6dfwuKGu4qzpXkCoP90nVlPt9QLa+wsTodnWsfr6K4iL7BJpk+xxaxnHxpcNgCHznSBjsWbCHFHMaCPx6Nz4MJgwMuvMSDgmnDXsDrBYosjO+BQuJYd9KfTSQaDgXseg8HiiAgDjsfjwvICEMQk1wdtZ+OtDISYeKwycV00p9PfIS6qLesYigYh60ZWZcsU5jIFlzuYncytVstFANbrtXS7XZlMJjKZTGQ0GsmrV6+k1+vJq1evpNvtyng8di4d6JIcKmy1WvLXv/618BzojyB2KmPAtMUMAweDDs4EAwuWPiYWjA12F6EOvAMXchvh1snz3G2WBD0WIMYkTZKksHJQr7LzGSE8tgCOfnWFdk1p5zcDGWXp/X/KqLJh4rOOY6zmGFbNehcGFpEX+BZ3u51sNhsXs+V0dgw2klLhp4QRBL0vSRIHMIg8TiEDh+Pd9LmdHGvmnbbA0QFA1hN1pIQXTqFvAGAAN89zB2iAkLkwyoe/1Wck6Fg12oK+wQQFF0XfwMBiHydcSJyXyKlheMt9rGiu/G47n6Ib6zoIXWfNWIABIIRVhwFB9kuWZdLv9+X169cyGAzk7u7O6VnwQaJjEHIDx0SnsfEA0Q/iGDDXFaDHb3A++EXBEeB6ghsG7QEQOO6MOkHlmEwmTidkNYHBDhBigycGmPb9MRC1Lsi6MDg2+3rBETlEiv7h57FKUEa1XjWrxWoTAOTzlkEj8jTbIMJYRKdpKt1uV7Isk9FoJGmaOj8cRNXd3Z0DHEQ3+wTBYbh9GFBOmBB5WjiF3/BpYncvcGDWaTk8CE4D/VGHF0WeQI1rAQbmbuzigt4MdxbqDk7M36zLst7IHJBByL5OTATepYIljsgVFzr5gGhxQt8xq6wy0vdZIjHLMul2u7JYLCTLMtntdoUXGsIh3Ol0XOwXKf7QG/Esdvuwm4YNoPP5W/Iru5NYJ9PxWs4egnNeRNwAo2wMMixncGyoCdCTwcWhgoAToj0AvrZY9Zix8cWAYv0PfkqeDMwtwSiYA1axkmu5aGIcmbEVqQJGfQ/0K4iIVqvl8uk42wUcEZxwNps5YwYr7OCjA0jAYQAEJF5A5OHY6XRyxgbqBVEKvZM5EkJ9KIs5DQYbFjpELYAEzgXVAo57dvbDsEFb2AUTWryvxwzX8ZILbWVzFIy9CyJPXDeGar/5vS75XDTWNRaIQy4CnsmI0WJwOakWgwMHNvQocA4OrwFA+nksemAcsKtHc28MHICFtSzMZQFUNlIASP7Ah8qThCcNPlg5CKAw17L6lb81h+S+9YGa+6QK1c6sZqBoFq9nk75X/+ZjlojXPir9TP6go+DKAGCGw6G8e/fOWcbYcwbuGaSagYNisGEkcPSFn41zIsUdVjnacT6fnZsJrh5kZm82G1mtVgXVgjfQRM4iGzHQZ6EX86SAOO73+zIej73SiMHC3ExLPAaWjgZZ0jFJkkLGUgw1siGSD/0asPp3qEzrv8/N4HsmlHz81rOaPywO4RdDh4JDsRULwOtsEx2TxfNZhWDOBRDDykySpMAtWayh3Zyh7nPJsG5rWcI8ZprTijwBk/VgtrJ1n3Ob2RkeQ7WtY57VvIjJmiEWsQVocT0mLbK4E8B9tOXGKVnQoabTacFQgW/MeibK4QVY7Jhm35pVLwYC9Cfuu+l0WrDaOVVsNpu5Z7VaLZegC7HOvk7OztaTip3auu85xs715ZCcboc1PjxuPMFZRy6ji7YBwQDowQCxJ10TGmv5k/RM8+lNnNmCAeGYKnQwtoDBRXiQLTHPnYn26rbjN7gA64/6HgyIDt2Bs7Euipg5ykMd4CbBBOO6an0PdbcmGa9wtABqgdMizZi0lImlSmE7do9gMOEYhlKMRnLFWZfigeIwEcQLW1i6IZzjh8GB6EQkAV59WJwYzOFwKG/fvpVeryfT6dRZwLwikLNnAFAeYLhHdJRBW9IsuuAfRN9wXyIChH45nU6FnEaIZYg2vJyRdUCd88iTGtdqjsT+R4t7o46WaOfrtBhnLnwVPyE/GJ3A+X8slpnDMLeES4EbiUEACCA+9ezGgPLMZq/9drt16yt4ZR6ePxwO5fXr1y72zJyQOSTagA7nDuaJxY5oDCy+dfv5OgYEi3VMGLZw4e/jDBr2KbLRYBmBbOHiG6DmiYLx5XGBdLHENCYRP4c/KCeWKm+cjsqCgwwGA8dZtG7IAOOMY60wc4dyx+rMFFbIuVM4GUGHm/AMLFBiHyBboYjPYkkBOIr2hXFfcN0Kndp5eosUuBmrECyOUZblX2MQo/9QD2RgQ5Treun6AnhMHO/FvT49juPVLKEsThiyBSyqzAnxGx08Go2cIg2XAq5B58OBCnEH7sMNsiqvOSDAwilLcLXw4ELU8VJPHjCuI0CIiQLXB+9RyEo+142jDChPRJ45vTnCgfpBfdCchQ0GTDaIdKgyACEf02PFxPVjPZL7WBsk2u1igVuXxSC8ik4YUlQtEx+kV7ahcnonfauheqayRQ6xDbBw/JI7EL+hCjA3YmKVQYe8WNRoMYRnizzprAwWtJPVGVzLbeCYtWUcoRw4qTlCAkODjTIwAPQJj6EGkTWe1jENLIvbhbipjy4CIToZCrB20uJ6cBEklrLOwUmpumzWSzC4rL9BfIpIwXjQYhz3DwYDOZ/PhQXo5/O5UC4bMqweMOB8Igd15/N5nhfai/bzctEkKSZI4JnoNyyYarfb8ubNG0mSxIGP98Nht4gGvSU2fQyFmQIzAy2lQFol0WWWUe2ICUDFu1GJSAFQmIGsI0IZZwWYFW1uvLayoPMxYbazZQYwMohFnrtHfEDiCcRtYYWeSeuwHDnR5aCt7AXgicJl68Fncc8GkJ4oXCbu1yCypA8fY4PHApVVlu7HWIoGIacxiYjLLcNAgnuwONIdzgo6Gy1sQVoDBusbDmPueFjSAJWvM5LkyT2kQYVwmRaDurNFxD0TIhHcXEQKDnMGPFQBvhftAMFrgDbjXtSBQQb9WIcR9aTSQMPzdMZQmarFfSPyPBZt6YZXAaGuEKezI82dxSYGnbkbczsLhNpCZtcGLEMePPaTsVNZz2Yc59Qo5l6cJcLZ0doK5+czh8F5XItkBtQR9eRnaxGm64X+1mKPn1U20Bp8lg7u44QhfQ/fXD8+prlyGdUSx/hoXS/LskKH82CJ2BEUBhcDkZ2/bGmyM1brkJYLBYBnPyGc6zyjeY0JDwY4F+uu4ECYQNpYYA6lP2wwcFjQ4kCW3w3twXl+WTgDU6s3TBZXA/E93Id8rwaeVeerc0KuPAwBiDUt9li5tSxK5oz8YU4I1w9AyB2n9TFdTwwyVrCxm4cNE8xeiGbMeJ25zFwI50ajkXQ6Hbm7u3O+U/SB1h+5T9gIQD0ZWJrbWFa25kYMPv1sXQ++V+uNFgD5Xm4LY8ICfRnVipgwMcBwjnUsq7H8jQprfVCLMOZKIUUZ37iHFzUhvWi5XBYygH0cK0mKm3hioLS6sN1upd3+tgALaVbwjcLviLphnQyezYv8+aXb3D/spPbV2QKqFpvadYXrLeYC9Ub3sVVuSCLFUK0ln7ohzBW5Y0MzQoMQ9+IYA4Hjq1b2h+YYIuK4EcDC+h44NxtJHFZkboL28jZzqBvuQQyYv8fjsZzP39YSc38hisP6rO4T9KcOz2lRh7pzP2pdURs4mnP6OCvfw8eZw7IOyM++Ggg1e7b0L00+Hc3nb9LX86xMkufxTJ+owESAigCVAZYqxDEszPF47DJXdBIC6oBEV80J2VJlBzKH/bTzm9uLjxVtYK6vHey+iSgiz0DClr5l7Vr/tZqDZ2j9kMGPZ1xNJwyBUJM+F2qwFhWhsjWntJRnNm5EnqxOXpSD7OnJZFJ4uSKn+OuPNkz4G/qflUWDdcPWMgG0FRME6gIGGyFO7XO0JqGO5ujyfWLSAqUeL54UofFAO9DvsfRd1piU3WvNMj7Hv326G4tscCdEVTjCwqBDcisMHljgKIefrS1jnbqFOvDHSpZgzmFZr/o8dDbfxAUx0LSbB2oEkxbbunzt3tLn+Tcv5ocEsvJEfXTRhkjaVK8LVN9A+ABn+RJ5rS3reNhsCBspjUYjeffunXv5Nu/UgHUZcOkkSVLYq+Z0OhUWEuEa3QZMAACf9SiUxT5QPF9zc0wQfj8K640MFkSIGFyIUOldJFiP1IaF7nfLEOWoFIwtpM9hf3JsNDCdTkvH/+JXzfJ37PX4HcPlRIpuHPYjcuQBsVSOSACco9FIRqORe3Eip1mxz02XjUHQxoy25HU/8DHcp61NfZ+l43IYUn9QLoNSAxPXMQjRJoh5n27N7fdxXF76yXvWQH+PFcm1dUJuDDrD6mhfGZY41U5q/k6SYnSF/XewatnYANggfjE74c8DJ8MieGz3hnbAimVAa2ewbgPaxskR2mCAv1KHNkWe1rXgfryFVFuzAAiAKCIFjsdAZV1TT3o22lhk4xnoD+3Q1vVAubzzrU59C1EtTsgdziC0DBKLW3IDMIAsRvFBbJa/IaZ09jFACY4IfY93JOAVbhbHY8sOug0GgyMdzH10G1ltATDwn+vHwILYxH8OieqJy/XhPoU41mHI0+n0bIs51IeTT3TECJMDE0LrxyLFJRngrGgX172MKiUwcGew6GK9ihvC17DPDkBi5ZzDY7BUORzG3wwi7d9jVwuLbwYPb/vb6XTcrlx45QMbJnppJQ+Ejnuzhc33s5Tgd7loYLXb7WdZSafT6VkMHn3NgEdCCT68/gaJuSiXgcr/2Yjhyal1TW2ksOoBvRn68i+//NIcCHUME7+t2Ccr2BCjLD6hw1liGNyLV52Be+BbO3Ehshm4enZCxDIgINLw5iPmTsyhWcdipZ/3fIGohSHCnJ45LFuS7Xa7ILLwHH7FGut/uAahPT7PC7wANvxP01SOx6PbmZYnodY1dWRIh1eZfOIfGfSNc0Kt/2DQeV2G9t4DDAAWAAUQomMZjLxwCgmbWvfgZ4BYvLDVyRwB7yjGbMfEwKBzapJ2+TDXYnEKkcW6K+uPrNOhjqz34QPrEi/0YWOCI1K8loZ9gFjYxe9FwTfK461ReDKiXqgH+yWZS7J+yIYJc2cs2MJkjKHKYTt2jSBYj/iozpEDgHiNCa7l5Yy4FlwTHBDgZoNHi3w0FHoLMpB5rQkWPUEsYYB5hwOt/+A4czbm1gAS9EdwRm01a91XZx5BBDOAsOM/yuD647VnAA2AwduZAJD6vXvWUgsAh7d7A6dlUPI6G36uxTXRrliq7aLRM4OB5PsvIgWxpN0KaAyvcBMpJk/iGp2powddp8bzDqMoG++A47qBAD52vjK4WecFJ+x0Ok4c6iRV1l3BSaFzsRjFhu54YxVELQCKFz/y1m24BsCDaNbvUOHtOQA+gEpvBcwckT8MPm21a2Mrliov+RR5HuSGzhISmbrxuBeDypyClwCIPLkuQOzWYEAwgVPwPs8Qw1qHRb1Qf145yBY5QMSbE7EEwFuqdIQEXL3b7cqrV6/crq08WXa7nWRZJtvtVhaLhWy328KbnlikMqcCZ8Q7/fQLfLjdzNXwzcc0wLS3w8KC5RnQY19GtTkhuwFYf7HEMa7XFjaO8zEGBPQpjqnqZ7AOx8Trj7UuqHVM5sb4YCkBLFmRJ/BiEnBdRaQwkCxuYQBxG3QkA+KUX8QDqx1iWL9QkkHI74Rm8LHuptfYMPi0oYLfTBawtE6o/ZExVNlZzQore8q1AYHreWDZyaxdHyyOecsM7jz2uWGwwVE0d+OBAPewnK4oD64QfODYxtsAON6MdulkCZSJ+kFnZk6PPmLuDFVhtVpJlmXu/SX4Xi6XkmWZpGkqq9VK9vu9bDYbx0FZR+TJrjkaGxW+8eXflkvGd5++/7twQhatHF3QINT6GtKpEN6xQmDWC2x4RmvRDhAysc+ME0dRJncYc1hY/SJS0ANRT9br2HnN/jTWnZi4T9hw4rir/sYnyzLZbDbuhUDggMzlNbf1fes6hbwOMQD0tTGWamXR8MCxt12DTxNzRQt8+l7muvx8q1OZq6FePoesVqiZG6NuANpms5FOp+OSH3jbNohpAIr9floM83PO57Oz1AG4NE3l/v5ettutfPr0yb3jLssymc/nTi9k65i5u9U/ofELnS8Tw2UA0+NZRpVByAC0ZruupOVS0eKXz3HZloIcapgWPSyyWUxptxBHbthCB6fjWC9edAOOx7qhNtBCIgpGBAwS7NiK1+PiXS0Qwcvl0nHHEJfV/2P6Tut1ofOa9H1X5YS++DBXwGdNxYgBfb0lVmLYfxmIfR3KSjV+Qw2A7sf+QP0uFESOoAsifIc3CHC2NRtMm81GlsulrFYr+fLli2RZJh8+fHA6Id6JDA4YUv71JI4dB+ucLj/Ub/r6q3FCbQFZFYkBaNk1PiDH1M8Coq4//7YGgMU5xCn7A7Hbv4i4zZg4ggKgQazzZkucNgaDCZxvtVrJw8ODpGkqX758kd1uJw8PD5LnuYuk+Np9CfnAZ4ErxBH1uauK4xDxTKxzTUgkhMqLqWOIe/jOsxEE3yCcwa1Wy7mOADy97ph/Q3xCP12tVpKmqXz9+lXu7+9lsVjI58+fnZ8QLhpellCmy+ljIUDFUJkuGOrTq1rHdWceg08DUZ8DhUDF3KxMHeDyrNnK9+vnw7KGDgjjIEkS9yoyiGFY6ZyWxhwQYvh4PMrDw4Msl0v58uWLfP78Wb5+/Srv3793HBBRlJBOHNNeq/1lotd3zOpHq0+rUmMv03kpigWgiC2Sy4Bedh6GDGf2aKCwKwXhtdVqJYvFQhaLhTw8PDijhOO8ofbqY7HjETOx61Ld+yvnE4Ye6tMVLfKBIFYU1xXpPlHhm9EAomXtgttB7+OtTHAfYrKIX6/Xa9nv9/Lvf/9b5vO5fPz4UT5//uyc1Doj2dfHdVQXqy/KfofOV+WgPrp4jUkVTlSFmi7P94yYTmNup/MZ+RgDUOQpVImwGt4+D4t3vV67eDE4IPtEY3TsunRNSVbVTVPLOtYP8ukaTFU4XtMd79OjLD1VPxtOZ6zOw6IpXjCFpQQI7cGRjDhunucyn89lu93Kr7/+KpvNRj58+CCLxcJFQTiGfsnE5vZU8RXqMmKNEB/phJIQ1eKEMT6oqh1Yd9aXdUyZRVnmcmCxi1xCbXzwf87ugZMcxkyWZbJcLp1LBlxRb/x5LfreevzVXDTakgz5Da3/IaCxQ9y6J9SokDsipLtaFjHuabfbLmV/Op3KZDKR2Wwm0+nUrWXmRfQixXSpNE3l4eFBsiyT//73v84RjWQFZL5Yba5LTelpVcu4xB3UGCcMHQ9RyBcV2yANuKYGM0mSwutqsWcNoiD80hv4CjlGjVzA1Wrl4sIIv4EDNglAqw0i5ePyUlYx6KIlnzEdWGbFlj2Dy4htrM/vGHo2rofBgSTU2Wzm3loFfXA0GrnFWBwFwWez2bjEg//973+yXq/l/v6+kLoPJzQ/uwpdEhRomizJV0WHvCiVq+75kNJsGTkxYlg/NzQI+tlamUc+Yb/fd+C7u7tzIpiNEjiqOdt5vV7LYrGQL1++yIcPHxwgOcH2ewEk1G4+VodCE71K+y5+1Sxzwiq+q7KZUiUyUJWsiAF0QF52ymJ3OBy6XbzYRSMi7sU4WFJ5f38vDw8PMp/PZb1eO9HLCQjfi3ySoCmndRP6ZuO7csWI5pBLR4eDYtl6TFk+4hzC0WgkvV5PZrOZ2yBpMBjIbDaT2WxWWLiE7X2R7YxMaIThkJQAN8334oDaT1fF3VI3BHcJN7yYE9Z5aBVqSrexOh7/tQsGxghSsfBbv5YMUZA0TQsLkqAT4sWI2gn9eyWtZjWuE+pEUHwscQy6NKR0ibXt82XqmQ4LGM7oyWQig8FA3rx5I4PBQN69e+fSt3jBfp7ncn9/L7vdTj59+iTb7dZlQiP/D8suv4cI9rWtSfJxO9/xxjlhDLKrdHRVD3wZ1QEtuJrehAm6IH9ghPBuCLz2A7//iBzwUqoctuP/erZVMUz0dT4QVS0r5BjXdQXwxuOxc0C/fv3aWcVwzSAc1+12neW7WCzkP//5j+OAEMe8MdH3NkJ8jvemytNk6ZzAhLXxgY8a1QkvoaY5YygqAuKNmDgVn7Ni2BmN7Gqs9UACAlbAbbfbZ2ukX4qqGHSh6+qOSxV1oJJOqK1V34PK9DK+JnQu1tXj++/7jXoj+jEajWQymThHNL/tE22HBQzf33K5dBxws9m8GPezSHsfyixXHtM6YTdfubFU641OdSsaKyrrgK/KeYgLWMH8YSc0jBDEgdM0lfl8Lp8+fXILlLBREYfrXpIsADYBrKaNHKZa77bTnLAJN0oTHDK2DgAhNuRkcYvoB0JqDw8PIiLO8Tyfz2WxWLhNivSa5h+BNGdr0mtR9jzQVcRxzEMvnXFcdhUjJcRhrbIR7WAQwgeo1ylD3/v06ZMsFgtnmLD7xZeK/5LkA18TY9M0NcIJQWUVbMrxfC06n5+2RIN+h5VvACC2beMtSX5L9CP2/0WpXNpN49PzrIB5THivSl2qkM944PffId778eNHl44P3e+S7JfvSTGcq6k48SXuoYtSuazjTQ5ME+LdKhMf3iIX4MN/uFuwVwy/zf1HBx/TNfowRHWeUxmEvH9LmWFyqQERopBrpozAybCpJS9E4iWZvNn4bw18mixpZNGlYGVJ13jYznpQiGLdLL6ymhLXvvthUGA7DpFvmxRlWSb7/d6Bz7f9xh+JqgKzSvaTSM0dGLTst0JmlvNT/y6bkVxu1ZBgGUHvO5/PkmWZJElSeP0CUu//SOTLMqpy/3fjhHggk++B2nquExWpcl0VwkadvPXx7xF8TRsoTZdTixNqfbCKeI4JD8VY2Va9qlrVenfT35q75VJqSje0Ehmuah1b+63oCmiKCZI3QVWByC8V/L1xP6ZQfD/0u6wM6zjG4GogtLhflfCMiM0R9Qzy6Yx19cKQ9f69XBc/KlUJNuj7YnX6Mqr8WrEycWyx5DqiMmQ1x4hwq/4hN9KPHs1pguo6pkPJJqFrY58Xv2FIoGCfbqg5pnW/776m6fcOsEspxBHLxsM3ub+Ln5A5Y0zlfGJWJy2EXDJ1dI5Yn+XvkUL6YJmu6CM9XnUNElBlTggKNST2fqsMn84Zw0Fv5Kfv1Vd1QHjx/oT8cK0PWBWydEjLiW1xw6b0trq+yt8alTEKX7+XlYd7Q266KqBvbEMk3QDfNfyN63zi2XpuE8D0uRX+6FTXW3CpVKpsHfNvfhFOjO5mVZazWviDc3yNLh/nQjpJbGLFH4Ur+n5fql7hXh9nDFHt2DEewkDka0TC4MG39Q5dfZ/mgCGXkM/AwX99Txn9VkGpGYZ13PdtMQqLfP1clWpxQl/SglW5skH0XcON4t1PLYCGvq0yY/Se37reaOl4Pp3bujf2+Pl89qb3xVKl14r5KNQYSzzGVpJnp9YBy8DoKy/k/rGe/aM4s+tMhtj2xejo+Ob+4PHRQLzKntX8UhmIz9AKMw0ULRJQSX5LpQUunAt9+46FOtM67mvHj0DXqEeZOPXp2j51KHRdiCpvDZfneQHxeJg1sFaFMIPwmtaQYRKqB5fF92m1wWcI6bKapO+pc5Z5EULXhL5DuqJ1jO9nsRxDtV00ZdxK/7bK4LLKQKgNDj5uPTfU8WV1uwbFKvvXeFYd0rpjjPFR10BpfJPMG92oKtUO293oRk3RDYQ3enG6gfBGL043EN7oxekGwhu9ON1AeKMXpxsIb/TidAPhjV6cbiC80YvT/wEx6CDmBCe84AAAAABJRU5ErkJggg==\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -450,16 +449,16 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 20: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0121]\n",
-      "Epoch 21: 100%|███████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.012]\n",
-      "Epoch 22: 100%|██████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0116]\n",
-      "Epoch 23: 100%|███████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.012]\n",
-      "Epoch 24: 100%|███████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.012]\n"
+      "Epoch 20: 100%|██████████| 63/63 [00:30<00:00,  2.06it/s, loss=0.0122]\n",
+      "Epoch 21: 100%|██████████| 63/63 [00:30<00:00,  2.05it/s, loss=0.0122]\n",
+      "Epoch 22: 100%|███████████| 63/63 [00:31<00:00,  2.03it/s, loss=0.012]\n",
+      "Epoch 23: 100%|███████████| 63/63 [00:31<00:00,  2.02it/s, loss=0.012]\n",
+      "Epoch 24: 100%|██████████| 63/63 [00:31<00:00,  2.01it/s, loss=0.0119]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -471,16 +470,16 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 25: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0118]\n",
-      "Epoch 26: 100%|██████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0115]\n",
-      "Epoch 27: 100%|██████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0113]\n",
-      "Epoch 28: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0119]\n",
-      "Epoch 29: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0116]\n"
+      "Epoch 25: 100%|███████████| 63/63 [00:30<00:00,  2.05it/s, loss=0.012]\n",
+      "Epoch 26: 100%|██████████| 63/63 [00:30<00:00,  2.04it/s, loss=0.0112]\n",
+      "Epoch 27: 100%|██████████| 63/63 [00:31<00:00,  2.01it/s, loss=0.0112]\n",
+      "Epoch 28: 100%|██████████| 63/63 [00:31<00:00,  2.01it/s, loss=0.0117]\n",
+      "Epoch 29: 100%|██████████| 63/63 [00:31<00:00,  2.01it/s, loss=0.0116]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -492,16 +491,16 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 30: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0108]\n",
-      "Epoch 31: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0113]\n",
-      "Epoch 32: 100%|██████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0115]\n",
-      "Epoch 33: 100%|██████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0106]\n",
-      "Epoch 34: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0108]\n"
+      "Epoch 30: 100%|███████████| 63/63 [00:30<00:00,  2.05it/s, loss=0.011]\n",
+      "Epoch 31: 100%|██████████| 63/63 [00:30<00:00,  2.03it/s, loss=0.0113]\n",
+      "Epoch 32: 100%|██████████| 63/63 [00:31<00:00,  2.02it/s, loss=0.0116]\n",
+      "Epoch 33: 100%|██████████| 63/63 [00:31<00:00,  2.00it/s, loss=0.0104]\n",
+      "Epoch 34: 100%|██████████| 63/63 [00:31<00:00,  2.01it/s, loss=0.0109]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -513,16 +512,16 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 35: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0108]\n",
-      "Epoch 36: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0109]\n",
-      "Epoch 37: 100%|██████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0111]\n",
-      "Epoch 38: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0112]\n",
-      "Epoch 39: 100%|███████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.011]\n"
+      "Epoch 35: 100%|███████████| 63/63 [00:30<00:00,  2.04it/s, loss=0.011]\n",
+      "Epoch 36: 100%|██████████| 63/63 [00:30<00:00,  2.04it/s, loss=0.0109]\n",
+      "Epoch 37: 100%|██████████| 63/63 [00:31<00:00,  2.02it/s, loss=0.0109]\n",
+      "Epoch 38: 100%|██████████| 63/63 [00:31<00:00,  2.01it/s, loss=0.0111]\n",
+      "Epoch 39: 100%|██████████| 63/63 [00:31<00:00,  2.00it/s, loss=0.0109]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -534,16 +533,16 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 40: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.011]\n",
-      "Epoch 41: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0107]\n",
-      "Epoch 42: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0103]\n",
-      "Epoch 43: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0109]\n",
-      "Epoch 44: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0111]\n"
+      "Epoch 40: 100%|███████████| 63/63 [00:30<00:00,  2.05it/s, loss=0.011]\n",
+      "Epoch 41: 100%|██████████| 63/63 [00:31<00:00,  2.01it/s, loss=0.0105]\n",
+      "Epoch 42: 100%|██████████| 63/63 [00:31<00:00,  2.01it/s, loss=0.0103]\n",
+      "Epoch 43: 100%|██████████| 63/63 [00:31<00:00,  2.01it/s, loss=0.0108]\n",
+      "Epoch 44: 100%|██████████| 63/63 [00:31<00:00,  1.99it/s, loss=0.0111]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -555,16 +554,16 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 45: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0101]\n",
-      "Epoch 46: 100%|█████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.00981]\n",
-      "Epoch 47: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0112]\n",
-      "Epoch 48: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0102]\n",
-      "Epoch 49: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0106]\n"
+      "Epoch 45: 100%|██████████| 63/63 [00:30<00:00,  2.05it/s, loss=0.0101]\n",
+      "Epoch 46: 100%|█████████| 63/63 [00:30<00:00,  2.04it/s, loss=0.00971]\n",
+      "Epoch 47: 100%|██████████| 63/63 [00:31<00:00,  2.01it/s, loss=0.0111]\n",
+      "Epoch 48: 100%|██████████| 63/63 [00:31<00:00,  2.01it/s, loss=0.0102]\n",
+      "Epoch 49: 100%|██████████| 63/63 [00:31<00:00,  2.01it/s, loss=0.0106]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -576,7 +575,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "train completed, total time: 2216.377239704132.\n"
+      "train completed, total time: 1794.846744298935.\n"
      ]
     }
    ],
@@ -675,7 +674,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 800x550 with 1 Axes>"
       ]
@@ -712,19 +711,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|█████████████████████████████| 1000/1000 [00:17<00:00, 57.90it/s]\n"
+      "100%|█████████████████████████████| 1000/1000 [00:15<00:00, 65.13it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -771,7 +770,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
diff --git a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py
index 19621569..d06d17eb 100644
--- a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py
+++ b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py
@@ -165,10 +165,9 @@
     spatial_dims=2,
     in_channels=1,
     out_channels=1,
-    model_channels=64,
-    attention_resolutions=[2, 4],
+    block_out_channels=(64, 128, 128),
+    attention_levels=(False, False, True),
     num_res_blocks=1,
-    channel_mult=[1, 2, 2],
     num_heads=1,
 )
 model.to(device)

From 33c5a36166e161c2e13194b0dafa32b263053c1f Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Wed, 9 Nov 2022 18:55:21 +0000
Subject: [PATCH 08/28] Rename parameters (#53)

---
 .../networks/nets/diffusion_model_unet.py     | 343 +++++++++---------
 tests/test_diffusion_model_unet.py            |  87 +++--
 2 files changed, 239 insertions(+), 191 deletions(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index 037cfa8c..aadce28c 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -30,7 +30,7 @@
 # =========================================================================
 
 import math
-from typing import Optional, Sequence, Tuple
+from typing import Any, Optional, Sequence, Tuple
 
 import torch
 import torch.nn.functional as F
@@ -65,7 +65,7 @@ class FeedForward(nn.Module):
     A feed-forward layer.
 
     Args:
-        dim: number of channels in the input.
+        num_channels: number of channels in the input.
         dim_out: number of channels in the output. If not given, defaults to `dim`.
         mult: multiplier to use for the hidden dimension.
         glu: whether to use GLU activation.
@@ -73,12 +73,14 @@ class FeedForward(nn.Module):
     """
 
     def __init__(
-        self, dim: int, dim_out: Optional[int] = None, mult: int = 4, glu: bool = False, dropout: float = 0.0
+        self, num_channels: int, dim_out: Optional[int] = None, mult: int = 4, glu: bool = False, dropout: float = 0.0
     ) -> None:
         super().__init__()
-        inner_dim = int(dim * mult)
-        dim_out = dim_out if dim_out is not None else dim
-        project_in = nn.Sequential(nn.Linear(dim, inner_dim), nn.GELU()) if not glu else GEGLU(dim, inner_dim)
+        inner_dim = int(num_channels * mult)
+        dim_out = dim_out if dim_out is not None else num_channels
+        project_in = (
+            nn.Sequential(nn.Linear(num_channels, inner_dim), nn.GELU()) if not glu else GEGLU(num_channels, inner_dim)
+        )
 
         self.net = nn.Sequential(project_in, nn.Dropout(dropout), nn.Linear(inner_dim, dim_out))
 
@@ -92,30 +94,30 @@ class CrossAttention(nn.Module):
 
     Args:
         query_dim: number of channels in the query.
-        context_dim: number of channels in the context.
-        heads: number of heads to use for multi-head attention.
-        dim_head: number of channels in each head.
+        cross_attention_dim: number of channels in the context.
+        num_attention_heads: number of heads to use for multi-head attention.
+        attention_head_dim: number of channels in each head.
         dropout: dropout probability to use.
     """
 
     def __init__(
         self,
         query_dim: int,
-        context_dim: Optional[int] = None,
-        heads: int = 8,
-        dim_head: int = 64,
+        cross_attention_dim: Optional[int] = None,
+        num_attention_heads: int = 8,
+        attention_head_dim: int = 64,
         dropout: float = 0.0,
     ) -> None:
         super().__init__()
-        inner_dim = dim_head * heads
-        context_dim = context_dim if context_dim is not None else query_dim
+        inner_dim = attention_head_dim * num_attention_heads
+        cross_attention_dim = cross_attention_dim if cross_attention_dim is not None else query_dim
 
-        self.scale = dim_head**-0.5
-        self.heads = heads
+        self.scale = attention_head_dim**-0.5
+        self.heads = num_attention_heads
 
         self.to_q = nn.Linear(query_dim, inner_dim, bias=False)
-        self.to_k = nn.Linear(context_dim, inner_dim, bias=False)
-        self.to_v = nn.Linear(context_dim, inner_dim, bias=False)
+        self.to_k = nn.Linear(cross_attention_dim, inner_dim, bias=False)
+        self.to_v = nn.Linear(cross_attention_dim, inner_dim, bias=False)
 
         self.to_out = nn.Sequential(nn.Linear(inner_dim, query_dim), nn.Dropout(dropout))
 
@@ -139,7 +141,7 @@ def forward(self, x: torch.Tensor, context: Optional[torch.Tensor] = None) -> to
         key = self.to_k(context)
         value = self.to_v(context)
 
-        # TODO: make use of xformers to improve attention speed
+        # TODO: Maybe make use of xformers to improve attention speed
         query = self.reshape_heads_to_batch_dim(query)
         key = self.reshape_heads_to_batch_dim(key)
         value = self.reshape_heads_to_batch_dim(value)
@@ -158,34 +160,41 @@ class BasicTransformerBlock(nn.Module):
     A basic Transformer block.
 
     Args:
-        dim: number of channels in the input and output.
-        n_heads: number of heads to use for multi-head attention.
-        d_head: number of channels in each head.
+        num_channels: number of channels in the input and output.
+        num_attention_heads: number of heads to use for multi-head attention.
+        attention_head_dim: number of channels in each head.
         dropout: dropout probability to use.
-        context_dim: size of the context vector for cross attention.
+        cross_attention_dim: size of the context vector for cross attention.
         gated_ff: whether to use a gated feed-forward network.
     """
 
     def __init__(
         self,
-        dim: int,
-        n_heads: int,
-        d_head: int,
+        num_channels: int,
+        num_attention_heads: int,
+        attention_head_dim: int,
         dropout: float = 0.0,
-        context_dim: Optional[int] = None,
+        cross_attention_dim: Optional[int] = None,
         gated_ff: bool = True,
     ) -> None:
         super().__init__()
         self.attn1 = CrossAttention(
-            query_dim=dim, heads=n_heads, dim_head=d_head, dropout=dropout
+            query_dim=num_channels,
+            num_attention_heads=num_attention_heads,
+            attention_head_dim=attention_head_dim,
+            dropout=dropout,
         )  # is a self-attention
-        self.ff = FeedForward(dim, dropout=dropout, glu=gated_ff)
+        self.ff = FeedForward(num_channels, dropout=dropout, glu=gated_ff)
         self.attn2 = CrossAttention(
-            query_dim=dim, context_dim=context_dim, heads=n_heads, dim_head=d_head, dropout=dropout
+            query_dim=num_channels,
+            cross_attention_dim=cross_attention_dim,
+            num_attention_heads=num_attention_heads,
+            attention_head_dim=attention_head_dim,
+            dropout=dropout,
         )  # is a self-attention if context is None
-        self.norm1 = nn.LayerNorm(dim)
-        self.norm2 = nn.LayerNorm(dim)
-        self.norm3 = nn.LayerNorm(dim)
+        self.norm1 = nn.LayerNorm(num_channels)
+        self.norm2 = nn.LayerNorm(num_channels)
+        self.norm3 = nn.LayerNorm(num_channels)
 
     def forward(self, x: torch.Tensor, context: Optional[torch.Tensor] = None) -> torch.Tensor:
         x = self.attn1(self.norm1(x)) + x
@@ -211,31 +220,31 @@ class SpatialTransformer(nn.Module):
     Args:
         spatial_dims: number of spatial dimensions.
         in_channels: number of channels in the input and output.
-        n_heads: number of heads to use for multi-head attention.
-        d_head: number of channels in each head.
-        depth: number of layers of Transformer blocks to use.
+        num_attention_heads: number of heads to use for multi-head attention.
+        attention_head_dim: number of channels in each head.
+        num_layers: number of layers of Transformer blocks to use.
         dropout: dropout probability to use.
         norm_num_groups: number of groups for the normalization.
         norm_eps: epsilon for the normalization.
-        context_dim: number of context dimensions to use.
+        cross_attention_dim: number of context dimensions to use.
     """
 
     def __init__(
         self,
         spatial_dims: int,
         in_channels: int,
-        n_heads: int,
-        d_head: int,
-        depth: int = 1,
+        num_attention_heads: int,
+        attention_head_dim: int,
+        num_layers: int = 1,
         dropout: float = 0.0,
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
-        context_dim: Optional[int] = None,
+        cross_attention_dim: Optional[int] = None,
     ) -> None:
         super().__init__()
         self.spatial_dims = spatial_dims
         self.in_channels = in_channels
-        inner_dim = n_heads * d_head
+        inner_dim = num_attention_heads * attention_head_dim
         self.norm = nn.GroupNorm(num_groups=norm_num_groups, num_channels=in_channels, eps=norm_eps, affine=True)
 
         self.proj_in = Convolution(
@@ -251,9 +260,13 @@ def __init__(
         self.transformer_blocks = nn.ModuleList(
             [
                 BasicTransformerBlock(
-                    dim=inner_dim, n_heads=n_heads, d_head=d_head, dropout=dropout, context_dim=context_dim
+                    num_channels=inner_dim,
+                    num_attention_heads=num_attention_heads,
+                    attention_head_dim=attention_head_dim,
+                    dropout=dropout,
+                    cross_attention_dim=cross_attention_dim,
                 )
-                for _ in range(depth)
+                for _ in range(num_layers)
             ]
         )
 
@@ -302,18 +315,18 @@ class QKVAttentionLegacy(nn.Module):
     A qkv attention mechanism.
 
     Args:
-        n_heads: number of attention heads.
+        num_attention_heads: number of attention heads.
     """
 
-    def __init__(self, n_heads: int) -> None:
+    def __init__(self, num_attention_heads: int) -> None:
         super().__init__()
-        self.n_heads = n_heads
+        self.num_attention_heads = num_attention_heads
 
     def forward(self, qkv: torch.Tensor) -> torch.Tensor:
         bs, width, length = qkv.shape
-        assert width % (3 * self.n_heads) == 0
-        ch = width // (3 * self.n_heads)
-        q, k, v = qkv.reshape(bs * self.n_heads, ch * 3, length).split(ch, dim=1)
+        assert width % (3 * self.num_attention_heads) == 0
+        ch = width // (3 * self.num_attention_heads)
+        q, k, v = qkv.reshape(bs * self.num_attention_heads, ch * 3, length).split(ch, dim=1)
         scale = 1 / math.sqrt(math.sqrt(ch))
         weight = torch.einsum("bct,bcs->bts", q * scale, k * scale)  # More stable with f16 than dividing afterwards
         weight = torch.softmax(weight.float(), dim=-1).type(weight.dtype)
@@ -326,35 +339,35 @@ class AttentionBlock(nn.Module):
     An attention block.
 
     Args:
-        channels: number of channels in the input and output.
-        num_heads:  number of attention heads.
-        num_head_channels: number of channels in each head.
+        num_channels: number of channels in the input and output.
+        num_attention_heads:  number of attention heads.
+        attention_head_dim: number of channels in each head.
         norm_num_groups: number of groups to use for group norm.
         norm_eps: epsilon value to use for group norm.
     """
 
     def __init__(
         self,
-        channels: int,
-        num_heads: int = 1,
-        num_head_channels: int = -1,
+        num_channels: int,
+        num_attention_heads: int = 1,
+        attention_head_dim: int = -1,
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
     ) -> None:
         super().__init__()
-        self.channels = channels
-        if num_head_channels == -1:
-            self.num_heads = num_heads
+        self.channels = num_channels
+        if attention_head_dim == -1:
+            self.num_heads = num_attention_heads
         else:
             assert (
-                channels % num_head_channels == 0
-            ), f"q,k,v channels {channels} is not divisible by num_head_channels {num_head_channels}"
-            self.num_heads = channels // num_head_channels
-        self.norm = nn.GroupNorm(num_groups=norm_num_groups, num_channels=channels, eps=norm_eps, affine=True)
-        self.qkv = nn.Conv1d(channels, channels * 3, 1)
+                num_channels % attention_head_dim == 0
+            ), f"q,k,v channels {num_channels} is not divisible by attention_head_dim {attention_head_dim}"
+            self.num_heads = num_channels // attention_head_dim
+        self.norm = nn.GroupNorm(num_groups=norm_num_groups, num_channels=num_channels, eps=norm_eps, affine=True)
+        self.qkv = nn.Conv1d(num_channels, num_channels * 3, 1)
         self.attention = QKVAttentionLegacy(self.num_heads)
 
-        self.proj_out = zero_module(nn.Conv1d(channels, channels, 1))
+        self.proj_out = zero_module(nn.Conv1d(num_channels, num_channels, 1))
 
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         b, c, *spatial = x.shape
@@ -396,7 +409,7 @@ class Downsample(nn.Module):
 
     Args:
         spatial_dims: number of spatial dimensions.
-        channels: number of input channels.
+        num_channels: number of input channels.
         use_conv: if True uses Convolution instead of Pool average to perform downsampling.
         out_channels: number of output channels.
         padding: controls the amount of implicit zero-paddings on both sides for padding number of points
@@ -406,19 +419,19 @@ class Downsample(nn.Module):
     def __init__(
         self,
         spatial_dims: int,
-        channels: int,
+        num_channels: int,
         use_conv: bool,
         out_channels: Optional[int] = None,
         padding: int = 1,
     ) -> None:
         super().__init__()
-        self.channels = channels
-        self.out_channels = out_channels or channels
+        self.num_channels = num_channels
+        self.out_channels = out_channels or num_channels
         self.use_conv = use_conv
         if use_conv:
             self.op = Convolution(
                 spatial_dims=spatial_dims,
-                in_channels=self.channels,
+                in_channels=self.num_channels,
                 out_channels=self.out_channels,
                 strides=2,
                 kernel_size=3,
@@ -426,11 +439,11 @@ def __init__(
                 conv_only=True,
             )
         else:
-            assert self.channels == self.out_channels
+            assert self.num_channels == self.out_channels
             self.op = Pool[Pool.AVG, spatial_dims](kernel_size=2, stride=2)
 
     def forward(self, x: torch.Tensor) -> torch.Tensor:
-        assert x.shape[1] == self.channels
+        assert x.shape[1] == self.num_channels
         return self.op(x)
 
 
@@ -440,7 +453,7 @@ class Upsample(nn.Module):
 
     Args:
         spatial_dims: number of spatial dimensions.
-        channels: number of input channels
+        num_channels: number of input channels
         use_conv: if True uses Convolution instead of Pool average to perform downsampling.
         out_channels: number of output channels.
         padding: controls the amount of implicit zero-paddings on both sides for padding number of points for each
@@ -450,19 +463,19 @@ class Upsample(nn.Module):
     def __init__(
         self,
         spatial_dims: int,
-        channels: int,
+        num_channels: int,
         use_conv: bool,
         out_channels: Optional[int] = None,
         padding: int = 1,
     ) -> None:
         super().__init__()
-        self.channels = channels
-        self.out_channels = out_channels or channels
+        self.num_channels = num_channels
+        self.out_channels = out_channels or num_channels
         self.use_conv = use_conv
         if use_conv:
             self.conv = Convolution(
                 spatial_dims=spatial_dims,
-                in_channels=self.channels,
+                in_channels=self.num_channels,
                 out_channels=self.out_channels,
                 strides=1,
                 kernel_size=3,
@@ -471,7 +484,7 @@ def __init__(
             )
 
     def forward(self, x: torch.Tensor) -> torch.Tensor:
-        assert x.shape[1] == self.channels
+        assert x.shape[1] == self.num_channels
         x = F.interpolate(x, scale_factor=2.0, mode="nearest")
         if self.use_conv:
             x = self.conv(x)
@@ -592,27 +605,27 @@ def forward(self, x: torch.Tensor, emb: torch.Tensor) -> torch.Tensor:
 
 
 def get_attention_parameters(
-    ch: int, num_head_channels: int, num_heads: int, legacy: bool, with_conditioning: bool
+    num_channels: int, attention_head_dim: int, num_attention_heads: int, legacy: bool, with_conditioning: bool
 ) -> Tuple[int, int]:
     """
     Get the number of attention heads and their dimensions depending on the model parameters.
 
     Args:
-        ch: number of channels.
-        num_head_channels: number of channels in each head.
-        num_heads: number of attention heads.
+        num_channels: number of channels.
+        attention_head_dim: number of channels in each head.
+        num_attention_heads: number of attention heads.
         legacy: if True, use legacy way to compute dim_head for attention blocks.
         with_conditioning: if true together with legacy, use ch // num_heads as head dimension.
 
     """
-    if num_head_channels == -1:
-        dim_head = ch // num_heads
+    if attention_head_dim == -1:
+        dim_head = num_channels // num_attention_heads
     else:
-        num_heads = ch // num_head_channels
-        dim_head = num_head_channels
+        num_attention_heads = num_channels // attention_head_dim
+        dim_head = attention_head_dim
     if legacy:
-        dim_head = ch // num_heads if with_conditioning else num_head_channels
-    return dim_head, num_heads
+        dim_head = num_channels // num_attention_heads if with_conditioning else attention_head_dim
+    return dim_head, num_attention_heads
 
 
 class DownBlock(nn.Module):
@@ -649,7 +662,7 @@ def __init__(
         if add_downsample:
             self.downsampler = Downsample(
                 spatial_dims=spatial_dims,
-                channels=out_channels,
+                num_channels=out_channels,
                 use_conv=True,
                 out_channels=out_channels,
                 padding=downsample_padding,
@@ -659,7 +672,7 @@ def __init__(
 
     def forward(
         self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
-    ) -> Tuple[torch.Tensor, Tuple[torch.Tensor, ...]]:
+    ) -> Tuple[torch.Tensor, Any]:
         output_states = ()
 
         for resnet in self.resnets:
@@ -685,8 +698,8 @@ def __init__(
         norm_eps: float = 1e-6,
         add_downsample: bool = True,
         downsample_padding: int = 1,
-        num_heads: int = 1,
-        num_head_channels: int = 1,
+        num_attention_heads: int = 1,
+        attention_head_dim: int = 1,
     ) -> None:
         super().__init__()
         resnets = []
@@ -706,9 +719,9 @@ def __init__(
             )
             attentions.append(
                 AttentionBlock(
-                    channels=out_channels,
-                    num_heads=num_heads,
-                    num_head_channels=num_head_channels,
+                    num_channels=out_channels,
+                    num_attention_heads=num_attention_heads,
+                    attention_head_dim=attention_head_dim,
                     norm_num_groups=norm_num_groups,
                     norm_eps=norm_eps,
                 )
@@ -720,7 +733,7 @@ def __init__(
         if add_downsample:
             self.downsampler = Downsample(
                 spatial_dims=spatial_dims,
-                channels=out_channels,
+                num_channels=out_channels,
                 use_conv=True,
                 out_channels=out_channels,
                 padding=downsample_padding,
@@ -730,7 +743,7 @@ def __init__(
 
     def forward(
         self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
-    ) -> Tuple[torch.Tensor, Tuple[torch.Tensor, ...]]:
+    ) -> Tuple[torch.Tensor, Any]:
         output_states = ()
 
         for resnet, attn in zip(self.resnets, self.attentions):
@@ -757,8 +770,8 @@ def __init__(
         norm_eps: float = 1e-6,
         add_downsample: bool = True,
         downsample_padding: int = 1,
-        num_heads: int = 1,
-        num_head_channels: int = 1,
+        num_attention_heads: int = 1,
+        attention_head_dim: int = 1,
         transformer_num_layers: int = 1,
         cross_attention_dim: Optional[int] = None,
     ) -> None:
@@ -783,12 +796,12 @@ def __init__(
                 SpatialTransformer(
                     spatial_dims=spatial_dims,
                     in_channels=out_channels,
-                    n_heads=num_heads,
-                    d_head=num_head_channels,
-                    depth=transformer_num_layers,
+                    num_attention_heads=num_attention_heads,
+                    attention_head_dim=attention_head_dim,
+                    num_layers=transformer_num_layers,
                     norm_num_groups=norm_num_groups,
                     norm_eps=norm_eps,
-                    context_dim=cross_attention_dim,
+                    cross_attention_dim=cross_attention_dim,
                 )
             )
 
@@ -798,7 +811,7 @@ def __init__(
         if add_downsample:
             self.downsampler = Downsample(
                 spatial_dims=spatial_dims,
-                channels=out_channels,
+                num_channels=out_channels,
                 use_conv=True,
                 out_channels=out_channels,
                 padding=downsample_padding,
@@ -808,7 +821,7 @@ def __init__(
 
     def forward(
         self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
-    ) -> Tuple[torch.Tensor, Tuple[torch.Tensor, ...]]:
+    ) -> Tuple[torch.Tensor, Any]:
         output_states = ()
 
         for resnet, attn in zip(self.resnets, self.attentions):
@@ -831,8 +844,8 @@ def __init__(
         temb_channels: int,
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
-        num_heads: int = 1,
-        num_head_channels: int = 1,
+        num_attention_heads: int = 1,
+        attention_head_dim: int = 1,
     ) -> None:
         super().__init__()
         self.attention = None
@@ -846,9 +859,9 @@ def __init__(
             norm_eps=norm_eps,
         )
         self.attention = AttentionBlock(
-            channels=in_channels,
-            num_heads=num_heads,
-            num_head_channels=num_head_channels,
+            num_channels=in_channels,
+            num_attention_heads=num_attention_heads,
+            attention_head_dim=attention_head_dim,
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
         )
@@ -880,8 +893,8 @@ def __init__(
         temb_channels: int,
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
-        num_heads: int = 1,
-        num_head_channels: int = 1,
+        num_attention_heads: int = 1,
+        attention_head_dim: int = 1,
         transformer_num_layers: int = 1,
         cross_attention_dim: Optional[int] = None,
     ) -> None:
@@ -899,12 +912,12 @@ def __init__(
         self.attention = SpatialTransformer(
             spatial_dims=spatial_dims,
             in_channels=in_channels,
-            n_heads=num_heads,
-            d_head=num_head_channels,
-            depth=transformer_num_layers,
+            num_attention_heads=num_attention_heads,
+            attention_head_dim=attention_head_dim,
+            num_layers=transformer_num_layers,
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
-            context_dim=cross_attention_dim,
+            cross_attention_dim=cross_attention_dim,
         )
         self.resnet_2 = ResnetBlock(
             spatial_dims=spatial_dims,
@@ -960,7 +973,7 @@ def __init__(
 
         if add_upsample:
             self.upsampler = Upsample(
-                spatial_dims=spatial_dims, channels=out_channels, use_conv=True, out_channels=out_channels
+                spatial_dims=spatial_dims, num_channels=out_channels, use_conv=True, out_channels=out_channels
             )
         else:
             self.upsampler = None
@@ -998,8 +1011,8 @@ def __init__(
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
         add_upsample: bool = True,
-        num_heads: int = 1,
-        num_head_channels: int = 1,
+        num_attention_heads: int = 1,
+        attention_head_dim: int = 1,
     ) -> None:
         super().__init__()
         resnets = []
@@ -1021,9 +1034,9 @@ def __init__(
             )
             attentions.append(
                 AttentionBlock(
-                    channels=out_channels,
-                    num_heads=num_heads,
-                    num_head_channels=num_head_channels,
+                    num_channels=out_channels,
+                    num_attention_heads=num_attention_heads,
+                    attention_head_dim=attention_head_dim,
                     norm_num_groups=norm_num_groups,
                     norm_eps=norm_eps,
                 )
@@ -1034,7 +1047,7 @@ def __init__(
 
         if add_upsample:
             self.upsampler = Upsample(
-                spatial_dims=spatial_dims, channels=out_channels, use_conv=True, out_channels=out_channels
+                spatial_dims=spatial_dims, num_channels=out_channels, use_conv=True, out_channels=out_channels
             )
         else:
             self.upsampler = None
@@ -1073,8 +1086,8 @@ def __init__(
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
         add_upsample: bool = True,
-        num_heads: int = 1,
-        num_head_channels: int = 1,
+        num_attention_heads: int = 1,
+        attention_head_dim: int = 1,
         transformer_num_layers: int = 1,
         cross_attention_dim: Optional[int] = None,
     ) -> None:
@@ -1100,12 +1113,12 @@ def __init__(
                 SpatialTransformer(
                     spatial_dims=spatial_dims,
                     in_channels=out_channels,
-                    n_heads=num_heads,
-                    d_head=num_head_channels,
+                    num_attention_heads=num_attention_heads,
+                    attention_head_dim=attention_head_dim,
                     norm_num_groups=norm_num_groups,
                     norm_eps=norm_eps,
-                    depth=transformer_num_layers,
-                    context_dim=cross_attention_dim,
+                    num_layers=transformer_num_layers,
+                    cross_attention_dim=cross_attention_dim,
                 )
             )
 
@@ -1114,7 +1127,7 @@ def __init__(
 
         if add_upsample:
             self.upsampler = Upsample(
-                spatial_dims=spatial_dims, channels=out_channels, use_conv=True, out_channels=out_channels
+                spatial_dims=spatial_dims, num_channels=out_channels, use_conv=True, out_channels=out_channels
             )
         else:
             self.upsampler = None
@@ -1152,8 +1165,8 @@ def get_down_block(
     add_downsample: bool,
     with_attn: bool,
     with_cross_attn: bool,
-    num_heads: int,
-    num_head_channels: int,
+    num_attention_heads: int,
+    attention_head_dim: int,
     transformer_num_layers: int,
     cross_attention_dim: Optional[int],
 ) -> nn.Module:
@@ -1167,8 +1180,8 @@ def get_down_block(
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
             add_downsample=add_downsample,
-            num_heads=num_heads,
-            num_head_channels=num_head_channels,
+            num_attention_heads=num_attention_heads,
+            attention_head_dim=attention_head_dim,
         )
     elif with_cross_attn:
         return CrossAttnDownBlock(
@@ -1180,8 +1193,8 @@ def get_down_block(
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
             add_downsample=add_downsample,
-            num_heads=num_heads,
-            num_head_channels=num_head_channels,
+            num_attention_heads=num_attention_heads,
+            attention_head_dim=attention_head_dim,
             transformer_num_layers=transformer_num_layers,
             cross_attention_dim=cross_attention_dim,
         )
@@ -1205,8 +1218,8 @@ def get_mid_block(
     norm_num_groups: int,
     norm_eps: float,
     with_conditioning: bool,
-    num_heads: int,
-    num_head_channels: int,
+    num_attention_heads: int,
+    attention_head_dim: int,
     transformer_num_layers: int,
     cross_attention_dim: Optional[int],
 ) -> nn.Module:
@@ -1217,8 +1230,8 @@ def get_mid_block(
             temb_channels=temb_channels,
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
-            num_heads=num_heads,
-            num_head_channels=num_head_channels,
+            num_attention_heads=num_attention_heads,
+            attention_head_dim=attention_head_dim,
             transformer_num_layers=transformer_num_layers,
             cross_attention_dim=cross_attention_dim,
         )
@@ -1229,8 +1242,8 @@ def get_mid_block(
             temb_channels=temb_channels,
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
-            num_heads=num_heads,
-            num_head_channels=num_head_channels,
+            num_attention_heads=num_attention_heads,
+            attention_head_dim=attention_head_dim,
         )
 
 
@@ -1246,8 +1259,8 @@ def get_up_block(
     add_upsample: bool,
     with_attn: bool,
     with_cross_attn: bool,
-    num_heads: int,
-    num_head_channels: int,
+    num_attention_heads: int,
+    attention_head_dim: int,
     transformer_num_layers: int,
     cross_attention_dim: Optional[int],
 ) -> nn.Module:
@@ -1262,8 +1275,8 @@ def get_up_block(
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
             add_upsample=add_upsample,
-            num_heads=num_heads,
-            num_head_channels=num_head_channels,
+            num_attention_heads=num_attention_heads,
+            attention_head_dim=attention_head_dim,
         )
     elif with_cross_attn:
         return CrossAttnUpBlock(
@@ -1276,8 +1289,8 @@ def get_up_block(
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
             add_upsample=add_upsample,
-            num_heads=num_heads,
-            num_head_channels=num_head_channels,
+            num_attention_heads=num_attention_heads,
+            attention_head_dim=attention_head_dim,
             transformer_num_layers=transformer_num_layers,
             cross_attention_dim=cross_attention_dim,
         )
@@ -1315,7 +1328,7 @@ class DiffusionModelUNet(nn.Module):
         legacy: if True, use legacy way to compute dim_head for attention blocks.
         with_conditioning: if True add spatial transformers to perform conditioning.
         transformer_num_layers: number of layers of Transformer blocks to use.
-        context_dim: number of context dimensions to use.
+        cross_attention_dim: number of context dimensions to use.
     """
 
     def __init__(
@@ -1333,18 +1346,20 @@ def __init__(
         legacy: bool = True,
         with_conditioning: bool = False,
         transformer_num_layers: int = 1,
-        context_dim: Optional[int] = None,
+        cross_attention_dim: Optional[int] = None,
     ) -> None:
         super().__init__()
-        if with_conditioning is True and context_dim is None:
+        if with_conditioning is True and cross_attention_dim is None:
             raise ValueError(
                 (
-                    "DiffusionModelUNet expects dimension of the cross-attention conditioning (context_dim) when using "
-                    "with_conditioning."
+                    "DiffusionModelUNet expects dimension of the cross-attention conditioning (cross_attention_dim) when"
+                    " using with_conditioning."
                 )
             )
-        if context_dim is not None and with_conditioning is False:
-            raise ValueError("DiffusionModelUNet expects use_spatial_transformer=True when specifying the context_dim.")
+        if cross_attention_dim is not None and with_conditioning is False:
+            raise ValueError(
+                "DiffusionModelUNet expects use_spatial_transformer=True when specifying the " "cross_attention_dim."
+            )
 
         if num_heads == -1 and num_head_channels == -1:
             raise ValueError("DiffusionModelUNet expects that either num_heads or num_head_channels has to be set.")
@@ -1403,10 +1418,10 @@ def __init__(
                 add_downsample=not is_final_block,
                 with_attn=(attention_levels[i] and not with_conditioning),
                 with_cross_attn=(attention_levels[i] and with_conditioning),
-                num_heads=num_heads,
-                num_head_channels=dim_head,
+                num_attention_heads=num_heads,
+                attention_head_dim=dim_head,
                 transformer_num_layers=transformer_num_layers,
-                cross_attention_dim=context_dim,
+                cross_attention_dim=cross_attention_dim,
             )
 
             self.down_blocks.append(down_block)
@@ -1422,10 +1437,10 @@ def __init__(
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
             with_conditioning=with_conditioning,
-            num_heads=num_heads,
-            num_head_channels=dim_head,
+            num_attention_heads=num_heads,
+            attention_head_dim=dim_head,
             transformer_num_layers=transformer_num_layers,
-            cross_attention_dim=context_dim,
+            cross_attention_dim=cross_attention_dim,
         )
 
         # up
@@ -1456,10 +1471,10 @@ def __init__(
                 add_upsample=not is_final_block,
                 with_attn=(reversed_attention_levels[i] and not with_conditioning),
                 with_cross_attn=(reversed_attention_levels[i] and with_conditioning),
-                num_heads=num_heads,
-                num_head_channels=dim_head,
+                num_attention_heads=num_heads,
+                attention_head_dim=dim_head,
                 transformer_num_layers=transformer_num_layers,
-                cross_attention_dim=context_dim,
+                cross_attention_dim=cross_attention_dim,
             )
 
             self.up_blocks.append(up_block)
diff --git a/tests/test_diffusion_model_unet.py b/tests/test_diffusion_model_unet.py
index f82a172c..36ccc291 100644
--- a/tests/test_diffusion_model_unet.py
+++ b/tests/test_diffusion_model_unet.py
@@ -14,12 +14,10 @@
 import torch
 from monai.networks import eval_mode
 from parameterized import parameterized
+from tests.utils import test_script_save
 
 from generative.networks.nets import DiffusionModelUNet
 
-# from tests.utils import test_script_save
-
-
 UNCOND_CASES_2D = [
     [
         {
@@ -178,8 +176,7 @@ def test_shape_conditioned_models(self):
             )
             self.assertEqual(result.shape, (1, 1, 16, 32))
 
-    # TODO: Fix problem with torchscript
-    # def test_script_unconditioned_models(self):
+    # def test_script_unconditioned_2d_models(self):
     #     net = DiffusionModelUNet(
     #     spatial_dims= 2,
     #     in_channels= 1,
@@ -192,28 +189,28 @@ def test_shape_conditioned_models(self):
     #     )
     #     test_script_save(net, {"x": torch.rand((1, 1, 16, 16)), "timesteps": torch.randint(0, 1000, (1,)).long()})
 
-    # def test_script_conditioned_models(self):
-    #     net = DiffusionModelUNet(
-    #         spatial_dims=2,
-    #         in_channels=1,
-    #         out_channels=1,
-    #         num_res_blocks=1,
-    #         block_out_channels=(8, 8, 8),
-    #         attention_levels=(False, False, True),
-    #         num_heads=1,
-    #         norm_num_groups=8,
-    #         with_conditioning=True,
-    #         transformer_num_layers=1,
-    #         context_dim=3,
-    #     )
-    #     test_script_save(
-    #         net,
-    #         {
-    #             "x": torch.rand((1, 1, 16, 16)),
-    #             "timesteps": torch.randint(0, 1000, (1,)).long(),
-    #             "context": torch.rand((1, 1, 3)),
-    #         },
-    #     )
+    def test_script_conditioned_2d_models(self):
+        net = DiffusionModelUNet(
+            spatial_dims=2,
+            in_channels=1,
+            out_channels=1,
+            num_res_blocks=1,
+            block_out_channels=(8, 8, 8),
+            attention_levels=(False, False, True),
+            num_heads=1,
+            norm_num_groups=8,
+            with_conditioning=True,
+            transformer_num_layers=1,
+            context_dim=3,
+        )
+        test_script_save(
+            net,
+            {
+                "x": torch.rand((1, 1, 16, 16)),
+                "timesteps": torch.randint(0, 1000, (1,)).long(),
+                "context": torch.rand((1, 1, 3)),
+            },
+        )
 
 
 class TestDiffusionModelUNet3D(unittest.TestCase):
@@ -263,6 +260,42 @@ def test_shape_conditioned_models(self):
             )
             self.assertEqual(result.shape, (1, 1, 16, 16, 16))
 
+    def test_script_unconditioned_3d_models(self):
+        net = DiffusionModelUNet(
+            spatial_dims=3,
+            in_channels=1,
+            out_channels=1,
+            num_res_blocks=1,
+            block_out_channels=(8, 8, 8),
+            attention_levels=(False, False, True),
+            num_heads=1,
+            norm_num_groups=8,
+        )
+        test_script_save(net, {"x": torch.rand((1, 1, 16, 16, 16)), "timesteps": torch.randint(0, 1000, (1,)).long()})
+
+    def test_script_conditioned_3d_models(self):
+        net = DiffusionModelUNet(
+            spatial_dims=3,
+            in_channels=1,
+            out_channels=1,
+            num_res_blocks=1,
+            block_out_channels=(8, 8, 8),
+            attention_levels=(False, False, True),
+            num_heads=1,
+            norm_num_groups=8,
+            with_conditioning=True,
+            transformer_num_layers=1,
+            context_dim=3,
+        )
+        test_script_save(
+            net,
+            {
+                "x": torch.rand((1, 1, 16, 16, 16)),
+                "timesteps": torch.randint(0, 1000, (1,)).long(),
+                "context": torch.rand((1, 1, 3)),
+            },
+        )
+
 
 if __name__ == "__main__":
     unittest.main()

From eb9e3177a5be4c8b3424d88a6ba803fec14e92bf Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Wed, 9 Nov 2022 18:56:33 +0000
Subject: [PATCH 09/28] Rename parameters (#53)

---
 tests/test_diffusion_model_unet.py | 32 +++++++++++++++---------------
 1 file changed, 16 insertions(+), 16 deletions(-)

diff --git a/tests/test_diffusion_model_unet.py b/tests/test_diffusion_model_unet.py
index 36ccc291..e5eba272 100644
--- a/tests/test_diffusion_model_unet.py
+++ b/tests/test_diffusion_model_unet.py
@@ -165,7 +165,7 @@ def test_shape_conditioned_models(self):
             num_heads=1,
             with_conditioning=True,
             transformer_num_layers=1,
-            context_dim=3,
+            cocross_attention_dimntext_dim=3,
             norm_num_groups=8,
         )
         with eval_mode(net):
@@ -176,18 +176,18 @@ def test_shape_conditioned_models(self):
             )
             self.assertEqual(result.shape, (1, 1, 16, 32))
 
-    # def test_script_unconditioned_2d_models(self):
-    #     net = DiffusionModelUNet(
-    #     spatial_dims= 2,
-    #     in_channels= 1,
-    #     out_channels= 1,
-    #     num_res_blocks= 1,
-    #     block_out_channels= (8, 8, 8),
-    #     attention_levels= (False, False, True),
-    #     num_heads= 1,
-    #     norm_num_groups= 8,
-    #     )
-    #     test_script_save(net, {"x": torch.rand((1, 1, 16, 16)), "timesteps": torch.randint(0, 1000, (1,)).long()})
+    def test_script_unconditioned_2d_models(self):
+        net = DiffusionModelUNet(
+            spatial_dims=2,
+            in_channels=1,
+            out_channels=1,
+            num_res_blocks=1,
+            block_out_channels=(8, 8, 8),
+            attention_levels=(False, False, True),
+            num_heads=1,
+            norm_num_groups=8,
+        )
+        test_script_save(net, {"x": torch.rand((1, 1, 16, 16)), "timesteps": torch.randint(0, 1000, (1,)).long()})
 
     def test_script_conditioned_2d_models(self):
         net = DiffusionModelUNet(
@@ -201,7 +201,7 @@ def test_script_conditioned_2d_models(self):
             norm_num_groups=8,
             with_conditioning=True,
             transformer_num_layers=1,
-            context_dim=3,
+            cross_attention_dim=3,
         )
         test_script_save(
             net,
@@ -250,7 +250,7 @@ def test_shape_conditioned_models(self):
             norm_num_groups=16,
             with_conditioning=True,
             transformer_num_layers=1,
-            context_dim=3,
+            cross_attention_dim=3,
         )
         with eval_mode(net):
             result = net.forward(
@@ -285,7 +285,7 @@ def test_script_conditioned_3d_models(self):
             norm_num_groups=8,
             with_conditioning=True,
             transformer_num_layers=1,
-            context_dim=3,
+            cross_attention_dim=3,
         )
         test_script_save(
             net,

From e48b3549ea774902796abc792cc5524115b2130f Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Wed, 9 Nov 2022 18:56:54 +0000
Subject: [PATCH 10/28] Rename parameters (#53)

---
 tests/test_diffusion_model_unet.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/test_diffusion_model_unet.py b/tests/test_diffusion_model_unet.py
index e5eba272..754a802c 100644
--- a/tests/test_diffusion_model_unet.py
+++ b/tests/test_diffusion_model_unet.py
@@ -165,7 +165,7 @@ def test_shape_conditioned_models(self):
             num_heads=1,
             with_conditioning=True,
             transformer_num_layers=1,
-            cocross_attention_dimntext_dim=3,
+            cross_attention_dim=3,
             norm_num_groups=8,
         )
         with eval_mode(net):

From a85428f568aa1ddbe0ca77742d3890b2ffa1126a Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Mon, 21 Nov 2022 22:51:32 +0000
Subject: [PATCH 11/28] Change output_states type from tuple to list (#53)

---
 .../networks/nets/diffusion_model_unet.py      | 18 +++++++++---------
 1 file changed, 9 insertions(+), 9 deletions(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index aadce28c..901a0ace 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -673,15 +673,15 @@ def __init__(
     def forward(
         self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
     ) -> Tuple[torch.Tensor, Any]:
-        output_states = ()
+        output_states = []
 
         for resnet in self.resnets:
             hidden_states = resnet(hidden_states, temb)
-            output_states += (hidden_states,)
+            output_states.append(hidden_states)
 
         if self.downsampler is not None:
             hidden_states = self.downsampler(hidden_states)
-            output_states += (hidden_states,)
+            output_states.append(hidden_states)
 
         return hidden_states, output_states
 
@@ -744,16 +744,16 @@ def __init__(
     def forward(
         self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
     ) -> Tuple[torch.Tensor, Any]:
-        output_states = ()
+        output_states = []
 
         for resnet, attn in zip(self.resnets, self.attentions):
             hidden_states = resnet(hidden_states, temb)
             hidden_states = attn(hidden_states)
-            output_states += (hidden_states,)
+            output_states.append(hidden_states)
 
         if self.downsampler is not None:
             hidden_states = self.downsampler(hidden_states)
-            output_states += (hidden_states,)
+            output_states.append(hidden_states)
 
         return hidden_states, output_states
 
@@ -822,16 +822,16 @@ def __init__(
     def forward(
         self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
     ) -> Tuple[torch.Tensor, Any]:
-        output_states = ()
+        output_states = []
 
         for resnet, attn in zip(self.resnets, self.attentions):
             hidden_states = resnet(hidden_states, temb)
             hidden_states = attn(hidden_states, context=context)
-            output_states += (hidden_states,)
+            output_states.append(hidden_states)
 
         if self.downsampler is not None:
             hidden_states = self.downsampler(hidden_states)
-            output_states += (hidden_states,)
+            output_states.append(hidden_states)
 
         return hidden_states, output_states
 

From dc257709350d40a6a81168c8ad30e6dfcb4ce447 Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Wed, 23 Nov 2022 22:03:08 +0000
Subject: [PATCH 12/28] Fix missing change the use of from tuple to list (#53)

---
 generative/networks/nets/diffusion_model_unet.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index 901a0ace..c108f79b 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -1352,8 +1352,8 @@ def __init__(
         if with_conditioning is True and cross_attention_dim is None:
             raise ValueError(
                 (
-                    "DiffusionModelUNet expects dimension of the cross-attention conditioning (cross_attention_dim) when"
-                    " using with_conditioning."
+                    "DiffusionModelUNet expects dimension of the cross-attention conditioning (cross_attention_dim) "
+                    "when using with_conditioning."
                 )
             )
         if cross_attention_dim is not None and with_conditioning is False:
@@ -1517,10 +1517,10 @@ def forward(
         h = self.conv_in(x)
 
         # 3. down
-        down_block_res_samples = (h,)
+        down_block_res_samples = [h]
         for downsample_block in self.down_blocks:
             h, res_samples = downsample_block(hidden_states=h, temb=emb, context=context)
-            down_block_res_samples += res_samples
+            down_block_res_samples.extend(res_samples)
 
         # 4. mid
         h = self.middle_block(hidden_states=h, temb=emb, context=context)

From df4873608a7ac73c45f183a6ebffa6cf17969250 Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Thu, 24 Nov 2022 15:27:25 +0000
Subject: [PATCH 13/28] [WIP] Removing einops (#53)

---
 .../networks/nets/diffusion_model_unet.py     | 456 +++++++++---------
 tests/test_diffusion_model_unet.py            |  80 +--
 2 files changed, 232 insertions(+), 304 deletions(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index c108f79b..f290ae0b 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -34,10 +34,9 @@
 
 import torch
 import torch.nn.functional as F
-from einops import rearrange
 from monai.networks.blocks import Convolution
 from monai.networks.layers.factories import Pool
-from torch import einsum, nn
+from torch import nn
 
 __all__ = ["DiffusionModelUNet"]
 
@@ -57,7 +56,7 @@ def __init__(self, dim_in: int, dim_out: int) -> None:
 
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         x, gate = self.proj(x).chunk(2, dim=-1)
-        return x * F.gelu(gate)
+        return x * F.gelu(gate.to(dtype=torch.float32)).to(dtype=gate.dtype)
 
 
 class FeedForward(nn.Module):
@@ -68,21 +67,15 @@ class FeedForward(nn.Module):
         num_channels: number of channels in the input.
         dim_out: number of channels in the output. If not given, defaults to `dim`.
         mult: multiplier to use for the hidden dimension.
-        glu: whether to use GLU activation.
         dropout: dropout probability to use.
     """
 
-    def __init__(
-        self, num_channels: int, dim_out: Optional[int] = None, mult: int = 4, glu: bool = False, dropout: float = 0.0
-    ) -> None:
+    def __init__(self, num_channels: int, dim_out: Optional[int] = None, mult: int = 4, dropout: float = 0.0) -> None:
         super().__init__()
         inner_dim = int(num_channels * mult)
         dim_out = dim_out if dim_out is not None else num_channels
-        project_in = (
-            nn.Sequential(nn.Linear(num_channels, inner_dim), nn.GELU()) if not glu else GEGLU(num_channels, inner_dim)
-        )
 
-        self.net = nn.Sequential(project_in, nn.Dropout(dropout), nn.Linear(inner_dim, dim_out))
+        self.net = nn.Sequential(GEGLU(num_channels, inner_dim), nn.Dropout(dropout), nn.Linear(inner_dim, dim_out))
 
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         return self.net(x)
@@ -96,7 +89,7 @@ class CrossAttention(nn.Module):
         query_dim: number of channels in the query.
         cross_attention_dim: number of channels in the context.
         num_attention_heads: number of heads to use for multi-head attention.
-        attention_head_dim: number of channels in each head.
+        num_head_channels: number of channels in each head.
         dropout: dropout probability to use.
     """
 
@@ -105,14 +98,14 @@ def __init__(
         query_dim: int,
         cross_attention_dim: Optional[int] = None,
         num_attention_heads: int = 8,
-        attention_head_dim: int = 64,
+        num_head_channels: int = 64,
         dropout: float = 0.0,
     ) -> None:
         super().__init__()
-        inner_dim = attention_head_dim * num_attention_heads
+        inner_dim = num_head_channels * num_attention_heads
         cross_attention_dim = cross_attention_dim if cross_attention_dim is not None else query_dim
 
-        self.scale = attention_head_dim**-0.5
+        self.scale = num_head_channels**-0.5
         self.heads = num_attention_heads
 
         self.to_q = nn.Linear(query_dim, inner_dim, bias=False)
@@ -135,23 +128,35 @@ def reshape_batch_dim_to_heads(self, x: torch.Tensor) -> torch.Tensor:
         x = x.permute(0, 2, 1, 3).reshape(batch_size // head_size, seq_len, dim * head_size)
         return x
 
+    def _attention(self, query, key, value):
+        attention_scores = torch.baddbmm(
+            torch.empty(query.shape[0], query.shape[1], key.shape[1], dtype=query.dtype, device=query.device),
+            query,
+            key.transpose(-1, -2),
+            beta=0,
+            alpha=self.scale,
+        )
+        attention_probs = attention_scores.softmax(dim=-1)
+
+        # compute attention output
+        hidden_states = torch.bmm(attention_probs, value)
+
+        # reshape hidden_states
+        hidden_states = self.reshape_batch_dim_to_heads(hidden_states)
+        return hidden_states
+
     def forward(self, x: torch.Tensor, context: Optional[torch.Tensor] = None) -> torch.Tensor:
         query = self.to_q(x)
         context = context if context is not None else x
         key = self.to_k(context)
         value = self.to_v(context)
 
-        # TODO: Maybe make use of xformers to improve attention speed
         query = self.reshape_heads_to_batch_dim(query)
         key = self.reshape_heads_to_batch_dim(key)
         value = self.reshape_heads_to_batch_dim(value)
 
-        attention_scores = einsum("b i d, b j d -> b i j", query, key) * self.scale
+        hidden_states = self._attention(query, key, value)
 
-        attention_probs = attention_scores.softmax(dim=-1)
-
-        hidden_states = einsum("b i j, b j d -> b i d", attention_probs, value)
-        hidden_states = self.reshape_batch_dim_to_heads(hidden_states)
         return self.to_out(hidden_states)
 
 
@@ -162,34 +167,32 @@ class BasicTransformerBlock(nn.Module):
     Args:
         num_channels: number of channels in the input and output.
         num_attention_heads: number of heads to use for multi-head attention.
-        attention_head_dim: number of channels in each head.
+        num_head_channels: number of channels in each head.
         dropout: dropout probability to use.
         cross_attention_dim: size of the context vector for cross attention.
-        gated_ff: whether to use a gated feed-forward network.
     """
 
     def __init__(
         self,
         num_channels: int,
         num_attention_heads: int,
-        attention_head_dim: int,
+        num_head_channels: int,
         dropout: float = 0.0,
         cross_attention_dim: Optional[int] = None,
-        gated_ff: bool = True,
     ) -> None:
         super().__init__()
         self.attn1 = CrossAttention(
             query_dim=num_channels,
             num_attention_heads=num_attention_heads,
-            attention_head_dim=attention_head_dim,
+            num_head_channels=num_head_channels,
             dropout=dropout,
         )  # is a self-attention
-        self.ff = FeedForward(num_channels, dropout=dropout, glu=gated_ff)
+        self.ff = FeedForward(num_channels, dropout=dropout)
         self.attn2 = CrossAttention(
             query_dim=num_channels,
             cross_attention_dim=cross_attention_dim,
             num_attention_heads=num_attention_heads,
-            attention_head_dim=attention_head_dim,
+            num_head_channels=num_head_channels,
             dropout=dropout,
         )  # is a self-attention if context is None
         self.norm1 = nn.LayerNorm(num_channels)
@@ -197,21 +200,17 @@ def __init__(
         self.norm3 = nn.LayerNorm(num_channels)
 
     def forward(self, x: torch.Tensor, context: Optional[torch.Tensor] = None) -> torch.Tensor:
+        # 1. Self-Attention
         x = self.attn1(self.norm1(x)) + x
+
+        # 2. Cross-Attention
         x = self.attn2(self.norm2(x), context=context) + x
+
+        # 3. Feed-forward
         x = self.ff(self.norm3(x)) + x
         return x
 
 
-def zero_module(module: nn.Module) -> nn.Module:
-    """
-    Zero out the parameters of a module and return it.
-    """
-    for p in module.parameters():
-        p.detach().zero_()
-    return module
-
-
 class SpatialTransformer(nn.Module):
     """
     Transformer block for image-like data. First, project the input (aka embedding) and reshape to b, t, d. Then apply
@@ -221,7 +220,7 @@ class SpatialTransformer(nn.Module):
         spatial_dims: number of spatial dimensions.
         in_channels: number of channels in the input and output.
         num_attention_heads: number of heads to use for multi-head attention.
-        attention_head_dim: number of channels in each head.
+        num_head_channels: number of channels in each head.
         num_layers: number of layers of Transformer blocks to use.
         dropout: dropout probability to use.
         norm_num_groups: number of groups for the normalization.
@@ -234,7 +233,7 @@ def __init__(
         spatial_dims: int,
         in_channels: int,
         num_attention_heads: int,
-        attention_head_dim: int,
+        num_head_channels: int,
         num_layers: int = 1,
         dropout: float = 0.0,
         norm_num_groups: int = 32,
@@ -244,7 +243,8 @@ def __init__(
         super().__init__()
         self.spatial_dims = spatial_dims
         self.in_channels = in_channels
-        inner_dim = num_attention_heads * attention_head_dim
+        inner_dim = num_attention_heads * num_head_channels
+
         self.norm = nn.GroupNorm(num_groups=norm_num_groups, num_channels=in_channels, eps=norm_eps, affine=True)
 
         self.proj_in = Convolution(
@@ -262,7 +262,7 @@ def __init__(
                 BasicTransformerBlock(
                     num_channels=inner_dim,
                     num_attention_heads=num_attention_heads,
-                    attention_head_dim=attention_head_dim,
+                    num_head_channels=num_head_channels,
                     dropout=dropout,
                     cross_attention_dim=cross_attention_dim,
                 )
@@ -270,112 +270,159 @@ def __init__(
             ]
         )
 
-        self.proj_out = zero_module(
-            Convolution(
-                spatial_dims=spatial_dims,
-                in_channels=inner_dim,
-                out_channels=in_channels,
-                strides=1,
-                kernel_size=1,
-                padding=0,
-                conv_only=True,
-            )
+        self.proj_out = Convolution(
+            spatial_dims=spatial_dims,
+            in_channels=inner_dim,
+            out_channels=in_channels,
+            strides=1,
+            kernel_size=1,
+            padding=0,
+            conv_only=True,
         )
 
     def forward(self, x: torch.Tensor, context: Optional[torch.Tensor] = None) -> torch.Tensor:
         # note: if no context is given, cross-attention defaults to self-attention
+        batch = channel = height = width = depth = -1
         if self.spatial_dims == 2:
-            b, c, h, w = x.shape
+            batch, channel, height, width = x.shape
         if self.spatial_dims == 3:
-            b, c, h, w, d = x.shape
+            batch, channel, height, width, depth = x.shape
 
-        x_in = x
+        residual = x
         x = self.norm(x)
         x = self.proj_in(x)
 
+        inner_dim = x.shape[1]
+
         if self.spatial_dims == 2:
-            x = rearrange(x, "b c h w -> b (h w) c")
+            x = x.permute(0, 2, 3, 1).reshape(batch, height * width, inner_dim)
         if self.spatial_dims == 3:
-            x = rearrange(x, "b c h w d -> b (h w d) c")
+            x = x.permute(0, 2, 3, 4, 1).reshape(batch, height * width * depth, inner_dim)
 
         for block in self.transformer_blocks:
             x = block(x, context=context)
 
         if self.spatial_dims == 2:
-            x = rearrange(x, "b (h w) c -> b c h w", h=h, w=w)
+            x = x.reshape(batch, height, width, inner_dim).permute(0, 3, 1, 2)
         if self.spatial_dims == 3:
-            x = rearrange(x, "b (h w d) c -> b c h w d", h=h, w=w, d=d)
+            x = x.reshape(batch, height, width, depth, inner_dim).permute(0, 4, 1, 2, 3)
 
         x = self.proj_out(x)
-        return x + x_in
-
-
-class QKVAttentionLegacy(nn.Module):
-    """
-    A qkv attention mechanism.
-
-    Args:
-        num_attention_heads: number of attention heads.
-    """
-
-    def __init__(self, num_attention_heads: int) -> None:
-        super().__init__()
-        self.num_attention_heads = num_attention_heads
-
-    def forward(self, qkv: torch.Tensor) -> torch.Tensor:
-        bs, width, length = qkv.shape
-        assert width % (3 * self.num_attention_heads) == 0
-        ch = width // (3 * self.num_attention_heads)
-        q, k, v = qkv.reshape(bs * self.num_attention_heads, ch * 3, length).split(ch, dim=1)
-        scale = 1 / math.sqrt(math.sqrt(ch))
-        weight = torch.einsum("bct,bcs->bts", q * scale, k * scale)  # More stable with f16 than dividing afterwards
-        weight = torch.softmax(weight.float(), dim=-1).type(weight.dtype)
-        a = torch.einsum("bts,bcs->bct", weight, v)
-        return a.reshape(bs, -1, length)
+        return x + residual
 
 
 class AttentionBlock(nn.Module):
     """
-    An attention block.
+    An attention block that allows spatial positions to attend to each other. Uses three q, k, v linear layers to
+    compute attention.
 
     Args:
+        spatial_dims: number of spatial dimensions.
         num_channels: number of channels in the input and output.
-        num_attention_heads:  number of attention heads.
-        attention_head_dim: number of channels in each head.
+        num_head_channels: number of channels in each head.
         norm_num_groups: number of groups to use for group norm.
         norm_eps: epsilon value to use for group norm.
     """
 
     def __init__(
         self,
+        spatial_dims: int,
         num_channels: int,
-        num_attention_heads: int = 1,
-        attention_head_dim: int = -1,
+        num_head_channels: Optional[int] = None,
+        rescale_output_factor: float = 1.0,
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
     ) -> None:
         super().__init__()
-        self.channels = num_channels
-        if attention_head_dim == -1:
-            self.num_heads = num_attention_heads
-        else:
-            assert (
-                num_channels % attention_head_dim == 0
-            ), f"q,k,v channels {num_channels} is not divisible by attention_head_dim {attention_head_dim}"
-            self.num_heads = num_channels // attention_head_dim
+        self.spatial_dims = spatial_dims
+        self.num_channels = num_channels
+
+        self.num_heads = num_channels // num_head_channels if num_head_channels is not None else 1
+        self.num_head_size = num_head_channels
+
         self.norm = nn.GroupNorm(num_groups=norm_num_groups, num_channels=num_channels, eps=norm_eps, affine=True)
-        self.qkv = nn.Conv1d(num_channels, num_channels * 3, 1)
-        self.attention = QKVAttentionLegacy(self.num_heads)
 
-        self.proj_out = zero_module(nn.Conv1d(num_channels, num_channels, 1))
+        # define q,k,v as linear layers
+        self.query = nn.Linear(num_channels, num_channels)
+        self.key = nn.Linear(num_channels, num_channels)
+        self.value = nn.Linear(num_channels, num_channels)
+
+        self.rescale_output_factor = rescale_output_factor
+        self.proj_attn = nn.Linear(num_channels, num_channels, 1)
+
+    def transpose_for_scores(self, projection: torch.Tensor) -> torch.Tensor:
+        new_projection_shape = projection.size()[:-1] + (self.num_heads, -1)
+        # move heads to 2nd position (B, T, H * D) -> (B, T, H, D) -> (B, H, T, D)
+        new_projection = projection.view(new_projection_shape).permute(0, 2, 1, 3)
+
+        return new_projection
 
     def forward(self, x: torch.Tensor) -> torch.Tensor:
-        b, c, *spatial = x.shape
-        x = x.reshape(b, c, -1)
-        qkv = self.qkv(self.norm(x))
-        h = self.attention(qkv)
-        h = self.proj_out(h)
-        return (x + h).reshape(b, c, *spatial)
+        residual = x
+
+        batch = channel = height = width = depth = -1
+        if self.spatial_dims == 2:
+            batch, channel, height, width = x.shape
+        if self.spatial_dims == 3:
+            batch, channel, height, width, depth = x.shape
+
+        x = self.norm(x)
+
+        if self.spatial_dims == 2:
+            x = x.view(batch, channel, height * width).transpose(1, 2)
+        if self.spatial_dims == 3:
+            x = x.view(batch, channel, height * width * depth).transpose(1, 2)
+
+        # proj to q, k, v
+        query_proj = self.query(x)
+        key_proj = self.key(x)
+        value_proj = self.value(x)
+
+        scale = 1 / math.sqrt(self.num_channels / self.num_heads)
+
+        # get scores
+        if self.num_heads > 1:
+            query_states = self.transpose_for_scores(query_proj)
+            key_states = self.transpose_for_scores(key_proj)
+            value_states = self.transpose_for_scores(value_proj)
+            attention_scores = torch.matmul(query_states, key_states.transpose(-1, -2)) * scale
+        else:
+            query_states, key_states, value_states = query_proj, key_proj, value_proj
+
+            attention_scores = torch.baddbmm(
+                torch.empty(
+                    query_states.shape[0],
+                    query_states.shape[1],
+                    key_states.shape[1],
+                    dtype=query_states.dtype,
+                    device=query_states.device,
+                ),
+                query_states,
+                key_states.transpose(-1, -2),
+                beta=0,
+                alpha=scale,
+            )
+
+        attention_probs = torch.softmax(attention_scores.float(), dim=-1)
+
+        # compute attention output
+        if self.num_heads > 1:
+            x = torch.matmul(attention_probs, value_states)
+            x = x.permute(0, 2, 1, 3).contiguous()
+            new_x_shape = x.size()[:-2] + (self.num_channels,)
+            x = x.view(new_x_shape)
+        else:
+            x = torch.bmm(attention_probs, value_states)
+
+        # compute next hidden states
+        x = self.proj_attn(x)
+
+        if self.spatial_dims == 2:
+            x = x.transpose(-1, -2).reshape(batch, channel, height, width)
+        if self.spatial_dims == 3:
+            x = x.transpose(-1, -2).reshape(batch, channel, height, width, depth)
+
+        return x + residual
 
 
 def get_timestep_embedding(timesteps: torch.Tensor, embedding_dim: int, max_period: int = 10000) -> torch.Tensor:
@@ -449,7 +496,7 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
 
 class Upsample(nn.Module):
     """
-    Upsampling layer.
+    Upsampling layer with an optional convolution.
 
     Args:
         spatial_dims: number of spatial dimensions.
@@ -549,16 +596,14 @@ def __init__(
         )
 
         self.norm2 = nn.GroupNorm(num_groups=norm_num_groups, num_channels=self.out_channels, eps=norm_eps, affine=True)
-        self.conv2 = zero_module(
-            Convolution(
-                spatial_dims=spatial_dims,
-                in_channels=self.out_channels,
-                out_channels=self.out_channels,
-                strides=1,
-                kernel_size=3,
-                padding=1,
-                conv_only=True,
-            )
+        self.conv2 = Convolution(
+            spatial_dims=spatial_dims,
+            in_channels=self.out_channels,
+            out_channels=self.out_channels,
+            strides=1,
+            kernel_size=3,
+            padding=1,
+            conv_only=True,
         )
 
         if self.out_channels == in_channels:
@@ -604,30 +649,6 @@ def forward(self, x: torch.Tensor, emb: torch.Tensor) -> torch.Tensor:
         return self.skip_connection(x) + h
 
 
-def get_attention_parameters(
-    num_channels: int, attention_head_dim: int, num_attention_heads: int, legacy: bool, with_conditioning: bool
-) -> Tuple[int, int]:
-    """
-    Get the number of attention heads and their dimensions depending on the model parameters.
-
-    Args:
-        num_channels: number of channels.
-        attention_head_dim: number of channels in each head.
-        num_attention_heads: number of attention heads.
-        legacy: if True, use legacy way to compute dim_head for attention blocks.
-        with_conditioning: if true together with legacy, use ch // num_heads as head dimension.
-
-    """
-    if attention_head_dim == -1:
-        dim_head = num_channels // num_attention_heads
-    else:
-        num_attention_heads = num_channels // attention_head_dim
-        dim_head = attention_head_dim
-    if legacy:
-        dim_head = num_channels // num_attention_heads if with_conditioning else attention_head_dim
-    return dim_head, num_attention_heads
-
-
 class DownBlock(nn.Module):
     def __init__(
         self,
@@ -698,8 +719,7 @@ def __init__(
         norm_eps: float = 1e-6,
         add_downsample: bool = True,
         downsample_padding: int = 1,
-        num_attention_heads: int = 1,
-        attention_head_dim: int = 1,
+        num_head_channels: int = 1,
     ) -> None:
         super().__init__()
         resnets = []
@@ -719,16 +739,16 @@ def __init__(
             )
             attentions.append(
                 AttentionBlock(
+                    spatial_dims=spatial_dims,
                     num_channels=out_channels,
-                    num_attention_heads=num_attention_heads,
-                    attention_head_dim=attention_head_dim,
+                    num_head_channels=num_head_channels,
                     norm_num_groups=norm_num_groups,
                     norm_eps=norm_eps,
                 )
             )
 
-        self.resnets = nn.ModuleList(resnets)
         self.attentions = nn.ModuleList(attentions)
+        self.resnets = nn.ModuleList(resnets)
 
         if add_downsample:
             self.downsampler = Downsample(
@@ -770,8 +790,7 @@ def __init__(
         norm_eps: float = 1e-6,
         add_downsample: bool = True,
         downsample_padding: int = 1,
-        num_attention_heads: int = 1,
-        attention_head_dim: int = 1,
+        num_head_channels: int = 1,
         transformer_num_layers: int = 1,
         cross_attention_dim: Optional[int] = None,
     ) -> None:
@@ -796,8 +815,8 @@ def __init__(
                 SpatialTransformer(
                     spatial_dims=spatial_dims,
                     in_channels=out_channels,
-                    num_attention_heads=num_attention_heads,
-                    attention_head_dim=attention_head_dim,
+                    num_attention_heads=out_channels // num_head_channels,
+                    num_head_channels=num_head_channels,
                     num_layers=transformer_num_layers,
                     norm_num_groups=norm_num_groups,
                     norm_eps=norm_eps,
@@ -805,8 +824,8 @@ def __init__(
                 )
             )
 
-        self.resnets = nn.ModuleList(resnets)
         self.attentions = nn.ModuleList(attentions)
+        self.resnets = nn.ModuleList(resnets)
 
         if add_downsample:
             self.downsampler = Downsample(
@@ -844,8 +863,7 @@ def __init__(
         temb_channels: int,
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
-        num_attention_heads: int = 1,
-        attention_head_dim: int = 1,
+        num_head_channels: int = 1,
     ) -> None:
         super().__init__()
         self.attention = None
@@ -859,9 +877,9 @@ def __init__(
             norm_eps=norm_eps,
         )
         self.attention = AttentionBlock(
+            spatial_dims=spatial_dims,
             num_channels=in_channels,
-            num_attention_heads=num_attention_heads,
-            attention_head_dim=attention_head_dim,
+            num_head_channels=num_head_channels,
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
         )
@@ -893,8 +911,7 @@ def __init__(
         temb_channels: int,
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
-        num_attention_heads: int = 1,
-        attention_head_dim: int = 1,
+        num_head_channels: int = 1,
         transformer_num_layers: int = 1,
         cross_attention_dim: Optional[int] = None,
     ) -> None:
@@ -912,8 +929,8 @@ def __init__(
         self.attention = SpatialTransformer(
             spatial_dims=spatial_dims,
             in_channels=in_channels,
-            num_attention_heads=num_attention_heads,
-            attention_head_dim=attention_head_dim,
+            num_attention_heads=in_channels // num_head_channels,
+            num_head_channels=num_head_channels,
             num_layers=transformer_num_layers,
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
@@ -1011,8 +1028,7 @@ def __init__(
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
         add_upsample: bool = True,
-        num_attention_heads: int = 1,
-        attention_head_dim: int = 1,
+        num_head_channels: int = 1,
     ) -> None:
         super().__init__()
         resnets = []
@@ -1034,9 +1050,9 @@ def __init__(
             )
             attentions.append(
                 AttentionBlock(
+                    spatial_dims=spatial_dims,
                     num_channels=out_channels,
-                    num_attention_heads=num_attention_heads,
-                    attention_head_dim=attention_head_dim,
+                    num_head_channels=num_head_channels,
                     norm_num_groups=norm_num_groups,
                     norm_eps=norm_eps,
                 )
@@ -1086,8 +1102,7 @@ def __init__(
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
         add_upsample: bool = True,
-        num_attention_heads: int = 1,
-        attention_head_dim: int = 1,
+        num_head_channels: int = 1,
         transformer_num_layers: int = 1,
         cross_attention_dim: Optional[int] = None,
     ) -> None:
@@ -1113,8 +1128,8 @@ def __init__(
                 SpatialTransformer(
                     spatial_dims=spatial_dims,
                     in_channels=out_channels,
-                    num_attention_heads=num_attention_heads,
-                    attention_head_dim=attention_head_dim,
+                    num_attention_heads=out_channels // num_head_channels,
+                    num_head_channels=num_head_channels,
                     norm_num_groups=norm_num_groups,
                     norm_eps=norm_eps,
                     num_layers=transformer_num_layers,
@@ -1122,8 +1137,8 @@ def __init__(
                 )
             )
 
-        self.resnets = nn.ModuleList(resnets)
         self.attentions = nn.ModuleList(attentions)
+        self.resnets = nn.ModuleList(resnets)
 
         if add_upsample:
             self.upsampler = Upsample(
@@ -1165,8 +1180,7 @@ def get_down_block(
     add_downsample: bool,
     with_attn: bool,
     with_cross_attn: bool,
-    num_attention_heads: int,
-    attention_head_dim: int,
+    num_head_channels: int,
     transformer_num_layers: int,
     cross_attention_dim: Optional[int],
 ) -> nn.Module:
@@ -1180,8 +1194,7 @@ def get_down_block(
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
             add_downsample=add_downsample,
-            num_attention_heads=num_attention_heads,
-            attention_head_dim=attention_head_dim,
+            num_head_channels=num_head_channels,
         )
     elif with_cross_attn:
         return CrossAttnDownBlock(
@@ -1193,8 +1206,7 @@ def get_down_block(
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
             add_downsample=add_downsample,
-            num_attention_heads=num_attention_heads,
-            attention_head_dim=attention_head_dim,
+            num_head_channels=num_head_channels,
             transformer_num_layers=transformer_num_layers,
             cross_attention_dim=cross_attention_dim,
         )
@@ -1218,8 +1230,7 @@ def get_mid_block(
     norm_num_groups: int,
     norm_eps: float,
     with_conditioning: bool,
-    num_attention_heads: int,
-    attention_head_dim: int,
+    num_head_channels: int,
     transformer_num_layers: int,
     cross_attention_dim: Optional[int],
 ) -> nn.Module:
@@ -1230,8 +1241,7 @@ def get_mid_block(
             temb_channels=temb_channels,
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
-            num_attention_heads=num_attention_heads,
-            attention_head_dim=attention_head_dim,
+            num_head_channels=num_head_channels,
             transformer_num_layers=transformer_num_layers,
             cross_attention_dim=cross_attention_dim,
         )
@@ -1242,8 +1252,7 @@ def get_mid_block(
             temb_channels=temb_channels,
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
-            num_attention_heads=num_attention_heads,
-            attention_head_dim=attention_head_dim,
+            num_head_channels=num_head_channels,
         )
 
 
@@ -1259,8 +1268,7 @@ def get_up_block(
     add_upsample: bool,
     with_attn: bool,
     with_cross_attn: bool,
-    num_attention_heads: int,
-    attention_head_dim: int,
+    num_head_channels: int,
     transformer_num_layers: int,
     cross_attention_dim: Optional[int],
 ) -> nn.Module:
@@ -1275,8 +1283,7 @@ def get_up_block(
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
             add_upsample=add_upsample,
-            num_attention_heads=num_attention_heads,
-            attention_head_dim=attention_head_dim,
+            num_head_channels=num_head_channels,
         )
     elif with_cross_attn:
         return CrossAttnUpBlock(
@@ -1289,8 +1296,7 @@ def get_up_block(
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
             add_upsample=add_upsample,
-            num_attention_heads=num_attention_heads,
-            attention_head_dim=attention_head_dim,
+            num_head_channels=num_head_channels,
             transformer_num_layers=transformer_num_layers,
             cross_attention_dim=cross_attention_dim,
         )
@@ -1319,13 +1325,11 @@ class DiffusionModelUNet(nn.Module):
         in_channels: number of input channels.
         out_channels: number of output channels.
         num_res_blocks: number of residual blocks (see ResBlock) per level.
-        block_out_channels: tuple of block output channels.
+        num_channels: tuple of block output channels.
         attention_levels: list of levels to add attention.
         norm_num_groups: number of groups for the normalization.
         norm_eps: epsilon for the normalization.
-        num_heads: number of attention heads.
         num_head_channels: number of channels in each head.
-        legacy: if True, use legacy way to compute dim_head for attention blocks.
         with_conditioning: if True add spatial transformers to perform conditioning.
         transformer_num_layers: number of layers of Transformer blocks to use.
         cross_attention_dim: number of context dimensions to use.
@@ -1337,13 +1341,11 @@ def __init__(
         in_channels: int,
         out_channels: int,
         num_res_blocks: int,
-        block_out_channels: Sequence[int] = (32, 64, 64, 64),
+        num_channels: Sequence[int] = (32, 64, 64, 64),
         attention_levels: Sequence[bool] = (False, False, True, True),
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
-        num_heads: int = -1,
-        num_head_channels: int = -1,
-        legacy: bool = True,
+        num_head_channels: int = 8,
         with_conditioning: bool = False,
         transformer_num_layers: int = 1,
         cross_attention_dim: Optional[int] = None,
@@ -1361,26 +1363,22 @@ def __init__(
                 "DiffusionModelUNet expects use_spatial_transformer=True when specifying the " "cross_attention_dim."
             )
 
-        if num_heads == -1 and num_head_channels == -1:
-            raise ValueError("DiffusionModelUNet expects that either num_heads or num_head_channels has to be set.")
-
         # The number of channels should be multiple of num_groups
-        if any((out_channel % norm_num_groups) != 0 for out_channel in block_out_channels):
+        if any((out_channel % norm_num_groups) != 0 for out_channel in num_channels):
             raise ValueError("DiffusionModelUNet expects all block_out_channels being multiple of norm_num_groups")
 
         self.in_channels = in_channels
-        self.block_out_channels = block_out_channels
+        self.block_out_channels = num_channels
         self.out_channels = out_channels
         self.num_res_blocks = num_res_blocks
         self.attention_levels = attention_levels
-        self.num_heads = num_heads
         self.num_head_channels = num_head_channels
 
         # input
         self.conv_in = Convolution(
             spatial_dims=spatial_dims,
             in_channels=in_channels,
-            out_channels=block_out_channels[0],
+            out_channels=num_channels[0],
             strides=1,
             kernel_size=3,
             padding=1,
@@ -1388,24 +1386,20 @@ def __init__(
         )
 
         # time
-        time_embed_dim = block_out_channels[0] * 4
+        time_embed_dim = num_channels[0] * 4
         self.time_embed = nn.Sequential(
-            nn.Linear(block_out_channels[0], time_embed_dim),
+            nn.Linear(num_channels[0], time_embed_dim),
             nn.SiLU(),
             nn.Linear(time_embed_dim, time_embed_dim),
         )
 
         # down
         self.down_blocks = nn.ModuleList([])
-        output_channel = block_out_channels[0]
-        for i in range(len(block_out_channels)):
+        output_channel = num_channels[0]
+        for i in range(len(num_channels)):
             input_channel = output_channel
-            output_channel = block_out_channels[i]
-            is_final_block = i == len(block_out_channels) - 1
-
-            dim_head, num_heads = get_attention_parameters(
-                input_channel, num_head_channels, num_heads, legacy, with_conditioning
-            )
+            output_channel = num_channels[i]
+            is_final_block = i == len(num_channels) - 1
 
             down_block = get_down_block(
                 spatial_dims=spatial_dims,
@@ -1418,8 +1412,7 @@ def __init__(
                 add_downsample=not is_final_block,
                 with_attn=(attention_levels[i] and not with_conditioning),
                 with_cross_attn=(attention_levels[i] and with_conditioning),
-                num_attention_heads=num_heads,
-                attention_head_dim=dim_head,
+                num_head_channels=num_head_channels,
                 transformer_num_layers=transformer_num_layers,
                 cross_attention_dim=cross_attention_dim,
             )
@@ -1427,37 +1420,29 @@ def __init__(
             self.down_blocks.append(down_block)
 
         # mid
-        dim_head, num_heads = get_attention_parameters(
-            block_out_channels[-1], num_head_channels, num_heads, legacy, with_conditioning
-        )
         self.middle_block = get_mid_block(
             spatial_dims=spatial_dims,
-            in_channels=block_out_channels[-1],
+            in_channels=num_channels[-1],
             temb_channels=time_embed_dim,
             norm_num_groups=norm_num_groups,
             norm_eps=norm_eps,
             with_conditioning=with_conditioning,
-            num_attention_heads=num_heads,
-            attention_head_dim=dim_head,
+            num_head_channels=num_head_channels,
             transformer_num_layers=transformer_num_layers,
             cross_attention_dim=cross_attention_dim,
         )
 
         # up
         self.up_blocks = nn.ModuleList([])
-        reversed_block_out_channels = list(reversed(block_out_channels))
+        reversed_block_out_channels = list(reversed(num_channels))
         reversed_attention_levels = list(reversed(attention_levels))
         output_channel = reversed_block_out_channels[0]
         for i in range(len(reversed_block_out_channels)):
             prev_output_channel = output_channel
             output_channel = reversed_block_out_channels[i]
-            input_channel = reversed_block_out_channels[min(i + 1, len(block_out_channels) - 1)]
+            input_channel = reversed_block_out_channels[min(i + 1, len(num_channels) - 1)]
 
-            is_final_block = i == len(block_out_channels) - 1
-
-            dim_head, num_heads = get_attention_parameters(
-                output_channel, num_head_channels, num_heads, legacy, with_conditioning
-            )
+            is_final_block = i == len(num_channels) - 1
 
             up_block = get_up_block(
                 spatial_dims=spatial_dims,
@@ -1471,8 +1456,7 @@ def __init__(
                 add_upsample=not is_final_block,
                 with_attn=(reversed_attention_levels[i] and not with_conditioning),
                 with_cross_attn=(reversed_attention_levels[i] and with_conditioning),
-                num_attention_heads=num_heads,
-                attention_head_dim=dim_head,
+                num_head_channels=num_head_channels,
                 transformer_num_layers=transformer_num_layers,
                 cross_attention_dim=cross_attention_dim,
             )
@@ -1482,18 +1466,16 @@ def __init__(
 
         # out
         self.out = nn.Sequential(
-            nn.GroupNorm(num_groups=norm_num_groups, num_channels=block_out_channels[0], eps=norm_eps, affine=True),
+            nn.GroupNorm(num_groups=norm_num_groups, num_channels=num_channels[0], eps=norm_eps, affine=True),
             nn.SiLU(),
-            zero_module(
-                Convolution(
-                    spatial_dims=spatial_dims,
-                    in_channels=block_out_channels[0],
-                    out_channels=out_channels,
-                    strides=1,
-                    kernel_size=3,
-                    padding=1,
-                    conv_only=True,
-                )
+            Convolution(
+                spatial_dims=spatial_dims,
+                in_channels=num_channels[0],
+                out_channels=out_channels,
+                strides=1,
+                kernel_size=3,
+                padding=1,
+                conv_only=True,
             ),
         )
 
diff --git a/tests/test_diffusion_model_unet.py b/tests/test_diffusion_model_unet.py
index 754a802c..231af572 100644
--- a/tests/test_diffusion_model_unet.py
+++ b/tests/test_diffusion_model_unet.py
@@ -25,9 +25,8 @@
             "in_channels": 1,
             "out_channels": 1,
             "num_res_blocks": 1,
-            "block_out_channels": (8, 8, 8),
+            "num_channels": (8, 8, 8),
             "attention_levels": (False, False, True),
-            "num_heads": 1,
             "norm_num_groups": 8,
         },
     ],
@@ -37,27 +36,12 @@
             "in_channels": 1,
             "out_channels": 1,
             "num_res_blocks": 1,
-            "block_out_channels": (8, 8, 8),
+            "num_channels": (8, 8, 8),
             "attention_levels": (False, False, True),
-            "num_heads": -1,
             "num_head_channels": 1,
             "norm_num_groups": 8,
         },
     ],
-    [
-        {
-            "spatial_dims": 2,
-            "in_channels": 1,
-            "out_channels": 1,
-            "num_res_blocks": 1,
-            "block_out_channels": (8, 8, 8),
-            "attention_levels": (False, False, True),
-            "num_heads": 4,
-            "num_head_channels": 2,
-            "legacy": False,
-            "norm_num_groups": 8,
-        },
-    ],
 ]
 
 UNCOND_CASES_3D = [
@@ -67,22 +51,8 @@
             "in_channels": 1,
             "out_channels": 1,
             "num_res_blocks": 1,
-            "block_out_channels": (8, 8, 8),
-            "attention_levels": (False, False, True),
-            "num_heads": 1,
-            "norm_num_groups": 4,
-        },
-    ],
-    [
-        {
-            "spatial_dims": 3,
-            "in_channels": 1,
-            "out_channels": 1,
-            "num_res_blocks": 1,
-            "block_out_channels": (8, 8, 8),
+            "num_channels": (8, 8, 8),
             "attention_levels": (False, False, True),
-            "num_heads": -1,
-            "num_head_channels": 1,
             "norm_num_groups": 4,
         },
     ],
@@ -92,11 +62,9 @@
             "in_channels": 1,
             "out_channels": 1,
             "num_res_blocks": 1,
-            "block_out_channels": (8, 8, 8),
+            "num_channels": (8, 8, 8),
             "attention_levels": (False, False, True),
-            "num_heads": 1,
             "num_head_channels": 1,
-            "legacy": False,
             "norm_num_groups": 4,
         },
     ],
@@ -119,29 +87,14 @@ def test_shape_with_different_in_channel_out_channel(self):
             in_channels=in_channels,
             out_channels=out_channels,
             num_res_blocks=1,
-            block_out_channels=(8, 8, 8),
+            num_channels=(8, 8, 8),
             attention_levels=(False, False, True),
-            num_heads=1,
             norm_num_groups=8,
         )
         with eval_mode(net):
             result = net.forward(torch.rand((1, in_channels, 16, 16)), torch.randint(0, 1000, (1,)).long())
             self.assertEqual(result.shape, (1, out_channels, 16, 16))
 
-    def test_attention_heads_not_declared(self):
-        with self.assertRaises(ValueError):
-            DiffusionModelUNet(
-                spatial_dims=2,
-                in_channels=3,
-                out_channels=3,
-                num_res_blocks=1,
-                block_out_channels=(8, 8, 8),
-                attention_levels=(False, False, True),
-                num_heads=-1,
-                num_head_channels=-1,
-                norm_num_groups=8,
-            )
-
     def test_model_channels_not_multiple_of_norm_num_group(self):
         with self.assertRaises(ValueError):
             DiffusionModelUNet(
@@ -149,7 +102,7 @@ def test_model_channels_not_multiple_of_norm_num_group(self):
                 in_channels=3,
                 out_channels=3,
                 num_res_blocks=1,
-                block_out_channels=(8, 8, 24),
+                num_channels=(8, 8, 24),
                 attention_levels=(False, False, True),
                 norm_num_groups=16,
             )
@@ -160,9 +113,8 @@ def test_shape_conditioned_models(self):
             in_channels=1,
             out_channels=1,
             num_res_blocks=1,
-            block_out_channels=(8, 8, 8),
+            num_channels=(8, 8, 8),
             attention_levels=(False, False, True),
-            num_heads=1,
             with_conditioning=True,
             transformer_num_layers=1,
             cross_attention_dim=3,
@@ -182,9 +134,8 @@ def test_script_unconditioned_2d_models(self):
             in_channels=1,
             out_channels=1,
             num_res_blocks=1,
-            block_out_channels=(8, 8, 8),
+            num_channels=(8, 8, 8),
             attention_levels=(False, False, True),
-            num_heads=1,
             norm_num_groups=8,
         )
         test_script_save(net, {"x": torch.rand((1, 1, 16, 16)), "timesteps": torch.randint(0, 1000, (1,)).long()})
@@ -195,9 +146,8 @@ def test_script_conditioned_2d_models(self):
             in_channels=1,
             out_channels=1,
             num_res_blocks=1,
-            block_out_channels=(8, 8, 8),
+            num_channels=(8, 8, 8),
             attention_levels=(False, False, True),
-            num_heads=1,
             norm_num_groups=8,
             with_conditioning=True,
             transformer_num_layers=1,
@@ -229,9 +179,8 @@ def test_shape_with_different_in_channel_out_channel(self):
             in_channels=in_channels,
             out_channels=out_channels,
             num_res_blocks=1,
-            block_out_channels=(8, 8, 8),
+            num_channels=(8, 8, 8),
             attention_levels=(False, False, True),
-            num_heads=1,
             norm_num_groups=4,
         )
         with eval_mode(net):
@@ -244,9 +193,8 @@ def test_shape_conditioned_models(self):
             in_channels=1,
             out_channels=1,
             num_res_blocks=1,
-            block_out_channels=(16, 16, 16),
+            num_channels=(16, 16, 16),
             attention_levels=(False, False, True),
-            num_heads=1,
             norm_num_groups=16,
             with_conditioning=True,
             transformer_num_layers=1,
@@ -266,9 +214,8 @@ def test_script_unconditioned_3d_models(self):
             in_channels=1,
             out_channels=1,
             num_res_blocks=1,
-            block_out_channels=(8, 8, 8),
+            num_channels=(8, 8, 8),
             attention_levels=(False, False, True),
-            num_heads=1,
             norm_num_groups=8,
         )
         test_script_save(net, {"x": torch.rand((1, 1, 16, 16, 16)), "timesteps": torch.randint(0, 1000, (1,)).long()})
@@ -279,9 +226,8 @@ def test_script_conditioned_3d_models(self):
             in_channels=1,
             out_channels=1,
             num_res_blocks=1,
-            block_out_channels=(8, 8, 8),
+            num_channels=(8, 8, 8),
             attention_levels=(False, False, True),
-            num_heads=1,
             norm_num_groups=8,
             with_conditioning=True,
             transformer_num_layers=1,

From bdf28bce47e874aebd5dd6ab598b32556c56b16d Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Thu, 24 Nov 2022 18:02:35 +0000
Subject: [PATCH 14/28] Fix torchscript errors (#53)

---
 .../networks/nets/diffusion_model_unet.py     | 34 +++++++++----------
 tests/test_diffusion_model_unet.py            | 21 ++++--------
 2 files changed, 23 insertions(+), 32 deletions(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index f290ae0b..561fa7a4 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -30,7 +30,7 @@
 # =========================================================================
 
 import math
-from typing import Any, Optional, Sequence, Tuple
+from typing import List, Optional, Sequence, Tuple
 
 import torch
 import torch.nn.functional as F
@@ -693,7 +693,7 @@ def __init__(
 
     def forward(
         self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
-    ) -> Tuple[torch.Tensor, Any]:
+    ) -> Tuple[torch.Tensor, List[torch.Tensor]]:
         output_states = []
 
         for resnet in self.resnets:
@@ -763,7 +763,7 @@ def __init__(
 
     def forward(
         self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
-    ) -> Tuple[torch.Tensor, Any]:
+    ) -> Tuple[torch.Tensor, List[torch.Tensor]]:
         output_states = []
 
         for resnet, attn in zip(self.resnets, self.attentions):
@@ -840,7 +840,7 @@ def __init__(
 
     def forward(
         self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
-    ) -> Tuple[torch.Tensor, Any]:
+    ) -> Tuple[torch.Tensor, List[torch.Tensor]]:
         output_states = []
 
         for resnet, attn in zip(self.resnets, self.attentions):
@@ -998,14 +998,14 @@ def __init__(
     def forward(
         self,
         hidden_states: torch.Tensor,
-        res_hidden_states_tuple: torch.Tensor,
+        res_hidden_states_list: List[torch.Tensor],
         temb: torch.Tensor,
         context: Optional[torch.Tensor] = None,
     ) -> torch.Tensor:
         for i, resnet in enumerate(self.resnets):
             # pop res hidden states
-            res_hidden_states = res_hidden_states_tuple[-1]
-            res_hidden_states_tuple = res_hidden_states_tuple[:-1]
+            res_hidden_states = res_hidden_states_list[-1]
+            res_hidden_states_list = res_hidden_states_list[:-1]
             hidden_states = torch.cat([hidden_states, res_hidden_states], dim=1)
 
             hidden_states = resnet(hidden_states, temb)
@@ -1071,14 +1071,14 @@ def __init__(
     def forward(
         self,
         hidden_states: torch.Tensor,
-        res_hidden_states_tuple: torch.Tensor,
+        res_hidden_states_list: List[torch.Tensor],
         temb: torch.Tensor,
         context: Optional[torch.Tensor] = None,
     ) -> torch.Tensor:
         for resnet, attn in zip(self.resnets, self.attentions):
             # pop res hidden states
-            res_hidden_states = res_hidden_states_tuple[-1]
-            res_hidden_states_tuple = res_hidden_states_tuple[:-1]
+            res_hidden_states = res_hidden_states_list[-1]
+            res_hidden_states_list = res_hidden_states_list[:-1]
             hidden_states = torch.cat([hidden_states, res_hidden_states], dim=1)
 
             hidden_states = resnet(hidden_states, temb)
@@ -1150,14 +1150,14 @@ def __init__(
     def forward(
         self,
         hidden_states: torch.Tensor,
-        res_hidden_states_tuple: torch.Tensor,
+        res_hidden_states_list: List[torch.Tensor],
         temb: torch.Tensor,
         context: Optional[torch.Tensor] = None,
     ) -> torch.Tensor:
         for resnet, attn in zip(self.resnets, self.attentions):
             # pop res hidden states
-            res_hidden_states = res_hidden_states_tuple[-1]
-            res_hidden_states_tuple = res_hidden_states_tuple[:-1]
+            res_hidden_states = res_hidden_states_list[-1]
+            res_hidden_states_list = res_hidden_states_list[:-1]
             hidden_states = torch.cat([hidden_states, res_hidden_states], dim=1)
 
             hidden_states = resnet(hidden_states, temb)
@@ -1499,10 +1499,11 @@ def forward(
         h = self.conv_in(x)
 
         # 3. down
-        down_block_res_samples = [h]
+        down_block_res_samples: List[torch.Tensor] = [h]
         for downsample_block in self.down_blocks:
             h, res_samples = downsample_block(hidden_states=h, temb=emb, context=context)
-            down_block_res_samples.extend(res_samples)
+            for residual in res_samples:
+                down_block_res_samples.append(residual)
 
         # 4. mid
         h = self.middle_block(hidden_states=h, temb=emb, context=context)
@@ -1511,8 +1512,7 @@ def forward(
         for upsample_block in self.up_blocks:
             res_samples = down_block_res_samples[-len(upsample_block.resnets) :]
             down_block_res_samples = down_block_res_samples[: -len(upsample_block.resnets)]
-
-            h = upsample_block(hidden_states=h, res_hidden_states_tuple=res_samples, temb=emb, context=context)
+            h = upsample_block(hidden_states=h, res_hidden_states_list=res_samples, temb=emb, context=context)
 
         # 6. output block
         h = self.out(h)
diff --git a/tests/test_diffusion_model_unet.py b/tests/test_diffusion_model_unet.py
index 231af572..f2e30c0c 100644
--- a/tests/test_diffusion_model_unet.py
+++ b/tests/test_diffusion_model_unet.py
@@ -138,7 +138,7 @@ def test_script_unconditioned_2d_models(self):
             attention_levels=(False, False, True),
             norm_num_groups=8,
         )
-        test_script_save(net, {"x": torch.rand((1, 1, 16, 16)), "timesteps": torch.randint(0, 1000, (1,)).long()})
+        test_script_save(net, torch.rand((1, 1, 16, 16)), torch.randint(0, 1000, (1,)).long())
 
     def test_script_conditioned_2d_models(self):
         net = DiffusionModelUNet(
@@ -153,14 +153,7 @@ def test_script_conditioned_2d_models(self):
             transformer_num_layers=1,
             cross_attention_dim=3,
         )
-        test_script_save(
-            net,
-            {
-                "x": torch.rand((1, 1, 16, 16)),
-                "timesteps": torch.randint(0, 1000, (1,)).long(),
-                "context": torch.rand((1, 1, 3)),
-            },
-        )
+        test_script_save(net, torch.rand((1, 1, 16, 16)), torch.randint(0, 1000, (1,)).long(), torch.rand((1, 1, 3)))
 
 
 class TestDiffusionModelUNet3D(unittest.TestCase):
@@ -218,7 +211,7 @@ def test_script_unconditioned_3d_models(self):
             attention_levels=(False, False, True),
             norm_num_groups=8,
         )
-        test_script_save(net, {"x": torch.rand((1, 1, 16, 16, 16)), "timesteps": torch.randint(0, 1000, (1,)).long()})
+        test_script_save(net, torch.rand((1, 1, 16, 16, 16)), torch.randint(0, 1000, (1,)).long())
 
     def test_script_conditioned_3d_models(self):
         net = DiffusionModelUNet(
@@ -235,11 +228,9 @@ def test_script_conditioned_3d_models(self):
         )
         test_script_save(
             net,
-            {
-                "x": torch.rand((1, 1, 16, 16, 16)),
-                "timesteps": torch.randint(0, 1000, (1,)).long(),
-                "context": torch.rand((1, 1, 3)),
-            },
+            torch.rand((1, 1, 16, 16, 16)),
+            torch.randint(0, 1000, (1,)).long(),
+            torch.rand((1, 1, 3)),
         )
 
 

From 7da7e1c261223fed17ac640def580e985945ece8 Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Thu, 24 Nov 2022 18:14:18 +0000
Subject: [PATCH 15/28] Add missing tyupe hint and remove vestigial variable
 (#53)

---
 generative/networks/nets/diffusion_model_unet.py | 4 +---
 1 file changed, 1 insertion(+), 3 deletions(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index 561fa7a4..03523cf4 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -128,7 +128,7 @@ def reshape_batch_dim_to_heads(self, x: torch.Tensor) -> torch.Tensor:
         x = x.permute(0, 2, 1, 3).reshape(batch_size // head_size, seq_len, dim * head_size)
         return x
 
-    def _attention(self, query, key, value):
+    def _attention(self, query: torch.Tensor, key: torch.Tensor, value: torch.Tensor) -> torch.Tensor:
         attention_scores = torch.baddbmm(
             torch.empty(query.shape[0], query.shape[1], key.shape[1], dtype=query.dtype, device=query.device),
             query,
@@ -329,7 +329,6 @@ def __init__(
         spatial_dims: int,
         num_channels: int,
         num_head_channels: Optional[int] = None,
-        rescale_output_factor: float = 1.0,
         norm_num_groups: int = 32,
         norm_eps: float = 1e-6,
     ) -> None:
@@ -347,7 +346,6 @@ def __init__(
         self.key = nn.Linear(num_channels, num_channels)
         self.value = nn.Linear(num_channels, num_channels)
 
-        self.rescale_output_factor = rescale_output_factor
         self.proj_attn = nn.Linear(num_channels, num_channels, 1)
 
     def transpose_for_scores(self, projection: torch.Tensor) -> torch.Tensor:

From 212285733b3ef5f3c0921f0876a96e5eb3852528 Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Thu, 24 Nov 2022 19:01:01 +0000
Subject: [PATCH 16/28] Add docstring (#53)

---
 .../networks/nets/diffusion_model_unet.py     | 138 ++++++++++++++++--
 1 file changed, 127 insertions(+), 11 deletions(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index 03523cf4..ef262bbc 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -167,7 +167,7 @@ class BasicTransformerBlock(nn.Module):
     Args:
         num_channels: number of channels in the input and output.
         num_attention_heads: number of heads to use for multi-head attention.
-        num_head_channels: number of channels in each head.
+        num_head_channels: number of channels in each attention head.
         dropout: dropout probability to use.
         cross_attention_dim: size of the context vector for cross attention.
     """
@@ -220,7 +220,7 @@ class SpatialTransformer(nn.Module):
         spatial_dims: number of spatial dimensions.
         in_channels: number of channels in the input and output.
         num_attention_heads: number of heads to use for multi-head attention.
-        num_head_channels: number of channels in each head.
+        num_head_channels: number of channels in each attention head.
         num_layers: number of layers of Transformer blocks to use.
         dropout: dropout probability to use.
         norm_num_groups: number of groups for the normalization.
@@ -319,7 +319,7 @@ class AttentionBlock(nn.Module):
     Args:
         spatial_dims: number of spatial dimensions.
         num_channels: number of channels in the input and output.
-        num_head_channels: number of channels in each head.
+        num_head_channels: number of channels in each attention head.
         norm_num_groups: number of groups to use for group norm.
         norm_eps: epsilon value to use for group norm.
     """
@@ -498,7 +498,7 @@ class Upsample(nn.Module):
 
     Args:
         spatial_dims: number of spatial dimensions.
-        num_channels: number of input channels
+        num_channels: number of input channels.
         use_conv: if True uses Convolution instead of Pool average to perform downsampling.
         out_channels: number of output channels.
         padding: controls the amount of implicit zero-paddings on both sides for padding number of points for each
@@ -542,8 +542,8 @@ class ResnetBlock(nn.Module):
 
     Args:
         spatial_dims: The number of spatial dimensions.
-        in_channels: number of input channels
-        temb_channels: number of timestep embedding  channels
+        in_channels: number of input channels.
+        temb_channels: number of timestep embedding  channels.
         out_channels: number of output channels.
         up: if True, performs upsampling.
         down: if True, performs downsampling.
@@ -660,6 +660,20 @@ def __init__(
         add_downsample: bool = True,
         downsample_padding: int = 1,
     ) -> None:
+        """
+        Unet's down block containing resnet and downsamplers blocks.
+
+        Args:
+            spatial_dims: The number of spatial dimensions.
+            in_channels: number of input channels.
+            out_channels: number of output channels.
+            temb_channels: number of timestep embedding channels.
+            num_res_blocks: number of residual blocks.
+            norm_num_groups: number of groups for the group normalization.
+            norm_eps: epsilon for the group normalization.
+            add_downsample: if True add downsample block.
+            downsample_padding: padding used in the downsampling block.
+        """
         super().__init__()
         resnets = []
 
@@ -719,6 +733,21 @@ def __init__(
         downsample_padding: int = 1,
         num_head_channels: int = 1,
     ) -> None:
+        """
+        Unet's down block containing resnet, downsamplers and self-attention blocks.
+
+        Args:
+            spatial_dims: The number of spatial dimensions.
+            in_channels: number of input channels.
+            out_channels: number of output channels.
+            temb_channels: number of timestep embedding  channels.
+            num_res_blocks: number of residual blocks.
+            norm_num_groups: number of groups for the group normalization.
+            norm_eps: epsilon for the group normalization.
+            add_downsample: if True add downsample block.
+            downsample_padding: padding used in the downsampling block.
+            num_head_channels: number of channels in each attention head.
+        """
         super().__init__()
         resnets = []
         attentions = []
@@ -792,6 +821,23 @@ def __init__(
         transformer_num_layers: int = 1,
         cross_attention_dim: Optional[int] = None,
     ) -> None:
+        """
+        Unet's down block containing resnet, downsamplers and cross-attention blocks.
+
+        Args:
+            spatial_dims: number of spatial dimensions.
+            in_channels: number of input channels.
+            out_channels: number of output channels.
+            temb_channels: number of timestep embedding channels.
+            num_res_blocks: number of residual blocks.
+            norm_num_groups: number of groups for the group normalization.
+            norm_eps: epsilon for the group normalization.
+            add_downsample: if True add downsample block.
+            downsample_padding: padding used in the downsampling block.
+            num_head_channels: number of channels in each attention head.
+            transformer_num_layers: number of layers of Transformer blocks to use.
+            cross_attention_dim: number of context dimensions to use.
+        """
         super().__init__()
         resnets = []
         attentions = []
@@ -863,6 +909,17 @@ def __init__(
         norm_eps: float = 1e-6,
         num_head_channels: int = 1,
     ) -> None:
+        """
+        Unet's mid block containing resnet and self-attention blocks.
+
+        Args:
+            spatial_dims: The number of spatial dimensions.
+            in_channels: number of input channels.
+            temb_channels: number of timestep embedding channels.
+            norm_num_groups: number of groups for the group normalization.
+            norm_eps: epsilon for the group normalization.
+            num_head_channels: number of channels in each attention head.
+        """
         super().__init__()
         self.attention = None
 
@@ -913,6 +970,19 @@ def __init__(
         transformer_num_layers: int = 1,
         cross_attention_dim: Optional[int] = None,
     ) -> None:
+        """
+        Unet's mid block containing resnet and cross-attention blocks.
+
+        Args:
+            spatial_dims: The number of spatial dimensions.
+            in_channels: number of input channels.
+            temb_channels: number of timestep embedding channels
+            norm_num_groups: number of groups for the group normalization.
+            norm_eps: epsilon for the group normalization.
+            num_head_channels: number of channels in each attention head.
+            transformer_num_layers: number of layers of Transformer blocks to use.
+            cross_attention_dim: number of context dimensions to use.
+        """
         super().__init__()
         self.attention = None
 
@@ -966,6 +1036,20 @@ def __init__(
         norm_eps: float = 1e-6,
         add_upsample: bool = True,
     ) -> None:
+        """
+        Unet's up block containing resnet and upsamplers blocks.
+
+        Args:
+            spatial_dims: The number of spatial dimensions.
+            in_channels: number of input channels.
+            prev_output_channel: number of channels from residual connection.
+            out_channels: number of output channels.
+            temb_channels: number of timestep embedding channels.
+            num_res_blocks: number of residual blocks.
+            norm_num_groups: number of groups for the group normalization.
+            norm_eps: epsilon for the group normalization.
+            add_upsample: if True add downsample block.
+        """
         super().__init__()
         resnets = []
 
@@ -1028,6 +1112,21 @@ def __init__(
         add_upsample: bool = True,
         num_head_channels: int = 1,
     ) -> None:
+        """
+        Unet's up block containing resnet, upsamplers, and self-attention blocks.
+
+        Args:
+            spatial_dims: The number of spatial dimensions.
+            in_channels: number of input channels.
+            prev_output_channel: number of channels from residual connection.
+            out_channels: number of output channels.
+            temb_channels: number of timestep embedding channels.
+            num_res_blocks: number of residual blocks.
+            norm_num_groups: number of groups for the group normalization.
+            norm_eps: epsilon for the group normalization.
+            add_upsample: if True add downsample block.
+            num_head_channels: number of channels in each attention head.
+        """
         super().__init__()
         resnets = []
         attentions = []
@@ -1104,6 +1203,23 @@ def __init__(
         transformer_num_layers: int = 1,
         cross_attention_dim: Optional[int] = None,
     ) -> None:
+        """
+        Unet's up block containing resnet, upsamplers, and self-attention blocks.
+
+        Args:
+            spatial_dims: The number of spatial dimensions.
+            in_channels: number of input channels.
+            prev_output_channel: number of channels from residual connection.
+            out_channels: number of output channels.
+            temb_channels: number of timestep embedding channels.
+            num_res_blocks: number of residual blocks.
+            norm_num_groups: number of groups for the group normalization.
+            norm_eps: epsilon for the group normalization.
+            add_upsample: if True add downsample block.
+            num_head_channels: number of channels in each attention head.
+            transformer_num_layers: number of layers of Transformer blocks to use.
+            cross_attention_dim: number of context dimensions to use.
+        """
         super().__init__()
         resnets = []
         attentions = []
@@ -1322,12 +1438,12 @@ class DiffusionModelUNet(nn.Module):
         spatial_dims: number of spatial dimensions.
         in_channels: number of input channels.
         out_channels: number of output channels.
-        num_res_blocks: number of residual blocks (see ResBlock) per level.
+        num_res_blocks: number of residual blocks (see ResnetBlock) per level.
         num_channels: tuple of block output channels.
         attention_levels: list of levels to add attention.
         norm_num_groups: number of groups for the normalization.
         norm_eps: epsilon for the normalization.
-        num_head_channels: number of channels in each head.
+        num_head_channels: number of channels in each attention head.
         with_conditioning: if True add spatial transformers to perform conditioning.
         transformer_num_layers: number of layers of Transformer blocks to use.
         cross_attention_dim: number of context dimensions to use.
@@ -1485,9 +1601,9 @@ def forward(
     ) -> torch.Tensor:
         """
         Args:
-            x: input tensor. (N, C, SpatialDims)
-            timesteps: timestep tensor (N,)
-            context: context tensor (N, 1, ContextDim)
+            x: input tensor (N, C, SpatialDims).
+            timesteps: timestep tensor (N,).
+            context: context tensor (N, 1, ContextDim).
         """
         # 1. time
         t_emb = get_timestep_embedding(timesteps, self.block_out_channels[0])

From bd16fe004e8bbe6248fa783cfc5f1883b989180e Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Thu, 24 Nov 2022 19:13:31 +0000
Subject: [PATCH 17/28] Remove misc (#53)

---
 generative/utils/__init__.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/generative/utils/__init__.py b/generative/utils/__init__.py
index 481f0c97..8b6a35ab 100644
--- a/generative/utils/__init__.py
+++ b/generative/utils/__init__.py
@@ -10,4 +10,3 @@
 # limitations under the License.
 
 from .enums import AdversarialIterationEvents, AdversarialKeys
-from .misc import default, exists, extract

From 30059c2d0fe5a090dc322610b37636ec38228fda Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Thu, 24 Nov 2022 20:56:36 +0000
Subject: [PATCH 18/28] [WIP] Rerun jupyter notebooks (#53)

---
 .../generative/2d_ddpm/2d_ddpm_tutorial.ipynb | 359 +++++-------------
 .../generative/2d_ddpm/2d_ddpm_tutorial.py    |  28 +-
 2 files changed, 106 insertions(+), 281 deletions(-)

diff --git a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb
index 1cc7d2e9..45dbed68 100644
--- a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb
+++ b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb
@@ -42,7 +42,6 @@
    "execution_count": 2,
    "id": "dd62a552",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -52,26 +51,26 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "MONAI version: 1.1.dev2239\n",
-      "Numpy version: 1.23.4\n",
-      "Pytorch version: 1.9.0+cu102\n",
+      "MONAI version: 1.1.dev2246\n",
+      "Numpy version: 1.23.3\n",
+      "Pytorch version: 1.8.0+cu111\n",
       "MONAI flags: HAS_EXT = False, USE_COMPILED = False, USE_META_DICT = False\n",
-      "MONAI rev id: 13b24fa92b9d98bd0dc6d5cdcb52504fd09e297b\n",
-      "MONAI __file__: /home/mark/Envs/gen2/lib/python3.8/site-packages/monai/__init__.py\n",
+      "MONAI rev id: c81b9467b43bb14e77956729d10f2aef4d69deec\n",
+      "MONAI __file__: /media/walter/Storage/Projects/GenerativeModels/venv/lib/python3.8/site-packages/monai/__init__.py\n",
       "\n",
       "Optional dependencies:\n",
-      "Pytorch Ignite version: NOT INSTALLED or UNKNOWN VERSION.\n",
-      "Nibabel version: NOT INSTALLED or UNKNOWN VERSION.\n",
+      "Pytorch Ignite version: 0.4.10\n",
+      "Nibabel version: 4.0.2\n",
       "scikit-image version: NOT INSTALLED or UNKNOWN VERSION.\n",
-      "Pillow version: 9.3.0\n",
-      "Tensorboard version: NOT INSTALLED or UNKNOWN VERSION.\n",
+      "Pillow version: 9.2.0\n",
+      "Tensorboard version: 2.11.0\n",
       "gdown version: NOT INSTALLED or UNKNOWN VERSION.\n",
-      "TorchVision version: 0.10.0+cu102\n",
+      "TorchVision version: 0.9.0+cu111\n",
       "tqdm version: 4.64.1\n",
       "lmdb version: NOT INSTALLED or UNKNOWN VERSION.\n",
-      "psutil version: 5.9.4\n",
+      "psutil version: 5.9.3\n",
       "pandas version: NOT INSTALLED or UNKNOWN VERSION.\n",
-      "einops version: 0.6.0\n",
+      "einops version: 0.4.1\n",
       "transformers version: NOT INSTALLED or UNKNOWN VERSION.\n",
       "mlflow version: NOT INSTALLED or UNKNOWN VERSION.\n",
       "pynrrd version: NOT INSTALLED or UNKNOWN VERSION.\n",
@@ -137,7 +136,6 @@
    "execution_count": 3,
    "id": "8fc58c80",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -147,7 +145,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/tmp/tmpibe4moz3\n"
+      "/tmp/tmpke4lye0u\n"
      ]
     }
    ],
@@ -170,14 +168,13 @@
    "execution_count": 4,
    "id": "ad5a1948",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
    },
    "outputs": [],
    "source": [
-    "set_determinism(0)"
+    "set_determinism(42)"
    ]
   },
   {
@@ -196,7 +193,6 @@
    "execution_count": 5,
    "id": "65e1c200",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -206,9 +202,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-21 22:21:20,681 - INFO - Downloaded: /tmp/tmpibe4moz3/MedNIST.tar.gz\n",
-      "2022-11-21 22:21:20,750 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
-      "2022-11-21 22:21:20,750 - INFO - Writing into directory: /tmp/tmpibe4moz3.\n"
+      "2022-11-24 20:31:18,725 - INFO - Downloaded: /tmp/tmpke4lye0u/MedNIST.tar.gz\n",
+      "2022-11-24 20:31:18,795 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
+      "2022-11-24 20:31:18,795 - INFO - Writing into directory: /tmp/tmpke4lye0u.\n"
      ]
     }
    ],
@@ -235,7 +231,6 @@
    "execution_count": 6,
    "id": "e2f9bebd",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -245,7 +240,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Loading dataset: 100%|███████████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1848.89it/s]\n"
+      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1773.73it/s]\n"
      ]
     }
    ],
@@ -267,7 +262,7 @@
     "    ]\n",
     ")\n",
     "train_ds = CacheDataset(data=train_datalist, transform=train_transforms)\n",
-    "train_loader = DataLoader(train_ds, batch_size=128, shuffle=True, num_workers=4)"
+    "train_loader = DataLoader(train_ds, batch_size=128, shuffle=True, num_workers=4, persistent_workers=True)"
    ]
   },
   {
@@ -275,12 +270,8 @@
    "execution_count": 7,
    "id": "938318c2",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
-    },
-    "pycharm": {
-     "name": "#%%\n"
     }
    },
    "outputs": [
@@ -288,16 +279,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-21 22:21:43,351 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
-      "2022-11-21 22:21:43,351 - INFO - File exists: /tmp/tmpibe4moz3/MedNIST.tar.gz, skipped downloading.\n",
-      "2022-11-21 22:21:43,351 - INFO - Non-empty folder exists in /tmp/tmpibe4moz3/MedNIST, skipped extracting.\n"
+      "2022-11-24 20:31:41,838 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
+      "2022-11-24 20:31:41,838 - INFO - File exists: /tmp/tmpke4lye0u/MedNIST.tar.gz, skipped downloading.\n",
+      "2022-11-24 20:31:41,839 - INFO - Non-empty folder exists in /tmp/tmpke4lye0u/MedNIST, skipped extracting.\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Loading dataset: 100%|███████████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1870.81it/s]\n"
+      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1005/1005 [00:00<00:00, 1792.71it/s]\n"
      ]
     }
    ],
@@ -312,7 +303,7 @@
     "    ]\n",
     ")\n",
     "val_ds = CacheDataset(data=val_datalist, transform=val_transforms)\n",
-    "val_loader = DataLoader(val_ds, batch_size=128, shuffle=False, num_workers=4)"
+    "val_loader = DataLoader(val_ds, batch_size=128, shuffle=False, num_workers=4, persistent_workers=True)"
    ]
   },
   {
@@ -328,7 +319,6 @@
    "execution_count": 8,
    "id": "b698f4f8",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -343,7 +333,7 @@
     },
     {
      "data": {
-      "image/png": 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       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ]
@@ -381,7 +371,6 @@
    "execution_count": 9,
    "id": "2c52e4f4",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     },
@@ -395,11 +384,10 @@
     "    spatial_dims=2,\n",
     "    in_channels=1,\n",
     "    out_channels=1,\n",
-    "    model_channels=64,\n",
-    "    attention_resolutions=[2, 4],\n",
+    "    num_channels=(64, 128, 128),\n",
+    "    attention_levels=(False, True, True),\n",
     "    num_res_blocks=1,\n",
-    "    channel_mult=[1, 2, 2],\n",
-    "    num_heads=1,\n",
+    "    num_head_channels=64,\n",
     ")\n",
     "model.to(device)\n",
     "\n",
@@ -409,7 +397,7 @@
     "\n",
     "optimizer = torch.optim.Adam(params=model.parameters(), lr=2.5e-5)\n",
     "\n",
-    "inferer = DiffusionInferer()"
+    "inferer = DiffusionInferer(scheduler)"
    ]
   },
   {
@@ -418,7 +406,7 @@
    "metadata": {},
    "source": [
     "### Model training\n",
-    "Here, we are training our model for 50 epochs (training time: ~20 minutes)."
+    "Here, we are training our model for 100 epochs (training time: ~40 minutes)."
    ]
   },
   {
@@ -426,7 +414,6 @@
    "execution_count": 10,
    "id": "0f697a13",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     },
@@ -437,127 +424,22 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 0: 100%|████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.863]\n",
-      "Epoch 1: 100%|████████████| 63/63 [00:39<00:00,  1.58it/s, loss=0.569]\n",
-      "Epoch 2: 100%|████████████| 63/63 [00:43<00:00,  1.44it/s, loss=0.344]\n",
-      "Epoch 3: 100%|████████████| 63/63 [00:44<00:00,  1.41it/s, loss=0.202]\n",
-      "Epoch 4: 100%|████████████| 63/63 [00:47<00:00,  1.34it/s, loss=0.117]\n",
-      "100%|█████████████████████████████████████████████████████████████████████████| 1000/1000 [00:06<00:00, 161.36it/s]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 200x200 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Epoch 5: 100%|████████████| 63/63 [00:47<00:00,  1.33it/s, loss=0.068]\n",
-      "Epoch 6: 100%|███████████| 63/63 [00:48<00:00,  1.29it/s, loss=0.0416]\n",
-      "Epoch 7: 100%|███████████| 63/63 [00:51<00:00,  1.23it/s, loss=0.0273]\n",
-      "Epoch 8: 100%|███████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0202]\n",
-      "Epoch 9: 100%|████████████| 63/63 [00:52<00:00,  1.21it/s, loss=0.017]\n",
-      "100%|█████████████████████████████████████████████████████████████████████████| 1000/1000 [00:06<00:00, 158.11it/s]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 200x200 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Epoch 10: 100%|██████████| 63/63 [00:50<00:00,  1.24it/s, loss=0.0154]\n",
-      "Epoch 11: 100%|██████████| 63/63 [00:52<00:00,  1.20it/s, loss=0.0141]\n",
-      "Epoch 12: 100%|██████████| 63/63 [00:51<00:00,  1.22it/s, loss=0.0142]\n",
-      "Epoch 13: 100%|██████████| 63/63 [00:53<00:00,  1.17it/s, loss=0.0135]\n",
-      "Epoch 14: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0132]\n",
-      "100%|█████████████████████████████████████████████████████████████████████████| 1000/1000 [00:06<00:00, 155.98it/s]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 200x200 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Epoch 15: 100%|██████████| 63/63 [00:54<00:00,  1.15it/s, loss=0.0133]\n",
-      "Epoch 16: 100%|██████████| 63/63 [00:55<00:00,  1.14it/s, loss=0.0124]\n",
-      "Epoch 17: 100%|██████████| 63/63 [00:54<00:00,  1.16it/s, loss=0.0123]\n",
-      "Epoch 18: 100%|██████████| 63/63 [00:56<00:00,  1.12it/s, loss=0.0127]\n",
-      "Epoch 19: 100%|██████████| 63/63 [00:55<00:00,  1.13it/s, loss=0.0116]\n",
-      "100%|█████████████████████████████████████████████████████████████████████████| 1000/1000 [00:06<00:00, 157.45it/s]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 200x200 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Epoch 20: 100%|███████████| 63/63 [00:52<00:00,  1.19it/s, loss=0.012]\n",
-      "Epoch 21: 100%|██████████| 63/63 [00:52<00:00,  1.20it/s, loss=0.0118]\n",
-      "Epoch 22: 100%|██████████| 63/63 [00:57<00:00,  1.10it/s, loss=0.0117]\n",
-      "Epoch 23: 100%|███████████| 63/63 [00:57<00:00,  1.10it/s, loss=0.012]\n",
-      "Epoch 24: 100%|██████████| 63/63 [00:57<00:00,  1.09it/s, loss=0.0112]\n",
-      "100%|█████████████████████████████████████████████████████████████████████████| 1000/1000 [00:06<00:00, 158.14it/s]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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nM1OV2JkUhRwsdcJqYiaPUUnnMQLTc0irU5rHNQ5r/XE8pjufqlNd628d3WlkJ4Lu4Mrn0e9KtwuBxYncbDbR7XbDNfqtlrRGtPLSrwqEABJxYjU8qLNUq1UsFoug/zQajbAhJK3sWq0WRDXv0XKUW5ATHw6HMHDqkFbxqeBR0WtzDHUSAMmQIcFJkWuBpTt0sQzrrokBv1wuB7FMa7ndbqPZbKLVauHq6iohjlV10X1vitKvDoQkz7mrSxg1Tk3lX0OKsZQygsw6cgG8AID6JNX57YlI1tPjjixL22bTqJSraZjTA7mGOrUMqibK3biBEv2uBJ9+q9+WqkQRKh1y+lDyKplfM7HTKHrU79XpdIJOU6vVXrgq1CfW6XTCuzos1wGSYLTRIIJQY+eWVK+juFcO6DmbLQg1/KlRJtbTuk+oKuj2wRSvDJPSOraREuvi0jbkcdP8ajmhRzRe1BFOjkjRSg5Bq9NauZoMQVDpeQWFAgBAgguyDgSUF+vVBI9yuZwArdXzdAJY/cyCkOVpWeSuGpNnlISiViWDxoyV+x7DrL46EFo3hRVPsRBgzDBQsu4KdafQCuXgMFmCgNOQGYBwLcNWGpvmc2g9ap29uvJbDRgruul6so5t65hWl1Ov1wugYfsBBGCpm2u1WgWfH8Uw66/6sFrVLJOTSttGjt1oNDLH/M1AGAueW7B5x1S51vPAywFTUWbdJbzeciIaMuSGtEQVsBxIGgm6qz2B5k0C1d14zrZB62XdL8BzOFCBru1QEGi8XTmhTg6KWnoPVM9VbkeuqlzO01e1zfwdUzU8OisIVYH3OJiCyjpytbEqymKNJtnUfY/TeO4MjZdyppPjccCAZKo6RTBBMZ/Pg3GjSr3qSOSobK+1SlWZ1/i4OqB5radrqoVO1UCfpW3RcVDdkdy1VCq90Am172ihK2DZJ9545zQ3zgtCbZinI+g5a8orEFTMpQFQY6Wr1QrAy8RNdZdYRzEHAHi2GMlBySFsMoTOcobSqE/R/8h661ICnZxK1kFMdw4ng5fFQwDwm+XT+W6fZbmvJ2GodtBYo4ph1+iwj7y2eJIsD50FhFRaGdbRbBXg2Q2h55iOb90G1gOvuobtYFXslWuwXBXVwMvMFVuecga1ipUjq1JPQDJKUy6Xw6TgMXX6qhNYB19TzbTuKhW4g5blOjqJqDMSTDoZOE5sk+pqCipyQpajYt9KKDVQrGR7U05It0W9Xke/3w8gUlHDBmpMstlsvpjpLI+cQX1rPBfjsiQ2XEGpAwc8x28VfNbVwkFgXbSe3jfB5FmK1tWj19RqtZCGpu3mOQUZNzLX9mhfkxPTmuUe01QfCDCOl05iTpJOp5OIAHHi6oSwy3ZVUpCKWMkngZAVaTabIS1IuYnNtlA2zw7XHLzD4RA6UC0wXqNuAttoBRT1FgW3/tZdTYFkEoHOXnVZWCtUSdtnrUdyNHITilpbTz5Dxb8aGlZPBZ65jdUR2U8EKstj32o/qrrCMvmt4NZxtfp7lqGSRUeDUENhg8EgcEKtGGc1G6UKLwPmVmzaCMXhcAizn/eqX4+DQOAqp9EO0dCZDfqry0Kzm0ulUuAMXgfz2TrZlJPZ9Sua4WInADmhinCmU9lBB5Kr42ihs/36WjEeK5fLIZGDWUXa73bJgraFDMOqVGkAfBPr2OoIKnr1PH97Yk/LUp+d9yxbDmcxOYxe5z1HOaPqmcp9NWNZVQDqaiTrgrEckB8FdWy3B2sxWxeN6o/KWawlqrqZWsd6nGPE/6rvefomy9awZF4x+yY6IRtHHY6hHRUxNkyklifXlmh5vJeWoc52r6PIKYFnPY96pvXsVypfsj6sP26/34d0Jc1S4ezvdrsJTuBZt97yRltHjUsDcatd9TwrKVS1sfqZJiAwvGavpZGluibL1uwc4CXgVLyq31I5op2ceelkwySLLQN4MdsIMm9QSQowXsNOUrCoP5DWpnXD6GDauquo0zrzHEV1jItTxdD6klTXtKvsNFqhCakKtLQP62O5H7md5WB6rW2vfrRvbFvthNC+987npaNByE7kqwrUH2Ybox2mr6vXa9WKVtApR6QVqSJSOQSQdHpzUHhOxTHv4Tk+g4PJbxpSfBavUU5Ly9KqBcp16K5SDmzdR95WKLZO2kdqQauuTfeL6qy2v9WoYfvtuOm33mO9Dl7b34QTKldSZVsrrcosLWENylsQ2qiC+qeow9CBqms3VBzpIFmgWVFTr9dDTNZ2qOpOTFrQa1QX1EHWflDXjHW8q+LONjERl2DkIiavXdpucmyqRGyXbrnigcICjGVaCeQBUvtT9fkiHJB0NAip1+mgMQpiK6QGiiXlGqrgkzjICipyAN6vnIvHlbPZcBc5l01OUD2K4GHdODC8Xl0qBCfLBRD0Pz6Dm5DrSj/WT61QGkr0BqjeyOd7biJ18ivH5lipCqNcUK1tK169sVIpBSRVLTtR8gLyJE643W6xWCzCYFgFnh/VN1T8kLMRPAoWq+dog6xCrNyJbg4dCPWT0aom9ymXyyGz2l5juaJ9lq5JUdeS6qeMtzKG3O12gzqh7eAg6zeJGzZp31N/5PXqOtEJo+4SPaeLvjwuZvU81pNgixkg2kd56WTDRN0QnBVWLNlG8T69hmEuK0oBf0thK/YVhNqpygnJbZfLZSJ6owt2VPzy+TpBVPxqBgrBrD5FdbOwHvTp0VenCQzaHgAJcW8BQhBaB76d+MrVVJ9jvXXC6viQtDzLUOy1x4rks7xqVvWzc5BthHIKnWl2llpdzlqE6tCtVqshQ1o3WNLVYgSsTV/XJY+qCrCeKi61XlQFNNRJ65uA0ms1xZ59bY0CjU0TzKVSyU3YUCnEPmbfWGB5jMSWYxmMN3Z56KtLagVezjB16QDPnUwqlUqJDraGCv9zUDn7dT8YfbYOtHWnUMwq5yGpCLK6F39rxjaNOl20r8BSLqu6p+d98IwIfa53Lsa5tM76X5+plPU/i3KD0EP9MWQ7Me8zPT+fRzGuTEuV6VKMdatPTcWiPpMgVD8nDRPgpVvH6kTaZqacTafTwJ05MXTpZKVSQa/XQ61WCyvePF0rZgSo8Wa5p0oG635SwMbEekx3PZbenBOeCuJjSTmeckfr87PiVS3m2GBbQyxtcFSF8EJ4yu04oXRxv+VIaSJRy9PjKiFOYS6Wwx5LuUH4HuDJeqaKFPUFqjhRY6LdbqNer+Pm5gbNZhNXV1ch4E9Oo7pbpVIJOZJWhGnKGXU5DoYNWXr6ohoTlpOS+2rSLLc1YeKHOr/5TUMjBlTWw6oq1mDxjEtvLN4chF8TKRhU8QeeQajnKeJoFOg6WholqodpRou1XlWU8R7dMgRIxrG1vvwNJEFo28JrKO6Z/cPJESPl9OwLfabl8B54YpxcgWgBaXXGonQSCIvod1nkiTVrFVsfouUieq1atPzNtcRcY8y3mxOgOkB20x+KUQWmXUjEdmj/2LrzOP97Fj7LUHcWgU1uR71Rd0GwkRELfJapE1WfkwUkra89fgq9Gye0M86Li1oOofqbppjzfhVpTLRVDsjcQA5gv98PHFFFKkGs5dHdYV01rIMFkQWUx4FKpef0fquLUickaHTC85kKPutL1H7mM9W4SouK5KFziWLgjUBoOYLVS9Ri046lSLQBfBWRKo71GfTB6Ta3TPbkc7mXnm6MpA53Dzg66DFnMpDU1TxRq7ql5eq8hmE89gH1V62D5yayOqHWx+OKPK7XWCtZ77HRFD7Xlp+XXg2EWnkv2mC3IFNwETi9Xi9xjwJO89/I3XSgNRqiIgt41pW63W7ghFxzQY6ni4Msx9aJos/WzBgLQjuYBB37ygOhbS/boqqAJz2s89nT4fTb0wM1LGetaBv18sa8CKc8+S2fKlqsSExzhWgqu41q6M6fOjgsjzoe8OxuIKhJ+kwVtTaCQIex5ifqNZ6jXEmB5PWRAknborFjXpcmUi0I0vx32j7e45UTA59+63F7baxPYsdidPR7THTWEVzqPiBYCAJyDv7WFCcvzMZz2hh1n1iFnNd6g0SwUbmnrsV3qZTL5USCAK8HnrOI2VaNljA3Unfx0n5RTk/Oxa3XyKm1zZojCSCxC6tugaztVCtcDQ3l5gpC62T3jKAs8iIw+l2UjgahAkCXGKqSbPcyITB1oRNjtVasWA6mOqHdnEc5LDtIrUmKFbtLgw6wHUBV4oGk9c6Bt8YUr+NHB4bclvdaka19a9UYHXT7PL039lvLYxkKtrzRqBh5XPJVxTEHnW/u4Xa83DrM0/Esx6xWq+j1eonzdtd51XuUU8Z0FA4Mgat7OuuCdOUQy+US5fJzPiG34+VAaYcqmFkn1s++XcAzssj51+t18FWqKuK1l5yR+YUk1Sc1C1vBwP4nqfGmFrld8mmjQ55Ron3OZ7F+lUolMfntIjEXUwUxGAaIEQOCjzFOq/dYEUXgMW5rlXG1Jq0xoxxGydORrBhWzqhRFYpl4DlRVwdMOavWje4adYyzf3hMB8qKU4I9MRj/X16lUklMrJghYY0Ptew1H1LvUU5q79djdjxsf9v/limwv84KQlZe3R3dbhedTgf9fj/oOTqDaHkqJyM4qcNZUHiz3IJSO0WjCvymmFXw6dZuBASNI7aJe9pwkijodaBYB88wUE6mkRd+s+5M49d8Q83UVutbl0XQG2Cd8+TyVrqoWsDfyvHJuTTxVQ2pGCfUa0m6Z81iscDhcAjbvaRRYRCqvkaQ2QHj9Xa1v4osVZI1IZb3srPU9cGO0JmsnAoAFotFAoA6M3UNMMtSVw/XrlAdsFyaFDvGb6t+qK9TQajAVktWs6Z5zOqoth90tR77z+p+2lZySjVItExP5UnTG7UOzFTPq2ceJY75UM2oZqNthTg7bBYyX+lKbhBrFMtV0LFcNphcRbmLV5YdwF6vF94+5IlAz2DQ1Hzdi4VSwhpLajBRH+N/9hcno0qGcvl5XYquMSFA+OZTb6Iox9V2sDy+HYrjoR4DzctU/V7BbC1oHRdKHHLCPHTSGhMFYkxHsSJVBwNAeCG2BZrqaiTdooObVJLzsRyCXgeCZC3Y/X6fePmLJa07y2MsWi1ytdo9EGp5QPJNUMp12Cd0Fy0WiwBC1fF0Aui3Wr92HPT56hEgeNRtxT5iGfxtk30VfBrf5ovOzw5CK/b0hYZ0FFudUPUSC4iYVcdzKjZ5LTuKYlOXSXJnfs1g0QFWdYGcyxou5fLLLdxU/aBLifqsttszoKxOSdJyvcminMZrk4JNvQaqd3vjp2Bhe/lbF+UrR1aOqpY0x8cm/HJ87NKCNMoNQlaID+Y73yj+VJlXV4AVDdQVKI7tILCTlL1zJyse43XaAfq+EOU0usuXDcHpO082m02Izeq1HFTdeUzfaMRvTw9THZnHlKOqvmjbrRPT7vTPyU8Dj+Vq5hDbr/1FaWH1PwUh22xDkMrpOOZcaUmwcTJoeXmokDhW1k4OR/2ESq9aVowksILc65kN4XFr7eps44zTwdGZZzmqdiZntFpzKiZtTJZWslr6OvDeR7kQSXUtrw9V7aC1a10pvJbHrNHH8+RovE7vU6NDdXQFoZZDUh3RswGs9FEQckLZvYbSqLA4pmnPilI3U+7BASHAFFjkhDFry848PtvTQdJmGjmgDiSBw3zCXq+HZrOJfr+PXq+XWHeim3gCCNtrtFqtwC3Vj6mAVxCoSLOiTUNwQPKFOexr6oKei0q38uX9Wmf2J69bLBYBXLEx5jn6S0mUGOrqsiKX3Fh1zDx09JvfrUuAg+BZbKqL6AsCbZnaESpqSXaQ00h1Loopcjp9aSDFLJMmlMsBL0NelixX9rg168Pr1TWipIaTclHLJQncmDFoJQtBqLpajBHEuLcXebIeB/payQlf3TpW5ZSzRkUvGxSz0BSknkvEI6+DLFHcdrvdsE0atzHm7gfMsB4MBmg2m+j1eiFjR8OK1G90wKgP8TkAgjtCAaikhg73idHJq0YUn8O6WKVf72V76dCm20ZBrLqgfWcyJZnW1wJUDVLeF1OL2CfqrM5DJ+UTerPJc8jG7uX1+l/J4zxZRG6mr5llbJtimG6ZTqfzIrPaczCrPqRuChLFnwJW++JweH7FrepZ2hextqZNUAUxJ4GqP6yvRorI0Qhaqx4peLWtqk9aA4rflD7cqS0vnfxuO++45yg9hmIA9VK/qMvxzZ1XV1cBZFy/q+/0rVQqYQcGuw9OtfplZR4HVK1u5VyermfrT85EkOue3epPJCmH0W/lNJxADJ+qm4Z9Tl8dOSCtWXKp1WqF1WoVvBzW+KPoVTXK6oTL5TIYKDxHoLPcv/3tb5njfPJCJ37rAFjO6B3PS97AUs/TQWH04/r6Gs1mE4PBAJ1OJxgS1AFVwWcmiwUV8OySsr41r06qhlhgqoOeHgL1xVHk8plA0pltxR6fpfqrjVSpw1gd+fw/nU6xXC6xXC4DMNUHCzxHslSfpDhneTR05vM51ut1KPPNxbEHRCtqjyXrbNbUdjUuarUv7y6u1Wq4vr5Go9FAv99/sVE4LV41FtgGPU6RBSQ3A1Xxo6LQrju2eh7LUT1OHcLqfmH5th84+ZSDWn+eikpyOYJuu91iNpths9lgPB5jPp9jsViEY/T5kWuSuxGM6/U6wQn1WjVarPM7Dx2d1JrnAaeAkQOoISnuH00O12g0Eu6WWq2GwWAQ4sGaWMGECzrRbaSEpAaXWrx2W18V3RTvJAWo6pVqafNbr2WfEYQ2EqKWvaaacZKoQ5lcbr1eYzKZYLPZ4OnpCev1GsPhELPZDLPZDJPJBOv1GuPxOAFYcjmGSNXHywl6LjraRVOU0gwQkg1nUX+iOCUImVCrxgY5IcGoK/VUZ2JdmDQAJPeRtgkR5DTkAvyvdVVfnuWAChZez980WHiM/aMgpOtDEyeApB9PdTj1CU6nU6xWKzw9PWG1WmE0GmG5XOLx8RGTyQSz2Qzj8Rir1QrT6TREwgg4lqflnqLjx+jkhU5ANihVl4ldq5kpjF70+33U63VcX1+Hl1xTFNO/1263gy6o2ckUHxxAAo8Dr/40bkLJz263w3w+f2EJahzcul3UvaNAVC5GAGnyqiZ9WsubxggNEXLA/X6P2WyWcK0QLORc0+kUw+EQy+USd3d3WK1WuLu7w3w+x+fPnzEajTCfzzEejxOGxLF0iu5/sk5YlKziTsXaLtGkK0WBxrit3Z+ZYACS4tTOXHVlUGSpyFEdiJaftRZDx1WrYVNM5Wzkipa7qeMeQEKn8wbf6pWqW1IPUxcYRSaNg9lsFgyQyWSC5XKJ0WiExWIRuOBisUjEk89FedU10kmpXEVIoymVSuXFK00VXHS3UAwPBoNwjSrndLuUSqWw5Zp1LajRYf1m8/k8oVgreJUT6jVqpXKycL0MVQDddFMTFFQX1Mmo3NWqDKpKaF0oPtlWWqiTyQSTyQTz+Txwu8+fP2M+n+Pnn38OeiDBdy5S/f9NOWFeYoeqyOJOAgQauZy1Zq0+pImkOpjkWBrXtDFUDSkpJ9SQFgdZ8xOpK2rYi1EK1qNWqwWgEfgq8glAdc/oxLAJCgpKLwynC7noLqFup/reYrHAeDzGcrnEdDrFfD4/OwBPpVcBIQdBOQM5HXUbhs7sOg92Ou9TkBFI6uJg8qSC0LoUdN2JfvO8JsnSz0VOqFanRkTUMGFbrq6u0Gg00Ov1wsaW+m48+jVpoauLRbea40e3/OBEWa/XWK1WmM/n2Gw2mM1m2G63geuNRiM8PT3h6ekJP/74YxDD9n0zr0Vp0Z8YnR2EKl4IMjqMuSegglCzkzXrRaMMQDJ/kKROXHYuuZx1LVgwAngxsMvlMgyUBaFayupbZJiKBgb3M2Qf8FVmygnV9aNc0eqAauhwopEjc5LRqKLvbzwe4+npCcPhEA8PD8E6/po4n6WzgZCgU6dyv99Hp9MJH+UMCjCrF6lSrnFNBujX63WwMAlAcjVyMjpbrbtBMzyUE9pMbftGUC8ESeAweXe9XqNer2M2m6Hb7aLf72O/3ydcRwQrozFUR0jl8vM7h/Vdy6wn3S6z2Qzr9RqPj49YLpe4vb3FZDLB/f09Hh4egjhmm79mOgsICR6KDnbszc0Ner1e+NDitY5Z5QLqY9PEAOB5s0j1kZGjUM+ZTqfBylVOpxauimyNi6o1nHfgWB/geTE9Le7dbhdUEWZAMx+TE4wvICJpHJzckyBcr9fBAKEOSA74+PiIp6cnfP78Gbe3t4FLvjVZ70ceOjsIaVAwAZShM3I4G0XRMJiWR3CoS8W6EihabVxUs0Vs9ocN1utxdXnk9YEqEbxc1VatVjGZTLDb7dDpdBKcXcU5jTE64O0CKfrxGGpbLBaBA97d3WE2m+H29hZPT0/B+fxe4vcYffOsIKTfTrNXqPt5ia9aaXYawUCvv4JGLVjlcvSP8R4FoYKLXE7rnadtSt79ypUPh0PgVsCXRWDb7RaDwSBhiADPW3WQWzLfUbO6CerxeBws38lkEtwunz59wnw+xy+//BJCcLHYs04w1UXT2p4XVHbSvomf0D7cilMq1BopsaIXSC7iUZcFgWVBaD8En+p3GufVLJSYiPXAGBsAe63+1xixGh/k6pqkquFJXfdCcQ48+zzJBenjm0wmwRqm24WTMU2NsDr2ua3kY8s7afE7/6tbQZ21FMM0AtQyJVfQyAaBqr46daloRgv1Poav1P1StDMsh8hKvIgdt2tEWFfqcJo8QbXFbuK+3+8xnU4TE+rz588YDocYDoe4vb3FeDzGv/71LyyXy2ABZ4lgnfynGirHqCppdHYXjc4yBY4CSIkdbTmH5YRahopia1AU1eGAYnHPLBFuOaMOmA4+uZ9KCvVfUg/kt2a9TCaTEHLTPsjT3rwGQ1Ff3ymALAxCz03BDibAVqsVSqUSZrNZQum3xoFmbdjMXHWlqMVqvzWt6NiOUBHqcXr9zrofeM781u191SBhQsJgMAguJzqTqQNut9uQgPDTTz/h4eEBd3d3+PHHH4M1TC6b1W6tX+zaNN3XK++cdDZOSLDQu8/ZzJQpC0ZdQK2GhA1JWc6apdMcKyoskDyukbdsq6LY/ELqzAz1aTazcsLZbIb5fB6432QyCdYvXVJ52/maUZJT6SypXBQFBNbT0xNqtRrm83lYXWatVDUkLECtIZE2e62hoxzMc7eoAZVmHXqA856lDnb+p8VLbwE9Be12O2ynx8mq6of6L1erFT59+oTRaITb29uQA/gaDmiv/96Sjs6sZucrl6Jux8QATXWyAXvdiUE5HJAOOmu1euLSnrf3aFJAFtC1zBhnVB8n/6u1qwkaNED0+aoDcmLS6BgOh3h8fAzWMPXkU6zbNAv/PegkcayzUd0S3JGBQXpPn7N6Hsuw5HG0PGIzTb+zwEsrK1Yv7z4mVlAX1BxIvriHoTiKZd7PePVqtcLDwwMWiwXu7u5CQsJsNnux7caxZNup/4vohueik9P7lZUDzzuQAskt2LzZG+NYtkPyWq8xkRIDoS2b11oL1yOPE+l6Fo2CcDdbpqqpO4v1USuYjmfGg2ezWfCHngsUWRPfu/a16CxLPi2YVMlPEx15BlvJE8P2fB6xmvY/j+M6pg7oElTqhMweshlDBB4NMSYl0BFNo4SqzTk4oEfWICsSJTkXnf0Fi56VqeCIAc8zALxz9tl2IhxrMac5prP0TRJzApm61uv1cHV1FdbG6DZ1qj8zHf/h4QHj8Rg//fRTyIJhJOQcwEiTFDHV5S3oVdeYxHQsIF3EFnWoxjjkuUVXVnnKBbkuRjPANVrBGDqtYq6OY6oWwXdODpg2Hmn3vDYdbR17/z0XBjs9dk+adWoHP6Y8K+dNW9Wn9fKAn1YHrx72fr7R4JtvvsGHDx/Cf4IRQMgE5yKu2WyG4XCIz58/45///GdwRNOBfW7KUovew0Xz8qUgGZQngqCU1ei0Y1n1sKLdM2i838dQHge13XZON1JXp7XmSzLzR1O17M6sb0mn9tMxdBZOmKbPeeCwZcUczpa7pdXF+gMtd47VN9Yuz9iK1ZO64GAwwM3NDQaDQWLTTX643KFcLgeD4/HxEf/+979xd3eH4XAY1rpkUVELNg+wslxRr0WFOWEeyrJi7XVpLpk85ZC7nIvD5v2vk0QXdOkLvzVJlU5r7g7GZNzJZJLQBc9NebwQaRLjtTnjUSCMuUK84zHXhvfb09Psh8djlKfDLGDzThTVNxWAKn65/w0NCl3ExfONRgPL5RLD4RD39/e4u7srHI7zOHKR9njleGUUVb+OobNYx2mmf+waT/RaYOi11nDI8mfFzlvxH3u+d5/XJuqCGi8ulZ73jS6VXr4RtVQqha06ptMpnp6eQiJHXsrjdiLFVJIiXgjreovV5xg6i05YpCJZrD42q7M4rHaq7bSsCWDrEdMtFbAa9dDXQTBuzOQFimOWw9jvaDTCcDhMpORnTay0fkqjY61f2w9eX6Y9Ky8dlVmdB4RpVnHWdWnultiMztspMZUgq65exo1GSHS3VxW7CsL9fh/2A3x8fAxhOaZlpU0O3m/bzXN52pXW3jTO6BlkXp/nVXEsvfo2IB5o84gCO/PynC/qjM3DedLAbcUxndJ2+47D4Xm7N64Hmc/nIWHBJnF4/khv4M9hEeeh1zZMTs6sziua7X9GDHjO0x+95wEvNwxPq1+WU9rObk/88jo7061VrJnUmpygeZMPDw+Yz+e4vb3F/f19WKKaRzWw7bJ1itU3r6/Wo7SxiDGKosZMYes4j06R9+Exq/icdclLWYNmn6sg1H1ktDxNdmWiAp3Sur9z1rPORWngOJbbeSAtWuejxPF+v8/tl7NiJGt2FnUkZ5G1gIGX71mJAVCPW52wVColsqb5HhSKXTVadrtdSMf6+eefw04JDw8PL9aIpLmr0vrC46ReyLSIUel5EexzbRl5jBdLZ3FWH6tX8VzMteOJ59g1Hr2mLlMqvXxPnnIaVRkAJJaoEpB2zfU5ud4x7Skqwc5FR3FCG0aL6QR5AFLEz+Vxh7SO80CcxhWsG8b71h0T+v1+2HdHJQN3l6WhstvtMBwOMZ1O8eOPP2I0GoU0LeqMeSnN2o/pt2mU5l2w3gnldHn05bx0NCe0D80yRHQw00RgjGLK+bH+siLl6zmNkNANY7mevmdFw3PcxoMbmTPj/FhKc13xWJ4+tupAGoizjI5jpM9J2wWnAU9njNcwjyN5emMet0uWqyZ2Lo9vTOuk++3o3tr8zbdI6ZsuV6tVSNXnfjKMjmTtBeP1jR4rAgTrifDa6/WVN9G9/jyFE76Jn9DmDHqmvf63HZUmVr1y7D2xa9OMKDv4XNBO0OlyTkZIut1uWNDOHSSYrk93DBcs5cmWzpogWffEdGo7uaz+7RlzseemceC8XPHN9qxOm336/5zug7TnZJHX2Wrx8nUO3HNRExeoC67X67BajguWiqwXKXJNGufJ6te8Vm0eyVek7qSTFr/HyIoOLvtMu07/p4mbGDeLifA0kW6vSStfV9IRdFxLwrdHkQPyeq6ce3p6wv39fdjY8hyvbIgZamyDpax+S6MYwDw1yss0yqJX5YRp+gx/59FP0iyxNBGRR5eMHY/VzXJC3Z/6cHhed83NzfnR/RLP4eLI8jzkfUYeaZTHQDmlTUdvDWd/e/+LlJfHAEnTkdKuUb3H6oieZRh7NjNk2u02Op1OyJ4Gkhu7j0ajYIz88ssvIUqiQDyF8uiKWWqNpzvz/+Hw/AYuT3+35Wmfajg2L73aKyQA3+ufxh3z6mpp4iZ2/pgJ4pVjN7fUPQnp7+MSTiYo6HvyTqVzTHzel+W2KSKyT6HCIPTCdZY72vPchSGNi3rHPPM/y13glRnTG+0xz5K2ZeoG8ZqscDgcwqsauIEROWJMFBfV67ReMcpyqWQdzyrbs3w9Xb4IcHOD8NTZUETUem6BInpO0TrFfGRp92naFgeeO6ZyG199Y1RMF9R25dGXs6joPfY5nr6ddo0t4xicvFoqV+x6S2miO+sZeV0YHof1vvVZ1In4relZ+v48vsiGW+Lpq1y5m6puDmonWNH22DYVVWtifUHyQnX2Xk+yxKRYHjoZhLaisWuOLV8bnMfNU6TMLNGloocuGiD5njzuMa0vthmPx+FlN/oajNemNBFu2xajvKI7S198FReNOkXTuJQ3S7Mq5F1vy87S97w6ZImRrE7SepOLcVtf3dyS64W5cH25XIaoyDF7aeehmGsly9gA4v5XAK7xlKef8jwjRkdn0eRprAdCNeVZVuzavIve9bn6HM/oSNNfvI7TvWO4kxZf2/Dw8IDtdpvICzwcXm5r/FZUBCyxfvPGxTPi+F/PH9vWwiDURMk8OogOjAIgxiX1d94d6b366ZJLXmfrHHu2glXLK5VKYS8Zfvg+vO12m5hgbwm+ImQ5ZhpHtaqQBV9a+UWodMjZW17B9r0dMbFaZEF3mqKdJkbykgfEvPdxX8Fz7hf9XpQGJOrA/F0qlYIe7KlAnkXN+/PsKPEq24Cci95Clyp6768BgKfQscZhGhU2TC50oXPTV80JL/S/QRcQXujd6QLCC707XUB4oXenCwgv9O50AeGF3p0uILzQu9MFhBd6d7qA8ELvTv8HObncNJ1HVhEAAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<Figure size 200x200 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Epoch 25: 100%|██████████| 63/63 [00:54<00:00,  1.16it/s, loss=0.0124]\n",
-      "Epoch 26: 100%|██████████| 63/63 [00:57<00:00,  1.10it/s, loss=0.0122]\n",
-      "Epoch 27: 100%|██████████| 63/63 [00:57<00:00,  1.10it/s, loss=0.0108]\n",
-      "Epoch 28: 100%|██████████| 63/63 [00:57<00:00,  1.09it/s, loss=0.0114]\n",
-      "Epoch 29: 100%|██████████| 63/63 [00:59<00:00,  1.07it/s, loss=0.0117]\n",
-      "100%|█████████████████████████████████████████████████████████████████████████| 1000/1000 [00:06<00:00, 157.78it/s]\n"
+      "Epoch 0: 100%|████████████| 63/63 [00:40<00:00,  1.55it/s, loss=0.295]\n",
+      "Epoch 1: 100%|████████████| 63/63 [00:41<00:00,  1.53it/s, loss=0.073]\n",
+      "Epoch 2: 100%|███████████| 63/63 [00:41<00:00,  1.53it/s, loss=0.0544]\n",
+      "Epoch 3: 100%|███████████| 63/63 [00:41<00:00,  1.53it/s, loss=0.0427]\n",
+      "Epoch 4: 100%|███████████| 63/63 [00:41<00:00,  1.52it/s, loss=0.0358]\n",
+      "Epoch 5: 100%|███████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0325]\n",
+      "Epoch 6: 100%|███████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0285]\n",
+      "Epoch 7: 100%|███████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0273]\n",
+      "Epoch 8: 100%|███████████| 63/63 [00:41<00:00,  1.50it/s, loss=0.0246]\n",
+      "Epoch 9: 100%|███████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0242]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.40it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -569,17 +451,22 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 30: 100%|██████████| 63/63 [00:51<00:00,  1.21it/s, loss=0.0117]\n",
-      "Epoch 31: 100%|██████████| 63/63 [00:56<00:00,  1.11it/s, loss=0.0108]\n",
-      "Epoch 32: 100%|██████████| 63/63 [00:55<00:00,  1.14it/s, loss=0.0106]\n",
-      "Epoch 33: 100%|██████████| 63/63 [00:57<00:00,  1.10it/s, loss=0.0114]\n",
-      "Epoch 34: 100%|██████████| 63/63 [00:55<00:00,  1.14it/s, loss=0.0104]\n",
-      "100%|█████████████████████████████████████████████████████████████████████████| 1000/1000 [00:06<00:00, 156.51it/s]\n"
+      "Epoch 10: 100%|██████████| 63/63 [00:41<00:00,  1.53it/s, loss=0.0237]\n",
+      "Epoch 11: 100%|██████████| 63/63 [00:42<00:00,  1.50it/s, loss=0.0201]\n",
+      "Epoch 12: 100%|██████████| 63/63 [00:42<00:00,  1.48it/s, loss=0.0226]\n",
+      "Epoch 13: 100%|██████████| 63/63 [00:42<00:00,  1.48it/s, loss=0.0206]\n",
+      "Epoch 14: 100%|██████████| 63/63 [00:42<00:00,  1.49it/s, loss=0.0197]\n",
+      "Epoch 15: 100%|██████████| 63/63 [00:42<00:00,  1.50it/s, loss=0.0195]\n",
+      "Epoch 16: 100%|██████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0185]\n",
+      "Epoch 17: 100%|██████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0176]\n",
+      "Epoch 18: 100%|██████████| 63/63 [00:41<00:00,  1.52it/s, loss=0.0184]\n",
+      "Epoch 19: 100%|██████████| 63/63 [00:41<00:00,  1.52it/s, loss=0.0188]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.44it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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Gw6E9PT3Z/f29LZdLq9Vq9vT0ZMvlMolqiHfNZjObzWZ2dXVl9Xrdzs7OrFqt2mq1SiCEG6MS5HQ2rbtvu+9D/2wEbD85lUPpfb4MvadIp9VrkadDRS0Jwt1u19rtdgLfr7/+ar1ezz58+GD9ft9Go5Hd399bpVKx//iP/0gbZR2iV/sJsXb9QHhrKtcx3AsYYeHoe0QxsMKxysmKwaJut9u2Xq+t1WrZcrm0RqORwIn+SDwTMCqX3m63Np1O7e7uzjabjTUajbQROHXSnaiOFbGvNQJy9x4jav05ryMrA2DdNke4Xa/XS0Ds9Xp7IPz06VPyZrRarcSUut1u4fZxnl5lHaPgK5dRfVBf7v1GPOuTGTAWAFur1Up5gGZmzWbT+v1+Egf9fj914Gazsel0auv12obDoS2XSxsOhzadTm08Htvd3V0S2eRBok5sNhu7v7+3x8dHG4/HiXt6q1kNLo0r/yiKjAPOH2ttRmWb7ftb9Y++bTQae8kd7XbbTk5ObDAYWKfTsdPTU2u1WnZ+fm6tViv9xk5ot9vWbDbty5cvbwNCLz4AkJf7ZdwYyo1UTANsdLV6vZ4WMMEFCbEBTtUbmYnNZtO2223y7eFrxCgha0Y5OfokYPafuIjaoe05ph+Ljrlzh+qR45p6VH2PyU5fnpycWLPZtMFgYK1Wy87OzpKOPBgMrN1uW7/ft2azmQxHQAcIW61WKu9NQUjhDGykByqb97qYcj4Fom6iiWEwmUysXq/b/f29NZtNOzs7S1xQO6tWq9lgMDAzs8FgkJzRgGo8HttsNrPb21tbLBb28PCQ9EhcPLhssJK9O0IHU9t5yG0D5QAdGRI+pe3QgEbXtO6ApNPpWK1Ws36/b51Ox3q9XuJ4Z2dn1mq19jgiwEMnhxFgGQ8Gg7TpgLrTWMvj197k6FWcMPpdpmOikJvX0dbrdXJSz+fz9EUAgInbhVmNEaGdQ9m6DJF0/3a7ndwIZMognne771EayuE9nmsfansZbpfro6JyfJ9FE0Qnj370plarWa/XS+DBJwvYEMN6T6fTScaI9gn9EkXPcLVFXo8cHW2YeJ+fDpTnbkpUSHVI7VRdvwwQ5vN56sRK5btTGXEAN/z06dMLccI9g8HATk5O7OLiwtbrtf3222+2XC7t5ubG5vO5ffv2zcbjsY1Go+SU1k2dosHPeQD0vuh6ZBT4Y876jRJ/uZ8JiFhstVpJLMKRFFj0EcYG96i+Xa/XUyxdxSscFcBhvMAAOp1OclxrUOMQvSqBIQKYR/2hFC//23NE9LdKpZLWFGO9soMC+l+73U4L31k/UqvVrNlsJv/Wbrezfr+/Z4WjbwI6du/STZ20fvx/KECvbTikM+ZEfKVSeTGp/eRWQxGOBLjgdBgdTNRWq5VAqH3XbrcTCAGzlgvQ1GOh18zsxbkfzgk1ZOeVYY5kVEPaiYeSDvwKfu/24TkAOJ1OU6Sj3W7bZDKxVqtl0+k06TL4t3Cy8lt9gdPp1M7Pz9NuDFjF0+k0cWX0VP73u475NukA5Fw0arHqNZ3QyklUxCpo4GC0l4iPckImo7pdMCparVYKmSoI6Sc1PBCzjJWKYVxmALvb7ZbOpjkahMyGyCqjgrg2tHMjAHrnqXZ6FHvWbOlKpZK+HIBljM+w3W7bfD5P4SRmPh3Lwnez73mF/X4/bZo0Go1stVrZaDRK6040bq0OehXZ3sWingSOOd3SczhNlYPbMeiISHxzGBQnJyd7IUcApUYi5zudTgIMINQViPoJOTifjrvPMdT7VITjwThEpUFIoVjGnlPlOhYw+RkfGToRFUUhSGDYbDapA3BcLxYL63a71uv1bLVaJWcqYppBhTsMBgObzWbW6XTs6ekpZVwj9nWHB7XkAaO2T9tbtIzU+1BzEgJAwNUVNN5twh/3IFoBH781FAd3BITqHfBRLfpN2wNzggtqEKEMlQYhhUehH9+BnoNF9yhI9XdEkUhjoPHvkYwwnU6TIxUuCLhWq1VSzAlJMTCNRsNms1lyWCOOAdr9/X0S1bpdSGTE+E/sKghVpHmJQrvg+EgGTejQ+sLdFKj8AUJ0QYDGc4AJ0Pb7/QRQTdH3lrhayX5M8Tww+Yt0YaXSIGTmmFnICRFTEQfMWcwQjdTfx9Bu97wNyHw+TzsrkNWBiK5UKnsRGNqFUUO2jk+w2O12exEcrxd69UPDkWpVqkhTbqJZSb5/8Q4AGHWXqAHBUY0yQHh2dpY4oRoN6lLRL7hyTaWbdwEBVDW8aJf+laHSIIRd40vTivnd+lWB950KRVahiqecjyx6nnebWVpDMhwOk8KNS+fx8dHa7bZdXFykkBSKN9aoihCUcTNLjlnNsKZdTD4fbuP9XgVQYGpbODJx4bj0r4IFtwmittfrpXPoZd1u11qtln348GHvGeXOOYe8Bx0TLko2gQEwyfkj++kQvXrdsVZQ2TedqPdHR1+m/53TGz3X9HXSe3y54/E4ieSnp6fknlE3A6QhLp0cOiiAkMnp8whVx6IcOCAcyyv82gYPQgWSxmtxRKslq/oZQNV25qx33/5In41EsRfZOskOUWkQInJ0jQjRCTgemwqpq8Zvpu6txsho0dCeHr1+4p/RTuH96HeNRsNGo5E1Go3ECf/+97/b6emp9Xo96/V6e52HWwN9iu1E1J/oJ4pyVOqp4k0VfEQlIMHoUDDSZ+qYJi6Oh0AtXr62uts9b6GMO0etXO03T6oaKFPRsfBl6Jh6X2IZelXYLkI9M1WveyvZP0vFPanDNsfVtF7REfHgJwH61XK5THFndbJ614hakbiftG36Tp6nvdpGb2UCQHx7AEnv1cFFNySNHrVDIxy6fIEy1GCJ4vlexcn5NcuS778y9KqN01kfTAPRm87OzvaMEriHOnrhIupri1w8ETg1i9v/8Sxl+T2sAcV2u7XHx0dbrVb2559/2nA4TOlKvV4v+d0AFPFlRB/RFwUVna+KvXIEH3dVn1+ULEF/auYQk5xzWN9sdwfn1gVhqqfqpKBPVG/3gI9A5XGgRPm0S32xh+joPau1ct7qIwuZRpL1TLKAWqAMro+yRCJXkxXoOAWxd3Mo91WOhX5FOZPJJE0O7u12u2ZmacUf79K8OQ2V6UBpZAEAoqdhmEDcq/Vl/x4frUANgKPRbzox1GhCh1XrVTk0UkGXPniOF/kHvc8z4pL0A3p3GTpKJ/R6Ao14enqyTqdj5+fnaebj1iAjhoGOjjRaO49GKrdRwHi3EPVToKrxoJ2Eco+jF9/Yer1OXBLR/fT0lNwd6G/obog9QMPR++vUIKEuCmaA5fVl7ldOSlmE13BMK1D8zrPKpVSV0GSIXDQk8nWq1IrWDZHcUJaOAqF2IiBgNys6hllp9l1HYp2B71hvkDCTFTjeaes3YlJ9j5CahtYYCOWe1AvjgMHl3fP5PKkPpI7hG+R5nmGSqNtEuaUaOmq0MLjqTtEBVs6soh/yYTL1xwEW7T84LECJrFofH470Q0jFOWWoBKtWq28DQs1I3m63KW5LBIGMaCoIcJSdFzkw6UydpTSSjlFHMp3J+0jBItFWP3GhXJJOVDcJpKBhEJgsqA+8Uy1AthUBnKorA0z06MhxreWqtPHGFM8w8NRPPRaIbtX31PXjDSYVuZEPEdJJQt8zlspMVC/84bFjRBQJoZPJxCaTSapErVaz4XC45wQ2e07vQWfEFeLjjyjWNB7wqPhkgBCJ2jl0EGBZLBYJkKqHbjabFG8uMnLMnhMRsEbh+tPp9IU7x//G5UJsmoxlrFn6gHeoakFbABHZy/j+VAp4Aw8QelDobz/RNISowIwMFOV6Wi51x+9K8kQZevVXPv3/LBTfbrcpkYDnaASd5jshaqx2ChwGzhApywocgEQ4Tl1IKpq8L1NFIJwGTkbZkRPWG0K6XQnvxr+njm3qooPLe1QX9gDJjY2KQ32eya3laf/7/qTuRVjwY6u6KO3+4WE7xAmcUENzsP+vX7+mnD71rZFihIWs1iL30GgVcxgMXPcfv9HOVLeG6nFaP4ykXMKB2X7IzOxZf2TC6Tu1wxkUJgBlrlarNCn1COlEw6kMF4Hbe6mhADDbF7eqJ6pbSCniepHrxU8O70ZTUldSpVJJPs8ydHTYTq1aL9IYODJamPlcbzabe1xA3Q3KyhlsOBYNZmArlcre3jM6eyPLD5EXAYhB0YFU/5qG7SIjwetp+k61fv1A+0H0xoKW7+/zuiPv9O/NrfXwel+REaLvVcO06D7q7eueo1fFjlXxV2uuUvnu3CUdn/s1HTyXwUumL3oPnFQ7CGCpWyIKDXk9x/s3fTIBi6i0jXBsnMGpw/6Pwyg30HiwH1iAR13UncJ1X0+d2DoRFXweDJrlrP3t+yXibjl/nxfzOsmoF7+13zAef3jYDvIN0PimmuyeW9E5AMyvJ9Z0c1Lvff6imSWVQKMNvFM7EF1OLfIIIMqltPPNLKkSpIEBNPS71IkSFVFuF3ED1S91suiAE1XiPtqHKkE9lbyREb3bg0cBpuObG28tJ7qu/t9DHFPpVRsi+ZfrDOaIeFZlVcWFWs8MLn9FUQa4iTqIlbiH9HUGRdvBedbcenFE22q1WuLq6u8zewZeBGr14flMZeUm2le8V315amChynjiHpUMRaJfwa4A9CG2omc0WMDEwIMwnU7TN2FIaDlEr/7ye1RxD0IMGG0MIibSrZjJPsqgupsHLNySDgUcfncAJRY8bTabFDXRQdbOVqOFa/SHNxjUGiWzudfr7VmKPjNGt1JT4KkBxfPo4V6soqvqxIhAWCSCiziXcjoVueqbZZsVXHdkqJehV8WO1evv/Ws6u7zlGDWUc+o6wTHudQp1qnrlG4qAqms0CPLDcVl/olxXLW7Wleg5rwroNeWGavFq2K1SeU7Bop80IgPImGBq5ap6w7vNnvd39IDRfi4Cpd6j4FbjU32RKukAYRQyLUOvTmDwemEU4fBGgXJObaj+1s7zoI8U/pz1p8BA1xwMBlavPy+TNLO9xE/EO89pIF7jo5Gel+OMAFIXp9fr9bQGBi7MWhm4uN7LOzVi5GPR1Nf7P+kPT/qs9yaork9EzCefKBgxRikLl5iXlDl6tYuGCnuweXB5PQh9R2e12XMoLXIDRA5UFUNeP/XKti/L19mXq7/Vz6jhOl9WNCFUB/YuG7i+inzv7PXSR61kv1eij4rkRG80aXXya0IIUasIhMp82EaPcvgqwg8Xx6qQ6poCb1maPYdwfKcoCCkTivxhXpxAkftCy+QdOvDKHeEkGlL0k0h1NgUKDmTVwTQi4YGhqgDWtsaCNe8RcaxWPVEf9cuaWdpljHcrSOlv1S/3Bt1xbOVe7ErGemtS8QAkYVB9D7tZcP/19bXd3NyU3jb4KBDSIM911Bmsx6LZqI3gHEfPTSKDyIsPtSR1cFTc6rdKOJL1o2IY612jNoAN0Q5QFIzeEa4+O3UZeTUD0vvRt7XvdSxyxob3KUZjiA9UI0rE09mTh+gUnFBB6Jc3zGazJJKXy6WNRqOUEleGjuaE6kbIeeQhb7DoTPYdSxkMNEBQQMBtvJ9LuYha2ehXgO309PRFMgGAAiiqj2nbaLvfWUDrqeKZa5rg6sUkxhj3+TXFiD04J9xf+49zKkZ9ZjVuLDUit9vv2+dNJpO0qSiJKXBF6ugjY3BugDoajWw+n6ftl+/u7uyf//znj1/8rqSiLgJh5Pk3e14A5bmf/o9DW7kQgwOwlBNQtm+wxp/hfGqYaEaL+hZZm6uuH9ps9pzRwrur1eftizUGTnupc+Sioa+47tP96TvvbPdjoZIATqVjgSWt1i3ZRGyNjEsFEDLpfBKxumZY4+1BOJlMkjgvQ6VBqIkGiDnfadpwZqcXC+pi0KMfDABUq9WSNat+P45wJQ9GUsN8BAHQeI7z9PS0t8OBD8Br3Flj3Wb2wq8ZAQTHLf2n6V5+/z+VOjppqbs3JACWmSXfrFrJgJBUNrjfbDZLYpMdJ9T4WK+/7xXJH/mj6I18S4bz1Gs+n9tisfjx1rFPqoST6CDTyfyvPiNV9tX3peXyW7mYci5dP6sRCR10BgVdj/epRamLwJXrqH9Pt7qgvbQ9p4cqp6b9qsL4e2kTgAfc3vL1LiuVAoCNPvaGhNYXYKGzscH8er1OaXjUmfVBAGqxWNhkMkmbRXENvVHXwOgOvj8UhBAv1fUZnU5nbyYzsz0HpENUz8NJ7I0X9DkVz8qJdBB1ABkA/vdpWmpEAQh2+TezFDkBvOhl2gY9KvjgiBCDqnUmqVfdUTjDIZ04ao16FYi2qIgFMMvl0iaTyZ7+zD3D4TBxQNwrOOV1FzK4H5xOt1ZW57r2F2OnjvNDdHTsmJfDUdiMEfcDGTJFRgviTkGo/jhmlUYb1Fmr8Vm4mo8+oDQrwMxsj5Oi1GPVAXzOY/lp7qS6h/jzCQzUgwHD6EB66LMqcr2bSkUq7VbRrzo3Vux8Pk8x3Lu7uz11CCkxHA73dqYFsOzbjZ4HQNX94lUoxYdXq94EhHC3MqwWbqOzV/UyzThRTqJp/TRSY6JwM+Uiu90u6SCz2SzpNOhH+NRU59RJwibriE5UAR04FX0ajqKO6iRXFcWn97NBpV+mybu8MaD96QFLfdDd0O0mk4lNp1MbjUZ7flTE8f39fdIL8fHhXFbxrLqll1IehJ4bqivvEB21SSaFq/VEBbRyqgPC7XSLC+9PM3tOKiAGCcDUx8Z7IdwEyvmY0X6NMpxbc/+oNzu+zudzm0wmiQsrh4U0j1K5l4pJjfmyg+r5+Xnalk4d5Krf+U/rKrcEgPQ3IKSt1P/h4SF9lwVOyDOI4OvraxsOh8mSZWkGDECBp2qLd/rzG5VAJ5QH7g8BoffE6yo7Yp9UGNCSPQ0Y1ADx7hnS3lFy6XRtcLQvIPcrCPW8dqb629TIgovQwZoc4H2AkEZjNMYLCPnDF6mcT8ujP9H96Ft1xkeqDf0DCNHdACOfXlMnMyL24eEh7TwL5+Pd3oXkj4oFJa9KcF8ZKg1CZiaKNr4l9IZ6vb639FGjCDh4I85C5QGwhp8AIc+qboIug9iAI2rHwwF5r3f5AB51wCsQ6/Xnne+51+xZr+TaycnJngsJcatZ4nxqy1vltAdRqJwQAsje54dzeTab7XG/u7u7lNe3XC5Tbt/Xr1+TW0W5uVrv1AsPBWDyngTvauM+jdb8cBDyEo7oIVSc2Qrn085msY/OarP9WaahKnVrqDtHA+lwL/VVqViGC2qHksKlUQStK45h3qnuGuXyZpb8e7iJuA9rHtGvxgr9ZvY8qVV3VatTVRoVwyqa4Z70h1qz+ABRMRaLReKORSE9xkNVgcjAVFBqGZGadoiOFsd0CKa89+vpbIXUj+jLUwACBAbKO1tVDDMAagXjFFbDwcdvm81m+jbbZrPZiy2js7Xbbfv48eNePiDA1mRato2Ds8L1IgWdwUf80QaAR795J7OqBrQPkb1YLJK7hajF3d2d/fnnn/bw8GD/9V//lfx7Pu0+smwVWKrr+nu88x9S5vHmnFCBorognaf6jjaAZ/WoYpt3+PxEtcy5zkBigABCfqsuqbl2DCC/vQHFzq58AwQRDtgpTz9E4/2ZtAOOphOHUJd+jxmlHotcfYvan2qdq+WPX1C5HdnNWL7b7faFNQ550EU6u0otf02xocB7ExeNvlwTJ+k0ZeFUwldERYrZy1xBfVaVc73mZ7W6LjgHAKrV7+lSfCKr2+3ap0+frN/v2+XlpfV6veRw73a76fNaxJk1q2az2exFaxC/DOx4PN6Ll3qOh5tE3SaoBnBXtYL123FwQTgpwBuNRjadTu3333+3+/t7+/r1q3358iWJYmUMnjnouPqx0/GOdMLIy6GGVlkAmr3CWa2kPioFV/QHRef0WsQ1PanD2M9snlcrervdJj2NL5X3+307Pz9PLhS2KGGTcY1Tq65LzBddU7k4wKB9WOlwXx0g6uxXBWofoCZQnhovpE+RNHB/f283Nzd2c3Njd3d3ezHkojGNQBgxDo8B7zfkuj7/JuJYK87L+WMG68ygw73/sKihUaO1I73u4suiQ7CoWWzU6/Xs48eP6UvlJycn9vHjRzs5OUlgw8Awe/5gjy5+hxtpKrvWEz1Zoxyem/O/pnhhdWv2i7ZNoyEYHg8PDzafz+36+tqm06nd39+nbzzrXjtmz/FqHSvP3TxH84aJHyPPETFAtU8it01ERxsmqpyqO0OVUdXvIsBEgIusKj/ztKO0M7VTOaoR8vHjx/Qly36/bx8/frTBYGC//PKLnZ6eJl0LMYu4g+CCqnRrxonPWvHWpzfaqD9iuF6vp/K81bnb7ZIBhsX7+PhoNzc3NpvN7Nu3b8kd8/DwkD6Xq32ongsdBw+UnO6n4xIBEu+IJnhEkjNHrzJMfMWKxKtnzzkQ5li3B6R2BKQDh3FwcnKSNu5ko3Q+JE2SK0BGbKoOqesoqtXnuLU6wjUmHelVeh6A4rpRXVINMG03iQP67ebJZJKsYT7+AzDxmXqGoX2fG0ffn77vIx3Rt9G/pyy9KmICKzbbX4DjG0aFVExHQIxAFRkmUdleuecbb58/f7azszM7Ozuzy8vLvW/6snUdYlZdPWbPO/5ruzQRlDSnx8dHq1aroYtGQ13ad1jcuvxUDTuICAduHVwtDw8PNplM7M8//0yc8PHxMcWDdTIh5r1HoghMXoopZ/R5lGqcqOr0pi6aHPnZr+c9gHIcs6icSH9U7lerPX97l49In56e2unpqZ2cnCQLWGPHcEANd6HvrVYrG4/He1Y4lq6GuogQ4dTWkKXZy9V43qJUnc23b7fbpWTb2WyWMmNYXI7uR14gk8RzQd93Cqro/KFzh+jNOaEOvs4q1dG04XS6WrN6zZer76LsHOfEaOCrlp8+fbJut2u//fbbC8tXv3Zp9uw6IeKDKIMjkuaurhWN1mh4stH4/o0T3CgKdnRlNXrgkJSLZa6+RMA3HA7T+g+44O3trU2nU/v69astFgu7vb3d4+SqA/q+9i4Vr9dpH3m91I+L2csPSarz/c10QiUPxBwnzM3EIiqynHk3IGi329br9ezk5MS63a6dnp7aYDCwwWCQYq5kXytXQ6zsdrskYvV7xySEqp9P47z49XQpwmKxeKHYe8s0UvjVu+CTEuCA/KEDTqfTFK6LuCDle5Hqj5H+mLOOj6FjuOHRzmrlehz1eu7lUYO8dcu5XFyTAYX7nZ+f22+//WaDwcD+9re/JUOE65pEoINLJAHuMR6P9753rEsguUcztiEmA7mC0+nU+v1+cgF1u92UEkYf4JbhnMbFqddoNLLlcmlXV1f2+Pho19fX9vDwYMPh0G5ublISqmbeUB+zlztW+Biv1t+7UXyYTq8fUpV0kh0jlo/mhJpocKwuF1mO/r6iytNpcEDcLb1eLxkfhNvY41l38EJMqMtjuVwmXWs2m9lwONwDHWnvKmbUPURcmaxp4tH8RZGFiCsC+OVymfQ89D9yBEejkT08PKRJUmS85axXf4+qRX5c9NmiccnVoyz9pV25/HX931vTVDYCXHSPcl5EHm6Xy8tLu7i4sLOzM/v1119TtIPMZdwvlUolBfn1eH19bfP5PKWiAUAAoCJbcxi1XvgFmZSAiA00Sf9iUlA/3QjJzJJoheOh583nc/v9999tMpnY7e1t0g81A1z73Y+PckD/Rz9HzuRIJEcGZqXyvJpS8zTf1DDJgTDSHSIAcj7H9aJ7KRuOdnZ2ZoPBwP7+97/br7/+mqIfmhuID5AOWa1WKdfu27dvaZAXi4Xd39/vJYCqv9D/eW5GKA7XDByW59FZqQ/rmX0SwXK5tLu7u5QLSBRkNpvZ169fE/ebTCaFAxyBxnNbb2zkmEoOgCru4X7qvD8WfNCrDBNf+WiWcT6yavUezwnpPFKkms2mffjwIemAg8HAPn36lHS/wWCwJ97ITmHtxN3dnV1dXdl0Ok0gfHh42FtXgWvGZxZHOqtOLqIy/X7fut1u0gXVJeSBgKED5726urKbmxubTCb27ds3m8/n9u3bt7STwePj495mk5EKU3bMPKf07THbt5L1ftUf8XQoHRLrRfSqnVojEEZhtKgyeh/k78Xv98svv1in07HffvstZbgw2Die+cw9EQ7it/f39zadTu3q6sr++OOP5ODFEU3yRSRCVFdC1/HcXTkd2TifPn2y09NT+/Dhw4stRug3xPvV1ZWNRiO7ubmx6+trG41G9vXrV5vNZvbly5ekLrCtcuQyUfLiORq7Q9dpl3JSVUM0C12BmCvzTQyTQ8jOXc9xFBptZntOX8B1eXmZQNfpdJLfT1fq4VBmJRmLeW5vb200GiV9ijUV0fJN6ki9vJqg7cMibja/f1mdevF1eVbT+YiMpuU/PT3Zw8NDMjiIdozH4+QqUqvX1yPq96K+9z7aQ+OVewd6HwbaXxHBSj8kYmK2H9bxuX3qk6NDcFOgKzFwJycndnFxYd1u1z5//mytViutVIMj4IwFfOhVGB2Pj4/29evXNLgPDw8pC0VFjwehDkqUfIs/kMwcJsnnz5+t0+nY58+f0ydrMUAQpaRgsdTyf/7nf+zu7s5ub29TMgL1fHx83EsGifRmtW4jtUfrzjnu8W6YyIiBuBe9WwGIaqEZO8cAG/ph1nHZMgASoCLchgKPo5n0K12pBvn8vOVymSxd0t3H4/Ge1RutlS7SX7x4I+lAP5bd7/dTQgSL2/06Ys3mxie5WCxsNBqlSAhcGm7uU8BUb1aDzY9LzsjjXM5g9GNk9jK6okkXRRw6kiCH6Oh1x/qCyPLVGaqcDyctgCKJAKNDE0tJQuDL7Dh0MTqIJOBeUYsX5V7z6khM8KFCKNJpqTdWN87nfr9v/X7fTk9P7W9/+1taj8LnaFmaqlxCHdBwPT74TVIqMWJvpHH0BpzGzXMA8JyN/yM3GH8AjT7QlYUfPnxIoUE4tpJyxWNcNT9MHOdI3RuIM/SpVquVuAkgJAVfrUuz53UtiNXpdJoyinG3kO4OQNXdokCL6mcWK9O4VYi8ECZkOQCxaV1VBzcjSqPLYx8eHlIKFhxQVwiqcZCrE+cjC/eQC0fbrdc4erGMrk4/AFRdTJZTvd4MhDmdz9+jVpRuXP7p0ydrNpt2dnaWnMven9br9ZLegStFN+kZjUZpZyl0QcJtKnq9kaH6H+0w21/2yUCQhIAr6PT01Hq9XuKEGp++uLhIYTtd96G7Wt3c3Ow5ykmYUCvdO49zHNuL4DK+Q+71lrLG4VGVvEUf3UvfKcf3emJZ+ktfdCo6r6KNQe10OinVSheMKwj5w6pkXxRE73w+t/v7+8RRWE8xGo1egCk383N1NdsPDRKKQz/F+sUahjOST/j4+JhCfQ8PD2n1m4KQo3f4ltG5D7XLi92oPK9KqRhWkGM46hjyW9fDaPQG7v9mC518RygniUSHihV8fGdnZ0kXZG9DGg030IXs6HTj8diWy6Xd3t4mVwbnsDpzXCTSXyMxpnoru7rCsZk83W43We+tVitxc6zZm5ubFJmB47HXCwmnfrWd71tfV3+taFz80T/jDRh18kdrtRG7miBRxHmZvLqAvwy9ao0JQXttnAcgs6dW+74NHNEEljGSho9o9+Eyoh7ogEQXsH5xOLM4iHfpAEez3neaLtbR9DCMo9PTU+t0Oskwubi4sE+fPiV9lgxottsYj8f27du3tPZjOBzu5SVG/aoUcboywMo97ykSx2a2B8Ltdps27mQs6CfvV/X9qe6zNzVMyhTuOwLDQjcDp4GaDKn/a4IpKViRy0W5cs5CzNWdjsNyV4MJFQKdkElEJIRVcCwuurm5sdFolMCo32f26VZRf2lCqdk+MHJ6Xa6/o+uHxLW6YtQ1Rp5mv99P3gnf357exDCJKszM4JqGeLSCCsDpdLrneAZQGimgkSRssrEPcVTldMo5qVeRi8Prf2bP+8qgNrTbbfvw4UPa8Z81K5eXlyljBHWBWO9kMrH//M//tLu7OxsOhzYej5POFNUrcqOopKHflFNrn+Y4okolxqZsIkO1+ryfouq8TMqLi4vUZrXGvV7q+/kQHS2OX0MAqlqt7u1hU6vVkoMWEKIT+t23MFK8hev9Z36WR4PldSLvgIYjwgl1YZKZ7U0oHOO4XHTFW9EgqD4a1ZtzPpEgN8n0eOi9StSBUCS6cJSXafa8JyRLYr2VfqxRYvbKJZ+qG/j/1YVDBfHjNZtNe3x8tEajYaPRaI8T6kf6ACHX4IzqGvLRD+9SUM4RhZQqlefP0SJmz87O7PPnzykzptFopI9u93o9q9frNpvNUqo9et8///lPm06n9uXLF5tOp+G7cnqdj0z4fo6y16NyIpUjpy96fZns8H6/b//2b/+W3GaeW7LC8I8//kipb6ytwc8Jozikmyr9kAQGFcvRLMDfl14q28Ppp6p0IZFucpTbGTZXt0js+XsrlcreJxzQ/fQL9Lhp+EwFkwUg4quEI9IGPyHK9OchEHmRl3u2LHnJBuB1H3DlxMpckE4+fHeMCFY66hMSkA+Mmz3vUhABQJdL0rDJZJJml/qXNJVeNzWiTM8tckfVWf0AIlovLy9tMBjYx48f7fz8PEVDiOwApu32+2bjrHbDAPn9999TyBBOnuOAUOTX8wNXxveXA2EO/JFOrCADWOQw4if85Zdf7PLyMo0Nert+LEd3s9Xd2d7UMPHizXMc/1vT4+GYAFZXijHbNOylHesHwhtBucH0dcMPRlLsYDBIew3qJ2dVpKOvjsdje3h4SAkIrNAj5HaIS3kdVs97UOY43CEuGE1UPyb+HeoW434c0s1mMxlIms7lwRa1vwwd/YHFSM8o+6zORMSzd2rqe+C+udVier+vizdA6JxarZbcLJeXl3Z+fp6+PQwIUdLNnnfawkcJJ8QR7ZMjDvVPEQeDila4lQFm7hl/1EkGAL99+5b8pewQcX9/n9w2Nzc3ZmbJVwxj8Q74Y4D4l0D4Gr1ERbQ2wOfFISq07CJuF4kpfmuns380XJCYMHogTnRmP37J29vbtPTy9vZ2b3dYb+XmqCxni9pbVsc8JAIj4wYJhB5utv81heFwmKJF4/HYzGxPVclZxT/cMCkq0FvN3gqLZkikaCvwont9eZGLI6fUayYPPkHAqFt4oL8SZtO1v3d3d8kqjGKkh4AYieGyxstrOEzu/sjH54+oRKR17XbfAwyr1erFMtbczgtvqhMqUPzyw1yWh94TzRj/5zvI/84t8C5aD819umchhoimjOFSms1myf3CmhU1orzOGv1fpj8j/fA1VKSa6D1FQFGxSn+S7dNoNNJOZD55V/V8P36H6OiwXcSpomMEKqXcQOUAe4gjFLkIOI/1RpKC2XM0B72Itb2s/R0Ohyl27XWfXLuj+kXnj+FqZcBdBvTaj9H4eIDqkk5cUBgnxOqj8Y1yN3P0qiwa/zLvslGFN8cR/dqJ3D2UqZ3mHdVmL7cW1veqZUeCAtvw6teQxuPx3hoVIjYaOlMQ+jhw5Hj29SkCUm7QIn0wmpS5yR4ZTfSnhghz5cANp9Op7Xa7ZDDiSYjep1/MOkSlQRhxwOhatLgmp1T78zlx8lfJi3Ec4kQ3dB8avnqkW/9GLo6y3CjXbo5RmUXG1rHgLjpflivTb6gfSBQf044kYBl61bpjz6EizqTPqb5GhaGiPMBcHDICt18d58UlC6K226398ccf1mw27ebmxprNZop4kDZGZGS32+1FP6IBjwysQxZtZKD4cvXo74kAFCUlFOmaOnZwLiUdU7Y7IRqED9UbKP65snQ0CCORo0q9nvfP5vSSQ1TE1nOAiO5B/yNPkYU8bLerUZqcePeDH+lTRXWJyvD9EL0rApbXRf3k9Jk3hzhsVHaOCfjoiL9+jCQ7ShyjQ0RiVNd1+Ip4l0pOCfZcsGjBjO77p2X79+NiMHueJPP53KrVagojsjrOl691823zxxz3ijg9VFaURu+IxN4hcaht0uv6BQGtt44foEOq6CrK3BLVN9MJVQ+AsJT8QHoQHiIPRP+cGizRABRZrApEX091OPvvouQmTBFH0vNlOEKR2I3uKwKhXj+Ug6gi1QPUZ/Do8/SXz2ZXOsbN9GpO6K+t1+u9dHmz/W/e5mZ7JCoiDhndc0h8RNZrVIeiBIlDQPDkPQJRXaKyj/lfAVYEQv+cb39uPM1efgbDzF7ssOGNFR37NxPHVERFoL7QL12M0tP5/5DO5AfNi/QisOQU8yi1nhntOWrR5Mml6Ps25CRAEbDL3JObhEVqgd4DeZUmN6lUjUKSRFt/aMTsTf2Emknh103A0nm5/3iLt449sKAyHemBrJ0ElTF8cpzZu6S0o/2Ae5XB1/GYth36XaQWRM95jukjWv7LAb49EbBVtfFj+qackAbj8MWSVDNdY7Ck7+vuV7vd81oQKq0i288cn1WspODWjoqycqLB82VFoI64i7ZX6+C5Z+Sw13bkLFe9JzeQhyan9p+e89/ii0gTSigXo8WDz4tsytatV8rQUS4aVWIRY9pQ5Yi6vzPP6/pgzw09CHRQoyRavc+f97OTazkfVjSAh6jIHXSI80WcJSeKtV9ydSwD1gh4uSCDntdIUaRb5oyXY6g0CMmeJe0d8OlROZ4OPA30FrRmaSjlOKNvpIpfzqvSrB2nCnWkT+bK5Xck7n29inIKczmC/loReb1Q/88BTseoqEzNltE6KoNhvFDHuM/vS3MsEF8dMVGWnSNmSU5h9UsCtCHR7+g+rZfnnB5YXv/MGR85EZnjVseeO5Z8/SIwFt1n9tJqLxLpvgzdDk7HnfHTXbzelBOSrqO6HGsqKpXK3kors2cA6kwtYylCOcuyiOigXIKD92cViZEiIEbA9++KjCZffjSRtfzIpeLrGd0T1Ydr+k4iRlpWq9V6oUfqRgWEP1XXRw/XZRpvYh0XmfC+sTRYRQ2zREEKe8+9z4v2yKDQ+yNfVdQRRcbAoXty3CcHuqJJljsfiVv+j0Dr35ObiF5S6Ee+tXzV8/XL82a2t5pQGRMcUXMKy1JpEC4Wi2SUsCySBpEarjl6Zs9+QnXRRNEKD0wtV/Uw7xKIjJfIWvXncjpndO3QbC7i7gpaf051abiG10O9+hANbm4SlyH93C1lqXQz+57mz1ho3mVkHevXqo7Zz7o0CFerVXoBrhjdjwXLN4r58n9kutMwz9V0EyEv3hRwke8xupaztqNnjgUqpGLUA8z7F3NZKPoObXfE8SJQKnB9n0ZtZQ04nM1HUNQ69uMRuWdo7zGT42hnta4wUz2APD3fGWbPOpLfZoxrZvkO1XuLWLxvdGQt5gCr5PW0nLjT+kYDr/44/d9/oiECS8TdtT4KAJ5F6njJEvVrFJKL8gHMLHlDtttt2jid8c/5Cbfb7xuj/nBOCML5HAOZJ9pAv/wxEqPohp5rKHcw2w8pcU4/aO11F93VgagO6oPvYM8ZIS8mfT30XVqvSGzyrALRl++t1ZwDO3J7+ZQzFZHqMqEvvFGpmw1AKsUox3NqXdSk9eJPLeWydJROWKk8O5yxhul0OB2/6cScPkbj+K0bZirowkr/HwgUzB4s/I5A6Em5E//zbnyirMPVCRDVzwNN6wXpBNKjTjLfTp7DXaKRIfQ0Bl/dYd5AVNJ7FeCRCqTqFAu+2K5FJwvgZN/IMlQahH69qW70jdWr+l1kIeoMoaOptIb8FBDaMdyrXEhJuZSC229EruUroLgXp3y1+vydFbYEjvQ5PwG0PH2GtlAvBbd+fJF3slcifcPifOV2Wq7qs9xPv2vbeaf2g98Ayf+xyyz7bq9WK3t4eNj77IVmqM9ms7LQKg9Cr7v5WRRFSxQceg/ntPO8o1NB5kHo3TB0nHIMbxQpCCNRGNVL65fTbxTUka7nubsHhIJad8pnxwN0MoDqQej3MlRJ470VTBbK00nUbDb3+l8BDQh1+2d8ipS72Wys2WymZRHHLHSq7Mre+U7v9EZULmj5Tu/0hvQOwnf66fQOwnf66fQOwnf66fQOwnf66fQOwnf66fQOwnf66fQOwnf66fQOwnf66fS/TX0wi4sewpoAAAAASUVORK5CYII=\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -591,17 +478,22 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 35: 100%|██████████| 63/63 [00:54<00:00,  1.16it/s, loss=0.0106]\n",
-      "Epoch 36: 100%|██████████| 63/63 [00:55<00:00,  1.14it/s, loss=0.0117]\n",
-      "Epoch 37: 100%|███████████| 63/63 [00:56<00:00,  1.11it/s, loss=0.011]\n",
-      "Epoch 38: 100%|██████████| 63/63 [00:54<00:00,  1.16it/s, loss=0.0107]\n",
-      "Epoch 39: 100%|██████████| 63/63 [00:54<00:00,  1.15it/s, loss=0.0103]\n",
-      "100%|█████████████████████████████████████████████████████████████████████████| 1000/1000 [00:06<00:00, 159.33it/s]\n"
+      "Epoch 20: 100%|██████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0179]\n",
+      "Epoch 21: 100%|██████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0174]\n",
+      "Epoch 22: 100%|██████████| 63/63 [00:41<00:00,  1.50it/s, loss=0.0174]\n",
+      "Epoch 23: 100%|██████████| 63/63 [00:42<00:00,  1.50it/s, loss=0.0164]\n",
+      "Epoch 24: 100%|██████████| 63/63 [00:42<00:00,  1.48it/s, loss=0.0167]\n",
+      "Epoch 25: 100%|██████████| 63/63 [00:42<00:00,  1.47it/s, loss=0.0167]\n",
+      "Epoch 26: 100%|██████████| 63/63 [00:42<00:00,  1.49it/s, loss=0.0155]\n",
+      "Epoch 27: 100%|██████████| 63/63 [00:41<00:00,  1.50it/s, loss=0.0153]\n",
+      "Epoch 28: 100%|██████████| 63/63 [00:41<00:00,  1.52it/s, loss=0.0157]\n",
+      "Epoch 29: 100%|██████████| 63/63 [00:41<00:00,  1.52it/s, loss=0.0153]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 66.84it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -613,57 +505,31 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 40: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0107]\n",
-      "Epoch 41: 100%|██████████| 63/63 [00:56<00:00,  1.11it/s, loss=0.0107]\n",
-      "Epoch 42: 100%|██████████| 63/63 [00:57<00:00,  1.10it/s, loss=0.0108]\n",
-      "Epoch 43: 100%|██████████| 63/63 [00:56<00:00,  1.11it/s, loss=0.0103]\n",
-      "Epoch 44: 100%|██████████| 63/63 [00:59<00:00,  1.07it/s, loss=0.0108]\n",
-      "100%|█████████████████████████████████████████████████████████████████████████| 1000/1000 [00:06<00:00, 157.81it/s]\n"
+      "Epoch 30: 100%|██████████| 63/63 [00:41<00:00,  1.52it/s, loss=0.0161]\n",
+      "Epoch 31: 100%|██████████| 63/63 [00:42<00:00,  1.50it/s, loss=0.0143]\n",
+      "Epoch 32: 100%|██████████| 63/63 [00:41<00:00,  1.50it/s, loss=0.0149]\n",
+      "Epoch 33:  59%|█████▊    | 37/63 [00:25<00:18,  1.43it/s, loss=0.0155]\n"
      ]
     },
     {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 200x200 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "Epoch 45: 100%|██████████| 63/63 [00:53<00:00,  1.17it/s, loss=0.0111]\n",
-      "Epoch 46: 100%|██████████| 63/63 [00:56<00:00,  1.12it/s, loss=0.0107]\n",
-      "Epoch 47: 100%|███████████| 63/63 [00:56<00:00,  1.11it/s, loss=0.011]\n",
-      "Epoch 48: 100%|██████████| 63/63 [00:56<00:00,  1.12it/s, loss=0.0108]\n",
-      "Epoch 49: 100%|██████████| 63/63 [00:59<00:00,  1.06it/s, loss=0.0102]\n",
-      "100%|█████████████████████████████████████████████████████████████████████████| 1000/1000 [00:06<00:00, 155.26it/s]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 200x200 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "train completed, total time: 2911.32178401947.\n"
+     "ename": "KeyboardInterrupt",
+     "evalue": "",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn [10], line 25\u001b[0m\n\u001b[1;32m     22\u001b[0m loss \u001b[38;5;241m=\u001b[39m F\u001b[38;5;241m.\u001b[39mmse_loss(noise_pred\u001b[38;5;241m.\u001b[39mfloat(), noise\u001b[38;5;241m.\u001b[39mfloat())\n\u001b[1;32m     24\u001b[0m loss\u001b[38;5;241m.\u001b[39mbackward()\n\u001b[0;32m---> 25\u001b[0m \u001b[43moptimizer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstep\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     26\u001b[0m epoch_loss \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m loss\u001b[38;5;241m.\u001b[39mitem()\n\u001b[1;32m     28\u001b[0m progress_bar\u001b[38;5;241m.\u001b[39mset_postfix(\n\u001b[1;32m     29\u001b[0m     {\n\u001b[1;32m     30\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mloss\u001b[39m\u001b[38;5;124m\"\u001b[39m: epoch_loss \u001b[38;5;241m/\u001b[39m (step \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m),\n\u001b[1;32m     31\u001b[0m     }\n\u001b[1;32m     32\u001b[0m )\n",
+      "File \u001b[0;32m/media/walter/Storage/Projects/GenerativeModels/venv/lib/python3.8/site-packages/torch/optim/optimizer.py:89\u001b[0m, in \u001b[0;36mOptimizer._hook_for_profile.<locals>.profile_hook_step.<locals>.wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     87\u001b[0m profile_name \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mOptimizer.step#\u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m.step\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(obj\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m)\n\u001b[1;32m     88\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m torch\u001b[38;5;241m.\u001b[39mautograd\u001b[38;5;241m.\u001b[39mprofiler\u001b[38;5;241m.\u001b[39mrecord_function(profile_name):\n\u001b[0;32m---> 89\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m/media/walter/Storage/Projects/GenerativeModels/venv/lib/python3.8/site-packages/torch/autograd/grad_mode.py:27\u001b[0m, in \u001b[0;36m_DecoratorContextManager.__call__.<locals>.decorate_context\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     24\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(func)\n\u001b[1;32m     25\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdecorate_context\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m     26\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m():\n\u001b[0;32m---> 27\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m/media/walter/Storage/Projects/GenerativeModels/venv/lib/python3.8/site-packages/torch/optim/adam.py:108\u001b[0m, in \u001b[0;36mAdam.step\u001b[0;34m(self, closure)\u001b[0m\n\u001b[1;32m    105\u001b[0m             state_steps\u001b[38;5;241m.\u001b[39mappend(state[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mstep\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[1;32m    107\u001b[0m     beta1, beta2 \u001b[38;5;241m=\u001b[39m group[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbetas\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[0;32m--> 108\u001b[0m     \u001b[43mF\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43madam\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparams_with_grad\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    109\u001b[0m \u001b[43m           \u001b[49m\u001b[43mgrads\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    110\u001b[0m \u001b[43m           \u001b[49m\u001b[43mexp_avgs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    111\u001b[0m \u001b[43m           \u001b[49m\u001b[43mexp_avg_sqs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    112\u001b[0m \u001b[43m           \u001b[49m\u001b[43mmax_exp_avg_sqs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    113\u001b[0m \u001b[43m           \u001b[49m\u001b[43mstate_steps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    114\u001b[0m \u001b[43m           \u001b[49m\u001b[43mgroup\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mamsgrad\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    115\u001b[0m \u001b[43m           \u001b[49m\u001b[43mbeta1\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    116\u001b[0m \u001b[43m           \u001b[49m\u001b[43mbeta2\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    117\u001b[0m \u001b[43m           \u001b[49m\u001b[43mgroup\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mlr\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    118\u001b[0m \u001b[43m           \u001b[49m\u001b[43mgroup\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mweight_decay\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    119\u001b[0m \u001b[43m           \u001b[49m\u001b[43mgroup\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43meps\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    120\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m loss\n",
+      "File \u001b[0;32m/media/walter/Storage/Projects/GenerativeModels/venv/lib/python3.8/site-packages/torch/optim/_functional.py:84\u001b[0m, in \u001b[0;36madam\u001b[0;34m(params, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, amsgrad, beta1, beta2, lr, weight_decay, eps)\u001b[0m\n\u001b[1;32m     81\u001b[0m     grad \u001b[38;5;241m=\u001b[39m grad\u001b[38;5;241m.\u001b[39madd(param, alpha\u001b[38;5;241m=\u001b[39mweight_decay)\n\u001b[1;32m     83\u001b[0m \u001b[38;5;66;03m# Decay the first and second moment running average coefficient\u001b[39;00m\n\u001b[0;32m---> 84\u001b[0m \u001b[43mexp_avg\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmul_\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbeta1\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39madd_(grad, alpha\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m \u001b[38;5;241m-\u001b[39m beta1)\n\u001b[1;32m     85\u001b[0m exp_avg_sq\u001b[38;5;241m.\u001b[39mmul_(beta2)\u001b[38;5;241m.\u001b[39maddcmul_(grad, grad, value\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m \u001b[38;5;241m-\u001b[39m beta2)\n\u001b[1;32m     86\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m amsgrad:\n\u001b[1;32m     87\u001b[0m     \u001b[38;5;66;03m# Maintains the maximum of all 2nd moment running avg. till now\u001b[39;00m\n",
+      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
      ]
     }
    ],
    "source": [
-    "n_epochs = 50\n",
-    "val_interval = 5\n",
+    "n_epochs = 100\n",
+    "val_interval = 10\n",
     "epoch_loss_list = []\n",
     "val_epoch_loss_list = []\n",
     "\n",
@@ -681,7 +547,7 @@
     "        noise = torch.randn_like(images).to(device)\n",
     "\n",
     "        # Get model prediction\n",
-    "        noise_pred = inferer(inputs=images, diffusion_model=model, scheduler=scheduler, noise=noise)\n",
+    "        noise_pred = inferer(inputs=images, diffusion_model=model, noise=noise)\n",
     "\n",
     "        loss = F.mse_loss(noise_pred.float(), noise.float())\n",
     "\n",
@@ -705,7 +571,7 @@
     "            noise = torch.randn_like(images).to(device)\n",
     "            with torch.no_grad():\n",
     "                # Get model prediction\n",
-    "                noise_pred = inferer(inputs=images, diffusion_model=model, scheduler=scheduler, noise=noise)\n",
+    "                noise_pred = inferer(inputs=images, diffusion_model=model, noise=noise)\n",
     "                val_loss = F.l1_loss(noise_pred.float(), noise.float())\n",
     "\n",
     "            val_epoch_loss += val_loss.item()\n",
@@ -742,26 +608,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": null,
    "id": "2cdcda81",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 800x550 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "plt.style.use(\"seaborn-v0_8\")\n",
     "plt.title(\"Learning Curves\", fontsize=20)\n",
@@ -791,33 +645,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "id": "1427e5d4",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "100%|█████████████████████████████████████████████████████████████████████████| 1000/1000 [00:06<00:00, 157.98it/s]\n"
-     ]
-    },
-    {
-     "data": {
-      "image/png": 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GhAkTUF1dzffh7e2NZcuWqSyOPT09MDc353GSnp6u1tAGoJZqIK00B1AbNjc3o7m5GWVlZdi+fbvs/Xt6eqr8fvz48dDR0eHxKITCQF6zZg2+fv0qe87s7Gy0tLSo9NP09HRMnz5dZlxQ3w4ICOBNHyEsNI6EUGyOysvLER0dzUhheHg43yttLCIiImT9kxD6/Px8FQPO398fI0aMYPerEApXmoeHB4KDg7F7926Vdu7o6JAhv2QALV68mD+bNWsWYmJikJeXxwizEIr5MysrCxs2bICOjg6MjIy4Lezs7GBkZAQnJyfExsbCxsaGUSA/Pz82TKgGBQUhPz8fbW1tGDt2LDZt2gR3d3fug9INL1VHR0c2fisrKyGEHMWm97V79250dXXJ7r2srEz2XoQQ0NfXR2xsLExNTWXokqGhITIyMjBmzBhe3HV0dFQ2Cubm5oyOUd/08fFhw4zacvjw4Xyf9A7d3d1lc0lYWBgbnD4+PjA1NYWOjg673pX7HFVbW1tGeqnSs9B8QPdPyBQZW/r6+jAxMYGFhQWsrKz4M21tbejr63OVolj/ZEhJjS/p90MZUGRESVEwZcNMaoD9F4PrP9lP/+koycRtZGSExMRElYmFyp49e2QvnaqbmxsSEhIYLpZOfsp8C6lhQYaBjY0N7yybm5vR2NgoG9S0WNbW1kJPT08tUkaT3/Tp06Grq4vVq1dj3759WLBgARs70urs7IyUlBS0tbVBCAEPDw9s2LCB3XQ0eUk778iRIyGEwODgIN8vudliY2Mxa9YsnDt3jiddmsylhmJDQ4MMMVq8eDG3V1dXF9zd3dHd3Y2SkhKMGTOGJ31aCKlWVlYyp0gIBddDylmqqKhAcnKyWuhZCKFiHEl3uGTElJeXY+XKlRBC4XrMzs7Gpk2bUFtby4sAuS6FUCy00gGclZWl0o+EEFi6dCkvRPv27YOXlxf3i3fv3qnca1lZGQDg9OnTzDWSXkfqepJWun5ubi4bnFu2bGFUr729Henp6ewKEkLhotywYQO0tLRkCJyykfrgwQNuw9TUVNl3yqgSnbupqYkXi6EGtRByI8jb25t35coGHLl7mpqa2GBYu3YtTxyEMPb393P7SlGaqVOnyiZ26TmFUCwyU6ZMQWtrK9auXSvjtQihmMzj4+MZQSUXFlXpPLBx40Z+5/X19cyntLOz42No4Xn06BGEUCATRkZGcHZ2hp6eHry8vNiws7Kywpo1a2SGzqlTpwBALU+Pxi7V4OBgNk6pFhYW4s2bN5g7dy5/RsaqEAoqxY4dO7Bz506VDZ/0N9RXjI2NoampifLychmvTzonJicnyyb6mJgY3Lp1iw0AHR0deHl5obKyUsaRunDhAs8jZKD/U78qKCiQvZezZ8/KjA/pu9qwYQMbHjdu3JCdS1NTk41idbwoZf4iVRp/UtQlOzub3eNTpkxBbm4u9u/fjydPnkBfXx/u7u5IT0/n30jnE3Wb9FmzZqG6ulr2zkpLS7F8+fIh24a+ow2z9DsNDQ3Y2Nhg5syZ/Blxy4ba2KmrLi4uSEtLw/r167nNcnNzUVhYyOuMg4PDkMaPch0zZgxGjRolM5SNjIzY+CJkT9lgGjVqFCIiIhAQEKBiUFI1NjaGhYUFxo8fj0mTJqm4Z6lKDS0jIyMYGhpCT08Pjo6OyM7ORlFREWxsbGBkZMSGEv2GOF1SLtdQRpY696GysaTu3386lzpDayge1/+JoZWTk6OCYBgbG/NxiYmJ0NDQkEHlVGNjY3Hs2DEI8W33oKenh9LSUtjb20NHRwdWVlaMchgZGcHHx4etZOkOJTAwUNYR6B7Nzc15QqCOrrxT6erqkk0K9vb2ao0NWiT7+vr4s9TUVPT398PNzU3tJEKVJqF/q1ZWVnB2dkZDQwOePXum1q1TUVGBq1evynhu0dHR2LFjB2xsbJCSkiJzbUrfixCKyY6MxREjRjCHJyoqCufPn0d5eTmcnJywY8cO/q2UR0BuloiICF5kaVFWx2vw9vaWGUMlJSUoKChAc3MzEhISZO0vxDdujRCKHSQRxAGgs7MTr1+/lk1I/9SeUg4XIQRCyFE7IgMLIXDv3j3+W+oiokoGpZmZGT58+MDtevDgQWzcuBFNTU18LLnBaGKuqanBkSNHoKOjo2JQCqEI8vjw4YNsjEnPR5XcQEIIFXI/tRn9/fTpUyYGUz/x9vbGmjVrmAskfWaaiEeOHImmpiY4OzvLOGGbNm3ChAkTZP1h8uTJso3JtGnT+P6fPHmicn/h4eEAgC1btuDOnTsQ4pvLf+PGjdxubW1t2LlzJ4QQ3EeHDRsmm29ozO3cuVPGP5s+fbqMwC2EwjAIDg5mFy1VIpdbWlry5iE8PFxlXnN3d0d/fz+0tbUxfvx4BAcHA1BwCaV9SMqP3LJlCwDg5s2bKu0gfXfqxqu66ufnJ3PHkeufAoSo3r59G97e3txXDAwMkJaWxm4p6RxIz6DcJv7+/ux+O3PmDIBvaHV4eLjM0Nq1axcAYNWqVSrtTgarus0NIV/Kn5uYmKgYRllZWYzGC6GYq/v6+pCWloaGhgb4+vqqXFta1bm2pIgLVQpQWrlyJcLDw7Fs2TJ2EQcHB7PxrxwsQka/srEi7Rv/tYaHhyMqKgpz5sxBdHQ0EhMTUV1djZiYGJk7X7rpkLaLhoaGbGMs5f0R2Z3GblJSEnx9ffm8s2bNwrhx42QbLOkcIsQ3wEO62TYxMUFJSYlKOxOiKjW0DA0NYWhoCAMDA3h7e2PJkiW4e/cu4uPj4eDgAB0dHWhqaspcier4WP+GVg1lKA31f2Uj7X9jbP0/NbT27dvHA5IQDGmlQjsZ6aBzcHCQvXgh5DudGTNmyNCA9vZ2meVOC3N+fj4PgGHDhiE8PBzBwcEqfKMtW7agtLSUdxmEdkhJgcroj3LV1dVlbowyZ0QIwYZLXV0d7O3tZYal9FkCAgJkrh1ptbCwgL6+Pkf/0CIljQCkqqenh9DQUMyePRsZGRn8OS1cNEkpc6CEEGrROmkNCQmBu7s7L5bKldBBCkD49OkTE1dpAldeOGiwUaUILAB4/vw5v0/la/3xxx+wsbFBT08PR+LNmDFD5R3/l+rg4AAzMzMcPXoUQgi0trbCy8sLQUFBmD17Njw8PNDd3c2Lk5TjIYRAcXExcxCdnJyQnZ3NbZSZmaliMErHwvXr12UTM012hGxVVlZycII0EpYMfulkLX0vAGQufCnXRAgFEghgyMgoIQS2b9/OY4PGBEX4UpVyzJSf89SpU/D19YW7uzvq6uqwdu1aXhBra2vh5OQEBwcH2Ri3t7eXIZuXLl3idiU02sDAAEVFRTAzM4O/vz8ARRSqubk5Pnz4gHnz5uHYsWPMlYmKikJxcbEKJcDPzw/W1taIiYnhuYrchNK2DAoKwvDhwxEQEKDWZR4dHY3BwUGYmJggPDwcPT09aGhokBlWxsbGKmiIlBukp6fH6JSU86LOCElLS1NB0PLy8thDkJmZyZGUyvPXmzdv4ObmhqqqKubPKrudqE3fv38vQyXnzp2Lz58/IzIyktty0aJFMoPIx8dH7fwg/YxQJaKTmJiYqAT/aGhoqCCkQgisXLmS+2JISAhmz56Nffv2yTbAAQEBiIiIgL6+PtauXYv29naZ4UTPa21tjbi4OBVE3traWm1UHc1lhMzs27cPU6dOZdRLOrcbGRlh+vTpqKio4GhB2tDTWHR2dua/pZw+dc8dHBws4/x6enqitLQUa9euVeFImZub83ufNGmSStva2tryxkndOiCEkAWbELKYlpYGNzc36OjoMHjh5OQEa2trGBkZYfz48UPyl9PS0pCamgozMzM+ht4JIVL6+voYNmwYjIyM2PUbExODwcFBLFy4EL6+vtDT04OGhoYM2fonztU/GVP/ZhwNxc1Sd41/+z2NgX8r/9nQqq6uRlxcHObMmcMRTqNGjZJNUHxS8Q3CVebJUK2qqkJsbCwvZNLq6Ogog87VEfioEp8gLS0NS5cuhZaWFuzs7HDkyBE0Nzdj5MiRMncF7eZjY2PZAJFGUdGEtHDhQmzdupWfR+qq0dTU5F2/gYGB2qgiaaUdUXFxMYT45uO/ePEihFAgVgBksHRJSYkMYk9LSwOgiI5U5ggpt530/y0tLbh06ZJa/oEQ3yLuqL319fVx7tw53r0CwKtXr2TvWPp7fX19WYSTunrhwgUI8W03LuWxqSOBA0BbWxtGjhzJi8aiRYtgY2ODpKQkJCcn45dfflEJY29ra1Ph3UiDKADg9u3bKC4uBgB2uQKKCLkpU6awu4cmNPo3MTGRkRnp+Q0MDNTyymjHT0jQDz/8wL+VurWlY6a8vJz71fjx4xEdHY3m5mYAUOsyGDduHGJiYlRQAgD4448/YGxsDG9vb+5H/v7+mDp1KuLi4v6RHCuEULuZUlcLCgpkzyCEQrKDkE4TExPMmzcPR48elR0jlU+IioqCn58fpk6dqoIs01ih33p6eiI0NBRPnjwBACxevBjZ2dkwNTXle+7t7WWUQmrEksQAjXvpAifd9dO7kP5fR0eHn5NQImUEhhbV33//XSZzouxOFUKobDxpo0LPGR0djYaGBrx48YK/8/X1RWJiIi/Y+fn5/P4+fPiAiIgILF++HG1tbTIDZKi5SVdXV61cx6hRo1BUVIS+vj6Zsezq6iojbk+ZMgUAZJ4FKeJM7ncpEV5dDQ0NRWhoKCNDtMlQRm+Cg4PZq7F+/XqW4aEq3VyMHz9exXWrzmuxa9cuNDc3s4EyVJBEU1MTNm7cyG79gIAApn1IXc5ktE2cOFGFI0aVECADAwMEBASoRFInJibKJD0CAgJU3Nqmpqaws7ODhYUFI1GWlpZwc3ODjY0Nb5TIeFSWypBWCtgS4lsUsp+fHweVuLi4sOeHfkPrSWBgoMxzQNeTGkw6OjoYNmwYTExMoKurizFjxmD06NFYunQpVq1ahZiYGOjr68sMKqm0g9QAUkdyV2cQ0bP8m6TDUAbXfzXQNDQ01JlLKuV/7DqkeuPGDbWRgCRH4OjoCD8/vyEHOZHnWlpaUFJSwgs77bQIGSsuLlYZUFISYU9PDw8sGoxCKBaQhIQEtRFrFy9e5AUtOzubFz4pj0YqAREWFgZXV1fk5eVxe5BO0D9NINJzGhoaymBwQC4zQeeiXYGpqSl35jFjxuDq1avMSdPW1gYAnojIYBNCMFJRUlKCkpIS/PDDD3j48CFfR7ozWbp0KV+Drk/vLCIigsPWpQNJWn/55Rf+3bRp02STA7mApJXaOT09XS1/YcaMGVi3bp3M7frp0yeGraUGTXZ2NiZMmMBGblZWFhYsWABra2sZGkNt3NDQwOiFEAo0kSZFegYKaVb3rPb29gAU7i/laCblSuc7e/YsTExMZJyr/v5+GTpHyMbMmTMBAOPGjcPnz59x4MAB1j4zMTFhrad169bB2dkZhYWFAKCiW0aSHkJ806iSusScnZ1VIimlqBghrMrtJ4Sqm9jBwQHR0dG4desWu3epz0j7tLKR/2/jBgDmzp3LyMi4cePw8eNHCKFwddIC+ueffzK3ycbGRuYOy87Olm1UJk6ciMbGRjx+/Fh2LVqkpO5ZBwcHVFdXy3gYJ06cQGVlJcrKyuDs7Mx9lIqy1txff/0FAEP2FSm3j1yKq1evZsNQmSd39epV2bn09fWRm5uL8ePHw9bWFrdv3+Z2obJhwwbeyMTExCA/Px/5+fn8PoyMjNDV1cXv9e3bt3j+/DkyMjIQEhKCGTNmcJuSS/TXX3+VIdFz587F+fPnVbhL0jp69GjeKISFhcHLywuTJk2Cjo4OCgsL+buUlBTcunULbm5usndnaGiI7OxsFBQUIDQ0FDU1NfDx8cHRo0fx9OlTDB8+HNHR0RyteOLECWzevFnGT5ozZw4AwNfXl9cKGxsb9g5IdSArKipw+vRplJWVybwgQgimVygb5n5+frLN8bBhw2TaekLIowtpnZKOjXnz5mHChAmwsrLC5MmTZWOb7tPZ2Znn8NDQUJ4bhRDsSj158iSysrJkIMioUaPUysbExsaqIG0zZswYkrdL71M6Xn788UcZUiaEAjkjzStdXV0YGxuzseXk5MTac8uWLUNSUpKMpyUlwUsNK0K4pBwrddINQ1Vlw0v62T/xudQdJ/3uv5T/kaFF/+7evRtr1qzBw4cPeQcgJUTGxMQMuThTJXfa9OnTedENCAjA5s2bYWpqioGBATQ0NCAgIACvXr2STc60WKalpWHRokUM8QKAnp4e9PT0ZCHMRGQGgGHDhsmeiX4nJTMKIWSTlvTz169fY8yYMQAUGjmzZs2SGYpCKHR4rl69qvLMyuci4U0PDw/mBynfF6DQ3lqzZg0bKjNnzsSePXsY7ZAe29zcjM2bN+PLly9sGNL5pBF+ym4FQGG4KXPrxo8fDwDQ0tJSQT8AwM/PTxaBJYQCLRwcHGSeCgAe5E+ePIGpqaksZJ9KQEAA/y3dDWZnZ+PVq1cybpEQiohA+n1RUZFaEjkZU1TT0tJkE878+fOxd+9ete9HuRI6e+3aNUYvjIyMsGbNGp7o6PP9+/fzzpwWZXo+6u+//vor+vv7ZW4g5b7p7u6O5ORkxMXFAYBMrFValV1R5OaUcljILbV//35GIZUnSCGEyuJC9xUVFYWcnByEhYWpdX3RgkkcO1p0EhMTOcpYer6amhpuo8mTJ/P7pHPQ34GBgbzr//HHH2XXtLe3x8DAALKzs2FgYAADAwPk5+czT1SqZScdo8TzIRSE0AlpNC+5N2kxrK2tlRmlhOzT/2NiYnDy5Ek0Njbys2/atEl2XVtbW5V3LK00b/3888/8maGhIRwcHFBUVMSRgl5eXvj9999l41+6qZS6jgICAtgQkl43LS0Nnp6emDdvHhITE/9xcT1x4gRvcDMzM2FrayujMAihMD6Cg4Mxffp0ODs7o7a2Fr29vSo8KkdHR1y6dInbwdXVlTfY1IcImffw8ADwjZOm3Kelm4iioiI2Zm7cuCEzVjU1NREdHY3Fixf/I7d29erVsg2jEOopDsripG1tbcjJyZFJxLi4uGDYsGFYu3atWm6Ycj148CAaGhqQlJSEhIQEpKamshEudUHa2NjwPD127FiZsebk5IQzZ86gsbERVVVVQ16rqKgI1dXV0NfXh729Pby9veHo6KgSgS2E3OUZGhqK7OxsGT8yLi4Ovr6+KCoqgrOzM2bMmIGgoCA2jPT19aGpqclyPTk5OTh79izOnz+PNWvWsAtfOcJQytPS09PDiBEjYGFhAUtLS5ibm7Nx9m/tKq3K8g5D8a7U/V8dT4z65L+V/zWipa5KB73086GiqKTHDQ4OygYNAN6RSLkdZ8+elRkDLi4ubNRRUUfIVe4w0urq6sq/laI0Q1WCuJWP+/XXXwFAJYpyqGpubq7SvrTok+GlLvKDOGfr1q3DkydPsHbtWhmhnGpjYyMOHDig0uZUfvvtNxXYWipqun//fo5WWr9+PS8YyhIXVNPT02FiYiLjF9EOHVAYpsqGz5s3b9Tqiwkhd7mQYUAuXABMuO/o6FCZVAwMDLB69Wp+lhcvXqgQPAHg4MGD6O/vZ9eLMklYmbtDk7Cvry8PQlqgPD09h+w7Y8aMYV6fuvdJCKuXlxc0NTURExPDyCWhg5GRkWqlCqR9kcYCcW0WLFjA/QVQZBnYu3cvAPXuSKrjxo3D27dvVZ5HHVIphOAsBurUxq9evYrQ0FDZ5xEREThy5IisT5aWlqpISijretnZ2bEI5Lhx42T9QQhFBBmheoGBgTh16pTM9S2EkCENY8eOZd4TuRTfv3+vViKG6qRJk9DX16eymero6FC51l9//YVnz55BCIUBS9IeM2bMULvg3717l/9ubm7G8OHDkZ+fz9wi4m9u2LABvr6+ePToEaNpAHgzNWLECBX3b09PD75+/SprU6nRUlFRgZCQEBw9epSNMPrOwcFBpm+1a9cuWf8JDg5mxN7f359pF5cvX1Y7JpQ5ZupI7bm5uSxefOnSJTY+o6KioK+vDwsLC5w7d05Fs04IBaLk5OQER0dHfpcUHW5vb4+ZM2ey7trUqVP5HHFxcThw4ADq6uqgra2N5cuXM2VGCIVxLeXcenh4YNKkSYiMjORocmlNTExUydJB711bW5s5jgMDAwAUSK46YyciIkLt50IovB/S9qS+Ym1tjalTp8LOzo7bwN7ennWqgoKCVOQe6G8tLS0VBNvMzAy+vr4qxo2TkxOio6MZdGlra4OpqalM88rGxgYJCQnYsmULTp8+jSNHjiAtLQ2hoaEwMzNjzSwyYKSGlq6uLvPrJk2ahEmTJmHy5MmYNGkSfHx8WOZjqPGqXIcytuj/Q6Fb6rhb0vnrn8r/2NB6+vQpDh48qDJ4lNEO5YXPzc1NJmEwYcIEbN68Ga9fv2YoVN3umq4zlJ9fT08Pra2tMl0XqsSDqK+vV9FeUuZIKPvT6brK6u5UCV0CgLNnz8LIyAhubm44evSoTHYiISGBz/X+/XvZORwcHFQ4SsrtSrwu5RcqhMIAJcPA3NycOUSAIlRbOsDVTXZCyBedixcvoqOjQ+bWUFfnzZvH7sh/uneqr1+/RkdHh8x1+v79e8yYMYPdIQDYEAGAn3/+GefOncPg4CCn6LGxsWHIGlCgkMrGE/HxCFEYPXo080Z++OEHtW05btw4joYVQoHiGRkZDRnheOLECVRVVeHp06eyzwcGBhjNEUKBhJBrEwDv+KVRrNJjqT9Tf1y7di0AhQ7RP+3ChfjGg5M+GwVx/JNu16dPn9jFSPXLly8IDg6GlZUVrl27ptZAnDlzJvLz8/HXX38hICCADeijR4/yRD98+HCeF6T8GZpcSe5AWnbt2sUItXKGAWX+zNWrV2XGNJ1LnQFJZG5dXV2ZAd/f348dO3Zg9+7dsLKykkkc+Pv7IzAwEKGhodi2bRu+fPmCxsZGnD59WkXVXCp+6+zsjKKiIlRUVGD16tXYunUrmpqaACiQVyrSgASpq4ye59KlS/D39+eMAhcvXsSyZcugpaU15PscNWoUcnJyVAzUlJQUAIoo3paWFnh4eDBiJ4TCzbx582YAimAVAJg6dSr09PQYZbGyslIRj6VN5dixY3neoD5M91hSUiLLpKBsTEvPBSj0FisrK3Hx4kUcO3YMM2fOhL6+Pjw9PdUKxHp4eODLly/Yvn07TExMcOTIEQAKPmtSUhK7+4KCgnDx4kXU1dVh7969aGtrw9atW7Fr1y54eHjgzJkz3PfCw8Ph4OCgMr8IoTBCjh8/LutHenp6Kv1OitJKXY1ubm5oa2uDm5sbVq9ejdTUVO4Tfn5+8PPzG5J8npmZiaKiItTV1cHGxgYhISFYtGgRioqKYGtry227c+dONDQ0oKysTMUFKtUvUzeuqAYHB8Pb21uF7ybd/FNKIRrn0neroaHBUYf29vYoLy/Hx48fcf/+fRQVFSE4OBgBAQEwMzNT4WFJIw719fXh5uaG6OhopKSkIDMzEzk5OSgsLERxcTEyMzMxdepUuLm5sVzKP82V0jqUy3EoXpYyWV55/hqq/GdDKz8/H7t371bZ8dOFhjJUCgsLZW4qghjpYaZOnYqxY8ciNDRURvijBdXDwwOnT5/mSUA6oVRUVPDiTRMdEVzLy8vZ/UCFJrP169dDV1eXja3r16+zj97V1VXmwqBrUt47IRQLhbm5Odzd3VFZWQlLS0vZrmrixInw8PDAgQMHONquq6sLLS0tyMvLw9KlS1VChR88eAB/f382rPLz81FfXw8TExPeQUmRQYKuQ0NDMWfOHH42aYTY48ePZbuShIQE7N+/n98HtZVUToF2VkIodlw08UgHqvRZaVLu7e1FWloasrKy0NXVBR0dHbS2tg6p6E8LWmVlpUqfkr5nab148aKMp0LKy11dXVizZg0WLlyIYcOGwdbWVobkAQr0CwALmwLy3IFhYWEqYovK93T48GF2Pc6ePRujRo1CTEwMAgICZMRoWlQoDRSljLGxsUFlZSU8PT3x6dMnAGBOk5RPkpqais7OTpUJkPiPANhA19fXl3EL//zzT45KpHacPXv2v6peSyfRxMREXoisra0RGRmJtLQ0TJgwAYsWLcKlS5dUuGyAgo8kfXfnz5+Hh4cHPn/+rCJ8OVS1t7dHUVERb2SKiooYvbp69arMIOns7JTl06MoLGqbYcOGDanxk52dzRu/wsJCDA4OoqmpCcnJybh8+TI/07x582REYktLS0yYMAHl5eUciEPPLH12Ly+vfxVEtbS0xMDAAJYsWYKHDx+iqakJjo6OjLCR+y8/Px/btm1DXl7e/yr6VlrJFffhwwfue1IUrby8HF+/fuXFlDTQbty4wSTu4OBg7mPJyclsPCpzaZXbZO/evTznpqamYvv27bL5iuYBADK0kMaTlOM0VE1PT+c+kpycjGXLliE3NxdtbW1ITU1FaGgo0tLSsH37do4qT0hIQGNjI/744w8sWbIEZWVlsLOzg5mZGSoqKhj1KS8vx6ZNm/Do0SMZsODu7q4icUCbE7ofqW4VoU8BAQEsu0JrYWFhIb+Xf6vkyi0uLkZxcTFGjx6NgIAArF27FsXFxdi6dSvCwsKwY8cO3sitWLECRUVFiIuLQ1hYGBITE9HQ0IARI0bIjCRCdz08PGSaYw0NDWr1CdUZpEJ8I8V7enpi/vz5mD59OkaOHIkpU6Zg2bJlmDRpEoYNG6bWyCI+lq6uLkaPHo2goCCEh4cjMTER6enpmD9/PiorK7F8+XKUlpYiOzsb4eHhzAH7J1T63+pQ3CxpvsX/E0PLw8NDBpkSLG1qaorCwkL89ttvMDExQXp6ugpUmpubi9u3b0MIgZs3b2Lbtm148eIFrl69ym4jPT09rF+/ngftPzUCuaZ0dHRUeDv04OoaWVNTU7ZLVr5OTEwMHBwc2H1XUlKCL1++ICgoCOfPn4eJiYlMSJSeycfHh6938eJFODg4wNfXl3clNLCIkJmdnQ0LCwu17j5ppSg9dd/NmTMHv/32G4QQsglu586dKoYLkcgdHBwQHByMM2fOqIQ50yS2YMECNiDoOwoLly78oaGhbCzu379fxlmor6+XaV8lJyf/Y44tKsTDGCqhr/K7EkJhAEujB4nbcfbsWXlHV3OOqVOn8qRBBFl1C1lbW5ta3hKhVWTU+fr64s6dO8zlunnzJn766SfZb8iFZm1tzfdFBtTKlSvx8uVLODg4ICUlRaaptnLlSj5eU1OTjeTU1FROOq4OyZk/f75sh0fHTJ06lTc2bW1t0NXVBaBYgCmTg7TdAIULk/ho0mAGKR9TOWBBimwTGgEo0kLRPCGVR7h37x5fV8qNUZaxkNaysjJUVlaqoNTEWSI0kPhdcXFxsrEnvecdO3ZgxowZQ/YZMuKk35MAI/1fuks2NzeXoUvSv/9Ja4+QdOU8dbRJnTJlCi+M4eHhMDQ0VJEnEUKedF2KKAvxDeXr6OiQLaZJSUkAAG1tbdja2rIBW1JSwu6x7OxsGTLy9evXIZEq0h+jc6s7hoxKXV1dODo6ykSv165di/z8fN4gWlpa8oaL1gKpCywyMhIxMTGIjY3lQIlt27ahuLhYti4MHz6c53obGxsEBwfDw8NDlhVk+PDhePr0KW8uKZhCKq1AG2AXFxdG+JSjBKm6uLjwPbu5ucmoFJs2bUJRURG/C2dnZ57LpXI5pKxOxkReXh48PDwwbNgw5ObmIjg4GJqamkyWz8vL4yhm0oMjbTZp8JWGhobKOKN5Ozk5GYmJiTyWLC0tVSR86Jnob4oeNDQ0hKenJzw8PODq6orw8HAkJydj5syZnCibxo2yyjsZNISKubu7w9vbm9O1JSUlYcGCBVi1ahW2bt3KuTzHjx8PBwcHjBw5EsOHD4eenh6fb6gxp1yVUa2hVOT/S/lfcbRiYmIwbdo0BAYGssIyoEC1pOHU0krEyd27d2PevHmMdBCnwMDAgNP6WFtby4QbAfALlN4LuQ3mzZvHef+Uowxnz54t+z8AWWSilO81fPhwzJo1iwcOoUE+Pj5qd1OjRo3CiBEjoKurK0uoO1QF5NFJ6kiW6iZyaSUytNS4Ig6bckg3oHDHkfGgzIPQ0NCAk5MTPn78yGRrdR2RJkrimqirQUFBnD4C+IbiUPqakydPynZqtNs3NzdXmaBNTU054mbHjh38Ny3a0kTboaGhyMnJgbGxsWzh2r59OyOT5DYRQoEckbGRnJzM75UmN2XOWmhoqAwVIfejr68vdu/ezQZPZGQk8vPzsWPHDlnQgXRBVzasAcgIyICCYzOUSjU9w/bt2/lZr127BgDMYQMUhl9oaCi6u7vZ+JAigUO5JaSRYwB4U2JiYoI//vhD5Xh16Dbx9zw9PWV8Lilvsbu7G5aWlhg7dqxaAvbDhw+ZK0hcRSKvS5FzdZuKX3/9lXXTqFZUVGDq1Kk4efKkWhcsvfv58+fzAmRhYcGLP6E72traCAgIQGRkpMyFtnz5cnh5eUFXV1eWJ5T+1tPTY9e0tA84Oztj/vz5ePDggYr+IG0YkpOTZdkkqL5//x7Pnj2TtV9fXx8uXLiAH374QSXRvbT/CCFkLlKqr169wq5du9DU1ISSkhJs2rSJ5934+HhcuHBBFuAgjeD88ccfYWNjw7I+Pj4+ss1XbW0tBgYG1MqJjBkzBrt27cKmTZswd+5c2YZh+vTpuH//vkzwlzIRfP78GbGxsZg4ceI/6qEpc4RjYmJw9epVAAoeMOWblUrjSCVYpNw06dhWBhSoSuV3iA4TGBgIJycnhISEwMPDA1FRUbK+OG3aNGRkZCA8PByOjo7w9PREUFAQnJ2dsWrVKtjZ2WHkyJHQ0dGBv78/GhsbVThbEydOlD3/9OnT0dDQgLa2NlRVVWHGjBmYPn06WlpakJ2dDS8vL0yePJk9A6NGjeKxQAaXm5sb3Nzc2LD8L8r0FKWvo6MDPT09GBsbw9zcHKNGjUJ4eDiSkpIQHh6OyZMnw97enjfwpKOljGqRQaOrqwtDQ0MMHz4cpqamsLKygru7OyIjIzFv3jx+1o0bN6KkpASpqamIjIzEhAkT4OPjA2dnZ1hbW8PU1JTT/BBqpu45hpJ/kBpd/+fyDkIoUqE4OjpyFJ7y93/88QcAICkpCaNGjYKjo+OQUL6Pjw/GjBmDqqoqXkidnZ3Zpacul5iTk5MKPK+np4f6+nqZfpeUiAsA/v7+8PHxkaXmoGptbc0TLMkmhISE8IRmamqKtrY2TJ48mY1BQuX279+vIiKnXOvr67Fjxw7Zzq6wsJAhdHXETiHkAq9mZmaYNWsWACA1NVW22ACAgYEBWlpaACiEK79+/apyvuTkZEycOJENqw0bNqi4g2i3RQmW79y5g+LiYkRGRqoolGtoaKC6uponpaCgIKSlpaG+vh7e3t4wMjICoOB/ODs7q90NqauUH5NIsUIoJnVCfYyNjTFv3jy0tLQwYkKTuVThXDrpR0dHY+TIkSoyB6GhoTLXlPJERqKuDQ0NAMCI0927d9kNefr0aWRkZCAyMpLdNP/lOend/fnnnzh27BjzP2JjY/kc0kTZ5ubmqKysxJkzZ2QRsytXrmQ3Jh3r7e2t8iwJCQkcFapM4KZr0TmkY0c5KrWoqAilpaUqiYCtra2HTEECKOQ4lCOxaPG3sLAAAGzatIk3Svv27WM0TQiFAU8bB2nSbeVIODMzMybKAlBR8aZKieeluSIPHTrEz5CUlIRt27ZxgMCiRYtkc9KCBQtUyOejRo1CXFycSsoZ6YJOrvpffvmFNa0IZRFCsdBRLk3pOdRFlI0ePRr19fUAIEPepXwyChQAgDt37qC0tBQbNmxgAyIrKwtjxoxhZXgyWmleGj58uCydD7nMrl+/LuuHyv3S0dER79+/x19//cX3LpUIoE2tupQw6oxj4q1JN1dhYWE8/27cuBGhoaH48uULduzYgYSEBHh7e2Pfvn1ISkpiz8kPP/yAKVOmICUlhe83KysLc+bMkSVkT0xMhK2tLcLDwzF16lQEBARwv1IWtK6vr0dycjK8vb0ZEaLnmjJlCiwtLVX0Dkm2wdvbG56envwcWVlZWLNmDaqrq+Ht7c0GkL+/P2czoCCv0NBQuLu7w9DQEN7e3qy7Nnv2bNy5cwctLS3Izc1FZWUlFi9ejCtXrqCqqgpJSUnsWrSxsUFgYCCnFhLi29ozZcoUmZyEnp6eSrAWGZaEZg0bNgz6+vowMDCAo6MjoqKiMGHCBLi7u2PUqFHMzyKjRjndDrnp1EUDknSEtbU1JkyYgDlz5qC0tBSrVq3CmjVrsHbtWl6TcnNzkZycjOjoaISFhSEoKIgNbCsrK45gHAq9UpdHkRC4/1L+n0QdAlAhzO7cuRP19fUYHBzkiYY4EQDY7SYlNyobKdIJdCiOB93bjBkzeNCZmZmpWN4PHjxQ+R0A3Lp1iyd8epnSziMlwycnJ2P27NkwNTWViaB+/vwZx44dQ2hoqAzqDw8PZ4OPkKrr16/j48ePsh1sUlIS36+3t7daJflFixYx2dTIyAiNjY0AFCrPUqNNOapPCMVOXToxT548WQXdoohP6QRAfKbXr1/Dw8MDtbW1TGBWFsBT1tGhHb/ydej/np6eane3hNTNmDEDFhYWiImJkeWNI+NWunh5eHjA3t4exsbGssjV/v5+FcJ6SkoKwsLCZIYHCf0R6uPm5oZZs2apTPBOTk7Yv38/L/hk5H/69AkuLi6ora2VuR0mTZqErVu3ylyuhIBlZmayDhotojRxEyROv5G2dXV1NR/38uVLJCQk4MqVK7CwsFAhuVKl48+dOwcHBwe4ubnB1dUVra2taG1tlaHAo0ePZoMuPT0dUVFRvAABijQlixcvVpvPVF0NDg7mCDgyRM6dO6dWr0wd0TkwMBCVlZWy8ebv7682Gpd280ZGRjIEet68eZg6dSrmzZunIh5K6B5FoNFzSuUlhFAs4mvWrMGmTZtkBiQZqYmJiYw2NzQ0oLGxkQ1yZSkAdbWtrQ2AKtd1KJ4JLdwUAKStrY2oqCjEx8ejsbFRhiDSHOnm5oYlS5bwgnzz5k1cunRJJYlzUFAQli9fLuP+kQeC5Cno80uXLiEwMBBHjhzhLBVCCJUNNc335G5XRvD+J9Xf3x9jx45FXFzckG7Z69evM7K0dOlSLFiwANOmTWNj3sbGBuvXr8eECRNgYGCAvLw8LFmyBLdv38bNmzfR0NCAnp4e3LhxAyYmJjh27BgWLlyI27dvo7q6WhbcITUOydCnzT0hzSEhIbC3t0dOTg4bNRoaGmrzPurq6jJympSUhEmTJqGoqAgeHh4q7RoQEIC4uDh4eXnBxMQEo0ePRkhICCZMmABHR0eEhobC3t4e2dnZ8Pf3R0dHB0pKStiQ3r17N5YuXYr29nZO3t7Q0ICqqipMmjQJ+vr6/EyWlpYyNHzMmDHQ0dGBg4MDbG1tYWFhgdTUVB7bZGgZGhrC2NgYo0ePhrOzM2xtbTFq1CiYmJjAyMhIhhINlePwn6L+NDU1MWzYMLi6umLy5MlIT09HaWkp6uvreY5rbGzEypUrUVJSgnnz5iE3NxfZ2dmYM2cOZsyYgbCwMHh4eGDkyJHQ1dVVQa4InaN0QsOHD8eIESNgZWX1/9bQsrOzw6FDh3hxlE6K1dXVahN4enl5ySBsQn6oODo6yn6nLtWNuiqNTty8eTPCw8PVRk4Qd8TBwQEfP36UuagAYOnSpRzqnpeXJ9utNzc3Iz8/X61yMlUy0N6+fYuzZ8+ipKSEF017e3scPHhQRgantCTSicrAwACBgYFMPpQuYOpcM0IoOCbKEYzkplE2LObOnYukpCRUVlbC1tYWq1evRnFxMQ8eR0dH/PDDD0OmCdLQ0GBuR3Z2tgqHiZ4XgCxpbkVFBUfCSfla0kq7vfb2duaMSV0kAQEB2LlzJ7vSpMiptA2phoSE8GJLfAJlNE9dCg5PT082ZgilAL6JgUoXosHBQRWyKnHKDh8+rGLgS12xJHoqhIJjpxySvGrVKp5ICVFSFrwkdx7x5iorK5lfNhQvhAJFrK2t2dClCZ52rUlJSZg4cSLs7OwQFxeHmJgYjBkzRuZ6X7ZsGbvIs7OzZVGcyrWzs5MXe3t7e1hYWKCtrU2mxq78Ds+fPy9zCwuhMPYJ9Zk0aRIyMjJw5MiRIXl89K7URcVu3LgRZ86ckeVrE0KxM5emqZJGjtrb26OtrY3zBlI+SDp2yZIlKimzTp48CUDhFia+E/Wl+Ph4REVFMdmafkPRqIBCliIwMFA2nqQ1LS2Nf1tTU8NoE/UZExMTAFBxmRkYGMg070aMGIH79+9j/PjxyM7O5r5QXV0NXV1dRimJv1dVVYWIiAhGyEpLS2WK/xs3bkRbW5usX9NmRUoFCQsLUysTopyTUlrd3Nwwffp0ODg4yIjyAQEBavmfQUFBbJz7+/vD1tYWaWlp0NfXR0hICNatW4elS5dyO9C4AIBTp06hs7MTq1evRkhICIKDgzE4OIjr16/j7t27KCkpQWVlJdLS0lBUVISkpCQeT4RGTpw4ETU1Ndi/fz8brDExMewxITealOtEhqKpqaksg4EQCukQR0dHGZJGNTw8HN7e3jz3ZGRkwMzMDOPHj0daWhri4+PZIE9OTsb69etx9epVJCQk4NatWzyeqqqq0NbWhv7+fly6dAkBAQHw8vJCdnY2SkpKEBERgczMTERGRsLf3x9xcXFwcHCAvb09wsLCsHHjRtbKWrx4MaffMTAwgLGxMbv8Ro4cCTMzM5iYmMDAwECGIunq6kJPT09maFHOREo2razcLsQ3fhehW6mpqaisrERzczP27duH/fv3Y+fOnWhpaUFzczPq6+uxevVq1NTUYOXKlaioqMDChQuRmpqKqVOnwtfXFx4eHvD29oa/vz/Gjx+PiRMnIiwsDGFhYZg8eTJviP9L+c+GFkHSQih2UcqDYurUqUhJSRlSYyk/P58RAOkOmo53cHCAubk5NDU1ER8fL+N6DZXtXYhvSuZS94fU6tbR0UFZWRmCg4Nx7949pKWlcQoYa2trlJSUYN++fdDW1paRepcvX66WrE6ogbu7u8z1WF1dzeft7u7mBUWKcNEuSBpxqO7ZkpOTObRf+rmlpSUburW1tbL0RSTT8PbtW/a5UwWAvXv3IiIiAlZWVti6dSsePXoEIRRuNOIr0PHKaAMNYDMzM9kiJV0otLS0cPLkSSQnJ2PVqlVYtGgRACA6OnpIt4D0/pSNymHDhmHmzJkwMzOTGZ/S+6RFn1KUxMfHY/r06cjLy8PJkydhZWWlYoBnZmaqoK8eHh4q3MLg4GAcPXoUmZmZKjwiyvtJddOmTTLUifiC6p6TFM7/Ta5BWinoITo6msfOkiVLMGHCBBWXkp6eHhsCkydPhq+vr1rendRFTcR8QI6+UFsTynL8+HFGCQwNDWUyIIQmU67F7u5umdo2VVqkQ0NDOTUVVWnUJ/Vnugd1CYKl5HflsaKOmE1cQ2UjbNq0aZg8eTKOHTsGNzc3ZGdn88IbFRXF93L48GE0NjYiMDCQIwOFULh9aCErLS1Fc3MzysrK0NraKhMVrqurg7e3N54+fQoXFxfZOwAwZMLlZcuWsYGdnZ0ty4FHIrSmpqYyRLO7u5uNUTLYqF94eXkhICAAzs7OsoABejcUNFBQUAB9fX28efMGv/32G5ydnREbG4u1a9dycAbxH48fP85zKfHcaGPd2NgoM/pMTEzU5pq1trbGhg0bhtSLoirtox4eHozQ+vj4yDZSc+bMGTKCz9DQkFHjzs5OXjM+fvyIyspKRt6ePn2KRYsWYdiwYXj48CEGBgZgbGyM1tZWpKenIzg4GGlpaQw8zJ8/H1ZWVoiPj0d/fz8iIiLw9u1bxMTEoLq6mufS0tJSeHt7IyAg4B9TzNEcm5aWBisrKzg7O8PZ2Rmpqamws7NDTEwMIiIi4O3tLdPqc3BwkG3ySW0/IyMD586dw5YtWzBlyhR0dXXh0qVL+Pz5M37//XccP34c9+/fx/v377F27VqcOHGCDbmVK1fi6tWrSE9Px6FDh7Bnzx7MmjULVVVVGDt2LM6dO4eDBw/i4cOH2L9/PxtIhATp6elBX18fpqamMDExgaGhIXR1dVmQ1NjYGGZmZrCwsIC1tTVnFHB2doaHhwe8vLz4fbu4uMDBwQGjR4+GhYUFTExMoKenB1NTU/j6+iI2Nhbz58/HmjVrsGPHDhw+fBjHjx9Hb28vLl68iHPnzuHEiRPYu3cv2tvb0dbWhra2Nmzfvh2NjY1Yt24dFi9ejAULFmDBggUoKSnBihUrUFVVherqaqxZswbbtm1jKZF/K//Z0KLdjnLdsGED9u7dixcvXqC+vn5IDpa00qLa0NCAEydOYObMmcjKyuIH0dfXx+nTpzmNTGNjI6ytrfH8+XMkJiaivb2dXVy2trYyeH3MmDEyLkdqaioePnzIkx2hIoAiMvHSpUuoqalhvo66nFDkl5Ym4KVBKkXkpJwgIQSr5yqjfXv37oWhoSHc3NyYE/LixQt2OwGAjo4OPn36hMrKSiQlJaGwsBA6Ojqy3Qw9Ewk/lpaWwtHRUZbah4IV6P/FxcUqO0DanRGpvrOzkydhugZxwqS/MzExYYSLeG3ScxPxX+oOoXvIy8tDYGAgOjs7ZdF15GqV5nSjRUya9474F0IoFlwpInf79m12Q9NitmjRIsybNw9Xr15FRUUFKioq2MgtKSnB69ev0dXVBU1NTZUsAXQfqampTLAvKCjgnWxBQYFKYMOXL194t0WGplTnzdPTkw04LS0tFQ4eXYMH6v/3O5qoCwoK4OHhgeHDh2Ps2LHMhevq6sKyZctUXF+086qoqMCiRYuG3LwkJSUhOzsbjx8/hpeXF9LS0pCXl6eSWkcaTSm9v3379qkkob516xYyMzNx4cIFtUT81NRU7N+/Hw8ePGBDQ3pOFxcXdg9LXbOmpqZqU78Qj6q4uFjmolLeHM6ZMwcHDhyAtbW1jLukqamJz58/A1C4uGi+2rdvH8+DO3bsUBkPHz58AAAWXybeHj0zoAjcKSwsZO2yzs5OXLhwAQ0NDXjw4AFWrlypklYpPDxchgRSLSkpYdQjIyMDGzduRHBwMDZv3sx9SyqquHPnTgAKnaozZ86wQSM13MhQls5pwLeIYCG+IVyAIj9rQEAA+vv7cerUKfz000+ora2VCZzu27dPZswPDAxg5cqVbMxStGRGRgbi4+PZUCODSmo8kbtGWTRTU1MTZWVlePjwIaZNmwYfHx9s3boVlZWVePr0Kfz9/WV9z8vLC7/99ht7R1xdXTFx4kS8ffsWHh4e0NTU5HyZgMIFSBlKvLy8eBMRHBwMX19f6Ovrs6GqXH799VfExMSgvLycx29WVhY0NDTg7u7+j9HntJ5aW1sjICAA8fHx6OzsxObNm9HQ0ICDBw+iqakJM2fORFVVFcrLyxEVFYXMzEwUFxfDwcEBkyZNQlpaGhITE5Gbm4sNGzZg586dKCkpwd9//42SkhJ0dXVx33j16hX6+vqwb98+AICzszPi4+Px8OFDnD59GlVVVSgqKsLRo0dx4cIFfPnyBW1tbUhPT8f58+dx6tQpXLp0SYZEUWJpErQmw0hXVxcWFhZwc3NDUFAQQkNDERYWxjIOM2fOREpKCqdgmjt3LrKyspCdnY3Zs2dj+vTpmDBhAnx9feHr64sJEyYgKSkJGRkZTJnZsGEDOjs78cMPP6C3txe3b9/G/fv3cf/+ffT39+PKlSvo7e3F8ePHOZDk5MmTOHLkCDo6OtDa2oqOjg709PSgt7cXV65cwd27d/HixQv8/PPPKu9bXflfcbSI2AxA7Y5BWlJSUlj40crKCnv27JEl2I2JiWH+lIWFBQICAjjyYfv27YiOjsbnz5/53FJhRmn19/dXIVh/+fKFo7KUQ6kJtSGod+TIkUzOtLe3x4IFC2TRCMptQJVQLEdHRwCQ7aQJtj158iRcXFxUohukIck9PT2yZMsAVNyA0u/WrFnDCAAZU8TzkCJmv//+O4RQ7PBLSkpYNV9Z3FU55ZCywSlFaZT7hK+vL08iz549kyEZI0aMkB0rfUeBgYGYP3++LKKI3IQLFixAY2MjfvrpJ9nvaeJXTqxdWVmJuLg4Nvx6e3vVugmlz/Dbb7/h0KFDMoSrt7cXPT09PDG8f/+en50Wx6ysLABQ2Ymq4w1Jq/IuPjExkfXhAPDOkb6nhZHGEfXTyspKxMTEcFtS+9nb2+PDhw8q762yshK//fabLDI2MDAQCQkJMlSKNhSnTp2ChYUFy5EQQkoLoLQq88I0NDQwd+5cmbvVzc0N8fHxABRZG9RpqxGCCyjySZILWZpsefHixVi8eDGjDepU8mfPng0bGxtGc+zs7HDlyhUZSquhocHv7pdffoGlpaWMA0b9bagxL4SCR7ds2TLs27ePNz89PT2YOHEiR0MDCsK59DyVlZXMr6R8iDSG4uPjsW3bNuzbt485joA8AEFdFLUQ3zaBGzduRFlZGerq6nD48GH8/vvvCAwMxJ49ezgCmNw6s2fPhp6enkxAV4hvkbXkUg0PD0dCQgK/C4oI1dPT4+fs6OiQBSb9+eefjGqTUQooggh+++03NDQ0oKCggCkMBw4cYIOD/pXOFb6+viguLuYNgoaGBgoLC+Hq6gotLS3cvn0bhw4d4ntwdnZmBJ3yXpaXl/Mcn5GRIRuPZCTp6ekhKCgI3d3d/B5XrFjBsiNUyMAvLCzkdywtUu5OR0cHNm3ahG3btiErK0sl/Zm0kmFFBpmPjw8SExMRFhaG+Ph4lJSUYGBgACUlJfDy8kJVVRWSk5Nhb2+PsrIyJCQkYObMmSw5s3fvXhQVFbE7LT09HXV1dSgrK0N1dTWKioowc+ZMfPnyBdXV1ey5+vLlCwBFmqxt27Zh165d+Pz5M0pKSvDjjz/ys6Wnp2NgYICPBxTrz86dO9l1KOU2Ue5XfX19FoUODg5GbGwscnJyUFRUhHnz5mHJkiWora3F2rVrUVNTg61bt2LHjh2or6/HmjVrsHnzZrS1taGlpQX19fWoqKjA4sWLeb5bsWIFVq5ciQ0bNmD79u3YvHkztm/fjo6ODhw/fhy3bt3C06dP8ejRI/T396O/vx8XL15EX18fLl++jB9//BH379/HjRs3cObMGVy8eBGPHj3CwMAAPnz4gD/++AO///47j+F/K//Z0ALkC0teXh6jF35+fiqCoUIIjmoimH3x4sU8KUldjFL1c6pSg0XKx1DmrCQkJPCiC6jXz6IFiv7+J02nSZMmYdu2bTA2NkZxcTFMTU0VDSUUuxcy2CwsLBhJorQsEyZM4FQkAFQi82iiNDY2VqsnIzVQpHomK1asgJaWFvr7+7mtnj59ilu3brGwqfQ8RUVFMDc3V+EnjRgxAlFRUcjNzZXtMPv7+zF69GiEhobKSLTKxFxpJKcQinxiAHD9+nUAcrcTCXJS21FVx82gtmhra0N2djYsLS35t+r6Bp2TCiF4BQUFsvdMxFdlDo1UkwoAL2o3b95EWloa67CQwW9oaKgiAiqtNDlJNd0ARbStdAFXd/+Uh1MIhXF79uxZ1NXVITY2lo1k6jNkbJG+Go0R4pXl5+cz0hYTE4MZM2bwwkTcBvr9unXr1Ianx8TEIDQ0VOaWjoyMhKenJ8zMzLjNyZVFY07ZnUqGDbl9Fy5ciDVr1jCKEhISgoaGBllKIymZWlqlaJ+WlhbS0tLQ2NgIMzMzrFmzhu+J+o1UiPbmzZs8VoRQBLeQOvnw4cNlhgvx+w4fPizru5s2bcLVq1fx888/M4eMkDVlN3RISIjsfmkeART0hnfv3smiSmmMOTk5cV+hjRLNpaS7NG/ePJZYAeQBSAUFBQgPD8epU6ewc+dOWRYOal/luYA2ZvSctAGmcvz4cSxbtgxmZmZIT0/H2rVrkZOTw9G07e3t7OKZOHEiAMUiS1IWx44d43N/+vQJeXl5KCkpQU1NDVpbW3H79m00NDQwshUbGwsHBwfW9woPD8fNmzdlG23pvBkbG4vQ0FA2yKg/BwcHw87ODsHBwZgyZQqqqqoAAJ8+fUJNTQ1+//13nDhxAoODg9DR0cGzZ88wYcIEPHr0CK6urvj69Stu3LjB/aCxsREbNmzAn3/+iS1btnBI/7Vr11gIGVBs5gkFOnPmDCorK9HV1YVdu3Zh+vTpWLRokWyzbWNjg9DQUB7Xp06dgqurKzw9PVFbW4u2tjZMmTIF69evR0JCAs6fP8+eBuIHxcfHw8fHBw0NDcjLy0NbWxsePXqE9PR0LF26FBs2bMCdO3fQ0dGBT58+IScnB9evX2fj9+TJk2wk7dixA52dnfw8nz9/xt27d7F27VqsWrUKwLcUdcePH8e+ffvw4cMH1NbWAlCIzJIr7dq1a0wgJ/ehstHl4+ODmJgYpKamIisrC8uWLUNNTQ1WrVqFmpoa1NXVoba2Fg0NDdi5cycOHDiA5uZmbNy4Efv27UN3dzd6enpw4sQJHDhwAK2trWhra0Nrays6Oztx4MABHD16FKdOncLJkyfR1dWFzs5O7Ny5k12mDx48wLNnz/Ds2TPcuXMHP/74I+7evYvHjx9jcHAQT548wZUrV3Dz5k28ePECg4OD+PDhA169esVG138p/9nQUscZ2r17Nze89DtKRaM8YVpZWeH48eMq55H+n4wg5WOkCx0g16MCwEZAYWGhLHIuKioKnZ2dGDduHACwOKE0f6L0ukIo+C++vr7Q1dVlt5GmpqbKPSnfZ0BAgEwU8OnTp2hvb2eSv/JOHgAv+tIolp07d6K5uRk3btxAWVkZ86KoraWL81BVOX0MGRtSAzczMxOAQkD1+PHj+PXXX7Fv374hw/KJZ/H06VNZmO+pU6fUqqpLeXOjR4+WoSf79+8HAEZNpM/z559/AvhGrqfIz7S0ND5OnYwGuSCU3dyfPn3iRUTKaUpMTBwSFQkODmYOkHSDIb3Pf5LykJLGpYhEY2MjFi9ezMm6lccN/d3T04Pnz5/LzkkuceWACun31dXV3EeEUHCbRo4ciadPn/K4kCJ9VEJCQmQ8ud9++02WXHfixInQ0NDA+/fvkZCQAF9fXzg6OqK7u5vdfTU1NdyPDx48iAsXLrDMAAAZ2vb777+jrq4O48eP53slNPLAgQOorKxEcnIyb8y6u7tVyN3SNqC/4+Pj8erVK+al7dmzR/aOSZdLOkdIkRNCRKiNpAakhoYG7OzssGjRIkYMtm3bxgKn3d3dcHBwwJcvX/D+/Xs4OzuzyzYsLIzlYgDgwYMHnPgbUEQ/U1GmX2RmZvKm7sqVK3B2dsaTJ0+wfPlypKWl4eHDh3Bzc8PChQtx5MgRLFiwAD4+Puwqc3R0xI8//ihz90rbZNu2beju7mZUrKCggFOWXb9+HaWlpQgODoa7uztOnz6NdevW4cqVK5CWjo4O/Pzzz9DQ0GDjMSoqCu/evWODpbu7G11dXcjLy8PBgwcRGhqKyMhIFWkQIRRGlL+/PxwcHFiM097eHv39/aipqWF+086dO7FixQokJCRgxowZ6O3tRXV1NT5//oxhw4ahpaUFOjo6WLNmDTZu3IjU1FTk5+cjMTER79+/Z8X92tpapqSsW7cOR44cwdOnT3m9AhSG2ty5cwEA586dQ1VVFW8Wnj17hhMnTqCurk42rgHAxcUFUVFR6Onp4UhjqtRPpbxlHx8fHDlyBJWVlbh79y6WL1+OgYEBXLt2DS4uLoiLi8OWLVuwfft2JCcnY8eOHdi0aRNiY2ORlpaGvr4+zJo1C0eOHMHdu3dx/PhxpKamoru7G+/evcOHDx8wf/58/PDDD9i3bx8CAwNRXFyM+/fv45dffsGVK1dYVgcAXr58ifPnz2Pjxo2or6/HmzdvsG7dOmzfvh2AIt3b0qVLMWrUKLS3t6O3txeHDx9m1yFFEerq6sLIyAijRo3CmDFjMHXqVOTm5qKoqAi5ubmcUqe4uBhz5sxBRkYGcnJyUFJSgnXr1mHDhg1YtWoVqqur0dTUhN27d+PgwYM4cuQIjhw5wqT3gwcP4tSpUzh37hxu3ryJ/v5+XLt2Df39/Xjw4AH6+/vR19eHvr4+3LlzB69fv8bHjx/x4sULDAwM4MWLF3j27Bk+fvyIN2/e4MaNG7h+/ToeP36MR48e4caNG7hw4QLu3r2LwcFB/Jfyv5Z3OH/+vNpwbDp24sSJ+Pz5s4paMe1oV69eLSM93r59G/v27cP58+eRkpLCYf7SEGPpvVy9epV/TykkaIcmhFBBeYT4RgY1MTFhQ0EKg379+pUX99evX7O8AaECyigUufbIvVVaWvqvqubSVD7SdpVq00if8+LFixgYGMDcuXNVRFO1tbX/Nc3HsmXL+O+rV69CS0uLDRdaID99+iQLBBBCYUSTSCU9N/FWaJJW7hc3b95EW1sbLl26hGnTpvG7I6ROOSpOuW8R6iCVhCBkZNSoUWr7oRCqsgDkElA+XhqpJ4QCKZVyq6RyIlRotyfEt9B06XmLi4uRlJSE3NxcjBs3TsVwU06n4ubmhvPnz/P30jYBwMhAcnKyWoFTMgCioqL4Wuo05sigIAFWKZkcAI8d5dLU1ITjx4+z24d4TYROGxgYwNraGra2trC3t2fZEOL2REVF8dhSJx5J1yR3JrUloVGU7uef+jRVGu/h4eG4ceMGhBAyLlFLSwva29sZcZVePzk5GS9evODNxuXLl7Fu3TqmJijfu4eHByorK5nvCYD7tZubG7uSqO8ZGxszfyMjI4OvT1SFhoYGmRSJEEJFMuPevXuc3Jfyzi1YsIBzmtKznD17llN9Se/LxcWFN01EU6BCmz8iDxOPcOTIkTAxMUFXVxfnoyMDnIwM5XEFKCIcyeDMzc3lY2jDR0Y7iUq+fPkSABjtMzIy4jQu5N5LTEzEihUrEBkZyQnVfXx8cO7cOezfvx/Xr1/nsUAu97S0NJw7dw7d3d0oKytjQv79+/cRExODyMhIHotCKFzrb9++RUZGBn799Vc8ffoU8fHxrEO4c+dOlJaWcuTrjh07MHXqVG6HvXv3oqqqCsbGxtDR0eHnbm9vR2lpKeLi4tDT04OmpiYsX74cs2fPRklJCRITE3nTO2rUKFY0J73JXbt24f379/jhhx94jic+WHBwMCZNmoSkpCQsXrwYRUVFKCkpwejRo7FixQoO0lq8eDFaW1sRGxuL8PBwTJw4EcuXL8fXr19x+/ZtbNy4kblZgIKHRnSFrq4uHDhwAL/88guePXuG8+fPA1Ck4qPgqQcPHqCwsBA7duxAa2srurq6MDg4iP7+fmRkZHBCaDK09PX1YWlpCQcHB7i4uCA8PBzp6elIS0tDamoqkpKSkJCQgPDwcISEhCA0NBTjx49HWFgYYmJiMHv2bE66XVhYiOzsbGRlZSE3NxfFxcVYtWoV2tvb0dXVhVOnTuHMmTO4evUqbt++jTt37uDJkyd48+YN3r17h7dv3+Lt27d4/vw5Hj16hOfPn+P58+d4/fo1Xr16hdevX2NwcBDv37/HkydPcO3aNfT19eHatWu4dOkSI1y//vor/kv5HxlaERERzNMwNDTE6dOnZVDomDFjsHTpUnh7e2PkyJEAwEiHu7s7fH19kZqaivHjx8u4VrW1tejr62NekBS5cHZ2xowZM3Dp0iUAkOXuS09Px7JlywBAlgsxISEBaWlprDzb1NSElpYWXiwIiVi9ejViYmJw9OhRmebVv9Wuri6eJG1sbFRyvAkhT4hrYWHBOxYAagn30klLmZu1ZMkSfPnyBRkZGcjOzsabN28QGRmpVnrCxMSEuRTKNT4+nuF1QgT/Sw46Ij9KxVyVq6urK27duqXybICqyKXUBUUTK/DNgJOGbwshONeV8jWHyq9lYmLCxqH0OspVOdLx69ev+Ouvv3Dw4EGkpaXh+PHjSElJgYaGBhsqxI2SGvIrV66UySxMnz4d5eXl+Pz5M4tv0rGkC9bZ2Ylly5bJ3JhC/HOELQCVzAcUkdjW1ob8/HyZTpf0OKkIpnKbODo6oqCgAAsWLMDLly8RFBSEefPmITs7W6aAfvToUezatUutBtadO3cQFRXF5122bBnWr1+P8ePHY8OGDbxIk+s/LCxMrYFIvB8h5NIYL168AABcuHABnz9/VumHhFSXlZUxCn3v3j1MnjwZ06ZNAwBGKCn6kMQnpefJzc3FwMCACqFfuVLU7vz589HU1IRffvmFtYmUVdkpKGbOnDkqCu9ZWVlsDFVXV2PXrl38fnbs2CFD2kNCQhAVFcUcHzJo7ezseFF++vSpjPMohCINj3STSGOe5lJXV1fU19dj9OjRMrV3IRQR0J2dnTA0NISmpia6u7vZcL179y62bdsGf39/HDx4EKNHj4aBgQEWL16Mo0ePyqKfc3JyGDGjAAVpGTZsmCwjgqOjIxvcUjoKacYlJiYCAA4ePIjly5dj/PjxKnplHz584GAYZb5mf38/EhIS4O7uzpHAgMLtPGvWLBXETlqKi4uxY8cO1NTU4PHjx5y0WgiF3BB5NZydnbFx40YOeALAdAQNDQ3o6ekxShoSEgJnZ2e4ubkhISEBNTU1ePjwIfbs2YOGhgakpKRgzJgxMDExga2tLSIiImRRq+PGjYOmpqZMp2vs2LFYvnw5Zs6ciYSEBBw4cAAHDhzA8uXLsXPnTkRHR2P16tV49+4dtm7dyh6TDx8+4M6dO6ivr8fjx49x584dRiHXrl2LrVu34vLly9i2bRsCAgIwd+5czJo1i/nQb968QUtLi0wXi9yHlpaWGDNmDGxtbTF27FgEBwcjMDCQ5RRcXV1hb28PKysrjBgxAiNHjoSNjQ1sbW0xZswY1gEMDAzElClTMGnSJISHh2PGjBnIzs7G8uXL0dDQgJaWFuzfvx89PT24cuUKrl+/juvXr6O/v5+jR1+8eIGnT5/iyZMnePnyJV68eIE3b96wMfbhwwe8ePECT548QX9/P3p7e3Hz5k3cunULDx48wIsXL2TctH8q/9nQCg4OZoJeXl4egoODZRMlFdKW2rhxIxYtWjSk0vk/5RxS5uWQcbBhwwbuRNOnT2cXEaDYUf2X9ADKvKXS0lKkpaXh+fPnPEBCQkI4MTQAmdhpfHw8/Pz8GEWjyUM6kf1TuO5QKYqktaKiArNmzYKRkRG+fPmCgYEB2S5WuUrbeMWKFSySJ4XkSaSOxBQJwn78+DEA4Pz58zwBk5uY0JgDBw5AR0cHM2bMwIMHD1QUvf/JOKCqjpslxDdXDSXypUhH6bNK/x8YGKgyoUqvT9yXR48ewcHBgQ0ONzc3fi9SlG9wcJDdAzt27GD3VHt7O548efKfEpMS6VZdaH5XVxejs1ZWVmhpacH48eOxY8cOHD16FCkpKbJIumPHjsHCwgJWVlbs+qH3CwDjxo3DwoULERgYiLNnzyImJgZv3rxhTSCaYHV0dJiALm3DR48eIS0tTYZwODg4yCKyTE1N1fK3CDVwcXHBjRs3ZFG20mjY4OBgBAQE4M8//2RtuWvXrnHfDwkJwcGDB9HY2KhWWkMIhRFMQQj0DBs3bsT8+fP5fUvdMHTM5cuX+Zmk53v58qXad/dvc0ZPT4/MrU/9Y/r06Whra0NRURFaW1tlY55QFDr/rVu3MGXKFADAlStXZOP12rVruHv3Lt68eYPm5mYmYF+7dk22adHV1cWECRMYYaR0ZcqCwPSdsgH5448/orKykjcsyu7wgoICODs7y4yjHTt2wMjIiA07Z2dnaGpqcv44qbdBCMGI1t9//83GlJTC8PXrV5w9exb37t3D8+fP8eTJE+Tl5cl4t35+fjA1NYWZmRlHgqempvLYMjIygq+vL7y9vREbG8suV6nmlIODg4w+QKKY5DGJjY3FzJkzZRGu+fn5CAoKwpYtW6Crq4t169bxuL548SIHKjU3N6O5uZnnzZs3b6Knp4cjyzMzM5GSkoJ3796xtMfLly8RERGB0tJSRt9dXV35/ElJSTAyMsLUqVMxYcIE2TwSHBwMNzc3+Pv7o7W1FcuWLWPumbTtlTedeXl5mD9/PsaOHYvo6GhMmTIFBw4cQEBAAOrq6rB//360tbXh1atXWLx4MbZs2YINGzbg06dP6OrqwuvXr3Hq1Cn2wJw4cQIAsGzZMkb8kpKSkJ6ezrSMpqYmdHV1ISIiAtu2bVMRINXR0eE8jWZmZqypZWlpCQsLC1hYWMDc3JwNLDpm+PDhrMNlaGgIAwMDGBkZwcLCAg4ODhg3bhzCw8ORkZGBhQsXorKyEjU1NWxw7d69G3v37sXBgwdx6NAhHD58GCdPnsTFixdx69Yt3LlzB48fP8azZ8/YwPrpp5/w9u1b9Pf34+7du3jw4AEuXbqE69ev48qVK+jr68OZM2dw+/btoY0mSfnPhhapHguhIIcCqtpH0lpVVYUzZ85w+KybmxuGDRvGE2J8fDwP4JKSEg7xJy4VTSDDhg3D0aNH1S5ihYWFmDZtGpYsWcLnlSJeVKWhwE1NTaiqqmKEIiAgAFlZWczdWblyJU9SRPAXQrGYbt68WWYEjhs3Ds+fP+drC6FAyby9vfHTTz8hIiJChliQKrn03vLz82Fubs4DtbGxEUIoFmX6++HDh6itrcXs2bPZveXr66uWbE+LgYWFBZYvX87XlgoGHjx4UKYvVVtbK+OiNDc3y3bFgYGBaG9vZ6NI2p7SxNfkhhtKCVuaHsXZ2Rna2tq4ffs2oyZ+fn78fNeuXeNoSum9EbdLCMXCTygCtYUUYaVFQ/p+lGtFRQW7iaRuv7Fjx+LGjRvshtm4caNsJ06LPXH56HdS94++vj4SEhIAKHbeUhSR7olSOKSmpqpEZN65cwcaGhq8o+dB+/89hojcQwlbSuvWrVtZmV3ZvTkwMCATspwyZQpndaCclUIo3LjqUifFxMRg1apVCA8PR1dXF5KTk/Hu3TsYGhoiNDQUpqamGDVqFIfHA99yGBL3Ulppl/jrr7+io6ODn9nOzg6ZmZkICQmRPQMZNpMmTUJ2draMrqCtrY2BgQEEBgZi1apVvGBKF2YAKpIedE1ClJydnWXGJwCOPhVCgcTt3bsXrq6unPIjJiaG57ElS5Ywx27atGkIDw+XufuokPGqzoCSbk6luU6p1tfXw9/fX4awkyFJUdHKQse0aaIxS++DDLp169YhLS0N169f53sqKirCkSNHsH79esTExCApKYnnBgsLCxXD2cLCAq9fv2buJRU3Nze0trbi5MmTjDZqa2sjPz9f9vz0rp2cnJCTk8MIUnh4ONrb23lc0tgDFERuQsQOHDiAdevW8TiPi4uDs7Mz/P39Wb2/uLgYCxcuZJf5wMAAuru7UVFRgb/++gtZWVkoLCwEoKCIAArCu6urK5PZ6R0AYAR2w4YNbCBt3bpVtiEnWQL6P3lBjIyM4ODgACsrKyQkJGDs2LG4efMmX2fMmDEIDQ3l5NAFBQVYtWoVUlNT4eXlhdTUVJaPoXr9+nXcv38fdXV1uHHjBt6/fw9AscHesmULBgYGcPjwYXz9+hWbN2/G+/fvGbksLy9n9+fZs2cRGhqKpqYmDAwM4OPHj7h37x6OHTuGR48eYeHChWhsbMSyZcugqakp42lpaWnBwMAAJiYmMDY2xrBhw1jM1MTEBGZmZpwT0dHRkQVDx48fjylTpmDKlCn83AEBAfDx8UFwcDCSk5Mxf/589hDU1dWxUOnRo0dx/PhxnD59Gn19fejt7eWcoOQCvH//Ph4+fMiuxcHBQfz00094/vw5rl+/jnv37mFgYABPnjzBkydPcPfuXdy8eRPXrl2TUQn+qfyPXIeUH0oIIcv2Lq1SqFtbW1tGGAbkUYF0LmNjYwAKaJ8k8qXH0HHSWlNTg+fPn2P48OGcD0wIwdFS9vb2CA4OZgONXBfK58nIyEB7e7tsh+ft7Q0fHx9Z9BAJuUkn28zMTJ64AgMDAXzj4iQnJyMrKwvjxo2TLf6ENilXWrhDQ0NlBuz27dvh5eXFxl9sbCwSEhJku0AtLS2eIMeNG8f8i8LCQhVe1JIlS/hajo6OKC0tRWJiIp+P2kjaVo8ePWIir3RCE+Ib+iVVy1aubW1tSExMVFkcysrK0N/fj6ioKA693bRpE7t+hFAYAefPn+edOCGJQijcNps2bcKpU6fYhUZ15MiRaGhogImJiSyNkru7O7S1tXH69Gl4e3vj48ePPKl3dHTAzc2Nw9t//PFHbnepQSltm9jYWFy5ckXmKqbvidRcUlLCrojw8HDeGFB4OmncSKPuiOsjfX/K+f4o3dJQhi29k507d8rcG1RpcQwPD5dFvBLiR+7R8ePH48iRIxg/fjx6e3tx4sQJ1NbWqhUk7e7uxp07dzB//nx4e3szquru7g4TExOMHTuW28fZ2RmmpqYqxpuNjQ3evXvH/7979y6ioqIwadIkTJ48WSXYwdjYWCaTQVFvzc3NaGxsZDf/yJEj2XAsKSnB1q1b2RAht29OTg6uXbuGhoYG5qKEhYVh9uzZsjlv1qxZOHHiBNra2uDi4oLnz59z8MeCBQsQHx+PLVu2YOLEiYxMESJIXEtTU1PU19cjOjoaHh4eqKurk6Esr169kvHVKAfevHnzAIA5PpMmTWIahXRuMjMzw8mTJ/H161d4e3sjODgY3d3dCA8PR2VlJbq7u3Hy5EksXLgQQUFB0NfXB6DI5enk5AQtLS12H5Mxk5mZiZKSEqZsEJ+KEHhSPLe1tVURptbV1UV8fDx++eUXPHz4kF24AGTRn8ouZYrAXrhwoWyeJq8GaZ3Rxpg2iY8fP+aIw82bN7Pu2OnTp5Gbm4tjx45h9erVLNsCKPJr3r59GykpKTh48CDfn5ubG3M0T506xRpbCxYs4LUnICAAGzduBKDg/C1cuBCLFy/msQLIkTdluZ+oqCge76NHj4arqyu3YW5uLjo7O2Fvb49du3ZhypQpWLZsGX744QfWAGxra8PmzZvR1dXFoqtr167FhQsXcPDgQaxfv56fh4xeyoIAKIzLN2/eMBeX8kmWlpZi/fr12LZtG5YsWYKVK1fi1KlTaGhowJYtW3Dq1ClcvnwZ79+/ZxS9s7OTES3S0tLW1oaBgQEjU8bGxjA1NYWlpSXs7Ozg7OwMb29vTJgwAdOnT0d2djaLhRJKVVdXx6ruK1aswPLly9mYPXDgAA4fPoz9+/fj1KlTuHfvHmtlPXr0CG/evMGnT5/w5csX/PTTT/j8+TN++uknvHv3DgMDA3j58iU+fvyIwcFB/uzu3bt4+vQp3r17h0+fPnHU4eDgIBtk/6X8jwwtmsyGynO2fPlyGcwuhILkSpMY7cjy8vJw6tQpPi/V9vZ2NszIZ0t55IRQIELEfxgzZgyOHDmCKVOmcPizci0qKsKGDRvg6uoKIyMjlYgP6XHKYoYAZK6Rjo4Ofm5aVHV1dTnEGvhGMCYF34kTJ7L/WHkCIfIw+a7VaTDdv3+fuWzHjh2TpXmg/Fd6enoy12ZaWhoqKirg7e2NCxcu4Pfff5dFCAJgYqqXlxf6+vq4s0qPkd5HVVUVIx7Ozs548+YNGyDEQaKJsq2tTeayDA4OxqZNm2QJWqlfENopDRBQNhoIBSHtHul39vb28PDwQFJSkkqSXeDb7l1fXx/d3d3Izs7GxYsXmfhfUlIi+x0N/kWLFiE/Px8rV65kFfHZs2fj+vXr6Orq4skwKSkJeXl5MDMz4wUyMDAQO3bskHGiqP9TlFljYyNCQ0Ph4OCA/fv3M+z/+vXrf1SMB1S1u5T7FfUpGq/0+YoVK2BmZqYSUQoA7u7uePToERuGp06dkiE8hLxQH71//z6jpRTNOm3aNFkkH70r4nO5u7vz+C8vLx9SpDEnJ4cT69Jn06dPh6mpKRvEjo6OyMvL476ycuVKzJkzRzaOlTeCN27cYP2qgoICmJub49mzZ9wXaN7Jy8vjBfvevXu4cuUKIiIi+Hk8PDywfPlyGBoacnBFdHQ0Lly4wClwzMzM4OjoiDVr1iAlJQUDAwOchmrUqFH8HA0NDcwLTUtL4zY3NzdHVlYWoqOjMXfuXFlaqLNnz7KelHK6Iqpubm7Ytm0bfH19cfnyZbS0tOD169dwcHBAR0cHWlpa2CBYt24d6uvr4ejoiNGjRwMAG3cA0NraymM/Ly8P7e3tGDVqFPT09FBfX49Hjx6xAfLw4UOen6Vix3Qua2trDB8+nKMSKysrAYBpBeRVCA8Px9ixYzF8+HAVTqK0/v777/zeaPPy119/wc7ODrNmzcLPP//MARP79+/nhfvu3bsAFITv6OhoFBcXM7/w8ePHiIyMhI+PDxISErBu3TpERUXJBHsbGxv5HIGBgXj+/Dmqq6vh6+uL3t5eAGB9uaKiItTU1GD9+vUoKCiAt7c3z5UGBgbw9vZmd2h6erqMRkB13bp1iI+Px/bt25GWloavX7+ioqKCtaEuXbrE0caAAqU6f/48u1XPnz+PGzdu4Pjx42w8nj17Frt378auXbtw+vRpXL9+HYODgzhz5gz27NmDe/fuYefOnbzZiI6OxsuXL9HV1YWdO3fi6dOnOHz4MDo6OnDz5k1s2bIF/f392LBhAw4dOoSqqipZSh09PT1oa2tzHmJHR0e4urpi3LhxCA0NZZkHekeVlZVoampCe3s7tm7dio6ODuzdu5eJ7qdPn2bpjD179qCrqwu9vb24dOkSurq6cPbsWdbIunDhAvr7+/HkyRM8f/4cL168YNI7cbKIs/X+/Xt8+vQJHz58wJs3b/Dw4UPcv38fr169wsePH/Hhwwd8+vQJP/30E3766af/9xwt6YtPT0+XZYf/LzUrK0uWtFX5e5qEnZycEBAQgODgYJlUAuWJe/v2LQIDA5kw7+HhMaQBRQukn5+fzL1jZ2eHrq4uNDU1obi4GAEBAQgICJDxCU6fPg1PT0+ZNhJVadg9RZpIkS51xG2agKWTYWFhoQy9EeKbfpiHh4csZQ0AVgZub2/ngap8jcrKSlaWDgwMZCV0+p4WatqJDhs2DEZGRipiqbSzlxpptPuXphWi3GdE+KX+IX1Our5U9LSoqAiJiYmMphCkTrII8fHxTHBWbhchvmlkqVtUpeehShN2f3+/LPH2/v37VdL0SM8nTZkhRRpnzJiBhIQEFRdrfn4+wsLCZCH6dP7w8HAm+tvZ2TEn7vDhw5g7d+6QeduEUBig0vagqqyXRCRtaRvY2trCw8NDRfNJCDkfUp0LsqKign8ndXOQgU3o0a5duzjCUQihIu9CKBQZpFKdLuUKqE/ETEbiuXPnZHlRiZ9GbV5cXCybO8aPH4+UlBSYmpoyMbmoqEjGzwoICMClS5dkfe3q1auYOnUqxo4dy4huaGgo50d9/vy5zNgxNTVFWFgYcnNzGbWKjo5GfHw8yzMcOnSI54/y8nI8f/4c69at4wAWOzs7+Pj4wNzcHD/99BPa2tp4rErn4kOHDsnmUU1NTYSEhGD37t1YsmQJTE1NMWvWLJX3EBwcjOfPn+PXX39FSkoKXF1deeGia5Dh//fff2PNmjW4f/8+7OzsYGFhgbCwMDaUCBXJzMxk/SjahP79998AgMOHD8PT0xMfP37EwoUL0dfXB3t7e4wYMQKFhYWsxTdlyhSOvA4KCkJtbS08PT1hZ2cnI8Pn5eUhMTERkyZNkm0Oi4uLsXLlSvj7+8PFxQUmJibsHrt+/To8PDw4cq6urg4fP37k8Xz//n2MGDECt2/fxqVLlzB9+nQ0Njbi7NmzmDZtGg4ePIiEhATY2dmhsLCQ6SLu7u7w8vICoNCXWrhwIRs8/f39KC8vR0BAAG7duoXNmzfj2LFjmDt3LtauXQtDQ0MWgqWIUi0tLTg4OEBPTw8mJiYYNWoUgoKCMHbsWEybNg3BwcHMQSoqKkJ5eTlKS0uxe/duAEBJSQlmzpyJffv2MeH78OHD2Lp1K9auXcsafcSlu3LlCgYGBjA4OIg7d+7g2LFjWLlyJdatW4eWlhZ0dXXh2rVrLPFBJPHbt2+jr6+P+39PTw/LWlRWVuLy5ctISkpiQ0tfXx+6urowMDCAh4cHpk6diujoaERGRmLGjBkoKirC0qVLUV1djZqaGqxduxb19fVoa2vDgQMHWEPr0KFDOHr0KE6cOIHjx4/j6NGjHB1Jyu3nzp1DR0cHurq6cP36dVy7dg1XrlzBlStXcOHCBfT29uL8+fPMtyK34MuXL9nYevXqFZ4+fYoHDx7g6dOn+PHHH/Hs2TN8+PABb9++xfv37xkNo+jZf7Wf/tNRUDWM1NWPHz+ya8zf35/dPFOmTIGJiQmTQKWo1Z07dxATE8MukYsXL7JxIzV8iK8k9XGPGTMGf/75J+zs7NSibD4+PjA2NoadnR10dHSQkpLC5xFCcL4iMvKkYp3EJ5K6hKhKid3SnGfKVSo6qpyiZffu3TI3GFV15FwKl1Z3/JUrV2QIkpub25DpkqR17ty5svuTVqnWllQ9mdAWElak56ZCbhrpzp54ef8Usk+L5pQpU5h8mJSUhNbWVm6P+fPno7+/H0IoXAjStD3SamFhwS6z5ORkZGdny1CigwcPYsmSJQgODpY9f1dXl9rE5EJ8U9eXcnKio6PR19enIuoaGxsr6x9S8cyysjJezE+cOIGxY8fyvUoTbycnJ6OpqQkVFRWorKzkhU850q6lpQUFBQVYvXo1LzpSIxiAWgSLokCVdd2UeUpOTk74+PEjHjx4wEaWlGcn7fd//vmnivuUxru+vj6ji7RJoHd169YtTr8zbtw4TJkyRSXB+ZUrVxj9nDNnDnJycmR8JWnWB0LUx40bh5UrV7JshNSIzM3NxcePH1mxXgiFlhSg2Lnb2toiKCiIx4GLiwtvkqi4urqyQSY1thcsWMCBHdI+sXjxYlYXHzFiBLZs2cJ80iVLlvCGa8eOHVi9ejVWrVqFhoYG6Orq8r1HRERgz5498Pb2liGmZ86cgZOTE3p7e3Hv3j1kZ2dj8uTJuHbtGo9Vyl8ofQZpSiuSpaGxQhIGz58/Z+M/NzeXjW7SB6M+vnnzZsTHx7MMBgDWsaqrq+Noys7OThQVFWHPnj0YGBhARkYG83+Tk5Ph5+eHoKAgFBUVwcbGRsZ/Cg4ORkREBEJCQvDmzRvetCxcuJDlfqqqqmBtbQ07OzusWrUKp06dQnd3N0JDQ1FXV4c///wT48aNw6JFixAXFyfTMtPW1sbw4cMZ7Tt//jzy8vIAKNThOzo60Nvbiy1btuD9+/eYM2cOu5sIOSMDs6enB5s2bcLJkyeZcH3ixAmEhobCz8+PdcGI1G5ubi7bXJSVlaGsrAyHDx9GYmIiU1wAMIJTUlKCQ4cOYdeuXejv70d2djacnZ1Zo8/b2xuVlZXYvHkzmpqasHLlSty5c4e9KeQa/PLlC7q7u/H8+XN8+fIFg4ODuHLlCv744w8eOz09PXjw4AF6enpw+/Zt/P333+w2O3fuHJ48eQIAnDfQz8+P5R0MDAygra0NU1NThIeHIy8vj3PI5ubmoqKigo2sVatWsUjpli1bsGvXLmzfvh0tLS1oaWnh1ENr165FdXU11q1bh6amJmzduhV79+5lUdPW1laZUXb48GEcOXIEJ0+exLlz53D58mXcvHkTjx8/xvv37/Hx40dGuQYGBvDgwQM8evQI79+/x6NHj/D06VO8ffsW7969w+DgIB9HwTf/Vv5HhtbGjRtx8OBBHviTJ09mqHjixInYtm0bIiMj+fiCggIOraZBTTyU7OxslJWVwcvLC8eOHVObbiY3N1cW8iuEwIMHD3jBcXd3h7+/v4zoTbIOQy3qwLfwa4LKz507B1tbW0RFRXHKGOWIGuAb/6q0tBTW1tY8QQBghd/W1lZW0QUUOeFosNKx0h0akfjU3Sf9rS5Ck3aQwLc8lBUVFTLomUQVhfgWgUihzDU1NTh9+rRs4ZROwtK/f/nlF5lBOWPGDGzbtg1dXV3s0gMUBFSaiJOTkznhrRACf/zxh0p0YkNDA0cJSqtUNuTEiROIiIiApaUlh8YDYNfE6dOnWQuNInp2796NsrIymWECgOU9pM8mLVu3bkVJSYmsPzU1NaGmpgYAmCgLyInQ+/fvZ6J5QkICo0xjxoyRpUOSRubROCHDaNq0acjLy5NJJxw5cgR79+5lNwV97u3tjfDwcJnq/NmzZ6Grq8sLcEJCAn/3/v171NbWMhdSCIGff/4ZK1eu5HFpbW3NCAAADjJQ7ovPnz9HeHg4YmJiZEmd9+zZwy7smTNnyn4jxDfSdX5+PlxdXREWFoaioiJGWOvq6lhJXGq4REVF4dixYxgYGMDy5csZ3RFCVXeK7lUqHZOWlsauLekxq1evxsePHwEocte5urrKCNjUx4T4lpJGeWwaGBjw397e3sjKykJXVxcyMzNRUVEhyzOoLB1DZceOHfD19eWgGVK6F0KwwK+WlhZsbW3h4ODAmwFK5kznc3Fxwa1bt3DmzBk2ugGgr6+P5VOE+MYPowCTmTNn4uzZs8jJyQEAGYXhzp07jKJKUWopgrJkyRJ4enqitbWVja89e/bg+fPnHBl57NgxlJeXY8mSJfj9998BKPJBkpuN7onmRanhTIZQeno6v+/q6mosWrSIjVPSflqyZAm7y8hoIWRz4cKFKCkpwfLly3Hu3Dn4+vqyS/bNmzfcPr6+vjwPXLlyBRs3buSxDijWDl9fX5w7d44/u3XrFg4fPowVK1awp2XDhg38PSFI9vb2sjFcVlbGCZQ7OzsxefJktLe3Izk5GWlpaVi6dCmSkpKwaNEiZGRkcBTjxYsXYWVlhcrKShw6dAg7duxgOZLx48fj9OnT2LlzJ1avXo3MzEzMmTMHdXV1nPYIAIvO1tTU4NGjR3j8+DGLePb392P37t24d+8e1q9fjyNHjuDx48d48eIFsrOzmev1xx9/4NixY6xRRWvBvn374OXlxYaWvr4+G1phYWGctD0zMxOZmZnIzc1FTk4O8vPzMX/+fCxYsADz58/ntbGkpASFhYXIzc1l3a20tDSkpKRwXkNK+kzG14YNG9DS0oK2tjbs3r0b+/fvR1dXF44fP85ipkRmJ34lcdTevXuHly9fsmo8/fv69Wu8ePECd+7cwenTp7F//342yv+t/I8MLWU1dSEUnB16yQDw888/D5kxndJ7CKEQvyQlaGniY5pY1q1bJxvcALgTKxOvqQPfvn1bdo9D5brz9PRUWeCVczVJXQ804ImD5ezsLEO/pJUMF0CRnJaiT9QdS1WayLW/vx8mJiYqv9HU1JSF4BMyIkX4CL4lbo46zasXL16gtbUVnz59wsiRI1XaISwsDIAC+q6vr4e5uTnCw8P/kewuhAKRoTJr1izOSSc9Rmp4UUSgu7s7Hj9+LOP21dTUyN69tBoaGsr6pTpOgxDfdKOePXsGQ0ND3L9/XyWSiwwo4Bv6osyRUk6CTCUjIwPd3d3o7e1lQicdo7w5CA8PR2ho6L/2A3VVWmjhUnfc8ePHGT1Tx+NKS0vj/GD02cmTJ9Wez8DAgLkZpHwcFxen4qKXcrLoXidNmsTn/Ldckz09PTKJFulcI3UN0ibs1KlTvDjTe5eK1fb398s0+KjOnTtXJTcm1fz8fACKqGoAsn63Z88ejlSTbnYMDQ15zBL/jgIDpGH2RC4HwEaTVFOpoaFBZhDTfWdkZLCoo7IL1cDAALdv34a7uzsGBwe5TxNSuHDhQuaEDgwMYNKkSQgNDWVxTwBsJMyaNQtmZmZYunQpz1vSbA5OTk6IiYlBX18f3xuhwIT2hYSEoLOzEw0NDfDw8IC2tjaSk5M5CT3NSevWrcPKlSuxePFidHR08CbBw8ODIzCV301bWxsOHTqEhIQE5m9RtLiWlhZyc3Ohp6eH9PR0zJkzB4WFhayDlZeXBz8/Px43hDKuW7cOS5cuxW+//SZDdJWjx2izVVlZiYiICFRVVSEhIYH5wP7+/mhra0NeXh5mzZqFhw8fssgpoRwkAZGSkoIjR47gzZs3yMjIkCHpzs7OyMjIwK5du9DU1MSRnKtWrcKwYcNgbGwMZ2dnjBgxAvv27cPevXtRW1uL0aNHIyQkBNOnT0dwcDCKioowZswYtLe3w9TUFK6urli7di2KiopQXV2NpUuXYuLEiSwU/ObNG2zevBmXLl3ifH6Awp1479499PX1ISMjg5HekJAQLFy4EAsWLEBhYSFu3bqF58+f8zO+evUKXV1dnMC5trZWpp+lra0NfX19uLi4ICwsDHFxcYiLi8O0adMwdepUhISEsKZWYGAg/P394eHhwZGHVD08PODi4sKaY97e3ggNDUVqaipycnLYOFuzZg0jXYRwdXZ2Msfr4sWLTHQnDiXlMiQi/PXr13Hnzh3cv38fAwMDuHfvHi5cuIB9+/Zh/fr1WL16NQvu/lv5z4YWlePHj2PPnj0YHByUJXyljpOcnCz7v7pqbm6u4h4QQjDfQ7kGBgbKstTT55Svb8OGDcjPz4ezszPmz58PQBHdcenSJd6lq5vopf8/cuQIgoKC0Nvbi46ODrXGop2dHby9vWXuNDrP5MmT1V5H2ZChCVuKbgihcLPFxsaqTbhL54iKiuKoDoJ9perS0hQbZMio09OhtqLPfH19UVJSgoyMDHbX/vzzz/y9q6sr817GjRsHPT09dkXQ9dvb2xEeHi5DHNTVoQIpqHp7e6OtrQ1z5szhcylH50gXJ9JFUz6mpKSEM7rTZ15eXqivr+fFVV0/SElJkfHyMjIyZDpW0sleCIG//vpLxbCiyFplpFJZfd/IyAiRkZFYv34992+p61iaCUCKXkl1mgi91dLSYsOns7NTdh3ipEkzHEgNSCli4+7uznkq1Y0XKdqg7GqltlYnTUCRYaT+Pzg4KAsk8fT0BAAZd4v68OXLl1mHSMpLJHfegQMHAHwTQyX9OyK59vX1ITk5mTd0XV1dCA8PR0FBAUsG0Dlpo0bPS1QDZYNbatBJxXEbGhpw48YN5t+FhoaioaEBixcvBgBeHF6/fs0yKYACHSChRkChXD8wMMD9Ytq0aTh//jx6enpk/a+7u5vn5vj4eAQFBWHmzJlYvXo1lixZgpycHBl/kjhyr1+/VkHFlJHzly9foqCggA23yMhIpgJkZ2dj5MiRHEkcFRWFuro6dhsCCmNFmnT36NGjABSBM+TpEOKbCj9FwZLHJC8vTxZlS0a/iYkJHj58CC8vL6xcuRJ2dnZ4/fo1z9ljxoxhKRU3Nze8ePECNTU1/E4OHjwoM+z+/vtvPH78GK9evYKlpSWCg4M5iAFQbDIo8IqeVQjBKCD1XSqkFt7c3Iw1a9Zg9uzZAIBp06apoPpGRkYssE3j19nZmecKLy8veHp6YuTIkRyAkp2djTlz5mDx4sWIjIyEra0tDAwMGGmi88TExODQoUNsrP3888/YtGkTrly5gjlz5iA0NBR79uxh9O327ds4e/Ysrl27hh9++IF5WvRdW1sbjh8/jrdv32LTpk2srUVu23nz5vFmR19fX2ZokbGlp6eHESNGwM7ODi4uLnBycoKDgwPs7OxgbW0NS0tLjBgxAsbGxjAyMoKBgQH09fVZR4ukixwcHLhtAgICMGPGDBQWFrKRRZvKvXv34tixYzhz5gxzsp48ecJ5C9+/f49Xr17h7du3GBgYYMPr3r17uHHjBouV9vX1oaOjA01NTairq8PSpUuRn5/P/fjfyn82tFatWqWCtJiYmCAlJYVfhvLkSn7/06dPy0i758+fZ4PpzJkzcHZ25rQPbm5uvPuqqqpi1IsWQfq7s7OTozekbi2KHtm/fz+Cg4NZt4quo3yPykl/N23aJJtoqdrZ2clcT9JKUW1DSUjExMSwASh9Dqk2GABZdBNVil6ZPXs2Fi1axKq7AKCjoyNT45byoFJSUmSIUmpq6reXrrQAqnveoSodp3x8WFgYTp48KSNEE6dKCAXiMnz4cLS2tgJQuEyk6Aqd7+bNm1iwYAHs7e0ZvaAUHIQiSq8tvQbVoqIiWS5MIb5pnikHH6ir0mAHupbUSKJChpQ0DdLEiRNlv1dO26Rs+ErPB4Aja/Py8mToGt2Hrq4uXrx4AV1dXY56U5faSAghW2CpSu9ValQQ7L98+XJOEaSuv6iLpiSXkRRJW7ly5ZCixA0NDaioqMCaNWtY+yo8PJwRCCLaS9FgKlKe4ty5c3HgwAEVTpSy0U33SX0DUCTkPnv2LAAwdyogIAC7d++WRcFSJeRNmvuO0CmpS4iqm5sb8vPzWTqA+o/y87x7946lAoqKiuDl5aUSlFBVVYWCggKZ1pkQgg0LqRgrucXi4uLw6NEjfPz4EXfu3OHrKj9bX18fnJ2d2WVNcyq5mQHw+wW+cd2am5vh4eHB+nXSc1K/JfK5dLxQEmZppDUgzx4hTc1GbUeCzcQjjImJUdnIkGFEbV5XV8epkYT4FkATERGBzZs3Y9++fbJ0XYRSUpk9ezZvDAB55LOtrS327NnD7mdpOXDgAK5fv47g4GCMHz8eurq6MDMzw6hRo3ijqa+vL5O00NLSwqhRoxg1dnd3h4eHB3x9fbFhwwaW75k4cSIsLCzQ1dWFQ4cOITIykvM+tre3w8XFBatWrYKZmRlCQ0PR3NyMv/76C1++fOHkz1euXOHkzwBw48YNvHv3Du/fv5clVN+5cye2bduG3bt34/fff2fXPpWbN29i165dmDVrFgtJS+cich1KjS0tLS1oa2tDS0uLxXBdXFzg5+eHwMBA+Pj4wMPDA25ubnBzc8PYsWMxbtw4BAcHY8KECYiIiEBcXBwSEhKQmJiIpKQk5OTkYPHixWhubsahQ4eYxP/s2TM8fPgQDx8+xMuXLzE4OIiPHz/ip59+wm+//YY///wTP//8M96/f8+8LHKRPnv2DPfv38etW7fQ1dWFzZs3o6amBmVlZZg7dy5CQ0Ph6OjIc9W/lf9saNHObu7cuUOmeJFOgGZmZmhsbMSmTZvUqsMrc6CEUOzgiUxIHfq/VKmGEvndXV1defIgbo9UB2wopWhl1xFNokQqTE9Ph5mZGUPndD4AKobWjRs34OTkhIULF/LkTxFtlBgYABYuXIjPnz9zvjYqdnZ2iImJwerVq5GXl6eSyoaOVV5YhFAgdGSoUDuoizqjSgN5zJgxMlI0oOA+0KQQFBTEkTbSY2SdSgh27YwZMwbe3t4yZMnDwwNNTU3Mp1BuR/qX2l6aqJUMBen1yUCtrKxkEq+6Z9TS0mKU6M2bN2olBqRkcnL9kNFGqAYATrorxDf+kZubG28MgG+Cvq9evcKRI0ewe/dulg6QpjrJzc1Ff38/6urqYGhoiI6ODjg4OLAwsBAKtIj617/lAmxpaZEpxUsjSun5pG1kZGSEkpISXL58WUUYmBAF5XceEhKCZcuW4e3bt7CyssKvv/7KSWbpnEIITpVC/BIPDw+ZpAYZZ/Q74j0BUEkHI4RQUcT28fHhvnv8+PF/bBe6RlFREXx9fRERESEzhBsaGpjgK70OcWzIvUjF1dUVO3fuxKtXrzBhwgQACmLxjRs3mIpACKWJiQn27t0roxzcvXsXb9++xa1btxiFkKJc48ePR3BwMEftUqCRctJp5UoGjKGhIbvc6Nn9/PyQnp7OGlY059DvpIU08ohXJR2bgMKgISNx06ZN8PLyYhd5T08PI1UDAwOYPHkyI2PK74Tco+TRUOb/qatFRUXQ0dFBQ0MDQkNDWSvvzZs3CAsLg7m5Of766y82jKUbMtqYUyHjU5rL9PDhw+z+pChTSrTs6ekp42s+e/YM3t7ebKhIOYZ9fX0q907vmJLXC6HwzpDRIT12xowZqKqqQk1NDUJDQ1FVVYXy8nLEx8dj2rRpGD58ONatW4fCwkIcO3YMly5dwpo1a+Ds7IyioiJG106ePIkjR46grq6OkTHi+aanp+PLly9obm7Gs2fPOBUP6Uh9+fIF586dQ29vLz58+ICTJ09i+fLlKC0txejRozFixAjZ/E7BbmRo6enpwcDAgNEpikI0MzNDUFAQEhISkJmZifz8fGRlZSElJQWzZs3C7NmzkZqaitTUVGRlZaGgoADLli3D6tWrUVdXx9pepMFIMhW9vb24du0aLl68iO7ubla4HxgYYOL758+fub57944NK8p7+OzZM9y5cwdHjhxBQ0MDSktLkZOTg0mTJsHa2prROmUqy1DlPxta4eHhaiO9aKKkRUVKwPbw8MCePXtUhCqVI+vIHUBkWnUDUlqlUXFCCHZDFhcXq00mTVF7RH7X0tJiGFmdbhHwbUHx8/OTJZi1t7eXRZLR8eTGVHYxSCsZnK2trYxUSdtLOZGt9D5oInR0dER0dLRssSXxuNmzZ2PSpEkIDAxEZ2cnmpqaZOf4+vUrSz/Q+d++fYvExETk5OTA19eX71FXV5eTk1KlyEmKwqDPyZ2Um5srM/qok7569Qp5eXlYsWKFWi6GMg9l5syZMikFqUK/EIpUTJTxPTU1FUVFRUzyFEKwsUOLPaBIg/HHH38gLi4Ourq6ACBre+Xq7u6OgoICfPz4kaPp/Pz8GEWQSnVQ/e2339Da2srRQUIImbCsMppGbhXl89DESpPXoUOHUFtbi9u3b6tIWZw8eZLlRPbs2QNra2vZGOjp6eENgvTdAKrBAU+fPsXixYsRHR0tk5kgJIDu1cTEhA0J2rDQdw4ODmhra4OWlhaePXuG1NRUlJWVqaRgUt58UXTk8OHDce/ePe4TPT09EELIBFcB4OPHj+xmT0pKwsaNG9HQ0IC5c+fKZESsrKxkri9AgVQYGRlhw4YNKCgoQENDA8zNzbF+/XoYGRnxsxgZGXEgC6DQ1SssLGRU782bN6zsT/eVkJDACIO6d07jVfnvNWvWQFNTU62en4eHhwrVgidwIWSImo6ODgIDA/Hzzz8zUXf16tUQQnBQhZ+fHxISEnD69GneEGVnZ2Pu3Ln4+++/MXv2bFRWVsq0mahI3Y0vXrxAX18fSkpKYGdnx+mJSJkfUERx9vb24uDBg4zqlZWVAVAQ/0mslsaYuvmYNs27d+/GjBkz4Onpifnz5yMrKwubN29GX18furu7kZCQgJiYGOYX9vX1ITs7m118ZNRcvnwZAwMDjNSRBpe0kIRDeXk56urqcODAAc47SPPG8OHDsXv3brx79w4dHR1MSZCiOiNGjJAZXmPGjJEhvdK5jdTRw8PDuS1HjhyJ58+fo76+HpWVlaitrcXBgwcxYcIEJnzX1dXhw4cPWLFiBa5fv47jx4/D398fx48flwEXXV1dMnV+QjpJsHrPnj24du0aKisr0dbWhqVLl+LRo0dMJVi7di0ePnzISGVDQwPGjRunEplPkdhaWlrQ09ODvr4+DAwMMGzYMFaD19HRgaWlJaZNm4aCggKUlpaivLwcy5YtQ2lpKSoqKlBbW8s6b01NTWhoaGDdr6tXr+Ly5cvo7e3FkSNHsHPnThw9ehRXrlzB8ePHceHCBVy9ehVXrlxBf38/+vv7cfPmTdy4cQOXL1/GxYsXcfHiRVy5cgWXL19GX18fLl++jEePHuHFixe4fv06jh07hs2bN6OsrAzx8fFwc3NjugQZWTRf/Fv5H8s7KJPEhVC4CIuLi3Hu3DkYGxtzKPb69etx6NAh5ObmqjWAhFBo1YSEhODSpUvYv38/u1akCwqhaaNGjZJxtKSSCSUlJRxRJ4TCJShVYZfukBISEnhCmzBhAg4cOMAkWBqMhB4ph+8LoZrbj3aHFOJLcPTcuXM5wpE0YgiloAklPT2d25h2tTTIhqpv3rxhhIk4HBTpJX1X0gVQCEXQwe3bt/HgwQPmWwkhT9pKddmyZSo8MiEUyIaNjQ0GBwdx8+ZN2Nvb48yZMzLFY5q4Hz58yLIFZGzHxsYCUOywKFKP7lPKPaGdIBnys2bNUkE/lN/B9u3b4eTkxAuPcnJqdb+ja6jjDAqhMPrnzZuHwsJCWWoRe3t7GBoawsHBAe7u7mrRFLoeoDDApfwVOkaa1JuSsgKKjY0y14rGQF9fH/bv38+kWuJElZWVoaWlBZ8/f5a5JaguWLBAZuhKUzgR6imNelPu32ZmZrJceNLnpELjisZCd3c3XF1dGWlOTk5mt8WZM2cQEBCA/fv3y2RX6uvrceDAAXR2dgKA2rQ/0sjeocaJdEP3448/MrFXes9k0Ek3T6dOnWI0TUNDA1u2bJEhfVKqBPHBSKuLjnFzc0NXVxecnZ1Z5Z5KUFAQNDQ0AIDHRXZ2NlasWKEiXEwGqbIoM9Egmpub0dnZyRGShLRQfwQULkl6HyQALIQCJf3w4QOfs7i4GJWVlXjw4AEqKioAKIIhiHNIwSx07l9++UUF5Vu5ciXfA23UAMiikdW9N3d3dxnf1M3NDbNmzeK51tLSErt37+YNppGREc+dCxcu5MAOWnB/++03AArDMDY2Fm/fvsX169cREhKCbdu24dGjR7hx4wYaGhpw+/ZtuLq6oq2tDTExMYiNjWU5CtJvlLpPd+3ahR9//BFWVlYsfjl79mzU1tZiYGAAP/zwA4MHubm5Kkm+ad4dPXo0rzP0PmNjYzF37lxer7S0tFBZWcnurdjYWPz999/o6upCRUUFdu7cierqatTX12Px4sVYv349o05PnjxBd3c3fvzxR/zxxx/YuXMnZs+ejbKyMuzYsQPr1q3D4cOHcf36dZZT6O7uRkNDA06fPs2cL8oCQNpTFy5cwOXLl3HixAkEBgbC3t4etra2SEtLk20siJNFhhYZW4RoGRsbw8/PDzNnzkRWVhYWLlyIJUuWYOHChZwcev369WhsbERbWxs2btyIlpYWHDhwgKMHT58+jUOHDmHbtm3Yu3cvRwMePnwYXV1d2L17N9ra2rBr1y7s27cPXV1dLPNw8uRJ9PT0oKenR4Z6PXr0CL29vWhubkZVVRWSkpJgZ2cHbW1taGpqyp5JGvDyT+U/G1oUQeTm5sahylIfu5T/9Oeff/LkYmxsrLKIvXnzhl2HNJFoamrizZs3+O2335jE7OTkhOjoaPT09GDNmjX/6jLZvn27zC3R29s7ZPQaVWU0ZdOmTbC1tZWlXKFqbGwsc2fQ95mZmXB0dMSKFStkRGCa6OlfMkABBWy7du1a7sQ02QBgLgZFXnl4eKgQ8AHAyMhIppmlra0tQ9TUCbmmp6dDU1NThk56eHjA1tZW5hL+9ddf2W3U39/PkyAhTcptQzU8PJyNLikvjzSA7t27h4aGBjQ1NankRKPIH3L1CqFwBZMRMGbMGOzbtw+XLl2SRe5I8+VRP21ubuY8g//0/gMDA3kRUE6WTden8xN3iZ5fncAnQf/SnSqd19nZmV1wFJkk/S31702bNkFPT485jtLq7+8PCwsLpKenIzw8nDckdC4SzpXm+1Pur5QOSHrdKVOmsEEj/a6zs1Pmcvbw8OCF1sjICC4uLmyQ0+JAiI+0SA0V6ealtLQUnp6e/D4Jxfvzzz85yIAm76tXr6KsrAytra3w8fGBr68vG9/qgiy8vLxkfJ/Ozk6euwgNI0PQycmJ+7a1tTXu3LkjS4mkXOl+4+Pj2RU1ODgoc9na29vDyckJvr6+2LJlCy5cuMD3U11djdOnT8PZ2VkmKkpoCEXx0ufKaDeNzdDQUIwdOxa7d+/m+UVaKXCCcogaGBjg2LFjjKhXVFTw5pnmG3KvK3P/hFBENQJgqQAhFO7os2fPcoqm8PBw3uxIeb2fP39WQTLHjRvH7s2hqrW1NUJDQ2FpaYmIiAjs3r0bQqjyHbW0tBAZGQkNDQ1kZmaioaEBM2bMQFpaGpYsWYLXr18jPT0diYmJGD16NOLi4mSCs3PmzOF1zMbGBr/88gumT5+Oz58/Mx/s0KFDqK+vh4aGBtra2lBbW4vi4mLmP1VWVuL8+fPcz2jsODg4YOvWrTLEjsZBQEAAXF1d4ezsDA0NDVhYWGDs2LG8CZsyZQqmT5+OUaNGwcbGBitWrGDR0vT0dCxfvhzNzc2orq5mo2T9+vWora3FuHHjsGDBAvT39+PgwYMICgpCXV0dSkpK4O7ujtmzZ2P37t149OgRcnJy0NzcjJqaGuzbtw/t7e148eIFGhsbsXfvXuzevRvXrl3D+vXrsXHjRlRVVXG/jIyMVOFk6ujoyNAs+ldPTw86OjrQ1taGhYUFPD09MX78eMTExGDmzJmYPXs2srOzOdXTihUrsG7dOlbY37p1K7Zv344tW7agrq4O1dXVqKqqQn19PZqbm9HQ0ICamhqUl5dj6dKlWLlyJXPyDh8+jKNHj+LkyZM4deoUzpw5gzNnzuDixYuslfXw4UOcPHkS9fX1yMnJgZubG7S1tWWcM11dXX6W/1L+x4iWtEoHP0HQ5eXlKml4pNXMzAwGBgYcIadONJN0cPz9/WFra4va2loEBgYyKpSenj4k30g6OVy5cgV2dnaYNm0aTybqEjH39fXJIryoSvP7qatRUVGwsbFhBIqELYVQhL7b29sPKXVBfuyCggLmg2zevBlLlixh1G7btm0qxqWRkRFCQ0OZxC4lvFNU5FCTLXV+KdQ7duzYIZNTCyGYoExoU2trK6KjowFAJbps8uTJ0NPTYxL2gQMH+P6zs7MRGhrKfSY8PFxFO02K7lDfkJJZtbW1MTg4qFZmpLKyUq3YqzL6qM4tTciRtO2FUEQVXb16ldXxaRIGFKlJPD09ERcXhylTpsjQJylpNi0tTabLNWLECHblKFfa3T5+/JgFCoX4pqckxDfhSWUFeeX3riytIYRCE2z+/Pm4ceMGRo4cKeMnBQUFoa2tDf7+/pg2bRoCAgJw8eJFvH37FsHBwSyjIA12qKioYJ4b6Y3RuKNzBgUFwdDQEF+/flVB/eievby8EBgYyEZTfHy82ndMdfTo0Sp9RVr9/f056nT+/PncFsTlycrK4ndCtAIAqKqqwvjx42XpgtQlsz979qxKYA29byLWS7X8yP3Z1tbGwTa00WltbVUhfwuhQMCdnZ2HTFUkhGKDkZiYiNbWVoSHh8t4SGlpaRg+fDhH6CYnJ6OkpITldxYtWiTzGlhZWeHLly9wcHBAfX09dHR0WPWajDIhvpH6KQnv5s2bsWjRIjQ1NWHJkiXYvHkztm7dKgtQKC8vhxDyjYoQijmS+oAyAks8Jjc3N0ydOhUNDQ2IiYlhiRNdXV2sXbsWQnwzxDU1NZlntXnzZpw6dQrBwcGYOnUqJ5IWQmGkuri4IDExESNHjuRk0iRtoampCScnJ/j4+CAjI4OlD0pKSpCYmIimpiZ4eHj8f9r78pgoz+7tB5B93wVZJjCBCUyEwEQIEIUgyEQWiawRUSIViKISRSQoKsR9qUqsWMGNqHVfCFqXqtW8dalWq7HVVtv6mi629a0tsa3v21+v74/5zvG+n3lo+315my/5MndyBxiemXmWe7nOdc65Dry8vLBnzx5ePzdt2oTo6Gg8evSIi23T9TQ3N1vFX40ePZr3DqPRCA8PD3h7e8NgMKC4uJhBGe11np6eiI+PR0hICMaPH4++vj68/fbbaG1tZZBy+fJlLqlUXFyMlJQU5OTkcNB8fX09Dh8+jJqaGsTExCAxMRFNTU3YuXMnuru7cf78eTx58gTnzp3Dzp078ejRI6xbtw6TJ0/GiRMnUFlZidTUVKSlpcFkMiEhIQEBAQFSNRRXV1eEhYVZAS0CWy4uLpyFKCYKUK1Dk8nE9Q6rqqowbdo0NDQ0oK6uDjNmzGCxU9LRqqysRHl5OeuPia9XV1ejubkZa9euxd69e3HixAmcPHkSb7/9Ns6cOYOzZ8/i7NmzrKn1+PFj3L59G0eOHEFraytGjx4NV1dXVrkXA/vd3Nw4DOVvAVq0UX/88cc8GEjUraKiQoozePHiBe7duye9PyMjgyciWYBiELKYfk6TSU2dBwUF8f/ELmqd0ODMzc1lBi04OBhr1qyRFlB1GRPqVMzZbDZLcgclJSVIT0/HqlWrJKsKeCW26OfnJ2X70GQkq//P2DlFsbjbxCLcimIBWqJ+EbEQJSUlaGpq+lO9K/FcPT09kZWVhZ6eHn7fsWPH2A/t4uLCAJo2Qb1ej+XLl2PBggW8cdJGtmjRIisF/KioKKSlpUnBxXl5eRJD5+HhgYCAAAZuYlkY6g0NDTCZTFxv09nZWVMvSqsT2+Hg4IDRo0fD19dXcs+WlJTgxo0bOHXqFHp7e61KG1HwMY319evXIzIyUnJ1ij08PJyfu6+vL5KSkjBmzBjeJIipEQGUCGD6+/sRGRmJrq4uZGZmcnyKoliAuVa1ArGvWrVKcxyUlpay7o2iaJfc0ev1DE4zMjJYI0/dQ0NDUVdXxywIfWZVVRWMRiMH1IrvoQQQYjkotm/06NEsw/L8+XMWRV61ahUmTpzIlr8Imv39/bFs2TLekBXlFYtXVVUFnU6H3bt3Iz09nTOPxU6q8Q0NDfD09MStW7fY+FHPE0V5BWxDQ0Oxb98+Bp5qQBYUFIRPPvkE/f39SE9PR0VFBS5duoTo6GgucEwxRIpiYTVoHInjLiAgAN7e3pqB7w0NDRg1ahQ6OztRW1uLvXv3YuHChRwv5+DggICAAERHR2NgYABTp07luq2dnZ1oaWmxCjan89m6dStevHiB6upqBlqkDZaamoqwsDDk5+fz2tHW1ob6+nrMnDkTX331FV6+fImbN2/i7NmziIqKQklJCRYvXoysrCxNcWKj0chgMiUlBZWVlViyZAkD6bi4OERGRrIeksFgkOYWzV+SlgEswtJZWVnYtm0bIiIiWI4hPj4eK1euxKJFi2AymXhs9/b2IiYmBhMmTEBAQADLobi5uWHp0qXo7OzE9evXea9asWIFcnNzsXjxYty4cQMdHR2IiIjAzJkzMW7cOEyZMgXZ2dmSmz4tLc2KgRs+fDi7m8kd5ejoiLCwMDYSUlNTpbVBURT+XKPRiLKyMmbMjx07hsLCQjQ1NaGgoIC9NaNGjWKQV1RUBBcXF9TU1LDAZ1RUFK5du8a6Zd3d3WhpaeEA86amJhw+fBgLFy5EREQEwsPDkZmZiZSUFF4TSa5BUSwxdWazmVkfchuKAfGurq5wdnaWgAsd7+XlBV9fXwQHByMiIgJ6vR56vR7R0dHc6TXS1IqMjER4eDi7Mak6gMFgQH5+PubNm4euri7s37+fayZS5ubZs2dx8+ZN3L17F/fu3cO5c+e4xmVAQIAEskiAla6FSvD9KX76S0f974EtxkqEh4fjyZMnUmyFetKKCywFQCrKK7CRkZHBAWYjR46ETqdDfX097O3tmSFQW0HUKa5I/V27du2yYjYqKiq48jdZPKWlpX+YvSPGD1HmFP09MDDAqd1/9P6CggKezE+fPmULcsaMGVKCgKurK8xmM4MaGrBiuRJF0RaIFP8mWYy2tjbpHtBxWvE1ZEnOnz+f6/RR0VpiWJqamjTjuKiTqzApKQk5OTlWcW3BwcEwGAzQ6XQYOXKkxPwpyqv4Nepa8U49PT24ffs2MjMzAbxS7d68eTMSExPh7u6u6eqIjY1lkG00GtHS0oKPP/4Yx48fR0JCAmcUUrabi4uLpBUl9smTJ0vB7UN1LRck9dLS0j8E262trbh16xbrKdHrxARu2bJFKqcidqPRiOHDh/PGHRERgXXr1sFkMklAl1ySxDSIrpuioiIYDAa+BmIART0j6qICO403Oufly5cDgFWtPeonT55kBmby5Mk4fvy4lFXb2NiI/fv3Y8uWLWhvb8ePP/6I5ORk5ObmYsmSJdizZ49UX7S4uFgz0UJRXhlpYo1LRbEkdajnFAEmJycnnDp1CvPmzYPZbGZw6+joyO5+ctv/9NNPmswTubG3bNnCmz1VCqD7FRwczBvpyZMn8fLlS4wYMQIfffQRK7zTs5g9ezaOHDmC+Ph4Bo+iK4rccmVlZfxeWrvEe6uOp5wyZQqHWMTFxTEg8vPzw4MHD/ja33jjDfT392uuQwC4QgO93tHRgaioKOj1eqkuoaK8WsvS09MBgFXB6ZouXLig6WVQFEUyIo4cOQKTyYTMzEycOnWK2VhFsQD4oKAgZg+TkpJQU1PDLuIJEybwcxD1C8WQj8mTJ6OmpgYffvghs5WUfXj+/Hns378fPT09PLZoPxRDOkaNGgUPDw9EREQgJiYGBoOBXastLS1SgpJ6PpM0iXjNYlKLaHSJBEd5eTn0er00RxTlVfiKs7MzysrKMHnyZEyfPh27d+9m/ayuri6sXLkSd+/eZVHmqqoqtLe3Y+TIkQgKCsLYsWORnZ0tjb+amhppDhLrowZZxGiJnUAMST84ODjwddrb28POzg729vbcRZkIBwcHPoY6nYODgwMCAwMxfvx4tLe3cw3Fo0eP4ujRozhy5AguXryIDz/8EPfu3cP58+fR29uL+vp6REZGWrFYYgYlMV1/CT/9paOEyXPjxg288cYbePDgAcaMGYPGxkYsWbIECQkJsLOzQ0tLi8QQ/fzzz2hubkZgYCDKysrw2muvMYixt7fH2LFj8cYbb0Cv11tluYkTmX6fPXu2puI0HdPa2orffvvNKvuPYmKamprg4+ODurq6IVXF1Z20MpYvX46xY8di//792LVrl8RoUGwJbZ4bNmzAjz/+yP9ftmwZWltbeZMlcCHGr1FgKpXHoGtSU87qBY7AUlBQEJKTk/HFF1/we+fMmSPdP0WxuEqnT59uJRALWEqFiCxaZGSkZiaQuGk9e/aMJzDJK5D2iYODA3755RcrJX3xmoYCNsePH4e9vT1+/fXXIV1JABgoiN8RHR2NL7/8Etu3b0d2drZUXkZRZE02GlcUxzJUB16JYhIjZzQaWT5BfZ+1XouPj7dKDLGzs8Pz58+5Lp9W8HdwcDD0er1mpqSYJACAM6oUxcKULVy4EOnp6aisrISPjw/mzZsn6WGpO8XKkctix44deO2119hQKC8vt1Jap+sUWbqSkhIsX75cclHRcQA4K04rtojm07BhwxAaGiqBOkWxMOU//PADTCYTFi9ezK4iRXnlghXnt7u7u1UiT3NzM548ecKxiSLwraysxIgRI6yeH2W0jhw5kmPTnJyc0NjYKBmdAQEB8Pf3x++//47c3FzJeKASRsRgqfX01ONm7ty56O7uxrp161iJuqmpCc3Nzfj111+t2MuBgQF2p9HalZqaitdeew2XL19GeXk5r4/ECJ48eRKTJk1CSEgIOjo6UFpaiqVLl0rBzbm5uaisrER3d7e0gf/888/YsWMH5s+fL7E2kydPltL+xa61psyZMwdRUVFs1BUVFSEvLw+tra2YP38+NmzYIB2flZXFRkNhYSH279+P2NhYXLt2DYODg5g3bx6uXr3KbF5TUxNLA+Tk5KC2tpZ12QgYEcjq7u7GxIkTOfONDB8Snv3hhx/Q39+P1NRU+Pr6oqGhgcFTamoqy9DExcXxtebk5CAwMBB6vR4dHR38+qRJk/iatUI/PDw8+Dp1Oh10Oh0yMjJgNpuxcuVKJCcnM/tF79Hr9QgODkZOTg6ioqIQFBQksfhiZuzChQvR29uLnp4e9PT0YO/evZwU8/nnn+P06dNYsGABCgoKeP+KjY1FaGgoz53Q0FArD4OLiwvc3d2twJYaZFHMFsVtEYASgRUBLRFI0e9qkCWCMdrLAgMDUVpayiXWdu7ciT179nCm4v3793Hr1i3s3bsXra2tSEhIYFCoZuTIDerm5vb3AS2amDk5OUhKSsLixYs1y16oe2lpKZycnJiGpo1OXQOsuLiYB3tISAiWLVtmJfrY2dmJ2bNn45133uEbrijKkPEMjx49ktgO9bl6eXnh/v37PNgjIyOlRdfd3Z395jTRAHAM11tvvSWdo6urq5WrU0sTSFFeAQ6xRAv9JIuutraW6yrSxFMUi0UWFxen6RpJT0/HlStX8Ntvv8FoNGLVqlVoaWlhTRytc6FYjJqaGrYCRUC0fft2BrliDMrRo0c5ziQvLw+enp7sflRbVFpdTFgwmUySwCT1L774Ysi4PBpD4lhNS0v70zEpZo+9ePFCCqguLCy0ArgiYIiNjeXFlACueKybm5uURaW+Z2qhXOo1NTUwGo0IDw/n7xPZ29zcXBQWFkrq9Wq2QN3HjBmD7OxsjqMQ5QCGukekOWc0GtHa2sqbldhpoVbLRqiPU8eT0Tl3dHTgwIED2LdvH8LCwvDLL7/A39+fqx4oikUDj567Wr9v4sSJWL16taabVM3AaYFXRbEketTW1mL48OEwGAzw8PDg5AtyJVJsF7FDJpMJ1dXVUi1DRbHEQhJbtGXLFrS0tGDv3r04ePAgZ1UrisJ1Dc1mMyda5ObmYuvWrXj58iW2bt2K1tZW/vzr16+joaFBcrcriiWGVKySoCiW9ZkqKtA6WlBQgHfffRetra1s5Pb19UmxYV1dXSgqKoLJZMKmTZsAwIpRJ73CjRs3wmAwMCCna+/v78eBAwcAWMQ9qR4p3UtaL/fs2aMpphsSEsISP1pdSxhWHItRUVHIy8vDtm3b8Pnnn0NRLIHkM2bMgJeXF9zd3ZGamoqRI0fCy8sLCQkJyMnJsQp3IAX7lJQU+Pn5sVaYXq/HjRs3cOfOHc5K3LFjBzZs2ICTJ0/y+ykOj0IhtLwBYhzzXwn3oGfp6+uL0NBQZGZmskRHamoqMjIykJyczGOW5lxMTAxMJhM8PT0lyRxFsax/K1euRGlpKWurffzxx+ju7saqVatw/PhxzpTesWMHoqKiMGnSJAQGBkKn06G4uBiRkZFsKKg17oYCWlqMFoEskc1Ss1NaXTxOC2wRI2Vvb4/ExEQ0NDSgo6MDO3bswMmTJ3Hjxg2Wiujv78eSJUuQmZkJDw8PuLu7S+dPP+l1d3f3/z7QAmBVnkLsL1684NcBC6NB9fhEPaPff/9deh/R4uqHpCgKR/TTYiEer/WevLw8zRI24jlfvHiRf09MTMTu3bt5MVUUS8aUqA2kjtehOJvExEQkJSVxYV7apAcGBvgYcTGhjUrr3ok9Ozv71cMRXhfjGwDgwoULACDVVqT/f/LJJ1wqw2QySYHD4eHhOHHiBADgt99+Q1hYGKdj0+YfFhbGZVmKi4thNBoRFRWF33//nSf8J598wu7gR48e8ff7+vrC09MTT58+RVpaGhoaGmBnZ8dAs6GhAS4uLlKmYFhYGFseAKTMLToHrXvl5OSE8PBwTRewwWCAt7c3Hj9+zK9lZGTA29vbSpHe3t5eylalRYj+D1iyrFJTU1FVVYW4uDhs3LgRP/74I8aMGcNjn5ST1eeiFXNWWloqsa4//PADLl26xAuU1ljREqzVYrj8/f3ZkKH5QsBZLHEjdrHuI7n0AIvGEGWXiZ1EYqmYuqLIbv7BwUGORdNykR4+fJg3mMTERCu3nsj6ESAQ2ZWMjAzMmjXLijFJSUmBnZ0dW8aKYmHgxAxpAPj000+RnZ3Nwog9PT1WaxMBU2oZGRnMRFOSCz0zRbEAETGOLCIiwuoZ/tn8V3cytgDwWqUoFhFasfSPoshZeAMDA7hy5Yp0fmJWmNqYmTRpEmbPno2cnBzU1NRIZbYI4JD7s7u7m/XJSNNw9erVkpzO3Llz/zCWkBJMqIvuSLGkldFoZOO8pKTEKrt05MiRyMzM5HV/0qRJ+Pe//83gxmw2833KzMzE6NGj+bwofEPct8aNG8frYHx8PJqbm3nPoHXo5cuX6O/vlwwndVYo3TetZC8xHtnR0RHz58+XdPmysrKk2ENFUSQvQ11dHcLDw7F06VJpHaVeU1NjFQ9HivGK8srF7Orqivnz5yMkJATvvvsuDAYDfvnlF1y8eJFV8t9++22W2tHpdLCzs0NhYSGfj6OjI5KSkhg4tra2wsnJCSaTCc7Ozn8JaIluwz9isxTlj4GV6EJ0cHCQgvEDAgKQmZmJpqYmrFmzBmfOnOE6j3fv3sW5c+ewatUqTJgwAb6+vlLwPullieDrbwNaimLZHEJCQvDvf/+bs9EASBkHZPXQe0TxwO+//94qZfq3337jh6geMGRp0GdRuQORuaIBTscMDg5aCYo2NTVJaueKorC+FaXpinXbiGKlzxTZJprA9FO09H19fVmY8ZNPPpGy6mjyiuwDuQ3Jtw5Y/P4RERGIj48HAFy9ehUzZ87kxUJk5ghkkfqx0WjE3r17+Vr+LJ5IzLBTFMtGTtcpyhPQa+IiOG7cOGzcuJHZB/XEBiw6OmrLVSy6S/3evXtYtGgR8vPzpcWrqKiIN5qHDx9yiQ0KiH327JlU7kbsYuUBOhf6u7KyUlrsFMUC5ijuKyoqSlrQRU2i5cuXcyIHNXom6tp/f7VnZ2fj7t270Ol02LNnD7OGK1asYFVqOlZrnojjUDyWBCfF40T3AgE3cZO7desWb87ELgwMDHChcuoiQyQyI1T+RP29imIJvj9w4ABKS0sRHBzMlnljYyOXmVGzNoryyo04bdo07N+/H9XV1TCbzZLrTR3cffToUUkaRFEs8SyUAFBQUCBlzdrb20uB1tQrKipYTFUrAxGQS7OkpKSgra0N+fn52Lp1K37++WdNd1Btba0kv5KXl4e4uDh88MEHVjUxiTlNS0vDf/7zH+l/BHTKy8vx/fffSxuewWDQjMtMSEhgxp2kBOg50zHifSOhZ/FcFMUiuHv69GmeB+vXr7ea77ROOjo6Mhii+0nnQK5/NeuoVcIpJCREM+RDXH8o5k38PJ1OJ62ddO/VRtx7771nFcPW09ODPXv28HXW1dVpln2ihJUVK1bg4cOHOHz4MJYuXQpPT0/NMaDuGRkZcHNz49qFY8aMgbOzs6ablXpgYCAz73RfXF1dkZSUhMLCQsk4E8Gck5MTFi9ezJntycnJ6Ovrw8OHDzl+qbe3F8XFxRg2bBhiY2P5udGzy8nJga+vrzSOxWxnkdEaKiieQBeBLWK2RIZLDaKGchPS/+l94rMvLCxEa2srXn/9dZw6dQqXLl3CuXPncPfuXXzwwQcsBRIcHGyVKUmgisAWAS4PDw8MGzZsaNAktP8joHX8+HHpIf/666+80Q0MDGjGTimKZXG/c+eOlerxwMAAHj58KLmORIqTYnfa29ulzUBNgdKCR0102Yhggizr1NRUODk5ISoqioU+u7q6mCEDXpWtIf0UMcWZ+oQJEwBYsqcIuGVkZMBoNFqBGLKiyJIrLi7GkSNHrK6FNi0K0u7o6MDy5cvR39/PG0t4eLhUB04r3sbBwQETJkyQpBvEZ6kocsAm/V9kJc6dO4fk5GRpMFEwuvg51DMzM5GZmYlly5Yxi1NUVMQAeaiFQhwXNTU12L9/P3JycjB79my0tLQwyDxz5oyk2eTv74/GxkYr8AGAF1v63lmzZkkFr8V0ctEFQu8hsUR6HQA/G3pNpPw//fRTq/lCYE6v10sAU4zZED8HgOSCoNfMZrOUydjU1GSVMQhYSoFosXuApXIBMa2KYgEaJ06cQGpqKioqKpCdnY1NmzZh7dq1fN60EXZ1dXEcFY1jUXx18+bN8Pb25iBh+l5y35Ih1tTUxOdHmciurq64ffs2vv76azx79gxdXV1Wz2LhwoX48MMP0dnZiSdPnjAIJkOCjBv1+xoaGljYVHTt/+tf/0JjYyMLcFK/ePEiA/Lg4GDeQBISEtDX14eTJ0+yYbFgwQJWq6f27NkzBliApfLA2bNnodfrcfHiRS4LQswQxXiWlpZi3759HEhM40/cnIeSs1i8eDFycnIkhWoxVgx4lQl97949npdnzpxBdXU1XnvtNSuXHLEkIqNHbj/yMqSmprJO3Ztvvslzi9TRxXkwfPhwjjGaMGECz6OLFy9yySNFUf40Zvb3339He3s7KisrrWIE1VpcH374Iezs7HjPGjZsmKbsEJUIUxSLQb127VosWLAABoMBZ8+e5T2IgNbhw4exbNkylJeXY/fu3WhpacGVK1cwdepUyUggYdb4+HjY2dlJOnXFxcUYP368tP4SIPXw8EBRURG8vLwwZ84cTeFh0m/y8fHhfUwUlxbZSn9/f9jZ2cHd3R2ZmZkwm82orq6GyWRCQ0MD7t69K4nIUixzf38/s/gGgwHu7u7o7u7Ghg0bMH78eMTGxjKYo301KytLCmNRxzMNBbbEGC0xTksd7K5muNRd7W50dnaGwWDApEmT0NHRgY0bN+L06dO4c+cOLl26xPpZfX19qK6uRkhICAe7i6wVgStPT0/u9Np/HWiFhISgsrISJSUlGBwchKenJ3x8fKysPNHiEeNQ1BNBnIhiFwunTpw4EadOnUJgYCADHlqMxLqFqampQ4rebdmyBUeOHGGdDvV304ZBx/v5+XH2no+PD7799lsoiiWu4tq1a0NmiFAfMWKElV+ZNlbxe0S2YdeuXZKqvaIoUvFcWpArKyvx/PlzqzIsimKxbGmBV7NLWtl49fX1WLFihRSITCq3Q11bc3Mzenp6cPLkSXz99dfw9PREXV0d6yaJz018zpRppb4HivKKxm5ububYBkWRCyKrLToA7K4b6nzV5Yconm+oLipkk1tIrW+k/i69Xs+xUqSAP1QnN+G+ffvw9OlTPHnyBL/99ptVppz4HWIRXvXn0fUEBwdLwqbqe6LW7BKtdTEZwmQyobKyEhUVFejt7WXXMXXKPkxPT8fTp0+tzufixYvM/NGzo02UXNWKItfyUxTLYujv7w+9Xo8jR46wq2XUqFFW7Ke6bhwAK0OF5p6Wy4Z6cXExl06ZMmUKIiIirGKdFMXCTDQ0NEj38/PPP2ej69KlS5g/fz6ePXuG5cuX4+HDh9LmSQXU6W8yvv7zn//g5s2bVhpvJBlB2l75+fmsSP7w4UPN8aQocuyfuhO4IGOEGAd1XJAIwsX7u3v3bpw/fx49PT08tjo6OtDZ2cnyOufOncOxY8c0x+mJEycQGBioqRXW29vL78nJyQFgUa5Xi0grimW90nLBK4olQ1Wdab1+/XorQ5LuGQFJWssBS3Ys1a2jenjvvfceb6SUqEIuc63z8Pf35/mlXg/27dsHDw8P6HQ6rFmzZsjY1bFjx2oWns/IyEBbWxtmzZolASkR3FFcFnl0xNhIBwcH7Nq1C++88w7XTD127Bg+//xzvHz5Es+ePWN9ymvXrqGrqwtdXV1sbKnX4Li4OHZxpqenIzs7G5GRkZg+fToz0FpAayg3oshoaQXGawEuNcslxncFBgYiPT0ddXV1aGtrQ29vL44ePYrjx49z6Z1z586hq6sLNTU1iIyMlDIKiYkjoOXp6QkvLy94eXlJgOtvkXdQD7Cenh5mXiijSUylTklJYaStpaGiDhjX6uL3q8+BXD2kkj3UZ8ybN4/f5+LiwgsZue7U8QLq67x37x7+8Y9/ALDEPFFmpfi5NDm0fOb0mSIA++c//ylNkufPn3MMxsuXLzF58mQrBpAGrzrIWlFeFUoV6WGz2WwV0E1ujsuXL1slGYwYMQKVlZW4dOkSfx5NsocPHzIIFoNc1ZP9xIkTHJ9TXFzMAcDqxSQpKQmjR4+2yg7V6XTsDhZBt6LI8SpU0kVRLNamOnbDzs4Ora2tLIwrxosQaADAz5UMBmI4FcWySWltwNu3b0deXh4WL16MxMREVFZW4tChQ3B1dZXuv8igiT05ORmDg4PMBosZaSK7S/ILT548gZeXl6T2Lo6Bp0+fAgC7Wuj8CwsLceTIEQ6QPX/+PG9Gd+7cwcOHD+Ho6Ij09HQrBpbKAdFc1roOcUNQg21FsbjdRo0ahXnz5qGhoUGKgQLAQE+0gl9//XXMmjUL586dw+HDh5Gens4CuVStQcvYASxF2ElOgsbHrVu3ONZIzQ4kJyezcbFt2zZm24g9p3CD8ePH8/giF/aFCxck4Edgx8nJCQ4ODuy6HiqBg55DdHQ0u68oCB2QAeSYMWOYZdy3b59VSEBERAS++eYb3uDCwsKsQJyiWGKr3nnnHVRXV1sZyGrA7+npiRcvXrDqNm20xP50dHTA0dERBQUFfO00r9zc3NDS0iKxq/Pnz+e1saioCF9//TWSk5OZTfP19bUKvh9KSJkyUH19fdHa2orhw4cjMTERRqMRc+bMwcGDB5GZmQmDwSAljag7AZKVK1dqZkfW1NTgrbfeQlVVFccMhoeHSy7JBQsWYOLEiVi/fj2Sk5Px3nvvWa3PNP/8/PwQFBSElJQU6fmo44Cp+/n5YcyYMSguLrZyZyqKxbWan5+P8PBw6fMyMjJ4fGVnZ6OiogL+/v5obW3lNXXZsmVYtmwZ1xT87LPP0NXVhaamJoSFhaG7uxu1tbXSODGbzZg+fTo6OjrYKBPPfeLEiQgKCuKxMhTQ0hIv/atAS3QlisCLWC5nZ2eu8jBt2jQsWLAAq1atQl9fH65cucKVLtavX4+mpiaYzWaEhobCxcVFCnp3c3OTmCwCWd7e3gy2vLy8/vtAKzw8nP39AwMDViJq6kWvra2NN1mRnaEuWkBkuXZ1dWlKGYjsBgV5i2g9Pj6eF1g1aEpISMCpU6cQERHBmzoxQoGBgQAgsXBiV2dEnj9/Hl5eXpzCzjdROIYWm8rKStjb20tgTDxWS66AJiQFLQLA/v37h8y2iY+P52uiJgZHZ2dnc0Cu+jzFTnISBw4cYDfD4OAgtm7dim3btuHx48dSAWI6hqxjABwnVl5eLsXz1NbW4sCBA1YxCnFxcUhLS0NCQgKL3YrjRzzW09MTJSUlqKqqQlRUFABLTTUxzurMmTNobW21KuJL41RciNSqzbQ4ZWdns+tUKxMoLy8PlZWVGD58uNU5tra28kap1n579uwZW/SDg4OagbPUKSNt0qRJTOur5S9MJhOWLFmCS5cuoby8HBkZGVYAn87vq6++QlhYGMcwUVFg+r94riLrQMKN4nUS+1lcXIwNGzZI5VTEJA7AUsdQXUhap9NJ95Xam2++iU8//RQnT56EwWDg66VnBoDTsgFIgJM2yDVr1nD8IG1K1BwdHSUjh0RWxa71vM+fP48bN24gKysL8+bNQ2JiIrKysjh5ZMWKFVbMWV1dHcaPH48DBw5I17l//34GX1rrzdKlS/H48WPodDqsXLkSbm5u2LdvH0wmE2JiYjiGbfPmzQxgCIi/++67ePDggabb2GQySZp9Op3OyuhtbW1l9fq4uDgG3c3NzVi6dCliYmKsXJcbN25EdHQ0Dh48iEePHnFcq8FgYLaVWA/62d3djZiYGERGRqKwsJBjba9evYrm5mbs37+f2fu0tDSJjQ0JCcHMmTOxfv16KYyENvrCwkJs376djW9F0QZqYjwR/Z/ijYlRNBqNSExMhLe3t2QI0rmJBlR4eDh0Oh2vhbNmzYLZbIbRaOTQgM7OTphMJgZEYWFhDISCgoI4ZCUyMhKzZs2y2sMUxZL5npOTA6PRiNLSUqSmpsLe3t7Ku+Hg4AA/Pz8O45k1axbq6+sRExODVatW4fDhw5g2bRocHR3R3d2N7u5umM1mREVFwWw2S+un+Dut32lpaewhUdfkHT16NNLS0hjoiczQnwGtvwq21K5CRXnFYru6uiIhIQGVlZWYPn06x2QRm3X48GGsWbMGNTU1yMrKQkxMDLy8vFgslsCWCLTUIIs6vfa3xGh5eXlJ1DktUIcPH0ZOTg5MJhMaGxtx/fp1+Pn5cRzIF198wem2tECodZVoQaIyIGr327BhwzTLihiNRpSXl0uuN7J4Ro0ahbVr1/L508/Ro0dLwdGi9ajX69Ha2oo9e/bg3XffZUC0c+dOvhdz585FbW0tAy5yYz579oy/Q1Fe0eFiPS1FsWho0Xc6OzvzwJ06darkKhJdNElJSax8TPESV65c4ckvfq9W3TfxHqtfKyoqQlBQEAoKCnD06FG0t7dj7969qKmpgbu7O5KTk5GWlsa1GL/55hts375dYrLE2pDDhg1DZmYmDh48iFGjRiEpKUkKTlcUC8NJDAcAiZqmSe3k5IS4uDhpwgOvxEpNJtOQooZ0Lu+88w7X/qJn9dlnn6G9vR2tra284BHYp5/9/f148803rTIgtboI2kQDhDYn0r0Z6v0fffQRj19ieamUBLk/KAhaLRZJ9xWwZEypXRa06SUnJ6OtrY3dPitWrIC9vT0DtHfffVc6R4PBwOOIrkP9nMS+cOFCuLm5aVZroKLG9LeLi4tkaJSWlvI99Pf3R2pqqgRg5s2bh3HjxnFtuoMHD2LMmDFSuAAAlnQQXaI6nc7KKBSrPIhjeNSoUSzSKR4vgtGdO3dajWWx5+bmSkH2YjarFjsqdpFVjIqKYmakra2NGVlyE+v1eixbtozLtiiKZTMWE4VExvHevXu4dOkSkpKSeGMnZobmV0ZGBhYvXozY2Fjs3LkTFRUVWLduHRwcHKwkOlxcXNDe3o7c3FxOWhLZXHt7e1y6dImBkGhAi/pG9vb2vJ/cv38fDQ0NCAgI4PU/JCQEZrPZyjgRS2llZWWhpqYGaWlpuHnzJhusAwMDVkkS6j5r1iyOC968eTPKysr4s+3t7SV35JUrVzRd0o2NjVYaX+LYpkQV0fWZmpqKnJwcZGRk8Jw3Go1Wa7fajerg4IDKykro9XpkZmbCzs4OiYmJcHJykgL+6bzT0tKQlJSE5ORkpKenIyUlBeXl5Ry/WFFRgaysLBiNRisG3tvbm9eHxMREBqLp6enIyMhAQEAAn/vcuXOlCgdjx479y0Drr7Ba1LXitOzs7ODt7Y2UlBRMnToVra2t6Ozs5PqGb731FjZs2IC6ujqkpaUhIiIC7u7uLEQqujPFAHgPDw8JYPn4+HAnsPVfB1qEkNXZWopisdIp7RkAioqK4O3tjdraWmY6bt68KSmGq0UKy8rKrLJtxDRfRbHo6NCmrWYkqHd1dUkMQFlZmRTMK1Kdv/32G1sPZOmFh4fDw8ODgyjz8vJw//59eHt7Y+/evZgzZ46V2OXOnTvZDQTAiuZtamqSNhYti0W05Olz6HfRmiwvL8e9e/es4leI2i4uLkZYWJhUMf7evXv4+OOPMTg4yM+T3B7Tpk1DSEgIWlpauHh1SkoKTpw4geTkZOmZlZeXs9VcUFCAyZMnS0DHzc0NDQ0NWLduHXJzc4esFVlcXIzXX3+dg3Zzc3OlDY/uwzfffGMFLESJkWfPnmkyoEajUbOsiaJYNpeffvoJhYWFmDVrFgdEFxcXa8a6DKW/pO7kehEzcKmrxQQpeJQY06lTp0psRGJiIkpKSmBvb4/Lly/zWFCzLvHx8Zg7dy78/f0l1wcZMc3NzZrzRMwope7n5ycxpyKLDABpaWkYOXIk+vv7NV3aFF9H53ro0CG4u7sjIyNDYib+KPtKXe6H7llKSgpLB1y9ehV5eXlWkhFidjOxFhMnTrRyTSuKIhVUVxQLGDKbzairq+MiturxqigWlo8YBLoHP/30E0aPHs3ga8uWLcjOzrYyAMRx7OLiYlU4XVEsgdDiZkz3UswcIwNtypQpDIy15DfEHhQUBL1eLwkoK4oi1RGlcXHnzh0UFRUxYNu5cyfmzZuHXbt2YcyYMdi9ezeSkpL4O/+oFuPp06et1nTqYkbho0ePoCgWZo1eT0xMxNixYyUj2NPTUwoZ0OpRUVHsQRFZbLUrtbCwEMOHD+d76OPjg5cvX2Lz5s1ob29HaWkpysrKEB8fzwBSZFLF9be6uhr379/XjIUVe19fn8S4KYoF6FO2Ms2NuLg4K6ZKy73o5uaG4cOHcxKBp6cnRo0axYDJzs4OxcXFmDNnDpYtW4Zt27ahpKQEXV1dmDZtGurq6mAymfgek2FLTJw6IzMtLQ0VFRWS8UmAODQ0lI0Bqg7yfwu0/ozZsre358xEe3t7BAUFwWw2o6GhgQHW7t270dfXx3pxeXl50Ol08Pb2ZtkHtatQnWFIbJYItHx9feHr68tg679e61AdWBgdHY3bt2/z32Icx5dffskbZ0BAAL777js0NTXh5MmT/JDUbrkZM2agvr5eQtUbNmzgzB7qx48fx08//cRq3LToEbCgQVtZWSm5QshKrays5EXwwIEDkluTsjgU5ZU+DpXsoQVSrQ0zc+ZMjvWiBXHfvn1WFpgIoijNecGCBSgpKeFCoeLxpJMlxkppLRhLlizhRTs/Px+JiYlob2+3ynKjzwgNDQUA3qhWrFjB95yOEQMaxU2S/q8VjE/WDmm8NDY2Dqn4ru70bMjVVFZWhrCwMPT29iI7OxvTp08HYKlhRnT/7du38dFHH1kBCQKxbW1tOHv2rLT4EQMiuhTU40trUaPrmDZtGubMmaMZUEzgWgRrZI2uW7cOn332GTo7O+Ht7Y2CggIAYEkH8bt8fX2xceNGfqZPnjxBdHQ0rl+/DpPJJLEzSUlJOHHiBF68eCEVrib2S4sBFrsYY6ROpR83bpwkGUEbXGZmpmZ22I4dO5CcnIzHjx/DxcUFX331FYKCgtDR0SEVNRcBpziuFcUCCHx9fTnjl+YmMR6UaUuW/1DGljreSKy+QPdY/Hvx4sXQ6XSIiIgYElhTAdmBgQEua6QoCmvILV26lMeAejMVr5OU2qOjowEAbm5uOHToEG7evImqqirpmdG8cHV1tTIojEaj1Rrz5ptvSlIQiiLrL9F5FBUVYcWKFSgvL+cYWnt7e2zatImZ1d7eXjg4OEjrUnl5uQR8DAYD69WJ88bX1xerV6+WhIQJaLa1taG4uNjK0KbgcHH+iONMZJLWrl0rGeHjxo1DZGQk0tPTJe1FMlDp55QpU1BWVobZs2ejvb0dcXFxuHbtGj9PcQ8TWUsKPhfvBbGNVPOvrKwMra2t/JzE/U897v38/P6QaXN2dub30zoeGhrKz4rWHfU5k4FBca6dnZ3YvHkzdu/ejU2bNqGtrQ1NTU3MTqanp8PBwYHHUVBQEGJiYqyIAmdnZ0RGRsLX1xcZGRnIzc3lmrs0D3x8fODm5obo6GhkZWUhJCSE3W9DgS2tkjxiyRs14BKZLdLd8vb2xrhx49DU1IRly5ahp6cH27dvR1dXF+bOnYv8/Hzo9Xr4+fnx94nnJYqSDgWyiMXy9fWFn58f/Pz8uF7u31pUmvqtW7d4wIvHAJBqBZaXl1tlnRCNvnr1al6Y7OzsEBwcjIKCAra61RZwZGQk1q5di8DAQF60XF1dWU9G7KKgKZ2fyJwkJycDAA80ElilRZ1+v3LlCs6dO8dBx/Q6ZWrR39evX+fBTp9JCxNRsDU1NfDx8YGjoyOCgoKs2AW6Dso2UhSLS+HZs2dYtGgRHB0dpSQCMQ5Gr9dLC5i6tIe4qYsLMLk6xGBUkdGgkhH0t6hSrxV0S+dMKedGo5EV9en/lM4sLhSnT5+GyWTSjK0AwBlUJpNJoth1Oh18fX0RFxeHb775hsesliRHRkaGZKlduXJFqggw1OKnKK9i6EjKg3pERAS7DiiY3mAwYNq0aaisrGRwJKpeEwNJC6loYIjMDoHaKVOmwGAwsJjo6NGj0d3dLc3Rzs5O6XlUVlby3+K437p1K7KysqxqUoo9NzeXN33RpaWeU+L6UF5eDm9vb5w7dw4NDQ2a7BWBnEmTJg1ZVunq1atSuRza4G7cuIH33nsP165dkzR9FEWuTaruWgkZ4nV+/fXXUBQ5M5rcRyR9sWjRIi4GXVlZiZaWFmZ1tm/fjpaWFtYjUosmi+OetJZ0Oh1OnjwpgXpHR0cJpI0ZM0YzoUINUoYNG4bExETs27fPKntZnQGsKBYDgIwAUS9LUSwGjKenJ1JTU60qTqi/V2QRFUWR3FZiaSBfX19m6rQ8IorySjooJSVFs5IAdXVGMJU1mzt3LlJSUlBQUMCGBpVvUhQLCKFSPlTGqKWlBW+88Qa2bNnCYIxKxND3TZgwgQPIyQjfunUrA7HZs2dL6yqtZ2TIaiVHRUREoLa2FiNGjGDwJN7rqqoqvj66hwRUExMTMXHiRBQUFKCwsBCNjY0IDQ3FiBEjeP3KyMhAU1MTDh06hN7eXvz444/Izc3lz1A/R71ej5CQECQkJECn0yE2NpYNDtpD1Gz65MmT2e2qKBbwS2CSvF+i5tRfyT4UAddQ7kQRaNnb2zO7unDhQmzduhVbt25FY2MjsrKyEBUVBU9PT/5s0scSdbDUgEsdAC+CLAJa/v7+8PPzY2LmL+Gnv3QUgPb2dri5uVkVzD19+rRUvkZRLHEhgBywnpiYiMuXL+O1117jOBIHBwds3LiRFzqxu7m5DWld9vX1sfuQYhbExUzsx44dQ0dHBy8K4nEvX77Ezz//jPLycnz33XdDujUSExOZ2SLrzcnJCSEhIXjrrbesjr9x4wZ/j1ZKOv2elZUFNzc3tLa28gYUHx8Pe3t7TsGljLT6+nqe0DQ5vb29JQFYcVLPnTuXXXeApR4gFXAFILEM1EWrS81axMbGWqUdk5hmT08PYmNjMX78eMnqA4B79+6hvb0dZrOZSyepJ7kIFtesWYM33ngD8+bNG3JRfv78OU6cOMGgdtu2bbh7966kLSX6ztW1BYfqImgGwN9PCy1JE5CQIB2blJSERYsWAQA2btwIAHj69Cm2bNkiSS+I/cGDB8w++Pv7w9fXV4pF8/T0RFRUFOzs7HjMADJ4DAsLg8FgwJEjR15NaOE7ysvLNdW57e3teYHUmjcxMTHS+0TwNnPmTGljIa0xURBYBEmff/75kHNTUV6BIL1eL1WQGOo9jY2NmDhxIlvSXl5eKCwsRFZWlibTRmyk+Hmi+0mM9RFBT3JyMtzd3XH//n2eF3PnzuX4L7XLjDKZ6W+tLGjaCDMzM/+QbQwICMDx48clVnrnzp3o6+uTDCStrtfr+TqMRiPy8/OtxoDRaJQMvJ07d0qq7oqiSAyp1til300mEzw8PDQLeh84cICvc8qUKVLWZ0NDAyZMmID6+nrcuHED+/fvh06n4zXFx8cH7u7uQ9ZKpGdK8zA4OFgzDlJMStDpdBgcHMT3338PDw8P+Pj4oLa2lueUlnuOxmRnZyfCwsJ4jUhISEBERATMZrP0TIqLi7FixQpmtsR4vfLycowbNw61tbVYsWKFZBxQ2S1FsRAOMTExbFCL8Y00LnU6HTw8PODo6Aij0YhJkyaxG6+pqQktLS345ptvMH36dMyePRt5eXlstNF1iqCS/hcSEoLMzEwGS2azmQtJE8Pt7u4uJYW5uLhIMV60XvwZ0BoKbBEgcnFxsXIlkvvQ0dERTk5OMJvN2LRpE5YtW4ZZs2YhKysLwcHBcHZ2Zveio6MjgzdRvkFLiPSPgBaxWQS0/nZGKyoqiuMc1NR0fHw8dDqdVapuVFQUzp49i8jISOnzPvvsM+Tl5SE6OppjBnQ6HadkL1q0CImJiRKlLBZKnjt3rvR5ZDnFxMSgq6sL9fX1+OCDDzjw2tnZGcePHwcAyfVJlt0//vEPacMjeQCxh4aGMuNFNZ/E/9OEF4tOK4oFWB08eBBHjhyBTqfjMj4XLlxgnTB1jA/wqmyROGlFzSkqR6Kmo0lQle4PBfWKStbUqRC4yKbMmTNHU/9GUf6c/Zk5cybfUwC4fv06Ll++LAFTWkhI1oISFNTnJlrdamBLLMTjx4/x+uuvo6KiQrpPf7RpUyeXb1VVFQICAthqVhQLm6PlosrIyEBKSgrWrFnDDBcA3LhxQ2K8aGyIMUUU4/fll1/iww8/xODgIDNOoptrKHmIodLB6Tr/6HqnTJnCAeuenp4SO0pMgPrz6dzFpI5vv/2W2YKYmBj+zpUrV0oxiIsWLUJmZiZu3rwpibHSBtbe3s4Mg6JYa5fRvBEz5wjkqF106vusKJYNuLW1VQJ/ANDc3IywsDApA9HV1ZUBEmXiDg4OYunSpVYbfkJCAvLy8jgQnO5jfX09ysrKeKMSY67oOi9fvoyoqCiWFyC3+9WrV3m8kuGqjqOi3t7ermkYLlmyhNfK/Px8Xp/VtR/7+/uxfPlyKxFqWvsSExMZkLa3t0siqIqisK6W+FyoU8o7PW8yrDdu3Aiz2Yz58+cDAB48eMAsEWCJAyZDPiQkBE5OTpg+fbqmvMjEiRM1x7maYa+pqYFer8fq1atx+PBhLF68GAcOHMCMGTNQVVWF+vp6ZmuSkpKswHpNTY0ELNVg7v3335fAl/i/+Ph4nDhxAq6urvxMCLB0dnYiLS2Nn+FQgrQGgwFNTU2orq7GiBEj4ODggJiYGISGhsLf359BdEBAAF+Hp6cnxo4dy4AvPT0dU6ZMwfDhw5GVlYW5c+da1XekTmNRNKZyc3P5e8rLy3nei3GH9N3iviC65cQYKPGnWsBUDbhEZkuM2XJwcICHhwdmzJiBbdu2obi4GAEBAVKdRGK+yBUpKr6LAEvUxhJ/V8dlEcii7uPjw67qP8VPf+koAAkJCZoDW0T5ivJKB0hU4RUH5549e1BaWsqfZW9vL30uWY+HDh2CoigsdvnJJ59Yff+VK1d4ADQ1NWHr1q24cuUKSkpKuJwGDSh1yQQAjMhpUhQXF7Mw3fPnz/k4OiY9PZ3dLVu3bmULTcwsIo2fsrIylJWVWS0I27ZtY5cnZT+R0CgdRz/FxZHUpBXlVVo3TQrx82mC1NbWSkH748aNY/cfJQxcuHCB5SDE2n7Eoqjvt1Z8TVlZGS8wIhjWCoTPz89He3s7swxFRUV466230NzczLFg6oB00WUp3kuRvfqf//kf6T1iWaR169ZJTJxer8eZM2eYmaBGtRjXr18vpb+LbAC5Dqn7+flJgFetNQRAqgXX3NyMgwcP4sKFC+z6FIUgRZasqqqKxRGJGVY/D9G9PFRfvHgxVq9ejRUrVmDRokUS00LgYyjBS6PROGTJH/F7yUWsKBYABsBKuf7YsWPo6urCd999J70uKomLgFX9PQCkuBmtOopiBqb4HcTWPH36FF988YXkpvn2229x6NAhAOBYHAInH3/8sdXaRG3nzp148803ERsbizt37kjfJ2Ze0vmlpKQAsNSOfPnyJTNA9fX1MBqN+P333wGAWeehngf9vnnzZk0DwGg0wmQy4aOPPpLWjGvXrlnVxTQYDFyaREty4p133mFmSyxDRn1wcFBSBidGhd4zf/58q4QmGisfffSRVE6IGH1XV1eJ3Tl27Jj0jMkzQXsK1akT57eWnFBtbS1SUlI0kyMePHggSRa9/fbbVoylTqdjYEEG6507d7B3716kpqZKawaFPvT19TGQVWcPGo1GxMXFoaamhgHDyJEjkZiYiNTUVCQmJmLEiBG8n5hMJgkUOzs7Iyoqyqr+6R8VmKd7TKCoqqqKDXyxx8fHIzo6msMEFixYoCkWS4Z9UlISqqurMWPGDMmroi5lo2aStLp4rDqOS2S3hg0bBk9PT+Tl5WH06NE89sQSPiK4Ej9bZLK0sgqJrRLBVUBAAAIDAxEUFISgoCAEBwcjICAArq6u+CvtLwMtUYRt3rx5HK9Em4/IOogCjFeuXMG//vUvAK9ihGjzWrp0KQBobsqkVaO1cEZFRXEcRFxcnBQYT8e//vrr2LFjB95//304ODhIVD0pv5OVKmqrRERESFb1V199hcHBQdTU1LClPxSdvWXLFgCvdLnouJaWFmmhampq4glE1o14/7SqvVNXgx36vrKyMuj1esnKXb9+PT744AN+T0VFheYi7uPjI6kki4DCYDCgpaVFkuPgwTPEOba1tWHatGmYNm2aNPHE4Php06YBsNQO/LM6YKtXr8Yvv/yCqVOnSucmjg812NJSdReZk9mzZw9Zykn991AqzrGxsZpxRqQjlpCQAG9vb5w5cwZ79+5FRUUF8vLyrL6DspkoLu7OnTvo7e3lzYR+AmClctEloj5fqj9Hr9EGIrrJ1F39Hur29va4fv06/6+ystJq06Cg54ULF7Kbg4wPsSwXjUNxI7xx4wZu3brFGU30+vvvv48XL15wTJPYS0pKUF1djZEjRwIAYmJipGB+nU5nxWyIdSgBsEGozooTx5TanWY0GjF16lQu60Ovi6EPtMb985//RG9vr1SLdffu3fws8/Ly0N/fD8AiliqyqOre2dkJnU6Hjo4OKQaL2E8xG05kE8+fP49du3ZxLGpQUBBvmH19fdDr9SgtLcWoUaMYHIhrsZubG6ZOnYrr168jNTUVN2/eZIaW2K61a9fi9u3bzM719/ezkawoFkBIbmUAVrUQxXFGv2dkZKC7u5tdp4WFhezGH6pQdU1NDerr61FXVyeVzlIUy/orZlDHx8dLRjY9DzLqJ02ahPv370syIcToDQwMYPHixZg/f77EBufn5zMQovlJoLegoEAzDMbHxwd5eXkckrBp06Y/FN6m7u3tDQcHB4waNcrqfk6ZMsXK26DT6diIy8rKgr+/P4Oouro66PV63n/0ej0mT54Ms9mMwsJCLhVE8zo8PJzDTrKysuDl5QV3d3fNTHoRGIlFpLVisLSOUXe1G9HLywt6vZ7DeURXIX2eKNsgBrqLrJU69ooYKwJWwcHBCA4OxvDhwxESEoKQkBCEhoYiKCgInp6e+CvN7n8PSFuzNVuzNVuzNVuzNVv7Lzf7/9cnYGu2Zmu2Zmu2Zmu29v9rswEtW7M1W7M1W7M1W7O1v6nZgJat2Zqt2Zqt2Zqt2drf1GxAy9ZszdZszdZszdZs7W9qNqBla7Zma7Zma7Zma7b2NzUb0LI1W7M1W7M1W7M1W/ubmg1o2Zqt2Zqt2Zqt2Zqt/U3NBrRszdZszdZszdZszdb+pmYDWrZma7Zma7Zma7Zma39T+19n2z6edS/gKgAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<Figure size 640x480 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "model.eval()\n",
     "noise = torch.randn((1, 1, 64, 64))\n",
@@ -848,7 +683,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": null,
    "id": "bab2d719",
    "metadata": {},
    "outputs": [],
@@ -856,14 +691,6 @@
     "if directory is None:\n",
     "    shutil.rmtree(root_dir)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2f81decf-e530-4043-a758-4a24c44b204f",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -871,7 +698,7 @@
    "formats": "ipynb,py:percent"
   },
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -885,7 +712,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.13"
+   "version": "3.8.12"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py
index 9375b1be..996ad4de 100644
--- a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py
+++ b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py
@@ -8,7 +8,7 @@
 #       format_version: '1.3'
 #       jupytext_version: 1.14.1
 #   kernelspec:
-#     display_name: Python 3 (ipykernel)
+#     display_name: Python 3
 #     language: python
 #     name: python3
 # ---
@@ -86,7 +86,7 @@
 # ## Set deterministic training for reproducibility
 
 # %% jupyter={"outputs_hidden": false}
-set_determinism(0)
+set_determinism(42)
 
 # %% [markdown]
 # ## Setup MedNIST Dataset and training and validation dataloaders
@@ -124,7 +124,7 @@
     ]
 )
 train_ds = CacheDataset(data=train_datalist, transform=train_transforms)
-train_loader = DataLoader(train_ds, batch_size=128, shuffle=True, num_workers=4)
+train_loader = DataLoader(train_ds, batch_size=128, shuffle=True, num_workers=4, persistent_workers=True)
 
 # %% jupyter={"outputs_hidden": false}
 val_data = MedNISTDataset(root_dir=root_dir, section="validation", download=True, progress=False, seed=0)
@@ -137,7 +137,7 @@
     ]
 )
 val_ds = CacheDataset(data=val_datalist, transform=val_transforms)
-val_loader = DataLoader(val_ds, batch_size=128, shuffle=False, num_workers=4)
+val_loader = DataLoader(val_ds, batch_size=128, shuffle=False, num_workers=4, persistent_workers=True)
 
 # %% [markdown]
 # ### Visualisation of the training images
@@ -167,10 +167,10 @@
     spatial_dims=2,
     in_channels=1,
     out_channels=1,
-    block_out_channels=(64, 128, 128),
-    attention_levels=(False, False, True),
+    num_channels=(64, 128, 128),
+    attention_levels=(False, True, True),
     num_res_blocks=1,
-    num_heads=1,
+    num_head_channels=64,
 )
 model.to(device)
 
@@ -180,14 +180,14 @@
 
 optimizer = torch.optim.Adam(params=model.parameters(), lr=2.5e-5)
 
-inferer = DiffusionInferer()
+inferer = DiffusionInferer(scheduler)
 # %% [markdown]
 # ### Model training
-# Here, we are training our model for 50 epochs (training time: ~20 minutes).
+# Here, we are training our model for 100 epochs (training time: ~40 minutes).
 
 # %% jupyter={"outputs_hidden": false}
-n_epochs = 50
-val_interval = 5
+n_epochs = 100
+val_interval = 10
 epoch_loss_list = []
 val_epoch_loss_list = []
 
@@ -205,7 +205,7 @@
         noise = torch.randn_like(images).to(device)
 
         # Get model prediction
-        noise_pred = inferer(inputs=images, diffusion_model=model, scheduler=scheduler, noise=noise)
+        noise_pred = inferer(inputs=images, diffusion_model=model, noise=noise)
 
         loss = F.mse_loss(noise_pred.float(), noise.float())
 
@@ -229,7 +229,7 @@
             noise = torch.randn_like(images).to(device)
             with torch.no_grad():
                 # Get model prediction
-                noise_pred = inferer(inputs=images, diffusion_model=model, scheduler=scheduler, noise=noise)
+                noise_pred = inferer(inputs=images, diffusion_model=model, noise=noise)
                 val_loss = F.l1_loss(noise_pred.float(), noise.float())
 
             val_epoch_loss += val_loss.item()
@@ -303,5 +303,3 @@
 # %%
 if directory is None:
     shutil.rmtree(root_dir)
-
-# %%

From 9ec821ba174dce456f86797fed058b73b58a6197 Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Fri, 25 Nov 2022 20:26:21 +0000
Subject: [PATCH 19/28] [WIP] Rerun jupyter notebooks (#53)

---
 .../networks/nets/diffusion_model_unet.py     | 178 ++++-------
 .../generative/2d_ddpm/2d_ddpm_tutorial.ipynb | 302 ++++++++++++++----
 .../generative/2d_ddpm/2d_ddpm_tutorial.py    |  18 +-
 3 files changed, 304 insertions(+), 194 deletions(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index ef262bbc..1f8d36d8 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -34,13 +34,25 @@
 
 import torch
 import torch.nn.functional as F
-from monai.networks.blocks import Convolution
+from monai.networks.blocks import Convolution, SABlock
 from monai.networks.layers.factories import Pool
+from monai.utils import optional_import
 from torch import nn
 
+Rearrange, _ = optional_import("einops.layers.torch", name="Rearrange")
+
 __all__ = ["DiffusionModelUNet"]
 
 
+def zero_module(module: nn.Module) -> nn.Module:
+    """
+    Zero out the parameters of a module and return it.
+    """
+    for p in module.parameters():
+        p.detach().zero_()
+    return module
+
+
 class GEGLU(nn.Module):
     """
     A variant of the gated linear unit activation function from https://arxiv.org/abs/2002.05202.
@@ -112,38 +124,11 @@ def __init__(
         self.to_k = nn.Linear(cross_attention_dim, inner_dim, bias=False)
         self.to_v = nn.Linear(cross_attention_dim, inner_dim, bias=False)
 
-        self.to_out = nn.Sequential(nn.Linear(inner_dim, query_dim), nn.Dropout(dropout))
-
-    def reshape_heads_to_batch_dim(self, x: torch.Tensor) -> torch.Tensor:
-        batch_size, seq_len, dim = x.shape
-        head_size = self.heads
-        x = x.reshape(batch_size, seq_len, head_size, dim // head_size)
-        x = x.permute(0, 2, 1, 3).reshape(batch_size * head_size, seq_len, dim // head_size)
-        return x
-
-    def reshape_batch_dim_to_heads(self, x: torch.Tensor) -> torch.Tensor:
-        batch_size, seq_len, dim = x.shape
-        head_size = self.heads
-        x = x.reshape(batch_size // head_size, head_size, seq_len, dim)
-        x = x.permute(0, 2, 1, 3).reshape(batch_size // head_size, seq_len, dim * head_size)
-        return x
-
-    def _attention(self, query: torch.Tensor, key: torch.Tensor, value: torch.Tensor) -> torch.Tensor:
-        attention_scores = torch.baddbmm(
-            torch.empty(query.shape[0], query.shape[1], key.shape[1], dtype=query.dtype, device=query.device),
-            query,
-            key.transpose(-1, -2),
-            beta=0,
-            alpha=self.scale,
-        )
-        attention_probs = attention_scores.softmax(dim=-1)
-
-        # compute attention output
-        hidden_states = torch.bmm(attention_probs, value)
+        self.input_rearrange = Rearrange("b n (h d) -> (b h) n d", h=num_attention_heads)
+        self.out_rearrange = Rearrange("(b h) n d -> b n (h d)", h=num_attention_heads)
 
-        # reshape hidden_states
-        hidden_states = self.reshape_batch_dim_to_heads(hidden_states)
-        return hidden_states
+        self.out_proj = nn.Linear(inner_dim, query_dim)
+        self.drop_output = nn.Dropout(dropout)
 
     def forward(self, x: torch.Tensor, context: Optional[torch.Tensor] = None) -> torch.Tensor:
         query = self.to_q(x)
@@ -151,13 +136,18 @@ def forward(self, x: torch.Tensor, context: Optional[torch.Tensor] = None) -> to
         key = self.to_k(context)
         value = self.to_v(context)
 
-        query = self.reshape_heads_to_batch_dim(query)
-        key = self.reshape_heads_to_batch_dim(key)
-        value = self.reshape_heads_to_batch_dim(value)
+        query = self.input_rearrange(query)
+        key = self.input_rearrange(key)
+        value = self.input_rearrange(value)
 
-        hidden_states = self._attention(query, key, value)
+        sim = torch.einsum("b i d, b j d -> b i j", query, key) * self.scale
+        attn = sim.softmax(dim=-1)
+        out = torch.einsum("b i j, b j d -> b i d", attn, value)
+        out = self.out_rearrange(out)
 
-        return self.to_out(hidden_states)
+        out = self.out_proj(out)
+        out = self.drop_output(out)
+        return out
 
 
 class BasicTransformerBlock(nn.Module):
@@ -270,14 +260,16 @@ def __init__(
             ]
         )
 
-        self.proj_out = Convolution(
-            spatial_dims=spatial_dims,
-            in_channels=inner_dim,
-            out_channels=in_channels,
-            strides=1,
-            kernel_size=1,
-            padding=0,
-            conv_only=True,
+        self.proj_out = zero_module(
+            Convolution(
+                spatial_dims=spatial_dims,
+                in_channels=inner_dim,
+                out_channels=in_channels,
+                strides=1,
+                kernel_size=1,
+                padding=0,
+                conv_only=True,
+            )
         )
 
     def forward(self, x: torch.Tensor, context: Optional[torch.Tensor] = None) -> torch.Tensor:
@@ -337,23 +329,9 @@ def __init__(
         self.num_channels = num_channels
 
         self.num_heads = num_channels // num_head_channels if num_head_channels is not None else 1
-        self.num_head_size = num_head_channels
-
         self.norm = nn.GroupNorm(num_groups=norm_num_groups, num_channels=num_channels, eps=norm_eps, affine=True)
 
-        # define q,k,v as linear layers
-        self.query = nn.Linear(num_channels, num_channels)
-        self.key = nn.Linear(num_channels, num_channels)
-        self.value = nn.Linear(num_channels, num_channels)
-
-        self.proj_attn = nn.Linear(num_channels, num_channels, 1)
-
-    def transpose_for_scores(self, projection: torch.Tensor) -> torch.Tensor:
-        new_projection_shape = projection.size()[:-1] + (self.num_heads, -1)
-        # move heads to 2nd position (B, T, H * D) -> (B, T, H, D) -> (B, H, T, D)
-        new_projection = projection.view(new_projection_shape).permute(0, 2, 1, 3)
-
-        return new_projection
+        self.attention = SABlock(hidden_size=num_channels, num_heads=self.num_heads, qkv_bias=True)
 
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         residual = x
@@ -371,49 +349,7 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
         if self.spatial_dims == 3:
             x = x.view(batch, channel, height * width * depth).transpose(1, 2)
 
-        # proj to q, k, v
-        query_proj = self.query(x)
-        key_proj = self.key(x)
-        value_proj = self.value(x)
-
-        scale = 1 / math.sqrt(self.num_channels / self.num_heads)
-
-        # get scores
-        if self.num_heads > 1:
-            query_states = self.transpose_for_scores(query_proj)
-            key_states = self.transpose_for_scores(key_proj)
-            value_states = self.transpose_for_scores(value_proj)
-            attention_scores = torch.matmul(query_states, key_states.transpose(-1, -2)) * scale
-        else:
-            query_states, key_states, value_states = query_proj, key_proj, value_proj
-
-            attention_scores = torch.baddbmm(
-                torch.empty(
-                    query_states.shape[0],
-                    query_states.shape[1],
-                    key_states.shape[1],
-                    dtype=query_states.dtype,
-                    device=query_states.device,
-                ),
-                query_states,
-                key_states.transpose(-1, -2),
-                beta=0,
-                alpha=scale,
-            )
-
-        attention_probs = torch.softmax(attention_scores.float(), dim=-1)
-
-        # compute attention output
-        if self.num_heads > 1:
-            x = torch.matmul(attention_probs, value_states)
-            x = x.permute(0, 2, 1, 3).contiguous()
-            new_x_shape = x.size()[:-2] + (self.num_channels,)
-            x = x.view(new_x_shape)
-        else:
-            x = torch.bmm(attention_probs, value_states)
-
-        # compute next hidden states
-        x = self.proj_attn(x)
+        x = self.attention(x)
 
         if self.spatial_dims == 2:
             x = x.transpose(-1, -2).reshape(batch, channel, height, width)
@@ -594,14 +530,16 @@ def __init__(
         )
 
         self.norm2 = nn.GroupNorm(num_groups=norm_num_groups, num_channels=self.out_channels, eps=norm_eps, affine=True)
-        self.conv2 = Convolution(
-            spatial_dims=spatial_dims,
-            in_channels=self.out_channels,
-            out_channels=self.out_channels,
-            strides=1,
-            kernel_size=3,
-            padding=1,
-            conv_only=True,
+        self.conv2 = zero_module(
+            Convolution(
+                spatial_dims=spatial_dims,
+                in_channels=self.out_channels,
+                out_channels=self.out_channels,
+                strides=1,
+                kernel_size=3,
+                padding=1,
+                conv_only=True,
+            )
         )
 
         if self.out_channels == in_channels:
@@ -1582,14 +1520,16 @@ def __init__(
         self.out = nn.Sequential(
             nn.GroupNorm(num_groups=norm_num_groups, num_channels=num_channels[0], eps=norm_eps, affine=True),
             nn.SiLU(),
-            Convolution(
-                spatial_dims=spatial_dims,
-                in_channels=num_channels[0],
-                out_channels=out_channels,
-                strides=1,
-                kernel_size=3,
-                padding=1,
-                conv_only=True,
+            zero_module(
+                Convolution(
+                    spatial_dims=spatial_dims,
+                    in_channels=num_channels[0],
+                    out_channels=out_channels,
+                    strides=1,
+                    kernel_size=3,
+                    padding=1,
+                    conv_only=True,
+                )
             ),
         )
 
diff --git a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb
index 45dbed68..bdba4d85 100644
--- a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb
+++ b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb
@@ -145,7 +145,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/tmp/tmpke4lye0u\n"
+      "/tmp/tmp_ik9ng61\n"
      ]
     }
    ],
@@ -174,7 +174,7 @@
    },
    "outputs": [],
    "source": [
-    "set_determinism(42)"
+    "set_determinism(0)"
    ]
   },
   {
@@ -202,9 +202,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-24 20:31:18,725 - INFO - Downloaded: /tmp/tmpke4lye0u/MedNIST.tar.gz\n",
-      "2022-11-24 20:31:18,795 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
-      "2022-11-24 20:31:18,795 - INFO - Writing into directory: /tmp/tmpke4lye0u.\n"
+      "2022-11-25 18:48:31,660 - INFO - Downloaded: /tmp/tmp_ik9ng61/MedNIST.tar.gz\n",
+      "2022-11-25 18:48:31,731 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
+      "2022-11-25 18:48:31,732 - INFO - Writing into directory: /tmp/tmp_ik9ng61.\n"
      ]
     }
    ],
@@ -240,7 +240,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1773.73it/s]\n"
+      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1803.07it/s]\n"
      ]
     }
    ],
@@ -279,16 +279,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-24 20:31:41,838 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
-      "2022-11-24 20:31:41,838 - INFO - File exists: /tmp/tmpke4lye0u/MedNIST.tar.gz, skipped downloading.\n",
-      "2022-11-24 20:31:41,839 - INFO - Non-empty folder exists in /tmp/tmpke4lye0u/MedNIST, skipped extracting.\n"
+      "2022-11-25 18:48:54,399 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
+      "2022-11-25 18:48:54,400 - INFO - File exists: /tmp/tmp_ik9ng61/MedNIST.tar.gz, skipped downloading.\n",
+      "2022-11-25 18:48:54,400 - INFO - Non-empty folder exists in /tmp/tmp_ik9ng61/MedNIST, skipped extracting.\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1005/1005 [00:00<00:00, 1792.71it/s]\n"
+      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1005/1005 [00:00<00:00, 1848.85it/s]\n"
      ]
     }
    ],
@@ -333,7 +333,7 @@
     },
     {
      "data": {
-      "image/png": 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       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ]
@@ -380,6 +380,16 @@
    "source": [
     "device = torch.device(\"cuda\")\n",
     "\n",
+    "# model = DiffusionModelUNet(\n",
+    "#     spatial_dims=2,\n",
+    "#     in_channels=1,\n",
+    "#     out_channels=1,\n",
+    "#     model_channels=64,\n",
+    "#     attention_resolutions=[2, 4],\n",
+    "#     num_res_blocks=1,\n",
+    "#     channel_mult=[1, 2, 2],\n",
+    "#     num_heads=1,\n",
+    "# )\n",
     "model = DiffusionModelUNet(\n",
     "    spatial_dims=2,\n",
     "    in_channels=1,\n",
@@ -387,7 +397,7 @@
     "    num_channels=(64, 128, 128),\n",
     "    attention_levels=(False, True, True),\n",
     "    num_res_blocks=1,\n",
-    "    num_head_channels=64,\n",
+    "    num_head_channels=128,\n",
     ")\n",
     "model.to(device)\n",
     "\n",
@@ -424,22 +434,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 0: 100%|████████████| 63/63 [00:40<00:00,  1.55it/s, loss=0.295]\n",
-      "Epoch 1: 100%|████████████| 63/63 [00:41<00:00,  1.53it/s, loss=0.073]\n",
-      "Epoch 2: 100%|███████████| 63/63 [00:41<00:00,  1.53it/s, loss=0.0544]\n",
-      "Epoch 3: 100%|███████████| 63/63 [00:41<00:00,  1.53it/s, loss=0.0427]\n",
-      "Epoch 4: 100%|███████████| 63/63 [00:41<00:00,  1.52it/s, loss=0.0358]\n",
-      "Epoch 5: 100%|███████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0325]\n",
-      "Epoch 6: 100%|███████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0285]\n",
-      "Epoch 7: 100%|███████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0273]\n",
-      "Epoch 8: 100%|███████████| 63/63 [00:41<00:00,  1.50it/s, loss=0.0246]\n",
-      "Epoch 9: 100%|███████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0242]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.40it/s]\n"
+      "Epoch 0: 100%|████████████| 63/63 [00:37<00:00,  1.69it/s, loss=0.863]\n",
+      "Epoch 1: 100%|████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.568]\n",
+      "Epoch 2: 100%|████████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.343]\n",
+      "Epoch 3: 100%|████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.202]\n",
+      "Epoch 4: 100%|████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.118]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 72.06it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -451,22 +456,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 10: 100%|██████████| 63/63 [00:41<00:00,  1.53it/s, loss=0.0237]\n",
-      "Epoch 11: 100%|██████████| 63/63 [00:42<00:00,  1.50it/s, loss=0.0201]\n",
-      "Epoch 12: 100%|██████████| 63/63 [00:42<00:00,  1.48it/s, loss=0.0226]\n",
-      "Epoch 13: 100%|██████████| 63/63 [00:42<00:00,  1.48it/s, loss=0.0206]\n",
-      "Epoch 14: 100%|██████████| 63/63 [00:42<00:00,  1.49it/s, loss=0.0197]\n",
-      "Epoch 15: 100%|██████████| 63/63 [00:42<00:00,  1.50it/s, loss=0.0195]\n",
-      "Epoch 16: 100%|██████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0185]\n",
-      "Epoch 17: 100%|██████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0176]\n",
-      "Epoch 18: 100%|██████████| 63/63 [00:41<00:00,  1.52it/s, loss=0.0184]\n",
-      "Epoch 19: 100%|██████████| 63/63 [00:41<00:00,  1.52it/s, loss=0.0188]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.44it/s]\n"
+      "Epoch 5: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0695]\n",
+      "Epoch 6: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0431]\n",
+      "Epoch 7: 100%|███████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0292]\n",
+      "Epoch 8: 100%|████████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.022]\n",
+      "Epoch 9: 100%|████████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.019]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 71.66it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -478,22 +478,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 20: 100%|██████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0179]\n",
-      "Epoch 21: 100%|██████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0174]\n",
-      "Epoch 22: 100%|██████████| 63/63 [00:41<00:00,  1.50it/s, loss=0.0174]\n",
-      "Epoch 23: 100%|██████████| 63/63 [00:42<00:00,  1.50it/s, loss=0.0164]\n",
-      "Epoch 24: 100%|██████████| 63/63 [00:42<00:00,  1.48it/s, loss=0.0167]\n",
-      "Epoch 25: 100%|██████████| 63/63 [00:42<00:00,  1.47it/s, loss=0.0167]\n",
-      "Epoch 26: 100%|██████████| 63/63 [00:42<00:00,  1.49it/s, loss=0.0155]\n",
-      "Epoch 27: 100%|██████████| 63/63 [00:41<00:00,  1.50it/s, loss=0.0153]\n",
-      "Epoch 28: 100%|██████████| 63/63 [00:41<00:00,  1.52it/s, loss=0.0157]\n",
-      "Epoch 29: 100%|██████████| 63/63 [00:41<00:00,  1.52it/s, loss=0.0153]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 66.84it/s]\n"
+      "Epoch 10: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0172]\n",
+      "Epoch 11: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0157]\n",
+      "Epoch 12: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0156]\n",
+      "Epoch 13: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0147]\n",
+      "Epoch 14: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0136]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.61it/s]\n"
      ]
     },
     {
      "data": {
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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -505,31 +500,167 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 30: 100%|██████████| 63/63 [00:41<00:00,  1.52it/s, loss=0.0161]\n",
-      "Epoch 31: 100%|██████████| 63/63 [00:42<00:00,  1.50it/s, loss=0.0143]\n",
-      "Epoch 32: 100%|██████████| 63/63 [00:41<00:00,  1.50it/s, loss=0.0149]\n",
-      "Epoch 33:  59%|█████▊    | 37/63 [00:25<00:18,  1.43it/s, loss=0.0155]\n"
+      "Epoch 15: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0143]\n",
+      "Epoch 16: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0142]\n",
+      "Epoch 17: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0135]\n",
+      "Epoch 18: 100%|██████████| 63/63 [00:39<00:00,  1.62it/s, loss=0.0136]\n",
+      "Epoch 19: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0134]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.47it/s]\n"
      ]
     },
     {
-     "ename": "KeyboardInterrupt",
-     "evalue": "",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn [10], line 25\u001b[0m\n\u001b[1;32m     22\u001b[0m loss \u001b[38;5;241m=\u001b[39m F\u001b[38;5;241m.\u001b[39mmse_loss(noise_pred\u001b[38;5;241m.\u001b[39mfloat(), noise\u001b[38;5;241m.\u001b[39mfloat())\n\u001b[1;32m     24\u001b[0m loss\u001b[38;5;241m.\u001b[39mbackward()\n\u001b[0;32m---> 25\u001b[0m \u001b[43moptimizer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstep\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     26\u001b[0m epoch_loss \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m loss\u001b[38;5;241m.\u001b[39mitem()\n\u001b[1;32m     28\u001b[0m progress_bar\u001b[38;5;241m.\u001b[39mset_postfix(\n\u001b[1;32m     29\u001b[0m     {\n\u001b[1;32m     30\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mloss\u001b[39m\u001b[38;5;124m\"\u001b[39m: epoch_loss \u001b[38;5;241m/\u001b[39m (step \u001b[38;5;241m+\u001b[39m \u001b[38;5;241m1\u001b[39m),\n\u001b[1;32m     31\u001b[0m     }\n\u001b[1;32m     32\u001b[0m )\n",
-      "File \u001b[0;32m/media/walter/Storage/Projects/GenerativeModels/venv/lib/python3.8/site-packages/torch/optim/optimizer.py:89\u001b[0m, in \u001b[0;36mOptimizer._hook_for_profile.<locals>.profile_hook_step.<locals>.wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     87\u001b[0m profile_name \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mOptimizer.step#\u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m.step\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mformat(obj\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m)\n\u001b[1;32m     88\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m torch\u001b[38;5;241m.\u001b[39mautograd\u001b[38;5;241m.\u001b[39mprofiler\u001b[38;5;241m.\u001b[39mrecord_function(profile_name):\n\u001b[0;32m---> 89\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[0;32m/media/walter/Storage/Projects/GenerativeModels/venv/lib/python3.8/site-packages/torch/autograd/grad_mode.py:27\u001b[0m, in \u001b[0;36m_DecoratorContextManager.__call__.<locals>.decorate_context\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     24\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(func)\n\u001b[1;32m     25\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdecorate_context\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m     26\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m():\n\u001b[0;32m---> 27\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[0;32m/media/walter/Storage/Projects/GenerativeModels/venv/lib/python3.8/site-packages/torch/optim/adam.py:108\u001b[0m, in \u001b[0;36mAdam.step\u001b[0;34m(self, closure)\u001b[0m\n\u001b[1;32m    105\u001b[0m             state_steps\u001b[38;5;241m.\u001b[39mappend(state[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mstep\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[1;32m    107\u001b[0m     beta1, beta2 \u001b[38;5;241m=\u001b[39m group[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mbetas\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[0;32m--> 108\u001b[0m     \u001b[43mF\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43madam\u001b[49m\u001b[43m(\u001b[49m\u001b[43mparams_with_grad\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    109\u001b[0m \u001b[43m           \u001b[49m\u001b[43mgrads\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    110\u001b[0m \u001b[43m           \u001b[49m\u001b[43mexp_avgs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    111\u001b[0m \u001b[43m           \u001b[49m\u001b[43mexp_avg_sqs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    112\u001b[0m \u001b[43m           \u001b[49m\u001b[43mmax_exp_avg_sqs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    113\u001b[0m \u001b[43m           \u001b[49m\u001b[43mstate_steps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    114\u001b[0m \u001b[43m           \u001b[49m\u001b[43mgroup\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mamsgrad\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    115\u001b[0m \u001b[43m           \u001b[49m\u001b[43mbeta1\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    116\u001b[0m \u001b[43m           \u001b[49m\u001b[43mbeta2\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    117\u001b[0m \u001b[43m           \u001b[49m\u001b[43mgroup\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mlr\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    118\u001b[0m \u001b[43m           \u001b[49m\u001b[43mgroup\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mweight_decay\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    119\u001b[0m \u001b[43m           \u001b[49m\u001b[43mgroup\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43meps\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    120\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m loss\n",
-      "File \u001b[0;32m/media/walter/Storage/Projects/GenerativeModels/venv/lib/python3.8/site-packages/torch/optim/_functional.py:84\u001b[0m, in \u001b[0;36madam\u001b[0;34m(params, grads, exp_avgs, exp_avg_sqs, max_exp_avg_sqs, state_steps, amsgrad, beta1, beta2, lr, weight_decay, eps)\u001b[0m\n\u001b[1;32m     81\u001b[0m     grad \u001b[38;5;241m=\u001b[39m grad\u001b[38;5;241m.\u001b[39madd(param, alpha\u001b[38;5;241m=\u001b[39mweight_decay)\n\u001b[1;32m     83\u001b[0m \u001b[38;5;66;03m# Decay the first and second moment running average coefficient\u001b[39;00m\n\u001b[0;32m---> 84\u001b[0m \u001b[43mexp_avg\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmul_\u001b[49m\u001b[43m(\u001b[49m\u001b[43mbeta1\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39madd_(grad, alpha\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m \u001b[38;5;241m-\u001b[39m beta1)\n\u001b[1;32m     85\u001b[0m exp_avg_sq\u001b[38;5;241m.\u001b[39mmul_(beta2)\u001b[38;5;241m.\u001b[39maddcmul_(grad, grad, value\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m \u001b[38;5;241m-\u001b[39m beta2)\n\u001b[1;32m     86\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m amsgrad:\n\u001b[1;32m     87\u001b[0m     \u001b[38;5;66;03m# Maintains the maximum of all 2nd moment running avg. till now\u001b[39;00m\n",
-      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 200x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Epoch 20: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0142]\n",
+      "Epoch 21: 100%|██████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0126]\n",
+      "Epoch 22: 100%|██████████| 63/63 [00:39<00:00,  1.62it/s, loss=0.0133]\n",
+      "Epoch 23: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0127]\n",
+      "Epoch 24: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0118]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 71.66it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 200x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Epoch 25: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0125]\n",
+      "Epoch 26: 100%|███████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.013]\n",
+      "Epoch 27: 100%|██████████| 63/63 [00:39<00:00,  1.59it/s, loss=0.0119]\n",
+      "Epoch 28: 100%|██████████| 63/63 [00:39<00:00,  1.60it/s, loss=0.0127]\n",
+      "Epoch 29: 100%|██████████| 63/63 [00:39<00:00,  1.59it/s, loss=0.0123]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.62it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 200x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Epoch 30: 100%|██████████| 63/63 [00:41<00:00,  1.50it/s, loss=0.0119]\n",
+      "Epoch 31: 100%|██████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0122]\n",
+      "Epoch 32: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0122]\n",
+      "Epoch 33: 100%|██████████| 63/63 [00:40<00:00,  1.57it/s, loss=0.0123]\n",
+      "Epoch 34: 100%|██████████| 63/63 [00:39<00:00,  1.59it/s, loss=0.0121]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.46it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 200x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Epoch 35: 100%|███████████| 63/63 [00:39<00:00,  1.60it/s, loss=0.012]\n",
+      "Epoch 36: 100%|██████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0113]\n",
+      "Epoch 37: 100%|██████████| 63/63 [00:40<00:00,  1.56it/s, loss=0.0114]\n",
+      "Epoch 38: 100%|██████████| 63/63 [00:40<00:00,  1.57it/s, loss=0.0115]\n",
+      "Epoch 39: 100%|██████████| 63/63 [00:40<00:00,  1.57it/s, loss=0.0115]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 72.46it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 200x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Epoch 40: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0117]\n",
+      "Epoch 41: 100%|██████████| 63/63 [00:39<00:00,  1.60it/s, loss=0.0112]\n",
+      "Epoch 42: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0121]\n",
+      "Epoch 43: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0112]\n",
+      "Epoch 44: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0119]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 72.22it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 200x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Epoch 45: 100%|██████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0116]\n",
+      "Epoch 46: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0111]\n",
+      "Epoch 47: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0116]\n",
+      "Epoch 48: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0111]\n",
+      "Epoch 49: 100%|██████████| 63/63 [00:39<00:00,  1.62it/s, loss=0.0115]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.82it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 200x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "train completed, total time: 2105.790970802307.\n"
      ]
     }
    ],
    "source": [
-    "n_epochs = 100\n",
-    "val_interval = 10\n",
+    "n_epochs = 50\n",
+    "val_interval = 5\n",
     "epoch_loss_list = []\n",
     "val_epoch_loss_list = []\n",
     "\n",
@@ -608,14 +739,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "id": "2cdcda81",
    "metadata": {
     "jupyter": {
      "outputs_hidden": false
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 800x550 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plt.style.use(\"seaborn-v0_8\")\n",
     "plt.title(\"Learning Curves\", fontsize=20)\n",
@@ -645,14 +787,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "id": "1427e5d4",
    "metadata": {
     "jupyter": {
      "outputs_hidden": false
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.73it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "model.eval()\n",
     "noise = torch.randn((1, 1, 64, 64))\n",
@@ -683,7 +843,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "id": "bab2d719",
    "metadata": {},
    "outputs": [],
diff --git a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py
index 996ad4de..d2f3f6e9 100644
--- a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py
+++ b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py
@@ -86,7 +86,7 @@
 # ## Set deterministic training for reproducibility
 
 # %% jupyter={"outputs_hidden": false}
-set_determinism(42)
+set_determinism(0)
 
 # %% [markdown]
 # ## Setup MedNIST Dataset and training and validation dataloaders
@@ -163,6 +163,16 @@
 # %% jupyter={"outputs_hidden": false}
 device = torch.device("cuda")
 
+# model = DiffusionModelUNet(
+#     spatial_dims=2,
+#     in_channels=1,
+#     out_channels=1,
+#     model_channels=64,
+#     attention_resolutions=[2, 4],
+#     num_res_blocks=1,
+#     channel_mult=[1, 2, 2],
+#     num_heads=1,
+# )
 model = DiffusionModelUNet(
     spatial_dims=2,
     in_channels=1,
@@ -170,7 +180,7 @@
     num_channels=(64, 128, 128),
     attention_levels=(False, True, True),
     num_res_blocks=1,
-    num_head_channels=64,
+    num_head_channels=128,
 )
 model.to(device)
 
@@ -186,8 +196,8 @@
 # Here, we are training our model for 100 epochs (training time: ~40 minutes).
 
 # %% jupyter={"outputs_hidden": false}
-n_epochs = 100
-val_interval = 10
+n_epochs = 50
+val_interval = 5
 epoch_loss_list = []
 val_epoch_loss_list = []
 

From e94199d572e31b0c1aba5fb4b97a18614f10c989 Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Fri, 25 Nov 2022 21:48:59 +0000
Subject: [PATCH 20/28] Remove einops code (#53)

---
 .../networks/nets/diffusion_model_unet.py     | 88 ++++++++++++++-----
 1 file changed, 68 insertions(+), 20 deletions(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index 1f8d36d8..daff9a44 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -34,13 +34,10 @@
 
 import torch
 import torch.nn.functional as F
-from monai.networks.blocks import Convolution, SABlock
+from monai.networks.blocks import Convolution
 from monai.networks.layers.factories import Pool
-from monai.utils import optional_import
 from torch import nn
 
-Rearrange, _ = optional_import("einops.layers.torch", name="Rearrange")
-
 __all__ = ["DiffusionModelUNet"]
 
 
@@ -124,11 +121,31 @@ def __init__(
         self.to_k = nn.Linear(cross_attention_dim, inner_dim, bias=False)
         self.to_v = nn.Linear(cross_attention_dim, inner_dim, bias=False)
 
-        self.input_rearrange = Rearrange("b n (h d) -> (b h) n d", h=num_attention_heads)
-        self.out_rearrange = Rearrange("(b h) n d -> b n (h d)", h=num_attention_heads)
+        self.to_out = nn.Sequential(nn.Linear(inner_dim, query_dim), nn.Dropout(dropout))
+
+    def reshape_heads_to_batch_dim(self, x: torch.Tensor) -> torch.Tensor:
+        batch_size, seq_len, dim = x.shape
+        head_size = self.heads
+        x = x.reshape(batch_size, seq_len, head_size, dim // head_size)
+        x = x.permute(0, 2, 1, 3).reshape(batch_size * head_size, seq_len, dim // head_size)
+        return x
 
-        self.out_proj = nn.Linear(inner_dim, query_dim)
-        self.drop_output = nn.Dropout(dropout)
+    def reshape_batch_dim_to_heads(self, x: torch.Tensor) -> torch.Tensor:
+        batch_size, seq_len, dim = x.shape
+        head_size = self.heads
+        x = x.reshape(batch_size // head_size, head_size, seq_len, dim)
+        x = x.permute(0, 2, 1, 3).reshape(batch_size // head_size, seq_len, dim * head_size)
+        return x
+
+    def _attention(self, query: torch.Tensor, key: torch.Tensor, value: torch.Tensor) -> torch.Tensor:
+        attention_scores = torch.matmul(query, key.transpose(-1, -2))
+        attention_probs = attention_scores.softmax(dim=-1)
+        # compute attention output
+        hidden_states = torch.matmul(attention_probs, value)
+
+        # reshape hidden_states
+        hidden_states = self.reshape_batch_dim_to_heads(hidden_states)
+        return hidden_states
 
     def forward(self, x: torch.Tensor, context: Optional[torch.Tensor] = None) -> torch.Tensor:
         query = self.to_q(x)
@@ -136,18 +153,13 @@ def forward(self, x: torch.Tensor, context: Optional[torch.Tensor] = None) -> to
         key = self.to_k(context)
         value = self.to_v(context)
 
-        query = self.input_rearrange(query)
-        key = self.input_rearrange(key)
-        value = self.input_rearrange(value)
+        query = self.reshape_heads_to_batch_dim(query)
+        key = self.reshape_heads_to_batch_dim(key)
+        value = self.reshape_heads_to_batch_dim(value)
 
-        sim = torch.einsum("b i d, b j d -> b i j", query, key) * self.scale
-        attn = sim.softmax(dim=-1)
-        out = torch.einsum("b i j, b j d -> b i d", attn, value)
-        out = self.out_rearrange(out)
+        x = self._attention(query, key, value)
 
-        out = self.out_proj(out)
-        out = self.drop_output(out)
-        return out
+        return self.to_out(x)
 
 
 class BasicTransformerBlock(nn.Module):
@@ -329,9 +341,21 @@ def __init__(
         self.num_channels = num_channels
 
         self.num_heads = num_channels // num_head_channels if num_head_channels is not None else 1
+        self.num_head_size = num_head_channels
         self.norm = nn.GroupNorm(num_groups=norm_num_groups, num_channels=num_channels, eps=norm_eps, affine=True)
 
-        self.attention = SABlock(hidden_size=num_channels, num_heads=self.num_heads, qkv_bias=True)
+        # define q,k,v as linear layers
+        self.query = nn.Linear(num_channels, num_channels)
+        self.key = nn.Linear(num_channels, num_channels)
+        self.value = nn.Linear(num_channels, num_channels)
+
+        self.proj_attn = nn.Linear(num_channels, num_channels, 1)
+
+    def transpose_for_scores(self, projection: torch.Tensor) -> torch.Tensor:
+        new_projection_shape = projection.size()[:-1] + (self.num_heads, -1)
+        # move heads to 2nd position (B, T, H * D) -> (B, T, H, D) -> (B, H, T, D)
+        new_projection = projection.view(new_projection_shape).permute(0, 2, 1, 3)
+        return new_projection
 
     def forward(self, x: torch.Tensor) -> torch.Tensor:
         residual = x
@@ -342,6 +366,7 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
         if self.spatial_dims == 3:
             batch, channel, height, width, depth = x.shape
 
+        # norm
         x = self.norm(x)
 
         if self.spatial_dims == 2:
@@ -349,7 +374,30 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
         if self.spatial_dims == 3:
             x = x.view(batch, channel, height * width * depth).transpose(1, 2)
 
-        x = self.attention(x)
+        # proj to q, k, v
+        query_proj = self.query(x)
+        key_proj = self.key(x)
+        value_proj = self.value(x)
+
+        # transpose
+        query_states = self.transpose_for_scores(query_proj)
+        key_states = self.transpose_for_scores(key_proj)
+        value_states = self.transpose_for_scores(value_proj)
+
+        # get scores
+        scale = 1 / math.sqrt(math.sqrt(self.num_channels / self.num_heads))
+        attention_scores = torch.matmul(query_states * scale, key_states.transpose(-1, -2) * scale)
+        attention_probs = torch.softmax(attention_scores.float(), dim=-1)
+
+        # compute attention output
+        x = torch.matmul(attention_probs, value_states)
+
+        x = x.permute(0, 2, 1, 3).contiguous()
+        new_x_shape = x.size()[:-2] + (self.num_channels,)
+        x = x.view(new_x_shape)
+
+        # compute next hidden states
+        x = self.proj_attn(x)
 
         if self.spatial_dims == 2:
             x = x.transpose(-1, -2).reshape(batch, channel, height, width)

From bc5ab7ec3f8c799a3c946fd08649fa549eba53fa Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Fri, 25 Nov 2022 21:54:27 +0000
Subject: [PATCH 21/28] Update diffusion inferer tests (#53)

---
 tests/test_diffusion_inferer.py | 14 ++++++--------
 1 file changed, 6 insertions(+), 8 deletions(-)

diff --git a/tests/test_diffusion_inferer.py b/tests/test_diffusion_inferer.py
index b5664f04..cbedebd5 100644
--- a/tests/test_diffusion_inferer.py
+++ b/tests/test_diffusion_inferer.py
@@ -24,12 +24,11 @@
             "spatial_dims": 2,
             "in_channels": 1,
             "out_channels": 1,
-            "model_channels": 8,
+            "num_channels": [8],
             "norm_num_groups": 8,
-            "attention_resolutions": [1],
+            "attention_levels": [True],
             "num_res_blocks": 1,
-            "channel_mult": [1],
-            "num_heads": 1,
+            "num_head_channels": 8,
         },
         (2, 1, 8, 8),
     ],
@@ -38,12 +37,11 @@
             "spatial_dims": 3,
             "in_channels": 1,
             "out_channels": 1,
-            "model_channels": 8,
+            "num_channels": [8],
             "norm_num_groups": 8,
-            "attention_resolutions": [1],
+            "attention_levels": [True],
             "num_res_blocks": 1,
-            "channel_mult": [1],
-            "num_heads": 1,
+            "num_head_channels": 8,
         },
         (2, 1, 8, 8, 8),
     ],

From e9185df154224d89ac7058170e9a4e98ceff9ddb Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Sat, 26 Nov 2022 07:26:28 +0000
Subject: [PATCH 22/28] Rerun tutorials (#53)

---
 .../networks/nets/diffusion_model_unet.py     |    2 +-
 .../2d_ddpm/2d_ddpm_compare_schedulers.ipynb  |  588 +++----
 .../2d_ddpm/2d_ddpm_compare_schedulers.py     |   13 +-
 .../generative/2d_ddpm/2d_ddpm_tutorial.ipynb |  296 ++--
 .../generative/2d_ddpm/2d_ddpm_tutorial.py    |   16 +-
 .../2d_ddpm/2d_ddpm_tutorial_ignite.ipynb     | 1513 +++++++++++++++--
 .../2d_ddpm/2d_ddpm_tutorial_ignite.py        |   17 +-
 7 files changed, 1853 insertions(+), 592 deletions(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index daff9a44..d1a7f1bb 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -349,7 +349,7 @@ def __init__(
         self.key = nn.Linear(num_channels, num_channels)
         self.value = nn.Linear(num_channels, num_channels)
 
-        self.proj_attn = nn.Linear(num_channels, num_channels, 1)
+        self.proj_attn = nn.Linear(num_channels, num_channels)
 
     def transpose_for_scores(self, projection: torch.Tensor) -> torch.Tensor:
         new_projection_shape = projection.size()[:-1] + (self.num_heads, -1)
diff --git a/tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.ipynb b/tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.ipynb
index ad9bd487..8e3d5c64 100644
--- a/tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.ipynb
+++ b/tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.ipynb
@@ -47,39 +47,33 @@
    "id": "cf51122f",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/mark/Envs/gen2/lib/python3.6/site-packages/tqdm/auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
-      "  from .autonotebook import tqdm as notebook_tqdm\n"
-     ]
-    },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "MONAI version: 0.9.dev2151\n",
-      "Numpy version: 1.19.5\n",
-      "Pytorch version: 1.10.1+cu102\n",
-      "MONAI flags: HAS_EXT = False, USE_COMPILED = False\n",
-      "MONAI rev id: 8bbc7c0eeceadae6b3d7a487b85068b4dc7e4899\n",
+      "MONAI version: 1.1.dev2246\n",
+      "Numpy version: 1.23.3\n",
+      "Pytorch version: 1.8.0+cu111\n",
+      "MONAI flags: HAS_EXT = False, USE_COMPILED = False, USE_META_DICT = False\n",
+      "MONAI rev id: c81b9467b43bb14e77956729d10f2aef4d69deec\n",
+      "MONAI __file__: /media/walter/Storage/Projects/GenerativeModels/venv/lib/python3.8/site-packages/monai/__init__.py\n",
       "\n",
       "Optional dependencies:\n",
-      "Pytorch Ignite version: NOT INSTALLED or UNKNOWN VERSION.\n",
-      "Nibabel version: NOT INSTALLED or UNKNOWN VERSION.\n",
+      "Pytorch Ignite version: 0.4.10\n",
+      "Nibabel version: 4.0.2\n",
       "scikit-image version: NOT INSTALLED or UNKNOWN VERSION.\n",
-      "Pillow version: 8.4.0\n",
-      "Tensorboard version: NOT INSTALLED or UNKNOWN VERSION.\n",
-      "gdown version: 4.5.3\n",
-      "TorchVision version: 0.11.2+cu102\n",
+      "Pillow version: 9.2.0\n",
+      "Tensorboard version: 2.11.0\n",
+      "gdown version: NOT INSTALLED or UNKNOWN VERSION.\n",
+      "TorchVision version: 0.9.0+cu111\n",
       "tqdm version: 4.64.1\n",
       "lmdb version: NOT INSTALLED or UNKNOWN VERSION.\n",
-      "psutil version: NOT INSTALLED or UNKNOWN VERSION.\n",
+      "psutil version: 5.9.3\n",
       "pandas version: NOT INSTALLED or UNKNOWN VERSION.\n",
-      "einops version: 0.4.1\n",
+      "einops version: 0.6.0\n",
       "transformers version: NOT INSTALLED or UNKNOWN VERSION.\n",
       "mlflow version: NOT INSTALLED or UNKNOWN VERSION.\n",
+      "pynrrd version: NOT INSTALLED or UNKNOWN VERSION.\n",
       "\n",
       "For details about installing the optional dependencies, please visit:\n",
       "    https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies\n",
@@ -144,7 +138,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/tmp/tmpc22g9eo1\n"
+      "/tmp/tmpmk0ge830\n"
      ]
     }
    ],
@@ -193,17 +187,14 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Downloading...\n",
-      "From: https://drive.google.com/uc?id=1QsnnkvZyJPcbRoV_ArW8SnE1OTuoVbKE\n",
-      "To: /tmp/tmpyo3rjshh/MedNIST.tar.gz\n",
-      "100%|██████████| 61.8M/61.8M [00:04<00:00, 14.6MB/s]"
+      "MedNIST.tar.gz: 59.0MB [00:03, 17.1MB/s]                                                                                                                                                                                        "
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-14 20:03:52,938 - INFO - Downloaded: /tmp/tmpc22g9eo1/MedNIST.tar.gz\n"
+      "2022-11-25 23:04:35,119 - INFO - Downloaded: /tmp/tmpmk0ge830/MedNIST.tar.gz\n"
      ]
     },
     {
@@ -217,15 +208,15 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-14 20:03:53,013 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
-      "2022-11-14 20:03:53,013 - INFO - Writing into directory: /tmp/tmpc22g9eo1.\n"
+      "2022-11-25 23:04:35,192 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
+      "2022-11-25 23:04:35,192 - INFO - Writing into directory: /tmp/tmpmk0ge830.\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Loading dataset: 100%|██████████| 47164/47164 [00:12<00:00, 3638.95it/s]\n"
+      "Loading dataset: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 47164/47164 [00:14<00:00, 3260.23it/s]\n"
      ]
     }
    ],
@@ -257,9 +248,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/mark/Envs/gen2/lib/python3.6/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at  ../aten/src/ATen/native/TensorShape.cpp:2157.)\n",
-      "  return _VF.meshgrid(tensors, **kwargs)  # type: ignore[attr-defined]\n",
-      "Loading dataset: 100%|██████████| 7999/7999 [00:03<00:00, 2499.17it/s]\n"
+      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1746.60it/s]\n"
      ]
     }
    ],
@@ -281,7 +270,7 @@
     "    ]\n",
     ")\n",
     "train_ds = CacheDataset(data=train_datalist, transform=train_transforms)\n",
-    "train_loader = DataLoader(train_ds, batch_size=128, shuffle=True, num_workers=4)"
+    "train_loader = DataLoader(train_ds, batch_size=128, shuffle=True, num_workers=4, persistent_workers=True)"
    ]
   },
   {
@@ -294,17 +283,17 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-14 20:04:14,256 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
-      "2022-11-14 20:04:14,257 - INFO - File exists: /tmp/tmpc22g9eo1/MedNIST.tar.gz, skipped downloading.\n",
-      "2022-11-14 20:04:14,257 - INFO - Non-empty folder exists in /tmp/tmpc22g9eo1/MedNIST, skipped extracting.\n"
+      "2022-11-25 23:04:58,982 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
+      "2022-11-25 23:04:58,982 - INFO - File exists: /tmp/tmpmk0ge830/MedNIST.tar.gz, skipped downloading.\n",
+      "2022-11-25 23:04:58,983 - INFO - Non-empty folder exists in /tmp/tmpmk0ge830/MedNIST, skipped extracting.\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Loading dataset: 100%|██████████| 5895/5895 [00:01<00:00, 3722.25it/s]\n",
-      "Loading dataset: 100%|██████████| 7999/7999 [00:03<00:00, 2536.67it/s]\n"
+      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 5895/5895 [00:01<00:00, 3320.09it/s]\n",
+      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1803.09it/s]\n"
      ]
     }
    ],
@@ -319,7 +308,7 @@
     "    ]\n",
     ")\n",
     "val_ds = CacheDataset(data=val_datalist, transform=val_transforms)\n",
-    "val_loader = DataLoader(val_ds, batch_size=128, shuffle=False, num_workers=4)"
+    "val_loader = DataLoader(val_ds, batch_size=128, shuffle=False, num_workers=4, persistent_workers=True)"
    ]
   },
   {
@@ -340,26 +329,24 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "batch shape: torch.Size([128, 1, 64, 64])\n"
+      "batch shape: (128, 1, 64, 64)\n"
      ]
     },
     {
      "data": {
-      "image/png": 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       "text/plain": [
-       "<Figure size 864x432 with 1 Axes>"
+       "<Figure size 1200x600 with 1 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
    "source": [
     "check_data = first(train_loader)\n",
     "print(f\"batch shape: {check_data['image'].shape}\")\n",
-    "image_visualisation = torch.concat(\n",
+    "image_visualisation = torch.cat(\n",
     "    [check_data[\"image\"][0, 0], check_data[\"image\"][1, 0], check_data[\"image\"][2, 0], check_data[\"image\"][3, 0]], dim=1\n",
     ")\n",
     "plt.figure(\"training images\", (12, 6))\n",
@@ -392,11 +379,10 @@
     "    spatial_dims=2,\n",
     "    in_channels=1,\n",
     "    out_channels=1,\n",
-    "    model_channels=64,\n",
-    "    attention_resolutions=[2, 4],\n",
+    "    num_channels=(64, 128, 128),\n",
+    "    attention_levels=(False, True, True),\n",
     "    num_res_blocks=1,\n",
-    "    channel_mult=[1, 2, 2],\n",
-    "    num_heads=1,\n",
+    "    num_head_channels=128,\n",
     ")\n",
     "model.to(device)\n",
     "\n",
@@ -466,7 +452,7 @@
    "metadata": {},
    "source": [
     "### Model training\n",
-    "Here, we are training our model for 50 epochs (training time: ~40 minutes). It is necessary to train for a bit longer than other tutorials because the DDIM and PNDM schedules seem to require a model trained longer before they start producing good samples, when compared to DDPM."
+    "Here, we are training our model for 100 epochs (training time: ~40 minutes). It is necessary to train for a bit longer than other tutorials because the DDIM and PNDM schedules seem to require a model trained longer before they start producing good samples, when compared to DDPM."
    ]
   },
   {
@@ -481,380 +467,360 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 0: 100%|██████████| 63/63 [00:32<00:00,  1.92it/s, loss=0.74] \n",
-      "Epoch 1: 100%|██████████| 63/63 [00:36<00:00,  1.75it/s, loss=0.59] \n",
-      "Epoch 2: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.42] \n",
-      "Epoch 3: 100%|██████████| 63/63 [00:40<00:00,  1.54it/s, loss=0.255]\n",
-      "Epoch 4: 100%|██████████| 63/63 [00:42<00:00,  1.49it/s, loss=0.148]\n",
-      "Epoch 5: 100%|██████████| 63/63 [00:43<00:00,  1.45it/s, loss=0.0925]\n",
-      "Epoch 6: 100%|██████████| 63/63 [00:44<00:00,  1.41it/s, loss=0.0698]\n",
-      "Epoch 7: 100%|██████████| 63/63 [00:45<00:00,  1.40it/s, loss=0.06]  \n",
-      "Epoch 8: 100%|██████████| 63/63 [00:46<00:00,  1.35it/s, loss=0.0574]\n",
-      "Epoch 9: 100%|██████████| 63/63 [00:48<00:00,  1.31it/s, loss=0.0558]\n",
-      "Epoch 9 - Validation set: 100%|██████████| 63/63 [00:14<00:00,  4.50it/s, val_loss=0.0561]\n",
-      "Epoch 9 - Sampling from DDPMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 147.71it/s]\n",
-      "Epoch 9 - Sampling from DDIMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 151.50it/s]\n",
-      "Epoch 9 - Sampling from DDIMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 150.97it/s]\n",
-      "Epoch 9 - Sampling from DDIMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 150.70it/s]\n",
-      "Epoch 9 - Sampling from DDIMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 150.81it/s]\n",
-      "Epoch 9 - Sampling from PNDMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 153.54it/s]\n",
-      "Epoch 9 - Sampling from PNDMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 151.09it/s]\n",
-      "Epoch 9 - Sampling from PNDMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 151.23it/s]\n",
-      "Epoch 9 - Sampling from PNDMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 153.73it/s]\n"
+      "Epoch 0: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:36<00:00,  1.73it/s, loss=0.74]\n",
+      "Epoch 1: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:36<00:00,  1.72it/s, loss=0.59]\n",
+      "Epoch 2: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.70it/s, loss=0.421]\n",
+      "Epoch 3: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.69it/s, loss=0.257]\n",
+      "Epoch 4: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.69it/s, loss=0.149]\n",
+      "Epoch 5: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0945]\n",
+      "Epoch 6: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0725]\n",
+      "Epoch 7: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0633]\n",
+      "Epoch 8: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0599]\n",
+      "Epoch 9: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0585]\n",
+      "Epoch 9 - Validation set: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:11<00:00,  5.65it/s, val_loss=0.0586]\n",
+      "Epoch 9 - Sampling from DDPMScheduler...: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.04it/s]\n",
+      "Epoch 9 - Sampling from DDIMScheduler...: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 70.03it/s]\n",
+      "Epoch 9 - Sampling from DDIMScheduler...: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 69.92it/s]\n",
+      "Epoch 9 - Sampling from DDIMScheduler...: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 69.13it/s]\n",
+      "Epoch 9 - Sampling from DDIMScheduler...: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 69.74it/s]\n",
+      "Epoch 9 - Sampling from PNDMScheduler...: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 70.16it/s]\n",
+      "Epoch 9 - Sampling from PNDMScheduler...: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 70.13it/s]\n",
+      "Epoch 9 - Sampling from PNDMScheduler...: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 69.97it/s]\n",
+      "Epoch 9 - Sampling from PNDMScheduler...: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 70.11it/s]\n"
      ]
     },
     {
      "data": {
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\n",
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\n",
       "text/plain": [
-       "<Figure size 576x288 with 9 Axes>"
+       "<Figure size 800x400 with 9 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 10: 100%|██████████| 63/63 [00:45<00:00,  1.40it/s, loss=0.0542]\n",
-      "Epoch 11: 100%|██████████| 63/63 [00:49<00:00,  1.26it/s, loss=0.0549]\n",
-      "Epoch 12: 100%|██████████| 63/63 [00:51<00:00,  1.23it/s, loss=0.0542]\n",
-      "Epoch 13: 100%|██████████| 63/63 [00:51<00:00,  1.23it/s, loss=0.0525]\n",
-      "Epoch 14: 100%|██████████| 63/63 [00:51<00:00,  1.23it/s, loss=0.0523]\n",
-      "Epoch 15: 100%|██████████| 63/63 [00:52<00:00,  1.20it/s, loss=0.0515]\n",
-      "Epoch 16: 100%|██████████| 63/63 [00:52<00:00,  1.20it/s, loss=0.0506]\n",
-      "Epoch 17: 100%|██████████| 63/63 [00:51<00:00,  1.22it/s, loss=0.05]  \n",
-      "Epoch 18: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0508]\n",
-      "Epoch 19: 100%|██████████| 63/63 [00:51<00:00,  1.22it/s, loss=0.0496]\n",
-      "Epoch 19 - Validation set: 100%|██████████| 63/63 [00:16<00:00,  3.89it/s, val_loss=0.0505]\n",
-      "Epoch 19 - Sampling from DDPMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 144.14it/s]\n",
-      "Epoch 19 - Sampling from DDIMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 152.53it/s]\n",
-      "Epoch 19 - Sampling from DDIMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 151.15it/s]\n",
-      "Epoch 19 - Sampling from DDIMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 154.64it/s]\n",
-      "Epoch 19 - Sampling from DDIMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 156.41it/s]\n",
-      "Epoch 19 - Sampling from PNDMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 154.93it/s]\n",
-      "Epoch 19 - Sampling from PNDMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 153.19it/s]\n",
-      "Epoch 19 - Sampling from PNDMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 151.58it/s]\n",
-      "Epoch 19 - Sampling from PNDMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 153.75it/s]\n"
+      "Epoch 10: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.70it/s, loss=0.0567]\n",
+      "Epoch 11: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0572]\n",
+      "Epoch 12: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0564]\n",
+      "Epoch 13: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0543]\n",
+      "Epoch 14: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0542]\n",
+      "Epoch 15: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0536]\n",
+      "Epoch 16: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0524]\n",
+      "Epoch 17: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0521]\n",
+      "Epoch 18: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0528]\n",
+      "Epoch 19: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0514]\n",
+      "Epoch 19 - Validation set: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:11<00:00,  5.60it/s, val_loss=0.0525]\n",
+      "Epoch 19 - Sampling from DDPMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.27it/s]\n",
+      "Epoch 19 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 70.18it/s]\n",
+      "Epoch 19 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 70.01it/s]\n",
+      "Epoch 19 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 69.80it/s]\n",
+      "Epoch 19 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 69.49it/s]\n",
+      "Epoch 19 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 71.09it/s]\n",
+      "Epoch 19 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 71.21it/s]\n",
+      "Epoch 19 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 69.82it/s]\n",
+      "Epoch 19 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 70.43it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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+fbtywQUXKHa7XfF6vcqVV16p9PX1jdtmNptVVq1apTQ1NSlms1mZPXu28rvf/U5z/8VuU2TNmjXKBRdcoPj9fsVsNiuNjY3KDTfcoPT29qrW+9WvfqVMmTJFMRgMCgBl3bp17LV169Ypy5YtUzwej2K1WpXW1lZl5cqVyubNm9k611xzjeJwOJS9e/eycVZVVSl33HGHks1mSx6PRCKRSCSS459JtZxJCrNy5UqsWbMGkUhksocikUgkEonkXUL6uyQSiUQikUiOI6Q4k0gkEolEIjmOkOJMIpFIJBKJ5DhCxpxJJBKJRCKRHEdIy5lEIpFIJBLJcYQUZxKJRCKRSCTHEZPSvimXy6GnpwculytvmyPJkaMoCsLhMGpra2UhWolEIpFIThAmRZz19PSgoaFhMnb9nqSzsxP19fWTPQyJRCKRSCRFMCnizOVyTcZuGbwViSx3iqIgl8vlfY+Whe9EyaWY7M9bIpFIJBJJ8UyKOOOFjk6ng16vh16vh6IoTPDwwqeQaDqSfZeyLo0vl8sdM1esTqdTicWjJf6k61gikUgkkhOHSRFnWuRyOU1BcrStU7QPEkLZbBaAWhhp7Z/WE8ek0+nY9o50zEdTkEkkEolEIjkxOS7EGW8tI6FzLEWKaLmbaFwTbUdapiQSiUQikRwtJjWFL5+1KZ8oOtoiqFjxpbU832uTYfmS4lAikUgkkv8cJlWcacWXkfDhrVLi83cTrbGIj8X13w30ej2L13s39yuRSCQSieTYclwUvyoU6yVa1I6GZaoYK52IOMZ88XH5hObRFE+iUJXCTCKRSCSS/xwmPeZMSxxpiZ5j6dI80u3nE3jHwsV5Ipf0kEgkEolEMjGTLs6IiQTG0SwrcaTbOp7E0PE0FolEIpFIJEfOcSPO3i1EMVMosF/LbfhuZJOWQj5Lml6vP6r14SQSiUQikbw7HBfi7HgROjyF6pZNdkbmRC7Y40k8SiQSiUQiKY3jIiGA52gHz2ttn+dEEDHFCrNj/dlJJBKJRCI59hwXlrN8JSmOhXCaKAGBb590Igo54JBIm6hfqEQikUgkkuOP40Kc5YMXSvT8cARSKSLrcMpsHGsKHX8+MXkse4BKJBKJRCI5dhyX4uxol6YwGAyq95M1qZQaZ++mUBMFF1/zTUtoaolY/r9EIpFIJJITh+NGnInC4mhA7j2TycT2QQ3Miy1oywudd0OgTXT8xdRk4xu7SyQSiUQiObE4bsRZsa2QShFIJpMJdrsdTqcTuVwO2WwWsVgM2WwW2WwWmUwGuVyuaDfnu00xFjBpJZNIJBKJ5D+LSRdnhZqLHyl6vR5msxl2ux3AmDvTYrEgl8shk8kgkUgwgZbL5ZBOp8e5Pt8t3u2m7hKJRCKRSI5PJl2caXG0hIrBYIDJZILNZoPBYIBOp0M2m4Ver0cqlUIsFkMymUQ2m0Uul0MikVBZ1cj1eazrnB1p6yhyuZ6o2aUSiUQikUgOcdyIs0JFX8X1ihEdJMpcLhfKysrgcrmYSDMajchkMohEIohEIgDGrGzJZBKRSASJRAKxWAzxeJzFqJFYo/GJrtF84xOD9Uv5LPJ1I9Davuy5KZFIJBLJfwbHjTjLV3/scGug5XI5Zh0jAaYoCsrKylBeXg6dTodIJIJwOKwSQYlEQiXSKFYtnU4zQUbLMpkMkskkYrEYMpnMOKFWaMzFWst4y50UYhKJRCKR/Odz3IgznmKzKAutRzFksVgM4XCYxZlZLBa43W6YTCYYjUZYrVYmzgwGA2w2G7LZLJxOJ+LxODKZDBNl6XSabYf+EokErFYrkskkE3Yk4Eop1VHMsecTq/lqs8kkAYlEIpFITjyOC3FWbLZkKWJDURTE43GkUikoioJgMAiLxYJwOIxAIAC73Q6LxQKTyQS9Xg+9Xg+j0ciEWzabRTgcZu5MEoOKoiCVSiGZTCKTybDtx2IxBINBDA8PIxaLMaGWr0SI1jHnK38h1jrTWq6FFGcSiUQikZx4HBfi7GggChESOhRLRpascDiMZDIJi8UCm80Gs9kMk8kEs9kMn88HYCxeTVEUmM1mFquWTqdhMBig1+uRSCSQTqeZ9SybzSKRSCAcDqO8vJzFsg0ODiISiTABl2/MhSxn+QSWmKjACzv6b7FYEIvFSv0oJRKJRCKRTCKTLs5KjZUqxVVIIiWbzbIgfkVRoNfrYTAYYLFYYLVaYbfb4XK5kEqloNfrkc1mmRCj7E6Hw8G2ZzabmeAi0ZfJZODxeBCPxxEKhRAOh2G1WjE8PIxwOMxcq+KxTJQwUKxljI6X3LN6vV6KM4lEIpFITkAmXZxNhChAgIkFGlmVSKxQvBgApFIplUhyu93w+XywWCxIp9PQ6XTI5XIqAWaxWODxeFgSAMWl0Xb0ej0bXzKZRCgUQjAYhM/nQ09PD4aGhpDJZBCNRjXHKj4u1JWAX4f2y38+BoMBVqsVBoMBdrsdo6OjBT8riUQikUgkxxfHrTgjoWG325mFii8SC0AVh6XX65koy+Vy0Ov141x95H4kjEajqv5ZJpNBOp2GXq+H2+1mrymKAqfTCYvFAqPRCJPJhGAwiFgshlgsxvZnNBqRTqdhNptRVlbGynmUl5fDYrHgwIEDzCVK7xGZSHjy76EyH4TT6YTD4UBZWRn8fj+8Xi+6urpK//AlEolEIpFMGiWJs29/+9tFrfeNb3zjsAbDYzabYbPZWBxYNptFPB7XrDWWy+WYwCIRR1DsGAk1o9HIhJter4fNZoNOp2NlMYxGI8xmM6xWK3N/UlwZdRwwGAxwOp0sXo32T6/T+na7HZWVlUgkEsw6Nzw8jEAggEgkwlyitG2tgre85VDMACWhaLFYUFdXh/LycrjdbpSXl8PpdMLlcuGJJ5444u9CIpFIJBLJu0dJ4uyb3/wmamtr4ff781p4dDrdEYszalZut9vh9XqZ8KKyF3ycFwkhLesXCSZeaJH1CxgTO9RFgJaZzWYWi8Zb3nhhlM1mWaYnX52fRB7VRCNhqCgKKisrkc1m0dPTg56eHuh0OqRSKbY+AHZs/OdA1jseEnFlZWVwOp1wu92YOXMmKioq4PF44PP5oNfrWdsqiUQikUgkJw4libPly5fjn//8J0477TRce+21+OAHP6jpmjsc+HgyEkxmsxlOpxMGg0EVoE+9MDOZjGY2o8FggNvtZm5LvV7PBBMAJooymQzMZjMcDgdcLpcqc9NsNjMrG5+lSSU0aH2j0cgEn9FoZAVps9ksywo1m82oq6uD3+9HX18fDhw4gL1792JkZIRlj0ajUTZGOj5FUeBwOGCz2Vh2qcvlYttsbGxEZWUlfD4fysvL4XA42HrxeFyW0pBIJBKJ5ASkJHH21FNPoaenB4888ghuueUW3HDDDbj66qtx7bXXYvr06UdtUCTCSLTYbDZWiwwAa2ZuNBphs9lgtVqZFQwYs3L5fD7mghweHmaJABaLBYlEgtUqo+B5sqpReyeqg6YoCtLpNJLJJHM9RiIRhEIhmEwmWK1WlJWVMfekw+Fg1q5IJMJcsRaLBU1NTXC5XLDb7TAYDAiFQkgkEtDr9cxiRvsjTCYT209VVRX8fj/sdjtsNhvKysqYcNTpdLBYLLBYLHC5XEy8SiQSiUQiObEoOSGgtrYWt99+O26//Xa89NJLeOihh3D66afjpJNOwvPPPw+bzXbEgyKhk0qlWIYj7/LjS1rYbDY4nU62DrkeybpEQovclA6Hg4mzVCoFm82mcpXy7k8SZ+Sy5LNAyQpnMBhUGaAk8PhuAzReh8MBYMwtGo1GUVZWhkwmwzIsSfyRoCO3pqIoMJlMqKysRHV1NQv8p+OmYychR0kUfPKDRCKRSCSSE4MjytY8/fTT0dHRgR07dmDLli1Ip9OHLc74ml9k9UkmkxgeHkY8Hmdii2K9qCYZlbywWq0YHR1FOp2G3W5HIpFQuSjJ2kRFYqmIrMfjgaIoSCaT6OvrYy5Vq9UKk8kEAGwbFNNWXl7OxFwul1MJSKPRyGLSrFYrO55EIsHEIVn4KGtTp9PB7/ezbM9gMKgSZ+TypOxVOhYSnVarVWWxA8YEYCgUOpKvVyKRSCQSySRwWOLstddew29+8xs8+uijmDZtGj71qU/hE5/4BNxu92EPRKyST03Eyb1JsV0U32UwGDA6OgqPxwOXywWHw8Fcn4lEgmVU2mw2lnEZDocRj8dZe6VUKsXcl+QCJddpJpOB1WpVvUYxaXzAv8lkQjKZZGNPJBIsi7S2tlZ1jH6/H8lkEqOjozAYDPB4PLBYLIjH46x0RyqVgtvtZoJQp9OxQrJer5dZACnZwGQywWAwqMqHUNN3flwSiUQikUhODEoSZ3fddRcefvhhDA0N4corr8TLL7+MuXPnHquxqeqbUZA8Wcx0Oh2i0SjraWm1Wploo3IYFLxPUCkN2i7FiInCkMQhuQWpXAUf3xaPx1ndNRJIlEBAljd6DRiLo6OitlQixOVywWq1MguewWBgmabkolQUBdFoFJlMhm2LjoO3lPHjpp6fMuZMIpFIJJITD51SQv8kvV6PxsZGfPCDH4TZbM673n333VdwO6FQCB6PRz0QTmTwZTBov6KA4stg8FYmo9HI+mFarVY4nU4kk0kmnhwOh8pK1tDQwN5LQf9UUJbqoJWVlaGiooK5EakILTVW52ujJZNJNiZybRqNRmbtIqFHyQgUF0eWM3KX8lmmkUgEiUSCZWCaTCaVG5OW8VYzitdrbm5GMBg8IqumRCKRSCSSd4+SLGdLliyBTqfD22+/nXedwynfoNWmCDhULV9MBOAtX+l0GvF4nAXhk5uRYrISiQQymQycTiecTifsdjuLactkMuju7mZCzuFwMFEGQCWu+IbpFOdF5TRsNhuLkaMsTiqrkUql2DoU+O/1euFwOJh7lQrsksik/VMsHB0/HSPtn6xufK00AKwXqEQikUgkkhOPksTZiy++eEwGIQozsl6JvTQpm5EyKvn38a2WKP6KRBjFnpFbkIqzkojjC9OSxY4P2o9EIqwmmtVqhcfjYWPkXa02m43FgZEbk689ls1mmVCj5AG73a6qpUbHTOU7kskkUqkUey8dH198lwQlL+rI+ieRSCQSieTEouSrdygUwoYNG5BKpbBgwQJUVlYe1QHxLkU+wJ1eA6Cq3E/P+V6a1NaIXIYOh0PVBcBisTChR9mffAwXWagAsISEVCrFMjx58Ubb4ctYUEFaapJusVjgdDqZiKOsTHK1iiKKt+xRcgG5OjOZDIsto7ZP/Jj5z0sWoZVIJBKJ5MSjJHG2detWfOADH0BfXx8AwOVy4dFHH8WyZcuOymDI+sSLK7J2AVAVmQUONS4nqxPfloncmlQTjALmeRFD4sVoNKoam5MFjgL++ZplyWQS/f39iMfjcDqdrI8lWbTIRWo2m5FOp5FKpQCA9eIEDhWapfETtA2qc8a7asWOCBT0LwpLQuzDKZFIJBKJ5MSgJHF26623oqWlBX/+859htVrxne98BzfddBPa29uPeCAkzMrLy+H1epnljOKwSKSQKzGdTjNrFbkbyQpGVfJJrFGjcaqH5vF4YDKZ4HK5oNPpVP0oSZxls1mVq5SsZmStoi4GFO+WyWRgsVhY3bNQKIRYLMZcmhSkz8MX1uUtYGR1y+VyLBOUOgDwFkLeDSrWiKOabBKJRCKRSE4sShJnr7/+Op599lmceuqpAIDf/OY38Pl8CIVCR5wNSO5Iu90Ol8ulKk9B7kmqdQaMuRvJGkUCjbZBbkSyStHyRCIBr9eLyspKmM1mVirD4XCw7EdynZI44y1tfG0z2i6fmUljI/FGgpGWU5wcb7WjXpq85YtEIq1L/+kYtdyVZBnk//gm6hKJRCKRSE4MShJnIyMjqK+vZ88p63B4ePiIxRkFsZNLkHpQUuA8CR6Px8MEmd/vZ1Y16nmZyWSYkBPjzlKpFCorK1FXVweTyYRwOMwsZTqdjtUmo5guYCw+zePxwO12szGQ+zObzSKRSLAxUvYkVfDn3ackrvjjpTg2EnwUv0ZjnyhmjBdfvCDj/yQSiUQikZxYlJwQsGPHDhZzBoyJgp07dyIcDrNlh1OYli84S7FaVFaCAumtVitsNhscDgfsdjs8Hg8TMDabjVXT53tTUskJynhMp9OIxWIsjstoNCKZTLKyFnzzcwr8z2azLBOT73VJYnFgYICV9rDb7UilUiwmjcZBTdp5yxeJTD6WjEQbCTQATGjxLlWy8NFrJOz47E2ZECCRSCQSyYlHyeLs3HPPHRdo/sEPflDlfqOm4KWSyWQQjUZZMVbqUUmiJJPJoK+vD1arFXa7HcFgkFnJ7HY7AoEAotEootEoSwag7gJUyJXciGSZItGWSqUQiURYcD0JM2rbRAJKURRWiJZEUjKZZKKISmVQ/BkvxvgYMLH0BQ9fLoNvuA6oM1X5uDNxHT7jVCKRSCQSyYlDSeJs//79x2oczJUYiUTYY+p9SZahRCLBBBm5P/nG34FAAIlEAolEAm63m5XAyOVyiMVirGBtOBxmiQaJRIJZnXjrH4knSkSgFkqZTAZlZWXMiqbT6WC325kQMhgMqKqqYskG5DYlCxxfUJYvFSJaucTyIYBajNFzEma0bXIP86VDJBKJRCKRnDiUdPVuamo6VuMAMFYUljIgI5EIC6jnBQ3fq5IsZuRyJFFC5SzS6TT6+voQi8WYZSkWizFRV1FRgdHRUWYto4xMqvZPmZZutxuBQIAlG6TTabhcLjidTlRWVrIyG4lEAkajEblcDslkEg6HA1arlWVzAodKXJD7EoCq9RI1XBeTE+h9ZEUk6yJwyBVKz8nidrgWTIlEIpFIJJPHYZlW2tvb8be//Q0dHR3Q6XRoaWnBxRdfjClTphzxgPgiq7xVS4TvVUliiy87Qa5IEnwAWK/KsrIylJWVAcC4xud8xiQf18W3TKIaaiTeSITZbDYkk0m4XC6W/UnN16kGGu/i5JMF+OxMMV6Md13y4o4vNms2m1n8GVnPZEKARCKRSCQnHiWLs+9///v4xje+gVwuB7/fD0VRMDg4iNtuuw2rVq3Cl7/85SMeFFmK+Bgtsc8mDyUL8H0xedcoX9CVb20Uj8dVwfPkquRjzagUhtvthsViUbVnAsBqihkMBjidTtYlgGLl+IxMEmc0NtoPWcNoOblBeYFFr5H44kUYZZDSZ0bvEeuqSSQSiUQiOf4pSZytW7cO/+///T98/etfxxe+8AVmfRoZGcH999+P2267DQsWLMCSJUuOaFBinBVZlPjXeGsauSvJ6iRamqgHpcFggMViYdYqihOjIH4qREvbobg2p9OJiooKAGDWOPqLx+Nwu92IxWLI5XLwer3MpUjN0kkcUimNVCqFZDIJk8nEisWS6zMWizG3rMViQTweZ8dI2azJZBLRaBTAoebsLpeLxdjF43HY7XZVDJ1EIpFIJJITA51SQo+fyy+/HF6vFw8++KDm69dffz3C4TD+8Ic/FNxOKBSCx+MpPDCNYqskuAq9h/8PQGVl0ul0KC8vx4wZM1BdXY2qqipUVFTA4XCw2DIALH6svLycZV42Nzcz65bBYIDD4WDxZVarlVnJqDCtXq9HLBZjhXIpTiwSiSAQCDBXq6IoiMfjrEZaOByG1+tlVr7R0VEmuih2js/GpC4J9H4Sex6PB6Ojo1i6dCmCweAR16GTSCQSiUTy7lCS5Wzjxo1YvXp13tevuuoqXH311Uc8KJ5CYoy3qIkZj3w8FwXP6/V6Vh+trKwM5eXlTJg5nU74fD623WQyiYqKChac73K5VI3F7XY7q5VGSQLpdBrhcFjV75NEmU6nQyKRQDQaRTAYZNX+aV/0fsoKJetbJBJRiTPebUm10Khlldh9IBgMHtXvQiKRSCQSybGnJHHW39+P5ubmvK+3tLSoCtQeCaLbMt/r+dbj47HMZjNLHvB6vXC73SgrK0NVVRWy2SwrO+H1eploymaz8Pl8LJOSOg3odDqEQiHE43Gk02kAYC7JXC6H4eFhtn5FRYUqDiwcDiMQCCAQCLAWVQCYO5NcpUNDQ6q4O/pPtdgSiQQrpEt/NpuNxdJR9ujw8PBR+S4kEolEIpG8e5QkzhKJhKoFkYjJZDomQej5Cq3yDcCpHAatR+5Iq9UKp9MJt9sNl8uF6upqNDU1oaKiApWVlTAYDKxOWnV1NYtpS6fTcDqdLCh///79iEQiiMfj40pU+P1+VoojFovB4XCwxIBYLIZYLIahoSFWYoO6EZhMJiiKgqGhIWaRSyaT6OnpYaIsm80ywZhIJFhMWTgcZsdNmZpUToM+B4pLk0gkEolEcuJQcrbmr3/9azidTs3XjmUAOsWOiRXy+b6YlElpsVhYOQuXywWbzYby8nLWI5PixShBIJvNIhQKsQD9ZDKJwcFBZo1SFAXDw8NIp9PIZrMsWN9sNsPhcLAOAYqisNiueDyOUCjExm61WjEyMoJQKIRwOMy2lc1mWVeEVCqFQCCASCTCrH7UXopi0+LxOKLRKEKhEMtm5ZMgSKzyyQQSiUQikUhOHEoSZ42NjfjVr3414TpHEzGOjO8tyVvNXC4Xq0PmdDpRXl4Op9MJr9cLq9UKn88Hr9fLquZTwD1ZnGKxGCt7EYlEsH//fhbYT22eaF8kwCjmi7cWejwepFIppFIpRKNRVqrDYrGw/QSDQYTDYcTjcSQSCRYPF4vFMDAwwAL9ySrG9wSNRqOIxWIIhUJIpVKsLhzVe6MYNxKNEolEIpFITixKEmcdHR3HaBhqqMQFbxmjOC4qNksWMuqhScH7JGqam5tZML/b7WZdBBKJBGw2GxRFQTAYZLFjlOlImZo9PT3M9eh2u+H3+5l1jo8XIxcjNVEPBALwer3weDyw2WwIBoOsp2c8HmflN3p6ehAOhxGLxQAAgUCAdSegfqCUEBCNRlnCQDKZVLV24t28fB00vhabRCKRSCSSE4eS3Zq5XA4PP/ww/vKXv7AOAVOmTMEll1yCq666alz5i5IH9P9bi8gCZLPZmAvSarWqGox7PB4mzmpra5kViSxpTqcTNpuNiZlcLsdKeITDYXR3d2NkZISJsnQ6rRo/FaAlCxy9RjXKFEVBNBrF8PAwK0RLyQTkhiRRNjAwgP7+fgwPD2NgYAC7du1iwpDqsJEVDwAbDwk7fox8BwDelUnj413AEolEIpFITixKEmeKomDFihVYu3YtTj75ZJx00klQFAU7d+7EypUr8Ze//AWPP/74YQ+GrGMWi4W56dxut8pSls1mWePzsrIy1kqprKwM8Xh8XJkJspaRZcxkMiEejyMQCGB4eFgV/8V3JADAenXy5Tr4orH0PipAS+OizEoSVJFIBCMjI+jt7UV/fz/6+vrQ2dnJ3k+10/gOAbwVjT57sooBUNVJo/9aiRMSiUQikUhOLEoSZw8//DBefvllvPDCC3j/+9+veu2f//wnLr74Yvz2t7897Fpner2eZVlShqXP54PFYmHWslQqxTIhy8rKYDQaWUNyk8nEenKSlYnivyg+KxQKYXBwEIFAAIODgzAajazqP1muKL7L6XSyRuRUM4zEE3UkUBQF6XQaBoMBRqMRFRUVrJWSyWRCMBhEMBhENBpFf38/Ojs7cfDgQQwPDzPrFvXg5F2UvBDj0bKGkfWMX19azSQSiUQiOTEpqUPABRdcgHPOOQe33Xab5uurVq3Cv/71LzzzzDMFt6PVIcBkMqG8vBytra2YNm2aqtURQTXLeBceuTwplouEGMV82e12pFIplikZCoUwPDzMBBxf5JWsXWSFcjgccLvdqKysxNSpU1FZWQmPx8PKVZAg83q9cDgcrIRGeXk5XC4XotEo+vr60NPTgx07duDll18eZ62jwrFieQ5eqPHPCyGWFwHGSoLIDgESiUQikZw4lGQ5e+utt3DXXXflfX358uX48Y9/fFgDoQxFm80Gh8MBAMyaxf9lMhmWrUmPqS1SMplUWczIHUrFX6mMRSQSYfFpVHVfdGkCh+K+stksy/Sk2DcAzH1IY6AxhcNhlq3Z19eHrq4u7NmzBwMDA4hEIkxw8k3NeSZ6PhHkApVIJBKJRHLiUZI4GxkZQVVVVd7Xq6qqMDo6elgD4a09iUSCtTICwMRTJpNhpSl4cUZV+wGwuK1wOMzE08DAAMuMJMEnxnBpQZa1TCaDoaEh2Gw2lvXJj5v2Q27RaDTK6pd1dHRg7969eOutt5grk38vjTkfhyPMAEhxJpFIJBLJCUpJ4oyC8fNBbYwOh3g8jq6uLkSjUWzdupXFklGAPcVnkQhKp9NMpAFgVjUKwqegfAqoF8nXRJ3vx0nvpWB/ao5OmaLk9qS2TsCYmzWRSCAQCKC9vR3btm1DZ2cnhoaG8saETdTQvVhEV6hEIpFIJJITj5KzNVeuXAmLxaL5+pEWPSU3IxVlNRqNCIVC4+p6aZWKILcnbxHLZz3KJ1745bxYojpoNAbKKKX2ULxA7O7uxvDwMIaGhrBjxw50d3cjFAqpgvbFvqBHW0zJTE2JRCKRSE5cShJn11xzzYTrHG6mJkH9IfV6PSu8CqjdnryoIbFTSJDw7Z603i8ibq+QxYvcqtlsFqlUCv39/RgYGMDAwAC6urpYEVq+YGyh7UskEolEInlvU5I4e+ihh47VOAAcipPiC7kSiqKMy2gsFtFSVWg9PuOR0Ov1rPsAtVkiseVwOJDL5RAKhdDf34/9+/djcHAQw8PDGB0dVblVD3f8EolEIpFI3juU3CHgWDPZgeyiVUun07E4M2pM3tzczFy73d3dyGazCIfDGBoawsjICOsEEIvFmMiUwkwikUgkEkkxHHfi7HiA3JW5XI7186SEAz4xIZPJsBIewWAQAwMDGB4eRigUQiQSYa2WJBKJRCKRSIpFijMBEmbU+slqtcJutyORSLCsTaqnlslkEI1GEQwGMTQ0hIMHD6KzsxPRaJStL5FIJBKJRFIKUpxBXVmfymjY7XaYTCZYrVa43W60tLTA6XSyMh5UqmN0dBQ7duzA4OAghoaGEA6HmYVNIpFIJBKJpFSkOBMwGAwwm82w2WxwOp1wOp2srRSf3Uk9MykzMxAIsG4DUphJJBKJRCI5XN7z4kysbWY2m2G32+F0OlFVVQW3242ysjI0NTUhnU4jEokgGo1ieHgYAwMD6O7uxsjICKLRKOs+cKRjkXFqEolEIpG8d3nPizMem82GqqoqVFRUwO/3o66uDna7HUajkfXiVBQF7e3t6OrqYsVm4/G4tJhJJBKJRCI5KrznxRlfoNZms6G8vBw1NTWoqKiA3W6HTqdDIpFAZ2cnstksYrEYurq60N/fj1AohFgshnQ6fUyFGW9RE7sJSCubRCKRSCT/WbynxRlfbFan08FqtcLlcsHtdsNutyOXyyGbzbJemalUCvF4HAMDAyphdqxqmIlCTKvNk3SFSiQSiUTyn8Wki7Oj1fT7cKG6ZQaDAQ6HAw6HA1arFclkEolEAul0mhWfDYVCCAaD6O/vZ9ayoyGOihFhWu8Ri+VKgSaRSCQSyYnPpIuzyYTvsUl/qVQKoVAIiUQCXq8XJpMJ0WgUo6OjGBoawvDwMBKJhKqn55GKItFdOVFDdN7aJwWZRCKRSCT/WbynxRnBC6xcLsfix1KpFFKpFILBIEZHRxEMBhGLxfI2MD/SMRRCS6jJ5ukSiUQikfzncVyKs3c7jopEFgkzij/j3Zg9PT2sVMa7bbHihZmWhU0KM4lEIpFI/nM47sSZlhB5N8RHLpfD6OgozGYzkskkfD4f2tvbMTo6inA4jGQy+a6LIXJ38m5OrX2Lgk26OyUSiUQiOXE5LsRZvoD4iUTJ0SaVSiEWi0Gv1yMSiSAYDCIejyOVSh1VF2Yp8PFoWqU0RIpJJpBIJBKJRHL8MunirJCYeLdEGY0hk8kgHo8jl8shkUggFoshlUodt8VlZRkNiUQikUj+8zguxFkhcUGvawmRYyHeotEoYrEYstksE2rift9ttCyI+eLQ+PUlEolEIpGceEy6OJvIVScKjYlcoIc7BhJjer0eOp2OFaAthWNp6SskwMSYMynOJBKJRCI5cZl0cSaiJXDeLfcmX0bjcClmrEfzeAoVsJUiTSKRSCSSEw/9ZA+ArFbZbHZcUVh6TOsV+jsemKh4rLje4WybED8jnU7HrH78a5LSefHFF1WfI/+3fv36ceu/+uqrOPvss2G321FdXY2bb74ZkUhk3HrJZBK33noramtrYbPZsHDhQjz33HNHbdyrVq3C448/ftS2J5lcNm3ahJtuugmzZ8+Gw+FAY2MjLrvsMuzZs0dz/Z07d+LCCy+E0+mEz+fDVVddhcHBwXHr5XI53HXXXWhpaYHVasXcuXPxhz/84aiN+2c/+xkefvjho7Y9yfHHsZojD4dXX30V3/zmNxEIBI7K9o4XJt1yxpd+yCe4jhfxNdmIsWf5ap7RnyypcWTcfPPNOP3001XL2traVM+3bt2Kc889FzNnzsR9992Hrq4u3HPPPWhvb8fatWtV665cuRJr1qzBF7/4RUydOhUPP/wwPvCBD2DdunU4++yzj3i8q1atwsc+9jFcfPHFR7wtyeRz55134pVXXsGll16KuXPnoq+vDw888ABOPfVUrF+/HnPmzGHrdnV1YcmSJfB4PFi1ahUikQjuuecebNu2DRs3boTZbGbrfu1rX8MPfvADfOYzn8Hpp5+Ov/3tb/jEJz4BnU6HK6644ojH/bOf/QwVFRVYuXLlEW9LcnxztOfIw+HVV1/Ft771LaxcuRJer/eIt3fcoEwCwWBQAaAAUHQ6naLX61WPdTode13+af/pdLoJ/ywWiwJACQaDk/E1n7CsW7dOAaA89thjE667fPlypaamRvUZ/+pXv1IAKM888wxbtmHDBgWAcvfdd7Nl8XhcaW1tVc4888yjMm6Hw6Fcc801R2VbksnnlVdeUZLJpGrZnj17FIvFolx55ZWq5Z/97GcVm82mHDhwgC177rnnFADKgw8+yJZ1dXUpJpNJufHGG9myXC6nLF68WKmvr1cymcwRj3v27NnK0qVLj3g7kuOXYzFHHi533323AkDZv3//EW/reGJSxFkgEJh0cfNe+CNxFggEJuNrPmHhJ55QKKSk02nN9YLBoGI0GpVbbrlFtTyZTCpOp1O57rrr2LJbbrlFMRgM44TyqlWrFADKwYMHC45pz549ykc/+lGlqqpKsVgsSl1dnXL55Zez71br++eFWldXl/KpT31K8fv9itlsVmbNmqX87//+r+Zx//GPf1Ruv/12paqqSrHb7cqKFSvGjW+i8UiOHaeeeqpy6qmnqpb5/X7l0ksvHbfutGnTlHPPPZc9/+lPf6oAUN5++23Vev/3f/+nAFBefvnlgvvu7e1VVq5cqdTV1Slms1mprq5WPvShD7ELY1NT07jzkBdqo6Ojyhe+8AWlvr5eMZvNSmtrq/KDH/xAyWazbJ39+/ezG5n77rtPaWxsVKxWq7JkyRJl27ZtJY1Hcmw4FnNkPn784x8rs2bNUmw2m+L1epX58+crv//97xVFUZQ77rhDc+7jv//Vq1crp556qmK1WpWysjLl8ssvHzefLV26VJk9e7ayefNm5cwzz1SsVqvS3Nys/PznPy9pPEeTSXFrhsPhydjte45kMglg7PP2eDyTPJoTj0996lOIRCIwGAxYvHgx7r77bpx22mns9W3btiGTyaiWAYDZbMa8efOwZcsWtmzLli2YNm0a3G63at0FCxYAGDP9NzQ0aI4jlUph2bJlSCaT+PznP4/q6mp0d3fjySefRCAQgMfjwerVq/HpT38aCxYswPXXXw8AaG1tBQD09/fjjDPOgE6nw0033YTKykqsXbsW1113HUKhEL74xS+q9ve9730POp0Ot956KwYGBnD//ffjvPPOw9atW2Gz2Yoaj+TYoCgK+vv7MXv2bLasu7sbAwMD485DYOz8+sc//sGeb9myBQ6HAzNnzhy3Hr1eyMV+ySWX4O2338bnP/95NDc3Y2BgAM899xwOHjyI5uZm3H///fj85z8Pp9OJr33tawCAqqoqAEAsFsPSpUvR3d2NG264AY2NjXj11Vdx++23o7e3F/fff79qX7/97W8RDodx4403IpFI4Ec/+hHOOeccbNu2jW1zovFIji1Hc47U4le/+hVuvvlmfOxjH8MXvvAFJBIJvPXWW9iwYQM+8YlP4KMf/Sj27NmDP/zhD/jhD3+IiooKAEBlZSWAsbns61//Oi677DJ8+tOfxuDgIH7yk59gyZIl2LJli8oNOjo6ig984AO47LLL8PGPfxyPPvooPvvZz8JsNuPaa68tajxHlaMu94ogm80qnZ2dSiAQUILBIFPhP/vZz5RgMKj6o9cefPDBca/dfPPNCgBlYGBACQaDyrJly5Tm5uZx6/X29ioAlC996Uslb1Pr77Of/azidruVkZGRvOs88sgjCgDlySefVC3v7u5WPB6Pcs0116iWt7e3j1v+iU98QgGg3HDDDWxZIBBQli1bppjNZmXfvn0FxxMIBJTOzk7VXalkYl555RXlkksuUf73f/9X+dvf/qZ8//vfV8rLyxWr1aq88cYbbL3HHntMAaC89NJL47Zx6aWXKtXV1ez57NmzlXPOOWfcem+//bYCQPnFL36RdzxbtmwpyoWQz6153XXXKTU1NcrQ0JBq+RVXXKF4PB4lFospinLobriurk4JhUJsvUcffVQBoPzoRz8qaTySo8/q1asVACqr56ZNmxQAym9/+9tx699yyy0KACWRSCiKoigXXXSRMmXKlHHrRaNRBYBy22235d336Ogos2gVIp9b8zvf+Y7icDiUPXv2qJbfdtttisFgYNYMspzZbDalq6uLrUehAV/60pdKGo/k6HMs5kgtPvzhDyuzZ88uuE4+t2ZHR4diMBiU733ve6rl27ZtU4xGo2r50qVLFQDKvffey5Ylk0ll3rx5it/vV1KpVNHjOVpMSramXq9HfX09PB4P3G43nE4nAMBms8Htdqv+DAYDAMDr9Y57je7QTSYT3G430um05jb8fj+AsSylUrep9ef3+xGNRrFhw4a869jtdgCAw+FQLd+wYQOCwSCuueYapFIp9uf1erFw4UK88sorbF2TyQQA+O///m/V+L74xS8ilUqx/ecbj8fjQX19PfT6SU/KPaFYtGgR1qxZg2uvvRYf+tCHcNttt2H9+vXQ6XS4/fbb2XrxeBwAYLFYxm3DarWy12ndfOvx29KCzslnnnkGsVispGNRFAV//vOfsWLFCiiKgqGhIfa3bNkyBINBvPHGG6r3XH311XC5XOz5xz72MdTU1DALzJGMR3L47Nq1CzfeeCPOPPNMXHPNNWz5ROchv86RnIc2mw1msxkvvvgiRkdHSx7/Y489hsWLF6OsrEx1Hp533nnIZrN46aWXVOtffPHFqKurY88XLFiAhQsXsvPwSMcjOXyOxRyphdfrRVdXFzZt2lTyGP/yl78gl8vhsssuU51v1dXVmDp1KtatW6da32g04oYbbmDPzWYzbrjhBgwMDOD1118/4vGUynF/1bbZbAAOueh4EomEah2bzVb0esVuU4vPfe5zmDZtGpYvX476+npce+21ePrpp4s6nvb2dgDAOeecg8rKStXfs88+i4GBAdX6er0eU6ZMUS2bNm0aAKCjo+OIxyMpjra2Nnz4wx/GunXrWHHiic4j/hwq9tzUoqWlBf/93/+NX//616ioqMCyZcvw05/+FMFgcMJxDw4OIhAI4Je//OW48+1Tn/oUAIw756ZOnap6rtPp0NbWxs63IxmP5PDo6+vDRRddBI/HgzVr1rAbTODYzJFaWCwW3HnnnVi7di2qqqqwZMkS3HXXXejr6yvqGNrb2/H000+POw/PO+88ABOfh8DY3Efn4ZGOR3J0OdI5Uotbb70VTqcTCxYswNSpU3HjjTfilVdeKWo87e3tUBQFU6dOHXfO7dy5c9z5VltbC4fDoVomXmuPZDylMumlNCaipqYGANDb2zvutd7eXvh8PqbKa2pqsG7dunFlJui9tbW1JW9TC7/fj61bt+KZZ57B2rVrsXbtWjz00EO4+uqr8cgjjxQ8Hipyu3r1alRXV4973Wgs/Ss5kvFIiqehoQGpVArRaBRut3vC84jON2DsnOvu7tZcD4BqXS3uvfderFy5En/729/w7LPP4uabb8b3v/99rF+/HvX19XnfR+fbJz/5SZW1hWfu3LkF9300xyMpnWAwiOXLlyMQCODll18ed64cizkyH1/84hexYsUKPP7443jmmWfw9a9/Hd///vfxz3/+E6ecckrB9+ZyOZx//vn4yle+ovk6XQhL4UjGIzn6HMkcqcXMmTOxe/duPPnkk3j66afx5z//GT/72c/wjW98A9/61rcKvjeXy0Gn02Ht2rWqmxmCPHalcCTjKZl3xXk6ARQz8dBDD2m+XllZmTcTiY/jeeCBBzQzkX7/+9+P83sXu81iyGazyg033KAAUNrb2xVFUZQ1a9YoAJR169ap1qX4nWJSiK+55hoFgLJ7927V8rVr1yoAlD/84Q9Fj0dy5FxyySWK1WplMXyBQKBgJtK1117Lln35y1/WzNb83ve+V1S2psgrr7yiAFC+9rWvsWVOp3NczFkmk1FcLpfy8Y9/fMJtUszZ7bffrlqey+WUmpoaZdmyZSWNR3LkxONxZfHixYrdbldeffXVvOsdizmyGPbs2aPY7XZVaY85c+ZoxpzNmjWrqLIxFHOmdc4uXLhQmT59eknjkbx7HMkcWQzJZFK56KKLFIPBoMTjcUVRFOWee+7RjDm76667NK+fWixdulQxGo1KJBJRLf/5z3+uAFBee+21osdztDju3ZrAWEbOk08+ic7OTrbshRdewJ49e3DppZeyZR/+8IdhMpnws5/9jC1TFAW/+MUvUFdXh0WLFpW8TS2Gh4dVz/V6PbM+kPmWzKNi1eJly5bB7XZj1apVSKfT47atVdH7gQceUB3PAw88AJPJhHPPPbfo8UiKR+s7ePPNN/HEE0/gggsuYDF8Ho8H5513Hn73u9+pMpBXr16NSCSiOo8+9rGPIZvN4pe//CVblkwm8dBDD2HhwoV5MzUBIBQKIZPJqJaddNJJ0Ov1qu/X4XCMO98MBgMuueQS/PnPf8b27duLOlbKkiPWrFmD3t5eLF++vKTxSI6MbDaLyy+/HK+99hoee+wxnHnmmXnXPRZzpEgsFmPuT6K1tRUul2vC8xAALrvsMrz22mt45plnxr0WCATGnVOPP/64ytq8ceNGbNiwgZ2HxY5HcvQ5FnOkFuK1zWw2Y9asWVAUhV0/811rP/rRj8JgMOBb3/rWuGLsiqKM23Ymk8GDDz7InqdSKTz44IOorKzE/Pnzix7P0WJS3ZoPPPAAAoEAenp6AAB///vf0dXVBQD4/Oc/zwKPv/rVr+Kxxx7D+9//fnzhC19AJBLB3XffjZNOOonFzQBAfX09vvjFL+Luu+9GOp3G6aefjscffxwvv/wyfv/736tMm8VuU4tPf/rTGBkZwTnnnIP6+nocOHAAP/nJTzBv3jyWoj5v3jwYDAbceeedCAaDsFgsOOecc+D3+/Hzn/8cV111FU499VRcccUVqKysxMGDB/HUU0/hrLPOUokxq9WKp59+Gtdccw0WLlyItWvX4qmnnsJXv/pVli5czHgkxXP55ZfDZrNh0aJF8Pv92LFjB375y1/CbrfjBz/4gWrd733ve1i0aBGWLl2K66+/Hl1dXbj33ntxwQUX4MILL2TrLVy4EJdeeiluv/12DAwMoK2tDY888gg6Ojrwv//7vwXH889//hM33XQTLr30UkybNg2ZTAarV69mwouYP38+nn/+edx3332ora1FS0sLFi5ciB/84AdYt24dFi5ciM985jOYNWsWRkZG8MYbb+D555/HyMiIan8+nw9nn302PvWpT6G/vx/3338/2tra8JnPfKak8UiOjP/5n//BE088gRUrVmBkZAS/+93vVK9/8pOfZI+PxRwpsmfPHpx77rm47LLLMGvWLBiNRvz1r39Ff3+/qrPA/Pnz8fOf/xzf/e530dbWBr/fj3POOQe33HILnnjiCXzwgx/EypUrMX/+fESjUWzbtg1r1qxBR0cHK4UAjMUwnX322fjsZz+LZDKJ+++/H+Xl5cwtWux4JEefYzFHanHBBReguroaZ511FqqqqrBz50488MADuOiii1jSEgmnr33ta7jiiitgMpmwYsUKtLa24rvf/S5uv/12dHR04OKLL4bL5cL+/fvx17/+Fddffz2+/OUvs33V1tbizjvvREdHB6ZNm4Y//elP2Lp1K375y1+y5LxixnPUOKp2uBLRKlhIf6KJcvv27coFF1yg2O12xev1KldeeaXS19c3bpvZbFZZtWqV0tTUpJjNZmX27NnK7373O839F7tNkTVr1igXXHABK+jZ2Nio3HDDDUpvb69qvV/96lfKlClTFIPBMM7FuW7dOmXZsmWKx+NRrFar0traqqxcuVLZvHkzW+eaa65RHA6HsnfvXjbOqqoq5Y477lCVxyh2PJLi+NGPfqQsWLBA8fl8itFoVGpqapRPfvKTeV3EL7/8srJo0SLFarUqlZWVyo033qgqRUHE43Hly1/+slJdXa1YLBbl9NNPV55++ukJx7Nv3z7l2muvVVpbWxWr1ar4fD7l/e9/v/L888+r1tu1a5eyZMkSxWazjStC29/fr9x4441KQ0ODYjKZlOrqauXcc89VfvnLX7J1yK35hz/8Qbn99tsVv9+v2Gw25aKLLlJVni92PJIjg9L78/2JHIs5kmdoaEi58cYblRkzZigOh0PxeDzKwoULlUcffVS1Xl9fn3LRRRcpLpdrXBHacDis3H777UpbW5tiNpuViooKZdGiRco999zDyhXwRWjvvfdepaGhQbFYLMrixYuVN998s+TxSI4+x2qOFHnwwQeVJUuWKOXl5YrFYlFaW1uVW265ZVx4yHe+8x2lrq6OdRvi9cOf//xn5eyzz1YcDoficDiUGTNmKDfeeKPK3alVhLapqUl54IEHDms8RwOdosjmi8cr1IvxaDWIlUgK8eKLL+L9738/HnvsMXzsYx+b7OFI3qN0dHSgpaUFd999t8qyIZEcK973vvdhaGhIM/RjsjghYs4kEolEIpFI3itIcSaRSCQSiURyHCHFmUQikUgkEslxhIw5k0gkEolEIjmOkJYziUQikUgkkuMIKc4kEolEIpFIjiOkOJNIJBKJRCI5jpiUDgG5XA49PT1wuVyq5ruSo4uiKAiHw6itrWXtNCQSiUQikRzfTIo46+npKdhLUHJ06ezsRH19/WQP47ijoqICer0eOp0OuVyO/QFg/ylfxmAwQKfTQafTQVEUtpyW0br0mH+/oijIZDLscS6XG7cN+s+3z9HpdDAajTCZTDCbzayFCH9DQ9tLp9PIZrOq4+CPhz8WHn7f/H+j0ciOjd+G1nvFsdD/XC4Hk8kEi8WCgYGBvN/Dex2dTgePxwO73Y7e3l7MmTMHAFhBTL/fj5NOOgnr1q1DY2Mj7HY7du3ahbq6OoRCIQSDQfj9ftjtdhiNRgSDQVRVVSGTyWDXrl2wWCyoq6tDU1MT1q1bV9SYvvKVr2DNmjXYt28fXC4XvF4vbDYbrFYrvF4vgsEgIpEI6uvrYTabkcvlEAwGsXnzZraNJUuW4K233mI9D30+H5xOJ4aHh5FMJlkvzTlz5rBjra2tZe38AGD58uUwmUwIBoPYs2cPent7AYz1KKYenTabDXa7nf12UqkU6urqUFtbi+nTp2Pjxo2IxWJQFOW4KjJ6vCHOAfR50vek1+uh1+uRzWZV8xzNiaXsp9j1jUajqucqb2SguUlRlHHGB37O4ven1+vzzmcTjYP2oXB9NMXx0T74z1Cv18NkMiGZTLJ9F9OHc1LEGfWgamxshMlkYhevQohfSj74L128MNFr+S5S/IWWTkR6zC/Pt21xu/zziU7GUi2I4vr8CUhj0ev1bHKVaCN+78DYd5vNZlXfay6XUwk5AOwzFsUZP2nQchJnAJiI0hqHuJy2Qz/yfIIok8kgm81qCjR+Xa3jB9S/LzpmrWMRxysiijMStZLCBINB1qw7FovBZDLB4XAgGo1iYGAAO3bsQC6Xg9FoRH19PaLRKKLRKILBIABgdHQUfr8flZWVeOedd9Da2sourhaLBbW1tZg1a1bR4iwYDLILSDgcRjgchtlsxtSpU5HJZODz+VBbWwuv1wuLxYJMJgOdTgefz8d6tXZ1dbHxAUA8Hofb7UY0GkVVVRX6+/sBqM9Lt9uNSCSCUCgEYOy8TKfTGB0dZcIMAOx2O3tcV1eHd955Bx6PBxUVFSgrK0MgEMDg4CBaW1tRWVmJQCCgGoskP+KcaDAYVPOhuA7NFfycodPpkM1m2bxCj+kvlUoVPRYe2gfNhfRfvGGl8WrNp/SebDY7bl+8iKP16Tm9Tu+jm2d6bjQa2fb5cen1ehgMBvZXLJNSSiMUCsHj8aCtrQ1WqxXAoQ9BayI/mpN7MYfL70/ry9faJm0338Uw337FuxXap7itYuCFBN3R7N69G8FgEG63u6RtvRdobGxkPx66A6LPMJ1Os8+RxBE/6fA/Yv4uUnzOw7+fF2i8uBOtagaDAUajEVarFWazWbVdugukCYO2qWWlo+2L8OefeMfHjyvfNngBy++PxmMymWCz2TA4OHh4X9J7AP4zv/TSS7Fjxw5Eo1FYLBbs2LFDta7FYkFLSwsSiQR6enrYRW7KlCnQ6/VM4DkcDtTU1LDG9waDATfddBN++tOfYsqUKWhubkZZWRn+9Kc/sW3PmzcPuVwO+/bt02wZZzAY0NDQALfbDb1eD0VRMDAwgBkzZsBoNGLjxo1MOHZ1dbEbbro5DIfDbFtnnXUW+vv78c4778BkMqksCY2Njejt7UU6nYbf78fo6CjS6TTOOussvPLKKxN+nqeddhra29vhcDhwySWX4Ne//jXi8TgcDodshVcAfi4gayh/XROtUVrzg9b1DBibq0jAG41GpNPpcUKOX1fcrjhOrWuyeJPMC6mJjllrP3SO0/zPP+avAfmOg+ZrEmfJZJLd0BcjTifFckY4HA7YbLbDNjUSh2uV4i9GouVJfG+hL7EYax29pmUBpAsjPS5GjIrCT7SWpFIpabGYALqLMRqNcDgc7Mej0+mYwCGRwd8lGgwGTWEFQHVHx/9Qxe+Vd4/yd2WiyCHhSGPlrXb8GPht0O+JF5f5xBV/d8ffiIjuVSLfecdbv8UJcRLu/05IstksysvLkUqlkEgkYLPZ0NjYyD7n7u5u2O12KIoCv9+PkZERpNNpKIqCWCwGh8MBg8GAjo4OAMC+ffuwcOFCtu3Vq1dj4cKFqKurg8lkwl/+8hdUVlYiHo8jEomgs7MTw8PDAIAFCxago6NjnDu6vr4eTqcTXV1d6OnpgcFgwFtvvYXy8nJcddVVeOCBBwCMuSczmQwGBgYQDodhsVhU21m/fj07T9LpNLsORKNRZDIZVFZWoqenB42NjWwMr7zyCqZNmwa73Y6tW7di2bJlyGaz2LNnD5LJJKxWKywWC0ZGRhCLxRCNRrF27VomzM4///xj9t39J5FPqPBzlJYIE+cG/rnoEix0E8u/dyJtIO5TvIGeyIU60Wvi8dFvkW5eC13TCX4Opvm8GCZVnBmNRlgsFnYxBA5dMLUsUSKFLFPihZAQP0gtk+jhfpnieAttS/wS+QujlqtJa/v8Pnh3ViaTke6kIiBBQuch/4MWYysIXgBN9N3y++GX0/Z56xhB3yX/w+cnMV7AieeL1rlMk5vofuDX5wWZ1rmXbwz8evl+pxP9niRAU1MTDhw4AGAsXopc1MAh9x3Nj4FAgJ0v5Pqj10dGRlSWofLycmZJA8a+i+HhYWa9iMfj41zWbrcbqVQKbrd7nAtGp9OhrKwMPT096O/vx8jICLxeLwKBAJLJJCoqKti6LS0tcLlc2LJlC/r7+8dZCkQBn8lkYLPZAIDFKup0Ova5EC6XC263G5WVlQgGg9Dr9SgrK0NjYyPzDjz99NMoLy9HNpvFvn372P5EgSgpHVHs8PMRj5aBQySfeBLfm09g8TecWi5Jfm473Hkon8GmkIWQnytF62Ip45hUcUaTBKC2PBRywxDFrEP7ILTEjngxEgPBxf3x62htk1f6hcSROC4tYZbvYsuPQevkK8YVKwETZmazGWazGdlsll0ExbumfCJE6weXb3LJdwPBu0zJYscLMxJqtG3+Ry8KPS3rnNZ/fmy85U2cdLQsfqJI5C19hzMJvdeZN28eXC4XQqEQurq6mAU3k8kgk8mgp6cHsVgMwNj3PzQ0hKGhIdU2crkcRkdHAQDV1dVYunQpampqEI1G2ToXXHCByo3Z2tqKvXv3Ahj7XisrKzFz5kw0Nzfjhz/84bhx6vV6eL1e/P3vf2fLaFyRSAS9vb2YNWsWKioqsGDBAkSjUSSTSZhMJnR1dam2ZbFYVMKRwgiIeDwORVGYO9zj8WDx4sXYtm0bdu3aBY/Hg/Xr1wMAzjjjDMyfPx9OpxPhcBjDw8P44Ac/CAB48sknAQCJRAK7d++e+Mt4DyO6MkXE37aWN0mc+3iLGyEG0Yuv8+/TikXn5zLxMcHHi/NehsMVaPy1lXd3AmA303xcsDgf8zfc/HlfiEkVZ2Ti5GOkREEhXiTF1/LdsYvB01rB1KIQosdiBkoh82ixlj1+f1rjzGcxE0/8QiZgSWmQlREYm7zJYkFuYT7OghcxAMYlDIg/VIL/IfMuT35ioZgEulnJZDKqwFIaKy/a+DHxr9M6Wu5MUWSJ4oyfXER3Am+h5YNtKXmCT6IolDEqGc/o6CiLq5o3bx6am5vR0dGBl19+WWUJW7RoETKZDPR6PRoaGrB27Vr2OgXhA0BfXx/WrFkDp9PJbn6nTJkCn8+H8vJyOBwO2O12lTWrpqYGo6OjeOutt7Bv3z7U1NQgEAggHo8DGMuITKVSWL16NS677DJs3boVe/bsYduwWq145JFHkEgkAAAbNmzIexG68MIL8fTTT7PnFHNG1jSLxQKr1Yp4PI5rr70WmzZtwvr16/HOO+8gl8vB6XSq5sjt27fjzDPPxO9+9zu88847AMYskBTH5vf7EQ6HsXXr1sP4dt47UCiMlnWMD4IXr6X5BB3vBch38yjOb6KlSXwvP5/x8yj/Xj4erJDYnAj+emwymVRzHD8e/gaav3nV0hATxcDxTKo4A9QXSADj/LH5hBkdeCGfdL4TQkuk8cso+I/GJ56shdJ2+f0WQsu9Ssu1BOpE+zmSk/C9Cn2emUwGkUhk3IQg/si0RBePaM0VLV6iwOO3xVuR6Zwmlz/dxFBArdYNy0SWq3wWsXzijP5oMtESXOKf1v7lzcPEvPHGGwDGPuN77rkHdXV1cDgcaGxsVCUEHDx4EBaLBTabDcFgEG1tbejr60NfX9+4oHq9Xo9IJIJsNoumpibodDo8/vjjGB4exsjICOrr6+FwOOBwOJiFbmBgAIFAAG1tbTj99NOZwFq0aBFcLhc6Ozuxfft2bNy4UZXg0dbWhoqKCgwMDKCrqwupVEpTmJnNZhiNRpUwA8aXFWhubobT6UQgEIDf74ff74fb7UYikUBXVxc7nyibNRKJYOvWrapszOHhYRaruWDBArzzzjvYtWvXEXxL7w1obqG5htASbLRcy4ImbpPWBTBO6FGAPT+P8K/z8bei6BLHIYq7I4G/OebDrfLNrfmW02MxkWAiJl2cAeovr5CljL+o8aJJS6CJgXqElnVKfI1e57c9kQDM97zQcYgXzHyuTDoecT+iGOCtK4U+R8kYvCWILAD8ZEHrAOoMST7YP9+kJd7Z0Xv5bfBQmjWfmk0B3plMhrmPtM5D/s6WH4MWouuSJkD+T4QXYDSJalnI+HNPirPiETMIKaD/Qx/6EDo7O1mWI7kGPR4PIpEITjnlFHi9XkQiEcybNw+bNm1isV/pdJqJlba2NuzevZuVolAUBf39/Whra0NZWRkSiQSzkFH9sXnz5uHNN99k49DpdHjrrbewfft2Nj5gLCaura0NNTU1qKqqQjweV5W84DnrrLMwODiI7du3w2q1wu12IxQKMWsbMPbbaGlpYdaucDgMk8mEhoYGdgNFVFVVoa+vD7FYDBs3boTFYoHP50MoFMLAwAA8Hg8WLlyIU045BYqiSHFWAlrJRvxr+bxQQHHhSPQequNIcwvdhBJiliR/bcvn1aBl+cYhzsta8PMiv33aJz8OLXGWb34XE8UKMekxZ+IXL37IohuHEN2PYkyQ1kWG4GN8xJNKvHDx8KqeLkT8e/n/Wsea7zl/sokWmXwJBvz+6eLMXyRLMZ++V+FFMf/50Y+SHvPCg843XpyI5wJtk/ah0+lgMplUBQmtVqvqPOTPV7prtdvtbP8mkwnRaFSV9EF/vCgSEZeJ++N/B/wx8CKLL9Oh5dKcyFomxVnxrFy5Eg8//DCAsWxLj8eDyspKmM1mtLe3I5vNIhgMIhgMoqWlBYFAAJFIBP/+97/ZNsR4tBdeeIE9njFjBvr6+hAIBLBjxw7MmTMHdrsdu3fvxsKFC/H6669j9+7dOHjwIEKhEHK5HMrLy/HOO+/Abrfj0ksvxZo1a1BfX4+2tjaEw2E8/fTTMJlM+PSnP82E2ZVXXok//elPqgstX2MtkUggnU5jxYoVWLduHROSV111FUtsqKysxF133QWLxYKZM2fC6XTC5XIxsWq323HKKafAYDDgpZdeQjQaZeJOURTY7XaceeaZGBoaQjqdRlVV1dH9sv5DyeVyqptEQkuAad2E5oN/3WazwWKxwGw2w2KxsCzkUCiEWCyGRCKBVCqlWRMSGB/bzVv5eW2gJYYm2h5tk3+eTCYLeuDIMsYfKz/HTmTk0WJSxVmhO/VC4koL+qC0shTFi6D4mN8vUDgLVKSQKMtnuaLj0zrZtUSVloWMnvMXZlGYyVifiaHKz/zdoBg3pmUdLSR6+Dsp+tFSppjBYIDJZILJZILRaGR3jvTDjsViqh8+b6ni49HIoiauw9/N5TsnteIcxTtC/hi1Ctvms5Lxn4+0mhWPy+VCeXk5XnzxRbZs+/btqKyshNFoRCKRYL9rp9OJGTNmYHBwEJFIhBV2FWtFOZ1ORCIR1TzQ1NSEmpoa9Pf3Y8eOHZg+fToaGxtRV1eHaDSKU089FYFAgHUWaGpqgsFgwL59+9DX14dEIoHFixfj4MGDWL9+PaZPnw5gzDX50EMPsf38/ve/n/CYs9ksBgYGEAwG0dzcjKqqKjzyyCPMrUkxYlRaZNeuXfD5fMziRtX+Z8yYwYra5nI5zJo1C2+88QaGhoag1+vR2dmJPXv2sKK3ksJoGQi0rEOF5pmJMJlMcDqdcDqdrCafXq/HyMgIE2jRaBThcBjJZJIVsRUz6rU8SLzXo1gjBX9MdMz8cv51/vPQsjDylj5+Hiw19GjSLWeiuZAoRVhoiSBRtdIy8SIqZleIMWa8laDUsUzkVqSTrFgxKJ4w4knIn4zyolgc/A0C/8PiKUac0fv5bB5aRiZtep1ibygmxmKxMHFGxRnp/bx1THQJ8PXWxDGI4lIUbqJ7s5DYKiamrJAYk+fixFgsFhiNRhbQTgwODsJiscDpdLJlRqMRp556Kp599lmEQiGW6ckzbdo0eDwedHZ2qtohZTIZGI1Gtj2/3w+fz4fR0VEoigKHw4Hm5mZ0d3ezG4d0Oo3u7m50dXUhl8th3rx5OHDgAOLxuGpcvHuyGMxmM2vtVFdXh7q6OmzYsAFdXV2w2WzMQqbT6di2+RsZIhaLoaamBgMDA1AUBVarFYlEAqFQCO3t7RgaGmKZrJKJEa1GhX6/E4mzfDe55NI0m81wOp0oKytTdbRIJBKIRqMwGo3M9W0wGFhdP37bNK8dLfj5UDy+fPvRulnnlx/OjeqkizMRrQ9ay5ImijoxXovfhpblTER0pYqiTOsLEk2r/LbEuwrR9VWK+BTFm2g5E9fjL8SSwogB+/Q433fFCzhR9FDMGP+9i+ZuvV4Pm83G9pVOp2E2m9lkRReWdDqNeDzOskj5c1Gv1zNxx9/J0T7NZjOLnQPASoRoCSx+IqJjF88j/n2lCDXahmRitMpjECMjI1i8eDGLmQoEAsz1w2dpEpdddhkMBgP27t3LhBkJMt7FeeONN8JkMuGNN97AE088gauvvhrxeByDg4O44oorcOedd+Kdd95BX18f9u/fj+7ubhgMBoyOjsJoNKK5uRmLFy/G4sWL0dvbi7/85S8qkfjhD38YQ0NDGBwcZBfhjo4O9PX1oa2tDXa7HaFQCFarFdlslo01k8kwYUbu//7+fsyaNQupVGrcMTudTsyfPx9LlixBKpXC3//+d4yMjEBRFDz++OOYMWMGS6KQTAwfT0vw1iotA0C+m1WtG16dTodkMsm+4/LychZ3mUgkUFZWxua1hoYG7Nu3D4ODgyw2WEwG4JOZxLmMXtcapyjytCyBWlZCLS0ieiQAtY6gLOtSmPSEALHwZbGCgv8Atdw0WjE1op8YKFy3SsvFQ9uk/3xmJy3jLXVaF3Z+vxNZaQolIognonRjlobBYIDVamXuQlGc8UKEJ993B6hvGsQfKy+oaDupVIrFoVEhXHIjJhIJJBIJ9uMWxRlNRvw5qNPpmGWOzkOaGPhSIeKxiROSeFOR7zehdYOgJfAkhamtrYXdbsc777wDh8PB3D1U4+wPf/iDav2XX34ZfX19mtv6xz/+wdo5WSwWFmQdCATwkY98BCMjI4jH48yN1NnZiWw2i5deegmVlZVwuVx44oknmEXj61//usrNThfV0dFR/OxnP0NDQwPi8fg4610oFILZbIbf74fBYMD+/ftZtX/RQkg1y9xuNxYsWABFUdDe3o6DBw+irKwM5eXlLHPVZDKp3uvz+fDoo4/ilFNOQUtLC3p6etg5V11djfLycuRyubyfl0QNWeRFy7qijHcTFnLVFfrdk8hLJBIYHh5mCSmZTAZms5n9BmiZy+ViAi0ej6vKwPDjmmi+0RKLhcSY1jpaYS8k2kjEkrik94k6oRgmPeaMV52Huw1CS+SJYmyiD0hU5VrvERU3/1hcJnY80Dp5+OfFCCx5wTs68KZ1alpLywtZTOkHzv/n0Yql5IUf3xqKBBpBVi6+/h8fU0brFHsjw7vv+dg6rclF63k+a5gUYUePxsZG1NfXw2w245133mHunOnTp8NoNGLPnj2q9fV6Pcve1SISiUCnG6vmP3XqVHR2djKrUSaTgdVqhU6nQ1dXF6xWK1wuF7uw0E1APB5HMBhEJBKB2WxWnaMNDQ3o7e1lbZbIuiWW88jlcjhw4ACGh4exfPlydHR0aIaw8ITDYezYsQNGo5GV4xgdHWUXb2D8nL59+3aEw2Fs27YNw8PDqvNw5syZ2L59O3OfSgpTioGkWEQXH3CohFYymUQgEEAqlWKlhOLxOEwmE8xmMzs/AahuokUrvlaIBg/NT8WKJK1r9ESWQjFBQbx2lJqkN+nijMTL0fYZa4ky8QPNt46WaRQY3xlA/LLyWe749/DWDz4I+3COUV4MjwyyQFFwfiqV0hRbgLb45gUavUbfO00CWhmQZMLnM4zJZE/p5GR54zMi+f3y/0V4Mzq1waHfGv87EF20/PYnEmPiOCaypEnyQ2433vIUDAZhMBhQVlaGuro6dHd3AzjU0JysoKFQCJlMhtX8Ivx+P+rr6+Hz+RCJRJBOpxGLxbB161a43W6YTCbs27cPZ5xxBtra2lBVVYWenh5ks1kkk0nYbDaWefmpT31KFex/3nnnYdOmTdi+fTuuuOIK9Pf3I5lM4pxzzlF1Fshms6zsRlNTE3bs2AGXywWbzQan08lEJ398iqKoYuQIPp5NLKBLwouK+QJjF/JZs2ahublZlSUqyQ/vmhMNEFoCq5hrNn9N5OcLalOWSqXYn8VigclkQjAYZMLLYDDAbDbD5/OhtrZW1TM6mUwyq7BYH5Wvs8ffbGuNJx+lzlt8eInoKj2c6/WkuzVFPzYhngTFZHDSh5LNZscFjYqCS8vKpqW4+dcmElS8ZYLGy1/AxcwO2o54IRetgVpWDt4CQs9Fy8jRvgP6T8ZsNgMAmzC0BNFEnycJKa33UGC/KLb4TE7gUEIAb+kSoe+ctkdZm3QukzCjdHg6P7TEE22Pxisu03qcT7jxx631WKLNs88+izlz5qClpQXnn38+PB4POjo6NEVFNBpFf38/qqqqVG1wGhoaWExaW1sbnE4nLBYLGhsbsW3bNpx66qlYuHAh9u3bh7/+9a9sewcPHmSPv/SlL+G1115jLkZgLJ5r7969qK6uZm7BTZs2YXh4mFng/u///k8lDPV6PZYuXYp169bBbrdj1qxZ2LJlC5xOJ5qamhCPx1FdXY3+/n4Eg0FVrF19fT07d202G1wuF2pqauDxePDHP/4R9fX1aG5uxllnnYVf/vKXTEDabDZmXVuwYAE8Hg9SqRSee+45tu3KysrD/5LeA9A8wScwkYU/3/rinKhlMRKFCm+lBcaycaPRKLO+JhIJDA0NwWAwwGazoaKiAuXl5aitrcXMmTNRWVmJzs5ODA0NIRqNslZfYv9W8lyRtS1fXHo+44g474nzK93w8iEnPLzQPRwDzKS3b+JdN8B43yyvRCc6QP7Dn8iESPvQsmSJlKJ6C7kotS5a/H7p2PmTR7TA8cJM9H3z8U6SiaGYB3ItivFYhCiOCyURkEVD/A55Nyb90XnF3yDw4l/sGMDDCy5+4hBr7YguVD65QMslqfW/kGWM/4yklezwmDJlCuv9SCUwxJ6C1NIJGHP9+f1+Fr8FjDUa37t3L9LpNN555x2Mjo6ivLwcFRUV2LNnD3p6epBOp7Fhw4a84+CLvFJiSiQSQU9PD2pra1lAP5WwAMDqi/Hkcof6fDqdTtTW1mLfvn3Q6/VIJpMYHh5GT08Pi11raGhgMWhiD86qqips2bKFWULo/H7hhRdUxW5PPvlkjIyMIBgMwmq1YmRkBIlEQmVRmTNnTt5jl4x3x2ld9ya6Foqv83PhRHMIxduGQiFVzOzQ0BAymQyqq6tht9vh9/vZfEfZu1QXjYcXgDQ23kAijkMcuzhGMa6Ntk/7EOdffhuHMy9Oqjjjg5/5ZTzFxqLxH7xWggCRzxoykTDjL6T51uWtZeK+tJ6L++H/03FolUUgYcZbyrSsj5LCkCuRYrxomdg/jf/R8j9M/gfOZ+bkM2nnc/nRBEZ/vHgTXZLA+OxRPluJuhvwglAUZ6LA5MfDI465kEiTwuzwaWxsVFXw93q94zISm5ubMTo6ymLHxPZIVqsVdrudvT48PIzh4WHmOoxEIgWFGQB0dnYy9+GNN96Ie++9F8CYS7G6uhplZWWoqKhQWdb+9a9/aW6LYuLsdjsMBgMOHjwIv9+PTCYzLivV6XSOi2sjxNpkiUQC4XB43LF4vV44HA7W8WBwcBDJZJJZxI1GI1pbWwse/3sdLRGltU6pv/NSroMAmBWNXJrUtSIcDsPr9bLCtel0moWkBINBpNPpca3AxOQssnqVejOZb26cqDPLkcyJOmUSZtRQKASPx4MFCxbA4XAgHo9ruvR4xFIXWq/nc8UUI9ZEASQ+LmQRm2hsxZAv41Q8kfgCs/yFlqyP9Ho6nYZer8e2bdsQDAbhdrsPa1z/yTQ2NrI7Hb6WGIklPpief43/jvkfOL8eMF6cidvjxRi/P62bDMr05PfJx7fxVlPeWsZbysRitYUmTf51sSsAL0h5kae1TZ1OB5vNNs66IjlEseEH8+fPh06nQyAQUGU7zpkzR2XNmjJlCvbt26d6b0NDAxYtWoQ//elP8Hq9aGtrQygUQkdHB/x+Pz72sY/h/vvvBwCcffbZiEQiGBoagsViwWWXXYbvf//7AMYyJa+//nq8/vrrTKTNmzcP8+fPx2uvvYYVK1agvr4ebrcbjz76KAYHB3HgwAH09/dj3rx5cDgceOWVV1RuSEJMKKipqWGCta2tDalUirlhp02bhrKyMlitVgCHRKLD4UAymURzczNGRkYwMjKCj3/846ioqMDIyAh+97vfFfVZvxcp9jzUCoMoBdGoQNuiuY6Pl83lcqzV10knnQSr1Qqn04nKykq43W6MjIxgYGAAAwMD7MaUCjLTfDc6Osoy38PhsKrEUKmIN+uipUwMMaFjE8OXivnsJj0hgApxAoW/bD6maiK0TjLe2iGKtHwXllKFVr71892BaC0j0ygfd0Tb4K0ztD5vTdGycEjyw5fSoNpifI0frfOEXhPN4bQ9Wo+3yvLWV/ExndNad2H8BKYVhyh2w9ByW/JuVH5MIuJ4xeDWid6bD3keTkxlZSUsFgv0ej2Gh4dZtiTR2tqKlpYWNDQ04F//+hf27dunijfjhRkwJlyMRiP27dvH1hkeHsbzzz8PYCyAnmJ26Pzfv38/e/+rr76KXC4Ht9sNm82GX//61+y15cuXI5lMoqWlBW63G88//zxGRkbwwgsvoKOjA2azGZlMBl1dXQgEApgzZw6mT5+O/v5+VvEfAKZOnYr+/n6VZczr9aoaqvt8PlaotqOjA9OnT2cCrquri1lQbDYbew+1cAoEAkzorV27FsCYNU+Ks8Lwsa7ib5cXU8Veh7V++/wNnVa2Jb2PbjJTqRTC4TD27NkDr9eLqqoqlJeXQ6cby0gmsZZIJJBMJlnRWko0MJvNLHSlr6+PeUuSySSLyy3UkFzUJ1ohRoXmRv4mtxQmXZyJZS/yCbB8tcNERIuZFvksBIW2W+jiVOi9xV6YRGuZliVQSyxoqXBafrjlSd4rUNFYukHgTd5arkxA28LKfzdaP1RxkhItZfy2xHOTrGwkvHhBxm9Dq36ZaCkTx5TvDli0Foqfh9Z7pAA7fKxWKzweD4vP2rVrFxNnJ598Mnw+H6xWK3p7e1l9MpfLlbfqfV9fH5LJJCwWCxNniURCVX5jeHiYxVzSfGOxWJBMJtlcFgqFxtUuM5lMaG9vh9vthtfrRV1dHQupsNlsLJaMxq8oCrNu8ej1epWoKisrg8PhUImzmpoaAMDWrVuRyWQQjUbhdrsRiUQQi8XQ2dmJSCQCn8+n2nZZWZnKdSrLaBSPeNMIjK9EUMpvvRQ3qHizSvsnkUbnBmU2m81m2Gw22O12dlOQSqVY27JkMolkMsnc5RTuEYvFkEwmkUgkmKUunU6zbH1+7iQLHj+/5rtpp2PgOZKb00nvEKB1IRPdhKLI0BId/EmlVatFvPiJ/8UYnEL+Y9H1qEWhL0QUkGIWJz9+0WwqupHEYyh0AZWo0RJC/HPRdVfofOWzd8gizMMLJjHGTOtOVZwQc7kcSxsHwAQlWdC0+l/mu/sl+NIa/M0FH7+odbxa8WpazyXF0dnZidHRUTQ1NeHUU09l7sIrr7wSL730Etrb25mwqqmpwXnnnYft27ejqqoKvb29qsr3Pp9PZaGinpM6nQ5NTU0YHR1FLBZT9WXV6XRYvHixKotTvKh6PB6YTCb8+c9/Vu1rZGQEF1xwAWbPng23243f//73qKmpwdy5c9Hf34+RkREcOHAAra2taG5uRjAYxObNm9He3s5E5oUXXohIJKIK8C8vL8fpp5+Oe+65h1nAOjo60NraipqaGmzfvp01gKdECWLBggXMWkY4HA6Ul5cfztfznoK/caTHNL+IXptC8dXiMvGmUryO8TFmYswvzZmZTAZOpxPDw8Nob29HOBxGRUUFs55VV1ezWLSBgQHmCaFyM+l0Gn6/n92U0E1EOp1mYi0WiyEejzPXqF6vh9VqRSgUUo2ZD0ERPVn0n/98DofjIiGAXDH0RfDw2YrihUJ8TUvQ8GqftzSJlgwt8qljLfKZe0WLCy/q+Isz/QjoTysRgI9Z4jNHxNgfPuNPkh+6W8pkMojH4+NcmqI7UOuPt74Bh7oAUFFb/m6LJh2aNOjc4F3XYvYuZS3x1jF6Hx87IcaC0bJ8TdzF35MoFvnfYiFzfDEu9EIWZ8lY0/NwOIy3334bb7/9Nlv+xBNPwGw2qyxevb29rMG3WA+subkZs2fPxgsvvIDy8nJ4PB74fD5MnToVAwMD6Orqwqmnnore3l6Mjo7C5/PhnXfewd69e/H666/j4osvxpYtW3DgwAFMmTIFe/fuZdt+3/veB6vVirfffpu5USlpwev1IpvNYvXq1TjppJOwf/9+rF69mjUoJ2h7Yoyc3W5He3s7tm3bxpYNDw/DYrHgrLPOYr0xu7u7odPpWPPzyspKdHR0jDs/RWHmdruRTqdVZUMk2pA7keDnAa2bWV50KYoCu90Ok8nE/vgbV35+4uc5vV7PSghRAgD98Rn1LpcLHo8HDocDwFiSC10LaV/UPaKhoYH1V9XpdIhGo+zYdDodHA4HPB4PkskkG5der0c4HEYoFEJ/fz/S6TSMRiPsdjvC4TBzm0ajUXbM6XSadVTgE7HEz/FwmPQ6Z+IXruWW1LJUabmQ+B6aWvBWCHHf+dbln0/k2qTxifE6+bYvHhcvvgodRz7xJS0XpUF3anS3RS4dLRclnw1J3ytZr/i4SRJTfEwQvz4vrvjgfWC8gOetcsD4hAPRuiVayMQ7W/6c5I9NS3Tyd36l3KRISodKSgBqi1U4HMasWbOQTqeZyNHpdKxiOm8xmz59OmbMmIGqqir4/X54vV643W5UV1fjtddew/DwMBKJBHp6epBIJGCxWFjfwlwuh7fffptdaGpqalQux8rKSnYD3dTUhEgkorJWDQ4OIh6PY9++fZg7dy4bXzwe13Rric/ffPNNhMNhOBwOlZijWlc+nw92ux3d3d3IZDLM3ep2u1XbcjgcsNls47JBRdesJD/875+fa0QrEBUSpnpyNF84HA5V+zj+T2uuI2MEn6lL/YQzmQwTRNlsFna7nX3HNpsNZrMZiqKwJumhUIgZfLxeL+x2O7uBttlszI1JcxrFHNN4jEYjXC4XysrK4HK5kEwm2XuDwSDrdTwyMsIscbFYTHUDzOsTAHlroBXDpIszQHvCzyfMtESN1sWF3y5/geEtXKI7RzTRagm0QsvFsYsiUGvM9Jy/+IvHwo81nxtWFGzFCMn3OmazmQU9U30yPq6L//xIgJlMJjYRia5FQG2+B7Qze3mrGqCdQMD/p/fR9sRzWFyXX5/ftmg1y2c9o/fRf60bhVJEmhR0EzNv3jwsXLgQyWQSDz/8MFve2toKvV7PLE02mw1Tp07FFVdcgW984xtQFAVLlizBzJkzYbPZWOwXnVtlZWWs+j4A7Nu3DyaTCVVVVbBarVi8eDGGhobw1ltvIZfLwev1Yvny5di2bRsqKiqQzWYxZ84cHDhwAF6vF7Nnz0ZLSwv++te/su3u37+fXVwpM3zu3LnYtWsXpkyZApvNxtywlZWVqvGUl5dj69atqKqqQm1tLSKRCHK5HEwmE/bv34/R0VFWJoR+p+T+FGuiGQwGNDc3o7q6mn1eS5YswUsvvXSUv63/XPgbUD5zluY3Oq88Hg/8fj9aW1sxOjqKXC7H2i1R7TGyUtENLMUh0nxCHgaKF6PuFPx6FB9G87LNZoPVamUiEBgTQJFIBAMDA7DZbDCZTHC5XLBYLCwujW6ErVarqnwSZVHSmIn6+npWVobq5tHY+vr6EIlEmAWNamTybfXIikduU76SQrFMekIAKWfelcOjZVmi5zxaYoRXyfydgJaSzRd7w29LFFf8PvKtJ25XvPBrCU5RJPKuS1LiopuWX19SHCR0zGYzmyx4SxVNLmRup4mEzim6G6Q7PD7ujMzsZEHjzfj0Hr4Reb6YDX5fvFCiiYk/Z2g7vGucd6PylbJpnPz5zrdSky7xd5edO3fCYDCo+mjOmjUL+/fvZ67OxsZG1ff9mc98Bk6nE83NzfjMZz7D3seXqdizZw+mT5+OQCCA/v5+TJ8+HcBYnbR//vOf4+qlBQKBcU3WqVOBw+FAX18fK+NRV1eHj3/843j00UfR09OD1tbWcV0NTCYTFi9ejJaWFvz9739XZWeaTCbU1dVh8eLFeP7559Hf349ly5bB5/NBr9cjkUjgjTfeADDmsm1qamIXYpFp06Zhz5492Lx5M8477zzWT1QKs9IgK5AYW8bfTFosFtjtdrhcLpSXl8Nut6vmQXJDAoduRo1GI9xut2r+4rsQ0FxIAf58r9ZUKsVaNfGWOWqSbrPZmAWPaqS1t7ez13w+H3w+H1wuF4vTJOuryWSCw+GAy+WC2+1GNBpFOp1mYzUajbBYLOju7mYxvxS3GY1GMTQ0xMZGLthYLMZcooFAAJFIhPW71Tp38zHpCQH8f/ExoRXgz1sQeOsR7xbkRYuW4BEpFHtWSCROdCHTciHlC/Tnj5cXlWIWntYxEVKkFQcvvnkxQ8uNRuM4axNvnqfvgq99xp93/HnCWzb571JEXMa7yGmbopWVTwigyZWf+Phx8bEivJuVjoX2wd/MiC4O8Xclz7cj54wzzsCMGTMQjUZZG6bOzk4232SzWQSDQeZ6MRqN2LJlC2KxGCorK9k5AIAJs6qqKphMJpxyyilIJpPo7u5mjcxJwJFYqq+vZ+UpZsyYgZGREQQCAZb1SYKJF3Pd3d14++23YTab0djYyLoU8FDMXCaTGdfVgEIJ6IIciUSwdetWDAwMoLq6GkuXLsXJJ58Mr9cLl8uFp556CvX19aiurobT6YSiKHC5XKioqMDGjRvZdsvLy1FeXq5y+wJgwlSSH34eBLR/47lcjnWPGB0dRSQSYUYDEjB0k+hwONi5SX1+efHHz8Emk4llGFPjcyp5QetbrVY2f2WzWWatczgcqqQocoWStYusZWazGX6/Hw6HAxaLBYqiwOFwwOfzoaKigmUCU+an2WxGRUUFvF4vu9bzQi0WizExqigKgsEgK+NBhXOHhoawc+dORCIRVWzzRBwXbk2Cj60BtDM1ebRcRkD+Uhn53JiFti/un79I81aIfPvQsuZpBftrWfR44ScmMkjLxtGBF1jA+MB4PqBfy10ppljTNoDx3x8fqK+VmKIldHjrWT6RZjQa2WtavyE+cYC3xPGB//z5y4v/fMKs1M9Ykp/6+npMmTIFNTU1qizfcDgMu92OiooKWK1W5lo0Go1Ip9Po7u5Gb28vTCYTamtr0dnZyd47b948nHTSSdi0aRNqamqQSqWQSCTQ19fH4iw9Hg8TZ1OmTEE6nUZFRQVqampY+QmbzYb58+cjmUwiEomoSl0AYwLNbrfD5/PB6/Uya4fP52PzZ19fHwYHB3HSSSehv79flQxAll23242hoSE2nt7eXvT19WHWrFnw+XzM1WYwGOD3+zFz5kxW0qO1tRX//ve/AYxZ85qamhCNRll8Hf+ZSPLDX5vEuY6fF0n0RCIRDA8PM3HGzx0knPiEpnxGCv67tVgsLFyEt+QDYOctLdfrx8q/WK1W2Gw2dg1Np9Ms25LmRbK+Wa1WuFwuFmuWTCZZnFllZSUcDofKIgaMWQrr6upgsVig0+lgt9tVhpJoNMrOdXJ/UveZaDSKgwcPoqOjA4FAoKTr9qR2CDjjjDNYphJwKDhQFC5AfuuaGJfDnwS8kBHje3gxVMjdKWZV8hdF0QLGu5b4fWptTxR9vCVFtM7xlg3eFca7OPmLPnCoQ8DOnTtlh4A8UCFNKnRJ55/RaFTVtqHAUPruxRZI9LlTQU/erUkTGR+XwH93olDjRZAYG8ZnhlosFhYnQS5OfnLkY+joNRo3H07AT15kmhfHpdV3VCsOMh9Wq3VcNXjJIerr6+FyuZBIJNDR0YHTTjsNZWVl2LRpEz7ykY/A6/UilUrhpz/9KZYsWYLZs2cjEAigqqoKgUAAu3btwooVK/CLX/wCnZ2duOiii5jVYXR0FC6XC1u2bGGNy4nGxkaWwUiWs0LYbDYYjUZMmTIFtbW1qK6uhtvtxptvvomhoSE4nU7U1NQgFAqhs7MTixYtwqZNm5hbdtasWTCbzapSHxdeeCEOHjyIlpYWOBwOvPTSS6pxGo1GnHHGGTjppJMAjLldR0dHsXPnThw4cADAmEWMSnM0NTXhxRdfREVFBdasWYOrrrqKbWvRokV45ZVXDv+L+g+HbvJ0OnWbI/4GDxi7tjidTtjtdtjtdtXcRe+l+dBqtaqu6TT3kWijODKa10wmk6qxOM115Eql5BB67PF44HK54HK5VFnwNG9TXBjNh3q9HhUVFaq6aGVlZaipqWG1BnU6HQ4cOIADBw6w/qyzZ89mrlEALJs0GAyit7cX2Wx2XGKDw+FAJpPB66+/ji996UvsRsHlchWVpFKS5azYVOTGxsait0kXDLpI5LOW0QcLjM9K04rX4h9rCTMttFyUNB4xtof2Te/jx1PoYkXb4y0t4uu0Hy3XJo9oqdHaniQ/iqKoTNC8OBa/QxI5NLnw29AS6TQB8e22SCzxoqYYt6F41wqAxYvRf97iwpeoEePd+O3mu4sTbzKO5P5N60ZEombu3LnYvn07s3xt3boVNTU1OPnkkxGPx+FyueD1etHa2oqBgQH09fWhr69PNcHv2LGDPR8eHsYpp5wCh8OBvXv34tRTT0VjYyM2bNiA1tZW/OUvf4GiKJg2bRpGRkYQiUTGCbOysrJxRW5JYB84cIB1GVi0aBFCoRCCwSByuRy7uPn9fmYhIxG4Y8cOAGMWrK1bt6Kurg4ulwtTp05lLqD58+fjqaeeYvusrq6Gx+OB1WrFunXrYDQaYbVaMWvWLCbOotEoKisr0d/fj7179+J//ud/0NDQALvdjq985Su45557YDAYxmVxStTwiUr8tVbLI0BxVuFwWBUOQevpdDrE43FVbBnNqxTcT/OQxWJRvY/2bzQamWveZDKxrNBYLAar1crEFWVyAocMPFQvjcpl8HG3lJVcVlaGXG6sRIfT6WSWMYPBgIaGBpaNKWoSRVFYT0+6Sea7GZBAtNlscDgciMVirEuGKHQLfh+lfHktLS2qAfJfGP9FFutTFYUU/yFoXTjyWaLE17UuroWEGS+8xAuZuH3atnixE61c+S5qWv52XpiKxyGitc18F3XJxIgWR95Kxbs8taxGgLp4LQk3raKwWoJH/I60LMb8Y3ov3Qnyd4R85ig/EYn7o3M4X49Q0bJcSEQWi7xpKIzX62UXKAAsrpFqMFHwciKRwNDQEFKp1Li5kBdqVFognU6jt7cXPT09SKVS8Pv9KCsrY9//rl27WJyPmBgwc+ZMvPrqq5rjpeKdIyMjaGhoQCAQQCgUQiwWYyUMrFYr9uzZw1w8Xq+XuUqdTicAIJVKYWhoCMFgkNWsov6JZGUgV6rZbMbbb7+NKVOmwGg0YnBwEPX19ax4KD9Xbt26Ffv27UNTUxM+8IEPYMmSJejo6JjQMvhehy8TBBSOZeZDQbTCcegco5tDWk7r87G7sVhsnIFFp9OxYH06R8myRje6ZrOZbZMXVtQKjUQazdHZbJZth9p+0U20ohzKTjWZTLDb7SgvL4fZbEY8HmeikjI8yWuh1+vhdrvZfEqvA2NuWCp+PHPmTPh8PnYjUwwliTOdTof6+nqsXLkSK1asGFcF/XDgJ3tRpGhdoPixAIdODF6NioU388GfLKI/PB9iPBl/MmsdEz92MUA7XxV2eo8ocvNZNHgLIX9hlRfFwojfE4krWs7/4LSsXbQNEuziRYIX3ySi+PguQut7Ei2w/G9D/H71ej0LtqVJj9YTty26+LVeo8mvkJAsFnmTUBy1tbXI5XLYt28f5s2bh2w2i/Xr12P69Ok4cOAAXn/9dZUAO+OMM7Bz504kk0mYTCZVrbRMJoPNmzdjdHQUvb29WL9+PRwOByorK3Hw4EE2r3R1dcFgMLDOAXr9WG9P4NAcSlYCvqwCnceU8UnnNjAmpujiyAf/z5s3D9OmTUM6nWbB+4ODg3jttddUcWHV1dVYuHAhNm/ejGg0ikAgoAr2B8YsPOvXr8fZZ5+NXC6HN998E9FoFH6/nyVHtLe3o729Hfv378eOHTtU+5Bow8dP8/MLP1+IN7Ji8h2tT+vyHgd6D+86JUhY8dfhRCKBQCDASmFYrVZWV0xRxmLUkskkAoEAK1pssViYIBL7rpK1zOPxwGg0Mo9JKpVCJBJh1i4q21JZWQmr1Yr+/n5ks1lVML/L5WKuUdoHfTYk2miZ1+vF+eefj927d7P4s2IoSV11dXXhkUcewUMPPYRf/OIX+OQnP4nrrrsOM2fOLGUzedG6My8UQMdfCEXT6kTwFy2xsamW5SyfAJuoenohgSS6Qwtth8ZF++R/KLyFgw/mLvTZSdRWTN6cTwInm82qso+Awlm+yWRynGmef85PbLR//oaAd2PSMnG8NAbRMksXTy23uuiWp//iYy2LWT7LWSlWtFLr+7wXSaVSzLK0ceNGmEwmrFixAna7HT09PeNiVDZs2MA+exIedrsdS5YswdNPP40lS5awsgErVqxAWVkZotGo6sIwf/58bNu2Df39/ViwYAH+9a9/ARibDzds2AAArE+h3+/H0NAQcrkcawkFjFVip9IaAPDWW2+xxz6fD4qiIBqNYuvWrTh48CAqKirgcDgwa9YsDAwMYGhoiJVjSCaTePHFF+FwOFBVVQWv14s33ngDer0eU6dOxe7du9HZ2QmPx4Pp06ezJIA5c+YwEWm32+H3+9HS0oL29nZWikMyMRQiId688bFnYkhPPu8QiTx+LhO7CZCljow8ZC2jZWazGel0msWCUeA+uRIdDgebg0jI5XI52O129PX1wWazwe12o7a2liUnxONxVRIBuUN1Oh1sNhtLOCCxZ7Va0dLSgkgkwmJ+A4EAs7aZTCY275P7lYcseACYm5MXjIUoSZxVV1fj1ltvxa233op///vfeOihh7Bw4ULMmjUL1113Ha677rqjGl8ykbgQ48GKeQ+QX3ABatem6EPn16GLoFacmnjRy5fAoGUOznectD2+lQYvwERLWrHWw/c6vIWJT/bgxUehiYgQP3P+7pMXXuL2tM4N0ZpM/3nhle8/rStabsXzV3y9GAEmrWfHBprwQ6EQczHq9XrU19ejt7cX+/fvV61PPS1F+AKeVOICGKtTVl5eDpPJpMroHB4eRiqVQiqVUvUObGhoYCKO6jKNjo7C4XAgHo/DarWiqqpK1aMTgKqcBzB2vSA3LDDW7omaVre2tqpanlHJBQAsw42SmKhaOwDEYjFs2rQJZ511Fnbv3g0A2L59O+bOnYt4PM4unH19faqacVarFU1NTcV/Ke9B+HmKv65phfLw64uPRQu/+B66ZlMCAgkaiiekyv3UCsrlcjFRQ4/JdU4307ncWHkPCswncUf7IA9ILBZjcXCU/UljpjgyAOycpVIdZA0Gxs5zajdFYydrstVqVc2Z5Nq1Wq1wOp1wOp1FJ+cdtl/y7LPPxtlnn41Vq1bh4x//OP7rv/4Ll1xyCXw+X8nbOlIRUWjyL2bbWlaxUtbXei9v7RKDCfNZRgoJS/EiWcitmc9tJVFDrmW6U6O7O+rvRtAdZT5LKf89aAkvLWsWLef/i9vT2mah9bTGRe8vJM6A/BnN4voT7VNSOgaDAYODg8hkMvjEJz6BNWvWwOv1oqKiAi+//LIqA8xms6GhoQEjIyMwmUyoqKiAx+PBrl27kM1mWVwVuScBsCKYIrwVjW86XlFRAYvFwsQPMGaZtdvtWLx4MQ4cOMAyTPnMS4vFwvqAlpWVwev1qroBAGCB//F4nP3GKIaOP58ymQwOHjyI5uZmKIqiGj9dSGtqati4k8kkQqEQhoeHkclkVPFlDocDM2bMQHNzc/4vQQLg0G+drFrAIQ+D+HsXw3p4T4TW3MC7/Cg7k8+ON5lMcDqdTMhQyQual6lQrNvthtfrhdlshtlsZpn1fCV+mtMpg15RxmLKgsEgvF6vKlmKjoMXcuS257ejKIcSvXiXLb0nlUoxyx+NgbLg6Xho/MVw2OLs1VdfxW9+8xs89thjmD59On7605/C6/Ue1rbyxW4VSg6YaHtHCm89y3cRov3QiSzGedEdiEgpFzVRbInZf/Q6X5qBlsksuYmhz4rumvgyJnyWEX3e9B7+/VqIwkvMNC50jmq5IMUx53N5am1LyyKXT9jzj7UsbOJ2ikFacAsTjUaZmPrb3/6GK6+8Ei0tLbBaraqaYJ/61KcQj8eZ8KCA/+HhYVYxfe/evaxWEwC8//3vZ1X7P/KRj7AYNB6XywW9Xo/TTjsNwJgwKisrU61TVVWFXC6HdevWwel0Yt++few1SjTgxdzo6CheffVVeDweNDQ0sMzObDaL/v5+1bo+nw/Dw8MqQQmMWdqam5uh1+vh9XrR3NzMjm3dunWYPXs23G43urq6sHv3bsyYMQNz5szBc889h8bGRiiKgs7OTkSjUbz++uuoq6s7vC/oPQJ/DeHnPxIlwNg8xpfuIQsSzQf8HErvN5lMcLvdzO3sdDphNpuZKKdsSarU73A4mGDjr3lWq5W12yNrFlnEqBMAZU7yfwaDgb0vnU6jpqYGZrMZ0WiU9dskixkJPLoZoUQCEomUTMB/LhTzC4yFGJBopILPbrcblZWVCIVCKlfqRJQkznp7e/Hb3/4WDz30EEZHR3HllVfilVdewZw5c0rZTMloiTTRNTnRBUArvosucuKFihddWu8heKsE73bSCsbPZ9nQQiuLToyN4tW5VgwaX3pEog25Yegz5l009KM2m83jJixeyIjinRdhoqtRSyTRc/5xPgFXSIDx/ycSTvkEmrhM/Ctm25LS0ev1THSUlZXh9ddfx2uvvcasQlVVVVi4cCF27tyJUCg0rsRFKpXC/Pnz0d7ejlAohGg0ylrr8BX7//rXv+KMM85Ac3Mz+vr6WKxaIpFATU0NK02h0+lUwfwAWIyZTqeD0+mEzWZDOBxGIpHAwMAABgYG4HK5WGJKNptFIBBAMBhk2WkHDx5EeXk5fD6fqiDn3r17YTKZVBmd1COxp6eHxYCKY6L6aWQU2LVrF/sN9/f3q+Y/h8OhcnNKxiPOO6K3gFx8ZGECDiWOkBhzuVxsnqTaZGJNRqvVCp/PxyxnFOdFrkhCp9OxshckjMjlTy5PssSRENPpdKzALAk3KpJLnTHS6TQTivw1nJbTcfC12GjboveEv27odDomOPlepAaDAV6vF5WVlQgEAkVfl0sSZ42Njairq8M111yDD33oQyytlQ8CBcbq9hSLlrjKdxHSEljF3JVPFGPGP9ZaRxwbfxKLr9GXwQsqrX2JaK2rZTXjl/OZMGKmoRh8LhkPTSL0mP/s6EdJmWqi6OItYqL7kM4DPp5NPFf4bYniJ58o04p7pDHw6/JBu1rCK1/sWjF//HtK+Zwl+clkMvB4PIhGo1AUBfv27WMiBRhrMt3a2or169cjEAgglUqNi+9qbGzE0NAQSxyYOXMmampqxpXDSCQSmDlzJk4++WRs374d+/fvZ9XMxer/WpSXlzMrRzabVVn2pkyZgmg0ylxN/DEAY+U+HA4HnE4na3tDKIoCn8/H3JfkdaCCtIUqA7jdbrYvEph0EacxGwwG9ppEm3zijL4Lqq5P4ow3mpDrr6Kigs2r1POSLFyKorA5tbq6mgk3vV7PSlAoylhwP13v+DJBFotFVaqCF4VUFFZRFFUXAYoPo21TvTQ6R8XQExKB5MakGw0ydtBzHtF6RhZIfpt2ux1erxcOh6Po76MkcZbNZnHw4EF85zvfwXe/+13VF0poDT4f9OGSDxconG1ZrGjjxzRRHFe+dfhMu3z75i+OtF8xkJK3umjtW9x/MZYyXpzxz6n0A29uleSHfvT0vfGTE00ifNVs8bym81cUZ/RaMSJGFPFawl9L2PGCT/ye+SQZ/pzRsqxpjVNLkGmNu1iRJq1thenr62MxOAcOHIDdbseMGTMwd+5cPProo9izZw98Ph8GBwfZZ3nZZZepGpQ7HA7U1NRgeHiYZUTq9Xqcd955qvX6+/vh9/vh8/mwYMECWK1WdHd3F0zv/9CHPoQDBw7AZDKhoaEBPT096O/vVxV19fv9mDFjBnbv3o0dO3awODlya27fvp2JLzEOjVrj6PV6tLW1MQsYL97oRpTixmi81GmmtrYWmzZtYlnLlZWVcLlczP1KcW6S/PCih7+G0bnp8XhYX0qydFEvTKPRCLvdjqqqKjYv2Ww2Vv0fAILBIHQ6HSwWC8rKymC1WlnQfiAQQCwWQzgcRiQSYdcxvX6sRZPT6URtbS2riWYwGFj9Mbr20ZxN5woF4xuNRlbdPxaLMRGXSqVgs9lYYoDT6WTzvcViYT056eaF3JVk4dPpdEgkEqx2Gr3GN2onkafX6+HxeNjvshhKEmdi1tCRwheVox+VmG7L/88ntIrJ6iwVrZgtrTgirYuoVv00OonEC5UYhF2M+5L/z8eYie+RJQwKQ+Z2KmaYSCTGtQ4h8UV3YKILk0Sb+N3yd538cxESTeJdq5aVi56L55vWTQRvLabxFRJi/OOJxJoUW0cXuvDU1tbipJNOwksvvYRwOIzdu3fj5JNPZufo5ZdfjtHRUfT19akE1xVXXAGDwYBAIIBIJMJiekwmE4aGhlhmpU6nQ11dHZ599ln23qamJpU7kaitrUVPTw+AMXfhwYMHkUgksHnzZhiNRpSXl8PtdjNL18DAAGKxGA4cOACHw8G6xDQ0NKC8vBy5XI51CBAhK2A6nZ6wHhmJMqvVira2NlitVuzduxc7duyA0+lEIpFAMpnE4OAgBgcHWXcFqlMlyQ8vzih8g6DSEzabDeXl5argeWBsLiWrGt+dhDcg0PqxWIzFe1HMGhkbyGpG0HlMbZhofRJDND9TqQuLxQKv18vKVpSVlbEEArvdzhJR+L6ZVNeMj6WjMdD2qWwHxaQBYIJUnH9JJIZCIaRSKRiNRrhcLuRyY2U+irWelSTOjnYqMi9mePcSbw483AtBvvdN5GIR3UpabiatEhtablk+qUDL1VRIbPIiS4wlE5fz4owXedKtWRiKT6D0bf7zEuMN6TzlxTcvpLREjpZFlN8mLefPI1Gk5Rs3P65C56Ao4EQhqOXezDdmHinQjh7UOsZisWDq1Kl47bXXEA6HEQwGUVdXxy4GFosFPp9Plb1ZU1MDk8mEeDzO3JJ9fX3Q6XTweDzMWkE1nsS4q1wuxy4Wfr+fZb7x/S3FWK9MJoNAIDAusHlgYIBtj+qiAWPzYFNTk6Y4M5vNKCsrY9YJscUSBY6LVFZWoqenB06nE36/H/F4nJUs4DOtc7kcRkZGVEV6JRMjXgMpG5EKt/LQ3JlMJllRV4rfoh7DZIAh4ZZKpZhQopthAEx88XFmVquVdQogbwd/baWWTXwyFy3nM0HpZjyRSLDwI7vdriq5wcN7U8iIxK/Dl/Ggz0wUuPy1WKfTsVi3YihJnImxZfkoNuaMrBO85SHfRWkioTGRlY2PGdK6iBV6LrqVtNxM+dCqg6Y1dt6yVkiY0bKJxJnYnkeiDf1YyEzOtz0CMM4qJtZAA6D5+Rf67PmbD63XxMeFxFi+bdEyOv+0RJyWhUzrMT0/XMtZsb+V9yput5tVM6cJnWLHKKuxvr6eWS/0ej2mT5+OefPmIRQK4Z///CdmzJihynbs7e1VlccgRMsUXQCBMaFHDaR5cRYIBFBfX49cLsesaWR9WLJkCfr7+xEKhbBnzx6WbZdMJrFnzx5miXa73Zg2bRqy2SymTZuG9evXQ6fTwe12o7m5GalUCqOjo9i/f78qno6sc/y4qWL8yMgIRkZG2PUmnU6rOhkAY5mwlLkqKYzW75Tmsng8rhJAvOghwUNJHolEgtUcEw0NZE0Ty6fwxVv5MhvZbJY1OAcOxQ/yMWUWiwUVFRXsfXSjQ1mVfCFxt9vNWpiRC1IrNIS2TfMnjY/Gy3cBoBhQ6udJcz/FZWazWcRiMSiKwjJXi6EkcTZv3rwJrVnkRikGXniI4oy/wJVyQcgXP0ZjK+VCIcb1aF0sxbHScxrLRFYVOmm1Pg8KLMwnyrQEAS/OpFuzMIlEAvF4nP2gyRxN5zh91rFYjN0xiu2XaF2t75xHFFRAcdZdLcuX1ntFyyx/fomiP98y4mi7MWXsY2FeffVV1NTUoKamBl6vF4sXL8Ypp5yCaDTKMs3i8TiriE/s378fbrcbQ0NDOOuss3DppZcinU6jsbERTzzxRN44MrqguVwuHDx4kC1/8803x61LHQIMBgOmTp2KOXPmoL+/nxW8femll1BVVcXa4uzatQsOhwMNDQ2ora2FyWTC6OgoBgcHUVdXh9HRUaxduxZerxejo6MYGRlRjbOmpoZl4hmNRpZwQFbFVCoFvV6PhoYGdHd3w+l0qs5Pcse2traisbER69atQ2trK6sHJ8kPH/QOHCoRRfNEJBJBPB5nllkS9nRTQUHx/PxDsVfpdJpZ1DKZDLOoEXzLORJ8ZrMZHo+HxZ0pyljSiM/nYxm6ZPUCxsQQVfUn8WU2m5nbkpK76Lion2sqlUIikYDb7WYWu1wupyoLEgqF2PVBzCjlS44EAgFYLBbWk9Pr9TKrtaIoqK6uLrqV2KTGnJGAyCckirFCTIQYFyZeKAqJuXyILtdCbiwtkSnGlfGP6XVS+qIwKyTOpEuzNDKZDKtybrfbVb3WgENCi8z5/Hmaz/2YT5hpiTOtGx3RnSAuz+d2zGcF07ox0HJlFhJiRyrUpOWsMDabDb29vejr60M6nUZ7ezv6+/uZ9aqtrQ0tLS3j3se7ATdu3Ai32w2n04ny8nJNYcbX79Pr9SgrK0MgEBjX9JyHYsoOHDiAaDSK6dOno7e3F2VlZSgrK8OBAweg0+lgNpvR1dXF6llFo1HY7XZmVaNSIQaDATU1NaysADCWEECN1Ht7e+FwOMa5bxVFwfbt2zFlyhTY7XasX78eZWVlcDgcLAvTYrGw99hsNtZFgQr6ulyuEr+Z9x68lV28kSOvAe9ZMBgMqp7CfFatTqdjcyp/DSTxI86hZAThXZk1NTUoKytjGcLkriQBRsH8mUyGFa2lcdB2SRRS3TFe/PNuUXLpp1IpBINBVhqGd6UqyljcGW2f4pBpOdVGA8bOR7IWkvU2l8uxrgQTMakxZ7zgoAPU8nXzz7XIN/nzwox/LFomirngkH+b3suPSxRf+cZdjDDj3Wq8cM0nzsR9SoFWPPSj4VO3KSiZP0fobo+P+eMnFlFs8eexljux0PmndT7y37EYN8a/rvW8WLGlZS0rJOxKQYqzwlgsFrS3tyMajcJisYyzYO3fvx8NDQ0Ft8FnL2rdXNbW1mLhwoX461//CuDQd0LZdQ6HQxUTNn/+fLz++uuqbVAfzIGBAVY2ARj7HUUiEYyMjKCurg6KomBoaEglwMLhMMLhMKqrq3HyyScjl8uhubkZHR0dmDFjBoaGhhAMBpHNZtmFLBqNYt68eQiHwyzDk7LywuEw6urqWKumSy65BNu2bUN7eztOO+00BAIBVqxXtAhJtNGyxvMiioQbf10hN6UWWnMZn1HJz2d8twBqXs4XHuZd+rQdsgBTpi+1ZaIgfJrPSVDmcjnWw5VKW9DNClngKDaOhD1Z3KgcCG2HxkLXCpobrVYru5kHxs7hVCqFcDgMnU6HaDSa9/MSOawOAe3t7fjb3/6Gjo4O6HQ6tLS04OKLL8aUKVNK2o7ougPUVqt8AocnX8yNljDjv1iRQq4dfj/iY/G/lis2n8uTnouWMN6tKVoXtdbTspwdqcXxvQDd7QBgpnSj0cjqmtHEU8g9rHWOaP0n+GUTxZzlO4dEVyq/L/69/H9xm4X+tM6pwxVm4jFJxkNNxgHg1FNPxeLFi7Fnzx48++yzuOKKK7B582ZW5Z96b/LY7XbWNikYDKpqjxE9PT2s5pnRaMQpp5yCl156CQaDAT6fj9WloozGBQsWoLGxETt37sSuXbvYdoaHh2G1WlmiwRVXXIE//vGPzILHl8ngXaZELBZDZ2cnent7kcvl4PV68cILL6CmpgYej4ddFEmgkTvS6XRCp9Ohvr6eFSOlcS1atAjRaJQlO2zevFm1z61bt+LNN9+UvTUngL8G89YiEsT8dXoi8v3mee8DlaYwGAyssLHH44Hb7WYWrgULFqj6XWYyGXYDbTaboSgKE1u7du1COBxGMplkLuxkMsn6c9rtdpYhSuLJarUyVyXFnxkMBsRiMej1esRiMRiNRtbyiUpq0HxMpT+oDlwul8Pg4CCGh4cRi8UQj8eZVZjaAsZiMSxbtmzCz7Bkcfb9738f3/jGN5DL5eD3+6EoCgYHB3Hbbbdh1apV+PKXv1zqJoua9POJMP65WO9My3ohZtppFYzVuiDy8KUy8h1LIWGmZY3gBVW+eLN8f/y+xIurJD/0Q+Qb2eZyOVVMAW/CJ4FfyDKVz0omCjStx4W2m+9GQet1cTz5rGP8e7VePxrCDJAxZxNx8sknY//+/Uin0zCbzXjrrbcQDAYxZ84cFvNIaLkg+dcBjAuKJ+g7TCaTeO211wCMXSwpy9PtdjNx9tJLL6Gjo4O5IumCWl9fj61btyKRSCAYDI4LtudbRwFjrZn8fj+cTic2b96MUCiEHTt2oKmpibXEoabssVgMIyMjzDWVSCSwadMm1mGguroagUAAmUwGfX19qKqqgsViQU9PD3bu3Mn2OXv2bNY9AABmzJgBp9NZtMXivYoYAkTXLv73W+o8wM9/fPYkX5rD4/Ew8eR2u1nlftpfKpVi136ap0OhkOraZ7fbWU0zvgit1WplfV6dTif0ej2i0Siz6FK2M2Vj0n4oxo2KJff397Ps0vLyciZao9Go6jocjUZZjDLFW0ajUYTDYWZhpmSfiShJnK1btw7/7//9P3z961/HF77wBdZ/bWRkBPfffz9uu+02LFiwAEuWLClqe/zFrtj186EVsM8vL+RmovX4L0dR1AVleUoVZbRcFFGikMqXgTmRMNOyfEiKgwI++YrifNNf0R1SihVIdKNrudVpeT6LsBaFvl+tGxhans86TI/zrX+kIl9azgpjMplQWVmJVCqFN998E7t27YLNZsOpp56K0dFRTWsFby3joZsNl8vFyksQ/GOKj6Ft5HI5Vf2lvXv3ssBlfv/UxokYGhqCzWaD1+tFVVWVqhE6FS2tqKhAZWWlyqJFbX+AMeuD3W5n1hr6LEgAEqFQCIqisHqEDQ0NSKVSqioCbrebuVvpc6JSOZLC8HMH/7sXC3RPNB+I5SzoP8WH2Ww2VT9NiimjODOz2Yx0Os2SCXiLHZXjEA0QZCGj2md8L1BKEiD3JwmqZDLJwoh0Oh278SEBSDXzYrEYQqEQs7rxrtJQKASdTseSdsLhMBub2WzGyMgIE2yxWAyRSKTosi46pYSZ9/LLL4fX68WDDz6o+fr111+PcDisKpCoRSgUYpWdnU4nK2EAHHI5TmS9AvJnYYrxZfmEG78fcX+8yOGX5aOQKBO3JwozMc6MTkBazos2sY+meIHl7yboLjYYDBadvvteoq2tjQV2JhIJdmGj2AP6bKkuTr7PPR/8Ocj/iQIqn0jKZ92i/1qxbuL++WUTxSgWenwkUGNriTY0R5lMJpVl7MILL8TmzZtht9vhcrnw9ttv46yzzsL8+fORy+Xwm9/8BrFYDG63m92Nk1uora0N8Xhc1eScLGCtra2YM2cOnn32WbS2tsJqtSIQCMBoNGJkZITVNfP5fOPaLAFAWVkZswQQZrMZDQ0Nql6ewFhTdY/Hg3Q6jYaGBgwODrIAfqqyTsfc2NiIefPmYffu3XA6nZg7dy4eeughAMD555+PF198EUuXLkUsFsOrr76K6dOnY3h4mLlUKyoqcPrpp2Pt2rWan/Ps2bM1Xb6SMXjvEsWXkcVLvK7xXXHEmHEqaUFZkhQXRmLM6/XC6/Wyqv3Ub5Ou5xSUT+IJAIsDI6sqX93fZDKxxyQGk8kkdDodOy+pdRLN9ySuqKAuMHajQUkCVDeQEsGoQwbFlCnKmDu1q6sLiqIgHo8jGAyqGsGT1YxKi4RCIXZt52868lGS5Wzjxo1YvXp13tevuuoqXH311UVvjy6EvCAT43UmQivWjJZrWcuIfFYm/sTkLSi0rBBa1od8y3lhJoq0QnFmWgJBtMhJisNkMrHihnxPP/oe6IdOd3JaFox8Vi/6z98ciDcI4vcnirZ8cWT8tsV98uvyE6b4m8on0o6mxYyQbs3C2O12nH766fD7/Xjqqacwa9YsAGMlNkKhEHw+Hy655BJMmzYNTz31FF555RXU19czq1coFMKcOXOQTqfR09ODzs5OdHZ2suzEGTNmoKqqCj6fD8BY5uX69euhKAo6OjrYuc9DFz2LxYJEIsGKNQcCAdZ4nXd36nQ67N27F36/n4m7k08+GdFoFKOjowgGg/B4PKisrERNTQ0MBgNeeeUV1T4PHjyoilPjH3d2duKiiy7Chg0b0NvbC4vFwmrAzZ49G7t370ZFRQUymQymT58OnW6seTvFsAFQuTol2vD1xQgyClAsmnjTxl9DPR4PO1ccDgdrWeR0OlFZWckq5ItlTSijMhqNsmK2JHToMfVtpXmMEmisViuy2Szr1UmNxulYqOgrJX5RiQ0qAULJLPR7SqVSOHDgAILBIBtXIBBg1j9FGSuZEQ6HEQqFEAqFmHGFt8ZRMgDFyPEhMkV9F6V8cf39/ay3mRYtLS2q4oUToeX2ESmmiKsWhcywhaxy4rJ8gdsiWr76QuMSx6HViom/eOZzZfI/EinMSofvD0d/vFimOyktcz89nwhRIBH8Nvnn/PJ864iP6bmWqCp0fmiJtaMt0KQ4K0wsFsPw8DA8Hg/OPvts6PV69Pb2MmuY3W5HZWUlrFYrnnrqKQBgmYjEgQMHoCiKptAaHR1FPB5HV1cXFi9ezApq1tXVscxHsWAtWS4o/tLn80Gn06naPNEF3O/3w2g0oqenh1nxqAhpMplktdqog0BdXR27kPKWQnGuHhwcZJaKXbt2oaamBslkEkajETNmzMCbb74JnU6H4eFh6PV6Zp1taWnB6OgoK5VTbF0pyaF5gKxl/BwgXgvFuYHECwkzh8PBYsmopRjfNJ2/nmUyGVY7j9oekQuRvEl8CQvCarXC6XSyvphUp5Lvi5zL5Zi1K5vNsmKxVJONjk1RFCYCR0dHMTw8zFySJOxoG4FAgNXJjEaj7PrNe7rE64nWZ1aIksQZZUjkgzq+F0uxVoJCiBe8XC43Lo4tn1gSLz75hBidTPz2xfGTUOLXK9b6x4+zUGxZoTgzLWSsT2F4MzzdEfGJGDRBFYoxFB+LYoo/P3mBpiWsDve5uE9+XFrjFMdbSKAdDWS8z8Rs374dmUwGl1xyCdatW6eqU+Z2u6HT6eDz+VBeXq4SUk6nEz6fTzMz0uPxIBwOq+LEpk2bxuK6Ghoa4Ha74XK5UFFRgXvuuQculwsNDQ0sKaG6uhrAmMtQ7L8JjFnlqqurEYlE0NPTw4o6A2NtpCKRCBNggUAAwWAQuVwObW1taGpqYhmWPp8Pzc3N6OnpweDgIBN+5557Lv79738jGAxi8+bNMJvNqKurQ1VVFa666iq8+eabLOaM+mnOnz8fQ0NDqKiowEc/+lFs3LgRnZ2d4wStZDy8hYy/1kxkRCFhRq4/h8MBu93O/ijDlgS7GL5EGZTxeBzDw8Ms3iscDqtCefg2jwBYBmZdXR0ThoC6pl8ymWRzOmVbUokMcnVSVwv6i0ajGBwcxOjoKEZHR6HT/X/sfXmYXFWd9lv7vq+9d7o7SafTSRqyEkIChGUwIiAIODoKIjoz6uiMoqLD5ziuI8MMM27o6DCKjjogoIJhNRAIe/at053e9+7q2vftfn/08zs59/at6uosglLv8/TTVbdu3Xtu3XPPec/72xSMiJHvmZSIUT/n5xV6rdfr2XfOWSqNH/3oRzCbzbKfLbZ+mdykwG8/Xcd2OVNlueNJlZFSBA3AvM7Bf09aZ4t3epWb6OR8e3hCxps1T0fZqCoW5UHyMw0MJKfz94Ei3yohK9LgAWn/BuQJWqn/PEopZvxx+L7Ef15u0fPHUFur/bA8rFYramtr4XK5sG/fPpbygnDs2DHceeedUCgUaGxsxLJly9DX14dCoYB4PI54PI4rr7wShw4dwsTEBLq6uljEWEtLC/r7+wEA69atw86dO9HZ2YmGhgZZ36xQKIRNmzbh0KFDEASBEcFjx46hubkZnZ2dOHLkCDweD5YuXYoTJ06wlBbbtm1jk2U0GkU4HIbVakUul8PIyAiAuf7m9/uxf/9+KBQKNDc3QxAERCIRHDx4cJ7rwOTkJOs/NL/Mzs5ifHycPZvbt2/Hyy+/zHyFfv7znwOYi+7kfe6qWBiU7Z4vWk7zGm3j3TVorKF5ine8NxgMAE6V+qLvAnNKLx0zHA4jlUohnU6zSEoiVlTwnBQrg8HAFtOUIqNYLGJsbAy5XA5OpxN1dXXQ6/UilY0nZ6Sieb1eRhTJN25mZgZTU1Po6+tDX18fQqEQU7DpOngljB9fiYyROER+b7xKuJiqPYsiZ42Njfiv//qvBfepFFI1iJSnhUjZYgd7OYd+ObVtMSZM6TEWq5JJJ27+N5AjYKUctitpZxXyoN8yn88znwA5CXqhgJByZEp6LKmiJke0+DqwcupuqXOWawu/6CinsJ2O/L4QquSsPOLxOKxWK1wuF5577jm2nc87RqAyMAaDQWTCfPLJJ9lrcthPJpMi1ZKI1pEjR3Dy5EnRcZuampijPqlZXq8Xer0ew8PDyOfzou+QStXS0oJwOAyNRgO73Y6jR48in8/DZDKxQC/emkJ+nI2Njax8k8vlkvXp1Gg0CAQC83zc9Ho9Ojs7WfRnT0+PbORqNpvFxo0bMTAwwHyZqigPfswrpZZJt9N38vk8U7rI8kARtoVCgZkGycxI+6VSKRaVSaZoAPMCEQRhzvGeSDhVJ0in06LqD06nE4IgMDMncGohXigUWHkl8iemyM1MJoNQKISpqSlMTEywSEsyqdL3eXcsPjJUOl5Lo1bpd610bF0UOStVq+10wV9IJSrZ6QzypSabUuYl/jzS6Mpy/j6LgdSZko8KlSOsp0PMzrSNbwfQA0v+DfzvTShlCuQ/X0jxkjMvyu1Lqy7ql5U8yLRvOeJI55Nb7UnPL73Ws4EqOSsPUhyMRiMrdaTVapFIJFguKIPBgKmpKeYkXe7ZTqVSSCaTzGGawJM53g9Lq9Vi2bJljJz19fWhra0NPp+PmYDI+V4Ki8XCFANgznFfpVKhoaEBkUiEKSbAqZQhwJyZNJPJYGJiQvZ5oELp+/fvZ9sMBgOrrdjc3MzIGalyhNbWVgwMDEAQBHR1dcFutzNFpIqFwavvpcY0OWGiUCiIyBnvc5XL5RhZLxaLogh4MluSWsbPh/zigsZEfnwmcma321m0vd/vhyAIrO8LgiAyQVJeMz7JbjabRSKRQDAYRCAQwPT0NGKxGCvQTuQREFtI+PqjdC4Cmff561qMiLNos2axWMT//M//4OGHH2YVAlpaWnD99dfjr/7qrxZFCHhHeH5bJVjoPOVMOeUgl4iv1KrhTMB3Mp4UlCrPxJO1Ks4OSHomh1PgVJ+kz4FTUj895KWIfSkFSqpYSb8rR574QYnvg3L/5Vaxcqh0YDjb5Ky6SCgPj8fDEl2q1Wp4PB4Eg0Fks1nU19cjHo+zzPtWqxUOh2NePjEKzbfb7cyUp9Fo0NTUhGAwiI6ODuzYsQN33303Ow6ZawqFwjyCc/LkSfT392Pp0qUlSU1DQwPz6QHmovmbm5vhdrvh9XrnETqqb5hKpVgNzfXr12N0dBT19fUA5syYlFeKz4tG5aSam5uxYsUKPPvss2hvbxel/iCkUim43W4olUo899xzaGxsFP2GVZSHlCzzpEIQBEZqFAoFGzdpfwoEoVQUUusPjVf89+TORe3glSr+PPS5IMylOhobG2OLEpfLxXzQtFotQqEQI1l8cXSFQoF4PM6I5NTUFEZGRjA0NISZmRl2LTQX8yZKmhP49knnZp7gErlbzPy9KHImCAKuvvpq7Ny5E2vWrMGqVasgCAKOHz+OW265BQ8//DAeffTRio9H/j7ErsvlIyv3mRwW2of/vFSiWqld/UwgZxqTI2TSziwlalWcPdADQ9I0+QrwZUzI0ZVWSHy2ammqFakSzJtppIsFacoX+qPVH398ucFJ+n2eDEpXn9LBsZRyJ23n2QJfDLmK+cjn83jttdfYeypKHo1GmRN7Z2cnc6JPJBIicvaOd7wDr7/+Opt49u3bh+bmZqhUKlYv89ixYyySXqlUwmQyicgZX6IJmAscIDQ2NrIoNh7hcJiZShUKBXw+H8LhMAKBwDwTos/nw+zsLKLRKA4cOMByXBYKBeYTB4A5k5OSTTh69CiWL1+Oo0eP4siRI6ivr0dfXx+b5Lds2YJAIICBgQGMj4+z701NTbEIPj45bRXykFPMeOJBRcn5yjrSNBs0xsjNZ/yx5UiNdPzhVdlyICUOAEv2ygssZMqkvGaCMBfZbDKZkE6nEQgEcOTIEfT09GBoaIiZYPk28eSUvxapWiZ3vZVau0TXvpid/+d//gcvvPACnn32WVxyySWiz/7whz/g2muvxU9/+tOKc51JzUg8QeMnEDl/MKmpRMqo6XjSz3gs5GdWStJdDKRqitwkzu8np5qdzo3lj12FPKTqJd1baaFkXp7miQY/QPEknl8hyj3gwKnKBNJ+LF2E8H+EUtv5z4loypkzFyOtnw1UzZrlIY3empiYYEk8yf+mtrYWq1atYmH9fr+fkS3ywwkEAiyiPpvNQqlUwmKxMEf6WCzGItqkvmwej4eVcQLmSBK1iyrBSEEVCGpra2GxWBCPxxEKhWAymZgzODD3nJC6x9eqlesXlIxU2kcLhQKWLFnC1Dg+8pJK/jQ3N4uUQ2DOFDo0NMQy01exMMq5SBAJo/vDEzL6biWuN6XGBGnuvHLt4/sIr2ZRiguqz0mEkkpG8aZVYK4e7dTUFEZHRzE9PY1IJLJgMB+dU27hzI/9pUyelWBR5OwXv/gFvvCFL8wjZgBw6aWX4vOf/zx+/vOfV0zOyAGQJ1E00RGkKla5CYmHnDlJajMudSy5H1FOyeOPWQmBkjJwqV+Z3ErjTG7uYiJD3o4glUxKYnlli0gXvdfpdKJ+RYob7UN9S5o1m4+6BeZMTjTQ0bF41a4U+GdBLgpZGkxAWCio4VyiatYsDyk5I+JEPjNU9kar1eJ3v/sdxsfH8YEPfAAPPfQQhoeHZa0VlFrjpptuwq5du2A2m7Fs2TI4HA7s3r0bY2Nj0Gq1uPTSS9HU1MTKL504cQIvv/wyDh06BIvFgtbWVthstnmqGbWbIjiz2SyeeuopAHN9beXKlVi3bh2bbLu7u0WBAWNjY8hkMnA6nbjssstw7NgxzM7Oor6+HsPDw/OeySVLlsimwjj//PNxySWX4J577sHmzZuxfft2XHjhhbjnnnsAABdddBGefPJJxGKxeYlPq5CHdL6RU+1pLKPUWuS7KycI8A7x/HHoGDSWqVQqaDQaNlaS7xp/fjmVjRbNOp0OarUaqVQK8XicJZmlPGt6vV405heLReZfNjg4yMyZ5JtJYzgPqQpG4ztdAy3spfMAHzhQKRZVvsnv9+OJJ55AV1eX7Of79+/HVVddtWAiWirfdN5550Gn04kK9UpJGK8w8NEPshcjYe8EqUlQSvj4/QB5Vl9OhSpFqKSki24U7yxJf3wOFLmi56czqdLKu1q+SR41NTXMtClVXqlvUJg1RffQAMKHl9N3+IGGnEipH/CRoDSoUZkTus9y5Iy/97yJU24AIPA+c6X6I9+/5D47W1AoFFi2bNk8s1kVp7AY8rpx40Y4nU4899xzWLt2LZLJJI4ePYpt27YhkUhgdnYWqVQKer2eZfjfu3cvDAYD3v3ud7M0Ezy6urqwadMmPPfcc7L3aevWrdi9ezcAcVQn5ZS64IIL4HQ60dvbi+HhYTidTrS0tOCZZ54BcCrq1Gg0wu12w+FwsKzrs7OzUKlUTCG88847oVQqcezYMTzyyCOsDXKRq7W1tZicnGT91WKxQK/XY2ZmBna7HYIgiMrk2O12FvlZxXxU2g9poUD+hvz4wlsTpHMWEa1SRIWiKylytxQxAsQKm0qlgtlsRltbG6vl6vP54Ha74ff7USgUYLFYYDAYWNuy2SwikQhOnjyJgYEB9PT0oL+/nyWUpUoDxWKRXaMceEuHVEnjvyNdLFcyny/K3hAMBuHz+Up+7vP5FtX55fxuSpW6kUKqfEnNPmdiSqlkkpJOeHITIU8SpaqZ1LQpZ8Y8E5Mmf84q5CHtP/wKTtrveFMhf1+l/YycZal0CN8XS/Vx6UMr52soNWXSflIyt1CfOV0VtopzB7vdLnpPfo5SUC1CYE5dCwQCKBaLTFUKh8MQBAHj4+MoFAqwWq0stVEqlZpXLgk4pcrl83nMzs4y9YEHXwKJfy6am5uRTqcxMzODyclJHDp0CDabDfl8Hi+//LLoHFarlfmYkRN/OBxGNpsVFVx/8skn8frrryMcDmPlypVsu9frBTA3gXd2dmLLli3QaDSiMZpyZAFg/nfSa62icpSzLNFCklehAMjOh9LvlppX+bFroTmcJ2nS6EsALM8ZnxiW/igxc29vL44fP46+vj5MTEyI/NZIMKGUIPxvQv/5BXK53/B0sSgGQ+VsSkGlUi1aupOiUrNlqc/kzJsEOcK1kEogNwmXMktKJ25+IpQjcKWUjbNBzCq5trc7pIsCcsanh5zuOZEsktV5U6icwz3VjOUfXF71la625O45nYe//9JkydJFhNzAx+8vR8z+GCbHqnm9PNasWSN6b7FY0NjYiM7OTtH2iy66SORD1tfXh1gshuXLl+PYsWM4evQoc5KnkkbLli1jxEYuFVJtbS3sdjtLJ7N06VLccMMNon14B3siP3q9npXyGx8fZznQLBYLy6QOzJEpl8uF9evXs9qco6OjCAQCSCaT0Ov1qKurY3U/9+3bh6eeegoDAwO4/PLL2XkbGhoAnDJjXn755bJjOSm1FI3Ho0rOykNaGgk4FTkunWPJGiC17kgz5/Nkix/zpODHV7JAUCAHQU55In8yyvhPRMpoNEKlUjF/TDpvsVjEzMwM+vv7cfjwYRw5cgT9/f0IBAKiyEuK4M/n8yxXGjA/dxnPC8r5wZ8OFh2tecstt8xbkRBOJ8mf1CmavyDpZET/eVvzQu2VI2S8w/diojH5faUrA14FkyNe0n2kKwwpeZN+93RwpkT5zx300Mmtfmig4lUqAMzsLPX5Ip8z+s2JoJH8Lj0OcIq0lLpPvMLGJzEE5itkvC8Efy18H5Wqb38MYiYIQjX55wJ4/vnnYbFY4PV6MTAwgHA4LFsq6cCBA6ipqYFSqYRer0c6nUZfXx/Wrl2LdevWobu7m0WpuVwuRKNR3H///dDr9Vi3bh0aGhrw4osvIpPJwGQy4dprr8Xzzz+PN954g5mojhw5wqIhyceLV87q6urQ3NyM/v5+PPHEE/M+b2pqgiAImJmZwXXXXQdBmCsSvW/fPmZVuf7667F//35WMzQajYqOAczlKquvr2f9+sUXX4ROp8PBgwfR29uL1tZWOBwOjI2NiZ4pv9+Pnp4elkaBh5zfXBWnQOMQbyGQm394P3HpXEzf5V1FBEEoWVmAf8/PeQuVOSKTPeXh8/l8cDqdsNvtcLlcMJvN0Gg0yOfzMBqNKBaLCIVCOHnyJA4dOoSxsTFMTU2xGqxSPzi6FhrDCTSW8xYNukbpolfOP24xWJTP2a233lrRfvfff3/Zz8nnbN26daKoIGD+RMnfdFHDy6hrcgqWVIHgz1VqopKrCciTKd7pW3ojpMoGycD0n/cx4zMQ8/5mZ+r/Q8Sg6nMmj9bWVrbKk6plhGKxyFQwes8PLPy9551Sqagu718IyPdNqY8YHZsPGODB9yVqTylyxqt8POnnnW6lZtSzrbjW1NSI1JcqxLBarSVL3/H5yAgejwezs7Ml75PRaGR1OJcsWQKNRoORkREcOXKEOTtrNBrU1tYy/zE5ny5CfX097HY7IpEIRkZGYDQaWT9raWnB0NAQa7/JZIJCoUAikUBraytLX8FHUF544YUA5kr4jI6OoqurS5QahOB2uxEIBADMka7Ozk4cPnwYgUAAdrsdDQ0NSCaTGB4eLlncXLr4rprzS4M32UnHEQJPXHgfMDlVSzqv8vvz4xxPZBYSS8iyodFoYLVaYbVaYbPZUFdXB5vNBoPBAKvVCrfbzXyDqT+GQiEcOXIEg4ODCAaDiMVirBwTLa6lplhp+6iNdJ28+VVKSkv9LtLXpbAo5Wwh0rVY8D4+hEpX83IXJ73xcsSJzkE/eCnSV84viPaj6AxpG6SqmtznC/2dDfwxlJE/ZZB0To75fIg4MD93GTC/j0nB+yjwDy7fz0i5lT7IBOp31CaCdEDjV6Pl+pr02H/sCapq1iyPuro69Pf3s2hGv98Pq9WKYrEIn8+H4eFhUZJYCmJRq9Wy6oJOp0MkEoFOp0NTUxMMBgMmJiZEFQKUSiUjZsCc31spcrZmzRq0traip6cHIyMjSCaT0Ol0qKmpwdKlSzEzM8PIGalTer0eJ0+eRDabnbcwHBgYQEdHB9s3HA6LHLwJRMyAOcK5ZMkSdHd3s0z08XgcNpsNGzduxPPPP8/25ZPytrW1sXJUVSwOPFkD5K1XPMpt48ncYl2LCDReazQaaLVamEwmOBwOlvSYPlMqlaw4uUKhYMpsIBDAyZMnmUmdnjfeWiXXfjmyJnetpBrS90oR00rxpmaHpAKmvG9NKTZeCnKTZSlSRqAJVMpwpT8mr6RIiZM0czF/HDmlQkrapCbRc0nSqpAHmT4oEpOX13npnhQmUpkot49U2icUi6dy7vCmAumqkPoPhaBLP6M2Uh/kJ2K5h53vM1JzgxxJ49twriBddVYxH+FwGFdddRUaGxvR3d0Nv98Pt9uNmpoa/OAHP4BKpUJXVxfOO+88NDY2IhgM4tvf/jbe8573IBAI4Omnn8bKlStx9OhRAHPkZHBwELFYDN3d3cxCAQDt7e1obm6G1WpFT08P0uk0fD4fLrnkEvz7v/87gLm8ZuSfplKp8Pjjj2PHjh0wmUzYsGEDXnvtNdZvd+/ejdnZWXYtlC+NlKzh4eF5bjDj4+Mwm83M7Dg4OAilUgmXy4XZ2VlceOGFiMfjOHjwIPtOf38/Vq9ezUyttbW1OHnyJJRKJa688krs2LEDu3btYtHpBL7mplwKqCrEoHGK5kPeB0sa2EQKvNSUWU6plHOr4MeqcspZsViEwWCAxWJh5ku32w2n0wmz2SyKiI/H40gmkwgGg5icnMTMzAxmZ2cxMzMjSulSSuUq5SMnN77SdZOlg7dqyJ2nUrzpqbtPp9FyhIh/LWdmlH6XJ3WlIi54Fa2UEyP955UQuf3593JEUo6MVcnZuQWvRKnVavZgU84ePlUFH94tde4HTpF7kt1pG0/w6B5L/S9KmQ/o+7y6zA8O1N+k6om0P0mfiT+mz5k0oq6K+YhGo+jr60MikYBKpcLQ0BDC4TCUSiX6+vrQ0tKClStXYteuXSKn/n379jGlwGAwMDPg+Pg4lMq5KgNqtRonT55ELpeDx+NBd3c3U7IOHDgAk8kEp9OJwcFBXHTRRRgYGGAkD5iLkuSrAGSzWTQ2NqKxsRENDQ2IRqN45plnmF9hU1MTmpqa0NfXB71eD5fLBWCu2DqPnp4eWCwW1NfXs8jKQqHAkuzKmXlffPFF9joUCsHtdqO5uRnNzc3QaDSIRCJ44403GDG0WCzo7OxkhG7Xrl1neqv+7CG3wANOzZO86U/qRiE1i9JruQUib7WS+qfxPm8EGqMdDgfsdjtsNhs8Hg9cLherq5nNZlmKDErVMjExgYmJCUSjUSQSCREx41FqLJSbg6XCitTKRtfFJ1v+kyNncg71C6lmvD18Mcoa/543aZb70fh9S6GceaqStpSaSM8GMauaNcuDFDICrQSz2azI6Z+PSqLvEaRRvPSfvkP+ZtLP+EhQfqXFD3j0ff74/H5SEzy/4OB90HhSRv/lVrBnE/z1VRcZ5ZHJZDA0NIRgMIjm5mZWW5JIEQC4XC6RmQ+YM2+Sz0w6nYbL5YJGo0EgEBDlE+vt7UUwGEQmk2GTHJH9RCKB8fFxWK1WZg2gYANAnDCUng2DwYBwOMyiLZuamjA6OopkMomJiQlYLBZYrVakUinEYjHZ8ZOi6QqFAux2OwwGA4rFIoLBIPr7+2XJGX/9fr8fmUwGer2epQKRWj9UKhWi0SicTue8gIMq5CElXHLzUSkhQaq2Se8H7QfIm0ylpE56Do1GwxLKWiwWmEwmUSRlsTiXWzIYDCIajSIUCmFmZgbBYBDpdLokMSNIVbRS8zB/nbyauNAxF4s3nZzxRaflbqYceNsuD+lkJEf0+E7Dy7BSoiZVLqTbS0HawUrhj6GUnUmut7cDaKVF0W9EtCnfDU1ipJqVIulSfzL6T75BcgSQf7j5gUCqsPImTyJsdBy51akU/Dmor8v1s7NN0ARBYCbZKjkrD/KhisViUCqVsFqtGB0dZYEACoUCJpMJgiDAarUin88jmUzC7Xajr68PADAzM4MlS5agubkZr7/+OpxOJwsm2LdvHztXW1sby5dGStvg4CCMRiNGRkbgcDjQ1tbGlC4iSfScpNNpKJVKUVHzq666CitXrsQjjzzCiovzpaeAOZMiKVdUqWBsbAyjo6PMb8hsNiMcDuPQoUMAALPZjEQiIeo/Wq0WW7duRUNDAzNj5nI5TE5OoqenB6lUCmazGfF4HOFwGC+99BKam5tZYFQVC0NKzuTMc6XU/lJjkZwSJhd8xS/mpHMp+ZkR+afAFKoGkE6nEYlEMDQ0hOHhYSQSCaRSKREpk5aH4hexpbZJ2wKIqx7wi2V+LJeO7ZUKSoQ3nZxJq7WXIhR8pzjXZhLeVEXtrOSHrSQth5xCxkd0VqqcyTnQ8n50fNmLKuTBK1rAKdLPR8zSNt4vstyKkH9gpVUBpA8ur3hJ7zff3/L5vCgHkfQ7fFQntVV6nFLnkbb/bMFkMkGr1SKfz5d0NK9iPgqFAhwOB5YsWQKDwYCHHnoIFosFhUIBa9euZZn6gTl/KlIOtFqtKCKSck729/fD4XAwk87AwADLSQYAK1euRENDAw4dOsQIIg96/+yzzwIAtm/fjpdffhnNzc3w+/04dOgQdu7cCQC4+eabRRHpjzzyCDQaDcxmM2ub2WzGxo0b8cADDwCYS1ze39+Puro6CIKAQ4cO4ZprrmHX09HRgenpaQSDQVxwwQV48cUX8cwzz8DhcECr1aJYnCvBc+LECRbwwAc+AHMVDHp7e/HGG2+c+Q16m4Afa6gv8QtKadQ6D+n4I2fupHGWQGNhqcUjRcLTZ6S00vcmJycxODiIQCDAlDM+Sl7Of4znElKlTxAEkSsJP34SgZSmHpEGkEktanIBhOXwppIz/iL411LwK//FoJS0Wm5/qf1Y2lbarxJIlbty0X+LhfR7UrKm0+mqytkC4O8Fn+qCVDKpv4Sc9A7Im+elyRlLKaVyfZSXyul7PNnmBzJ+P/5zOfVY2g65/2eLpFEJlHw+X81ztghYLBYcPXoUCoWC+WsdOHAAw8PD8/J2DQ4Owmw2A5grwUQRnR6PB52dnVCr1YjH4/D7/QDAlIVCoYB0Oo1oNIqGhgbY7XZYrVaW7qTcIjMSiTBHa5vNBq/Xy/zg3njjDTQ0NMBsNrO+mMvlEIvFWPHzbDbLiJlCoWCRnwMDA6z9u3btgsfjQUtLC2ZnZxGJRBCNRnHs2DEWXR0KhaDVapFIJNDb28uuSQ7kv1cdDxcGrxwR+DFILgiK97WWy2FG+5c6Nn/eUm2i9Bn8mJtOpxlJmpycxOTkJEKhEBKJBBN9pGMcD7ksDnx7+DlA7veQe81vk0ZvLhZvekBAqYmLv1FyKS8A+UGEZ/b0vtyxpdukfjiLlSJLQY6gyV17peeSXrf0e7Ta5k0LVciDHnC51Q8wf+CQrrDoe/znfN1K6QMsNQ3ImQqkvgz8A0/yv/Qa+P/SbdJrK0XQzhZUKhWsVquobm4V8tBqtSzLuVKpZAlo+VJ45DNlMpmQTqdRKBQQj8dhMpmwceNGrFixAq+88gpmZmawZcsWeL1eZLNZhEIh1NbWwmQyQa/X4/Dhw3C73TCZTBgcHIRKpUIkEhGlbOns7GSmRT7XGABMTU0BmAtiGB8fR2NjIyNnJ0+eRCQSgdfrZWWmgFMKtdvtRn9/PwBgw4YNKBaLOH78OPR6PQYGBlAoFKDRaBCNRhGNRnH++eejt7eX/Q4jIyPQ6/Ww2WyYnZ1FLpeT9SO68MILRaWqgsEgFAoFK2VVhTykc59UGePHDZ608EFL/PZSOUv5z+m4peZp+oxKmlG9y1wuh3Q6jUwmg2QyidHRUVa0nFJoVIJSPsP8f/76gfKZGuTaf7pj7KKS0J4tSAufS+VN1jjJpMWvfuTs1YC4A1Vi/uTrH/KJSOVUE/41nxKDXkuLV9OgxCf8JCdv8mPik9DK1SpbLMhp8uqrr8b09DSeeuqpahLaEqirq5unbknBDzI0SPCDGC9py/3RMfj/wPxIX/4/9UPpwy89Lw+pWwD1N2n/5PstmV3l9j1dUCSfx+NBe3s7jhw5gp07d1ZJWhlcdtll2L1797zfyGKxoKGhAceOHQMA3HDDDXj99dcRiUTwF3/xF8hkMnjjjTcwMjKCtrY2NDQ0QK/X4+mnn4ZCoYBGo4HdbseGDRtQX18Pr9eL3//+9xgZGUEoFILZbMb09LTonGQ6MhqNzBezubkZ09PTmJqaQiwWg8fjQTabRSKRYPur1WrYbDZRPratW7fi6NGjolQbPNauXYtrr70Wd911V9nfx2w2MxLJ/zYf/vCHEY/H8fzzz7PoT5/Ph46ODqY2AsD73vc+JJNJ7N+/HwMDA5XfmLcZyEzMjwFS9Yt8caVjGX2PJ/lS8ya/4CxnUZCCTOONjY1wOp3Q6XRQKBSIRCIIh8OIRCIIBALI5XKMzEnNl6XOQeMtVcjg53zpaznTKFWCoe1yvwv9bhqNRjQGL4Q3XTkj8D+qlFEvtJ8cKiU3PJHjf3w5ZUKqjpRSWvjjlpJDpfucKUfW6XS46KKLWK6g9evXs9VvFfLgzeX8veQhXTXxUrecelZOneIhffilx+bPzbdFbvDgr0dupVoOp6PalsM73vEOrFy5EolEAps2bUI2m8Xvfve7Mz7unzP0ej3Wr1+PwcFBUSWFWCyGyclJ9v6hhx5ir3/5y1/CbrfDbDajra0Ner0eqVQKqVQK+XwebW1tMJlMOHLkCB599FE0NDSgq6sL3d3dTJmTqurkSA/MBQDY7XYsW7YMwWAQg4OD0Gq16OzsRDweZ2Mv5UkrFosYGRmB3W5nuZ4SiQRcLhfS6TQSiQQjkN3d3ez5ePXVV2V/E51Oh0wmg02bNqG3t1dE8EgVJNcNv9/PxmadTodcLge32w2LxQK9Xo+pqSmEw+GSZs8qTkGaBgKYr/bLkRD+u/Qd+oy+wytOi1kEkmiRyWQQjUaZekZKWSqVYgsbXm2TtlHaJr6t5fiCdBHOH6PUeCtV3RQKxaIXqG8ZciZ3gwk8IeNJ09kODKAfX6FQiDon/zn9L9WxSm1fyAxZ7ruVYOXKldiyZQtMJhP27NmDpUuXMhNEFfLgHy5pEAj/utx958lYpcRMDvz+cuRMSuSozZXK93LnO5uLA2AuMeh5552H5cuX48SJE2htbYXP5zvj4/65IxQKQaFQwOFwzCtzReki5IhFOBxGPp/HmjVrUCgUEAwGmRJG2dRpHBsZGYFKpZKt2UmQ5sujOp2UWqZYLMJkMqG/v5+NZ5lMBtlslo3LXq8XdrsdWq0Wk5OTSCQSrA2USxCYM5dqtVpRAILD4WAmTDJX5vN5UU3MtWvXoqWlBY8//jhTSxKJBEtortVqMT09DZvNBqPRCKvVygpgSwMFqhBDjlBIxx2pKkWQW6yWElf4/5WAVH5aeABz/SIQCCCbzYqIGU/OSo2NctvlyGY5kAWl3OJWqj4utlLKW4KcSX3EpCjHSKXb5ViwXEeQSpRSUshPfOXMpPzEXCkW6ph8J1sIKpUKTU1N+Mu//Ets27YNY2NjuPvuu3H33XeL8iRVMR/8IELOpjzJ4u+B3H8+VLqUTF/qPpYaIPhVpZxyJj2mVG6XJomUXid/DfxxT5fkEWw2G6677jq0t7dDq9Wiu7sb1157LaxWqygXURXz8dJLL7HX119/PYLBIILBIMbGxli9wHw+j+7ubrZfbW0txsfHEY/HsWfPHlxzzTWiaE0qWeTxeKDValnKDOAUwYnFYti7dy9mZmYAYB4BzOfz2LVrF1avXs1KRckpXaTuXXbZZXjmmWegVCrxd3/3d7j//vuZKdLhcKC7u5tdQ6FQQGdnJ1avXo3nn38ea9euRWdnJx566CFR+gw+wvKqq66Cy+VCKBRCMpnEgw8+KMqj1tLSgo6ODjz22GO4/vrrUVNTg9dffx2/+tWv8PDDD4v80KqYD56cU23gcuZAfn6ke8An86bP+LGK9pW6Di3kypNOp5nfZakIcDoXzycWSggvdaOiOspkIqW28wll+awIpAjy+/IBWxRlz19zpXhLkLOFCJkc5Fiq1Owot1+p80jlylIdRY4py0WwyEEq5Z6OYiFtn06nQ7FYxLPPPgun04m2tjY89NBD8Pv9LJKritKQ+ojJERk5IiRHnORITymJXQ4LLUJKqWr8sUutaul/Of+6ShcEUtjtdjQ3N2NoaAhPP/00Ojo68A//8A9wOp2oq6vDZZddtuhjvp3AF/6ur6/Hr3/9awBzPluUOoMKiANzOcRaWloQDAYhCAJqamrw9NNPw2azMaWpubkZLpcLe/fuxbJly6BWqzE0NASz2Yze3l709vYyRUmKlpYW5rgPAIcOHYLNZkM0GhX1Dwr6aG1thdFoZKpfsVjED37wA1xxxRV44403MDY2xqIrrVYrAoEApqen8ctf/hK//OUvAQB79+7F3r17S/5GarUavb29LM8alYkC5gIA0uk080lqb2/H448/Do1Gg3Xr1kGpVKKurg5r1qw5ndvztgGZC4E5gkFR1rziCcgr+rygwJsAiZBQ4m3pgrfS8aZYLCKRSJRd7MpZF6g9/Pmk4gd/bXzUvtz10v5yLia8Tx1PRIE5cmc0GlEoFCpOLfSWIGelTHyVskw5olZO7QLkAw+kfmylOsJCk2EpyKU4kLZ3IdDvQqkzkskkxsbGWH0+lUqFWCyGRx55hA34VciDJ2KlJOnFgCdjdAzpNun+cq8rOU+5NtLgIPUBkfrLLUahLXUeQRCQTCZZLqoNGzbAYrFgfHwcv//973Hy5Ml5tRWrEIO/T7zZ0Wazsdcmk4lFTSoUCsTjcZHSpdPpWFLORCKBWCzGJppUKsX2jcfjLDqUSh7xMJlMshHecuNcoVCAz+dDMBjEyMiIyI0ilUqx4ujBYBCpVEqUq096zkwmM8+sSvU3M5kMCoUC6uvr0d/fzyI1rVYrdDodhoeHYbVaEQ6H2WRMOa6i0Sief/55jI2NwePxzP/xq5CFdMySkpqFFpKlFo/lsNBYRONXOUuEdCznyaJc2+VUNLlFtlw7eT91KaQElBdmKk3p8qbnOSt3M+RuOm2XY7P8MRciTUTEpOeQCzSQa+NCx5cqHKXKPJUiaQt1Ut6fhOqI0XcefvhhPPjgg2XbV8X8B7rU778QuZLK9fwKTU45k3631LHlPpNul3MH4BPhUuSnnKmz1DkqAfn4JJNJZLNZppq0t7ejvb0d3/3ud3HvvfdCoVDgoosuWvTx307g/cyOHj2KZcuWwWg0sigws9kMn8+HoaEhpkL09vay7wwODmLLli0IBAIsQz/vQB8KhUT+Vmq1Go2Njcw/i7Bjxw4MDQ3Nq4NJBEluTNLr9SJzK49EIgG9Xo+6ujoWUSdH/C699FKk02mMjIyIjtXU1ASNRoPJyUlEo1Fs3boVzz33HPv8ve99L06ePMlqblLutWg0ivr6evbbfP/734fZbIbBYJBtZxVz4H2i5EyPBCnx4scU6fgnF0QnN/aUshRIUWpeXIhL8Kqe3P78YlYQTmVckGsj1fGk49F4K5digz8PLT74iNZyeFPJGV+vkC6AsrITpGxXSqoqQSmJUupvJp3wFnNcqVLHf8Yzd17VoGuhP2knL9cOaeRHV1cXurq6cN5556Gmpgbt7e147bXXmNmgCnkQqaK0J5WQ40pUp0pMmXJmUuk26cNeSr6XXg8gTj0DnAr7lqZzoX0JC0VSaTQaaLXaeYPM9u3b0djYiJaWFnzlK1+B3+/Hq6++ioMHD5Y8VhVgZa6KxaLIx4qU73g8jtdeew3A3P3NZDLst1coFNiwYQPq6uoAzE0AW7ZsQTQaxejoKIaGhlBfX4+TJ0+yyaG2tpZl7V+3bh0sFgump6fx+OOPy7Yvm81i2bJlUCqVTCFVqVTweDzz+sCFF16I2dlZdHd3o76+Hi+99BJCoRCuvvpqqFQqzMzMYM+ePXA6ndDr9VCr1di5cyc2bdoEn8+H7u5u6PV6bNiwAStWrMAPfvADduw9e/awoAGLxYLu7m44HA7ceOONcDqdqK2thcfjYTmx+vv78e1vfxubN29GJBLB/v37z84N+zMGjS1khixnXeDnMv4/T2LovTQfnVTVlzMFlmsffY+2SR3uKYu/VMHi2yQlhNJFOB2Xjk2f85VjeALLp/niqyjQ9ZDZuNLAgLeMWZP/oeTSacgRNHotPY6c75n0fTkFS24iLWf2kgtA4DuF1JepFMs/HQWDQCHj09PT8Hg82Lx5MwBUyVmFkCPacqSo1IpP7r6Wel3JseVMBHKql3Q7/zkwP6KTJ2x8wfXF9D1p9m2C3W5njsSUz8dsNjMVowp5UD4uAqWmIJ8qKYxGIzweDyMi4XAYe/bsYX3iwIEDmJ6eZqWggFN9SK1WIxqNMgVrbGwMOp1OpLTxiWeJiEuz7BcKBUxOTjLzKC0We3p6mAn1lVdegdFoRC6Xw+HDh+H1eqFQKNDW1ga/38+KVw8ODsLn80Gr1cJms8Hn82FsbGyeD9qRI0dYNGc6ncbExAQEQWBF1l977TVMTk7ixIkTeOc738nyxN13333QarVwOp2nf5PeJpAbp/jxRO49/58fS/hi9JRDrVyNYjk1qxIRhvaRkkkp+OPJjbM81+A5hrQygvQ3kM4XdJ2FQkGUR7Vc2+TwliBncqiEoPGQu2jp5Ch3I/hzlTJBSY/Ft1FuP56Q8f8XCghYjBrIg3wzhoeH4XQ6YTKZ0NLSMi/BZBXzIaeCSQeccsRK7vNKH0C5gaKSiB5p++SOK0fueMdeWv3J+aFVArnVn9VqRSKRwNTUFILBICvkXfX1WRwo/cjMzAw0Gg0aGxtRX1+PRCKB6elppNNpmM1meDweZDIZjIyMYHR0FADgdDpZVBsAFpWpVquZnxblQwMgiui22+1obGxEXV0d8vk8TCYTcrkc9u3bh0AggEKhME8pi8fjWL16NXK5HA4dOiQilAcPHkRTUxM6Ozvx+uuvAwBcLhcaGhrQ3NwMi8XCFFiDwQC9Xo8bb7wRvb29OHz4sCiFBgCRT5sgCIhEIjAYDCxdx7Fjx1ggw+7du7F+/Xr4fD6W77GaiHtxKLWAlBIofjziI835esTkd1pqzuOJCz8WSgmT9HvSdtDCsNzcz3+Hr5/Jj4WUaFdOySvHM+g34PO6kWsJzwcqwZtKzsheK1c3UArpNqlyJjeRyk245Y5VbrIr1X6+DfwxeLNlKSJZSklbaHJXKpWs8KvT6YTH44HP58PevXtx6NAh6HQ63HTTTdVs2AuABgA+NJr/jCB3f6SmaPqO3CJA7rzSc8jtIzfA8FK79BxyK89SKWKk0v7prFgJ7e3tWLt2LbZt24aHH34YwWAQBoMBRqMR2WyWEYcqysNisSAWi+Ho0aOM/DY2NsJkMmFsbExUsDwQCMDv96O+vh7btm3Dr3/9a6RSKQSDQdTX17PfnKI1a2trEQwGsXTpUuTzecRiMfT09MBgMDCiFg6HmWP+0NAQOjs7YTQaRQSOzFNqtRqbNm1CKBTCsmXLEIvFcOjQIbjdbqTTaebjNjQ0hHQ6jXe9611snNdoNLjkkkvQ09ODp59+Gv39/VixYgVMJhN27tyJ973vfVi+fDmOHj2KvXv3shqKwJz7xvLly1kEqEajQSqVwpIlS3DFFVdgcnISjz76KNatW4fm5mbs27cPl19+OWw2W1U5WwT48YHGOwDzCAaRG6VSyRZ/9KfRaFh/oVx0dOxyYyS9p/PI5RQjSCv7ECni52YiXbQPTzR5UyOv+pHqJTXV8ueVmzN4MgaABcHwZlFpgvtSeMsoZ/wNkfq/EHgSRQ86P7lIgwKk35dCGp1RKTkrN6nK3UTglA2ctvGTO08Q+D/pCoA/B5mWKM9POp1GKpVCoVCAVqtFKpUSJXisYj6kytVCimk5EiT3Wk7xle5XbqAq9b1SZs5S7eT3l9b8lB5XSvoqIWlDQ0OsAPXQ0BAymQzLFF8sFqulmyoElUYi051Wq0U+n4fVakVLS4uInBWLRRiNRjQ2NmLlypX4+c9/DpvNBo/HIwowcDqdGB4ehsfjwcqVK3HixAnYbDbo9Xo2TvAwmUws0GNqaopNJA0NDZienmbpFfx+P2w2G+x2O3p7e5lp1mq1QqvVMnLmcrmwZMkSjI+Pw+l0QqlUIhQK4ZlnnoHBYEBHRwdeffVVkeI2OjqK2tpaaDQavPOd78TRo0dZCatoNIpgMAiXywWDwYCJiQm88MILSKVSqK+vZ+d/7bXXsHv3boRCIVxyySXIZDKi9CBVlIfc+MSPk/yYQvMXmbeJuMj5gJUaa0ul6pD7TE7IEIRT9ZHlrkWOZEm/k8/n510XoZT/Hd9WaRAFqWj0Ga/SVYI3lZzxCdzoRhKTlVvRS/OL8ChF0qTHIPAE71yBv65SKhm1hX/NPwzlyJkgCIjFYshkMoyMEePX6/Xn9Nr+HFCKlEv7jdQnS07uLid1L7Y95drCy+9y55SqYVK5H4CIoC1GZi+FVCrFUinQSplMaeSzVEVlqKurQzKZhFKphMPhYKY7frWt1WqRzWYxMTEBt9uN1tZWOJ1OZhq02WxobGyESqVCIBBgkZBGoxGhUIjlXNLr9SIljOpkTk9PQxAEzM7Osn6v0+lgNpsZOaNi016vF2NjY6LKBHxEZi6XQywWY1UD0uk0+vv7kUgk0NjYCL/fP+83IH+3oaEhRvIJ09PTMJvNaGlpQSKRQDabhcFgQDgchsfjgclkgkajQSwWYwQxlUqVzOlWhTwqda2gMYQ3Z9LnZB4kSBeLcueSsyrILYSlvEDu+Px76Vhfai4utRgvZUmRtl36G5SznCyEN52c8c5ztI3/X0qhkMqKUqVMjqzxkJp7FqOGLXRN/Pf46+ILoFM5FKmSUalawV9fJpNhgyYwN/mOjo5WnE/l7QopeeHJSimSA5zy1+J9CaR/lZIe6WBB2+RWe3zkDz8Q8NcgPS9/DL6fUYQqb4aQu/bFgI/I4gepxZYtebuhra0NSqUSRqMR7e3tCIVCGBoaYj5W4XBYlGIim83C7/djcnISr7zyCoaGhnDhhReip6cHAwMDeOc734ne3l5MTEyIFKkTJ04AAKtA4Pf7EY1GAcyVf1Or1Th06BBTOkl5b25uRigUYkSIzKfBYFBUWqq9vR3hcFiUqy0ajeLo0aP48Ic/DKVSiRMnTmB0dBQzMzNszOro6GClp4rFIiYmJtDb24tsNovBwUFYLBZ2vfF4HN3d3bDb7XjppZfQ2NiID33oQ3jhhRegUChYQfaOjg74fD6EQiEEg0Hk8/mq72MFKDXuSK1U/FjFz98EQRBEhb7pONKxFBAHKdF2KdkDxOob3w7pWMX7d0nbS9VKSDXjTZ1SPzP+Na+KSc9Jvw9vHePbslg3EcKbSs5GR0eRy+WQTqdRLBbh8/lgt9tF+9BFZTIZzMzMIJVKQaFQsAdW6qBaLBYxOzuLUCiEfD4PrVYLl8s1zxm0WCwik8lgenoayWSSHdPn88kesxykN5SKtFKeHwrFpY7KEzXa/0wnRimi0Wg1+ecCkJrb6Hen1b4crFYr8yOgv0wmg3g8jlwuB4VCAb1eL5tTSRAEpNNpljNKrVbDZDJBr9eLzi/nuyAlV/x+NABQUWB+UJT2Tbno5nKkdDEg/1HgVD08oPKki29XrFq1CsePH8eBAwdw4MABuFwurFmzBtFoVNZvtK6uDl/84hfxt3/7twCALVu2QKlUIpFIIJFI4Fe/+hXUajXq6+tx5ZVXYufOnQCAmpoakf8YHzhw8OBBbN26lZlFTSYTc8jv7OxEIpFgptEHHniAmVgtFgsLNLjgggswMTGBiYkJOBwO9PT0MBPrj370I9E1ZDIZHDlyBEeOHMHmzZsRjUbZpJtKpRjRv/POO2E0GjE2Nob77rsP9fX18Pl8rHLC8PAwent7MT4+jubmZjQ2NgKYC6rQ6/UYGxvD9u3bkcvlquXsKgSNBVL/VCmkcxWRbRq3yEzI51mUfk/OalHOesRv54/J+5XRPkSW+DFPOuZLU11Ixz85UkfnVyhOFTPn3ZSoHXJ54/hjLIQ3lZxFIhGWk4YImtwqO5/Ps8K9brcbgiAgGAwinU6jublZdIMpDw/5VcTjcYyPj0MQBFHG7Vwuh+HhYSiVSni9Xkbq0uk0WlpaFm0S5DuhSqVi2al1Op0onJaP4uCdFfnJ9GyYmqhNVZQG/1vL5c6jeweIZXr+fubzeYRCIajValgsFhSLRRY9Jl0QkAnaaDRCpVIhnU4jEolAq9UyIs0PPnLO/FLpnrbT8Q0GAwwGg2jwklNlpcRMqpzJkbmFwEc9S49bRWkMDAwwciIIAkKhEAwGQ8kFwtjYGB544AEAYAuBcDiM8fFxdgyv14vR0VFMTk6ycbO1tZUVCwfAFqTpdBq5XA6Tk5OwWq0IhUKw2+1sAfv666+jpqYGRqMRs7OzoijKQqGAmpoa6HQ67N+/H3q9Hn19fTCbzRWRclrcZLNZNvabzWaW8f/48eMoFApMRYxGo6LFs8PhgEajgV6vx+DgIDOJTkxMQK1WY2ZmBoODg1Cr1fNybVUxH3KKkHS7HKTKET9O8RYkaRAdfVaKuPBjFu+GVMqt40zGGrlsCnQuaR5MOZco6bjJ+4yXUg3L4U0hZ9Rgp9PJJrp0Os3MfdLGz87OQhDmasjRg6nRaDAxMcGIGDBH4ui92+2GQqGA2WzG2NgYZmZmYDKZ2LEDgQCKxSLLQg3M+XKMjY1hdnaW5Qda7M2m4/PRGlqtVjRZkYrGmzl5skbnPVOCtlim/nYDkSs+Hw3/8FCZG2C+gyyZNUOhECP4BLVajUgkgkKhwL6fzWaRyWRgtVphs9nY8cbHx1lGc2m/l05u/IAmHZz4gUSj0YgkeqkSJkeepP6fUnNEJaDjSxMwVs2a5XHgwAFoNBqYzWZG7skpvlAoiLL7E15++WUAc+Qsl8vh2LFjEAQBbW1t6O3tRT6fh9FoRDQahcfjwYoVK+B2u2Gz2RiByWQyWLFiBerr6/Hiiy9iYGCAJbImk2UgEMDU1BRTs2ZmZkQKFB2jUCjglVdegd/vRzabRSQSWXAScrvd6OrqwvDwsMhPzeFwYOnSpfB4PPif//kf0Xei0Sii0Si6urrgcDhgt9vhcrngdDpx9OhR5lfW29vL+uOrr74Kn88n699WRXlUOnfQApcnJ1JzKB/4Rj7T9F1ebeLHMunYs5CqfyZzndx3aUEuF9QkJVtSCwQw382JEoFX2qA/OkZGRgQA1b8/0t/IyMibcZv/ZLFr1y4BgPDggw8K0WhUyOVysvtFIhFBrVYLd9xxh2h7JpMRzGazcNttt7Ftd9xxh6BSqYRIJCLa9+tf/7oAQBgeHi7bpp6eHuHd73634PP5BJ1OJ9TV1Qk33XSTEA6HBUEQZO/7Bz/4Qfb90dFR4dZbbxW8Xq+g1WqFjo4O4cc//rHsdf/yl78U7rzzTsHn8wlGo1G4+uqr57VvofZUce5w/vnnC+eff75om9frFd7znvfM23fZsmXC9u3b2fvvfve7AgDh6NGjov3+93//VwAgvPDCC2XPPTExIdxyyy1CXV2doNVqBb/fL7zrXe8SBgYGBEEQhKampnn9cNu2bez7oVBI+OQnPynU19cLWq1WaG1tFb75zW8KhUKB7TMwMCAAEO6++27h3/7t34TGxkZBr9cLW7duFQ4fPryo9lRxbnAuxshS+M///E+ho6NDMBgMgt1uF9auXSv8/Oc/FwRBEL70pS/Jjn38/X/ggQeE888/X9Dr9YLD4RBuuummeePZtm3bhJUrVwpvvPGGcMEFFwh6vV5obm4Wvv/97y+qPWcTb4pyVltbi5GREVgsFigUCuzbtw+XXHIJvve97+F973ufaN/x8XGsWLECX/7yl/GpT31K9NlHPvIRPPXUUxgcHAQAfOITn8Cvf/1rjI2NiVZt/f39OO+88/Ctb30LH/3oRxd1TDn84Q9/wHXXXYdt27bh6quvBjCXGXt6eho/+clPMDAwgPvuuw/33XcfPv3pT2P58uUAgEsuuQRerxe//OUv8dd//dfYvn07rrzySiSTSfz4xz9GJBLBCy+8gKamJgDA3/zN3+Dhhx9GXV0d1q9fj3Xr1uGZZ57BE088gc9+9rP44he/uGB7vv3tb6O2tnZR96eKOdx6662Ix+NQqVS46KKLcPfdd2PdunXs88OHDyOfz4u2AXOKW1dXl6hczP79+7Fs2bJ5ps4NGzYAmFNPGhoaZNuRzWZx5ZVXIpPJ4BOf+AT8fj/Gxsbw2GOPIRwOw2az4YEHHsCHP/xhbNiwAR/5yEcAAK2trQDmkndu2rQJCoUCH//4x+HxeLBz507cdtttiEaj856Br33ta1AoFPjc5z6H6elp3Hvvvbjssstw4MABGAyGitpTxbmBIAiYmprCypUr2TaKlpT2Q2Cuf/3+979n7/fv3w+TyYQVK1bM248+37JlS8nzX3/99Th69Cg+8YlPoLm5GdPT03j66acxPDyM5uZm3HvvvfjEJz4Bs9nMxidKqptMJrFt2zaMjY3hox/9KBobG/HSSy/hzjvvxMTEBO69917RuX76058iFovhYx/7GNLpNP7jP/4Dl156KQ4fPsyOuVB7qji3OJtjpBz+67/+C3/3d3+HG264AZ/85CeRTqdx6NAhvPrqq/jLv/xLvPvd70ZPTw9+8Ytf4N///d/hdrsBgAV/fO1rX8Ndd92FG2+8ER/+8IcxMzODb3/729i6dSv2798v8nEPhUJ4xzvegRtvvBHvfe978X//93/4m7/5G2i1WnzoQx+qqD1nFWed7p0GXn/9dQGAcP/995f87Kc//em8z+644w4BgJBOpwVBEIQdO3YILS0t8/ZLJBICAOHzn//8oo8ph09+8pOC1WoV8vl8yX0efPBBAYCwa9cu0fZYLCbY7Xbh9ttvF22fnJwUbDabaPsHP/hBAYDwiU98gm0rFovCjh07BK1WK8zMzFTcnioqx549e4Trr79e+PGPfyz85je/Eb7xjW8ILpdL0Ov1wr59+9h+dI9379497xjvec97BL/fz96vXLlSuPTSS+ftd/ToUQGAcN9995Vsz/79+9kqtRxMJpNILSPcdtttQk1NjRAIBETbb775ZsFmswnJZFIQhFOr4bq6OiEajbL9/u///k8AIPzHf/zHotpTxdnHAw88IAAQqZ7nYoyUQygUYopWOaxcuVKklhG+8pWvCCaTSejp6RFt//znPy+oVCqmZpByZjAYhNHRUbbfq6++KgAQ/v7v/35R7ani7ONcjJFyuOaaa4SVK1eW3efuu++ep5YJgiAMDg4KKpVK+NrXvibafvjwYUGtVou2b9u2TQAg3HPPPWxbJpMRurq6BK/XK2Sz2Yrbc7bwlg+jIh8CuchD8uehfVKpVMX7VXpMOdjtdiQSCTz99NMVXwfh6aefRjgcxnvf+14EAgH2p1KpsHHjRuzatWvedz7+8Y+z16R+ZLNZPPPMM2fcnirmY/PmzXjooYfwoQ99CO9617vw+c9/Hq+88goUCgXuvPNOtt9C/YjvQ5X2TTmQEvXkk0+KfHMqgSAI+PWvf42rr74agiCI+tyVV16JSCSCffv2ib7zgQ98ABaLhb2/4YYbUFNTwxSYM2lPFaeP7u5ufOxjH8MFF1yAD37wg2z7uRgj5WAwGKDVavHcc8+xRLmLwYMPPoiLLroIDodD1A8vu+wyFAoFFoFJuPbaa1lBd2BO3du4cSPrh2fanipOH+dijJSD3W7H6OgoK/+1GDz88MMoFou48cYbRf3N7/dj6dKl8+ZatVqNj370o+y9VqvFRz/6UUxPT7M6r2fSnsXiLU/OKCUBn8eLQPl1aB+DwVDxfpUeUw5/+7d/i2XLluGqq65CfX09PvShD+GJJ56o6Hp6e3sBAJdeeikrXkx/Tz311Lx6mEqlEi0tLaJty5YtAwBmej2T9lRRGdra2nDNNddg165dzMF9oX7E96FK+6YclixZgn/4h3/Aj370I7jdblx55ZX47ne/i0gksmC7Z2ZmEA6H8cMf/nBef7v11lsBYF6fW7p0qei9QjFXrJr625m0p4rTw+TkJHbs2AGbzYaHHnpIlJT2XIyRctDpdPiXf/kX7Ny5Ez6fD1u3bsW3vvUtTE5OVnQNvb29eOKJJ+b1w8suuwzAwv0QmBv7qB+eaXuqOLs40zFSDp/73OdgNpuxYcMGLF26FB/72MewZ8+eitpDQSEUXML/HT9+fF5/q62thclkEm2TzrVn0p7F4i1TvqkUampqAEA2R83ExAScTidj5TU1Ndi1a9e8VAP0XfK9Wswx5eD1enHgwAE8+eST2LlzJ3bu3In7778fH/jAB/CTn/yk7PVQ9MYDDzwgGz1UcSTHWWpPFZWjoaGBJbm0Wq0L9iPe16+mpgZjY2Oy+wFY0C/wnnvuwS233ILf/OY3eOqpp/B3f/d3+MY3voFXXnkF9fX1Jb9H/e3973+/SG3hsXr16rLnPpvtqWLxiEQiuOqqqxAOh/HCCy/M6yvnYowshU996lO4+uqr8eijj+LJJ5/EXXfdhW984xv4wx/+gPPOO6/sd4vFIi6//HJ89rOflf2cJsLF4EzaU8XZx5mMkXJYsWIFTpw4gcceewxPPPEEfv3rX+N73/se/t//+3/48pe/XPa7FC26c+dO2XqWZrN5EVd25u1ZNP4oxtMFUM7nTBAEwePxlIxE4v14vvOd78hGIv385z+fZ/eu9JiVoFAoCB/96EcFAEJvb68gCILw0EMPyfqckf/Ok08+ueBxyefsxIkTou07d+4UAAi/+MUvKm5PFWeO66+/XtDr9SyyLBwOl41E+tCHPsS2feYzn5GN1vza175WUbSmFHv27BEACF/84hfZNrPZPM/nLJ/PCxaLRXjve9+74DHJ5+zOO+8UbS8Wi0JNTY1w5ZVXLqo9VZw5UqmUcNFFFwlGo1F46aWXSu53LsbIStDT0yMYjUbhfe97H9vW2dkp63PW0dEhXHDBBQsek3zO5Prsxo0bheXLly+qPVX88XAmY2QlyGQywo4dOwSVSiWkUilBEAThX//1X2V9zr71rW/Jzp9y2LZtm6BWq4V4PC7a/v3vf18AILz88ssVt+ds4S1v1gTmInIee+wxjIyMsG3PPvssenp68J73vIdtu+aaa6DRaPC9732PbRMEAffddx/q6uqwefPmRR9TDrOzs6L3SqWSqQ8k35I8ypcyAYArr7wSVqsVX//612Vzp/DlVgjf+c53RNfzne98BxqNBtu3b6+4PVVUDrl7cPDgQfz2t7/FFVdcwfKP2Ww2XHbZZfjZz34mShj6wAMPIB6Pi/rRDTfcgEKhgB/+8IdsWyaTwf3334+NGzeWjNQE5nI7UbZ9wqpVq6BUKkX312QyzetvKpUK119/PX7961/jyJEjFV0rRckRHnroIUxMTOCqq65aVHuqODMUCgXcdNNNePnll/Hggw/iggsuKLnvuRgjpUgmk8z8SWhtbYXFYlmwHwLAjTfeiJdffhlPPvnkvM/C4fC8PvXoo4+K1ObXXnsNr776KuuHlbanirOPczFGykE6t2m1WnR0dEAQBDZ/lppr3/3ud0OlUuHLX/6ybMJa6bHz+Tx+8IMfsPfZbBY/+MEP4PF4sHbt2orbc7bwppo1v/Od77DM1gDwu9/9DqOjowDm0mKQ4/EXvvAFPPjgg7jkkkvwyU9+EvF4HHfffTdWrVrF/GYAoL6+Hp/61Kdw9913I5fLYf369Xj00Ufxwgsv4Oc//7lI2qz0mHL48Ic/jGAwiEsvvRT19fUYGhrCt7/9bXR1dbEQ9a6uLqhUKvzLv/wLIpEIdDodLr30Uni9Xnz/+9/HX/3VX+H888/HzTffDI/Hg+HhYTz++OO48MILRWRMr9fjiSeewAc/+EFs3LgRO3fuxOOPP44vfOELLFy4kvZUUTluuukmGAwGbN68GV6vF8eOHcMPf/hDGI1GfPOb3xTt+7WvfQ2bN2/Gtm3b8JGPfASjo6O45557cMUVV+Av/uIv2H4bN27Ee97zHtx5552Ynp5GW1sbfvKTn2BwcBA//vGPy7bnD3/4Az7+8Y/jPe95D5YtW4Z8Po8HHniAES/C2rVr8cwzz+Df/u3fUFtbiyVLlmDjxo345je/iV27dmHjxo24/fbbWS3Dffv24ZlnnhGV8QHmkkNv2bIFt956K6ampnDvvfeira0Nt99++6LaU8WZ4dOf/jR++9vf4uqrr0YwGMTPfvYz0efvf//72etzMUZK0dPTg+3bt+PGG29ER0cH1Go1HnnkEUxNTeHmm29m+61duxbf//738dWvfhVtbW3wer249NJLcccdd+C3v/0t3vnOd+KWW27B2rVrkUgkcPjwYTz00EMYHBxkqRCAOR+mLVu24G/+5m+QyWRw7733wuVyMbNope2p4uzjXIyRcrjiiivg9/tx4YUXwufz4fjx4/jOd76DHTt2sKAlIk5f/OIXcfPNN0Oj0eDqq69Ga2srvvrVr+LOO+/E4OAgrr32WlgsFgwMDOCRRx7BRz7yEXzmM59h56qtrcW//Mu/YHBwEMuWLcOvfvUrHDhwAD/84Q9ZovpK2nPWcFZ1uEVCLmEh/UklyiNHjghXXHGFYDQaBbvdLrzvfe8TJicn5x2zUCgIX//614WmpiZBq9UKK1euFH72s5/Jnr/SY0rx0EMPCVdccQVL6NnY2Ch89KMfFSYmJkT7/dd//ZfQ0tIiqFSqeSbOXbt2CVdeeaVgs9kEvV4vtLa2CrfccovwxhtvsH0++MEPCiaTSejr62Pt9Pl8wpe+9CVR0sZK21NFZfiP//gPYcOGDYLT6RTUarVQU1MjvP/97y9pIn7hhReEzZs3C3q9XvB4PMLHPvYxUSoKQiqVEj7zmc8Ifr9f0Ol0wvr164Unnnhiwfb09/cLH/rQh4TW1lZBr9cLTqdTuOSSS4RnnnlGtF93d7ewdetWwWAwzEtCOzU1JXzsYx8TGhoaBI1GI/j9fmH79u3CD3/4Q7YPmTV/8YtfCHfeeafg9XoFg8Eg7NixQxgaGlp0e6o4M1B4f6k/Kc7FGMkjEAgIH/vYx4T29nbBZDIJNptN2Lhxo/B///d/ov0mJyeFHTt2CBaLZV4S2lgsJtx5551CW1uboNVqBbfbLWzevFn413/9V5augE9Ce8899wgNDQ2CTqcTLrroIuHgwYOLbk8VZx/naoyU4gc/+IGwdetWweVyCTqdTmhtbRXuuOOOee4hX/nKV4S6ujpBqVTO4w+//vWvhS1btggmk0kwmUxCe3u78LGPfUxk7pRLQtvU1CR85zvfOa32nA0oBKFa2+etiltuuQUPPfSQbPmWKqo423juuedwySWX4MEHH8QNN9zwZjenircpBgcHsWTJEtx9990iZaOKKs4VLr74YgQCAVnXjzcLfxI+Z1VUUUUVVVRRRRVvF1TJWRVVVFFFFVVUUcVbCFVyVkUVVVRRRRVVVPEWQtXnrIoqqqiiiiqqqOIthKpyVkUVVVRRRRVVVPEWQpWcVVFFFVVUUUUVVbyF8KYkoS0WixgfH4fFYhHVd6vi7EIQBMRiMdTW1rKMzVVUUUUVVVRRxVscZz1zWgUYGRkpm1yx+nd2/0ZGRt6M2/yWh0KhYL9RQ0ODYDabRb+byWQS6uvr52232+2C1+sVXC6XaLvVahX8fr/gdDpF2x0Oh+D3++cdw+fzzTt2U1OTYLfb5x23paVFUKvVbJvFYhFqa2sFr9fLtimVSqGurk7weDzzzlVTUyP4fD7RdoPBINTU1LBkpLRdr9cLLS0tgsfjYUkdVSqV4Ha7hebm5nnt9fv9gslkYvs5nU6hubmZfVepVL7Zt/otDYfDIdTX14vupcViEbZs2SLodDrR793S0iJ0dXXNS+Bts9mEtrY2ob29XXR/N23aJLq3KpVKaG1tFc4//3zB7XaLjlFTUyO0tbWJju33+4W6ujrRebq6uub1Z6PRKCiVSqGzs1Nob2+f92xs2rRJaGhoEG1zuVzCunXrhLa2NtlrWblypWj7li1bhNraWvZeo9EIzc3Nwtq1a9k2hULBEo7SNp/Px56pKkqDnv3Ozk7hH//xH9nvd/LkyXlzyoUXXij88z//s/C73/2ObaP7eN111wn//d//LeqzAIRPf/rTwm233SbqG9Q39Xq90N7eLlx77bXsM6o7fP755wu33377vHEHgPD3f//3wsjIiGCz2USff+tb3xI6OzvZ+7Vr1wpf+cpX2HNB23fs2CFce+21rH9s3bpVuP/++wUAwj/90z8JH/nIRwQAQmdnp2A0GkV996677mLP7LZt24T9+/eL+vvjjz8uatOnPvUp4YYbbqi4H74pyhmVOVAqlVAoFCgWi3+0c/NKXSnVTm67dNtC7xfTjtPdn7ZJ/wOAIAgoFotIpVJnv6zEnwm8Xi8ikQjS6TRGRkag1+uh0+lYXb5EIoFisQi1Wg2VSoVCoQAArByXVquFRqNhNdWi0SgKhQJUKpVoezgchs1mg16vZ7UAo9Eo9Ho9tFqtqE2zs7NQKpUwGo1IJpOsHUqlEgaDgbUpHo9DqVRCpVJBq9Uim82iWCwiFArBbDbDbDYjmUyyfXO5HAwGA6xWK9LpNLLZLFKpFJRKJXQ6HUwmE/L5PIrFItLpNEKhEBQKBSwWCyKRCAqFAhKJBHQ6naht4XAYGo0GRqMR6XQaSqWSnVej0UChUJQtCVTFqWeV/53i8Th6enqQzWbZNoPBgFAohEgkwn5/QiaTQTgcFinkqVQKQ0NDUKvV7DiFQgHj4+OYnp4W1ToE5vp1JpNhxzAYDAAgqnkZiUQwPDyMTCYDhUIBQRCg0+nYON7f3w+VSjWvluHw8DCy2SwMBgNSqRQAIBaLoa+vj107PV/JZBKzs7Ps/ITe3l6kUimo1WrWpmg0KjqXIAiYnJwUbZuammLPShWl8fd///f47//+bxw5ckT0+91xxx3sXhP27NmDAwcOiMptqdVq9tnU1BTbPjw8DAC455572DaDwYDa2loYDAb09vZizZo1sFqtmJycBAD4fD4cOnQIwFzNTofDIWprJBIBAPzv//4vXn/9dfaesGvXLtjtdvb+6NGjaGlpgV6vR2trKyYnJxEIBDA1NQW9Xg+bzYZwOIzZ2Vns2rULwFz9T+qD0uS0dXV1OHLkCKanp2E2mzE6Oioqk/bKK6+IyjACwL333ovF4E2J1oxGo7DZbFCpVPNuuvT92cbZIGeLJWaLIWKLPZYcMaOBUhAExONxRCIRWK3WitvwdkFjYyMikQhisRgEQYBWq4VWq4UgCEgkEmw/i8UCQRCQz+dFhZaNRiM0Gg1SqRSb/FQqFXQ6HTQajWjAMBqNUCqVKBaLbGJVKpWw2WzIZrNIJpMQBAEKhQImkwlqtRqpVIoRRa1WC5PJhEwmg3Q6jWKxyMikUqlEKBQCMHfvPR4PCoUCstksm4BVKhV75jKZDJLJJPL5PFQqFfR6PUwmE1KpFNLpNHK5HPR6PfR6PTQaDStKrVQq4XK5GFFLp9PQarUwm83Q6/VIpVLsuEQmqV/KFcKuYg5EjjUaDeLx+DzipVKpoFQqGbmXK7BMJF2lUokqihiNRigUCuTzeWSz2XljK90jOif/DGi1WtZnqX8RaGFCbaM+zF+TSqUSHVev18vuS8cRBIH1d7VaDZPJhGw2i0wmg2KxCKVSCbVazfqUIAhQq9XQarVIJBLsd/F4PEgkEshmsygUChAEAUqlEmazed4kXsUpvPrqq7j++utFxeYJ7e3tiEajmJiYAADZOXrz5s146aWXZI9tMplEY+qaNWtgMBiQz+cxMTGBVatWQaFQoK+vDxMTE7DZbDCbzeju7gYAdHR0QKlUYnZ2lo1T0qL3PGpqatDY2AiLxYJnnnkGANDQ0ACVSoX6+nqk02ns3bsXLpcLer0eKpUKQ0ND8Hg8cDqdOHHiBIC5MXrTpk3zrmvLli0QBAF79uxBc3MzYrHYvKLoAEQLCYLRaBT9FqXwphY+BypTqRYLKdk702OX+87pHv9M9pMjinLtqPrzlcfIyAiAuYnDYDAgmUwimUyyVbZCoWBKEIG28RMerfhVKhVTAGiSoe2CILB9FQoFU5Xi8Tj7Pm3P5/PI5XJMxVCr1dDr9UgkEkzdMhqN7FzxeBwKhQJqtRoGgwHZbJb9AWAqn1KpRDweZ+0gcqlUKhGLxdjkZjAYoNPpUCgUGBE0Go1MgSH1TqPRML/RdDqNVCoFQRCg0WgY4chkMvMUmirE4O/VypUr0dPTg1wux/olqZy5XA5KpRIajYaRYX7g1+l00Ov1TEU1GAxobGzE0aNHZc/r9Xpht9uRSCSQTCaZQkxKHinBUtjtdtYfJicnUSwWmfWD1AoiVQQ6dj6fn0c+PR4PUqkUI5VqtRpGoxE6nY4tnNRqNdxuN2ZnZ9lvZTAYoFar57WRnpl0Og1BENDV1QWVSlUlZgvg4MGDWLZsmSw5S6VSWL58ObZt24aHHnqIjRWk2q9cuRLvfOc7S5KzRCKBO+64A6+++ip2794NlUqFV155hX1O53Q4HIjFYmzMaGtrYwQnnU4zAmQ2m0XkjCdBSqUSExMTjEjec889+Kd/+ic23icSCdTV1WHDhg149dVXRe2cmZnBzMwMe18sFpFIJOB0OplCPD4+jsnJSaxfvx6JRALxeBxms5lZXZqammA0GvHiiy9CEAQ4nU4Eg0HU1tZi48aNuPzyyyu6H28J5YzHuWhOKQKzmO+We13Jsc8GaatUNQNO/Y7RaLSqnJUA/VZklksmkygUCkwtoH3IVMmTMkEQ2KRBRDiXyzH1i+/bxWKRkTLe5EmTml6vZ8egAYf2lZpsiDiSkkdt0Gg0bBspYiqVik1e9EffV6vVbH+a3IjAEZEEwMye9P1sNsuUQbVajUwmg1wuh0KhwNQ2+v0ymQw7Pj9RVyEG//zq9XpYrVYIgoBoNAqj0ShSSwEwUmwwGERmaEJzczMGBwdlz0XqgVKpRKFQQCAQQD6fh9FoFB2Dt2BoNBpotVp2T30+H0wmE7RaLSYnJ5lKJQiCyDzJ96dMJsNULq1Wi2g0ytQwh8PBTI60IKCFCgDR9ZtMJhiNRraAoedNoVCIFgFerxcajYZN+kqlEl6vl03YVczHVVddhWg0itHRUQwPD8PpdMJoNGJ0dBR6vZ495y6XS1YlAsBU12KxiIaGBvj9fgQCAZw8eRKf/exnodPpcOjQITz11FPMvN3V1YUDBw7MO5bH4xERpbq6OiQSCdZ3pLDb7dBoNJiZmcF1112HiYkJvPLKK+jq6kI6nUYkEsHExAQjlOUgt097eztWrVqFo0eP4tixY/O+4/P5EAwGodfroVarEQqF4Ha7YbfbIQgC+vr62L6V8Jw3NYSPGkgT3bniidLj0sMs9dFa7Oty7+XaUMl1ltuv1PtK2luFPKgP8ISrWCyKiJXc/vxvX6ovke+OnJLL98FSzwF/LmoTTxBpElSr1WwSpAGUlDSVSoVischIG5E+tVot2s6rhUTE6BpoG6l2RMyAOYWEVqzUDtqeyWSYeayK0vB6vew3IgUym82KyAePXC7HVFvah4dUSdLpdNDpdOz4pNQlk0lGrKTR3PwxVSoVjEYjDAYDM+NHIhEEg0FGzqmd/Peon9Cx6RkzGAxsf41Gg2QyyUyXBoMBuVyOmfRpEcM/E0qlkplH6dy06CEQmXO5XADmnuNShKKKOTzxxBN46aWXGCFyOByw2+2iBR5td7vdsj582WyWuXZMTk5iZmaGkeaRkREEAgEYDAY4nU7Wr/1+P5xO57xjSe8XmQL5MZlUegBwu93wer0A5vosqXsHDhxgWQuojQStVsvawftm19TUsNc6nQ7Lly+H3W5HKBSap/wCYP7AuVwOsViM+f7Sc22z2eZ9ZyG86WbNhYhKKUgnQzlfNTkVih5sAg0Y/Pnk1Dx+opQ7d6k2l1LCFruflBQs1MYqKgP9bmSSoz9e+SLiUygURIqaHJnjQf4uUjWNlC2e4NAERP2Tjs+TJKk6RuYbrVbLJl0KYODNSLSdJkNSN8jsQ+oY71dHkx2pfPzkSUpaMplENptlZja9Xo9MJsN82sh/jnfMrWI+zjvvPMzMzDBTDK8AUR+S9q9YLIZoNMreE9kuFosYGRlhpFwQBNTU1CCXy2F6elqkRBAEQRBNhGSeIYKvVCqRy+VYPyingpKZnCboXC43T4Gg5wmYmxxjsRgLTnE4HGx/qTuB1WpFsVhkQTz8ZyqVCmazGYIgIBwOIxqNIhqNYt26dVCpVJienpb11atiPlKpFOrq6pgfZGdnJ4aGhpiyWl9fD6vVCqvViqGhIRQKBdhsNixZsgQHDhxAOp2G2+1GIBAQqUVPP/008vk8wuEwbr/9dgBzqmgkEsGFF16I48eP4+TJk2z/YrGIlpYWTE9PIx6PIxwOi4JE3G43bDYb1Go1hoaG0NDQAK1Wi6NHj2LPnj0ilXRsbGxev5UqzGvWrMGLL74IAFi6dCkmJibg8Xhwww03YO3atXjkkUfwyCOPAJgjckuXLsWRI0dwzTXXYGpqCrt37xYdv6OjAyMjI4hEIjAajdi2bRtGR0dFv0k5vKlmTVoFlYNc8xZrniSFQqlUQqvVwmg0MnmdHnTeH6icn1clPnJnMwBgoeOXMm0SKYjFYlWzZgk0NzdjZmZG1qeMV71oggQw7zMiPTwxJsLD3wc6Nk1a5GyvVqsRjUaZCsBjId9J/hykXikUCrZaKxaLyOVybF8yZZKZlVfLeL8h3qRK+9O1kzpBZiU6H50zk8mw54hflUodyqs4BSLNWq0WyWSSKQG8mku+fHTv+AUET+IJNLEWCgVG9qjP0SJDo9Ewn7ZwOAyXy8UCPfioSuCUwsBPcNRPqH/odDqRcgKAkTpalPDty+fzyGQyjFQVi0Vks1nRNfEk02azMfWWCB79UWAMmYNpkUJEYmpqClNTU9WFaxmUmovsdjvWr1+PUCiEgYGBeYqWyWSCy+WC3++HRqNBT0+PaBFA99Pv9zMT9/bt23H8+HEMDw8zB/1EIoGZmRnY7Xa28PN4PMz5n/eJdbvdzIds06ZNCAQCTBGOx+NMdQXmVDAiaj6fDzU1NRgZGcHs7Cz8fj9isRhT5fx+P9xuN/r6+pi7iE6nw8TEBBwOBy6++GIcPnwY0WiULSr8fj/zw9y3bx9aWlqwevVq9Pf3swV1MplEd3c3Nm/ejE984hO4+eabF7wfb2nl7Ey/I2eCAuZurtlsht1uh8lkYn5ZlAJAbqXKn3shQlXJPtJrKbf/QmqddFt1AKoMgUBAlhDxJEZqUqF96H85RZWHdD+j0QiTyQSLxQKj0Yh4PM4e9lLnlLvnvDJHfzRZSrfL7S93LdJ9iYySeZPAq4tSlZD8znhyWkVpkPnO6/UiFAohl8uJiDMRcFI0iVwD803vvN8XLQBIEaV0J+Q3SH3RarViZGQEarUadrudqV50TiJFBCL7vD8imdTpNfUd3seNSDsdE5gzV8ktMpVKJfO/KxQKiEQiomPR8en3IDJLvm6FQgGDg4Pw+XxQKBTMxFmFPJqamjA0NARgTkU6ePAggLlI676+PhiNRvh8PhE5UygULKCExjDpmErjyeTkJLRaLRoaGhCNRqHRaGC1WjExMcFSopjNZmzbtg0nTpxAd3c3I2vk8wbM9WmbzYbx8XFmqszn8yxlBwBYrVacf/756OjoEKloRNKBOR82PviBFgnBYJCZ1nmEQiEcP34c+Xyekbjjx49jcnIS8Xgca9euRV1dHbLZLA4cOACXy8WUQSKSBw4cwL59+yoiZ3/WaeP5iYFXAHQ6Hex2O+rq6tDY2Ai/3w+Hw8FWh/zExB+r3Hkq2VZpWys5h5RwVrF4kI+AVqtlK33glNlFqibx5IcnUAR+m1wf4rfrdDpYrVbU1NSgoaEBPp+PSfR0LOn3+HbQPryqRZM1KSOkrki384o1rwzy26X78god7UsmLFLo+GgpIgi8b1wV5VEoFGC32xmxIQLG32+6p3xuMSIper0eZrMZGo0G2WxWd8oO3wAAlU1JREFU5HfF+2NRv6F+bjQa0d7ezvoYmbQsFgv0ej0LPOBB+1IksDRqkj6n85CJ1Gg0wu/3s89oX2oTr9gScbRYLDCbzew3IqJIv5FCoWA+jplMhv0O9LtNTU0hm82iqanprN+zPyd85zvfQUNDAwBg3bp1WLlyJfusv78fgUAADocDy5cvZ3Mm5TnjSY0UfN/JZrOw2+2YnZ2FXq+H3+9HJBJh/UWj0aCrq0vk82UwGEQ+W7TvjTfeiBUrVrB0UTysViu6urqwY8eOknlUv/nNb7LXWq0Wy5cvRzqdxvj4+Lz0F4Tu7m7Mzs7C5XKhtbWVXX88HocgCFi5ciVCoRAGBwdZahyeACaTSfz0pz+VPbYUb7pZc7EmysVCSmKUSiVqa2tRW1uL5cuXw+FwsKSHhw8fRiAQYCkLaFChiamUCZFHpdez0H6LMZ+WMrlWzZrl4Xa7EQqFmAlEr9czCZrvL1L1iidh5RyppUoafUa5dvx+P5YuXQqz2YxEIoFAIIDjx48jGAwyFVfuGZG+l5pQeWVMav4pp6TxhE16DF4FI8JH28nURr+jTqeDzWYT+SlV0xiUBt1PIrQmkwnAKQdoIjXUN3kSRAmL0+m0aEKR5lfSaDRobW1lkZ2UHqC+vh4WiwVarZapZz09PaIcewS9Xs/8HfnjUk6y+vp6lusuEolAq9WynFQU5adUKhGJRFhaELVazV4TqaeAAQqOIJBfpFqthtPphNfrRTQaxdDQECMFlHMvFovNa7/D4UAwGDyje/XnjL/+67/G888/z3KLXXPNNWhsbMQLL7zAoim1Wi1qamqQz+eh0WiwbNkyvPDCC8hms3A4HMjlcuxZJ7XL6/Vix44dePHFF5kvKil0Go0GS5cuhdPpRDgcZsleGxoasGbNGjz22GP48Ic/DIvFgn//938XtbetrU3ko9bZ2QmdToe9e/di5cqVLIUM5b1LJpMwm83w+/1Qq9WIx+PQ6/UYGxubp5JJcd111yEcDrNk5QMDA0gkEjCbzaK8gjU1NUzxplx/wWBwnq9nJbTrTTVrVmoiPJsoFosIh8NQq9WwWq0wmUwso3qxWMTg4CCmp6cxOzsr8jUq1e5S5qxKr6uc+VT6+WLMpVUsDJLnyQxChIgH/ea8EgDMN3HKoRS5KhQKrA/a7XZmYid1YGRkBNPT04w4LtTHpAuQUqRQ+n2pGidn4pReI39OKUnlfdLI74cCEqoojfb2dgSDQfabkWkbAIuIi8fj81Rcuk/kvE9pDHgVk1AoFNDX18fyoNHCLZlMMmXCbDbD6/Uin88jGo1iamoKqVQKNTU1LOeZVqtlwSSFQoEpZqFQCIFAQNQ/qE9Q0Aodg66DTKAWi0VE8mkC5xcd0msJh8MYHR0FABaQAsyZt1KpFFQqFex2O9xuN8bHx5FMJqt+jwvg5ZdfZsQMAPbt24dUKoXzzjuPkTPqKwMDA4jFYpiYmGAkOBAIwGQywe12s3s+PDyMiYkJPPDAA6ivr2fBS8Ac2fb5fLDb7WhtbYVarUZDQwP27NkDh8PB7ukvf/nLedGOOp2OETMKYNm+fTu8Xi/27t0LhULB8otRDktgThWmKGUa80upZISLL74YSqWSmVdHRkbYwunaa69Fd3c3hoeHMT09zQIF7HY7fvGLX8Bms80jftLKF6XwlvM5K+e3cybgH/JUKoVwOIzp6WnU1NSwsjbNzc1MJqeEpPzkWIqUyZGmSonU2SBccu2ronKQyiD1qQHk06fI+WbReylKESlSF2ZnZ0V9EDhFANPptIgwno6fYTklT247D7ljlzsGKWqUe4tIRLVsTnnQCpt8waSRiLxLBoFIEpmUKaqSIisJJpMJgiCwJLb8ZxRVazKZGIlyOBzQaDQIhUJMkbNYLAiHw0in0ywKmO4zKcmk5vF9gieYCoWiZLQkn8+PFDP6XSgpM78QoP5FIDcBIqVEIvV6PZxOJ9RqtWhCrUIefPQvMLdIVCgUWL58OdtGaU/omZaqk0ajES6XS0SeaD8i89QPbDYbLBYLE0GMRiOWLVuGiYkJWK1W1qfi8bhInXI6nSznnkqlgtvtxtjYGKLRKKxWKzZs2MAiO+12O8u3CMz5dlLib6PRyMpFSbF582acOHECHo+H+d+RCZ9UP2AuqpPcPaanp1mAIe86QM8R4cILL6zofrzp5KwUzoW1lU+JQHI4JYjT6/VYsmQJLBYLfD4fczDkzUt8u+TIGm1fDKpk6s2D3+8X5a3R6XQsszgfucv7xvCQe1+KoEl91nK5HMLhMIaGhuBwOKBQKGA2m9HW1gaLxQKPx4N8Ps8kd94BvFKlVk4Bk5rApYRT+hn/vhQR5K+NoqQop5rdbq86Yi8AcrymZMQEMpkoFHMpSfR6PWZnZ2UJEG9u5CMtKfqRFC4pyQsGg+w+WSwWeL1erFixAmNjY5icnMTo6KgoizrvV2gymdhEpFarYbFYWNoWAOxZogmc1D0ql0NjKLWBCCIhk8nAYDCIIoF587vX60Umk0EwGEQsFhMpbQrFXHqc48ePo6WlBTU1NSUn4irmsHXrVhQKBYyMjODyyy/H008/jeHhYbz22mv44Ac/iKeeegoTExM4ceIENm7cCL1ej+effx7A3NjpcrmwevVqxONxZvYjdHV1ifLjEeFLpVIYGRlBX18fXC4XVqxYgYsuugiTk5MYGRnBXXfdhX379uHFF19EJBJBZ2cnampq0N3dzaJwyafr/vvvB3Cq4oucK0V/fz9rb6nyT01NTWhsbERTUxOLQN6zZw9LLUTRz1qtFmNjY3jyySdZugw+4GDz5s2wWq2wWCxwuVy47777AFReyu4tR87OtQscP/glEgn09fUxZm21WuHxeOBwOJgP0sTEBGZmZkSpCvhjlZsAy6mC/P6lPpMeT+740teVqClVzEGawJMciikiTs7xfyFiJDUV0jb+vvABB5FIhPXBYrEIi8WCmpoaOJ1OaDQa7N+/H1NTUyyTuxyJKtUW2i4lV/z+cu8rUYHl+hatdCkamnJc8VFUVZQGKVNE1olgCcJcrVda7ZNZEZBPZqxQzBWsJxMfgdQOqsNpNBqZGXVgYIARJoVirj4rKQ9qtVqUJ4r6L5VioueEzIaUKiaVSrHzULqiTCbDcuNJ/Tmp/Q6HQ+RzRimQzGYzUwCpgLtOp2MJTGlRoNVqkc/n2eR88OBBGI1GLF269Jzevz911NXVsX7FE/JXX30Vr776Ktrb27F27Vo89thj2Lt3L1P8SQ0bHx9nPlZSlfL48eOsiojdbme1K4E5kkOBMC+//DJsNhva2tqwbt06TE5OQqPRYMWKFQiFQmhtbYXNZkNjYyP279+PQqGA2dlZ1m6lUolLL70UTzzxRNlr5RVWUpsLhQKsViump6fxy1/+UrQ/71t27bXX4tFHH0U2m4XP50NHRwdeeOGFecqwz+dDPB7HyMgIXn/9dbb9jTfeqOh+vOXImRwqIRmLMSHSvjQ50mDS1NTEIn1aWloQCoWgUqlY6YdSaTbKESi56yj3mdznlRK0KhYHPiScL9ch56dFWMgHsRRKqVD5fB6hUIit9hoaGuB2u2G1WtHS0sJ808ipXk7pWkjBlWvzYvtMqWvknydAHJxAKRWqPmeVQ6FQMPVJurLPZrOsNAwRJf5+k6JECwxplCyZlXg1ighTOp2G1WplCxNKMkpqHpk6Y7EYJicnRZUhpKBFDwVV8dGaZALlgwB4kpbNZtmEyZvE8/k8m/B5820mk2FF2CmggCJVeSSTyWowwAL41a9+xRzX4/E42tramL8eMOdTtmrVKgBz92Nqaoqli+CrAGi12nlpKsgSQdUBeAd5h8PBzJuxWAyBQIDl5ItGo3C5XPB4PDAajRgcHMTMzAxTZalfEYrFIv7whz/A7/ezPkL7+/1+5qdIz4bH42GLn0gkwtLLSP3E2traMD09jYmJCVxwwQV49NFHAQAnT55kuQnT6TS8Xi+CwSBLXTM2Nobx8fGK1TIeb3lyVqn6U4lKJfcZJb4rFouor6+H0WiE2WxGa2sr8vk8TCYTEokEK6nCmwWkJk7+2KdLxEp9V+74pVSzqmK2OFA0HPmekcM0oZLftJSJs9R2/t5Fo1H2vra2FgaDASaTCcuWLWPRe6lUivXBSgjiYhXZSj4vRTCl2yjohkxqfBqHKuZjw4YNGBsbY4sFXnUg52FK+ktRcnq9XkRAKA0FrwLIgb5LCbj5c42MjDDC5fV64XQ64XA44PF4mF/QxMTEvPI1Wq2W1dqkdApEyMmsqVKpmIM3qW3URorCpAABmujVajXMZjMjjwSKyAwEAgDmqiVQaSmFQiFqn9VqZWob5ZqqQh5k8gPm+hNltH/yyScBzJGz/fv347rrrsPTTz+NeDwuSg5LMJvNuPnmm3HPPfewbUajkalmVG+yv78f4XAYS5YsEUUXDwwMYGZmBjabDTabDatXr0ZjYyOsVisOHTqE48ePIxQKwWazQRCEeX5v2WwWN9xwA9xuN15++WU89dRT2LFjB1asWCFKn8FHnZMZNJ/Pw+12o6GhgUX99vX1YdOmTWyBYLPZsH37dhw8eBC/+c1voFKpYLVa0djYCKfTiZqaGmau5WtwdnR0YPPmzVizZk1F9+NNTaUBVF7e6GyBNwPQ5Em+DkuWLEFHRwdaW1tx3nnnMYm2u7sbL7zwAqamppiEWmpikm6TO/9itst9Vum5BUFgOWCqqTTmg7KjSyPj+IntXJBdaR+kiVWn06GtrQ0rVqxAa2srVq1aBUGYK61z4sQJ7NmzB5OTk6ymIR2L/y99Lb2Os93/CHRsPk8bKTRarRYDAwML/CpvXxCp4AkLgfwgBUEQkQ5e6aUFJIHSmJC5kff1mpmZYQ7b4+PjonPRosBut2P58uVYsmQJampqUFNTg3A4jKmpKfT09GDfvn1MqRsYGBBlUidipVKpmM+YyWQSpVgA5voQkcRoNMomSmqrIJyqE0vE0OFwsIhPtVoNt9vNlEZp1nqLxcLyCJLiIVeHtIpT+PGPf4wvfelLIsXLbrfjK1/5Cu666y5mZWpvb8fAwMA8ny4+tcXatWuxd+/esufz+XzYvHkzTCYTQqEQJiYmsH//fjYXr169Gtdccw0efvhh9Pf346qrrsL4+DhmZmYwMzODbdu2YefOnYwA2e12XHDBBejr68PAwAAjjTfeeCMefvhhUQ1gh8OBTCbDkuE6HA5MT0+z4Bi+hBqVsCNYrdZ5wRMUGbpx40ZWooov09TY2Ijh4WEYjUbU19eLzLql8JZXzs4FpA8ohfwHAgGMjo5Co9GgpqYGPp8PFosFbW1tLIBgdHQUk5OTLPqET7fBqyILmTaBc5Mmo2rirBx2u51FoQHzC0YD59Zvj1eiqHTN9PQ0rFYrNBoNfD4fM3G2tbUxkj02NsYSa0oj2aSQKrmn0/8qDXSQlrVKJpPzFjJVzIfT6UQ8HmfkiwiKRqNBIpFAsVhkpj5aSGSzWeZrJZ0oaNIk0kREhyanUgXAyZQaDAaZeUqpVMJsNrPksdSG2dlZhEIhFhTAj4e8mZLypdlsNkbSSP0lcknRmvRd8r8kYkkRolQair9OOpfRaBSZRjOZDEKhELLZLGw2GzweT9WsuQDuuOOOeelGwuEwIz1Hjx7F8PAwxsfH0dzcDEEQcOjQIbYvr0z29vaWXdgajUbU1NQgmUxiamqKjRVNTU0YHByEQjGXJ+yBBx5AOp1GbW0tGhoaWOJwtVqN/v5+kctES0sL7HY7isUi7HY7IpEI82/kTfD5fB4zMzNwOBxwOByIxWKYnp4GcEq19vl8okoCfA3O2tpa0TPX2dkJu92OyclJka8ewWQyQa1W413vehd2796Nnp6eBe8F8BYlZ+d6QpQzQ5L/2eTkJNRqNcuSbbVaUVtbi1QqxYo+07408Egnx1LnKHWdC5lCT5e4VSfF8uCz5/Ogh/lc9cNSJnjKF0WOtXV1dSxDel1dnagPUsQxTYzki7aYNi/GFC9tq5TkkX8Qn6yW6tVWUR7SOpbkF+Z0OtHf389qU+p0OtF+VAi8FOkg53gi/tK+QZMjJd2mhWYul8PU1BQz9TscDtTW1sJms8FoNAIA+vr6kE6nWbZ3inAGTi12+RQ1VEMTADN5U2CDTqcTnZ93HVGr1ewvkUiwGqSFQoH9FgrFXGkmIm7JZBKxWAzZbBbJZJI9Q9T2KuRBxIwWrYRYLIZVq1YhEomwfF6UOPbIkSMwGAxIJBIi82I0GkVbWxvcbjdisRiOHj3KfLoLhQKWL1/OotUnJyeRSqWg1+tRX1/P/Cqz2SyeeuoprF69GsuWLWO5IAVBgN1uR29vL/R6PXw+H8LhMJxOJ1OMHQ4HaxeZv4G5qFE+ZxsFmUj9J9vb2xn5t9vtWLduHWZmZjA7O8uqAgBzEdZut5u5H/DpQ1QqFbvmeDyO9evXs8LqleAtY9Z8s+RmWvETmdLr9bBarejo6EBXVxcaGhrQ0NAAhUKBcDiMQCCAkydPYnx8HMFgELOzs2wgoKhPvnwOfx45E5Tce7k2lnstPTb/m1YrBJQG/U6U4ZwSfZIz9R+rT0rN7EajETabDatWrcKaNWtQX1+Puro6CILAkn2eOHECExMT7H08HmeFf2lClKvRyfcP6e9QSRvLbecVY1I7dDodDAaDSOKvQgz6/ZxOJ0wmE1MgSikPVIWBVvk2m40pbDyxobFNSpDJD5AUhnQ6LcojRWZRk8kEh8OBNWvWoKOjg/kK5fN5zM7OYnp6GgMDAxgYGGDmobGxMTaxL1u2DJFIhCkQwJy5UafTiVKCUBH0YrHIlL5CoYBsNguj0TgvkbFKpWJRq6lUih1Ho9GwJKjRaJQlEid0dHSwrPFVzMeTTz6Jj3/84zh58iRWrlyJvr4+GAwGdHV14fzzz8f4+DiOHj0qUstqa2uxatUq5pcmBSmvLS0tjBRJ/SWluOqqqzA9PY29e/cyH1y9Xg+LxYJ3vetdaGhogNPpxCWXXIKf/OQneOCBB3DBBRcwU+HFF1+Mz3zmMwBOJaglPPTQQ/jqV7+KyclJbNu2Db///e9ht9uZdYxMsQ6HQ6Qi3n///fja177GyJfdbofdbhcpagDw/PPP45vf/CZ27tzJtmk0GqxduxavvPIK21bJ3PKWVM7KyaGkdvA12Gi1Val6UMrRGTiVpG50dJRlOjabzXA4HKxunUajgcvlQjQaRTAYZI6R5LRNDqzJZJI5o0pVBLmcVaUgF3gg91vJOYRXsTAoRxQpUlIHUyko5YC03NHpFPqWI0rZbBaxWAzDw8NwOBxsgKMIOkrO6fP5WN4gUtGkfZDK51ACUt5cVIpwSVHueshnkyeX/F8ikTitSKW3I4LBICMkZCaker8A2AIrn8+LyBT5AlHgBY01UhUKAEufQX0+FovNS76czWYZ6VGpVBgZGWGLaVJuXS4XTCYTdDod3G43kskkMyFGo1GkUikWfED+OABYWSVK9ZFOpxnJpMh4umYiliqVCiaTiTn7U9AAVaQgHzVy2CafNLPZLMqzxjtnVzEfn/rUpxj56O7uZgurVColcu4nGI1GhEIhHDp0aJ7aRuDTrNCitxwxA4CxsTEolUo0NDQgFAohFArBYDCgvr6eRUIODw+jra0NRqMRy5cvRz6fR319PXsO2tra2LbJyUkMDg4in8/j8OHDMJvN0Gq1eOqpp5jim8lk4PF4WJSp1Lx76623it6Hw2F2Lt4f7d/+7d+gUqmwadMm9Pb2YnZ2FrlcjhGzrq4u3H777RXdj7cEOatkMqOHlaJyKMKH/njFivcF4yfNhdrA+/4Eg0FMT0/DbDbD5/OxG0oOuiRVks06nU4zQkb5siKRCCNuvPmAz0Zfrl2VmDdLbTtbPmxvF6TTaaYmlAL1QXooaVKgP+p3fCkavg8uBLpnNFjMzs5iZmYGFouFJTmkPkg1COPxOOx2O+uDqVSKmRjS6TRisZho8UDlSviEpKXMrJWAV2mlPpfVwueLRyaTYXU0U6kUTCaTKCcYjR2UmoBXjWjhSrmaiDjTpEjfoePl83lGXHiFisyFRJ4CgQBmZmZgMBhYMIHBYGBmQipRk06nWUkcSrJM5X68Xi8mJyfZc2axWFi9Q4JOp2O+R5TbjBZA9CzxiyIAogoJ1Pd4x28iiwsRgiogSm9Bz2w2mxWVdCLY7XYYDAYEAgFMTU3B4/HgwgsvxJ49e0T7GQwGWCwWqFQqtLa2Ynx8XLSwAOb6Ht8P4vE4LBYLLBYLU5HJyZ6UWbVajdHRURGJa2lpgc1mg1arRWdnJ4u8pL90Os1KLBmNRgwPD8NgMLDs/pRSS+pmwOPKK69kKiFZAHmz6e9//3usXr0adXV12L9//zzljmp6VoK3BDmTohRh0Wg0cLvdrBYhvz8NNDSgUKZyMjfyE6dUYZNOKpTAcGxsDFqtFm63GxaLBQ6HAyaTiaXbIHMAmTUp3J2Omc1mEY/Hmd2bOlY4HEYsFhORtFJmyXLReNLvyE2UVZRGS0sLAoEAiwCrJEpTrVYz1cBqtYr8xYh4U/4l6oO8cio1N5brg6FQiAWoOJ1OpuAajUbmR5NOp+HxeFgf5M2aRPJisRgSiQSCwSBGR0cRjUYRjUYRi8VEBFLOREmvpc7+vOmSJ3t6vZ45dZMKVK0QUDlIlaWo11gsxogXP6irVCr4fD6mMpHSpVarsXz5cqRSKUSjUeh0OrS0tCAYDGJ8fByJRII5QvPJgTs7OzE2NsYi9SjtRTqdxtTUFKxWK5RKJWw2G4vCpfQIfIF7o9HITJB8fdVkMomenh7E43GmUPMRvC6XCxaLBUNDQ6yP0TlJUSTU1taivr4evb29CIVCbOzX6/Ww2WwszQb5aJKyVw0IKI97770Xd911FzPVFYtFEfFob29Ha2srNBoNnn76aRYsQIqZ3W5Hc3Mz+/6yZctYMmMaW/R6PXp6epBOpxlx12g0UKvVzMleoVCwSEpCLpfDq6++iqmpKdTW1qK2thaHDx+GxWJBU1MTotEoLr30UrS0tODEiRPM7zCXy+Hw4cN4xzvegYaGBrz00kuMqHV3d8Pn8yEQCGB6epqpclTjU5p65fbbb8fNN9+M3bt3MwtFKpXCddddh1gshhdffBHpdBp79+5l5tGuri4sX74cBw8eRHd3N9544w288cYb+OxnP7vg/XjTfc4qBZULWbp0KbxeL7xeL1tZ0eqQL6jLEzNaoRGZSiQSTOki4ib1D1Or1fB6vairq8OKFSvQ3t7OouccDgc7XzqdnmdSkjMpUDFhMoWSv1AsFmNmAJrcpRGgpVCKnJFztlarRSAQqPqclQD9XtKEnXT/pakNyLxCjq4ej4elQVCpVCJTO91Lvg+SukCReaRu8dFpdH7q016vF/X19VixYgWWL18On88Hj8cDu93OzkdJkqV9UKrc0aIjGo2y0HVaKJDyRv2P78N836LtfPJQnmySKkP7UHLdao6p0ujs7EQ4HBZlOgfEWcl5UOh/TU0NywVltVoxMzODaDSKrVu3oru7G8FgEBqNBn6/H4lEAmNjY4jH44zsxWIxVv1Er9fDaDQiEAiICqkTAa+trUVdXR2WLVuGtrY2VkmFVBEAzFpAxDyRSLDFgiDM5fMjkjU5OYlwOIxgMIjBwUG4XC6o1WocPXqU/QbkHM47WVP1lpmZGRiNRuh0Ouh0OlFppi1btmBwcBCTk5MsL5zb7YbL5cLhw4fPyT38c4BCoWABcC6XS6SCWSwWqNVqNm4BYNUZJiYmAADNzc2ora3F9PQ0otEo1q5dC5vNhnw+j5GREdTX12NiYgIHDx6EVqtlC81oNMqU20AgwFRQCsw7duwYkskk1qxZg/b2dkbA3W436wPpdBrnnXceampqoNVqMTIygkAggMnJSUxNTbGx1WKxYNWqVThx4gQ+85nPYNu2bbBYLExxjkQimJiYEGXxN5vNaGxsRCaTYVUv4vG4qD83NTVh1apVeOyxx9j3TCYTVq1aBYvFgmAwiJmZGTbfL1RsHXiLKmelwJsoKZM1DSD0nyYN2jeXyzEixitdqVSKFVSlwYQGEZpsKVopl8uxQuipVApWq5WZl8hZkW4cDUjk38OrVyT/0wRL5CwcDjPTE69+8IoEr7hIlTF+Mqf/VKSVX/lUIQ8iYFKTHG2TEmWe/FIma/rN+XxNPCkiYpbJZFgfpD4l7YMEClRQqVTI5XLMLJlKpZhjNZnYST6nPk59UGpSpD6YSCTgdrtZ3wuHw6zvUj/kiRr1PbkoVv53ocmc0jjo9XqmwlQhD/Jj1Wq1InJGpYukTv403lEuL5vNxgp8U0RlY2MjPB4PlEolnE4nG7cSiQRTQZPJJLxeL1u40hgaCoWYPxfdS6qHSRGQyWSS5TCjEj7kj0aLElq05nI5GAwGVlnAaDTC4/FgZmYGExMTaGhoYGWkaFwmQpVOp5lzdk1NDQseoKzvVqsVDodDRM6ovWazGeFwGFarlbkEVFEeJCAAcwEUhUIBJ06cYHm/+PnMaDSiqakJVqsVBoMBfr8fwWAQTU1NjLSTGb22tpaNkX6/HzabDS6XC2azmRF5WohQXj+FQsFMoaSCUq1KIorkYkJjWjQaZWqpQqFgQgwwlxuwqakJs7OzSCaTuPjii7FmzRrodDr2eSQSYYsiMuVT2pDZ2VnE43Hmi06qLgkvfJoXAGhtbWXP07Fjx+D1etHU1ASHw1HRvfiTIWf8JEcTHe8jxGe+ptUUETVSQGjiIeUiEokgFAoxNY2cSYn8UX4f8v8gSZ78z8g+LXVupfZRUWAAjDTRtTQ2NjJFjx4I+j5NkrxpjMgaH4lHoCS6NMjrdDoYjUaoVKrqSrEMfD4fqw4BgK3Y+LQDRPQBMNJG94QncBRBR2SNyDH1QTJ7EsmiPheLxRAKhdjgRA7PpDxZrVaYzWaWN4zvg7yPhNVqZZMiLT6oH/KKHKltxWIRzc3N7Jxk5qRBju+DfCQy3//4IthEbCntAS1ayARbRWlQH5RWUigUCnC73cjlcsxflX5nUnEpW75Op4PP52NKZk1NDevP5Ffj9/tZvyoWiyySm3wTefJPEyWRNJqAi8UiEokEI2JEzmj8pTxTuVwOwWCQBQpQSgW1Ws2yvQ8NDUGpVKKrq4vlj5ROXENDQ9BoNMhmsywYhuoVEjGjfJR84lCyFCiVSjQ1NTEfuypKY8uWLaJUDzt27EBbWxu+/vWvY2hoCMAcIUskEszntbOzk5VW0mg0+NnPfoaVK1fi/PPPx+7du5FOp2EymbBmzRqcOHECZrMZy5Ytg9vthtfrhd1uh8lkwv79+zE5OQlBENDQ0MAEEbfbzfIACoLA5l2FQoFQKMRKjE1NTbESTLFYDO3t7VAoFCyPpdPphNfrRVtbG/71X/8V0WgUn/70p9kYSW4Bdrsdfr8fa9euxe7duwHMmXMPHDjAiBotRigY5tixY4ygtba2ssj0hoYGpNNpliokHo+jubkZHR0dFd2PN92sWS4yUw40IFEoK18WwmKxMF8gi8XCnFZpwqRVPXBqouUd+WmgoskIgGjlSH92u51J+g6HA3a7nU3G5GtGpiyeXBF4J1cywfLZsHmlgjcv8U7m/IRLqxOaGElRSafTuP7666tmzRKgVaDBYIBSqRRlWS/XL6mvORwOtion/wmTyQSTyQSLxcImTiIqdH+kfZBMBalUCuFwmBEiKn9EKjFPxmw2G+uDTqezZB/kVTQ+qogmaOpTRByp/0lJGK/e8mouD2onr5rR6vmd73zn2b59fzbg1Yi2tjZG1sxmMyYmJhjppfunVCqZr43dbofNZmMqEpU7oknPbDazfGdEpGhsIYUCACP/tCCMRqNs3CLiSKZ7vh9S6goac51OJ6sKQcfN5XKYnp5mixmVSsWUL71ej3A4DIvFAkEQsH//fqxZswbFYpFNcmQZ0Ov1mJycZLnLyDzE9+VsNotwOAyv18ue60wmw871+c9//o95a/+kcODAAdx+++2yhblXrlzJ3HEAMLKj1+uxYsUKxONx9PT04MYbb4TFYkEmk8Hjjz8Ol8sFr9eL5cuXo66ujvnSUkkvKnp+/PhxAHNqExGsRCKBxsZGjI2NYXp6GrOzs2hra2O50o4dOwa/34/GxkZotVo2DtbU1MDj8WB2dha9vb1YunQpmpub4fF4kMlk8OSTT6JYLOKKK67AV7/6VaxevRrXXXcdXn/9dRZNDMzV3XQ6nXC73Xj/+9+P5cuX46KLLkIul4NGo0E4HMYTTzyBlpYWGI1GKJVKhMNhNidTiiO73Y6LL74YTz75JJLJJDQaDR5++OEF78eilDPegbQcGhsbF3PYRYFCX8nXi1QyGojIUZqc961WK5xOJyNpFP5NkyQVXCWnVfK7IfWEH7xoEOV9K+iPJmSygdO5yDzEp9Lgj0n/5QIVSjn+86/pPcms1OFphVtFaVCSzFQqxSYA6T2QA2WpTqVSCIVCoj5IASN8H+Qd+UlNogzw1AdpEqMJUkqmALH/YTabFfVBWqHSAoXaRA7aPPnij8P3SeqDlUYSS4MGSPmhPriYdB1VzGFqaoot3iicXxAEVigcmPutKfIsHo8zR3ebzcaSdM7OzrL+oNFoWMJN3gGbN1dSuhYi39KoXiLZdM9JLaV9ySxZLBaZWkqRppT2ha4ln8/PW/SS7+b69evhdDpZn3W73Yx05fN5+Hw+lhiUzzlFaR2i0ShTU4A507DL5ZqXfqSK+fjSl74kImYU/DE1NcXGGUIwGGSJY7PZLBs7+/v7mUWrra2NKUZDQ0Ms8txmszGST8Ehbreb5a2z2+2iYvbkwrF8+XJYrVbm5jEyMsJUND6QilRmut8UWELJujds2IBEIoHe3l6cd955aG5uBjDHWyjDAgWYUGWMd7/73fD5fGhqasLhw4dZ/lNSqSnN0dTUFA4cOICJiQl84QtfYL69+/btw5VXXskIZCVYFDlbsmQJey0lELSNHthzBVrZk9olp2zRZEgdgYqV0iqSbjZJ8zTQWCwWNoHxSheZRPmoJH7CI5MmreIomkmv17PBjl+FVpJWgcxh/B+tXIFTZIyfAKVRdbzMX8V8mM1mRCIRRsZotb9QnjPqB5TLiZ/oSCWjBJ7UB5PJJFPTSHkDwApC070jE7k0epTUML4P8gORXB+kPk4TLN8HpQErcpUS+H7FV1PgfRuLxSLrnxqNRpSugTfpV1EafEBKLBaDyWSSzQfFP9u5XI65ZNBiLBKJwGQyAQBTc4msU4Q5+Xzp9XqmntH91Ol07H4TUaN7yN9/vn+SGZ4WCOSXRuoC9Qu73c4Urmw2y/o8Kf1ksm1sbGQLFJ1OB6/XyyoMkP8YP25T4BYVXSfTEZlTC4UCvF4vK0tVRWn89re/Fb0///zzYTabsW/fPmZV4pFKpZjCT64V4+Pj7HdfsWIFU6LIMlBTU4Ply5czc7tKpUI4HGalvaanp9HZ2QngVCklUmgbGxtZHywWi/D5fLDb7XA6ncxnEwDzc6RyX+SnSGJOQ0MDkskkdu/ejY6ODhZNTmor+eASDxAEAZdffjmsVitMJhOOHj0Ki8XCMkdoNBrYbDb4fD6Mjo5iamoKuVyOXcehQ4ewe/duXHzxxfB6vSwSeyEsyqypVqtRX1+PW265BVdffXXJkyxUdf1MzJoLgSYSImomk4lFFlGNNafTyZxpqcwDPfA0CPE5zeg6iYxFo1HE43Hmn0MTFDkiUvQUHZuOKY2e4wmVnCJ2pqoD/c5Vs6Y86LeVmwypRMxiFxo8mSGiZjabWYQl3wcpsSzlDCLfISLhZMokAkgLn1wuJ8pfRn2QVqMul0tkZiKTKk2OvEpWqr/JqbVVnBtcfPHFLIqWUrsQ+IhYyp4vjSIm6HQ6WCwWBAIB1hf45LFUCJzImsfjYZFvZConxUKr1c4zY/IBWGSSj8fjbFwMhUKsnxEhowmN+jiNpTTuZ7NZFm1Hqhsl+DQYDKzWrF6vRzAYZPVEDx06hNWrV7NrP3LkCNrb29nxR0ZGGLkLBoPQarWsfFQV8rj11lvxyCOPIBKJYNu2bXj++ecBnPJFo0CTVCrFKjwsWbIEY2NjiEQiKBaLuPbaa9HT08MS/vp8PqYwxeNxOJ1O5hRfV1cHvV6PZ599Fpdeeiny+TyeffZZ/MM//AP6+vrw8ssv45JLLmH+r2q1GjU1NSxdTzqdRmNjI5YsWQKz2Yzu7m4WANfU1IRUKoXx8XGsXbsWU1NTLKiEcvXRgoYCE2hBAcz5gfb29rIkzVu2bGELakqTYbFYsGzZMhw/fhz5fB5GoxFTU1NYvXo162uPPfYY9u3bh7vuugsKhQL9/f340pe+hAceeGDB+7EocjY5OYmf/OQnuP/++xEOh/H+978ft912G1asWFHpIQCcHXJWasLgoxhpdU+DDw1Q5JtBzn/kQ0amJxrkLBaLyKmZJHrgVLoOcp4mNY1UA51Ox87DByj8MVElZ+VBkYtkPiTTTaWOwwv1QSLevKqm0+nmTVq0AqR+SMqG2WwW+U6SOZQmQOqDlOBY2ge1Wi07D/XBKtF668FsNrP7KU3KSgqSXq9nBc0BsFQvvO8pEahYLCaKOgcgCmAi30RaIJAZnvI5ktrLl80hfzUKhqLjAKf8F2mRQIlsaWFLxIj6rzSqTQpa7AJzKohctC8/kUpzOlZzPJ4elEolGhsbYTAY0N3dzQQMs9mMkZERUd+0WCws/QlZaHQ6HQsyKWcdslgsWLJkCS688EL4fD7853/+Jy699FKoVCrs3bsX27ZtYy4nLS0trG3UT2mxmsvlsHLlSqxevZo9D8PDwzhx4gSuvPJKAMD09DSmp6cZF6BFhNFoxOrVq+fVV6bUGFqtFuFwGKOjowiHw1i/fj3r71LQ8d1uN4aHh5lbVyQSYfU5/X4/ZmZmEAqFMDs7i4suumjB+7Eos6bf78fnPvc5fO5zn8OLL76I+++/Hxs3bkRHRwduu+023HbbbX8UAiJd3cuBVnYkTfJpNKgcBIWWu1wuxONx5HI5UYFcGnRISaNOwQ8WbrebRYGSzxqRTd7xu4q3HgwGg8iEKU19Ug7S/eg9PzHwDvW8GZQSwpLZKR6Pw+Vyscg8mgyBU9GilHdKrg9Swd9MJiPqgzQ5VyeqtzbkfEOJhJMpWrqPNO0Gn7qFEgOTD45CoWBmcJ40xeNxtvg0m82IxWIs0CSbzbKxkFf2iRCRVUGhULDSShSpSSYs3r9xMf2Qn0OkEyJvNi8FSnBaxeIgCAKmpqaYfyClaZEbF0nNpDx5RNwr8UuPxWIYGBhAc3MzVCoVEokEjh8/zkycfX19LNAuHo8zUk9+Y5QoVso1KG0MjZ3AnKlybGyMuT9RH6WFDE8ii8UiotEoOw75hvGZFkr9btQfeX/7gYEBdHV1sffPPvss6uvrcfHFFy/4GwFnkEpjy5Yt2LJlC77+9a/jve99L/76r/8a119/PZOdzyVo4pHm+ipH2khCp1QDJNfHYjG4XC7mXE1+QrT6I3t3IpGA2Wxm0Un85EjRSbw6RStI4PR8bvj0DXIJac+W6fPtjFAoNC+fWaVEWs7nspRpkEATFwWUUB+MRqMs5xjldaKIJ74PJpNJFmDgcrlEExCpurzphvr8mfQR/jr5PGc0ONK2YrFYcmVZReXweDwsN2MikShZJFpa8oYWAuT/RyAzOams5K8GzJXJ4X12yWzI5xejgKl0Os1qfqrVauZXRDVp+WTMculTeIWvFOQUL/49+YyREkyLEP45oNxUhFLKWxXySKfTGBoags/nY6WW1qxZg+7ubigUCni9Xpx//vlIJpOYmZnB7OwsgDnFiczl0kL1wFxCYcr9WSgUEAwGcezYMRawQQXptVotQqEQszpQEAv5iyeTSZbqyuFwsDJ3iUSC+R7W1NSIzq3RaBAMBqFWq7F582bU19ezzyhRsVKpZAlwTSYT4zEUnKBUKln7pePc7Ows3G73vN+SJ2YA8KMf/Qjvfve7zz05e+mll/Df//3fePDBB7F8+XJ897vfrTgK4WxAjrBIIfXpov80IPE+ZrzCQSpbLpdjfhd8Yk2S/S0WC/Mfkq7kKPT7dK9N+id3rVKH7SoWB34AoYLQ1A8q9TVbqB9KgzX4+0X9iXdylVYVoFWitA/SoEXmKEphID336RImnpRRMAGpMuT4T35C5CtXxemhpqaGKRBU35BW+VSf0mq1sgzrExMTzLfG6XTC6XTi5MmTbPEJzE0qer2epSQgUE1iaXQ4kWw+yImcqokEkXUAmIsqpQXBxMQEM8HTRCrti5UsUMu5CVCKAj4PGvmoAWB+ULlcDh6Ph+0zMDDAcl5VURnMZjM2bdqEbDaL1157jeX7cjqd+NCHPoRvfOMb8Hq9TOGn3J6ULJbALyz0ej1GR0dF5wmHwxgZGcH4+DhTabVaLcbGxliqDZVKxfzCLr/8chw5cgT5fB5Op1OUgujpp5/G8uXLodPp0N3djVAohIaGBvh8Pvj9fhgMBiQSCbz88ss477zz2NxcW1uLXC6H8fFxtLe3Y2RkhF0DLYypj42MjOCVV17BTTfdxFLPmM1mdHR0IJ/PY3BwkEV+AnOF5G+55RZG0p577rlF3YdFkbOJiQn89Kc/xf33349QKIT3ve992LNnD4tKOBco91DxCoU0Qz5J9/wEyG8jHwzKVUW+P+QjZjKZRAEPcjnR9Ho9ZmdnWV04CgQ4U9OunP9EObWwOvCcOSjSjMzhPKS/r1yqE56A8X1N2hf595QLzOl0wmazwW63w+v1wmw2M7WMJ/28+kuJQ3nFg88Yf7b6IP0efMQmKTB8ygw5JbGKylBbWwsACAQCTNWiUlsAmNo/MDDAyDrtR1YAaRLWQqHAon+pHBP5j/FpMfh+SKYku93Ocpfx6ThoX1JPKWKdMqdHIhEkEgk2Fkr77+mA0isAmJegVqrOkamKh8ViqfbJRUKhUOD555/HBRdcgJqaGqaOrV69Gh0dHdixYwf27t2Lvr4+kSggLRZuNBoZOSOrEylflLg4mUxCoVCgoaEBdrsdCoUCkUiEpa0gM6RWq8Xg4CDrww0NDZiammJ503jyR+b7YDDITI6pVAozMzMYGxvD0qVLRcKJRqNBY2MjFAoFli5dysZ/qWmcangCc4sNKrlot9uhVqvR3NzMnk8AuPnmm+epZ4vBoshZY2Mj6urq8MEPfhDvete7mM320KFDov34KJrTBT94yJEQfiLkFQU+WSdFXPJ5peg/5f6hQYQCBOh7/MqPQsVJ0SAHbIVCgdnZWczOzs4jeORMeybXD4h9jnhHc36f6uBzeqitrUUgEGAmGjm1jPqXHAnm+yBFqPGJgPk+SOlVqA/Sa+qDpDxQVBt9j8/oT8SM+iHlZwuHwyyRp91uh8fjYX3wbChaFClIfTGVSolSgJCpbCFfoCrkQX2gWCwiFAox9YsILwUKkGpF/YPy7c3MzLBEmMFgkKmcSqUSDoeDmWUo0InMkNKxkFK8UJSvyWRiPml0/ylKjleZ+bJk1Fby5aWUHgulDyD/NOl+MzMzjHwCYPmryEojCAICgQDcbjcLquDh9XrZawquqKI8aHyZmZlhv3N7eztWrlwJu92OW2+9lZkhpb83b9bM5XKilFWrVq1iiqxKpWL+sRTBSWkmotEo/H4/lixZArvdzupRnjhxAmvWrMGSJUtYEGKhUEAgEIDX60Vvby/S6TSam5uhUChYNHttbS0SiQSmp6cxOjoqyh9Jzwk/tpezQq1atYq9psoqfP98/fXXkUgkYLfbsWnTJtF3BUHA9PQ0YrEY2traFrwPi4rW5Ffj/MpadEDFwnnOFip8rlAomHJgs9mY8ykfyk2vaaChCDciYzSwUNQbPxDRzeCPQ0oaT/L4Wp0AmCmAOh6frJYmcZoUyUGy0pwm5wLVaM3yoIGaL0UEnCLERLDI74Cv4crnNqM+xKfDICdripDj+yBf1on8zqjP0UTIn4vkfd4vji/pRX2Q+jRNiJRK5myZvImY8YoF5dmq1i08fdB4p9PpEA6HAZzqg7xLBvl/abVaNDc3IxqNIhgMYnp6GpdccgkzzU9MTLCIYJfLxRQsrVbLxlMa7/j8ifyigF7Tfnxf5L9DfZHGRh58YXJaZEshR5hoUiUiCcxNwtJ+HIlEoFAo2NiWyWQQCoXg9/vZPgMDA0yZrqI8mpubWWqVZDKJI0eOsM+WLVvGhAiC3W7HJZdcgkKhgJMnT+LYsWPYvHkzampqoFQq8eCDD+L9738/HA4Hvv3tb+MXv/gFZmZm8Mgjj+Cyyy5jAVnPPvssNBoNli9fjptvvhm9vb0wGAxwOBzwer04duwYpqam4HA4UFtbi+bmZrS0tGB8fByjo6MIBAKsfqzdbsd5552H48ePs+Aq6nepVAovvfQSbrvtNnYNtKAo1T/IR06pVOLAgQPYt28fMpkMDh48iNraWnz5y19GoVDA7OwsUqkUamtrMTExgUgkglWrVmHfvn1oampiudQAYP/+/TjvvPMWvB+LYg4DAwOL2b0i8CYRAvl1eTwe1NbWsgmQyBYNIPSaJjV+MJEONOQrQwMKgfcp40vs8OWeaKLkk8DKgc9dVsVbHyqVCplMRjbsW61WM8d76oPUt/j6mSTP8+kF5NIWEOmi/sSbAXn1l8+tJyWCfBqNNwMKhUJEzAqFgigAQW4CraIykImkpqYG4XCYZdHP5XIsFUVDQwNTl/x+P5YvX454PI7x8XEsX76ckbDW1lbmnM3nLqOarPzYxo9X/EKA+jhfJ5bGRf796YL6ipySJQgCc/qXpgShiDryuQTAXEyoqDYhk8kwFbmKhTE0NCRKiEzw+XyYnJxkJj2/3w+/3w+9Xo/jx4/D6/XC4/Fg48aNaGpqYgmOt2/fjvXr10OtVqOrq4uZ5ZcuXYr6+nrU1dVBrVazcluUNYHUOko8rNfr4ff74XA4WH93u92ora2FwWBgfYS3FJCyNj09DbvdjsOHD6O/v5+l5iAcPXoUKpUKbW1t83zm0+k0Tp48ibGxMXR0dDDz65o1a7B9+3ZRInFeoW1sbER3dzeAuUS+hP7+fhgMhoqIGbBIctbU1LSY3SuGlKCp1WrmBEv1u4icmUymeQRMurrjV2u8eYgvOQKIyZRUJeN9iGjiXGhSrGZC/9MCT8xooiEfKyJblAuPBn+edElN5rRN+pr6KD8h8gmJgVPJk3kzqZzp/q3Sx+SUEgoYqOL0kMvlmKMzH0VMORO9Xq+o5FdjYyMrfVNbW8vGRgCi/kkLU1pY8K4iwKnSXdIxT64/0lh5phaBUkSecrTRdUgXuuRWwi8SIpHIPHM6qY7VxcPiwBMzlUrFFgR8dYWWlhY0NjYin8/jwIEDbOHQ3NwMvV6PVCqFTCaDTZs2MTJ0wQUXYGZmhpXyIlXXYrGgq6sLXq8XKpUK0WhU5FtL0eZWqxV1dXUYGBhgpcsoB5tGo0E2m5WtvkPjM3CKrPOg9DF8+g0CJb+NxWKsYoZSqURNTc28iFAp5I73v//7v9iwYcOC3yWc1hPW29uL3/zmNxgcHIRCocCSJUtw7bXXzmOlpwtyqCbHfOkqjjc78lI7DR58Fm0yV9HnfP4zfgCUKhNSCV9qyqL8P1X86YIeZAr9DwaDIrJGkxtJ/US0pOot3zd5AgacInuUbqJUH6RzyvVBacQwn9T2jz3ZUI1HPsqZatZJHbSrWDyImFDwEfmJud1u+Hw+OBwOFgVHZkOv18sWoJQKgPoQjW2kdvEmfI1GwxYoPEGjPGnU1yh9BvXBWCzG9iMrx2J9uXgzONVAVKvVsFgsiEajrCQQj1gshnw+D4/Hw8hYLBZDOBxm+aWo9E59fT3bh+ptVolZeXR1deHAgQMA5vJ3CoKAwcFBAHMmzyVLlqCxsZEFH01PT7N+2NzcjC1btkCj0WBsbAxjY2OIxWJwOp2oqalBsVjEnj172DiRSqUQCASgUChw7bXXIhAIIBAIIBgMoru7G9FoFJlMBn6/Hy6XC01NTVixYgUcDgcCgQBmZ2fh9XoxMDCAwcFBWK1W2dqpRM7Xrl2LlStXYmhoCEeOHGFEbtOmTbLKaj6fh8vlgsvlYuqXw+GAQqHA8ePHkU6nsXTpUtF3p6enme9jQ0MDgFN9DwD+8R//cVH3Y1E+ZwDwjW98A//v//0/FItFeL1eCILAnDa//vWv4zOf+cyCx1ioQgCV/nC5XCxjsXQylJo1+TI3pFTwqz/eV4fP0UMTKykl/KDGQ2oK5Ytd22w2NsFTtu+3Aqo+Z+VhNptZsWbglCNooVCARqOB0+mEx+NBQ0PDPLO59DXvYE19kFQOPgs1paWgGq60mud9zngVVxq5KyWP1Aep5iBl0f5jmNartTPPDtxuN0KhEPs9yVRD5MzlcsHr9aKtrY35ElqtViSTSej1elGOJTLvkD8Z1dKk/kXFqtVqNUKhEFQqFSPYfESm1AwvNYHS5EaKHI3BNBaSWbUSUOFshUIhS8qAuZyE0mhN/vtarZYFB/DqSDwer5o1K8Q73vEOPPnkk6JFq1KpZKTH7/dj06ZNyOVyaGxshN1uRzqdRltbG6amprBnzx5s27YNDocDKpUKr7zyCrZu3Qqfz4dwOIzZ2Vnm29jb28sWF5FIBE1NTRAEAcPDwzAajaz8XCgUglKphM1mw5YtW9hxRkZGWO60eDyO4eFhZLNZ+P1+3HTTTSwSNBwOz3O+j0ajzHeW+u+ZYNeuXUilUvD5fFi7di2eeeYZHDx4EJ/+9KfZPn/5l3+Jv/3bv0V7e7tsTjQ5LEo527VrF/7xH/8Rd911Fz75yU+yhyUYDOLee+/F5z//eWzYsAFbt26t+Jhy3JCSzfEJEvnVn9RcSRMlETK+oj1fm44SMZIDK3BKNeFDxqUlHei7RPAoMo/MrJlMhkXbAWB+SFW8tUFFxqlKAKWMoNfJZJLVC5T2QZ7U8695n0W+DwKnVDRpH+TLM1ksFpEJlMD3P75igFarZX2QBjWaoM91MEqxWHxTA17+XFBTUwOFQsFyl1E0LHAqcXE8HmcJVvV6PXK5HKsyQZG81C/IBK9QzJUi0+v1bEzLZDIsIIUSc9KilQJJyKWEdxPhLRNEzIic0Z9erxflxKM+upBilc1mGYGSI2ZyPqF8ygLeAiJdhEqToVZRGgcPHhT91m63Gw6HA4lEAidPnkQul2PJ2qn28JIlSxAMBhEMBlEoFNDf3w+32w2TyYRwOIzh4WEkEglWN9ZsNsPr9WJ4eJhF/Wq1Wma+nJqaQn19PQwGAwqFAmKxGEtwfPjwYZhMJmY2nZ6eZn08nU6z/jAxMcH8ieUSOGu1WhZMw2f0Px1QQEskEsHx48exdu1adHR0zJv/yZ9tMQrzokbW++67Dx/+8IfxT//0T6LtTqcT//zP/4zJyUl8//vfXxQ5k1POBEFgtQJjsZjIfCk1NfI5pWjQofe8KZPkfMrRQwMHdUBK5sivMnnTFJkC6Ls6nU5kHiDzATnlVsnZWx+UGZoHmZWy2SyLGqMBgu9XvJmR+iRv+paqDXx2fZ6Y6XQ6uN1u2O12UR8k4sUTOz5xqFKpZP2ZT2FB0Zpnwy+oFOh55Y8vl929ispgNpvhdDqRzWaZ0zUFW1D/o1Q+FJWu1+uZs3Q4HGY1/Kgf0phE/pN0TCJX0ihfslZQ+aZ0Os1cSig4gfzRpCVv+AUDmUDJNLtQ6RtgzvFaTt2iJKCknND5yJRGGBsbY+oITX6pVAqpVKoaRbwIjI+Pi953dHRgyZIl0Ol0ePjhhwGAEaJwOIyxsTFotVq8/PLLsFqtWL9+Pf7whz+w1CyxWAwmkwkjIyOYnJzEsWPH0NDQgPXr16Ovrw8nT55EIpHAVVddhf7+fqaCqdVqpNNphMNhTE1Nwe12o1gs4qWXXkJXVxerSRyNRln/s9lszJeNzxeoVCrR29uLpUuXsusSBAGhUAi9vb0iP/oTJ07A7XaLIisX+r1qa2uxefNmJJNJfOYzn8H73/9+1NbWstyFJ06cgFKpxPe+971FV6tY1Oj92muvla2m/ld/9Vf4wAc+sJhDlgWfqV1u4Ofzn9HAIZcTDTiVdZ9W++RkS35FgiCIipxTtBBvouKjlcicRatNMqtW8acDUironpK5mx5sPmVFuf5Hr/n+V8o0Tn2QFF6r1cr6Ix+IQCZyuT5ISh6ZNWn/P1ZKi1K/RRWnh1deeQXAnFmdfGeUSiUMBgNTdinxME/6KY1JNBpl/r+k/BN5oX2kOSIpLQqvvpKfDJlE/397bx4c2VmdDz+9L+pd3a2ttYw0I2n2sRkPg8f+4TEmtjEYiHEKCGAqQBaqWFyV8FfYKokdChMXJEUqGHBCgg1U7AAmGAdvY4M9Ho/HGnk0o32kVku9q/dVLfX3h75z5r23u6XWLNjg+1SpJN2+ffv2vee+73nPec5zKBomaqOJvEpxMUpFXCQZs1nxCqVXVSqVJM0jkvYpiiZKZKjV6w2wKQpjMBjqakbRd1Yiu83j7rvvxv3338///+pXv6q7n5jCnpycxCuvvAKv14sDBw7glVdekey7d+9edHV14Re/+AWi0Siq1SpaW1tx4sQJAOvE+bNnz2Jubg7lchkOh4PnYq1Wi127diGdTiOZTKK9vZ3lMd761reiWCzi/PnzWFpawrZt29DZ2cmcN6o4Jt0+ESaTCXv37pVolgHA0NAQ/53JZGreJ4fX68UjjzwCg8GA4eFhfPvb367ZZ2hoCOVymYXCY7EYjh07hjvuuGPDYwNbdM7C4bCkPYEc27ZtQygU2sohAdSPnhGaadNEx2g0QYjirWKq1GKxsKI6KbTbbDZOL4lcNzGdJUp6KJPS7z9WVlZ4MhGbNYuol1qRQ+6sEcTjkeNGaVBKp9tsNhYyJt6O3AbF4gPRBhXO1x8GSE+Jqs+olRNwQfeMUvBi2jMej0uKoAwGA3K5HItni3wyUZOMomiURSBtSaJoUDWc3W6XVCiTQyeX2NhKQUijxuQkUCrCYDDUyByQ/TeCKHtEVXYKNsaLL74o+b+lpQXt7e3w+XzI5XI4c+YMisUi0zIAsBZaPp/Hq6++WnPMyclJSfTW7/dzc3Ti2qbTaXb0u7u7eSzW6/Xo7+/nVkmzs7MYGhqCxWLB6uoqWlpa0N/fj7a2NlSrVbZbn8+Hc+fOQaVSMQc8Ho9Dq9U2rXe3mWMGrGcO9u7dy7JfjaDX67lXZzORZD5+U3v9/ygWixuuzGlQ+V1BLoQrToL1dKSIjEjedHt7O2u0UDiTWpZQuwn5RKiEyf9wIPZ+K5fLNRp4gNThque0NbJBuUwGLQyomMRqtTL/guxPboO0UBD11WiB8EZbFChpzYsHNb2nKFm9xSoR3ikVSXwvAEz9EFM54gRKTpuY3qTJjBwySquLLZyocwVJDdACQfx9OSogRf6YCDGKJjpia2trEqkC+fvlwraKXTaHU6dOSXTO9u7di+HhYezbtw9LS0tIJBKYmZnh/Yn2QYUnp06dQkdHB4LBIO9z5swZrKys1DjSJNFBiwen04nW1lYMDw8jn89zmp00+1KpFEZHRznVns/nJc5cIBDgLAKw7liWy2XodDqsrKwgHo8jnU6jWCw2pF39+Mc/xtVXXy1JgW6GwcHBhq899NBDeN/73idZtOj1eokm2kbYcoeAv//7v29Y/ZLJZPClL31pSx0CNoow0LZGD5cYpZBr9IiyBzTZtbS0cHks6axQntpms8HpdHIFidhuR5Q4uJIQJRZE8jcgjdzUcwDkulhra2soFApwu91KtWYDiLpNYksPYH2hQfejnl3KjyP+LbZzEsU/6cflcqG1tRV2ux0ej4dtkPg+RMom8jdFJpohV18q6DvXa4wN1Nqh3AmlCAUN8kq6f3OQ/Wi1WkmnCuJ7kQ12dnYygT+dTnPvTavVimw2y/eBUua02KDG5w6HA52dnbyA7urqYvV8j8eDjo4Odsyo9RKNn2JHFjHqdSXtkcZ+kqEhKRByPEl7KpPJYG1tjR1GanWl0+m4aI04pBTBUFCLM2fO4J577sEjjzyCarXKjc1tNhvGxsag1+uxd+9eTE5Och/X+++/H1//+tdr+GpyGAwGuFwudtxcLhenwPV6Pdra2tDW1oaBgQFMTEzAbrejr68PH/rQh+ByuVCtVjE6OsrVvO3t7ejr66urb6dSqXDq1CnE43G2CaKoUHrR5/NtmAUE1gsd8/k8HA4Hzp07B4vFAqfTieXlZZRKJVitVklKnfp8El0qEAhwyzVq7E59P30+36b3Y8u9NR944IFN97lUyCc7gjhJUq84eZqHOGRkWHRB6X+73Q6r1cqVlsRboB8abIi8TaRxaoxN4VaqxLtcoAGHhPfE3nU0UdKkKf6I10MkqRNxVkFjdHV1IZFI8AMEgFM8dP/rQXRGRB6YyEWkijfijpHgYktLC9sjcXTIBsXuA8CFnq7Uj65UKkkcv8udVhdtkKQ+KOpC9ib+TTZJ10QULSUngs5TVG5XIMXAwAD33AMgqbgsFAocKa03AapUKu6xSmlGun9GoxH79u3DzMwMtFot3G43du7cyffH6/XC4XDAbDbD4XBIWs+JPFpK+4uOIj0DtM/lThtSw3PR5ihCs7Kygmq1ytFG4s6JdutwOKBWq7G4uMjPZqNUqoJ1EAdLjJ4Vi0XJImBwcBDveMc78PLLLyMSieC5556Dx+NBqVSStHYiUHcLGht6enp47h4aGkJXVxf3onS73RgYGIDL5YJareZG6WSDoVAInZ2dsFgsvOhIJpPIZrPYs2cPgAv+QkdHB/edNZvNuP7666HT6TA6OopQKISZmRmsra1tqM0aDofZSaUoH3UwCIVCLDFCUblsNguTycQFCVQBrVarkUgksLCwAJvNhra2tqbux5acMxKku1JodqKhlSGJgxJ/jLxT4u4Qn4cq4CiELzp1otwBlaSTBpq8wECcGMV+n0TCvVjQAEPNrIvFIkfQxElSdNrkEbZ6zlmhULjoc3ozgDg38m20vZ5zJkYqSTSTJlKLxcLFJHIbbG1t5dep56YoxVGvVyGldcQCA/pdT7pDFL/dKmgypPJzskGqCCV7k/8vOmqiOC19Fzo3xTlrDHl6kO6j2HGhXjaCbJAcMbIvupcOhwP9/f1sIw6HAzt27OD/SfJAbENG90vUhaSm9qLoMKXpidgvyg9dSrU6RcaoE4CoB0iLFHpms9ksL15bWlqQSCSQSqW4uAcAp7uIX6zY4eagSmGz2cwyGMD62EiK+sTj+t///V9OLYogDpnH4+G03traGlwuF7xeL0KhELZt24aBgQEkEgleIHg8Hq70pTmMKovL5TKSySRUKhVaWlowMTHBY2Q4HJY4PWLKnxaJwLrTlsvlkMlkato5JRIJ7rJBjj5VPIt8T6PRyMLbq6urOHv2LDuwbrcbhUKBP4MEoguFAsLhMDweD7RabUPNPsk1vNgb+HqBKpFcLhe2bdsmiUYQN4IE7MR2O/JOAgAkDoxYNABcENaUV+NR5EwkaovyG6Qv1CyoV1wqleIbSoMSGSUNUGLDdXGgEidH+myKgChojEAgAAD8sESjUYlmFIGiQMT1oZWf3W5HT08PE6cpXU48HZvNxvYnyluIEzE99HJ+GgDJ/RT/JxsUOxWQjZMNbmWxIKbJstkscrkccrkcT8z0I9qj2HRd1AEUz5/I3RqNBm9961sv/kb9gePs2bMAwMT7UCjE6U2n04lUKiVZRFAVGm03mUycJnc4HOju7uZVfH9/P/bs2cMOX09PD98nkZ5CxTDkHFUqFU6NlkolSdsnkrIwmUwsgyG2z6Ox8GLEXzOZDDKZDAqFAnOayP6oyIGi2+Pj4yyjYLPZuHKvp6cHMzMzWF1dRS6Xg06n44Wu2OtQgRSPPfYY3v/+96NSqWDfvn1Qq9UYHR0FsJ4Sj8Vi+MUvfoHf/OY3SCaT/D6RhzY8PMyC2CSBQnMytR1zu92YmprCtm3b0NXVxc4e8clogZjL5ZBIJLC8vIxyuYy2tjb86le/QltbG+68807cd999ePe7340777wT586dQyaTgc1mg9vtRigUQjQaRSgUgsvlYqV+j8cDj8eDUCiEJ598EnNzc3A4HBywIXoAyWuRvEexWORxOpPJIBaLcbXxd77zHZRKJRw6dAgulwt6vR6lUgmPPPII+vv7YbVasbq6iuXlZV4gfOELX9j0fmzJOfvBD37Q1H6XU06DQIO+yWSCy+VCb28vBgcH+YaK8hcUlaDVO5WiA+AVmCgGKkYAxM8SUzSi8K1YSUfRAXofReKacdAqlQqy2SwikQhisRiy2SxSqRQymQwbA02UZKzZbFYS3aDzl2t2KWXkzYMil1arVWIrwAWnXN7r0Ol0wufzYefOnRyxpdWmvOemSqXiCQ+Q2iA5OHIbBMD2J7ZyEhupkw2KERZSfKf3i9+jHlZXV9kGo9Eostks0uk0T5DE1SEbzGQyrEFIkV4xmiYHRXSaGYzerDAYDCiVSkilUkzcJxtMJBIA1u9ra2sryuUyKpUK88hoYTo0NMSFTsRnodZKlDbX6/XcfouiIGJkSozMU3cCkuzweDxYXV1FIpHA7t27EY/Hkclk0N/fz44cLUbomRGV/+WL3XrIZrMIhUJIpVJIp9OIx+O8GCiVSjh//jzLfBSLRYyOjvJEajAYMD8/j6WlJWi1WnR3d0OlUmFhYUHiOCpojE9/+tM8Rr3wwgu8/brrrsPdd9+NL37xizh79iw7Zi6XC6lUipuWU8ssiiiRDYvjUW9vL44cOYLu7m52/ilIkkwmMTs7C4PBgHQ6jXQ6DbPZjMXFRRa83b59OywWCzKZDD760Y8iGo3i3/7t3+Dz+VhweWBgAMFgEN3d3bjlllvwP//zP3wOFC1rb2/HRz7yEQDAwsICRkZGJCLg4XAYZ86cwerqKjweD1544QVegFcqFZw4cQKZTAbT09NwuVwYGxvDl7/8Zdxxxx3YtWsXzGYzHn/8cfT29sLhcHDkjqhVzWBL1vq5z32u4WsqlQq5XA6VSuWinTMxerDRayLhX4xE0GRH/eJocKAydFoV0gNfLpdRKpXq9jkk54ZWgsTDoBwyedr0maJatUjYF508OYrFIjtksVgMyWSS1ZbJKaOIGjln+Xyez18eORNTsLS6VNAcSA+qnmSGvECDnCWKoJItUJWdGH2j6JH4Gk025JjR341skNL4Ih+IbFCr1dakGOk7iHbRqISbQvDUFoVsMB6Pb2qDFL0VCwjkkT5yzhQ0BqVLAEgqLkVbpEUoOflUOU+iw1TUROMTvUY2KEYz6W9Kf9JCVUxlF4tFXmim02nkcjmoVCrk83mcP38ewLp9plIplitYWVmBwWCQUC/IJijiJe++QqBIWSKR4LEwFArxAqFQKGBsbIzTr2traxgdHYVKpUJXVxcsFgvm5+exsLDA56bX6xEIBKDX62G1WpueFN+sIP6X2OQcADweD6anpzE7O8vbWltbMTQ0hOXlZUl6uaOjg6NdZLNWqxU9PT1sQ9QjleyCuLU0FvX29iIQCGB0dBSDg4OYmJhAJpPBzTffjKWlJVgsFgwPD2NmZobHVxIKX11dRTKZ5FSmVquFx+Ph54oCH2L1KGU7yPGnwoFIJIJCoYBUKoVgMAij0cip89nZWeTzedhsNszOzmJmZgb5fB7nzp3jbi0AEAqFEAwGUS6XmV7VrBDtlpwzWsXJEQwG8dWvfhXf//738c53vnMrh2TI+T0bkbFFhWuq5iFnS1RxFzsEiEZAESdx5S82SRf10ChNRKlSCtnW493InTzKh9PkKqJcLnMaMx6Pcxg2GAxiaWlJsnokLhA5kvIUmDjoyblxChpj+/btiMfjbNe00qNrKGpHNQLZInEkiDxdr0MAHYvsjiZEMfok2iA5VBSxpQmYbLClpaWmQES0Qzo/kQsmOk8rKyvI5/NsZ8FgkG0wGAwilUohlUpheXl5Qxuk33IbpGsqViAqaAwxYkapSnI2jEYjO/JU6ENFGHK5HypwEe2NxjM6PmUU8vk8H5MWtvRDkbNkMolYLMbR4Gg0Cp/PB5/Ph3g8zp8vLhbldghccDjlhSyVSoUbmJP9RSIRLCwscLugfD6PV155hb+n1WrF4uIigHU79ng8WFpa4kk4Ho/DZDIxXwqA4pxtgg9/+MP4r//6LxaIBdbT6ouLi/jGN74hKTAjG6HIFgknv+1tb0M+n0cul0NPTw+0Wi1cLhd2796Nubk5vo+FQkGy4KAK23w+j46ODrzyyit47rnn8IEPfAAnTpzAwsIC/vZv/xbHjx/nbgQ/+clPcPDgQVx//fWIxWJc1FIqlTijkE6n0dPTg1KphKWlJZb8IOcSWLeL4eFhAEAymeQiA1qozs/PIxqNckBkYWGBW6xNT0/jqaee4uvy2muvYWpqCjqdDp2dnZIiHgq8NItLivNmMhl87Wtfwze/+U3s3r0bTzzxBI4ePXophwSwseBsPp9HLBbjSZFSmGK7JjqGOEDQCp9W/aS4TStRcrKACxELsaE1SXB4vV5JxSZNSCJhVUS96BXlrSla4ff7MTo6isXFRczNzSEcDvNkSCsMmvCI9yFG40SiuPj9t6CS8qZEOByWRC0IJpOJUzz1UCgUuCEvCRqLNkgQJyqyDUqhku0Vi0V2YMTJjJwdioAYjUaW4Ghra5NER0QbFDsc0HFoMpRHpMkGY7EY/H4/zpw5g0AggLm5OY5akDNGEFOtcpuT2ymla5XClI1x9dVXY35+nqvd1Or11lzkmAHrbXMoOk/VdJR+zGazCAQCzFkrl8uwWq3QaDQcraCFQiqV4rFB5HXRPRLHRYoGp1IprsJPJBLYv38/4vE4pqencdVVV9U0VhcXrSJ/ktJYjewwGo1ibm4O09PTWFhYwMzMDOLxOD9DdH1UKlWN6GehUIDBYGAHIhgMwmAwYHBwEHNzc4hEIohEIpf71v1B4bOf/azk/0OHDmFhYQEnTpyA0WjEnj170N7ejlAohEgkgomJCVgsFvT396NarSKbzeKpp55Ce3s7rrrqKtaRXF5exs9//nPs2rULExMTeOaZZ3D33XdjZGQE8/PzOHLkCI4dO4a5uTnE43G43W5MTk4il8vhJz/5CcbHxwEAX/va1xCNRrGwsIC//uu/xvvf/36Ew2H85Cc/wYc+9CFMTU1Br9fjfe97H4vhkzYgcSSNRqNE3Hl5eZkr5mlspsxVIBBAMpmEXq/Hz372M9hsNni9Xj4fYF1k12az8SKAnFabzYYvfvGLuP/++7mQcvfu3Vyp3wwuyjlbWVnBP//zP+Oee+5Ba2srHnzwQXzgAx+4mENtGZSfXl5e5tClPG0oTorkpJGjJjpiYsWjPC1DES9amdJAlsvl4Ha7WctErLKjCJ0YeQNq07QUpk+lUohEIjh//jxmZ2cRDAYRDoclYWIx+iKfEOtNjBdbrfdmBEkXAIDZbOZUpNwhkYMUq+meiE66WDhQL4pA0TUxyiraqlwzTKzAzefzyGazyOfzXHwgttMRFySik0THE1Eul5HP55FMJhGJRDA3N4eZmRkEg0EuEycbFG2unv3Vs73V1VX+/K00+30zgnhmxD2jtDgAJt2TrA8gjeyWy2WkUimOthOvjGQjMpmM5L5RtRsAyeKgXC7DYDBwBkLk0ubzeR5vqcqNJIo8Ho9ECkYsngEuOPON7JAI14lEApFIBH6/HzMzM+wA0CJIXs0q8kJTqRQLjGs0Gubu0bUhnpBSILUxvF6vxIEVI2jFYhHz8/NYW1vjSt9isYhwOMxVjl6vl2k6arWa+6zSe0mCYn5+HqdOncK5c+cQCASwtraG06dPs9NEHQMAYGxsjM9hZGREUrS0urrKBQYrKyvMeRS7YhBPu1Kp8Hzd2trKIsa0mCEbn52dRSAQwNLSEoLBIGKxGNO1kskkp0BJRgOoDSY5nU7YbDY88MADqFarMJlMnJan69wMtuScVatV/OAHP8CXvvQlVCoV3HPPPfjEJz5xxYUx5SASs0hulU+K4v9bBaVKxUGNGukWCgV0dHSgra2NRfRE54xSDQAk6VUCpVMptx8KhTA3N8crZ2rmKk7OGzlj9Lf8/IHNW14puICWlhYeUOSRJ6D2Wq6uriKTybATIrdBkYclynI0e0/k95xI0PTT3t6OtrY2LoIhmxOFSOtFWYHGNuj3+xGNRpFOpyUOntw5E89PvEZ0Deg8NuJbKrgA0kUifh5FiCgaJZKrATDvkRx94vCIOmfEy6LIGd2jdDotkToRK5PFylsAkueAhF5LpRJH6crlMpaWllguwWKxsHMGXIj+igtV0RYoUkHUjmAwiPn5eR4LKaUJgItg5JQRujb5fJ4ro+l7VyoVxONx9PT0QKPR1GQ1FEixf/9+/PrXv67ZTum5TCYDv9+P3t5e5v4RN7VUKsHn8zH/i+6r1WpFPp/HmTNnsH37dszPz6NUKmF0dBTz8/MIhUJcDEegzJhKpZKkAScnJyWp/7GxMdjtdhw8eBDpdJrHm2QyyYuMfD7PkWGNRgOXywWXy8V2YjKZkEgk+DwWFhYwOzuL8+fPY3Fxke0QuLAob29vx/T0NJ9XqVRiyYyenh6oVOtFNCMjI+js7ITT6ZRkD5qN4G7JOdu3bx9mZ2fxmc98Bp///OdZB0WOS1WjFwf5jVAvJdXoeI0cmHr7yl+vVqs8KaZSKda3oqiaSnWhRx0NRvLUJw1sJGQXCARw9uxZnDlzBidOnEA0GpXoBzVyyMTv08g5U9AcxAc9Go3WKLRvBhJCbBaN7mWjfcXf9WzQZrNxYQBwoSpKFIOV2yClreQ2+NJLL9XYYL20pfyc5c8JvVen0/HnNOKqKlgHcacAMH2CuGKULtHr9ZIov+ik0L5AbSEBULvAoNQ3ccpoO9FE9Ho9pz8pIpXP5/m4VElOUTgqQmhpaYFKdUEXStTkI3oIOWfEI0un01hYWMDY2BjOnj2LU6dOMTeI0vl0fm63m6kI1CeR9MuoxyOwLoTe1taGbDaLxcVFTE9P/84DCL+PeOaZZ2q22e127Ny5E5FIBHq9Hg6HA1arFa+++ioqlQo+/vGP45VXXkGxWORG5efOncNrr70Gh8PBJH8A+OlPf8rHDQQCnHoUHTMAeOSRR6DRaGC323H06FG89NJLzN2SRz9TqRSef/55bNu2jTXt3vWud2F4eBhGo5GdMnL0TSYTfD4fC92SbJVOp0Mmk0E0GoXf78exY8cQCoXQ0tKCoaEheL1evPTSS4hEIrj++uslzlm5XEY8Hsd1112HbDYLr9cLt9uNkZERlMtl7nZA6c0PfehDTd2PLbdv4jfWmVTEypyN0Kh9U73jNYuNUnryCWSjz2008QAXqvZaW1tx/fXXY8+ePdi1axecTqekYTCF+M1mMztaFO0jbsXx48dx8uRJTE5OYmJiglWvG6WN5N9R/n3l2ymKs7y8rLRvaoDe3l4kEglJepMgpgmbxUa2s5X3bnQsuQ3u2rULu3fvhsvlamiDFLVYW1tvdUPpdLkN0sAncjc3ssV6501jBF07KqghTTkFtRCvYW9vL2sdNurwIXe2rFYrLywoGkWo56xtBrkjQxVswHr63+12s5NvNBpxzTXXYGhoCPv374fb7ea+xJR2p+IVcSxMpVKcUj9+/DhOnTqFqakpTE5OcnSvtbUViUSCF0yUvieBU4rKhMNhTrdR0QKwHvmjqAcA9PX1caWpglr88R//MZ566ilJEQXhpptuwsTEhIQHCQDvec97cOTIETz22GP47W9/K3lNFEWOx+Po6OhAKpXivphUHazRaLgXZrFYxNVXXw273Y7V1VU899xzAMCpQbGikmySenB6PB709PTgpptu4nHQ4XBI6EZer1cyrhuNRkQiEczOzuKXv/wlzp8/z4sFwi233IJqtYrz589jenqabc1ms6FQKKCtrQ0GgwGrq6vstBmNRhw6dAjhcBiVSgVutxsvvfQSH7MZ32ZLkbN6nvWVxEYRtEaT2WaT4lYmTZGDJg6IVFWSzWYlxHFR4kOMqNFKNZlMIhwOY2FhARMTEyyaSM1j63F3mj0/cZuC5tBoEUFNpjdbZIho5CzXQ717JL+X9e6taIO0IqUCl41sUFRYb9YGxc/b7LvUe0bESmUlatE8UqkUc8DkIJ4ZsH6fK5UKLyJojNnofXI+I01YBDGyRv0IxSgdFUlRcQtVZxIHiApbKOImFlWRk0gZBNEOp6am4Pf7EQ6HJdpYpJ9GcjEijYUiNRTRo2yGyWTicblarcJsNnPK82IoLm8mJBKJhvJLarW6bmHP8ePHMTQ0VDOmdXR0IJ1O83jU0tIi6RxB6XbSChUdwlOnTsHlcknU++mzidSv0+ng9/sBrEdhY7EYuru7YbVakclkoNFoOOpKXEhy6qlCOZfLwWg0IhaLcTGe3++vaZOmUq23TiORcmDdIRwaGoJKpUI6nUYkEuFIIABu90jKDheT3dqSc3bdddfhvvvuw89//nOUy2W84x3vwJe//OXXpWdZvclro+3NYKPjiXwbGjjE6kyxf5tcA41y31SBdO7cObzwwgtYWlqStMZo5rzpfMTf9c5fqdbcHGI6iUAEfyJhN5tiB6RR2a1e+0a2J3+dbFCcjOvZoEjOpv1yuRz8fj9mZ2dx9uxZvPDCCyyZQZ+xmWMmvyaiLYrb1Wq1hP+joDEOHjzIg7uovA6gpjWXKP1js9mYUC9C7I24trbGDZcpVUht75LJJGvmUeUncS7FYiTRWUun05JzFFvdUGpVrstHwqQirUO0wxMnTiAcDiOTycBgMPDYmkgk0NfXx5Ps9PQ0UwnECZ00zMRiG4o6Op1OHDlyBIuLi9yJQUF9PPvss5L/r732Wmi1Wjz33HN48cUX62YYotEo7rvvPgwMDOBTn/oUdu7cyUT8f/qnf0JbWxun5EOhUA13krTD5CDZiTvuuAOPPPIIb7fZbHA6nRL6CVUIO51OmM1mnDx5Em9729tgsViwsrICp9PJ46FareY0PI2HCwsLCAQCyGQyWF5ernkGl5eXuVMCgSgbH/jAB3DvvfdK+jMTnnnmGRw+fBg2mw1+vx/ve9/7cPz4cYkTtxG25Jzdc889+MpXvoKbbroJJpMJ3/zmNxGJRPD9739/K4e54pBPjFuJRMlB7xVlDqhdCOlNUZkutXSiVSmtEJPJJBYWFjiFdO7cOZw/f549arG8vJ6TVs8hu1zpYAXrE2BraysymQw7MQT5/djIRsR9mrW5rSwkxGIXatUjtogSbZAm1c1skERJ60kciJGwRnYnpuLpf4qcxONxfl1BY5w8eRJAbTqRUj9ixEJ0gqkxuBzkTGm1WhQKBZ44RBI3AJ6g6G/izVLVKAl8OhwOqFTrIuOUqqb77Xa7mYdEdki/idNGjh8JeIZCIZw4cQLj4+MYGxvDmTNnuP1ePp/nbid2u13Sz5mU30ViP7WJymazEgFm6tFIzkWz/OQ3M372s5/h7/7u73Dy5EmYTCbuEuDxeCTyE6Lz73A4eGx5/PHH8cADD/B+d9xxB2ZmZpBOp7F7926srKzg+eefR7VaZRsjB7xe3+6PfexjWF5eRn9/P/x+Py9KFhcXJecDXKg8XltbQ2dnJ1ch6/V6JBIJljpSqVRM9YnFYnjxxRcxMzOD8+fPQ61W49Zbb4Xf75dol7300ks4deoUHnroIdx333347Gc/i6effhqzs7P4zne+w89Xb2+vpNOG2+1GJBJBJpPB4OAgnnjiCea9NYMtt2/69re/jb/4i78AADz55JO47bbb8N3vfveKDcByfkUjbMQlazY1utGxacLR6/Voa2uD2+2G3W7ndj1iCokkCNLpNJaWlhAKhTAxMYHXXnsNfr9fsoKQC4Mq+N2jUqkgn89vaidbcXobRTS3inpOj06ng8fjQWtrKzdXp1C/mMZcXV1tyga3en4bRa3F49EgpDhnG8NisfDqn0A8QbHzCCCN5NerPhRTn/JuEyQyS5A7dvRZYlSCtCFJe42ORXZI1W9kh1QxKuruEd+W7HB2dpZlFNLpNDcqJzFn8buIyOfz0Ol0HPkgJ5UKEyh1Rdp6lPKkDi9Kx5SNce+993KqULQNcoT0ej1cLpck8nPVVVdhZmYG1WqV5SkIJEEVj8c5oklFhDabTXLcevjP//xP7Nu3DzabDf39/ZiamuKK4Gg0ylw1itBTGh0A2tvbYbPZ2GYAcESWqtTHx8dZNJY4sfIoNGFqagqpVAomk4m11qgPLH2HtrY2LC4ucjEVtaKiwghaZDWbXt+Sc+b3+/Gud72L/7/ppps4H0v93K4UNkrhiWgmsrEViNIARqMRNpsN3d3daGtrg8vl4hUjpZBoxVkqlRCNRjE9PY25uTmMjo7i9OnTSCQSnG+/VMdsowjNxaTW3mxwOBysgUPtPxrZT6OUZbOp6Gb3rfde8X3Uw7CRDQJg8eJSqYRIJIKZmRnMzc3h9OnTbIOk6C1KZWz1O8mdVnl602q1SpwFBfUxPDyM6elpTqeQrAu1aCJHR0wJ0TYRlEoGIOnkQGmljaQkNBoNLBYLR+paWlo4Mic6dCTRQdIWbW1t8Hq9bIckSCsfC+PxOEcoRkdHMTk5yc6T3W7H8vJyTaX0ysqKRFMqGo2yCjzJIJCKu1gRSn1KCdRcm1rqKKiP48ePA1iPAM3Pz9e8brPZYLfb2Tnr7u5Gf38/NBoNcwCpEwBpJVKEKhaLAVjvx3nw4EGMj49zEUsjh6harWJ8fBxvectbuJiAHB1y0Ds7O9HR0YFz585x1DaXy6Gvrw8qlQrBYBBut5uljZLJJDKZDCKRCEZHRzE2NiaRthAFYycnJ/mZefDBB7kDxYkTJyT2BYAlNGihTw3UqYtRNBrlcbHZKO6WnDMqtRah0+leF/2YrUx4F8tDEz/D5XKhvb0dPp8Pu3fvRl9fH2ud0Wotl8uxenwsFmOZgvn5eczMzPANE/vLNVvI0AxhvN6EqaAxxBW3yB8k3hlxCzcqDNiKo9aMzda7z7TN4XCwDe7Zswd9fX1ob2/naj3SXqMU0mY2KKbRLuYZEZ0xMf1L1y8Wi3EUWUFjUFrTYrHA7XZLUjxEyl9bW5NIX5CtUiRJ7D4hXm+dTldzD8ROIy6XCyrVeheARCIBrVbLjcQp5Skn0zscDng8HnR0dGDv3r3cSJqccSoWKJfLSKfTSCQSmJqawtmzZzE9Pc3SCwaDAfv375eInVLjaYpw9PT0wGw2s/NGmm7EVSIZBGoBRFw8+t6VSgWLi4t1+aUKpDh27Bje/e53s2NG950WBbFYTDIWLiws4KGHHsKRI0dYF4wwMDCAJ598UhLl12q1mJ+fx7FjxySfKxLwrVYrtz7yeDx45plnoNfrsX//fkxOTmJsbIzvM8Hj8aC7uxterxd6vR4ej0eSerVarZxBePTRRzE7O8tCufU0x6699lrs379fUrF55swZLiiQO2bUM9PhcODAgQN4+umnUa1W0d3djYWFBRbVvfnmm3H69GkEg8Gm7seWRWg//vGPSxS/i8Ui/vIv/1IS0nz00Ue3ctimUS8adCkFABsdhyZFaprb19eHjo4OdHZ2oq2tjVdiJG6Yz+dRKBSwtLTEg8HY2Bj8fj+3g6Dv0KxDdjHnraB5uN1upFIpyeKCBDop6rDVgoCLvRf1HDfRBi0WC/r6+nil2N7eLrFBImUXCgXuz0o2OD8/zw2K6RzlKaNLsUm5g0ocI7PZ3HShiwJw1SOlZuR9SestFKgggMYh4vjRPaHqSQIdm2xLPlEQEV8Ead+RHXZ1dfFY2NHRAYfDwer85XIZ2WyWK+io8fPk5CQikQii0ShP9qVSCbOzs1w8RVIvJOxNemsqlQo2mw3Ly8vMo6SFE30nquSkhS+1HqOKTeIjKWiMD37wg8yfIqkreQWw3W7H7bffjjNnzuDcuXPI5/OYnJyE3W5HtVrlqu9EIiG55uPj4zCZTLBarZz+o6IrYJ0CYbPZEA6HMTg4CLvdzrZKDs7MzAxsNhtcLhdHb91uN6xWKzo7O+Hz+WC1WrG6usryKoVCATMzM0gmk1hcXOTIbS6Xg9PpBLAeqXY6nZzanJmZQblcRltbGzuk4XBYMk+YTCa43W7unLG0tIRIJIK+vj709vYiGAxKZEdIQPfw4cM1rccaYUvO2V133VWz7SMf+chWDvGGRD2Hj6ILdBO6u7tZlZ00pUhyIZvNIpvNIh6PY2pqCvPz8/D7/Ziensby8jIPJvWaT1/MuSqT3eWBnOsgRjQbDeT1opWXinrHEG3QaDTC7XbD5/NxdwqyQUohkQ0uLy+zDQYCAUxNTSEej/NAKe9BW+87Xez5i1FbUQZB4Zw1D3LGtVqtxAEhLiFBXDTIG4wDF7hn8ogZiRFXq7VSMWK0gUD6UiR27HA42Dlrb2/nqAE5WCTxkkgkeBwMBAKYnp7mfquivcViMTidTpYPIWeAUpT5fJ4LruTcITpnkfNLkR5yZDUaDbxeL3K5XA2JXIEU5Kh3dHTwNdbpdLDb7ewkr62toaenB8FgEEajEfl8Hn6/H8PDwzh69CjGxsaQTCbZwRef/UKhAK/Xi507dyIWi0kKXShVDVzoAERSF3NzcxI5F6fTCb1eD6PRiLa2NjgcDgn/O5fLIRKJcNUu9Q+mimg6NyrI6+jowK5du9g5C4fDiMfj8Pl82LFjB9RqdU2lr9FoRHd3NzQaDafR8/k87HY7XC4X7HY7XnnlFd6f5Dba2trQ3d3d1P3Ykgjt5UKzIrSXG/Wq0epNLPTT2tqKjo4ODA0NYfv27WhtbYXL5UJbWxtsNhv3DZubm2Ov/PTp09wTrlAocJRCLuzZ6Jw2el3+/noVnvLIC1VIKSK0taBrRW1ziBcBQOKkNVsZezkqNMkm6cflcqGjowODg4PYsWMH3G432yB1qSiVSpifn8fS0hJmZ2cxOjqKcDiMZDKJXC7HtrdRReZm/28UWRP7J4qN26mFjqiVpaAWt9xyC+bm5hAMBiV6T/JnGbggU0F9MCkdTxNbPZoJyWWoVOttZUh7jIjZ1WqVOZf03oMHDyIcDvPi0uVywev1Yvv27di2bRs8Hg9cLhc8Hg8LzFI7p1AoBL/fz6T/YDCIUqmEq6++GmazGSMjI8wzIucPWLej7u5unrjX1tY4zUmcslQqxX0V6fsajUa0tLQgnU5z5Ieq6anXYktLC9xuN55//vkrcQv/IOBwOCQpO7PZjPb2dpRKJe5nLceePXu4O8MNN9yAZ599lqkXJ0+exODgIFZXVzEzM4Pu7m7Y7XZUKhVJ8/BGHLd6oBR6R0cHNBoNhoaGMDAwAL/fL2kVVq2uC7AvLCzg1KlTXDVJvDSHw4Ht27fjqaeegs1mw7Zt21Aul3Hq1Km6n9vd3c0UgJGREdhsNnR2dmJ8fBw33HADQqEQ8+iGhobg8/kQDocRDoe5PZuIZtyu1905+10Rhhs5QfLJlXolUtsGn8+Hbdu2wefzwel0wuFwsOpwLpfDzMwMRkdHsbCwgLm5OUQiEZTL5ZoWJps5XI3OVXHOrhzEaybyzMQwvnhtL4edbubA0epUpVKxDXZ1daG/v19ig6TrlMvlOFQfCAS4X52YEmu0MNjK/xvZpFgEQBDbmKnV6hphRwUXQLxHo9HIDpTojIkOL1FKqKqRrrs4jsrvAzWvlzcMB8CcWaouB9Ydm3K5zGlBm82GHTt2sB12dHRwc2dKI5GO4/j4OJaWlrCwsMBpTDofcpDa29slaunt7e2sDp/P57mROlXlUdaBOgLQdxBFblUqFUfeKIpH14tSviSvoKA+PvKRj+CHP/wh/9/Z2QmLxQKTyYTu7m68+uqrWFxcRE9PD6e4e3t78dxzz6FQKMBqtXJ0sqOjg6Nr1CaJHGmj0chSOyaTCf/4j/+Iz33uc3W560ajkW29r68P27dvh8fjQXt7O/R6PXw+Hzo7O5FKpThaWqlUMDk5iVgshng8zj2DC4UC+vr6EAqFoFKp4PP5UCgU4Pf7G3bjEHHbbbfhT//0T/HhD38YAwMD6OnpQSKRwOzsrGRRZbFY8Ja3vAXDw8N44oknJBxStVqNQ4cO4cUXX9z087aU1vx9RaMJsV46k/a32WxcieR0OrkVBYkkksL1uXPnMDExgXA4jGg0KuGWbeaYKXh9QdEHiuxsxo/aCv/sYiGmM202Gzwez4Y2GIlEMD4+jomJCUQiEUQikU1tUPw+Wzkv0UndyNmTO2xb6Vf6ZgWR+an9kGiXBKrQFG2Q/jYajZKWNsCF+0/HIZ4OOSh6vZ5TlpQypPtGkxWJ1nq9Xng8Hq6WJOkW6nwSi8W4DVgsFsPy8nKNPE0ul2NStRxic3TxeSTncnV1lUVzyXmU2xjx4qjAh9KatIhROGcbo6+vD263G7FYjDMHarWaRYDJFru7u5nSEwwGWRSY7h9wIUVaLBbZSSYnmpx+steFhQX09PRgZmam5pxI6w9Yd3rsdjunMOk+E+F+eXkZ6XQamUwG4+PjXDhAwRatVsvSLcViEadPn4bb7a47PhmNRknnFWDdfldWVrBv3z6cPXsWMzMz6O3traFtUNuwpaUlpnWI7aKuueaapu7HG8I5a5Re/F2DPlOr1XI1kkj+J48/lUphYmICs7OzePnllzE/P89heHnTchH1JsPNOGQKx+zKoa+vT5JKEnksoq4UcHmc6mait3Ib7OrqktigwWCAWq1GMpnE5ORkjQ3ShLSRU7bRuVzs96HojRgto0btzaxKFYDJ7iQiTNeNJpdSqcSOFfGACNSWhpwzcQzSarVcLEB9LsnxiUajLLNhsViY70MOlNFoZPK/1+vlFknkzCUSCczMzMDv92NkZATz8/MS509MWwLr7alSqRS6u7tRLBYRj8cRi8VgMpk4elgul1EoFFCtVlnklGC1WtHR0YHl5WWu3KRJnpq2k0NAfV2J86tgY7hcLgwMDCAWi7FDa7PZoFKpMDU1hXA4DGCdk0WyK2J6sr+/v24lYrW6LkPV1dXF8j5it4F7770Xhw8fRktLS40SvzyVSkLbRKEIh8OIRCLo7u7G2NgYZmdncf78eQQCAVgsFnYkKTo7MjKCXbt2Me8sFotBr9dL0rPAup0dOHAAmUyGJUbGxsbwox/9CF/96lfx/ve/HwAwPz+PgwcPIpvN8rUwGo0IBoMYGRnB8PAwdu7cyZWf+Xwer776alP34w3hnAEb88Eu1zE32keULDCZTOyYOZ1OrkSirvWnT5/Ga6+9xqRrSkNRefpWzkVxvF4/TExMAABPCsSDoYlLtAng4hcMzaQyxZQUFaJ0dHTA4/GwDarVamSzWUSjUYyOjuLMmTPcfoQiDaJ6Ox3vckduN4pEU8SiUChwT7329vZL/sw/ZAwPDyMcDiORSDAxXoxMGo1GXu2TrZCDUy6XOWoPgFfqxPUrl8vsNNP7ROh0Ona4RCkEir4aDAY4nU5OY5K8AhGgz549i/HxcQQCAQQCAV7gGI1GtLe383eScw71er2Ez5nJZKBSqeB0Otkxo2gZpc9IMysej6O1tZUjFisrK+xwUnSQ7DCfz8Pn80l0ABXUx/Hjx2G329lRIUcaAB544AF86UtfQjAYxPT0NPbv3499+/Zhx44deOyxxwCsR7aAdc2vgYEBPPPMM8xbI609jUbDfFm1Wg23240vfOEL+PCHP8znceuttyIej+PEiRO86PP5fKhWq9i/fz/cbjcSiQSsVisKhQIymQzGxsZY25GEdNPpNMbGxvD5z38ezz77LEZGRgBAQu4/evQogsGgxDEDgJ07d+LXv/41AHC/zmg0iscffxyPP/44DAYD9u7di8XFReaYA+BCBafTieHhYWSz2Rq5DtGh3Qhv6DKqS5lItpqyIRCxmdSuqRqOdFImJiYk8gQUNt2oAu5SoheK83blQRMB8VzE1BFNhlfKMat3bEozicr/wPpgs7i4yHo/c3NzrCVGKaytfv5G+12M7dFgSinYRg2TFVzA7OwsisUiTCaTZCFAfKpyuYx4PM5VloRAIIBsNsv8XeCC3AY5ZAA2LMigfpTkxImgiYYiZRRRTiaTCAQC3AbM7/cjHo+zY0ZK/UTslztFer2eyfvED6PqzFQqxRFDvV7PP8TDo/9LpRLS6TQXB5ADSItkYF2qo1gsIhAIIBqNNhQ7VbCOSqWCkZGRGkcFAKanpzE8PMz/JxIJRKNRHDlyhIWPn3jiCQDrztnRo0cBrEeKlpeXWWKF9Bc1Gg0CgQBGRkbwve99T/JZLpdLYoskY2WxWLC4uIhAIIDV1VUsLS1hfn4es7OzmJ6eRiaTgdfrxcGDB/m9RqMRhUKBNQJF3HXXXXjmmWdqnCU6t+7ubphMpro9RUXxXLVajdbWVvT19cFut/P1mJubg0ajYckOglh4thH+IJcSF+OY0W9yzsR2H5VKBcvLy1hcXMT8/DzGx8eRSCRQKpVqxDzFz1ccq98PkAo6EbJF+YJLwVbfL7dBsSXTysoK4vE4FhcX4ff7JTZIE3EzEborCTElSymyYrEoIcsqqAWlAYlLRc4VRZeoAlGemqOiJFInz2QyLKuh0+lq5DRI84uKRYh/lslkUCqVOGVODjVJWMg7oEQiEdbRo7Y25NyRRplarUY8HmfOks1mYzvo6OjAwsICNBoNa5CR8yeqp1ND80wmg2AwyLwhOj+RKyRqscl5PpRaV4oBNkYwGJREedra2qDRaLC0tITnn38eu3fvxvXXX48HH3yQeWkOhwM7d+6UVDnKo+XU9oi0zwBpQETsY2mz2ZDL5diB6evrg8/n4yK8+fl5pFIpbNu2DdPT04jFYuzw+Xw+9PT04N3vfje0Wi0SiQRLcVQqFTidTkma9IMf/CD+4z/+g/93Op28GA8Gg/jUpz6FqakpPP744zXXanV1FYFAANVqFU6nE16vFz09PRgfH+fI9fz8PFpbW7mzgjxqvRneENWam2Erp9jsBNVI24wUht/5zndiaGgIGo0GiUQCr732GhYWFrC0tMQ3mNJf9Y5/MRPlZtvkxxY5RfX4RUq15sbYuXMngsFg3YeG7FKMbG3FudmssICOTRAXCUajER6PBzfeeCMGBweh0WiQTCZx5swZtsF4PM73XG6D8s+/HLZYz67r2ZzYEiqdTvMEqUyMjbFjxw4sLi5yhNFgMHCandLc1CLHaDTCarWiq6sL586dY2dGXFjIq95sNhu3lQHW+WpOpxPt7e3Mp6FjWK1WGAwG3tdqteLw4cPo6+tjruPZs2c5nZPJZNgpa21tZa0oOUjaolwuswOgUqlYqoHGVIfDwfIvlL3IZDLIZrNMACfY7XauQF1dXYVWq5VUBJKoLTV6b21tbTpq8WaE+Cxfe+21mJ2dlfTRHB4exqFDh/CDH/yg5r1arRZ33nkn/u///o+vt91ux7XXXouWlhbmxTbCQw89hO7ubnzyk59kugkVnFgsFtx4441417vehZGREeRyOWg0Grz66qsIh8NIpVLweDysxefxeHD99dejUqlgdnYWjzzyCH/ORz/6Ubz22musd3bgwAGuHP7Upz6FH//4x0in0/j4xz+Of//3fwcADA4OYnJyko9x9OhRHDp0COl0Gv/6r//K22+66SZ0d3djYmICZ86c4cVIa2srrrvuOvzsZz/jfZvxaV7XyNnFpFwafamLITM3Ev+sVCpIpVIIhUKoVCpYWlrC1NQU9ySUE/63ykn6XaVrFWwMCmdT5IkmNYpCXalUZqP30OdRqkm0QVJZTyQSzM9pJGh8uZzIZiFG/Oj8y+UyRzoUrs/GqFarsFgsHO0hdXsA3C6P0pJUnZZOpzmqKi+6IMkJcljS6TRPXKQVlkqlJCX+dOxsNsuSFuTkxONxbocUDodx/vx5jraJ6fRMJlMjZKvVamEwGDgdqlKtV8Jns1msra0hGAyyiC21bCL5BZK/IBkNMb1E/DedTgeLxYJcLodisYhsNssyINTail4jp0HB5mhra0M6nUa5XGbHeWZmpmFhRaVSwcMPPyzZtrq6il/96lfQarXo7e3F1Vdfjddee02ipbd79248/PDDePTRR6FSqSSRO5vNhq6uLkxOTuKXv/wlHA4HZxBmZmYQiUSgUqlgNpt5UVKtrvf0vffee+ueJxH1CaKkS0tLC44cOQK/34+XX36Zt5NjptPpMDAwAJ1Oh+9973s1jv709DTGxsZQLBYlEeBsNot8Po8/+qM/YsmYZvB7N2peaceGSnwTiQR0Oh1KpRICgQAikQgKhQK3CZH3xqS/m4mYNPva5SZyK6gP4qnIZQouphBgK1GqjaK45JxptVqUSiXWjaJ0TqNqzK1wFpvlQm51EUWpNJJHqBfZU3ABNMkYDAZYrVZJhIGuZaVSYVK/OPATBYOibuQsUUpTo9FwcUC9ym9ywMjxocmjWq2iUCjAZDJxBKBYLCIUCiEej0vSryrVuj4kSRoAF5xJimbRcdVqNWw2G1paWjgyuLKywtFBcihpO9ENxG4eFFmk70LflapOiWNH383pdHI7HwXNgSK54jVbWVnB/Pw8a5gBUh0yEd3d3QiHw3wfk8kkduzYgWQyidnZWQDrESXSLHv++edRLBYlWYxyuYy3vOUt8Pv9SCaTOHXqFNxuN5LJJPx+P6fbtVotzGYzL1zFtknAeuN7olhspC8WDod5YVQvAtzV1YWenh7WUAPWU6FUDFAqlRAKhZgXSdtKpRKCwSBuu+02LC8vS3p2boTXNa25mTNzubBRdZn4Nw1mBoOBK0yoibS8kq/RsbdC/t/otc2KCxqlNsXfa2trSlpzA8ivO8kH0KBEk5w4QMknuGalTjbaR0xpkg1SaxKdTodisVjTn1UejdpqBO1SHLN6kWM6J1GOJJvNMgdK6RDQGOI17u7uhkqlYh6k2HLIarVyVwBRd4pAVb0k+EsRYLVaLUkrU0seKnSighKLxYJ8Pi9JHRqNRvh8PlQqFY5Mka4VANbcE8+lpaUFLpcLyWQSxWIRlUqFJTHofaQvRYR+qkgVI13ySb+3t5fJ/xSlE9s1kQ2urKyw09ra2gqHw4F8Ps+Vngrq49VXX8W3v/1t/PCHP9ywiOe9732vJEXndDrR1taGtrY2HDt2DDabDXv27MELL7yA4eFh7qIDrKc6r7rqKrzyyit1ifYAJGPuO97xDsTjcYTDYQSDQV7EqFQq3HjjjZifn8fi4iJuvPFGvPzyy1ypeeTIEbz88sts9zfccAPcbjf++7//mz+nr6+vJnosgroCEP98dna2xmnr6Ohg7T2v14t0Oo2VlRUuMBMjcwcPHsTJkycB/B50CGi08r+cp7TZxFmvUo6kDGhFWCqVuBKoUcSMjnU5JsmNJshm+GaKc9Ycent7EY/H2ekhiIODPHVYL8q1lWhZvf03skHggv4VSQ/Uc8jlx7+YRYK4z0b7iVE78XldWVnhCdJkMnG0plqt1pSTK7gA+bVubW3lZ1fcR+Q+ir0IgfWoVj0HmGyIokkUgaOCAZqEqaoNWHeutm3bhlAohGQyydE38fgajQatra2Sgg9KmwIXuJM0WdFxRTI/tU1LJpNcSEAyLPJnQqvVwuv18sQHAMlkkq+BSOamlK5Op0Nrayt3CVCr1Th37tyW7s2bCWSHnZ2dWFpawp/8yZ9Ao9Hg4Ycf5ggocGHhRTCZTDw++Xw+dmA++clP4rvf/S4A4BOf+ARXZe7atYvlLERRZIPBAJ/Ph3w+L9FLc7vd6O/vRygUwvLyMlwuF/bu3YuJiQmkUimuZBaxfft2qNVqzM3N8fFbWlrgcDgkkjHUHmxlZQVmsxn5fB5qtRpDQ0Po7e1FuVzG9PQ0xsfHG4ppX3fddVheXq7pv0kg9QeKCt5+++0S57YRXncpjWZSM5dy7K3sIzo1VIYtnxS3+nmX6pg1+9pW9lGwDooaAI0jlZstFDZLPW/VtuvZoFyputnPuxhb2Op7xKgfOWaUfqPtSoeAjUF9egmpVIodnnqVuCqVqkYhX7RTsXUWLSzVajVLYlBqVHSCyOGh966trUlEXOWOHzlBFP2gaC+w7qTncrmaanaxSpS+k6jiT2lM0fGniY14avQ8iMKyKpWKnce1tTXmrFEXjVwuh0wmIxGzVdAYFHldXFxEPB5nzh9V08olSShNDUBix2azmf/u6Ojgv8lZop6owLqT1NLSgkQiUSNkq9frma9IXTJSqRSmp6cRjUbrjlnpdBp6vR6HDh3ibblcDm63W7IftWjU6/UIhUJIp9NQqVTYuXMnqtUqN3GXj2EajQadnZ0AUJP+JahUKjgcDnR0dGBgYIC3i7SEjfCG4Zw1msR+F6TsepMx3YzNKvUu1plq1jHbqgOnoHnQYE2cFkqx0CBwKfpmwOb3v5Ft0eeKYqT1jrtRpFaMrImTWCPHs5FTJ38O5ZE78RpRQ24AzEmiCVdBYwwODiKbzSKVSiEYDEomAtIBW11dZXkSuqYUqZQ7TuSgkINfLpeZf6VSSXt3EsrlMlwuF3Nzzp49C4fDwWlG8XwMBgOy2axE54miYmKXgmw2C6vVyo4VveZwOGAymVAul5HL5Zg+Qt+bshYUXbNarTAajZiZmWGnjvYlLbZ0Os2UFIfDwSlT6h5QLpcva0bmDxFDQ0NcKQkAv/3tbwEAhw4dwtzcHDKZTI0TQh0kKpUKO3PkoE1NTaGnpwdqtRqhUIgjwsC6llkul+PosMvlQj6fl6TxAeArX/kKfvrTn2JkZARmsxnV6npDc5GMT8/IgQMH4PV6cfLkScRiMTidTuzYsQO/+c1vAKw7jhMTE2hvb2e+ms/ng9/vlxwvkUhg165dePTRR1muQ45rrrkGt9xyC37xi19gcXERNpsNt956K8LhMPd/pX6jLpcLO3bswOrqKs6ePct6cJvhDeOcNcLldEQapYA2gjyN2Uxk4nJsb+SsNpPyVLA1EFnZbDZDpVIxcZkcDzFyKqY8SXC1XvSiXlRDlI0RI0vy7fKUofh++efJ05j10q7iOYkVlWI/URpQRS6TmNKt91l0DCL+k4p9qVTiaj9qt6OgMSgaJJfAoIIkkqogrhdVXopOL3WQUKnWO5wkk0nJ8YjDRTZE94uKDYjHJb6HFi8UbSDOGaWHSIHfarVCpVIhkUhIBLxJfJRsxul0coN1cZKnAhdRBFqj0cDlcsHhcGB5eRnBYJAV6AEwp4cWMQaDAXa7HQ6HAy6XC9FoFMFgEPl8vqbyVUF9iI7Z7t27mbi+vLzMunfUUcLv9/O4SB1KxKb0ACT6YE8++ST27NnD3Rump6cBrI8xZrNZUgTT19fH7cKMRiP+3//7f2htbZXooYkoFouSnq00Rk9MTGBiYgJer5ejY8ePH+cenQsLC/jpT38K4EJ61Wq1YteuXdi+fbtEZsbr9WJ1dZU5i+fOnUMwGEQmk0FnZyey2WxdPbRUKoW1tTU4HA6cPn16S/fjdeecNaNzdim4lNROo9+NjnslnbJGf8ujJCIUztnGoFYxNHiLDpGork6DkFgFJ3faKEJFDgy9n5wd2kbHF9XeRcdIjHKJ6UGxQEE8B/o8UZdNtAlytOh4NHCRYyVO1uL5khMgjyBSizLab21tjVOZKpWKoznULJm+k6Iv1Rh0r6gjRCaTQbVahcFg4JS2aIfkDNP1p33pXpGkALVQmpmZkTjpdL+ppQ7ZgrxamaDX63niI2eL+rgSF6larfIkSdEs4u+IYrhE6Acg4b6JBQbic0Q9WkulEldxAhd4PPTcUZEEHYMawUciEd7e1dXVUIdNAfA3f/M3ePjhh7G4uCiJoh04cABjY2M1iwdAmgEwm83o7u7G1NRUw8rY7u5udnxoPJKLVDudTrbneDzeMPK+f/9+5r9NTk7ywsRkMkkKPxwOBywWC0f1yZaz2SxXjsoxMDAgacS+fft2mM1mrK6uYmxsDFarFQ6Hg6N28Xhcku51u92488478fTTTyMQCECj0fD3fOtb3ypx/BrhdeecXQnIUy9bfe9Gv+V/i5/X6Dya2d5oWzPnuNG+ChrDYrGwU0KOUCPJAaBxaq8eGr0uRr5ov3r7i9Ey0WkUjy//rI3srZFTJ38P7St3IskpEJ1O+TGoYk6v13PlIOlbKdgchUIBHo9H0jqOnGFxsqP/ibPT0tLCZH9Ke1YqFeh0Ou4PLC6CydETJTbEhQCwXlVns9m4owBNzNSYnJx+4q+trKxwD2JyEOnZIrsQVfrF1lBiVwFxoZDL5bjikxz/SqUiccQolanT6bjPYiwWQ7FYREtLCwYGBmA2m+F0OpnQrqA+vv71r+Pw4cMAwFxCg8EAi8VSlzeq1+slNlOpVDA4OAir1QpgvbDgr/7qr3DzzTfzPgsLC9x3Vy6RAqwXaSUSCYRCISwtLW1IiTh48CAOHTqE/fv3A7jAgyQHjWgWlUoF8Xgc8Xgc+/btA7AeINqogpwcM5PJxB0HrFYr+vr6+LuSzS8vL0scs8OHD+OTn/wk/uzP/gwejwe5XI4ds3379uHtb397w88V8bpGzuqJaG7mZDQ63Wadk83228zx2ex8LyVKtpXjb+Y80sSqRM4ag66ZVqtFa2srR9EolVQvKkZEaXovTRRyB4nuQaN0oOgAURqHHB+qSBOrhok/ROctTjTi8WhfioLodDrel5pqazQa1uKhCW91dZUnV5VKxRVv5ASIwqBE2qaWO/T9qCqOKu5ogNfpdDUVsQouQP6Mk9o5VTpSZFJ+DYlXtln3BZLniEajzL0S0+nkEBUKBU4v2mw2STSWWoXVg0ajgc1mw8DAAAKBADtUIkQtNopikK1mMhlOmZHAMjmZ4jUizh3ZNT0zpAVYKBT4c91uN9xuNzo6OhAOhzE/Py+RAFFQi5tvvhkvv/wy88AsFgtaW1vR3d2N0dFRFg4G1vlpVqsVIyMjEsft5ptvxtraGuLxOE6dOoXp6Wn09/dj7969nCaVCwrTWGSz2dDZ2YlgMMi2KoKkeq6++mp87nOfw9133y1px0T4xCc+gQcffBBra2vo6+uDxWLhsW91dbVGBw1Yt5cPfvCDePrppzExMYEdO3awSLnVaoXT6eTWYGtrayxMK+9aQWhpacHtt9+O559/vm60thk7fEM5Z1cq+rOV427k9Mj/v5KO2kb7bORA0m/FOdsc4jUjh4siEJRuoYiQPNJVj9slihOLESfRaaLBjfr/kcMjpq1oMqbX5CkfmrhIgNFgMLBDR6kmOqe1tTVJdRxJLlSrVa7eo8q2UqnE35UI3sAFToc4EdL3IKcNAJOv6TyoTN1gMOD8+fNX7D7+voPSlwSxz6RoZy6XC9lsFpVKhZvK008ikeB9STFffC/piBG/jBwfMaJKzh691qjK1uVyoaWlBXq9HolEgp8ZufNIumxkExQpoWehWCxiZWWFbY14SwaDgX/E60K2TLptomApNU7XaDScFia5j56eHiSTSSwsLDStzv5mhNlsrtE3k+s8yiH2TAWAPXv2wGKxoFAoYGpqCh0dHdDpdEgkEpxuzGQycLvdbDsejwe7du3C6uoqxsfHUa1Wa/TotFotjhw5gtOnT6O9vR233XYbvvWtb9VNtb73ve/F008/jWq1CrfbzVpmBoOBixIKhYLEfoaHh3HXXXehWq0ilUrhxIkTOHnyZI0Wm8PhgM1mYz01kavW3d3Nch/AOk+tVCrB6XTi8OHD+NGPfsTHacbt+oNMa74eaMYBvJR0ZiNnUQ45MV1BY1DoW6VScXk+6UDRhCWKW5IDR5GmarUqmWyI2EyOFzkpYqSLnDC1Ws1pKzHSReRvkexMXSmMRiNHpkRHjlZvYgWb6GiK50/fiY4pVlhS2qlSqcBkMnEkjHhP9N0o2lepVCRpN1F2RpRzUJTZN4bP5+NUEHCh/ZX8OSbJAmp1lE6nkUqlUCwWYTKZ2O68Xi+LZxLo3ra0tMBisdTon5HjRPaxkfwJnYfJZOJKyHpRNep4QAtDipAQT4cmVjGVDoClO+x2O8xmMzuWJDBLnVrovS0tLbwQAC5MfCIXSK1Ww+Vybe3GvMkgSl8QNptLaAwgiIu1UqmEmZkZjI+Po1QqYWBggIuDxIi+VqvlYo1YLMa9MwlOpxN9fX08XicSCRw7dqyujXq9XsTjcRgMBm5ITiiVSlhaWkIoFMLKygq6u7sBrNtlPp9HMpmETqeD2+1GW1sbvF5vjdh3MplEoVDg7TS2E0dODIJQj1iDwcBZCbVazRIcm+F1r9YUuTSNuD6ES01pNnMuzb6+WcTvYs/pch1LcdI2R29vL+sfiat+t9uNdDrNq0iTycSVnOKKTqvVwmazIZVK8UBBAw1JGNA9sFqtNdERmiDFlafFYuGScZGrZbFYODxPn0V8ECJj034Oh0OSFjAajTCbzVhbW6vpXafX67G2tiZpb0ON19PpNDKZDDus1CuT2vcQKTuXy6FQKKBQKKC9vV1S8p5Op5VoxSbYtWsXp43EZt8iP6uzs5OrJqlVEnCBZ+N2u9HZ2cnOG90PMe1SKBTQ29vLZH1KzVSrVfh8PiwvL/O90ul0aG9vh81mg0qlQjqdRjKZZMmKYrGITCYjiSxQE3OqUEun0/D5fHC5XAiHw5wON5lM3FgdADe3VqlU/BySJlU0GmUNNYPBIElJ0STa3d2NarWKiYkJieI76aeNj4+jpaVFqRreBB/72Mfw+OOPY3x8HDabjRdoZrMZmUyGaR/UbxUA8vk87r//fuj1ejz77LNwOp2IRqOYn59nThc5VTqdjseVRCLBbbuoepPGpmKxiK6uLmzfvh3RaJQXyqOjoyx6HA6HmY5isVhgNBoRiURQLpe5hdK2bdvwtre9DQsLCzXaafl8HgcOHIBOp8PCwgL8fj8ee+wxrkY9evQozpw5g56eHnR2duLkyZP8bCQSCXR2dkKv1yMQCECv1yMWiyEWi/GYaDabsWPHDkQiESSTSTz00EM4cOAAUqlU01mE1zWtCdQqsF8ObHS8ZiNc8n03SiE2Ou6V3LbR62KVHK2ulbRmLeh60QqOVuN2u511agg0UJXLZcnEYrPZuAJNVMinCUzcTxTarNdah8jNACQOF1W1iRWSNNjReRcKBahUKiZZU/SDni+RAC6u9Oi8V1ZWODVE50D8O5GYTt+Vvic5ffIqPJPJJEkvySuyFFyASrXevNlut/MkIkZb6b65XC6ukrTb7TWaUAC47Rc1DRdV9AkajQZ2ux0mkwmpVAr5fJ4jnuJ0QAsNs9kMvV6PVColccYo+iGm6kX+FwCOEJO9ijxLMa3kdDp5TgiFQhInUSxCsdvtzFcLBALcwxUAFzBkMhlO65K2G0V666XBFKyDxsPt27djYGBAosdFavmJREIyrlFTc2BdNmJ4eBjVahW5XA6Tk5Ms30JOm1qthtvtRrFYZPuOx+NsjyqVip8BKo7x+XxYW1vDCy+8IDlfk8mEP//zP8ftt9+Of/mXf0EkEsHi4mLdlkw+nw9XXXUVfv3rX0Oj0cDtduOaa65BLpfD8vIylpaWarhofX196O3thcPhkCj6Hz16FJOTk0gmk+jo6EBXVxdyuRwWFha4vRmwnuKl3qNihwGSHNr0fryezhml9MRS6suNrThj9bY166ht9nmX4pRtdV/ggoOmOGeNIV4/ikBRSkmUoKDUI71ONqvRaJgTRhEBmgDEkn/iJdB7zWYz823oMygyIEp7qNVq1nYiRwlYn4BtNhtrV1EUi3g6JDKq0WjgdDo5srWyssKTLTW0zuVyWFtbk5DAK5UKC06qVCq43W5OX6XTaXZUTSYTv5+uIX2OmPJVqVR1ibsK1kG2Y7fbEQqFeDsRkSlqJaKzsxPRaJQXBDabra5yvigiK29STa2NCoWCpFWUTqeDw+FALpfjhYjFYmEenHgMUu9XqVSIRCKS1LrD4WDxWfo8lUrFsiryVnmUUqVFEJ03RTOWl5c5hen1ejE+Pl4TjfZ4PNwEm3p0kh1SZamC+hDHwxtuuAEvv/wy3wOSJyGHl6JcQ0NDyGQy3FWA9t22bRvUajW3NNq3bx9GR0d5n56eHphMJo78Emne7XbXyO4MDg7C4/FgdXVVIkHR1taGm266Cbt27cKDDz7I2mlyGQxg3fYPHToEq9WKYDCIcrkMi8UCvV6P5557ruZa9PX1IRgM1tiLSqVCf38/jEYjcrlcjSOo1WrhcrlgNpslC3Gn08kFBs06Z68L50xOrpa/ttGPqPkj/2lm/8322ehzG/1d7/9mtjezbaMfsam0/H8xramkN+tDXsZNqzexxLq1tZWV02nSa2lp4ZW+eI0dDgcPYARqAk3RD4p6UHQKuCDEaLfbJZ+tVqu5rYkIaqcCXGiFQilOSp/SwNDS0sI8NXovOVZiWyiSZSB9KEqfrq2tMfmb9q1Wq8wnyufzvFoU06SFQoHlEi53ZPwPDcTPK5fLcDqdvJ34KW63u0YPkriExK0ZGBiAx+ORXOtqtcr8Mo/Hg/7+fsnx4/E4zGYzWltbJce2Wq3YsWOHhAeXzWah1Wqxa9cuOBwO3l4sFuFyueDxeCQcIJPJhMHBQQnPixY1BK1Wi6GhIfT39/NCMp/PQ6VSwePxoKenh78HHSeXyyESicBqtbLwLmFlZQX5fB7t7e1wu92SbhUAap4jBVKI42EoFMJ73vMeTgWXSiWk02kYjUZ87GMf4/127dpVs/AnB3779u28TWxfBKxHxTweD7xeL6655hreXk8PcWpqCqurq/jWt74l2d7a2opXX30V3/jGN9gxA4BPf/rTNccoFos4ceIE9u7dC6/Xi7W1NZw7d07iVBIOHz6Mf/iHf5A4Zrfeeis+85nP4K677sLMzAza29sxODhY816SE3n729/Oqc5wOCz5js1ycF+XyFkgEGAynoIrj4WFBfh8vtf7NBQoUKBAgQIFTeB1cc7W1tawtLTEbT8UXBlUq1VuL3GlOzEoUKBAgQIFCi4PXhfnTIECBQoUKFCgQEF9KOEUBQoUKFCgQIGCNxAU50yBAgUKFChQoOANBMU5U6BAgQIFChQoeANBcc4UKFCgQIECBQreQFCcMwUKFChQoECBgjcQFOdMgQIFChQoUKDgDQTFOVOgQIECBQoUKHgD4f8DDLDU2ZsjG7QAAAAASUVORK5CYII=\n",
       "text/plain": [
-       "<Figure size 576x288 with 9 Axes>"
+       "<Figure size 800x400 with 9 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 20: 100%|██████████| 63/63 [00:48<00:00,  1.29it/s, loss=0.0498]\n",
-      "Epoch 21: 100%|██████████| 63/63 [00:53<00:00,  1.19it/s, loss=0.0481]\n",
-      "Epoch 22: 100%|██████████| 63/63 [00:52<00:00,  1.20it/s, loss=0.0492]\n",
-      "Epoch 23: 100%|██████████| 63/63 [00:52<00:00,  1.20it/s, loss=0.0487]\n",
-      "Epoch 24: 100%|██████████| 63/63 [00:50<00:00,  1.24it/s, loss=0.0489]\n",
-      "Epoch 25: 100%|██████████| 63/63 [00:52<00:00,  1.21it/s, loss=0.0486]\n",
-      "Epoch 26: 100%|██████████| 63/63 [00:51<00:00,  1.21it/s, loss=0.0484]\n",
-      "Epoch 27: 100%|██████████| 63/63 [00:52<00:00,  1.20it/s, loss=0.0469]\n",
-      "Epoch 28: 100%|██████████| 63/63 [00:52<00:00,  1.20it/s, loss=0.048] \n",
-      "Epoch 29: 100%|██████████| 63/63 [00:52<00:00,  1.20it/s, loss=0.0469]\n",
-      "Epoch 29 - Validation set: 100%|██████████| 63/63 [00:16<00:00,  3.87it/s, val_loss=0.0488]\n",
-      "Epoch 29 - Sampling from DDPMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 145.69it/s]\n",
-      "Epoch 29 - Sampling from DDIMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 150.64it/s]\n",
-      "Epoch 29 - Sampling from DDIMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 154.82it/s]\n",
-      "Epoch 29 - Sampling from DDIMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 155.34it/s]\n",
-      "Epoch 29 - Sampling from DDIMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 154.92it/s]\n",
-      "Epoch 29 - Sampling from PNDMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 151.79it/s]\n",
-      "Epoch 29 - Sampling from PNDMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 152.92it/s]\n",
-      "Epoch 29 - Sampling from PNDMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 153.53it/s]\n",
-      "Epoch 29 - Sampling from PNDMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 151.78it/s]\n"
+      "Epoch 20: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.69it/s, loss=0.0517]\n",
+      "Epoch 21: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.69it/s, loss=0.0499]\n",
+      "Epoch 22: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0511]\n",
+      "Epoch 23: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0505]\n",
+      "Epoch 24: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0508]\n",
+      "Epoch 25: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.05]\n",
+      "Epoch 26: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0502]\n",
+      "Epoch 27: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0485]\n",
+      "Epoch 28: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.05]\n",
+      "Epoch 29: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0484]\n",
+      "Epoch 29 - Validation set: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:11<00:00,  5.62it/s, val_loss=0.0503]\n",
+      "Epoch 29 - Sampling from DDPMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 70.95it/s]\n",
+      "Epoch 29 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 71.63it/s]\n",
+      "Epoch 29 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 71.35it/s]\n",
+      "Epoch 29 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 71.01it/s]\n",
+      "Epoch 29 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 69.55it/s]\n",
+      "Epoch 29 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 71.46it/s]\n",
+      "Epoch 29 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 71.31it/s]\n",
+      "Epoch 29 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 71.18it/s]\n",
+      "Epoch 29 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 71.27it/s]\n"
      ]
     },
     {
      "data": {
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\n",
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\n",
       "text/plain": [
-       "<Figure size 576x288 with 9 Axes>"
+       "<Figure size 800x400 with 9 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 30: 100%|██████████| 63/63 [00:46<00:00,  1.36it/s, loss=0.0482]\n",
-      "Epoch 31: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0476]\n",
-      "Epoch 32: 100%|██████████| 63/63 [00:51<00:00,  1.21it/s, loss=0.0474]\n",
-      "Epoch 33: 100%|██████████| 63/63 [00:51<00:00,  1.23it/s, loss=0.0459]\n",
-      "Epoch 34: 100%|██████████| 63/63 [00:53<00:00,  1.19it/s, loss=0.047] \n",
-      "Epoch 35: 100%|██████████| 63/63 [00:52<00:00,  1.19it/s, loss=0.0469]\n",
-      "Epoch 36: 100%|██████████| 63/63 [00:51<00:00,  1.22it/s, loss=0.0453]\n",
-      "Epoch 37: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0464]\n",
-      "Epoch 38: 100%|██████████| 63/63 [00:52<00:00,  1.19it/s, loss=0.0452]\n",
-      "Epoch 39: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0459]\n",
-      "Epoch 39 - Validation set: 100%|██████████| 63/63 [00:15<00:00,  4.04it/s, val_loss=0.0472]\n",
-      "Epoch 39 - Sampling from DDPMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 146.07it/s]\n",
-      "Epoch 39 - Sampling from DDIMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 152.03it/s]\n",
-      "Epoch 39 - Sampling from DDIMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 152.73it/s]\n",
-      "Epoch 39 - Sampling from DDIMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 150.71it/s]\n",
-      "Epoch 39 - Sampling from DDIMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 154.44it/s]\n",
-      "Epoch 39 - Sampling from PNDMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 154.15it/s]\n",
-      "Epoch 39 - Sampling from PNDMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 155.58it/s]\n",
-      "Epoch 39 - Sampling from PNDMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 155.10it/s]\n",
-      "Epoch 39 - Sampling from PNDMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 148.37it/s]\n"
+      "Epoch 30: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.69it/s, loss=0.0493]\n",
+      "Epoch 31: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0494]\n",
+      "Epoch 32: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0489]\n",
+      "Epoch 33: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0475]\n",
+      "Epoch 34: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0483]\n",
+      "Epoch 35: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0483]\n",
+      "Epoch 36: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0468]\n",
+      "Epoch 37: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0474]\n",
+      "Epoch 38: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.047]\n",
+      "Epoch 39: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0472]\n",
+      "Epoch 39 - Validation set: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:11<00:00,  5.61it/s, val_loss=0.0489]\n",
+      "Epoch 39 - Sampling from DDPMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.71it/s]\n",
+      "Epoch 39 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.82it/s]\n",
+      "Epoch 39 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 69.00it/s]\n",
+      "Epoch 39 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 68.52it/s]\n",
+      "Epoch 39 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 68.73it/s]\n",
+      "Epoch 39 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.09it/s]\n",
+      "Epoch 39 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 68.80it/s]\n",
+      "Epoch 39 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 69.24it/s]\n",
+      "Epoch 39 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 69.95it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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Mj4/bDEgACIfDGBkZwdjYGEZGRpDJZDA6OopYLIbq6mpEIhGUl5ejvLwciUQCwWDQxs9CoZDdnkwm0djYiHg8bjMkQ6GQtRCJgYEBAI57ktcjdGmCtuSMMZ670oMHDx4OAOxT4omIvGqM+TGAKIALASwC8Myf80HC4bCNlQWDQUQiESQSCYyMjCCbzSIejyMUCmFsbAyJRALhcNim7TNel047RmYymURZWRni8TgSiQTi8TgikYhNPolEIohEIlagxWIxawmOj48DgLUeKWSz2SwymQyi0SgCgcJh89yUHjx48HBgYloh57LgdsBxWX5KRIb+3A8yPj6OgYEB7NixA4FAAKFQCBUVFVYgjY2NIRwOIx6PIxqNIhwOIxqN2hjd4OAgAMDv99vYW0NDAyoqKhAIBBCNRhGJRGyCCF2S6XQaw8PD1g3p9/ut5UcL0u/32/NZhuDBgwcPHg58zJRdmQPwHIAfA0jBSTaxEJHPTXGevN4+laFQyAofZlPSugqFQkgkEqisrEQymUQsFgMAm/3IDMfy8vICtyWFIeA0etZWHYVlMBi0iSWBQMDemxYiE1+YhbkvVpvnrvTgwYOHAwMzuStvxoRgi7+eC8+0qrYbTPxwL4yqrxcOh205gBZIiUTCNm72+XwF3U5EBJFIxApLCsH6+nr4fL6CZBXG1nQLL1p2nvXmwYMHD28/TCvkROQmADDG1IhI13THFjn3dVlyFCx6aR5aUPlnsAkn3B+JRKyVFwgEUF5ebi21RCKBWCyGiooKW8zNeBrPCQaDBeUKupUXhRsAK1Cnem7Ci8158ODBw4GFmWJypwD4GoDRvOvybBH5w75c+PVacvpY3UKL1hUtsWAwiHg8bi0yujGbm5sxZ84cu3/evHm2eJstvaLRKMrKymyNm75HMQE1k/XGdl/uPpYePHjw4OHAwEzuyk8B+GsR2WSMORLAZwAcsy8Xfr2WHDMdmcrPmBozJRmzq66uRm1trf2fySAVFRWYM2cO+vv7UVlZiWg0iv7+fvj9fptJOTg4iO7ubgQCAcRiMZSXl9sEFHfGJH8DUWxVAl1Izto+z5rz4MGDhwMHMwm5MRHZBAAi8qgxpnw2HsIYg/r6etTU1CAUCtmkELocmWFZW1trLbjq6moMDw8jnU5jYGAAY2NjyGQyGB4eRl9fn23L5fP5bFkCrS4Wlsfjcdvcuby8vKCdmFtguWN2ImIF3NjYGHw+n/3fgwcPHjwcGJhJyNUZY/5hqv+nyq4ECt2VM2VaBoNB1NXVobGxEWVlZQiHwwgGg6iurrYtvAKBgG2MnMlkAAC9vb3YuXMnhoeHUVVVhWAwiJ6eHmsRssaNlhqLxBnLq6ioQE1NjS0I57NqN6WOEXJFg1wuh/HxcQwNDdmC9ZGREYyPjyOZTM4wpB48ePDg4a3CTELuywDKp/l/SrBlFjGdoBMRZDIZu2QNywICgYBdx01fh0vksPdkLpdDLBbD7t27rcXGTEy29WInlNraWsyZMwe1tbWorKyc9jeMjY2hq6vLtvaikGUCTCaTweDgIIwxiEQidp8HDx48eDgwMFN25SfeiocYHx+3FhhjbGx+PDY2ZltpDQ0NYWxsDOPj49ZKS6fTMMagtrYWPp8PyWQS9fX1aGhoQDweRzgcRkVFBRoaGuxHt+Zi4XexWNrg4CC2bduGPXv22OMymYxt7szleILBIEZGRtDX11dwbQ8ePHjwsH8xY1svY8xaAB8CsDi/aSOAfxeRX72eG03ntszlcujq6kJvb691TbJuzl0zp+voaCkyuSQQCKClpQXz5s1DOBxGZWUl6urqbBILALz22mt2jTgRQSwWs8vnsKtKWVkZRkdHsW3bNmzduhWZTAbZbBZ9fX12NfF0Oo2+vj709fUhlUphYGAAmUwGVVVVr2dYPHjw4MHDLGKmEoKTAfw7nKLwm+EstbMCwFeNMR8SkZ9NdW4xYTZTtiUtNCaMMPlDC0e6QSnsQqEQmpubsWTJEqxcuRJtbW0Ih8O2vEBEMDg4aJfM4YKrXV1dNgGFmZU8zxiDVCqFnp4epNNptLe3Y9u2bdi+fTs6OzvR19eHwcFBDA4OWuEdCoWssPbgwYMHDwcGZrLkrgVwhog8q7Y9Y4x5AsAXABQVchRM7rXgXg8oyNzf2cUkGAyipaUFDQ0NmDt3LpYtW4Z43GnKUl5ejr1796Krq8sukxOJRDA4OIhAIIBMJoNgMGhLE3i96upqxGIxDA4OorOzEx0dHdi2bRt+85vf4KWXXkIqlSr4fRTCukvK6ymb8ODBgwcPs4uZhFyDS8ABAETkOWNM/XQnavfiG2X8+jz9vaKiAkuWLMH8+fORTCYxf/58lJWVIZPJoL+/H+FwGLlcDgMDA9izZ491QwYCAdTW1toVvGnBMXOSnU127NiB9vZ2bNy4Eb/73e/w6KOPQkRsX02eo4UwY4henZwHDx48HDiYScgNvsF9Fm/WstHnh8NhzJs3D4cccghaWlpQXl6OZDJp15aLxWLIZDJ49dVXMTg4iD179qCvr8/2rGSpQENDA4aHhxEMBm3cLxQKoaamBr29vejr68Of/vQnPProo3j88cetO5LPowU4/3oWnAcPHjwceJhJyC0wxvykyHYDYP4sPE/hTfLCg67E+fPno7W1FYlEwnZIGR4eht/vx/bt29HV1YX+/n6bJNLd3Q0RsevK1dXV2e4oLDVgoXh1dTV27tyJnp4evPjii/jjH/+IJ554AkBhOUSRBVIL/nptvTx48ODhwMFMQu70afb960wXfyP9K/W5XNC0sbER8+fPR01NDerr6xEKhTA8PIze3l50dHSgo6MDnZ2dtsYulUohm80WZGCGQiE0NTUhm80iFAoVlBNQaOZyOfT29uKJJ57A448/jsHBQQSDQWSzWQCwyTAz/V4PHjx48HBgYKY6uV/zuzGmNr+tc18u/Odw4fn9ftTX12PRokUoKyvD+Pg4UqkUxsbG0NfXh46ODuzcuROpVAqjo6MYGRkpSHZhnAwARkZGsGvXLnR3d6Ovrw/HH3884vE45syZA8DputLe3o7Nmzfj6aefxt69e+H3+wsE3Ewxt6nq7Tx48ODBw/7BTCUEBsDHAFwBwJffNAbgCyJy80wX162yXo/AoxVHK2t4eNh2N9mzZw+GhobQ09OD3bt3I5vNFjRIZg9JCju6F5lkwlZc6XTaCrF4PI6BgQHs3LkTv/3tb/Hiiy/a/pXuNeYAFI3JvRmr1YMHDx48zA5mclduALAawDtFZCsAGGPmA7jTGLNBRG6f7uQ3k1XJjiapVAqRSASA04Gkv78f6XTaCitCW3C6gJzWHLfFYjGbfVleXm77UHZ1deHxxx/Hr3/9a4yOjk65WOpM1pwn5Dx48ODhwMFMQu5CACfoBVNF5FVjzAUAfgFgWiH3ZlyWxhiMjY2hu7vbdvcfGRmxPSvHxsYmFYq7sx1pvfE4tghjD8tAIICdO3ciEongiSeewM9+9jMMDg7C7/fvk9uR19UfbwVxDx48eDhwMJOQCxZbEVxEOo0xUzZp1AJCuyzV+TM+GJNG+vr60N/fb6+jC8P1dbXA09YcAOvC9Pl8qK+vR2VlJYLBILZt24ZQKITnn38eDz30ENrb2+25LDrXXVfcmZTu3+zF4zx48ODhwMJMQi77BvcVgMLn9Vp1PJ6CS1tKWqDoom5tSWmXZS6XQ0NDg01kCYfDCIfDeOWVV/CLX/wCW7duxcjIiBVw7ud3f58qHueVEHjw4MHDgYOZhNwyY0yqyHYDIDLdiVow6CV33ijc3U+KWU7uRBcKvbGxMSSTSSxatAj19fW2mfOuXbvw8MMPY+PGjRgaGkIgECiI7RWzGIv9Rm3peasQePDgwcOBg5lKCN60WaKtsTeDYtYUv7szOOnW9Pv9Nr7W1tZmVxTPZDLIZDL44x//iD/96U8203J8fHySa3KqZylm0XnxOA8ePHg4sDBrXHk6y+f1nu/+7hZCbgGn3ZbZbBYNDQ1oa2tDc3Mz6urqkMvl8Mwzz+Cpp57CyMjIpLjhvgrkfYnVefDgwYOH/YcZ15N7M3D3eZxJeMzkEpzp2GJWY1lZGZqampBIJFBTUwO/348tW7bg6aefRl9fX9FEFt22y5256b6X22XpWXMePHjwcOBgVi25fSmSns41WMxCKwa9z/23oqICZWVlqKmpQTQaxWuvvYYnnngCe/funbQQ61SuypkEtD7enbTiwYMHDx72H2bdXTmTC28qS0lfp1iCx3TXAib6THKF8Gg0ilQqhT/+8Y/Yvn07RkdHJ91bW3DT/Q53bRy3eYXgHjx48HBgYVbclW6XH7v4FxMC+xLHmimbsth1aN0Fg0FUVFRgz549eP755/Hyyy9jeHjYuhXdJQlT/eX36QSsz+fzSgg8ePDg4QDCrAg5Chgt1IoJoZncgjNlOAIoKPrWwpCZkslkEplMBrlcDq+99ppdmkc/50wCbipr0v3RXVY8ePDgwcP+x6xyZGOMrZHTAquYYJnpOsWEXzEhqTMlI5EIxsfH0dHRgd27d2NgYKDAqqSwmy5p5PVmT3qJJx48ePBw4GBW3ZX87s6w3BcLbartbmHphr7+8PAwtm/fjnQ6jf7+fruSgdv9WSy2NpPbshg8d6UHDx48HFiYVXclv+u/06X+vx4US/RwF2azwXM6nbaJJtO5IAm3NTZVoslUz+XBgwcPHg4MzHoAqZj1NpWAmikxZV9q5bjdGGPbdHG9OV0o7hZYOrZX7FrTCbqZsj49ePDgwcP+wawJuZkWGS2GYtunyqqc6d7ue05lSU4ltNx/pxK27uv9Ofp0evDgwYOHPw9mLSbnto6msuZmyrostuqAjqkV66iivxc7Vj9jsQzJmYTdVNsDgYCXXenBgwcPBxBmTchFIhGMjo7aVP6pkkR4PP9OJYh0E2a3ZbUvgs79fFoQF3M37otgc+/P5XIYGxt7o8PmwYMHDx7+zJiVfPdcLof+/n4MDAzYNdr8fr/tQgI4jZOz2SzGx8cRCoUQiUQQCoUQDAaRy+XsfhFBKBRCOBxGKBSC3+9HNpvF0NAQstksgsEgotEootEoIpEIIpGIXSsuEonY7Tw/FAoVjdMBU2dr6oxMoFDA+f1+BAIB+2x/CXE5Y8yvjDHDxph0/vOSa//fGWO2GWMGjTE/MsZUqX1Vxpgf5vdtM8b83Ru4f5sxRowxntn8Z4AxJmyMuTdPjwFjzDPGmJNcxxxnjNlkjMkYYx42xrS6zv+qMSZljNljjPmHN/gcYoxZ+GZ/j4fJeDNz9nXc4z5jzD//+Z76z4NZYRK5XC4FoBNAYnx83JfJZF5z3XMpgG0A+sbHx5vT6XQcwKb8/mYAcQCviEhwZGTk4JGRka0AUsXOHRgY0OfuK5oAhEdHR7e+wZ84E1pnPuRtjw+JyFfcG40xSwDcDeBkAE8BuAfAlwCcmz/ki3AW3K0HsBzAT40xz4rIC2/FQ3soigCAHQCOAbAdwN8C+I4x5h0i8poxpgbADwBcDOAhALcAeBDAqvz5NwE4CM573wDgYWPMiyLyf9/SX+FhJrzROfv2hu5O8uf+APhnAPe5tn0AwB/U/2UAhgAszv+/G8CJav8tAL69L+cWuf/1AHYBGADwEoDjALwbDpMdBZAG8Gz+2AoA9wJoz5/zzwD8+X3vBfB7AP8OoB+OUD1O3ee9AF7N32crgPNnc1z39wfArwBcPMW+TwH4pvp/QX68y/P0ygJYpPY/AODTU1zrCABPwFFw9gL4XH77dgCSp18awP/Kb/8/ADYC6AXwXwBa1bUEwIfzdOoCcBsAX37fQgC/ztO2C8CD+3uM9/cHwHMA1ue/v+E5W+S6RccawG/yNBrM0/Sc/PZTADwDoA/AHwAcpq71GoAbALyYp/nXAETy+2oA/Gf+vB4AvyW9/xI/b3TOFjnWALgdQEd+Xv4JjuHxATg8NZun30P545sAfB+O0bMVwIfVtW4C8D04CtMAHAG7TO2fxL/f0G+f5YEtJuTuAHCna9vzANYDqMy/6PVq35kA/jTTuUXufTAc7bQp/38bgAVqcP/DdfwP4WgzZQDqADwG4IP5fe8FMAZgA4AggHPyk7Qqf3wKwMH5YxsBLNnfL/Us0/VX+Ze2C47wP1bt+zGA613HpwEcDuCvAGRc+67hhChyn0cAXJj/HgewStFSAATUsacDeAXAIXAskxtRyJgFwMN5ms0FsBn5SQ/gWwD+CY77PgJg9f4e4/1M33oAw5gQYm94zha59pRjnb/OQvX/X8FhpkcC8AN4DxzBFs7vfy3/HC15uv4ewD/n9/0LgLvy8zUI4K8BmP09tvuRpm9ozha5zrsAPAkgCUfgHQKgMb/vPo5//n9f/tiPAQgBmA9HyXxXfv9NcATjmXkaXQNHEAYxDf9+vZ/90YMqDkdAaPTD0fTj6n/3vpnOdWMcQBjAocaYoIi8JiJbij2QMaYejovmKhEZFJEOONqKNtc7APybiIyKyINwNIuT8/tyAJYaY6Ii0i6l73q7Hs4L2wzHtfGQMWZBft9M9E1Nsa8YRgEsNMbUiEhaRP44zTNdCuBfRGSjiIzB0U6X69gRgFtFpEdEtgP4NwDnqfu0wplQwyLyu2nuU9IwxgQBfAPA10WEYYA3M2fdeD1j/QEAd4vIoyIyLiJfBzCCCTcpAPy7iOwQkR4An0QhTRvhWPOjIvJbyXPLv1C80Tnrxmh++2I4SsNGEWmf4p7vBFArIjeLSFZEXgXwZRTy1SdF5HsiMgrgc3AUn1V4Hfx7JuwPIZcGkHBtS8AxSdPqf/e+mc4tgIi8AuAqONpChzHm28aYpimeqRWO9tBujOkzxvTBserq1DG7XJNkG5yJOgjHsrs0f/5PjTGLp7hPSSDPdAZEZCTPeH4PR0kAZqbvPtEvj/cDWARgkzHmcWPMKdM8ViuAOxT9euBoms3qmB3q+zY4rhQAuC5/7GPGmBeMMf9nmvuULIwxPjju4yyAD6ldb2bOuvF6xroVwNWkaZ6uLZigGzA1TW+DY9n/whjzqjHmI9Pcp+TxJuas+zq/hBO2+SIcvnqPMcZ9LtEKoMlFv3+E4ykgLP1EJAdgJxy++nr497TYH0LuBQDL+I8xpgyOD/gFEemFExNbpo5flj9n2nOL3UhEvikiq+EMtgC4lbtch+6AoyHWiEgy/0mIyBJ1TLMpTJ2cCycWARH5LxE5AY7muAmOtvKXBIHDuIDJNJoPRyPbnP8EjDEHqXM1fQsvKvKyiJwHR9m4FcD38jQvppHvgONeTqpPVET+oI5pUd81/faIyCUi0gTggwC+9JeW5Zd/t++Fw4DW5zVr4s3M2QK8zrHeAeCTLprGRORb6pipaDogIleLyHwApwH4B2PMcTONw18Q9nXOTj5R5PMicjiAQ+Eoodeqa2rsALDVRb9yEflbdYylX17JmoMJGk7Fv18XZkXIGWMCxpgIHD+63xgTUeneP4Tj2lufP+ZjAJ5TrpH7AdxojKnMW0SXwPH17su5+hkONsb8jTEmDCe+MATHrQg4SQxt+UFF3tz+BYDPGmMSxhifMWaBMeYYdck6AB82xgSNMWfB8UX/zBhTb4w5PT/xR+BoRSXb9sQYkzTGvIs0NcacD2ANAGbSfQPAqcaYv86Pyc0AfpBnOoNwsvRuNsaUGWOOhhNLe2CKe11gjKnNa3h9+c05OLGFHBz3C3EXgBvymWIwxlTk6aRxbf69agFwJZyAN4wxZxlj5uSP6YUzoUqWhlPgTjjv9KkiMuTa92bmbAFmGOu9KKTplwFcaow50jgoM8acbIzRbrTLjTFz8inv/4QJmp5ijFmYF979cNxff2k0BfDm5myRa70zT48gnCShYUxNv8cADBhjrjfGRI0xfmPMUmPMO9Uxhxtj/ndePlwFh4f+cQb+/frwRgJ5M33gmJji+tyk9h8Px+IZghMQbVP7wgC+iomMun9wXXvKc13HHcZBhuO6+k9MBDGrAfwOziR7Kr+tAs5E3wlnUjwN4Nz8vveiMLtyM/LZZHCsN2aL9eWf6dDZGNcD4QOgFsDj+XHtA/BHACe4jvk7OBmQg3CC2lVqXxWAH+X3bQfwd9Pc6z/gxELTcLTNM9S+m+EIuz5MJKRcCCfbKwVHi/yqOl4wkV3ZDeCzmMie/QycLK40gC0APrC/x/ktpik15WFMZKymobKE38ycdd1ryrFG3uWfp+nZ+W3vzr9vffl930U+6w+F2ZV9AL4OIJbftyG/fzA/pz+6v8d5P9L3Tc1Z13HHwcm8TcNJYvkGgHh+30GYyIT9UX5bE5xkoz1w+O0fARyf33cTCrMrnwawIr9vSv79ej8mf0EP08AY8144mXir9/ezeHhjMMYIgIPE8fV7KAEYY16DMy//Z38/i4fXD2PMTXCyaS+Yzft4K3x68ODBg4eShSfkPHjw4MFDycJzV3rw4MGDh5KFZ8l58ODBg4eSxWwttSNmiuV19jdY6jbTs5kiy/bM9JtMfume8fHxLhGp/fM99f6Hm6b6O5crGh8f/7Pe071KhAbX7RMRu7KFXrBWL/HEVTCMMchms/Z49zlcSZ7buGpGPB5Hb29vSS0vkU/EsQgGgxgdHS1YVsq9AHAkEsHIyIhdVmqG6wNw6BMMBiEi8Pv9EBFEIhG7AgnnVTgcBgC7VJV+n/QqIOPj45aWgUDAriYyPj5e8P6Z/HJfADA0NGR/I88bHBwsKXoCgM/nEz1XYrGYXQWG9BgbG7N0EBHEYjEMDw/DGGPHMpfLFazjqcec19c0zeVyiEajGB0dxdjYmJ1z4XAYxhhLU5/PZ/eLOKu7TEVTv9+PsbEx++E7wvdkaGjIvks+nw+hUAgdHR1FaTorQo4DFYlEEAwGMTIyAhFBIBCwg8eXFoD9UZxk/KGBQMAOvt7OAR4bG7PMjgPl8/nsudw/NjaGYDBYwDQ58JpogDOhNEE56UXEvgxkCADsM3KCRSIR9Pf3b5uNcd2fiEajGBoags/nQ1lZGQYGnBKasrIyxONxhEKhgjHds2cPKisr0dvbCwCoqKhAf38/KisrMTY2Zs8vLy/HwMAAysrKMD4+juHhYUSjUQDOixyLxVBeXo7Ozk5Eo1EMDg6iuroa3d3dqKmpsS//2NgY+vr67BqG4XAYNTU1yGazGB4eRmVlJUZHR+0STLzn5s1OvWssFkMmkwEAJJNJBINBdHZ2Fkz4UgTnhGZEVNY0w+S4cv5wXsXjcQwNDdn33+/3Y3x83F5HC6ixsTErkDiunG/ZbNbyB30NwJnbgUCggDnz+pFIxDLbcDiMvr4++zso3EKhkJ2j5AWliHA4jOHhYYTDYUtTk18OjDTVizpns1krdMbGxuz5yWQSQ0NDGBsbQy6XQzAYtPwVgKWfFozj4+OWj5N2IyMjdqwDgYBVPAHnfeLyZKQprx+NRu3/iUQCnZ2d9l0YGBiAz+dDNBq1NKVMmAqzth5XIpHAyMiIlbj8kdlstmDBUgB2wCi9OZm4CCknA7VwHsMfyYmiBSM1GAojfW8txHK5nH02Hsf7U5jqCQzAvhjUYgDY/7PZ7GwN6X4FX/bR0dECAeXz+bB37157XDQatRNpeHgYiUQCqVTKjuHo6CjS6bQ9fmBgAKFQyCoRPI+MLJPJWMY3ODgIAOju7rbX6u/vRygUQkVFBYLBIILBoBVgmUwGxhgMDAxgYGAAwWAQDQ0NyGQyyGaz2LVrl30OTr5EImEnNwDU1tZaxllKiEQidh4BKGCEIyMjACYEnhZ6FG4UXCMjI5ap5XK5ScomBZ0WaoRWijiXOSe10hQIBBAIBArmGC2SsrIyyyMymUyBcktLnHMZcJTZUp2jtGq0wsJxGBoasnQk39U01bxwZGSkgO/q8RweHrZ8j9u1BU1+S9rzXSH/4HvA6/H/sbExq+jE43ErMAcHBxEKhez/4XDYCkYqL6FQyPKOYpg1IccJwBdeCxgABaYqBQ4HiwzObTZzEgET1iK1AO3a4Hm2GFC5rdzHULBSAyH0MwOwhNXX5qTUvzEUCs3WkO5XjI2Nob6+Hrt37wYAaw0BQDwex9jYmLV0uV1EkEo5/Zj5gg4ODtp3gIyQC+SSploBATBJSySMMaisrISIIJvNYmBgAMlkEslkEj09PYjH41ag+v1+xONx7Ngx0eowFApZhsfrDgwMWDdITU0NOjs7rYuklDA8PGyVOK1dAyhgemRUeo7yeM5fzgfShx9NT+3iJBPlfchQyfy4jZaAMQZDQ0OIRCIYHBwsYNRUQDSzBmCtNj4TPTAjIyP2d5YahoaGCtz4xhgMDw9brxoAy7NogQGwwgVAgcWtlYrR0dGCOUghxXlDa55zm8eSx74emvb29lrezWP5/vBZtQszm81axawYZs0PMzIyYjV0AJMEDIACgVUstqL/UqARWtho14o+hgPHyaav46riL5jseoJr/zGhz+E+bdGVIoLBILq6uuxk4csMAOl02r5kdPlVVFQUuCD6+/sLlAMKLo1cLodwOIxcLofy8onOTdTSjDGIxWKIxWJWyPb39yOVStnxpxbL47U7OZVKIRaLFeyn24PPT/oxvkDmWGrg76ZmzBXuddxEu+FJRzIsCo5iiibBOQTAKn9uRSYQCCAcDhd4a+ga5TU4xym0gAmPi7ZAeX1tMWo+wfeB73CpIRaLWcuGNA2FQggGgxgeHrY0o5XFsQyFQsjlcnY7vWO01oCJeUGvGS0p/q/fAyq0FIKkqbbqtAtbGz78X9NU5ToAmAhNaQ9gWVnZlOMya0KOD6VfaoIvrfbba7dIsXMAWM3ALQw1wQg9AfWk0vfT1ygm+HQQvpigo5air1eqQo5uhOHhYcRiMat9ESKCRCKBYDAIv9+P/v5+RKNRhMNhK5h0jIQIh8MIBoN2G4VNMBhEVVUVABQwsKGhIWQyGQwPD6OsrAy5XA6xWMz66kdHR612PzAwYCcW7xsIBKzQymaz1p1OlJWVIZlMFrwX02mJb1fo2LJ2cfFdpnuJsTBq9wAsAyXT0fOUgoTWL+cNtX/3fKMlr3kFAGthk/lSKdIMWM9T3oOuZu4jowcm3K/TubbeziAfzGazNnwDwLohaT1zjjKkQ8EUDAYLFByOM8cwGo1aQcQPXYmad5KmVBJpPWqvCfeT9qSd9r6RprQiqUgFg0H7fvE3k7cUw6y6K93BawoN7booJpzcLilC/3h9D+020RlA7kmgmSUnsw5uF3sOd9yNf7Vm8ZcAjkUoFLKKRigUstl2fr/fuiZramoAwE6CXC5n9wGwLgbAEWrhcLhAkNCa6+vrQ3l5uY3PcHIQqVTKMjAmxoRCIZuIQquS4DMmEgk7aQhaFYz76XejFDV/ziUyPC0UAOf3Z7NZiAji8bhNHnOHFgAUCCfuc1vUwERmn46V6evo8AaPZzxOWxUaTGAoNkd1jJ9MnvG+UgR/O2nq5rGMt+ZyOSQSiUkKv55bmpeSRu79AGwehDY+dGLKyMhIQcIhQzqkabH46MjIiE0o0vcnrRkXJF9geGEqzJolp90FbkEHFMbd3HEYHqOFkp58/MvvOtit71/sXvrZtNZAE5nfKRR1lpcOxHM79+ngdikil8uhu7sbkUgE6XTaMh337w6HwxgYGMDg4GCBsOFLyPgdAOti0BlftAT6+vpQUVFR4LKgACLi8bidJNTkBgcHkUqlEI1GC56rrKwM6XQakUgEqVQKZWVlCAQC1m0HOEw1Go2irKzMaqTNzc0laZ1T2ybjcyuG2vWUyWSsNcA5yrmgrTPOUT3unC/M3tPb3UpiNBq1DFJbAaSxnt+8r87M5DNoxZfWKN1lZLClCNKUVprbMwVMZKoODg4WWNc6g1UrDVQIGBsDJlzCzFYGJpQmnbQlIpampCN5KpVaTQsqt4yd6veJdGPmNBNk+AzT0XTWhJwOULsFDAWJ1h51TIwggfT5PFe7LLV1qI/jX239ceJqv692lWrhyfO1W1VP/mL3K1XoFx9w/P8UVoy/0kUyMjKCWCxWoEHTdZJOpzE0NIR4PG6FFssE+FJra2pwcBDd3d1FNT4mlaTTaYTDYZSXlyMQCCCZTGJ8fNzGIwAUWAe8diQSKXBXBoNBDA0N2fvzN5WixU6GomNVmhlyjgATc4ZjppknmZrOstOxTu3mp1JEK9o9Z6io6EQUPd/5P59J/+W7RiFJvkFXl+Y5pTpXI5FIAU8qRlMKLXoufD6fnasUdnQlBgIBO+8YD6cFznk0OjpqXcrFxpYKEi0+XQ9HmuqYnH5fSFMmplG5Gh0dtUlu+0LTWVNpyDCAQktK/yBgoq5G10voGBt/OAeHwlP/KB1Y5nfNkHkMMNn9qS0xfV33hNLX05mf2qTmi1OqaGpqstmVmUzG1pbF43EAEy7fRCKB7u5u1NbWFtQxlpeXY3h4GKOjo9a1GI1G0dnZaRkZxzmRSCCXy1lrj+OrQSFEGo6MjCCbzdo6m8HBQVRUVGBoaAh+v99uZ2xRx2b4W3RRa3d3N7q7u23dXqkhHA7b1HJaQ+76NAA27uL2XOiEAwomHevR88edMs74j4Z7Xuukl6mEKQBbx6UTmXQMisfSknCHSEoJbpq6aw5JR46/9mBpa11npwYCAZu5qenD/8lHaTFraNc0+aiOEdLa1sfTO0QLkNvpqqTyyvgqrzcVZpUjU3DxxdZJGhQqOmOG57i1NT1h9MTSySMUcNqyK2Yp8lm0tqBjhzxGC13CbRW6BWmpaoiA81tHRkasQEun07YuLZ1OF7iSGH/r7OwE4GiYkUgExhjLMIPBICKRCAKBAMrKyqzrgQkqvEYikbAvtkY0GrUxI55HrTOdTltGlkqlUF5ejr6+PhuHYO0NEYlEbPzOHcAuZaUll3M6VdDSDofDlrnpd5njOjw8bAWYjtloBVFnX2olUtduAYUdaYDCMIZbM9deIRZzM0Wd2ygIeQ9+1/VetCRKWci5aRqJRKx7UAuwYsoJeag7RMOkFF2TzHnHY4DJNNXetqn4LjARayNN6fbUyTM+n89ab9ls1tbc6UzSqTDrrRw4KLp2hlogMOF+1O5FDiYw2ZWphY6O92lhSuj4mjv5pJgAc19Dn6cFNo8HCjUV7YItRXCM0uk0otEo+vv7rRsil8tZ/zxTiGmFRaNR9PX1obe313YfYfCYFpcu6NVjmEqlJiUw0ToLh8MYHR1FeXn5pLhDJBKxsTXG6MbHx23Wp67Xc2fbJRIJxONx+P1+JJPJkqWpjnn5/X4MDAwUzFE9l8jsuJ1MVM8NYKI+jf+7Y/LFYvWavrT6io252xrRsXEtmN1zNBQK2cJhzWhLDfr3MabFRgyco9qyZaaldgO6i/spCElrjnkxmmqeqhNfiiX7uA0QJrAZM9FFhe+lVlp00pvOsJxujs5q4gklu7bS3PENPZg6k0abuNpCAyZeXi3BtbtL+/F1TI37eQ99Tz3ptIbqji3qZ9PPoq3NUkUmk7GlA7R4dGyOLx2zLmkdsbUXY2W9vb1IJpPo7e0tcFkx6JxIJAA4ySK05IwxKC8vt4KTQoj1cm4LLJVKFWRX6uwrWonxeNxaprp+Trczmorhvt1BpqeVFLqcinko9LwhzXTNGud2sXN1XFTHAnUIQbsRi2VRFgtBaMHK30TXsqabFrqlDAosFlxTWGl3r+aHuuMNrXVdjE/XsObZpJtWaBkLpKJPQcTMWAosN/2KZeGSTjqOSprqJBdNU7eb241ZrZNza4Lu0gBtzbmtO21RacJQsLkH021laQGrBZm2vLRVN9VzagvOHc9zT2wSphTBMYlGowUZV1qQMN7l9/sRi8UgIgVFmn19fUgmk1ZrjMVi1r0SjUYRiURsVmR5eTkGBwdtckkgELB1b/39/Uin00in0xgeHkZ5ebkVUtq/T7rG43H09/dbLZZCtL+/v4B2gCOIM5kMhoaGkMvlsGfPnoL3uFRAetLlDEx0u9DQCiKP0ddgbETHqLWCqec2GTCvo11XzKgEJhTWqaCTwPgbgInsQmDCumCGr7YsS3mO0qPCOapdfwRpo5Ubglmw5Hukha6ZpLFAQarbwJHfMq5N4aaTwIqNv5uXsrkzC8n5+wDYuDlp6XavuzErAQcRsT9Ouxq1cNEWEgec33XSCSeK24rjfXTCCTUX9199XjFrjeA5OgOI19eCTscT9W8pdXelu+4McKwtlguwnRdBrR1waudyuRx6enrsflqBxhjbVBZwtEq+5Ez37+vrQyQSwfDwMOLxuNUwdeNoAJMC37FYDOl0GslkEn6/H7W1tdYlxvIGukgA2NhdKpWyloGu8SsVsFaRDElbcjqORfh8PtsbUURsjRIte8ZYmZmn54V2k3F+6VZh2rXF5IXpmBZ5iJtR09rUc55WDWN5xphpC4ffzohGo9blTOFAJYbfdYyLnYPIt5g5m8lkLD3Z45Q0JX1Jo5GRERun5VjrWCCAgtgaMLlhBnkp3xEKT747dFvyPB2qoNAtxpuIWYuq84dpLZDQcTq+pDpDhy+tFn7a0qNl5nZjElqwurU+oNC1qLODtEBzC9aphKG26IDSTlTQnfqZ/aiLurmiAP8yUSWZTKKrqwuVlZUAgMrKSvh8PnR0dKCxsRGAM6Y9PT22UFvTVAe2gYnMXV1DRUtO00oXmWcyGVRUVFjFpaysDP39/QCc94XHxuNxywD4W0uxdyUwkXEIwCadaIuHAo8lHslkEtFotCCDkklBfr/fJiOl02nbTYaaPoWaVkh1HE67qdzPWExx1JmAWiBrhVoLNp1NWKrZsoDzuxlv5soeOreAyuTcuXMRj8cRiUQQj8ft+FB4xGIxhEIhG38fHBy0851xeab2uwUo4IQHRkdHbT0eBaVu8cX3gbQjvbTiQz4LTGTZMr5KK127qYth1jgyJbHb0uFLqC0mncaqLTN3Qgf36ywed9DTHfPTMb5iZQVuv64Wmu6JqTVGrX3y2UrZksvlcjZBo6ysrCD7kdlXqVTKLrtTWVlZEBdh3VRFRQV6e3vR3NxskzqCwSA6OjpsoghXryBoIdJ60DE+tvAizfiyZzIZW0A6ODho4wbt7e0AnBUUaBlSoLFgHJgQrBUVFZOK0EsBbJFFRZKBf93tnwkAFRUVWLp0KebMmWPTyXVR7uDgIJLJpG0SMDIygp07d9p3pre3F319fXZFCc5J1l2RcVHRYBkI+53qtHOdtcnt5CWck7QGdWcdxoZ0jkCpQXd3IV2YXEKaDg8Po76+HgcddBDq6+uttUb+SZoODQ2hurra0iyXy6Gjo8O6QRkuGBgYsPxbxGntRzqxiHt4eNheZ+/evUilUujs7ER3d7c1EHQMkK5rWqGseaWFSC+hrrWbju/OmpCbKttQa1y0sLS1pl/gYr597aLUbhUtwNyJIu7kkGKCTQtRoLC0QCezABNxOj1hZwp+lgroKiRyuRyGhoasUOLLX1lZCb/fb1cHqKiowMDAAOrq6qzVRbrr3nc9PT02nlfMrUSXGTX0RCJhY3zARDISLQm+A9lsFqlUChUVFchkMnbpHbpj4vE4RMS6P7X7rBRjclpwaGWN23VmXF9fnx2jQCCAdDqNeDyOcDiMuro6qwzW1dVZAdPS0gIRJ3OWxbvd3d0YGBiwAoiWNS1lMi8uodTZ2WmTijKZTEF3fHf2Necr+QEZppu30A1eiqDiot19wESsTmei9vf3o76+HmVlZQiFQraFnt/vR1VVlXUFRiIR2wiCLn8KJJ/Ph/7+fltaEgqF7PJbFIa6aHxwcBA1NTXIZDLo6enB9u3b0d7ebhVLvnehUKigTk97/TRNebzO5C4GMxuWh8/nE7o6dIIHoa0gnbGo3YDFXIpaiyOj1ZmZvJY7E5O/kffVz6Pjaho6hqctUB1gd5/D7KZsNvukiKx8k8N4QMHv98t0qdeMzWlEIhHEYjHrhmSXdI7h+Pg4Ojs7EQqFbJak23/Pd8G9jWPPrElacGNjY3Y9ueksME7oXC6HwcFBuy6Z27dfV1fHxVNLijOGQiFxZxnruaI9H36/H/X19Zg3bx4qKyvR1dWFZDKJyspK25SbNY8jIyNIJpO2JRvjNkxlp/t4eHjYuruosGazWXsdwJlrAwMD2LlzJ/bs2YPOzs6CEhM9Ryko3XkA/F/HhgGgs7OzpOgJAMlkUnQDDp1DoK3zYDCI+fPno7a2FjU1NXZh0mQyaZO4/H6/9YSwTIdeG3dmLq9NVyatMLo3SVPGf1OpFHp6epBKpbB9+3Zs2bIFO3bsKAhvuWmqjQ79vobDYTQ2NiIej+Ppp59+61YGBwqTTNwxLz15gMIGrm6XIYACgTZd3ZwOSLstSS1AtfWlJ7N2SbqhJ5Y7pRZAQXC3FKHrVTiG2g9PgVJeXm4XrwwGg+jp6SnomECa62V7WMPGFQm0QON9qDCxBdH4+LhdL44uUMChj3Zj0jKjxcCYAAtKjXHaFbEeTyOZTKKjo6MkY3J8T90FvATnBLXq/v5+vPzyy9ajsXv3bsRiMSSTSeviKi8vR3l5uV1mpaKiwnaZiUQiCIfDyGQyqKqqKsgETKVSGBgYgDEGPT09NnvOGIOamhrMmzcPe/bswdatW63A0wyWMR7t9aElwqzAZDKJ1tZW62EoRXDu6GxDKhAafN8ZW+PYtbe3IxaL2Rgd5wazoOlGZsOGbDZrPTv19fUoLy+HMQbxeNyWG0UiEXR3d9tFjIPBIGpra1FfX4++vj7U1taitbUVzz//PLZt24Z0Om3nJxOctKJLt3Y0GkVNTQ3mzJlj15CcCrPqrtQCyy3cigkxPdm0C4ITURPMnfyhr6OTVLQ247bYtAWon89tsbiFYLH7azO6VMGx01YUBRI71Y+Pj9uFEBkPIc1yuRz6+/uRSCRs0gi7kQCwWY1MPmEQHZjQ1rU1wIbLTCDhcWzuTG2Tz6AnO7PC9MKpiUTCum3opquoqCjJpXa04kjQFQU4tNXtubRLmnMqGAzC5/OhrKzMurbKy8vxwgsvIJFIoLq6GoFAAA0NDSgvL7eClc0CyBT9fj8qKiqQzWZRVVWFPXv2FLilI5EI2trasHz5cmzduhUvvPACNm3ahM7OTnt+KBSySU5k1DU1NSgvL0dTUxMqKytRXl6OxsbGggzfUoLOSNR8ivyPnYUAJ0NRJ15RMEajUQQCAVsKFAqFLH1jsZgND1CoAbDekGg0ikQiYXl/eXk5xsbGUFNTY2PuPp/PWoPV1dVoaWlBT08Pamtr8corr+Dll19GV1eXjZHX19ejtrYWZWVlCIfDSCQSiEQiqK2ttUpUY2PjG2/rZYypmm6/iEz5tmghRuvHbTlpa0wLIu1311abu6hcuyd1Vpj7ObSF5nbDqN9SYPXpa+ln0PfXiRV83lLVEnW2E6FLBuhXL5YqrDu/j4+Po6+vz/rQmcBSXl5uW3C543FMeAkGg1Yg6aV1dAoxk1ko4HgurUZ3dxNad5WVlbbUQP+O/v7+krTk3NnDbo2f41Rs7TUdThgZGcHw8DDC4TDS6TT27NmDQCCAiooK+P1+1NTU4OWXX7bCrq6uzmbvUfCVlZWhtrbWup8AoL29HX19fairq7OusFwuh+rqaixatMi6MV955RXs3bsXiUQCbW1tmD9/PioqKlBTU4N4PI7q6mokEglbzhKPx7Ft27a3YIT3D7QXC5iIdwMT87VYs3MKnmw2i3Q6bWPjup8pXdANDQ3o7OxEMBhEXV0dqqqqbBYuk01yuZylXTQaxUEHHYTOzk4MDg6ivr4efr/fWoPhcBhVVVU47LDD0NHRgU2bNmHr1q0Ih8OYP38+Fi5ciHg8joqKCkQiESSTSZSVldmEGr2ySTHMZHp0AdgJgFfQPk8BMH+qE3WShp5M7poyHePSHQ+0cNLCxz0xtXACChstawHkFm7aynQLwGKxJ95bZ4Rq/7DbjVpqGB8fR1VVFTo7OxGLxTA8PGzHhAKBLkomfJCpBINB9Pb2IpPJoKamBl1dXTbzKxwO2+wuYOpFZ3V9FpNKuGwOMNEBpa+vz2ZLMtbnbsZM0JVVXV1trQmmu2ezWSQSCVv7U2qgxc3MRlrOwITCx1gKF7bk+JPGuVzOtljjXOaCloy9MAWdrsqenh4MDg6iubnZCjcA1o3JlPa2tjaMjIxg06ZNCAaDNk4kIujs7MScOXOwaNEiLF68GB0dHQgEAliyZAkWLVqEyspK23SAZUn8S0u/FEGXP916fHeplFOJYAkI51osFkM4HLZzury83NKXvE6XjqTTabviRyqVsnWW1dXV6OzstIsd0x3JudXc3IyRkRFs27YNoVAIFRUVVrnau3cv4vE4mpub0djYiHnz5mF4eBiLFy/G4sWLUVFRYXvP0sLXCS5UsothJiH3eQBrAfwewLcA/E72IVOFQkZbZ3rAdFBYH6+Fnjvr0X0cz9duSC0Y3d1V9IfQ2ZduS43X5/30MTqQrZ9zplTWtzO0WziTydh071AoZLMluboAMNFJQ0TQ29trEz26urrsNcfGxmw2FpkqY2ZMXAImklp0IgmtQ2bLiYjtfqIzI/nMXNWYCzIODw9bdysD6b29vdY9pmMOpVgMzviqMRPd+cfHx5FIJNDQ0GC1cb3sCoViJpNBa2urTUknw6G7KxqN2pjM2NgYIpEIKioqADgrWVRXVyOdTuPVV1/Frl27UFZWhpqaGoyNjdmYGbveHH300bYEAXDoXlVVZd2SPT092Lt3L3p6ejB//nybMUhFjPOTqyxEIhHs2LEDy5cv33+DP4sgTfXCog0NDTa1nzFMNlJgaGBoaAjJZNLGzyk82ECdK3foFT3YFL2urs6230ulUkilUrY9HxOR2FYskUhg2bJlVgGi+zIWi6GiosIqOI2NjdizZw+am5tRUVGByspKlJWV2Vgt5zwXYe3u7rYt+tyYVsiJyFXG4ezHArgQwBeMMb8AcKeIbJ3uXE4ct2DQBd06k0Zbee7yAV1TB0xOGNEZkO6YmbbUeC235ajdozoD030PHaTXgpvnM6uoFCEi6OrqgjHGxktY08TAtHYrMphNoTcwMGAnVSAQQE9Pj2VspD8TDhhkZjYm3StMNAFgrQseS6HIQDWtsuHhYevaZEsy7YrT7lVen640xhVLcWVwrZgBE4peVVUVDjnkEMRiMds9g4XBPp8P6XQagUAAoVAIyWTSlhUMDg6itrbWzhsyTs5d7WqioIzH47Z/aW9vr3WRRaNR1NfXo7KyEgsWLEB1dTXq6urQ29trE0r8fj8qKyttKQPnYE9Pj62zJBOkFUKBXarF4NooYK1cXV0dFixYgNraWpswwvgcE4ZSqZQViJWVldbtmMlk0NDQYMcbmCjzoGCia3p8fNxmKXd3d1sa7NmzB11dXQgGg6ipqbE0LS8vR3V1tbUEOccSiYRNZqLXgF4Z8lpaqLr8hY0mimHGTIm85fawMeZpAOcCuAXAywC+PN15oVDIMjhOIF06QOh4G7/zOAou/hgtpPTxOqWUA6EtOW0Z6mxPnqsTX4o9m44BupNT9O8p1Wa+ACwD7OnpKYiXMZNRv3Ach6GhIZvxVVFRYa2nYDCIpqYmdHd3o7KyEr29vbYDCQvCRSbaC7GvpY4BsuNKOp22AfV4PG6VEG19kSZ6fTHeV2dzUoCyz2UulytYwqeUwHFgEThjzOySwcLi2tpam6I9MDCAZDJp4y780BofGhpCY2OjVUAYt9E1VbQq+A41NTUhGAwiHo/bZAjOfSY2GGPs8kl8f/iMzLILBALo6OgoaDMFTHTSYdZnLBazmbilBp3aD8AKj+rq6oIsxZqaGmvxDgwMYN68eTaRiHVxmqZ1dXUYGRlBLpdDZ2endWOzyw2VQr5LlZWVNhFoaGgIfX19NuuTAhGAteTo+qSFyVhuLBbDrl27rHLFlRV8Ph8GBgZsSzK27mNP2knjMt2gGWPKAJwO4BwAtQB+AOBwEdk+04BrN5DOftSuQGBCQLkTNihQtLXFv+44nM4g0pYfoa1GLejc8T4+F4Uag7H6etp9qoVpqSacELmc03eSwopZWoyB0Y1AWjJmRquPmiItIwpNBrR1H0W6OrUSw9o30o7XYckCswEBFLg5GY/jvY0xdgUEpiPrfn5sYaSt8lKkLceCQpzKXnt7OyorK22LJ9ayZbNZm6pNVxfHjpYUEz3GxsYwNDRkmRaz4qqqqlBRUWHLEurr661VxfOpqbO2jlY3kxOY7MJno4DcuHGj7dDBrFvWabLAmNZLqYJ0ZKbz6OgoBgYG0N7ejpaWFvh8PutyHh8ft/VvdANyjBhb9fl8Nl2f1jrd2IAzv6iA0sCoqamxrk6fz4fm5mY794aHh9HX12dpyNIOWtk6BOLzOX0ym5qakE6nrQWqZQUNIMbopsJMllwHHKvt2/m/AmClMWYlAIjID6Y6UTMVd0zLbTlpC8rdAozCyG3x6XiZTgLRZQTubEf3MSQEk03IjEWkoIemLhNwW4rabVnK2ZVkQu4axkAgMCn5hGnl2oUUDodtq69sNov+/n7bZYSuTMARUMPDwzYVeXx83GZOsn6GcTfSmK4S/UxsHsz6Ld1Tk64RaoQAbJwOmLDcGZsrVjf5dgfppPuEGuMsKMvMNpYBsHyjvLwcu3fvRiqVQjKZtO7JPXv2YGRkxDI9avSc/6FQyK4Sr9cRBGAVFVp8ulM9XW4AbFyN5QGMCw8NDaGsrAzNzc12XjKWSgVKlx2Njo7a1m6lhmKNE7LZLPr6+qzSyPGmIKPnhKU9NTU1MMZg165dBZ4Xzg2GIYLBIKqqquD3+wtqTEkXurE5j8gnaQGSd+vOKqQv42xckYR8m/W0unSJc5Xu8mKYSch9F45gOzj/0RA4ll1R8MVyuxDd/2tryl5YWWpamPB8Znrp62hXohZCUwlFCjB3Qgxdme4EFwo7PrNOntHunlJ1V4qIbcDLF5oxLNK6oqIC/f39VuBQQwNgNcuxsTGrqUciEZuUohML6JosKysrWLeOwm5gYMCWDVBrpJDSTZnJ6IaGhmwLKWDCVef3+21Si86+pOVO91wpJp6432MAtmPJ3r17ISKoqKjA1q1bbUyOgov/MxWci21ytXZaauFwGPX19aipqcHu3bttX1NaWCJihRoTmNhJhS5I9hzl/OKcZS9U8gF246C7jbV4fAdHRkbQ39+PiooKbNmyZX8N+6xCZ6WTnyUSCaTTaTsn+b5rlyMVFL/fj4aGBit8OJ8o7JgcVl1dbZuu67KBcDiMXbt2WcFEQUWaUgixG4rOfeDxwIRXjYoP57Gev1SA+Yw9PT1oa2srOi4zJZ68940OOH2smulrK8fd81G7ATkAOo7GSUkBpBNV9PW0W1HH4kh87iN0RqS2Gjn4uh7PNTaTsi91zKcUwXoUChJqdMyGY3EptUbShs12BwYG7KTRS/PQ8tNWGzARI9PaOF3IjBHo/pfARGo8hRZjFEx0KC8vt4KV75QGl47h+9TX11eSlhxdeG5Gwz6AZH7j4+OWDhRedAHv3LnTznO9rlxtba0VZplMBl1dXTbRIBqNFmjctOwymQz6+/vR09NjMysrKiowd+5cVFZWYmhoyGboMVOSn+HhYfv+0JqhS50JYX19fTaOV6xEqBRAxYJel7KyMhvzpGU8ODhoFQsq/PR89PX1ob+/39KDc2tsbMy6llkOxDHnOxONRu07RL7MBgKsn9y1axcSiQTmzp1rS0/oOmVnIz4nMKGM+nw+qxTRKAoGgwUt4t6wu9IY8w/T7ReRz021T2dW6hiXOwamrTv9krqFizujMf98BdfT16CwK5ZUwvvpl10LLH2ehjte5z6ulAWcz+dDMpm0woVWmxYWdG1QeFGzLysrQ3V1Nbq7u62rUCsFTPSgtUAaGON0TaArRWdMEjqexmtSIDIphcf19vYWxHR12QHdmPr5AUewl2LiCceLbnlaPLW1tZg7d25BI+POzs6CfoTUuLWAIoMis6yqqkJ5eTmqqqpQVlaGxsZGW5jt8zkFxfF43MaNtEdFxOlmX1lZifHxcQwMDNhaPjI5xvvI+LhvaGjIppLTZcYG4YODg4jFYlO6td7uoLLCxYeZ2l9VVVVgRQcCAezZs8cKFtKUcTPASb7SLsVMJoPy8nLU19fba9XW1toMWxFBdXW1Ld0YGBgoCBmNj4+jrKwMFRUVGB0dRTqdtkoTMNF1RWe1k8dqS1LH48rLy62CVYxfEzNx5fI3OuBuFyEw4QaiANOrCOgfoFsOuWNebgFF05znaS1FM0t+tI9fPxuFqLb2KGxJLP0s+njtsizVmByZIa0xalFkIHQFUfCxezw7kHR3dwOAXQSVmqKOl2grjllYqVQKlZWVBZm1+pmY4cdYjBt0STLjj9YFkylCoZAVakyi0M2dh4eHS9IFTUHFd1YnorS2tlpXoTEG73jHOyydKEDa29utBh+NRjE8PIxczmmFpplpfX09mpqa7DI9IyMjaG5utjG60dFRew4LfslwR0dHrduMCtD4uLPsiqYJacSuG27FmVYes/w6Ojre+gF/C8CkGoYFWOs5PDyMqqoqmz0bDAaxfPlyqyAmk0kYY9De3m4TdhjvzOVy6O7utkX+Pp/PKiCk4djYGKqrq22XGyomtMjZqIFNuZn0wgQTTVN3AiAAK+DcrnVgwkh6w8XgIvKJNzrgrJ6n61EniOjsRJ3+Tyamv+uMGgqXYgKJWiD/1+5Euh+1C00fS+jEEj2gPH6qLEvC/X+pYffu3TatmxoftXFuTyQSBcKKvSApOFjETf/+8PCw7TACwDJOamjMvmLSiS5L0e3CjDG27Rf9+7qUgH0SyaxFxD4T06X5zpWqoqLBeam7DDH+AcA2W2afUe3Wr66uRmtrK0ZHR5FIJGzP0aamJog4y+v09fVhZGQELS0tqKurs+PP6zJORyueljoTkDQT00ru4OCgvQ4AO+/pumZWt1ZEmezE2q3Ozs63erjfEuhchUwmg6GhIRjjdDnhivcszs9kMnZMu7q6bKnI2NiYXY0gnU7bZtrpdBqpVArZbBb19fWoqqqydXKxWAxlZWWoqqoq6GZElzNpyXeLMVby2sHBQbvoMqFDVVM1vuc7nM1mp11xZEb/mjFmLYAPAVic37QRwL+LyK+mO4/amO6IrS2iYgkh7qxFHs+4D32xbistl8vZSarXnNKaATCxrI52lep78nrcBxQKN7eQdWdplrIlJyJoamrC0NBQQZ2RiFPPlkgk0N/fj1gsVtBHjgkcwIT7UmdWjo2N2UxKLrXDQHZ3dzdqa2vR398/KeGFkzmVSiEQCNjMK6Yiu7MteawxE6sUsFMLGSDjdbRydJC+1KDjN7oNWyqVwrZt2+z6X5y/7HpBjZyF3ZwXc+fORTKZRDabxYIFCzAwMICtW7cWKJ+9vb22ATPrnliaMD4+boUe6xOZocvYIeNHnOdMQ+dvYHq8TkLTK1lnMhls377dehVKDUzI8fv9GBwchIhg+/btEBEryDo6OmySDpfVCYVC2LNnT0FnE5+vsH6N9Y179uwpsLL7+/sRjUbR3t6O/v5+Sxe6JXfv3m0V07KyMhs+8Pv99t3SNGW8le8ZS0B08wKuhEKrcHBwsCDE4MZMMbmTAfw7gJvzHwNgBYCvGmM+JCI/m+pcCjjtSuSLp/2w+oXUAk8HxH0+n63VILNjUHx8fNx+n07A6EQUveK3zgLlM+g4nxZw+re4LdLpfMKlgGw2i/b2dogIkskkhoaGMDIyYoUJLSa9kjDgjBUzI5khF4lEbDNkpgNT62RshXRgRxSgMBA9NjaG0dFRqx0WKwUgxsbG7PNFo1FrXTL2Q88B406cdPxtpWqh022k5xRLBMgMuYIAANv0mMKMtYqjo6Po6elBZWUlhoeH8dRTT9lVn9naidY546Ck9eDgoB17JkzEYjHbj5LvCLtgUGAxu5LvirYW+N7wMzw8jHQ6jc2bN+PFF1/Ezp079+ewzxpExAp1dh3q7e3FwMAAYrEYtm7dimg0amOjxhj7PZlM2mWOWPs2Pj5esGwOVxpgb0u6hvW6gIyL6ngc26xx/ldXV9u2X0woYemBdlcyREI3rLbq+e52dHSgt7cXr732GlavXl10XGay5K4FcIaIPKu2PWOMeQLAFwBMKeRocVHQacZXLBZG6IxJAFaTY8fr2tpaDAwMoLOz01bcM7bCAKrOxHO7SouVG+jvBAmmXazFLE93hmWpghlW2WzW1r3pmJoGNUoqKBRAWikBYMsG2K08l8shk8lYTbu2thadnZ3WmmM8gIXGdKXR2mLWn34uBsKZUs7151KplC1GZ0nC0NCQ7eVHhca9vl2pgHEQY4ztJMFxY1/B9vZ2dHR02ISDTCZjGyVzXvJadDnR7SwitnM8mWtlZSVeffVVuyIAFUdjnPotjn1/f39B78z6+nqr4NKNxufX7jdmfrIkhJmEqVQKr7zyCp577jls3rwZu3fv3p9DP2vQgoHWGLMQGU8fGxtDR0eHzXJlDJ0eFCo8FFY8l/SuqqqyLmqWB/h8vkk05fEUiLS0ub2pqck+Nxs6UAgyiU2vFE9FiC290uk09u7di/b2dgwMDODFF1+cclxmEnINLgEHABCR54wx9VOdRI2CVhAHCZho9OsWIO54mDZP6VdftmwZVq9ejeeeew4PP/xwgaVHs5nuRGo02mJzC08+B//Xz6ETYXRqLI/TqbLa6ixV+HxO0S8wse4bV9Nmij+FDcsLGD/hwopkojqrUURw9NFHo729Hdu3b7eZWyKCXbt2oaGhwWaAdXd329RlLrbJd4apzFxFAJgIxFPbHx0dtenxtDrYb48MM5VK2TZBLJbVbcxKBdpqZsd6WkNUULPZLHp7e9Hf34/u7m4bL2XyAt24ZKqMjdDTwUzGpUuXYnx83Lb14tzi/GEWJF3X1dXVaGxsRE1NjY3Hkl9kMhnbKJgZnXSd7dy5E7t377YMd+/evejv70dvby+effZZtLe3Y8+ePSVJT8ChKQUDE0d0Wj6NDiajsFUaW3DRywLAjjsVBwC2fKC6uhrz589HNpvFwMAAamtrCwyJsbExlJWVWZqydKeurs6uMaj5rl4lnkYR+XhXVxd6e3vtXO7p6bE03b17t40Xbtq0acpxmUnITR3Nm36fDRTq1b61wNMWFIWR233JinmayGeccQZqa2tx0EEH4Ze//CXq6x05+9JLL6G2ttZOJHf8jIJOx9J0Iop2rfH++q8WaNqV6hbOZOSlCBGxneRZD0cBQW0QmEhIYb0Zx3ZoaAhVVVVW4NAi+/u//3usWLECo6OjuOyyy1BTU2N7WbK4s729vSAoTTcZraxYLIbBwUFrrZFB0+XIBs2M2dB1wmek24zJERR0wWAQfX19JRmTAyaKatn1hG2ydGslWrHsYqLj4rTkuJ11aTpmvmPHDnR1dWHp0qVobW21zIpKBbP0amtrUVNTg2Qyad8zreB2dnZaD4BePLevrw+ZTAapVApbt25FLuesNKEbP+/atQudnZ3YtWtXyfatJEgbjhXff/6l8OIcYcw8lUpZ6xiY8GrxOqR3f38/+vv7kc1m0dbWhqamJhs7jUajVlGprKxEVVWVzbrU8VvAkQvd3d2WP1BB5Xp2Q0NDyGQy2LVrl31W8p2BgQEMDAzY7jUbN24sWDjZDTNderQxpg/Ab4rtArBaRIq2fvb5fEKfMDC5958789EtXHTSBxs9U9sEYAXeunXr8MlPfhI9PT22S0YqlbKMlNq7W4BqC9JdSqA1TJ2JqTM29TZgQjiSAQwNDT0pIiunHNi3IQKBgOi4Ixskj4yM2O7mnDQcJ764evUAuqSY9s0xPP3009HT04NHH30Uo6OjaGtrQyKRwGuvvVbQcUSXLwATnVBocTFep2nqLlXI5XJ2oUe6PgHYuixqr/y9+fZeJeWLDgQCopO4tKbPOaBDB5w3ul6OCSIcb50azq4jfr8fVVVV+Ju/+RssW7bMMkK6J+vq6qxbU/e1LCsrQ09Pj11mh1YFV6fu7u7G0NAQurq68OqrryIej6O/vx8dHR3YvXu3jQl2dXWhr68P7e3tBRaciJQUPQEgGo0K3bykKXkgaeemKRUZKg50M5Mv0vJjLJarrdfU1OCwww5DW1ubjd+x92VNTY2tiWPGLBMDqZD09fVZrw5byDF7s6enx7q4+/v70dfXh97eXtuTlE0DXnzxRWzevFlnTBel6Uxmx+nT7PvX6U50CwZ3gZ/OcAQm97HkXzK0M844A8YY9PX1YWBgAMYYPPHEE/jiF7+Ir3zlK3ZFYjJbFo/yGRi0pDWZHxR7Lx3EJrQ1SPB36MxMapylHJOj644Tht3HKSBYy8K4FzAhkEhrKix0K59//vnWgvjxj39sx+/yyy/Hs88+ayfeCy+8AJ/Ph8bGRmux0UXGIlXG/bRmSI1Wxw0pcBmzYDyB2j9LINjfT3dmKSUwbgI47zSXxgIK4+Rc6gQoXJWD8R9aeBx3NkxmwkFDQwPWrFmDgw8+2K4MzszW2tpa69ZiRuDevXutq5FCiasNsMNGOp3G6OgoOjs7kclkMDIyYi21HTt2oKOjAz09PZZufEb+5lKMsQKFK7YzkahY2RRjWnqb21UdDodtbVwkErFF4JWVlaisrMTSpUvR2NhoLW92MWJxOMt7xsed1ShEBB0dHXb5JS6BxGxLdj/h6uEDAwPYs2ePdU329fWhs7MTe/futTkZTHZhHexUmKlO7tf8boypzW/bpyITtzaoY1z5601y9eWvP6m+DgC+853vQESwYMECvPrqq7j22mvxmc98Btdccw3GxsYwZ84c+P3+Sd0ZtODSFlyxzE6gcDUCdzmBZgJaWOqY43SW8dsZ2ioi82ASB4PCtKaNcYqKdcYla9gA2Al47733QkRsMsGtt96K6667DhdddBGSySR2795tJwGzvng+s+a4nAdLVujCZNICAFuk2tPTYwPfZNx6bTG9QCrdl7p7TilBK3hk+hTqVAhJQ7qwOJ7MhNQeF86nyspKG+dbvnw55s2bh8WLF+Oggw6yKwRwSSUWfg8NDdksOdKV0HF3xpbq6+uxdetWZDIZG5t5/PHHsWXLFuvycieY8VqlnCCmE/uYk6DdyoBT+J1Op1FdXQ3AES5svs26N6b6U1BxrbZgMIh58+ahqqoKNTU1aGhosHHtgYEB1NXVFcS3Gc9lxxRtHLA9IA2Pqqoq7Nq1C+l0Gt3d3ejt7cXGjRuxdetWu62np8fyGmAiKdGdb+HGTCUEBsDHAFwBwJffNAbgCyJy83TnaoZGgUYC6IxH/RLqli3aPXLBBRfg4osvhjEG69atw5YtW9DT04PR0VEceeSRyOVytk0NM8YYjOa1dA1dMQtNJ71MV46ghbE767IUmSEhIjbZhIJncHAQmUzGdrxgXQsDyADsxCFNWP9SU1ODD33oQ/blFBH853/+J3K5HOrr620Hle7ubttCiNo7053ZYQWA1ebcLnLG8np7e20mmF441RgzyVJhAJ6xxmIZpG938B1nzEsnCnFe9vf32wbJwES9oY6VlZeXF8TV2K6rvr7eLnzJBtx0V9FyfPnll22GLeO7ZIJMYGL2Jzt2sDFwV1cXxsfHsXXrVjzxxBN48cUXrZegmHeIFhwFXSlCGxW0jqmQctHaSCSCpqYmG3NljWlZWZkVdDU1NYhGo6ioqLCWOTDh9hdxVgRg4gq9ANlsFlu3brWrErCNGvmuzsAcHR21GdgVFRUYGBiwPL2zsxMvv/wynn76aezYsQPGTHQ00WVEfr/fJkxNZ53PFJP7BwAnAfiA5FcCN8bMB3AngP8rIrcXO8/v94t+SbW7UteWAYVJJ/zxPCYYDNpB4o985JFHkEgksGTJEoyNjeGZZ57Bv/zLvyCXy+HVV19FR0eHdWnRj5/L5QqKRMkAKWz1M+n97lght6nxsRqsDsgPDw+XXEyurKxMQqEQ+vr6bCIH3YS02mn5kO58IXVMTa++TeGirYpf/vKX2LZtG+6//36kUik899xzVgNkohFjB93d3daXz3KCTCZTwMQ4MSsqKqygTiQSdgIyPugGn4+JMGNjYyWl/kejUdGNDvR46Peax1AppSUfDofR3NyMlpYWBAIBNDc3o6qqCvPmzUNzc7PNtOzv70dlZaVt89XV1WWz6eiqJHMVkYK1zYAJxl1bW2sza/fu3YuRkRE8+uij+K//+i+8+uqrNht2Kmank2byYYySoicAVFRUCPleIBCw84w9SefNm4e6ujpbBkKrrby83LY644rsLLEJhUJoaGiwCWa0xGtra20iS19fn82OTCQStgsK+SEVD/5PnlxXV2fPYWLRs88+i9/97nfYuHEjXn311YJMecLtiWO44Y3G5C4EcIKIdHGDiLxqjLkAwC8AFBVyfCBtPrstHVpC2u3BScX99B1Tk+7t7bWm8wc+8AGMj4/jvvvuQyQSsemkuuhcN3TVGpwWbNTy6NbUliahBZx2eegSAlqdpWrN6TgNYyVco41jSJcEJwTBZBO6Rth9AgBuu+02S4vPfOYz+M1vfoMXX3wRg4ODeO2111BRUVGg7VPZMcZY1wsw0UaOE4DdSqjcsM4OcN5LNnfV7efI0IEJF2tvb29Jav602BgfYWIXGRGFAZOJWEdVW1uLlStX2gbMdXV1tr9oVVWV7Yyxe/duK8z27t1rs+nySqC9LouCa2trbVswnYXn9/tRUVGByspK7NmzB9u2bcPw8DCefPJJPP3003j55ZftCtjTxWV0klgpg3yIGbKMlYXDYVRXV1trjvFNzo/ly5dbNy/r1jQfZZLPwMCAXTYLgE30Y+kCC8nLy8uRTCZRXV1tlV6C9a6VlZXo6urC9u3bMTIygueffx6bNm3Cs88+iz179tiwhjaEgEL54nZJF8NMQi6oBRwhIp3GmKnXNnANun4w/XBAYdNm/hidxCHidLdet24dKisrceSRR+K3v/0tvvKVr9h6mVQqhUwmYxknY3L0/fI6umyAHx2oVb/PPqd2tXJfsZII9+QsNegCaboraQFxPTFqjf39/bZ1Fvezm4EusZg7dy4+9rGPwe/3Y82aNXj++efx2GOP2QQFroPl8/nQ0dFh08/T6TRExHYuSafTBWuHsR0RGTafXUSsgOazAQ6daWGyqJyu0Jqammn74r1doRc0ZvYbQe1ZJ6YsWLDApoTX1dVhzpw5tgaLpTNMRHnppZdsav/27dsBwLq3RkZGbIo4u+X39vbarLv58+ejrKzMrjkHAHPmzLGtorLZLF544QVs27YNW7dutc/ptsZpwbstOF2jVWrQZR7abSvidBTp7Oy0LRIBWKuL9ZCMr9MdnMlkEIlErEXOGsjOzk67MCqbONPaYmswetGGhobQ2Nho5yNXt2hoaLA1dNlsFq+88op1U7J1mFZaNA21Bce5PV2N8kxCbro1RqZdf0QHs4vVxHGfFhQUHtqnTvfXQw89hObmZlx00UW466678NGPftTWUTCbinEhAJMClNpVyntT0GkB6NYW9PnaitPBdv38paj1E9pq4iQaHBwsSMCh+yGVStl4GDseAChgpuw8v2rVKrz88ss2Xbi6uhq9vb3o7OxEIBCwrpTBwUH7XtFVaowp6H0JTGQLsh6O/+tsXwozul79fj+SySRyuVzB2nja01BK4DzT4QG3J4LjVVtbi+bmZjQ0NCAWi9neoJy7g4OD6OrqQiqVwubNm631Njg4aJMFAFivTHt7u3WXRSIR1NXVYc2aNbZVG1v4GWNsW6m+vj4MDQ3hqaeewp/+9Cc8/fTTaG9vL2j1pDV+XeKjk2u0p6fUQA8UFRhg4vcODAzYtnwsB9DLSzEDkmPDlTro8cjlcujp6bFNH7RSAwBdXV0Ih8M2a7ahoQHveMc77PMw49bv9yMWi2FkZMTWum3cuBFbtmzB448/jueffx7pdLqglrpY6Ze+tzsr3o2ZhNwyY0yxZZENgGkrZLXF4xYcZBw6JgAUT/6gtkgz+Gtf+xqeffZZHHTQQbjnnnusy7C3t7egf5q2DHlPd3kA4XZHurdrq4+/R1+bv4u1IKUIukEA2C4DwIRLmu5BWkDMWvT7/TYew3geO1cMDAwgGo1i69atAIAXXngBIyMjSCaTtgBYQ2vr7IfIdauAiQYEtBhFBD09PbZ9F61N0lUnR7FejitUE2yBVGrg3GOpjU6g4vjRDagTt7ikDuPkgUAAvb29GBwctK7d4eFhm+7Nhst0ZxFUQtkt/7XXXrMNHdgxv6amxnoJ2tvb8corr+CXv/wlNm/ejD179lhXG6GTyXQcR89Jd5Z3KYE00q5bCn1aa0NDQ6ipqUFnZ6dVWGjdMTEoFApZhZI0ZeF9d3e3TVCiUqLpSsV1wYIFKC8vxyGHHGL5RSwWQ11dXYH7c/v27fj973+PzZs3Y9OmTTZpRfNn8lpdH0u5oMNeU47LdIMmIm/qbdAPSiFBbYFaoLam3IkgnDDBYBC7d+8uSOfu6OhALBZDT0+PXbFaW1ZEMZ+tO5WY956upEC7LbXVyUlDwV2q7kpCJ4wAE4kkuvsJgIKeeToZgK4TANi7d6/drruXbNq0CXPmzLH7aBkSdEtqcI26srIyS4Ouri4kk0lrddAFwnZiTF8HYDPMent7bQE7BfN0E+jtCh0a0L8vHA7bVRmCwSCGh4fR19dnLTMyPB7j9/ttuIDbyfw0WNIDwGZOMn570EEHobGx0caL2Narq6sLY2Nj6OrqwlNPPYU//OEPeO2112ynDM3g3HEbelvYpJmhhFKPm2uacizotejv77flGj6fz4YdeC4w0dOUyoxenNYNFp4DsM0YqCiyBpLt36qqqlBbW4vu7m6MjTkL627cuBGPPfYYXn75Zbz66qvW9QlgkqeM25gly45GDEnpMgk3ZtXscFtROhVZ/wCdoMLB5AuqEzyMMbY2amBgwG7nKrZjY2MFApTX1AkHbtelruNzdzrRFqgWem4LUaeelzrctKJFV1lZaXtDsrSAsQEyPFp5xdy6NTU1aG9vRzweRzgcxs6dO+212GYrk8lYy5BjzngcBRnr4TiBuSAnJwSfn11NWLTM5szABEMeGRmxSTOlBgoIvtu03NiJRrcyy2QyePXVV+24DwwMWOVTMyYNd1ayjqVwqZ5gMIhDDjkEK1aswPLly5FMJpFKpRAOh/Haa69heHgYe/fuxcMPP2yz7cgT3B4XzYi1RUpo3lOK7mdggk9pQ4JWk4gUeCi4Ojcw4d4n3dPptB1DDbfnjYKGLkyuZvCOd7wDy5Ytw9KlS5FIJGxYgMlI3d3d+N3vfodNmzbh+eefR2dnp3VB6vARDRftRdNxYvJs3V2rGGaNK7sZmY5l6SxF/cBuQcIfSvcJM7LolqQ2SGJqi1C7IHWmljZtdWBWP7d+PgrhYtqftt6oKZZqTI4vEbV7/VuZPEDXFwDbMYSWXTQaRSaTKWjxpdttdXd3wxhj/f6JRKKg0wiX4mB2Jt8VCiFOYN1XkwgEArbGb3Bw0HZX0PEG+vgpiHlNdxuxUgHniH5v+ZdjQWWRcTcdW6USqhUHd+yd9+HxuiQnFovhHe94Bw455BA0NDRYJaW5uRk9PT0YGhrCs88+i1//+tfYuHHjpNIQfS137J3QLco478lHShFMANK8imPipil7uOqkHbZUY2OFqUI0/J+F2BxXxuEOOugg1NfX21h3Q0MDurq6bFLSI488YjMotaBlEgljxQAmJQrxN1LZoZt1OsVl1i05nVgCFFpTU9WraUGlY3SU2PxRtLqYVeS2snSwklK/mDuT2omeoNq/r5MPigkyrUGVqitEd7Bxuyx1zRytod7e3gLXLV1YnFgiTvpyVVUVenp67MRi30O6J7n4It+DVCple+tls1mb4KIFYmVlJXp7ewvq+ICJZChO8JnadenVk0sNFHDabUtPBJNvaHEx+cudxabnKOeAZpA6AUTP16qqKrzzne/E/Pnzbf/Kmpoa9Pf341e/+hWqq6vx1FNP4YknnrDFwCITq0xoZZbQdHILQ/289PaUIijgOFYsg+HYkM6kKY0GWlEiYt2Nupcp3Z00OvieUFlIJBKYN28eli5diubmZls+kEwmMTw8jN///veoqanBCy+8gGeeeQabNm1COp0uyGbWPJvQ2fGEm+5UZPaLJUdBpF2DbmvHbX5qIeQuPdBmK3+QDpjzetpHz7/F3Bh8Lp1sUiyI6c7Y0pahNq2pAZcyAoEAWBBORKNRm6oPwBZbA7BuZWppXHLHrZlRaAETgoU0yGQydukOrmfG7CueMzAwYC1EJkLoco7h4WGrpRJ8h5hdqX8jrbyBgYGCriqlBAqyQCBgXY98lzmnOBbUlmkNcOw13XVMh2PPBDCt7AaDQbS0tGDu3LkIhUJobm626e0dHR3Yu3cvfvOb32Dbtm3Ys2dPQe0iaVZMSOkwRzGtXls0pRhjBZz3nKt+U1hpxdsYU2AoUChqmrIHreaFNDB0iIfKTTgcxty5czFv3jw0NjYiGo2iubnZrl2XSqXQ39+Pp59+Glu2bMHGjRttHZ/Oc6BF6Pb+AZPXdNTyhO/bdCuFzBq1+cAcYN1FRAsSPUl02i+3aWtOu1WAwhgYr8cJRk2V+6YSTLynOxlGX5Pn6efiXz3gel+pQURsl37Gu7iOXCqVwsDAgM1upIXEZBQyJVpkujVYLpezMQAAtnlzLjfRR9Hv99vGrqQJG8dyQd10Oo1EImFrJMfHx63VRzcI05f5e/RfgucDsO2MSnX9MS14gImMNTIh7danVk/GSSHGucZ2evp4MlVacn6/H7W1tXYJJR1n6ezsxFNPPYXf//73eO6557Bnzx6rmEyV/QxMXrV9KiuNz8Pi91IEeR6tNqBwyTPSlONAurD+dDqaMj7m9/sL+pvOnTsXLS0tdmFbxnZFnLXgXnjhBTzyyCN45JFH8MQTT2B8fNx6BWg5aj5OhUjDrbTouavjvFNhVkwPLYy08NAuEkILO+0S1BaTDjK6fySvrwPSo6OjBRoLC0a1cAMmhCSfU1t5bstSC0k+k/ZVAyhgGKUGphUHg0FrOfX399tEEU6a0dFR2xCZiyoSIyMjNr5FzUuvGq7dYYyfkekCKHBL0n1CS5BrwnEJHcbu6PMfGhqyblZeR2eH8Tdms1nb9xRwElt0FlqpQM8DdqLJZrOTGB6ZIJNxmHXHOa3noHZL6muQcfn9fjQ2NtpV5RctWmSTWp555hls3LjRWuFMhqDCQqvS7aKkB2Wm/qL8rVS0ShGkEddRpHuXc43zZXx83Jb1iIiNUTP+pWnK491Z5j6fD01NTbZxAxuoz58/H93d3di+fTs2b96Ml156CTt27LAeAb5jtA6Zvam9bDouqA0U/gYdfgIm4nRT4S3xr7lfeh07c08EPjR/nNsF6U4McVtfHBhOFO3D1ya4dnPy2XQiCQfQnQzD7zooy21uc7uUYIwpEAp8qUSkoO8h4Ew2ui059rT0uFIBux1wvOmK5AvOglO6UwBYhstWP5yEXA3B7/dby254eNj20NNJJ8CEYNVJJezIwEkNOFZlqcbk2BGI46jnIhmjft+5UC3HieOr6aPfD80YKQArKytRXV2NWCyGtrY2hEIhvPTSS3j44YexZcsWay3QYtTXoBKrFWe3G1PH1YHJ8XP3nC81uGlKnkSa6npP8kbG57Tb2u/3W8tId07RuQsVFRWYM2cO6urqbPuulpYWGGOwa9cu/Pa3v8XmzZttaYkxxgo3TVM+Iz0o5CG0tt2Z8jpvg/tn4ruzptKQeblTPvVHuxPdll8xgagtJ/1db+M9ObC6aFA/g9s0L+YGcbtA+awUglrAAZhRm3w7g0tnsDUP/fccA9ZHVVVVWWuOsbOBgQHEYjGEQiHb75KaI1PWASf+RiHHe+rMRq54AEx0seD/LCLt7Oy0z6afT09awHFF6veNZQic0Gx5pBNsSglcZ4+xN5/PZ+cKLQJq/ICjENB6poVFK1uvEK6TP3Rdqd/vRyKRsGUHFRUV2LlzJ373u9/ZhS9FJkoXyOSYQa1XQAAmXFg6HOKOv2vGp8MJpSroaJGRppr/UWng2nxMTmEZjW6KzTZ8mk8CsAqIMQb19fVIJpN2pQkmuWzZsgWPPPIInn/+eavMurM4WXZSjKbM1NTJMDpspUtF6E6dqT551oSc+6bahaljYdpFycGkAON2bWER+oXmIOnJxr5mWmgSWvBqaHclr6NjdjouqK9VLKur1KBdxOxCoYupqYlls1lkMhnbLaOvrw9+v992tgCcgvLKykr09fVNSvQhzcrKygrqeoLBIBYvXmyTXti1nueytRf/ckKz0wLfs0AgYDXKVCoFY4ztfE/odeVKFRRQdK+7XfNkQhxLvbq0dlUCEx1mdDNdPW9ZEtLc3AwRsU0cdu/ejaeffrrg3kwm45x1x7qLFXPrcINmmoSbf5RqnRwtIvJBd5IdaUoFhoqmrmHU16LFTppqD1gymURlZSUaGxvtedu2bcOWLVvwxBNPYGhoqICmwIRQ4jvH61JpchsqWqi6jSWGofg80xkYs+qcdmsClMbaN1ws1sbv7oEn+PLr63FCMn5An69eA0m7O/U99TNMdT9OkJkyu0pV0PEl44KXtJTj8XhBU9Z0Om1jcXRpajdHMpks6HQCFK7mzXgNzwOcBr3GGGzatMkmLgwODtrmsYFAAP39/bbLPelJK1BbY3RnB4NBlJeX23IFHXPQ7vXq6uqStNDpltLxamBijqplowq8FromjcoqLTxq4AQtOLqNfT4f5syZgyVLluCZZ57BV7/6VftuUIjquAwFk87sAwprXzUD5v11+AIo3sKvFMEm5boeDpigKeOtxWiqwy963T93rMvn8yEajaK8vNzOeS6J9thjj+E73/mOrY9jsThpyvib9hqQfnRd6m06+cWdo1EsTjcVZjUmRyvK7UpwaxhaSk+Vog8UWm9aCGrzXLtIqEVoq1Cfq2N7Otan7+VOOuH/bvenNqtLEW4mV1VVhVwuZ2ttdK0cAFRXVyMQCNiaNTKzUChkFRRaVLTwRkZGbOwsEolgbGwMyWQSO3fuBAC7raOjwx6nlwxhyQK3RSIRm3DChAkG5UdHR+05wIQ7k65uwBGI02VtvZ1BlxSZlLvEQvf5pMZPBqfjJWRYwIQA0XE5zn1jnM5Efr8fd955Jzo6Oqy7mdYHnwWYyLam1cHr6xAGgILEMj1/tTdG84xSVUKBCZrpelOtlA8NDdm2d5qmPAeYoCmFix5P8kMKy3A4jP7+foyMjOA73/kOOjs7bWydvN9NU3fhNmlMI4VKjS4x0DV7bkG4LzSdNY7MJRXcmrHbEipWPK0ltX6xtbmsY3SMz/Blp8bgbgrrthSp8bstOfegaYFXLOlkOiuvVBAMBtHa2lognDiZKKQ4hlxaQ0+SyspK687kit9+v9/W2XEFYsbleH5fX5/NbqTvf2hoyCaRUOMEJuomU6kUstmsfS69NhbfNwrrdDqNeDwOn89ZjZqMmdBLzpQSKNj0cjmacWhryl12oQWbtua0S4sKDeeWMU5y0f/8z/+gvb3dtmOjEKMyqhmg1vL1dfQc1comAJs+r+PsmmeUspALhUI2RqbzBtw0zeVyVrlz05TH0ppz05SKEVdh7+vrw8MPP4z29na7TYcLtEUOTKz+Qnq7rTy9TbuouTKFrvnjc7ktdzdmtU5O11nouJXbiqKUJrQprRml2+ojdGCSgm26IHQxy9B9PX0/LXT1oLoFuNuMLiWIOOs51dXV2d9KgQQ4MbFMJmNr54aGhqwFBjgdUBjk9vudZW3IZCk02c8QcJgws/Eo0KhBkrECE1me5eXlBYoHMzmLgfd2l5Dw3rwPrc5SRLF3WAsaCny6/gHYmBvjsjp5IBKJWPeknkuc49ls1jZ6pmKiY2k6w5NMltfhNbXipOM2ZH4649edtAYU8o9ShLZ43TSloCBN6aKkp4I01Qqmm6ZaCerr68Pu3buxZcsWu6q3O5amaUb+oTuskGa03jQNmcVLhYXvZTGazjRHZ43ifHn5IHzxtN+eWhx/tHZv6p5lOnCqB4sps9zHQdW+fXcgXPupdeE4t9GqACaYKYscud0dZyzWALjUQJpx/TiOxdDQECorK+3L2d/fj87OToyOjqK+vh7d3d02UzGRSNilOlKpFEScpXBY3xYKhdDQ0IBwOIyxsTF0dnbaDgqJRAJ9fX1WANG6YCE44xC6DIUumJqaGlRXVwNwrLpAIIBkMomqqipUVVVZi49/w+EwamtrC1qQlRq0K1GHDWgJARMZrKxPY4o3mR7jLrncRP0cM+c4LxkXJ1Nk5q2ubeO1eF3dmFczML6DVIz03KblyO1uQUuGWYq0JHTsWyv+dN1zrFgHypIcxs7IU0dGRmxMW0SsMqv5ZU9PDx599FE899xzGB8fR01NTdGekqQrhe1UxkAoFCooW9GWI7fTbQmggN7A9LHWWYnJiTjd6XWRnraKtKlKs5oxAbo+tPuBg0VzVhekcsVp/k+Jr91TDKLrgkdqGnpScOAZI9AvBV1t2l/M6wOFdR2lCL6oTCjRlnd/fz9CoZCNvwFOLRoLsTn22gLkMdzPTC6uPs1MPjJd3p+ZWixF4POUl5dbgdfY2GgTUpht2dXVZV2jgUAA3d3dSCaT6OnpQVNTE3bv3m1/E60YWqKlWAweCoUwMjJihRZT9QFYpVOncHPJGq1R61IfYybW+9IxdyqetKz1Pajg6ppWCiPOPTJiWil0szG7l9eiwkxLhTwCmPDYkO+Uavs9lmfoInrOuVQqVeAKNsYUvNdcOgmYECB0X9KtDEyMJXkgrUMtOPnuaI+ZDl+xWYO7HpXt9wgKa9KUQlfHB3nP6ZbaMbOh2fh8PtEd6bXJSgGjM6G09qgZG38EGVMu5xQ1UrDR5+t2SxX7TVpD4MuuB2aqcSjm8ix2LPeHw2EMDAw8KSIrX++4HciorKwUWkeMfVEx0VYtGQ01OAoOMjOmK3MCsdsG6a3fA621ac8AtctYLGYnMd8pWt+6DZFeHFW7yrWlT21WM16d0NLd3V1SfuhAICDMZKUAY5cJveAm6Uy3li7C1sdoS0+DglDHzsgA3RmAVFyAidgaGTfnLfcx5kMGTEFJ2ur0eO4HoBXWkqInAASDQSkrKytI5gBgY9ja0xEOh+248v1304PGhXZ5crs7CYhCiAJSu575zjBpJRgM2nif7kfKJu7RaLQgD4M0pQClYOO7xUbiQ0NDxWlKyfzn/ADoBPAEgN0AuvLf+XkNQFr9/xSAHIDn8/9nAWxW+3cD6NnHc92fnfnrjQMYBvBS/tq5/GccQCZ/7NP5587mP7vVdbbm79sBYAzAUP5aev9I/nojAFKzMa4HygfArwBcPMW+TwH4pvp/QX48ywGU5b8vUvsfAPDpKa51RH58UwD2Avhcfvt2AJKnSRrA/8pv/z8ANgLoBfBfAFrVtQTAhwG8mn8nbwPgy+9bCODXAPrz+x7c32O8vz8AngOwPv/9AwD+oPaV5efA4vz/uwGcqPbfAuDbU1y36FgD+E2eRoN5mp6T334KgGcA9AH4A4DD1LVeA3ADgBfzNP8agEh+Xw2A/8yf1wPgt6T3X+Lnjc7ZIscaALfneWEKwJ8ALM2/I6P589IAHsof3wTg+3B461YAH1bXugnA9wA8CGAADj9fpvZfD2BXft9LAI57Q799lgf2nwHc59p2B4A7XdueB7AeQGX+Ra9X+84E8KeZzi1y74MB7ADQlP+/DcACNbj/4Tr+hwDuzk/gOgCPAfhgft974Qi3DQCCAM7JT9Kq/PEpAAfnj20EsGR/v9SzTNdf5V/aLgC/B3Cs2vdjANe7jk8DOBzAXwHIuPZdwwlR5D6PALgw/z0OYJWipQAIqGNPB/AKgEPguOFvRCFjFgAP52k2F46yc3F+37cA/BOcGHUEwOr9Pcb7mb71cJRCCrE3PGeLXHvKsc5fZ6H6/6/gMNMjAfgBvAeOYAvn97+Wf46WPF1/D+Cf8/v+BcBd+fkaBPDXyHuu/hI/b3TOFrnOuwA8CSAJR+AdAqAxv+8+jn/+f1/+2I8BCAGYD0fJfFd+/01wBOOZeRpdA0cQBjEN/369n/2RahSHIyA0+uFo+nH1v3vfTOe6MQ4gDOBQY0xQRF4TkS3FHsgYUw/gbwFcJSKDItIBR1s5Vx3WAeDfRGRURB6Eo1mcnN+XA7DUGBMVkXYReaHYfUoI18N5YZsB3APgIWPMgvy+mejrbiUyFf0AZwIsNMbUiEhaRP44zTNdCuBfRGSjiIzB0U6XG2Na1TG3ikiPiGwH8G8AzlP3aYUzoYZF5HfT3KekYYwJAvgGgK+LyKb85jczZ914PWP9AQB3i8ijIjIuIl+H4ylZpY75dxHZISI9AD6JQpo2wrHmR0Xkt5Lnln+heKNz1o3R/PbFcJSGjSLSPsU93wmgVkRuFpGsiLwK4Mso5KtPisj3RGQUwOfgKD6r8Dr490zYH0IuDSDh2paAY5Km1f/ufTOdWwAReQXAVXC0hQ5jzLeNMU1TPFMrHO2h3RjTZ4zpg2PV1aljdrkmyTY4E3UQjmV3af78nxpjFk9xn5JAnukMiMhInvH8Ho6SAMxM332iXx7vB7AIwCZjzOPGmFOmeaxWAHco+vXA0TSb1TE71PdtcFwpAHBd/tjHjDEvGGP+zzT3KVkYY3xw3MdZAB9Su97MnHXj9Yx1K4CrSdM8XVswQTdgapreBsey/4Ux5lVjzEemuU/J403MWfd1fgng3wF8EQ5fvccY4z6XaAXQ5KLfP8LxFBCWfiKSgxNianqd/Hta7A8h9wKAZfzHGFMGxwf8goj0AmjX+/PfX5jp3GI3EpFvishqOIMtAG7lLtehO+BoiDUiksx/EiKyRB3TbArzXufCiUVARP5LRE6AozlugqOt/CVB4DAuYDKN5sPRyDbnPwFjzEHqXE3fwouKvCwi58FRNm4F8L08zYtp5DvguJeT6hMVkT+oY1rUd02/PSJyiYg0AfgggC8ZYxbu648vBeTf7XvhMKD1ec2aeDNztgCvc6x3APiki6YxEfmWOmYqmg6IyNUiMh/AaQD+wRhz3Ezj8BeEfZ2zk08U+byIHA7gUDhK6LXqmho7AGx10a9cRP5WHWPpl1ey5mCChlPx79eFWRFyxpiAMSYCx4/uN8ZEjDHM2/0hHNfe+vwxHwPwnHKN3A/gRmNMZd4iugSOr3dfztXPcLAx5m+MMWE48YUhOG5FwEliaMsPKvLm9i8AfNYYkzDG+IwxC4wxx6hL1gH4sDEmaIw5C44v+mfGmHpjzOn5iT8CRysqzWI5AMaYpDHmXaSpMeZ8AGsA/N/8Id8AcKox5q/zY3IzgB/kmc4ggB8AuNkYU2aMORpOLO2BKe51gTGmNq/h9eU35+DEFnJw3C/EXQBuMMYsyZ9bkaeTxrX596oFwJVwAt4wxpxljJmTP6YXzoQqWRpOgTvhvNOnioh7ldg3M2cLMMNY70UhTb8M4FJjzJHGQZkx5mRjjHajXW6MmWOMqYIT6yNNTzHGLMwL73447q+/NJoCeHNztsi13pmnRxBOktAwpqbfYwAGjDHXG2Oixhi/MWapMead6pjDjTH/Oy8froLDQ/84A/9+fXgjgbyZPnBMTHF9blL7j4dj8QzBCYi2qX1hAF/FREbdP7iuPeW5ruMO4yDDcV39JyaCmNUAfgdnkj2V31YBZ6LvhDMpngZwbn7fe+GY9/+e37cZ+WwyONYbs8X68s906GyM64HwAVAL4PH8uPYB+COAE1zH/B2cDMhBOEHtKrWvCsCP8vu2A/i7ae71H3BioWk42uYZat/NcIRdHyYSUi6Ek+2VgqNFflUdL5jIruwG8FkA/vy+z8DJ4koD2ALgA/t7nN9imlJTHsZExmoawPnqmDc8Z133mnKskXf552l6dn7bu/PvW19+33eRz/pDYXZlH4CvA4jl923I7x/Mz+mP7u9x3o/0fVNz1nXccXAyb9Nwkli+ASCe33cQJjJhf5Tf1gQn2WgPHH77RwDH5/fdhMLsyqcBrMjvm5J/v97PrNTJlRqMMe+Fk4m3en8/i4c3BmOMADhIHF+/hxKAMeY1OPPyf/b3s3h4/TDG3AQnm/aC2bxP6TZy8+DBgwcPf/HwhJwHDx48eChZeO5KDx48ePBQsvAsOQ8ePHjwULLwhJwHDx48eChdzFLKakH5wCGHHCIAJBAISCgUklgs5i4vkL/6q78SABKPxyftc398Pp/93tDQIH6/XyorKwWAHHbYYZJMJguOX7hwobS1tYnf75dgMChVVVUSCATE7/dPunY4HBa/3y9NTU0CQMrLyycdE4lEZN68ebJo0SK7raKiQqLRqCxZskQAdO7vtOHZpunjjz9ux7+1tVVWrFgxaZx6e3sFgKxevXpGOup34rrrrpOKigo555xzBIBs375dTj/99ILzfvjDH8q9994ryWRSWlpa5IILLpDa2lpLWzf9k8mkfOITnxAAsnbt2knPsnjxYnnggQfkv//7v+22U045RZYtWyZ/+tOfZH+P/2zT81e/+pUAkPr6epk7d64sW7Zs0hht375dAMiqVatmpGc0GrXfr7rqKkkkErJu3ToBIBs3bpSTTz654Lxvfetb8sUvflEqKytlzpw5cu6550pNTY1UVVVJMBgsuM+CBQskmUzKP/3TPwkAWbNmjeSzZ+1n0aJF8pWvfEV+8pOf2G0nnXSSHHbYYfLoo4+WHD2L0fTf/u3fBIBUVVVJfX29LFy4cBLNvvOd7wgAWbp0aVGaah4ZiUTs9zPPPFPi8bgcc8wxAkAeeOCBgvfC7/fLxz/+cdmwYYMkk0lpbGyUE088UaqqqqSyslLC4XDBfebMmSOJREIuuugiASDLly+fxJ9bWlrkhhtukH/5l3+x24466ihZvHix3HPPPVPSdFYGmy/lypUrCx6yqqpKVq5cKRs2bJCLLrpIzj//fLnwwgsnHXvSSScJABkbG6PQsIyIL3ltba2dlBRwwWBQHnroIfH5fPa8E044wU60tWvXys9//nM555xzpKGhQaqqqgSANDU1yfr162Xt2rVSW1sr5513npx66qly5ZVXyvve9z5ZuHChpFKpgknG75dddlkB0/zyl78sAJ7Y3y/8n/vT3NwsAOTwww+fRNPDDz9crrrqKrngggvkvPPOk/PPP38STd/1rncJABkeHi5K0/nz50tNTU1Rmv74xz8uoOnxxx8vAOTDH/6wrF27Vh566CE5++yzJ9F03bp1cuyxx0pNTY2ce+65csopp8gVV1xhaUoh7KbppZdeKscee6z9/+67755yAr1dP42NjZaZaHpWVlbK8uXL5fLLL5dzzz1Xzj77bKts6GNJg66uLktDChcA0tbWZulZV1dn6RkKheTBBx8Uv99vz+P8ueyyy+SYY46R73//+7J+/Xqpr6+39GxsbJTTTjtN1qxZIzU1NXLWWWfJSSedJJdddplcdNFFsnDhQtm1a5d9jvnz59vv73//+2XNmjX2/zvuuKPk6CkiIE/UyjfgKOCLFy+W9evXy/HHHy/HHXecpZ+mHefrz3/+c2lra7Pb586da+cU6VhVVSUVFRUCOIbBLbfcIn6/3563cuVK8fl8sm7dOjn88MPl05/+tBx//PFSW1trr1FXVyfHHHOMHH744VJdXS3HH3+8HH300bJ+/Xo5+eSTpbW1VX76058WCDl+P+200wr4y4YNG6ak6awMdmtrqxx88MFWswsEAnLcccfJnXfeWTD48+fPtxrj0qVLrXDjNgpArRWuWLFCvva1r9n/3ZZWe3v7JCIDsC95bW2t/OlPf5Ljjz9errvuOonH43LjjTfKaaedJg888ECBJiIicuedd8oDDzxQcE1qmRdddJEcfPDB8tWvflUAaGuj5ITc3XffPYmma9eulS9+8YsF49zW1mbpt2TJEnn3u98tgGNhA7ACUNN0+fLl8pWvfGVKmu7YsaOoFkoLsa6uTp555hk5/vjj5ZprrpF4PC433HCDnHrqqXL//fdPoukXv/hF+frXv15wzXPOOUdqamrkwgsvtFYAJxOAKSfQ2/Vzxx13yMKFCwvoecwxx8jnPve5SfSklr948WKrNHIbBaCm57JlywreCzc9X3rppaL0PProoy09H3nkEVm7dq1ceeWVEo/H5dprr5WTTjpJ7rnnnkn0vP322+Wee+4puOb69eulurpazjvvPFm4cKF9HlqQ+3v8Z+Nz5ZVXSnNzs7Vq/X6/HH744XLllVcWjHNjY6Mdq7a2NissqBhQAGpra+HChbJhwwb7f1lZWcE1v/WtbxUIIf0uAJCamhr5yle+IitXrpSzzjpLysrK5IILLpCjjjpKPvKRj9jjA4GAPPHEE3LVVVfJRz7yEStgAUcZSiaTcuKJJ0pbW5tcc801Bbx9qnGZlcHmi8qH46Dx+6mnnmonjR5E/WMWLlwo5eXl0traKnPnzpX3v//9BYNHy0JrbHrytbW1FbjA1q1bJ1/+8pfl0ksvlc985jMCOJbAJZdcIgDkhz/8oT02EonIeeedV3DdhQsX2ntxUPkSHHHEEfLpT39aH19yQs5N0+OOO67g+ymnnCIA5OCDD56RpnPnzpWWlhZ53/veVzDGdBFrLZLCkts1Mz3jjDPkrrvukg9+8IN2/K+44gq5+OKLBYB8//vfL6DpueeeW3DdBQsWWJpSYJKmK1eulE996lP22P09/rNBT2r+pA+/H3vssVY50cqdnmtr1qyR+fPnSzwel5aWFpkzZ45VSjUzBSCtra0F2znv586dW0DPU089Ve644w55//vfLzfffLMAkA9+8IPynve8RwAUKKHRaFTOPPPMguvOnz/fvjtHHXVUAT0PP/xw664uRXqSptXV1fY3aq/LihUrrDtRCw7yUcBRNpubmyUajUp9fb3U1dXZ94AfvjMNDQ0F2znuDQ0NBW7N1atXy4YNG+TUU0+1vPb000+3Bs3HP/5xe2wsFiuQFYDjxuQzUlEmTQ899FD54Ac/OCNNZ2Wwk8mkNDQ0WBfVhg0bCpgfUKjdrVmzRg477LCCAae7aLoY3apVqyQUCsm3v/1tARw3F10kbW1t8sADD8i9994rK1asKJjQvPZZZ51lB/6kk06StrY2+5JUVVUVTPxVq1bJZZddJo2NjXby6hflhhtukNraWsYJSk7IrVu3ThoaGuTEE08UwHH/zkTTpUuXFtCU/nu3Fqg/Rx55pIRCIfnGN74hgCNYSdPW1lb5+te/Lvfcc48sX768gKa89plnnmkVone/+90z0vSDH/ygNDQ0FKXp9ddfL3V1dXLDDTdMOYHerp9TTz1VGhoarLJy+eWXT7Ku9Nw7+uijZcmSJVYRIQObiZ4rV66UUCgk9957r2WSpMfcuXPl7rvvli984QuybNkyS2d97dNPP90KuRNOOEHmzp1bQE/thjziiCPk/e9/v9TX109iwk1NTXL11VdLXV2dXH311SVHTxEBXbm0zNavXz/JutKK/7JlywrcytwGFFrm7s/BBx8swWBQbrjhBgEcFzddl3V1dXLttdfKhg0bZNGiRVJZWSk+n0+MMdbdvXr1aivkjjjiCGlsbLR5FBUVFQVu8SVLlshpp50m1dXVBc/JezEWf955501J01kZ7OrqavnQhz4kAKzV5n7pbrvttoIkkbPPPlsOPfRQWb16tQ0+AoXa48qVK+XKK6+Up556quBaF1xwgXUr8VNfX19gbt900032GoBjyh966KFTEnLp0qVy/PHHW6LrlyORSAjgaL8PPPCAHHbYYfLII49oa7PkhNxFF10kl112mQCwVpubprfeeqssXbrU0vSss86SxYsXy+rVqwu0fDdNr7jiCnnssccKrnX++efbd2cqmn7sYx8TYEJj3ReaHnfccVYjLEbTY489Vu6//3457LDD5Le//a21Nvf3+P+5P+edd5584AMfsMoAx1eP18033yxLliyxDGzdunVy8MEHy6pVqwo8HdryXrFihVx66aU2kYWfs88+2zI2zaQ0Pem2IpPTcbtin0MPPVSOPfZY670pRs81a9bIPffcI0uXLpX//u//tgJzf4//bHze9a53yRlnnCHARHKQtuwAyCWXXGItcI5PS0uLLFmyxLqiARQofYsWLZLTTz9dvvCFLxRca+3atdZi5qeyslJCoZD9n/OeHoFAIDDJsteftrY2Ofzww22MXAtbPvOKFSvkhhtukAULFsgXvvCFGUMKszLYfr9fbrrpJlm4cKHcf//9Ul5eLitXrpRkMimtra0FL66IyHnnnSdHHXWUrFq1apK5eumllxb87w6Ut7S02LjAokWL5PLLL5dzzjmnaAbd/Pnz5corr7Ra4gUXXCCf//znJwlIEhBwhHFLS0sB4QDH4uD3WCxmXSF5baPkhFxVVZV8/OMfl4ULF8p9991XQNO5c+dOoum5555raapdmwAsc52KpnPmzJGzzz7b0vSyyy6Ts88+e0qaXnHFFZam559/vtx+++2TBCQFGOAI42I0PeKIIwpoSldKTU3NlBPo7fqpqqqyjOKuu+6S8vJyWbFihVRUVEhLS0uBlS4icuaZZ8qRRx4pRxxxREFSDoBJbmcqEfw0NzfbzMqFCxfKxRdfLOvWrSuwwjSTu/TSSy3zPPvss+XWW2+dJCCBCWvv5ptvljlz5kyip05MiMVi1vIoRXqSphdddJHMmTNHrrvuOikrK5ODDz5Y4vG41NfXFwiXxx9/XI455hhZvHixLF68eNIc1NmvnGf6/9raWus9aW5ullNOOUXWrFlTNCu3qalJzjjjDKuMrF27Vi677LKiWbp8jksuuUTq6uom0VQrsbFYTN773vcK4AjzqcZlVgabD/Gv//qvAkCMMQUxNJrQyWRSQqGQJJNJue+++2TOnDkSDAZtluPNN99sNQFqKHR7ULLzRX7ggQekublZzjnnHLnxxhsnDV5nZ6cVbO5973vf+wqITC2Vk/WOO+6Qgw8+WI477jg57rjjrM/53HPPtQycAj0fJyg5IcexYTzT5/PNSNN77713Ek1vuukmSwMm6uhkAk3T+++/X5qbm+Wss86yDEp/2tvbC+jlpqmecIzHkaa33367LFq0SNauXStr1661NNUKEgX6+vXrp5xAb9cPx+WWW26x9NQx0Tlz5gjguI+CwaBUVFTInXfeKc3NzRIIBGT16tVSU1MjN9xwg1UyyRi1xl9WVmbn1t13322zXpk0oD+vvPKKFWzufRdccEFBmjvjcdz26U9/WhYuXCjHHHOMHHPMMdZCXL9+vRXKCxYskHvuuUdOP/30kqOnpinjVD6fz8bRm5qa7Pd4PC4+n09isZhcc801UlNTIz6fT5YuXSoVFRVy0UUX2TnAZKCrrrrKjn00GrWu7WuvvVaqq6tl9erVRefhgw8+aAWbe9+JJ55YIDx5DK24yy67TObMmSMrVqyQ5cuXW5quXbvWem9aWlrkxhtvlGOOOWZKms7KYHMw+dD6pQ+FQnLdddfJ3LlzrY/1Ix/5iNx9993S398vAGyKKT866eRb3/qW7Nq1SxobGwvqcvQEcFuD7s/ChQvlggsusBbDgw8+KOedd55NcOBz0/2xcuXKgoxOXkP///GPf1z+67/+ixlIJSfkmKHFsWENDml6zTXXFND0uuuukzvvvFN6enqs8HMLIX7/xje+Idu3b59EU11q4LYGi9H0/PPPt0Lxm9/8ppx77rlW8yOj0zTVGZ3FaPrRj35Ufv7zn8uVV1455QR6u37oeqY2fuuttxbQ88Mf/rC0tLRYd9dVV10l//Zv/yY7duywwk+PlXZHf/WrX5WNGzdKfX19Qf2atvbd1qD7M3/+fDn77LOtFXDvvffK+vXr7TVoxdGdtWLFikmZvroshHzmhz/8oVx22WUlR08Rwfr16wWYsIZIY8BxE5511llSX19vaXfWWWfJlVdeKT/4wQ8EmBxbZU4FALnxxhvlm9/85iTerJNY3Nag+9Pc3CzHHXec1NTUyOrVq+UjH/mIrF271l6DSikVzoMPPniSMkTli5/3vOc98q//+q/TKqKzMtgVFRWTXBh0V6xZs8YWcQKQ66+/XgDIfffdJyJSwNT4ksbjcVm+fLncdtttdmLW1dVZzfPiiy+W22+/XdatWydHHXXUpJgdicFkiEMPPdQS+sQTT7QTfcOGDdLW1ibHH3+8TZq48cYbJ8WeaM2ceeaZsnz58gL3TF7zKTkhd8opp0xJ09WrVxdYWtddd51ldpqma9eutZobacqxXLNmjdTV1dlYwPve9z757Gc/K6effrqsWrVqUswOcLS41atXT6LpCSecYF1hV111lbS2tspxxx1naXrDDTdMoimzM9evXz+JpkcdddSUE+jt+jnppJMmeTXo4j3qqKPk6quvttupxd95550F9FyzZo2Nx8XjcVm2bJm1DI8++mipra2143zhhRfKJz/5STn55JPliCOOmBSzIwM76qij5NBDD5XFixcXxL7pvrz88stl7ty5snbtWjn00EOlqalJrrnmmknxRIYPTjvtNDnssMMKlOBVq1aVHD1FBEcfffQkty6VgaVLlxZYWrS+r732Wnn00Uft9sMOO8yOZTgcloULF9rwAuPtFHQnnniiXHzxxXLkkUfK4sWL5fOf//wkmtbV1cnSpUulra1NWltbrSBdsWKFpcm6deukvr5eDj/8cJsIc95559kaSX6YNb169WpZuHBhgVJ62GGHTUnTWRnsWCwmy5cvl9tvv926HkTEMrhiXUT4Wbp0qZxzzjny3e9+1xKILo4tW7bIaaedZrW5o48+uqC7xYoVKySZTBakpVLDqKiosIFLt99YB85Zy3fqqafKSSedJBUVFXLttdcW3KPYc9fU1MhRRx0lX/rSl0pSyK1cuVKWL18un/3sZ+Wss86yNOXYTUfTJUuWyFlnnSUPPvigdX+Qpps3b5ZTTz11SpouX75cksmkfPSjH51E00QiYWnqjgNpmtKTcMopp8i73/1uSSQSBUx8Kg2UNP3CF74w5QR6u34OP/xwWbZsmXzqU5+yyoqm53RZzYsXL5Z169bJfffdZ+MqjY2Ncuqpp8qzzz4rJ510kk00WLVqVQE9DzvsMEkkElYRcm8nE3R34NDxpM9+9rMCOAkzJ5xwgiQSCfnwhz9s9xeLCwFO3GbVqlXy2c9+tuToKSJYsmSJLFy4UC699FKruP/2t7+1iuN0GZOtra2yZs0aueGGG6z3o7q6Wo4++mi5//775eijj7YhiUMPPbTAQp8/f76Ew+GiJTqxWMze1x3X04oJExWPPPJIWblypcRiMctngMleFn6SyaQsXbpUrrjiiilpOiuDHYlE5JhjjrF+c82AOHk4kJWVlbJgwQI70WjZ8cNsqAsuuKCgaHCqSXjEEUfYgtZoNGqFLAXmXXfdNYkhHnfccQU1N4sWLbLaC60Xna6uP7/85S/l6quvllAoJBdffHHJWnKHHnqorFmzRugSKUZTCirSlHFUrSQAsNmz559/fgGzm4qmK1eutFZ8JBKxtKLA/NKXvjSJpmvXrrXPSppSE2Sweiqa/vd//7ds2LBBQqGQvP/97y9JS45Zr4yLaqFCOjD5JJlMSltbm82qdRcX00I4++yzCwqGp6Ln8uXLrcUXDoftM1Bgfu5znytwVQOO90a3dlu4cKGlIxsMuFPM+fnJT34iH/rQhyQUCsl73vOekrXkFixYIMuXL7deDO2upZuersF4PC5NTU12DrnjoAz5HHfccQXCaypBOXfuXDuvjTHW8iafv+KKKybVvy5fvryg5d+cOXOsJUpXqTvMwc+tt94q69evl1AoJCeffPJbb8ktXLjQag988QKBQEG6KV/YqSQ0X1xgousEtRP++He9613S1dUlAOSaa64REZGqqiq57bbb5Oqrr5YLLrhAHnjgAfnXf/1X+f73vz9tern+nHzyyZOy82677TabvKJ93QcffLD1K1999dVk7CUn5B566KGiNNUZUhyzqWiq3SVkmDrDjjTdu3evAGA9k1RVVcmtt94qGzZskPPPP1++/vWvy6233irf+c53pk0x15+TTjrJ3lNPlD179hSl6bHHHitz586VDRs2lGSiwne/+13rSmTcLRAIFGSYkuG4NXB+tKbNY8k0Sc8TTjhBtm7dKoAjHDOZjFRWVsrNN98sl19+uZx11lly5513yic+8Qm57777inYrKvY58cQTJ7nmbr75ZtmyZYsAE64tvo+rV6+WOXPmyBVXXCEnn3xyydFTRPDJT37S0pKue7/fX6AwcL7qekf90QkizCDXClB5ebkcccQRNo531llnyS9+8QuJRqNy0UUXySmnnGJris877zy59tprC2plp/sceeSRkzIuL7nkEvnud79bwF8AR6guX75c6urq5Oyzz5bVq1dPSdNZGWxqcGeffbZtAOrWzNauXWv74vFldfe6/OQnPynGGNtaaPny5XLsscfKGWecIevWrZNrr71Wvvvd78p9990na9eulfe9731y7LHHyubNm2XlypU2YaWtrc0y3ttuu81aiwsWLJiUosrnpFuSZjQwEYMik3/44YftPvqP87GdkhNy1LjOPPNMW3zvVhqOPfZYOfPMM+Wss86ytVdumt5yyy1ijJHW1lZZunSpLFu2zGrppOmDDz4oX/va1wpoumnTJlm5cqW1rDVNP/3pT9sA9fz586ekKd2Sl19+ud1Ha5M0/Z//+Z9JNP3Upz415QR6u37ITM444wy57777BMAkhWH16tV2rrGGyu2u/+hHPyrGGGlpaZHFixfL0qVLZfXq1XLyySfL6aefLhs2bJBvfOMb8pWvfEXWrl0r73nPe+TYY4+Vp59+WlauXGm1/9bWVitMb7rpJut+bGtrm0RPPifdkrokhYyQzP6hhx6y+xhLuummm0qOniICjscxxxxjM8x1YgjHbPXq1bJ69Wo7N92KxXve8x4xxkhdXZ3MnTvXtl9cvXq1HH/88XLxxRfL5z73OduPkkLmW9/6lixbtsxm2dbU1Fg6XHjhhXauNTY2Tmq6TSuPc5rH8j3UgptxfGCiHvKSSy6ZkqazMthM79Q/ZOHChXL55ZeLMWZSqxgKPU6ku+66qyCR4fjjjxcRkc997nNy5plnyq9//Wu57bbb5Oc//7l87GMfExGRn/3sZ3LKKafIH/7wB1m5ciVjY/L000/Lxz72MdmwYYM8+eSTcuKJJ05yiepnJCM/9dRT5eKLL5bVq1cXdMMOBAIFv4va7NKlS637pBSFnIgUpelll10mxpiCTCxNU7o9vvSlLxWM+3HHHSciYjOjHn74YfnMZz4jP/vZz+SjH/2oiIj89Kc/lVNOOUV+//vfy8qVK2323JNPPikf/ehHZcOGDfL444/LCSecMMkl6qbpunXrhMkzRx999LQ01enpJVw8LAAKBMiCBQvkkksuEZ/PV1AYzM8xxxxjNf3bb7+9IK557LHHiojIJz/5STnjjDPk5z//uXzqU5+SH/3oR3LjjTeKiMiPf/xjOe200+RXv/qVHHnkkTZR4Q9/+IPccMMN8uEPf1h+85vf2J6VxehJQXjaaafJu9/9brnwwgtl1apV09KTDHPJkiXWQ3QAjP+f/fOHP/xhEk0ZKzXGFFjpgONWXLlypd1+9dVX2/fd5/PJEUccIY8++qhcfvnlctxxx8mXvvQlufbaa+Xuu++Wa665Rl555RX52te+JuvWrZNvf/vbsnr1arnlllskFArJN7/5Tbn00kvlggsukLvvvluWL19ujQT3h5be0UcfLUcccYS8613vkiVLlhTEcoPBYMH/2iVLeTLVuMzaenLLly/H6OgoAOA73/kOzjjjDIyPj+OQQw7Bpk2b8JOf/AS1tbW477770NDQgJdffhnLli3DZz/7WfzzP/8zDj30UADAl770Jdxxxx1obGzEhg0b0NbWhq1bt+Kxxx7DggUL0N/fj69//evw+/1obm7G//pf/wt//dd/jUgkAgAYHR1FdXU1br/9dhxzzDF45pln0NbWhpNPPhlr165FfX09wuEwFi9ejJ07dwIAvve976G1tRUbN27ERRddhJNPPtn+rrGxMRx55JEAgBUrViAQCODUU0/F888/j5/85Cf48Ic/PFtDut+xbNkyS9NvfetbOP3005HL5XDIIYfgpZdewo9+9CPU1dXhq1/9KhobG/Hyyy9j+fLluO222/CpT30KS5YsAQB88YtfxO23346mpiZcffXVlqaPP/445s+fj1Qqhfvuu8/SdNWqVVPS9G/+5m/w7LPPoq2tDSeddBKOPfZY1NXVTaLpD3/4Q7S2tuKll17ChRdeiJNOOsn+rrGxMRxxxBEAHJoGg0GccsopeP755/HQQw/hQx/60Fs5zG8ZDjvsMGSzWQDA1772NZx88snI5XJYvHgxtmzZgu985zuor6/H3XffjebmZmzduhXLly/Hpz/9adx+++2WnnfccQduu+02NDc34x//8R/R1taG7du346mnnkJbWxtSqRTuvfde+Hw+NDY24ogjjsBRRx2FaDSKUCiE8fFx1NbW4vOf/zxOPfVUbNq0CfPmzcO73vUurF69GjU1NQiFQli4cCF2794NAPjJT36ClpYWbN68Geeeey5OPPFE+7vGxsZw+OGHA3D4UDAYxEknnYQXXngBP/vZz/DBD37wLR7ptwY1NTVYuHChpekNN9yAVatWAQAWLFiAjo4O3HbbbWhpacHNN9+M+fPnY2BgAMuXL8dHPvIR/PSnP8WSJUtQXl6Om266Cddffz3OO+88/P3f/z3a2trQ3d2Nl19+GY2NjRgcHMRDDz0Ev9+P+vp6LFu2DEceeSTKy8vR0NCAcDiMxsZG/OQnP8HNN9+Mvr4+HHTQQVi1ahWWLl2K8vJy+Hw+zJkzB52dnQCA3//+96ivr8fOnTtx/PHHY+XKlQAAYwxGR0exePFiAMCiRYvg9/uxatUqbNmyBY888gjWrVs39cDMhkah3Vg0XRcuXChPPvmk3HDDDfLyyy8L4NRaPfvss/LSSy/JK6+8Iq+99pr85Cc/keuvv14eeOAB+cY3viHl5eUiInLTTTfJk08+aWvpPvGJT8jDDz8sGzZssO7OCy+80MZ9nnnmGbn77rslFovJLbfcIiIin/jEJ+Tggw8WEZGamhr55je/KVdccYUAjmuUGs2pp55a4BteuXKlddMwU48uHijN6dxzz6VrrOQsuWeffdb+Xo73ggUL5LHHHpMbbrhBXnrpJavhP/3007Jx40Z5+eWX5dVXX5Uf//jHcv3118v9998vDzzwgCQSCRER+fjHPy6PP/64XfLmpptukv/3//7flDR9+umn5a677pJ4PF5A08WLF4uISG1trXzjG9+w7shbbrnFumROOeWUgi41hx9+uHVf3nHHHQLAriahaXrOOefIoYce+v/b+/O4HPP+/x9/tFChfV+lUk2aCqmkQUOpUcjeUAlZxpAm62XXaJEUjX3X2xIiDJIlNHaGCtllKWu0UAk9fn80x2s6LTPX+3u7vH2ufvO83V43Oc/jPM/jeN2P47U810+uEv9b28mTJ8W1SrtwCwsLHjt2jBMmTGBubi6B2oQOp0+fZk5ODi9fvsyrV68yLS2NEyZM4Nq1a7l+/XopgwhnzJjB48ePiyD9adOmMSMjg2PHjqWvry8VFBREiS2gNuvG0qVLqaWlJXjOnDmTLVq0IEkaGBhwzZo1Irh56tSp4jn08fGRUYU7OTkJ9aWkzpK0OXV5SrF2X7r/P0dbtmyZuF7pXtfX1+eyZcs4ZMgQYUebPn06d+zYwb179zIzM5OHDx/m6tWrOW7cOC5atIhLliyhnZ0dq6urOW3aNO7YsUOEGURGRnLt2rUcOXIk/f39aWRkxNDQUIaGhlJPT4+ZmZlMTk5mixYtOGvWLBYWFnLy5Ml0cXEhSVpZWTEmJkZowAYOHCi0LVIognQN1tbW4j3JZl43bq5ucLiFhcUnmX6WzpYcFKRaQvhjaxwWFkZ7e3va2NjQwcGB7du3p7y8PNesWUNJnJycuHfvXqk+EPft28e0tDQRc7Vr1y76+flxwYIFwo2ZJIcPHy6SBoeGhpIkjxw5Ir73xo0bfPHihfiORo0aMS4ujsuXL2dwcDDd3NyEKkbaPvv7+wu7jIqKigh27t27N1u3bv2BvenmzZtS5vt6N8lJOv7u3buLgUZOTo5Dhw4VTB0dHdm+fXsqKCgIXhLTPXv2CKZ79+7ltm3bxDE7d+4UGegDAgLE/SAxtbW1/SjT69evs7i4WHxHkyZNGBcXx2XLln3AVDK0+/n5CdtMXaYBAQFs1arVB0yvXr3KLVu28Ev3/3+6SV6tfn5+YrKXk5PjoEGDaG9vL1I9SdlD/ihKSZJ0dnbmzp07Bc/du3dzy5YtXLVqFUlyx44d7N69u4hdXblyJauqqjh8+HCGh4ezRYsWHDJkCEny0KFD4nvz8/P5+PFjkuT27dupqanJmJgYLl68mAMHDqSLi4uwz0hOMz4+PjI8pQD2bt260dHR8QMb4u+//87169fXO54kIQXkS3FkdTcaUvqu1q1bs2PHjjQwMGB8fDzv37/P4uJienp6cu3atRw7diyfPXvG1NRUrl+/nsuWLWNhYSE3bNjAwMBAxsbGsn///kxKSuKVK1c4YsQIkSpx5MiRrKys5M6dOwXTEydOMC8vjyUlJVy3bh2tra05ffp0RkdHs1evXjIxjJLNzdXVVYQkKSkpiQB26breTwy/Zs2av7SzypH89Dbv/6P8EUMhI2pqaqiqqkKjRo0QEBCAnTt34vnz57C3t8fLly/h6+uLxYsXQ05ODjNmzICbmxvMzMxw+vRp2NjYQFFREX379kVwcDA6dOiAs2fPQldXFzdv3sSVK1fg4OAAQ0ND6Ojo4MiRI9DS0sKmTZswZMgQNGrUCLGxsZg3bx4sLS2hqKgIXV1dmJubY/DgwXBzc8OGDRugpKSEAwcOAAAMDQ3x4sULVFVVITExEaWlpTh58iT2798PNzc3kMTp06cB1KoJnj17hvj4eEycOBE1NTXnSTr/xzv2C8rfMe3Rowd27dolmFZUVMDb2xtLliyBnJwcpk+fDjc3N5iamuLs2bNo3rw5GjRogP79+yMoKAjt27fHuXPnoKOjg1u3biE/Px9ff/019PX1oauri6NHj0JLSwupqakYPHgwVFRUMHfuXMydOxeWlpZQUFAQTIcMGQJXV1ds3LgRDRs2xMGDBwEABgYGKCkpQVVVFebNm4eysjKcOnUKmZmZcHNzQ01NDc6cOQPgT6Zz587F5MmT8fbtW7n/2x7/vPIxnqqqqnj9+jUaNWoEf39/7Nu3D8+ePYODgwNevXqFTp06YdmyZZCTk8PUqVPRpk0bmJqa4vz582jevDkUFBQQGhqKwMBAeHh44Pfff4eOjg5u376Nq1evokWLFtDX14e2tjaOHz8OTU1NbNu2DcHBwWjUqBGSkpIwZ84cmJmZQVFREdra2jA1NcWPP/6I1q1bIzU1FYqKijh06BAAQE9PDyUlJaiurkZUVBRevnyJM2fOICsrC87OzqipqcHvv/8OANDW1kZxcTGioqIQFRWF169f1yuewMeZqqio4M2bN1BWVkbHjh1x+vRpPH36FE5OTqiqqoKLiwtmzpwJCwsLREZG4quvvoK+vj5u3rwJMzMzNGjQANHR0fD29kbLli1x7do1qKmpoaioCHfv3kWzZs2gqakJdXV15OXlQU1NDceOHYOvry+UlZWxZcsWjBo1Cjo6OpCXl0fjxo2hqamJ+fPno3nz5sjIyEBVVRV+++03AECTJk3w6tUrkMSQIUNQUVGB/Px8XLx4ETY2Nnj37h1u3rwJoPZ+LS8vx5gxY7BhwwY8e/bso0w/i01OX18fZmZmACD0qKampqiurkZJSQkyMjLw/Plz5OXlCR1927Zt4erqCn9/f5w5cwanT59GUVERFBUV8dNPPyEzMxMdOnTA7Nmz0axZMwQEBGDIkCHQ09PDpUuXoK6ujjlz5sDKygqdO3dGRUUFbt26BR8fH2zduhWPHj1CUFAQ2rZti5iYGPz8889YvHgxlixZgry8PCgoKGD27Nno378/hg0bhoSEBHTv3h0AsHPnTjx8+FDYkE6dOgVlZWU4ODgAAJ49e4a8vDycOXMG48eP/xxd+sUlIiJCMLWxsQEAmJiYCKb79+/H8+fPkZOTAwMDA7Ru3Rpubm4yTE+dOoWioiLIy8tj3LhxyMzMRPv27QXT7t27Y+jQodDT08Ply5ehrq6OuLg4WFlZoVOnTqioqMCNGzfg7e2Nbdu2oaioSDCNjY1FdHQ0lixZgsWLF+Py5ctQUFDArFmz0L9/f4SFhSE+Ph7+/v4AgN27dwumERERgqm9vT3k5OTw7Nkz5OTk4Ny5cxg3btwX6/fPJT/++CNMTU0BAFZWVgAAY2NjwfPAgQN49uwZTp48CW1tbTg5OcHZ2Rlt2rRB165dcfbsWZw6dUrYPCdNmoSDBw/C3d0d06dPh5mZGbp27YqhQ4dCV1cX+fn5UFdXR2JiIiwtLdGxY0e8evUK+fn56NSpE3bs2IE7d+5gwIAB8PDwQFJSEhISErB69WokJibi6tWraNiwIaZPn45+/fohNDQUc+bMwXfffQcAyMjIwOPHj2FsbIwff/wR586dQ6NGjWBvbw8FBQUUFxfj7NmzuHTpEiIiIr5Mp39m6d27NwwMDABAsNXV1cXbt2/x8uVLnDhxAk+fPsWqVaugrKyMpk2bomnTpujZsyc6deqE8+fP4+zZsygoKMDLly8xf/58HDt2DFZWVvj++++hoaGBNm3aICgoCBoaGrh37x5UVVWRlpYGMzMztGrVCtXV1cjIyECrVq1w9OhRZGdnY9KkSejcuTO2b9+OtLQ0HD58GBMmTMDjx4+hqqqKyMhIBAQEoEePHvjhhx/g7u4OADh9+jRKSkpgaGiIvn37ignW1tYWTZo0QXl5OXbs2IHnz59j2LBhn+yXv5zk5OTkyuXk5MrqtPK6/37qc+Xl5ZCTq51Ur169CqDWACzJ/v374ejoiMLCQgwdOhRpaWlYuHAhLly4gN27d2Pfvn0oLCzE6NGjUVFRgaqqKhw7dgyurq7w9vbGjz/+iJycHKirq6Nfv35ISkrCuHHj0K5dO1RUVOD58+cIDAzE4cOH8fPPP6Ndu3bw8vLCwYMHIScnh1atWuH8+fMoKirCrFmzkJycjMOHD6Nhw4Z4/PgxDh8+jO+//x7V1dWws7PDnTt3kJWVBX19fTx79gxOTk7417/+hbZt24Ikzp49i6ioKGzZskVMjPVNsrOzxd/Xrl0DUOuIIsnevXvh4OCABw8eYMiQIdi+fTuSk5MF04yMDBQVFSE8PBwVFRWorKzEsWPH0KZNG3h7e2P06NHIzc2FhoYG+vTpg4SEBIwbNw7u7u6oqKjAixcv0L9/fxw6dAhz5sxBu3bt4O3tLcP0woULePjwIX7++WcsXLgQhw8fhpKSEp4+fYqsrCwEBwfj7du3sLOzQ0FBAY4ePQp9fX08f/5cMPXw8BA7uujoaKSmptZLpidPnhR/SytjadEGAFu3boW9vT0KCwsRFBSE9PR0LF68GBcvXsSePXuwf/9+FBYWYty4cXj58iVevnyJY8eOwcnJCb6+vvjpp5+Qk5MDHR0d9OjRAzExMRg3bhxcXV1RWVmJkpIS9O3bFwcPHkRCQgLatm2L7777DpmZmZCTk4OjoyNycnLw+PFjxMfHY8GCBcjMzISKigpevHiBkydP4ocffgBQu5AuLCzEqVOnYGRkhPLycjg7O2PixInw8PBAdXU1Tp06haSkJGzevLle8gSAS5cuib/v378PoNbhRJKff/4ZlpaWKCoqQseOHZGZmYmNGzciNzcXhw4dwpEjR3Dnzh3Ex8ejuLgYz549w2+//QZDQ0MMHToU0dHRyMnJgZOTE1xdXTF48GAMGjQIX331Faqrq1FVVQVvb28cOnQIW7duhYODA0JCQvDLL78Ip5iCggKUlZVhy5YtmDx5MrZv3w41NTUoKiri0aNHWL16NRo3bgwrKytUVFSgsLAQVlZWUFFRQfv27REREYFOnTrh0qVLOHToEA4dOoTVq1eLxc5H5a90vADSAZwCMAGA2b+rG1ZXV5fRCdd17/27pqmpSRcXF5kQgsDAQEZHR9PKyopaWlrcs2cPzc3NWVZWxqSkJCorKzM0NJQDBgxgUlISHRwc+Pz5c548eVIKEuTy5cv58OFDkmRKSgpDQkKE3ri6upp37tzh6tWruXjxYpJkaWmpSCVlbGxMJycnXrlyhYmJibx79y5TUlJYV0JCQrh69WpevHixXtrkfH19ZTIo/G+Yamho0NnZWSZjTf/+/RkVFUVLS0tqaWlx9+7dNDc354sXL5iYmEgVFRUZpk5OTiwuLubJkyfZvn17wbSoqEgwHTRokODx+vXrD5iWlJQIpiYmJmzdujUvX778UaY1NTUMDQ3l2rVrefHiRX7p/v9Pty5dusgEef9veKqpqdHJyUkmM31AQACnTp1Kc3NzampqcuvWrTQ3N2dRURHnzZtHVVVVhoaGMigoiElJSXR2dubjx495/Phxenl5kSRXrlzJ+/fvkyQ3bNjAoUOHCh4VFRW8efMmV69eLXJoPn36VMSDNW3alC4uLszNzWVSUhJv377NDRs2iM+/e/eOw4cPZ0pKCnNycuodT7I29rFuAuO6Lvd/15SUlGQyT+EP297AgQOpp6dHVVVVxsTE0NzcnAcPHuTUqVPZtGlTDh06VOQO9vPz47Vr13j48GEGBwfz1atXTElJ4Y0bN0iSqampnDBhgmDy8OFD5ubmikLIJHnlyhUx9js4ONDb25vZ2dlctGgR8/LyuGXLFr57944k+erVK0ZFRXHv3r28cuXKJ5n+bccBUAcQCmA/gKMAfgCg9Tef4fnz5wnUpkgyNDQUgaJSB+rp6YkkoZKRsUuXLiLQGAAzMzMJ1MZIWFpa0tfXl5mZmbx+/Trt7e05YcIEJiYm0tzcXJSRaN26NePj45mbm0uSjImJ4ezZs3n37l0mJiby3r17opOtrKyYk5PD1NRU5ufnkyTl5eUZFBTE+Ph4BgUF0c/Pj35+fjxw4AA/Jm/evOG5c+dkXquPkxwAkSQ5IyPjk0wlrymJqbe3Nzdu3CiO2bdvn3gALSws6OPjw3379jE/P5/29vYcP34858+fT3Nzc5HbTkrr9cfgxNjYWEZFRfHu3btMSkqSYWpjY8OcnBxu2bJFMG3QoIHIVh4cHEx/f3/6+/v/JdPz58+///IXZ/Cf5iklSd6xYwcNDAxobW0tE+Cvq6srBj0pwYOnp6dMuas/HK2ooKDApk2bsnPnzty+fTvPnz9Pe3t7RkREcO7cubSyshIOXW5ubpw7dy5///13kuTcuXMZHR3NgoICJicny/B0cnJiTk4Ot27dKg1kVFNTEwNraGgoAwICGBAQwMzMTJIUg2BdnhcuXKjXPCWmkkdpTEwMtbW1aWpqKpNOS0tLS2SOklJ0OTs7y2wqpGTlioqKNDQ0pLOzM2NjY5mSkkJ7e3sOHTqUkydPppOTk3j+u3Tpwri4OGZlZZEkk5KSmJSUxGvXrnH9+vUsKCgQHd+7d2/m5ORw9+7dzMvLI0mxsVm5ciXHjx/PkJAQBgcHc8+ePSRrJ7S6Ul1dzevXr/9bTP83HSgP4HsAzwD89FfHKikpyaTVkTycpPIZXbp0kel4FxcXHjp0SKyy58+fL1z1tbW16eLiwsaNGws345s3b3LixImMiIhgWFiYKIMTEhLC06dPs3v37hw+fDi7d+/OTp06cdu2bXz79i2vXbvG3NxcPnr0SAyAJLlw4UK+fv2aJJmRkSFelx5C6XfrPnxRUVHi/V27donv++Oa6t0kZ2NjI1PySPLIs7CwYJ8+fT7KNDMzU6y0582bJ4J/dXR0BNPZs2eTrPWUnDBhgmAqufMPGjSIp06dYo8ePThixAj26NGDXl5e3LZtG9+8eSPD9OrVq4JPcnIyq6qq/ldMo6Ojxfu7d++WYfql+/8/3aysrETgL/Bn9hBzc3OR4aQuT2dnZ+7evVsE9MfExIhEybq6unR2dqaqqqpIzpCbm8tx48Zx7NixDAsLE2WNQkNDefz4cfbq1YsjR45kQEAAfXx8uHXrVlZWVjI/P5+5ubl8+PCh4FlTU8MlS5awsrKSJMVkRlJMXn9kpZHhOW/ePLEw2rdvnxgU6yNPkmjatKlMsVNJm9a0aVN6e3uzffv2tLKyEnksW7duzUWLFomMMePGjROTnbm5Od3c3GhoaMiIiAg+fvyYu3fv5ujRozl69GiOGDFCjNEjR47kvn37GBISwvDwcIaEhLB///7cuHEj79+/z4sXL/LixYu8f/++2NVVVlZy06ZNLCkpYWVlpZgcpXuHJBMTE0mSd+/eFe9t3ryZt27dIkmePn1a7Pz/CEv6aL/8bccBcAeQDOAigF8AfPNvfIZArZuvs7OzTGzD2LFjWVRURBcXF2pqatLPz4/du3dnSkoKgT9rCcXHx/Pw4cM8ffo0GzRoQJLctGkTKyoqSNaqL7Kzs5mRkSEumiTPnTsnch4OGjSIw4cP56hRozh37lxu3ryZvr6+TEtLo5OTE6urq8Wq7/Hjx9y2bRsrKirEA1NcXMy1a9dy2LBhzMrKYkBAAMeOHcu4uDiSFKpQkjx16pT4uz5OclLWcX19fTo7O8tkuwgPD+f9+/fp6upKLS0t+vn5sUePHoKp9FDFx8fz4MGDPHnyJJWUlEiSGzdu5KtXr/ju3TuWl5czOzub+/bt482bN2WYSrlJQ0NDZZhu2rSJXbt2ZVpaGlu3bv0B07S0NFZUVDAmJkYwXbduHUeMGMGsrCz26tVL7DZISsUXSdY+RHXkizP4XDxbtWol4kUBcMyYMbx16xbd3Nyoq6tLf39/9ujRQywmpVRKcXFx3L9/P7Ozs9mkSROStWrjFy9esLKyki9evODRo0e5d+9emVX3mTNnOHHiRJLk0KFDOXLkSI4ePZpz587lxo0b2b17d27fvp3u7u6sqqrimzdvBM/09HS+evWK8+bNI0k+f/6cGzZs4OjRo3nkyBEGBgZy0qRJTEpKIkn6+PiI3z179my95UkSkspZW1ubtra27Nu3L+Xl5amhocHRo0fz2LFj9PLyop2dnUipKE1UVlZW1NTU5Jw5c7ht2zbu3buXtra2fPLkCdesWcOrV6/yzp07vH79OjMyMpiens4LFy6IEJ4TJ05wzpw5JMnx48dz4sSJnDBhAuPj47l+/XqGhoZyx44dHDBgAEtLS8U4/ujRIx46dIhlZWVct24dSbK8vJz79u1jVFQUs7OzOXnyZC5atIipqakkKUJXSPLy5ct/y/QvOw1AwR+T2yQALgBa1W2f+lzTpk1lkrdKLT4+no0aNRIFFm1tbTlz5kwRSLxgwQKGh4dz9+7dnDNnDrOzs8XZW1tbk6RI+WRra8s7d+7w4MGDPHLkCA0NDZmXl8eamhq+ePGCS5cuZUREhFRWg2TtpHft2jUePHiwbscwNjaWY8aM4a5du0jW2gaePn1KkuLzY8eO5eXLl5mSksKYmBiuX7+e27Zt48CBA1lYWMgpU6awtLRUurZ6N8ktWbJEplKD1ObOncvGjRuLHIR2dnacOXMmr169SqA24D88PJy7du1idHS0DFMpiFta/dva2vL27ds8ePAgs7KyaGxsLJg+f/6cy5YtY2RkJOfPny++IzQ09KNM586dy7Fjx3L37t0kyVWrVgmm0ucjIiIE07i4OKakpDAtLY3BwcEsLCzktGnTWFpaKtlvvziD/2RLTEyUyQ8oqRzj4uKoqakpUtQ5Ojpy1qxZzMvLEzzHjh3L9PR0xsTE8NixY2IS+iMTvBSzREdHR964cYMHDhxgVlYWLS0tmZeXxzdv3rC4uJgrVqzgpEmTuGDBAsFt2LBhzM/P/4Dn/PnzOXHiRO7du5ckuX79ej579owkpVJInDBhAq9cucJNmzYxISGBGzduZHp6OsPCwlhYWMjZs2ezrKyMw4cPr3c8SWLMmDEfFKPV0tJidHQ0HRwcRJIEX19fxsXF8cSJE9TU1OSCBQs4adIkbtmyhQkJCTxw4ICIV/Tz8yNZ+zyVl5fT19eXFy5cYEZGBg8ePEgvLy9euHCBpaWlLCoq4ubNm5mQkCAmrOrqak6ZMoUXL178wDyQkpLChQsX8vjx4yRr0/iVlpaSJNPS0gT3q1evcs+ePVy3bh337NnDrKwsRkVF8eHDh1y1ahUrKioYGxv7SaZ/2WkAjgDI+kQ7/BefIwA+fvz4g7Lne/fu5YgRIxgWFkYrKyvu3r2bMTExXL16Nd+9e8ebN2/y0aNHJCkcBkjK2L2Ki4s5Z84cHjhw4P3VGck/b3pJ7ty5I/6Wgk/PnDnDGzdu8M6dOzIOBytXriRJoUYjKVUSJknm5OTw2LFjPHPmDMlaY2p6ejqfP39OstYeUB8nOYlfUVHRB0z37NnDESNGcNiwYbS2tubu3bsZGxvL1atX8+3bt7xx44Zw+pGcBsg/mdbU1PDZs2ecM2cOMzMzRd/Wlb9ievjwYZJ/Mi0oKJBhKgUpSypKkvzxxx/F3xJT6V7asmULd+7cKcP0S/f/f7pJ7G7cuCFTCQKoLU0zcuRIjhgxgi1atODOnTsZFxfHVatWsbKyklevXhVqoqVLl4p+lPqvurqajx49YkxMDPfv3y+j5ZCk7n1AUsZmc/ToUfF9Es9NmzaJ9/8I5ha7b1J2dZ+bm8vs7Gxxf6WlpXH37t2C5x+T8hdn8J9uEr/U1FSRhAN/2NY2btzIyMhIjh07lp06deLWrVuZmJjIVatW8f79+zx9+jRzc3P5/PlzkaShqqqKJ06cIEk+efKE165dY0JCAnft2iUYVVZWCrPA+854dVXHkhng4sWLvHnzJu/evct9+/aJ96W/6zoLSbtxkszLy+Pp06clJzAeOHCAR48eFQk+/lBlf7Rf/jKEgGRHkp6faN9+6nNaWlrw8PDA4MGDYWFhAQBwc3ODn58f7t69i/Xr16OgoACBgYFwcXGBnZ0dvv/+e5SXl8PKygoxMTF4/vw5PDw8kJubi++//x6vX79GWVkZfv75Z9y4cQNycnK4cuUKtm7dihcvXoiYjHnz5uHSpUv49ddfkZycDAAiNxpQG9Lwyy+/YOrUqbh37x4qKythZGSES5cu4fr16xgyZAimTZuGadOmITo6GgDQrFkzAEBBQQHmz5+Pb775BufOnQMAdOjQAdXV1dDU1ER+fj62b9/+V136Xyv9+/dHu3btMGTIEJibmwOQZZqSkoKCggL069cPzs7OsLW1Rf/+/VFWVobmzZsjNjYWxcXFcHd3R05ODgYOHChcyefMmSOY5ufnIy0tDc+fP8eRI0dw7NgxzJs3D5cvX8avv/6KX375BcCHTBcvXozp06fj3r17qKiogJGREa5cuYLr169j8ODBmDFjBqZOnYrY2FgAENdQUFCApKQkfPPNNzh//jwAoH379oLp1atX6yXTXr16wc3NDaNHjxb3t7u7O7p164a7d+9i8+bNKCgoQM+ePdGyZUtYWVmhV69eKCsrg62tLRISEvDo0SO4uLjg/PnzCAkJQUVFBZ4+fYq4uDjcuHEDJJGfn4/09HQRmnP06FHMnz9f8FyyZAkAWZ43btzAihUrEB0djcLCQlRWVsLQ0BD5+fm4efMmgoKCEB0djfHjx2P+/PkAZJ/RxYsXw8PDAxcvXgQAtGvXDm/fvoWmpiauXbuG3bt3/x/29P+ddOzYEQ4ODliwYAFMTEwgJycHDw8PdO/eHQ8ePMDOnTtx584dtGnTBiYmJtDS0kLbtm3x7Nkz+Pj4YP369bh//z4sLCxw+PBhREREoLi4GJcuXcKKFStw+/ZtvH79Gjdv3sSBAwdw5coVHD58GNnZ2Vi8eDGuX7+Offv2Yd26dQBq44cluX//PtLT07Fp0yYUFxeL/LO3b9/GgwcP4OPjg5SUFHz//fdITU0FUBuHCwAPHjzAr7/+ChcXF9y5cwdAbfhSTU0NNDQ0UFBQgOPHj3+6Y/6N1YE2gNEAFv3RfsS/4V0J1LqASjkIV61aRSMjI+GwkJ2dLXTFISEhwuApeXM9efKEMTExIru8pDtOSUmhh4cH+/XrJ1Yc4eHh3LlzJ6dNm8aJEyfyyJEjtLW15bp169itWzcuWrSIW7du5evXr2V2ahUVFczKyhJqSpLCJZ38084mqdPI2izrOTk5wsZw/PhxVlRUSKUe6q3jyceYrly5UoRXAODRo0epqan5SaaPHj1idHS0YCo5oqxbt04wlXZd4eHhTE9PF0yzsrIE0+7duwumVVVVMju1iooKHjly5JNMJTubpFIjaz1wc3JyhFH8xIkTrKiokNRa9dJRQeJpb28vsrgvXbqUZmZmwlHs4MGD1NXV5Y8//sjg4GBR4FbieffuXUZFRQn7rFSseNWqVezQoQP79evH5cuXs7q6muHh4UxLS+P06dM5adIkHjp0iI6Ojly7di0DAgK4ePFibt26la9evRJp3eLi4vjq1SseO3ZMeNmRFFoB8k9tgGRzJWtNDHl5ecKue+rUKb569UqqHl0vedZlamtrK7Qt0dHRtLOzo5ubG5WVlblu3Tqam5szNDSUgYGBQoXZo0cPKisr8+jRo5w8eTJHjRpFdXV1zpgxQ6ixvby8GBgYyPnz5/PatWuMiIjg+vXrOXPmTE6dOpW7du2ij48PV69ezSFDhnDp0qXcsmULHz58KOxpa9euZXl5Oc+ePctjx44JZpJtj6RwOKq7M9y0aRNv3rwpNAh5eXkyttmmTZt+kqniX60M5OTkvgJwGLXhAxcAyAFoA+BfcnJy35K8+qnPOjk5wdjYGO7u7rh37x5ev36N4OBgqKmpYdKkSZg8eTKMjY1hYmICPT099OzZEyoqKujfvz9u374tAjmjoqIwceJEsSr75ptvoKWlBV1dXURFRWHz5s04fPiwSP+yZMkSyMvLw9vbG69evcLIkSORm5uLGzduoFmzZrh+/ToOHz6MrKwsBAYGomPHjhg8eDC8vLygrKyMffv2oU2bNvj6669F4OqsWbPEdQ0aNEjsMiorK2FrawsLCwvExsZi5MiR8PDwEClq6ptITN3c3ATToKAgqKqqYuLEiZgyZQqMjIxgYmICHR0d9OzZE8rKyujXrx/u3LmDyZMnw93dHT///DMmTJiACxcuAJBlOmfOHKSmpiIrKwuVlZW4cuWKWO1LTEeMGCGYmpubC6ZHjhxB//790aFDBwwdOlQw3b9/P5ydnWFvbw8XFxdUVlZixowZ4rpCQkJQXFyMI0eOoKKiAjY2NmjevDmio6Pxww8/oEOHDl+kvz+3ODg4wNjYGK6urnjw4AGqq6vRv39/qKqqIiIiArNnz4a+vj6MjIzw9ddfw9/fH8rKyujZsyfu3LmDGTNmwNXVFXPnzkVkZCRyc3MBAG3btoWmpiZ0dHQwb948bN++HdnZ2aiqqsK1a9eQlJQEAPD09MSrV68wdOhQXLp0CTdu3BCVBaTg5J49e+Kbb77BDz/8gG+//RbKyso4ePAgWrVqBTs7O7Ru3RqVlZWYNGmSuK7vv/8eL168wG+//YbKykpYW1ujZcuWmDFjBiIiItClS5cv0d3/J2JlZQUdHR04ODigtLQUb9++RadOncTYunbtWujo6EBXVxeqqqpwd3eHvLw8OnbsiHv37mHJkiWws7PDqlWr0KdPH1y5ckVUj2nSpAk0NTWxdetWHD16FJcvX8abN2/w4MEDkUWmZcuWePXqFXx9fXH79m0UFBRAS0sL169fx4EDB3Dy5El88803cHZ2RlxcHJydnaGiooJz587B2toa5ubmsLGxwZs3bzBw4EBxXd7e3igvL8elS5dQXV0tUjIOGjQIiYmJIpPRx+Tv0npFAQgnOYjkApJJJENQu7Ob81cfbNmyJUaMGAE1NTVMnToV0dHRMDU1hbW1NQAgMTERly5dwsSJE7FkyRJs2rQJ2dnZePDgAZKSklBZWQljY2NUVFSgUaNG0NDQQEJCAszNzXH69GkoKiriu+++w/PnzzFlyhT07dsX2dnZGDBgAAwNDbFgwQKMHDkS+/fvx7Nnz0SutYMHD+Lt27dITU3FnTt3MH36dJFyBqjNh3f27FmsXLkSAIQKCwD8/f1hZGQEDQ0NDBkyBA4ODtiwYQNCQ0Px5s0bJCYmymQGqW/i6OiI4cOHQ11dHVOmTEFsbCyMjY0F04SEBMF0+fLlSE1NxfHjx1FYWIj58+ejsrISJiYmqKioQOPGjaGlpYV58+bBwsICZ8+eRYMGDfDdd9+hpKQEU6ZMQZ8+fZCdnY2goCAYGRkJppmZmSguLsbDhw9x7949HDp0CG/fvsWmTZtQUFCAmTNnolOnTkhPTwdQy/TcuXNYvXo1AIjJFQB69OgBQ0NDaGhoYPDgwXBwcMDGjRsF04SEBBw5cuT/uqv/T+Trr7/G4MGDoaqqivHjxyMhIQHGxsYizdecOXOQl5eHf/3rX1izZg3S09Nx+vRpPH78GHPnzsXr169hbGyM8vJykZMwLi4OdnZ2uHDhAho2bIguXbqgvLwcEyZMQM+ePZGVlYXhw4fD2NgYiYmJ+OGHH5CVlYWSkhI8ffoUhYWFOHr0KGpqarBmzRrcvXsXP//8Mzw9PYWaUU9PD7///jtSUlIAQEyuABAYGAgDAwOoq6sjKCgI9vb22Lp1K4KCgvD27VtER0cjIyPj/76z/4+kWbNm8PPzg7KyMvr374/U1FTo6enB3NwcDRo0QHh4OPbt24fly5fj6NGjuHDhAu7du4c3b95g3LhxaNCgAczMzPD8+XNoampCT08P06ZNQ48ePXD37l2oqqqiQ4cOqKmpweDBg9GlSxesWrUKycnJaNq0KaKjo/Hjjz8iPz8fb9++xevXr8XkBABTpkxBUVERVqxYgZYtW+LEiRMAAA0NDdy8eRP79+8H8GcWHgCYPXs2tLS00KRJE3Tp0gUWFhbIysrCd999h5qaGowYMUKYpj4mfzfJfU1yy/svkkwDYP+pD9nY2KCiogLr1q2Dnp4eMjIy8O7dO4waNQrv3r0T6WFcXV1RWloqaj1lZmbC09MTnp6eMDQ0xN69e1FcXIx3797By8sLEyZMQHx8PNq0aYM5c+bgzJkzcHV1xahRo2BmZobvv/8ehw8fhqampjgXIyMjWFhYYMqUKejZsyfOnz8PExMT5ObmivpUSkpKUFNTw9u3b+Hn54e+ffvi22+/xdu3b2UmrY0bN+Lw4cNQVlbGo0ePAACjR49Gq1atsHHjRigrKyMxMfFvuvS/U6Sd1bp166CrqyuYjh49Gm/fvkVsbCzy8vLg5uaGFy9ewMfHB1euXMH+/fvx7bff4ttvv4WxsTEyMjLw9OlTvHv3Dp07d8bkyZMF05iYGJw7dw4uLi4YOXIkzMzMMHDgQBw4cABaWlriXIyMjGBpaYl//etf6NmzJ86ePQsTExPk5eWJtEV1mX733Xfo3bs3PD09P2CakpKCrKwsqKioCKY//vgjWrZsic2bN0NFRUXsPOqT7N69GxUVFdiwYQN0dHRw4MABvHv3DuHh4Xj79i0SEhJw5coVtGvXDo8fP0aXLl1w7do1ZGRkwNvbG97e3jA2NkZWVhYePnwIeXl5eHl5ISoqSvBMSkpCbm4u2rRpg2HDhqFp06YYPHgwdu/eDR0dHXEuxsbGsLS0FBPh8ePHYWpqivz8fFhaWuLx48do2LCh4Ont7S12eG/fvpVJUbZixQpkZ2dDWVkZT548AQAMGzYMDg4OSEtLg4qKirDr1jeZM2cOKisrkZGRgSZNmuD06dN4/fo1pk2bhnfv3mHLli24e/cuBg0ahOzsbLRv3x5Pnz7F9u3b0bt3bwwbNgzm5ua4efMmcnNzoampiU6dOiEtLQ1z586Fi4sL9u7di8LCQrRu3RqBgYEwNzfHvHnzsHDhQjRt2lScS9OmTWFjY4MRI0agR48e2Lx5s2Bpbm6OFy9eoGHDhmjUqJGo59iuXTtha6ubomzy5MnIzc2FkpISSktLAdRuOCwsLJCdnQ0VFRVs3rz5k/3yl1UI5OTkfifZ6n/7nqamJktKSjBw4ED4+vpiwIABcHZ2Rvfu3fHy5UuoqanBxsYG/v7+mDhxIkpKSvDgwQPk5OQgLS0NysrKSEhIwODBg+Ht7Q1zc3McPXoUt2/fxr1795CRkYFTp04hJSUFFhYWMDAwAEkoKCiIc3jw4AEuXryIoqIiWFlZ4dtvP/STefbsGbS0tCAvXzvXh4WF4dGjRzKG6V27dsHFxQUGBgZYuXIlhg4dCgB49+6d+L3t27ejoKAAbdu2xfLly7F27dp6V4UgICCA6enpGDBgAHx8fBAUFCSYlpeXQ1VVFba2tvDz88PkyZNRUlKCwsJC5ObmYsuWLWIBMGjQIHTp0gWWlpY4dOgQ7ty5g3v37mH//v04ffo01q5dC0tLS+jr6wPAR5k+fPgQVlZW8PT0/OA8i4uLoampKZgOHz4cjx8/Frs6oHaAb9OmDQwMDLB69WoMHjwYgCzTHTt24O7du3B1dcWKFSuwevXqepW13s/Pj3v27EG/fv3g5eWFoUOHwtnZGV27dsWrV6+gpqaG5s2bw9fXFzNnzkRpaSkePXqES5cuYf369VBWVsaiRYswcOBAdOnSBV999RX27NmDgoIC3L9/H4cOHcLZs2exfPlyNGvWDHp6epCTk0ODBg3EOTx48AB5eXl49OgRLC0t0b59+w/O832eY8aMwZMnT2QGtX379qF169bQ09NDSkoKgoKCAMjy3L17N+7fvw9nZ2esXbsWixcvrlc8AcDNzY2nT59G586d4ebmhp9//hmtW7cWiwFVVVU0a9YMbdu2xfr161FZWYni4mLcuXMHM2fORMOGDbF9+3b4+vriu+++g6+vL+Lj4/Ho0SM8evQIZ8+exfXr1zFhwgSYmppCW1sbCgoKUFJSgpKSEoBaprdu3cKLFy9gamoqitfWldLSUjRp0kSwSUxMxIsXLzB79mxxzKlTp2BrawsNDQ3s379fqJhJirzIJ06cwOPHj2FjY4OdO3di8uTJH2f6N4bMBwB++kiLBHD/U59r0KABo6OjWVFRIeqxNWjQQBRijI2NpZqaGteuXUsNDQ2OGTOG48ePFwUwIyMjmZ+fz2XLlnHWrFnCyaNuYOfQoUOFoZqkyIm2adMmXr9+nRcvXhT1jSQ5dOgQt2/fzurqapK1WS2qqqo4ffp0jhs3jjt27BCB5XVjujp16kSytr5ZXl4e09PTSZJjxozhixcvOGvWLFZUVHD+/Pk8depUvXQ8MTU1ZVRUFMvKymSY/pGrkzExMVRXV+eaNWuoqakpw9TOzo6RkZG8cuUKly1bxtmzZ/PatWskSV9fX8EnLCyMW7ZsYXl5OUly0qRJJGuzHEhMR40a9QHTHTt2fMB05syZnDBhAtPT0wXT2NhYwdTb25tkbXhIXl6ecFQZO3YsS0pKhBNLYmKi5ID0xRn8J5uxsTGnTZvGoqIiUY+tYcOGPHHiBIHagrNaWlpcsWIFdXV1ZXg6Ojpy3LhxzMvL47JlyxgVFcX8/HzW1NSwe/fugs2IESO4ZcsWlpSUkCSnTJlCsjZEQ+I5duxYERhMUjiCSRmI9u3bx6qqKkZHR3Pq1KncvXu3CB+ZP3++cHGXfjciIoJXrlwR8XSTJk1iaWkp4+LiWFFRweTk5HrJkyR0dHQ4aNAgpqenizRsKioqXL16NRs2bMjIyEiam5szPj6etra2HDt2LCdNmsTZs2fTy8uLU6dOZXZ2NpcvX86EhAT+/vvvfPr0qXCqI8mJEydyy5YtwgFEiiPetWsXr169ypycHMbGxgrmZK1z3sGDB8VYffz4cVZVVXHt2rVcunQps7OzWVhYSLJ2/JZSfUnPf3JyMu/evSscAZctW8aKigpu2LCBlZWVTE1N/Uumf7eTm/HJN2snyFkfe11eXp4AoKysjGHDhgk1x/tia2uLpk2bCscAoHbLvXnzZlhZWYlSGWFhYTh58iTmzp0LJSUlxMbGYvTo0VBRUYG/vz8MDQ1x+PBhhIWFYdOmTaIG2bp169CzZ0/IycmhcePGMDIygo6ODpYsWYLz589j5cqVGDt2LJycnIRr++LFi/Gvf/0Lb968wTfffINnz56hWbNmwjYIAFeuXMFXX32FwsJC4eb6r3/9C1VVVdDT08PkyZPr3U6uUaNGrKqqgpKSEsLCwnD9+nWhP68rH2P6888/IzU1VWQTt7e3x4gRI/Dbb78hPj5eMB0zZgxUVFTQtWtXGBoaIisr6wOm69evR/fu3aGgoIDGjRvD0NAQurq6WLp0Kc6fP48VK1bgp59+gqOjo2C6dOlSTJo0CW/evIGHhweKi4thbm7+t0ynTZuGyspK6OjoYNKkSfVq5V+X56BBg3Djxg1Rp62u1OXp4uICoLZftm/fDgsLCzRq1Ah2dnYYO3YsMjMzsXDhQjRo0ACxsbEIDw+HiooKfHx8YGBggGPHjiEsLAybN2+Grq4udHR0sHHjRuE00KRJExgYGMDAwADLly/HxYsXsXjxYkycOBFff/013NzccOnSJaxatQo//fQT3r59i7Zt26K4uBhNmzaV4Xnt2jXY2Njg4cOHMDQ0BFBr26msrISmpiYmTJhQr3gCtUxfv34NRUVFdO3aFffv3xehTnJycpDG+hYtWsDY2FiUupKXl8fgwYNx7NgxmJiYQEVFBc2aNcPChQuRlJSEbdu2QU5ODuvXr0dgYCAaNWoEd3d36OrqIicnB99//z127twp6splZmaiXbt2AGrnAF1dXVhZWWH9+vW4c+cOJk2ahKVLl8LGxgYtWrTAnTt3sGvXLvTr1w81NTVo0aIFXr58CQMDA7x+/VrsEu/fvw9TU1MUFxdDW1sbALB06VJUVFSgQYMGGD169EeZfraiqQMHDoSmpiaSk5NhYWEBIyMj/Pbbb7CyssKDBw9QVVUlChnGx8cjJycHpqam2LlzJ6qrq2FjY4PHjx9DSUlJJgbCwcEBubm58PHxwcOHD6GkpIRbt25h7dq1WLduHUJCQpCbmws5OTm0a9cON2/exKVLlzB//nzk5+fj119/RXh4OBwcHERc1ooVK6Curo6+ffuKemcGBgY4c+YMXFxcsHnzZgQEBEBJSQkPHjxAeXk5MjMzER4eLs4rISEBX331Fbp164Z3797Vu0lOTk6OAwYMgIaGBhYtWgRzc3OYmJjgt99+g6WlJR48eIDXr18LpnFxccjNzYWZmdm/zdTX11cwvX37NlavXo3169cjODhYMHV3d8etW7dw5coVzJs3D1euXMHevXsxevRoODk5QVFREXl5eVi5ciXU1dXRp0+fjzJNTU1Fjx49ZJgePHgQo0ePFuc1f/582NraokePHqiurq5Xg6KcnBz79esHdXV1LF++HObm5jAwMMCpU6dgbm6Ohw8f4vXr19DS0sLz588RFRWFy5cvw9TUFHv27EF1dTWaN2+O4uJiNGzYUMaj2MnJCTk5OfDx8cGTJ0+gpKSEgoIC4WAWGBiIS5cuQU5ODm5ubqKoanx8PC5duoT9+/dj5MiRaNeuHRQVFXH27FmsXbsWampq6NmzJx4+fAg5OTkYGBjg3LlzcHZ2RlpaGvz8/ATPly9fIisrCyNHjhTnlZSUBGtra/Tr1w/l5eX1iidQy9Tb2xuNGzfGjh07YGRkBC0tLVy6dAlGRkZ49uwZqquroaGhgZKSEowePRoFBQUwMjLCyZMnUVNTA1NTU5SVlUFRURFHjx4V3+3s7Iy7d+/C3d0dpaWlUFJSQnFxMcaNG4dDhw7By8sLt2/fhry8PL766isUFRXhwYMH+Omnn3D16lWcPXsWvXr1wpgxY9CwYUNs3LgRu3btQpMmTfDtt9/iyZMnIAl9fX1cuXIFdnZ2OHLkCNzd3UUJtIqKCpw/fx69e/cGAFRUVCAlJQXGxsaYPHky8vLy/vdFU+Xk5Kb/RZv2V5/9n//5HyQnJ2P48OG4ffs22rRpAwDo0qWLuPHatWuHhg0bYu/evdi8eTOSkpLg6uoKU1NTDBs2DJaWlnB3d4eGhoaoR/fgwQOYm5uLIO7Tp0/jyJEjiIuLQ3R0NDp27Ig+ffrg6dOniI2NRYsWLdCjRw/069cPv/32GxwcHHDhwgVcvXoVv/76KxISEqChoYG+ffuitLQUa9euxaxZs7B582ZoaGgAqA2ELioqEp5/X331Fb766iv861//wm+//YbmzZsDgHDHro8iLy+PDRs2YNGiRQgLC0NBQYFg6u3tjREjRgCAuCkzMjKQmpqKpKQkuLi4wMTEBEOGDIGFhQXatm37UaYVFRUwNDTEqVOncPDgQcTFxeHnn39Ghw4d0Lt3bzx9+hTx8fGws7ODv78/AgMDceLECXz99de4ePGiCDxOTEwUdelKS0uxfv16sZuUmPbr1w9FRUXw8/MTTG1sbARTGxsbkISRkZHYwdQnUVBQQGpqKpYvX47Q0FAUFBQI+0nnzp2FndLV1RUNGzbEgQMHsG3bNvzyyy9o1aoVjIyMEBQUJOwumpqaguf9+/fFzkpPTw/Hjx/Hzp07MX/+fEyZMgXt2rVDt27dUFxcjKSkJHz11Vf47rvvMHDgQJw+fRr29va4dOkSLly4gNTUVPzyyy/Q0NBAz549UVZWho0bN2Lu3LlIS0uDuro6gNrg9qKiIvTs2RMlJSWwtbWFpaUlpk+fjuzsbNjb2+Pt27fQ09OTqW1Zn0RRURGZmZnYsWMH/Pz8UFRUJAocS/ZWoHZ3rqSkhOzsbOzbtw/r16+HsbExlJWV4e7ujsaNG4swIHv7Wv/Ce/fuQU1NDcXFxVBWVsbu3bsxbdo0rFu3Dt9//z1sbW3Rrl07vHjxAlu3boW5ubkooHvjxg3Y2tri4cOH2LZtG2JjY7F582bhqVlWVobMzExs2rQJBw4cgIqKCoDa4PYHDx5g7NixePr0KZo1awYNDQ3Ex8fj4MGD8PPzQ3l5ORo2bCiKxX5U/krHi1rb2/ttOoC7AF7+xefo5eXF0NBQmXRBbm5uBEA/P78PciBqa2sTAN3d3QnUlm7o0KEDBwwYIIKPpWZvby+S/gLgtGnTuGbNGubm5nLGjBk8efIk8Ud27Lo2HklPf+rUKZnSG+PHjydJbt++nWRtnbLbt28zKyuL7969Y1FRER0cHLhy5UqmpKRwwIABJGuzoXt7ezM9PZ3p6ek0NjbmzJkz66VNDgA7d+78SaZ1s59LTbLdScd4e3vTw8ODgYGBIgD575jm5OTIMB01apQMUykdUN2UP+SfNtodO3aQrE3Xdvv2bR45coRv375lYWEhnZycBNOBAweSJPfv309vb2/u2LGDO3bsoImJCWfMmPFJff9/awNqy+ZIeWSl5uLiIp6/93lKtjtnZ2dKn3dzc2Pv3r3ZuXNnmWPt7OzYuHFj4o+cmFOmTOHKlSt5/vx5zpw5k9nZ2QRqk3tv3bpV5Czcv38/ydogbykbPUlOnTqVJIXtdM2aNbx9+zaPHj3K6upqkSBc4hkcHEyy9pn39fXltm3buHXrVpqZmXHy5Mn1jqfE1NnZ+YPxskWLFjLPYd0mlcSytbUlUFtdxM7Ojh06dBCcpWZhYSGO19LSYmRkJJOTk3no0CGRZtHExITTpk3j9u3bRRIGyQ6en58vk0x/0aJFJCkqEKSnp/POnTs8ceIES0pKeOPGDfbu3Ztr165lSkoKR40axTdv3jA1NZV9+vThmjVruHTpUlpZWf1lPtL/TQeqApgK4A6AOAB6f9XZUlNWVmZ8fDxHjRpFXV1dDhgwgLq6ugQgasABoI2NDQGwffv2bNCgAQHw8uXLTE5O5tq1a2XqFq1du5Y7duwQOfckA2VaWhp1dXVpa2vLzp07Mzc3l2vWrOGSJUuE0VIqlnrt2jXm5+dz8uTJPHXqFEeOHMkBAwbw999/p4eHBxcvXiyy6JO1ufXmz58vbhSSYlCtmycO9TzjicQ0Li6OI0eOpK6uLgMDA6mjo0MAgm1dph4eHqKAY05ODhcsWMBVq1YJpl5eXly9ejXT0tIE0z8GIqalpVFfX58tWrSgt7c3c3NzhcFayl4SGhoqw3TKlCmCaVBQEC9cuMCOHTtyyZIlMkxv374tw/Tdu3cix977TL90/39unrNnz2ZYWBh1dHTYt29fseiUuAJ/lm5xc3MTRVaPHz/OuLg4Jicni4HS09OTixcv5qZNmz7guW3bNjZt2pStWrWin58fc3NzmZKSwpUrV4rsJVKu2Bs3bvDq1aucOXMmT58+zbFjx3LIkCG8ePEifXx8uHz5cm7YsEHwvH79OhMSEujh4UEAfPXqlXjupSwu9ZXn+0yVlJQYFhbGbt26UV1dnZ6enqJ6hLq6ujjOyMhIZpIDarNLDRs2jOHh4TQzMyNQW5ZnwoQJjIuLE/07ZcoUlpWVccuWLfT09GRAQABHjBjBnJwcpqenc8eOHSJ7iVQ2Ryq3s2jRIp47d46xsbGcNWsWL1++zB9//JGbN2/m1q1baWlpyaqqKp48eZJz584VE3deXh7T0tKYl5cnMi39HdO/tcnJyclpodajcgCAdQAWkHzxV59RU1Pj119/DUVFRfTr1w+jR4/Gt99+i4MHD8LT0xOqqqq4cuUKZs2ahQEDBgCoDeLctGkTdu7cie7du8Pd3R2vXr0Sxs3KykooKSkhPT0dxcXFqKmpwaRJk7B//37cv38fGhoa+Prrr3Hw4EFUVVXBz88PAPDy5UsoKipi9+7duHr1KqZNm4YRI0bAxMQErVu3xtatWzFv3jwoKCggPT0dJ0+ehLm5OXJzc7F48WIkJiZCV1cXurq6ePDgAWpqarBo0SLcvXtXlG9v3rw5Xr16BVtbWyk7R72zyXXu3JmvXr0STMPDw+Hp6YlDhw6hY8eOUFVVRX5+PqZPn47g4GAAtWrezZs3Iy0tTeRKrKiogK6uLnJzcwXT7du34/nz56ipqcG//vUv7Nu3D/fv34empqZgWl1dLUrcS0x//fVXXL16FVOnTsUPP/wAIyMjtG7dGmlpaYiLi4OCggJ27dqFU6dOoWnTprh06RIWLFiAhQsXQkdHBzo6OoLpkiVLUFBQgEmTJmHHjh2wsrIS2U+WLl0KkvXKhuPp6cmKigooKiqiZ8+emDBhAr755hscPXoUHh4eUFVVxbVr1zBp0iQMGzYMQK1KMC0tTbjpOzs7o7KyErq6urh06RKqqqqgrKyMjRs3oqSkBDU1NZg9ezbS09NRVFQEDQ0NODo64uDBg3jz5g18fX0B/Mlz//79uHbtGiZMmICxY8fC0NAQjo6O2LlzJ2bPng1FRUXs2bMH586dg6mpKS5fvoy4uDgsWrQI2tra0NTURGFhIWpqarBy5Urcvn0bkZGR2LlzJywtLfHq1SvY2Nhg1apV9Y4nAPxRagry8vJo3749Fi9eDAcHB1y8eBGOjo5QUVHB3bt3ERQUhLlz5wKAyNA0efJkxMTEwMbGBq9fv4aGhgbu3buHt2/fQkVFBVFRUaisrBRmiwULFqC0tBSamppwdnZGVlYWSKJDhw5QUFDAy5cv0aBBA5w5cwZ37txBcHAwYmNjoaWlBQsLCxw9ehTDhg0Tx1y7dg06Ojoi12xqaioaNWqERo0a4eHDh3j37h127tyJmzdvom/fvjh8+DAMDAxQVVWFZs2aYffu3Z9m+jcrg3gAtwBMBNDkf7OisLW1lSmyCdRW+p4yZQrd3NzI2gMZGhoqcuLhD5XWoEGDqK+vT1tbW06aNIkWFhZihSgdl5CQwNDQUKHemD9/PvPy8uju7i5TVFGStWvXsrKykmfPnuXVq1c5depU5uTkiEzXmzdvlin5MW7cOG7fvp3x8fHiN5OSkoSqtVu3bpRqcgG1JWc8PT3p6upaL3dyioqKtLW1/UBduW/fPk6ePJmurq6CaUhIiEwNQS8vL4aEhAimEyZMoKWl5d8yTUxMZF5eHj08PD7KdN26dayoqBBMp02bJsM0NTWVCxcuFMePHz/+A6aJiYlC1erv7y/DNDY2lp6ennRxceGX7v/PwdPa2voDdeX27dsZGRlJZ2dnwTMwMJBjxowRx3h6enLAgAE0MDAQIT/SLq9Tp04yPMPCwkTR2oULFzI3N5edOnX6aFX2lJQUlpeX88yZM7xy5QpnzpzJCxcuCIZbt24VlUnevn3LSZMmcdu2bZw7d674zbi4OLHqf19tN2vWLLZv356tW7eudzzJ2tAtc3PzD657zpw5HDhwIB0cHJiTkyM0Yn379hXHuLi4sGvXrjQyMhJjt6TmrPt9HythdeHCBYaGhvLIkSMfME1PT+ezZ8+EOSExMZFnzpzhihUrSNaG/GzcuJEkWVpayujoaG7cuJHR0dFCmxARESF2j5I6XWpDhgyhk5OTVLbro/3yl50GoAZAJYByAGV1WjmAsr/4nNjiSsXygFrdsKQuAsDhw4dz0KBBHDduHAMCAhgbG8tFixaxuLiYhw4dkknaefLkSZK1SXifPHnC9PR07t69m1evXuWOHTuYnZ3N7OxsoeclKR4ODw8P3r59mwsWLBBqk1atWnHr1q3s2LEjyT9tOzU1NVyzZg1v3LjBo0eP8tixY9LEJcXAiQcfqI1DkQZJa2vreq+ubNWqFUNDQ7lt2zYCtbaX9evXi34ZNmwYQ0JCGBkZyYCAAMbExDA5OZlPnz7lgQMHRE03kiLGKSoqio8ePRJM8/PzZZjWLbkkldxp3779B0ydnZ25bds2enp6kvyzIvi7d++4du1aXr9+nUeOHOGRI0cE0+PHj4tz79+/v2AqPdjS4P2l+/9z8XRycuLAgQPFc2lra8uVK1eKyX7o0KEMCgri2LFjGRAQwKioKC5YsID379/nvn37RHwTWWt7efv2LaOjo1lYWMgdO3Zw9+7dvHz5MtPT0wXPpUuXsqamRoZn586defPmTSYnJ4uE6B4eHty2bRu7dOlC8k973Zs3b7hu3TpRdy4zM1PYjzIzMwXPXr16CXWst7c3AYjF1Zfu/8/J1Nramj4+Ppw+fTqB2srgs2bNErFzgYGB7NOnD4cOHUo/Pz9OmDCBUVFRPHbsGNevX8/Tp0/z4cOHrKioYEZGBouKihgfH8+8vDxu3bqV6enpPHfuHHft2sXs7GweO3aM69atY2lpKd+9e8dVq1axpKSEISEhvHLlCletWsWEhAS+evWKAwYMYHp6ujAxSBNjeXk5t2zZwnPnznH79u1ct26dUEdKFegBsEOHDkIdK014JiYmf8n0s3S2vr6+OMGQkBCxmtDU1GSHDh3o5eXF2bNn886dO1y3bh0TEhKEfUW6GKk4HwDOnj2bLi4u3LJlC8naCgJz5syhgYEBt2/fLioLBAUFccqUKfT09GR1dbWM4VoaKDt16sTS0lLeunWL+/fvZ79+/bhlyxYC4IULF0TF4o0bN9LS0pLjxo2jvr4+w8LChH5aapJdQtJnDxgwoN5OchEREXR0dCQAUSA1KipKhumsWbN469Ytrl27lgkJCWJhUpfp77//Lpi6uroKplFRUZwzZw4NDQ2ZlpYmmIaEhHDKlCns3Lkzq6qqmJOT8wFTLy8vlpSU8ObNm9y/fz8DAwO5detWwVSaBDds2EBLS0tGRkZSX1+fQ4YMoamp6V8ylRYzX7r//9Ptxx9/pIODg8w1Tp06lRoaGmzfvj29vLw4Y8YMXrlyhStXrmR8fLxwIJD6qlu3bjxz5oy4Fzw8PLhlyxa+ffuWc+bMYXR0NM3NzZmWliYqRYSGhnLatGn08fFheXm5jAOYVGOua9euLC4u5vXr17l//34GBwczLS2NAHjx4kVRODklJYVWVlYcM2YMdXV1GRwcTGNj44/ylBagUjHnL93/n6P17t1b2MGlST0oKIiqqqp0d3enl5cXx48fz4yMDM6fP5+zZ88WjllSfw0YMIAHDx6kmZkZY2Nj2atXL27dupVPnjxhQkIC582bJzivW7eO1dXVjIiIYExMDIOCglhQUMDjx4+LRYxUKWbEiBG8d+8e8/LyuH//fk6YMIF79+5lq1atmJeXJ2x2q1evppOTE4OCgqipqckuXbrI2IUB8I84bPHsStqgT/XL34UQKMvJyY2Vk5P7RU5ObpicnNxfVi2QRFlZGYMHD4aKioqoLTRlyhT89NNP8PDwwLZt23Dz5k3MmDEDGhoaOHr0KFxdXREUFASS2LNnD3R0dGBhYYEmTZqgvLwcdnZ2wlX/+vXrKCsrQ2RkJN69ewcjIyOYmprCwsICDx48gIGBARYsWICoqCh8//33iImJwciRI3Hw4EHo6enh2LFjePDgAUpKSuDr64s+ffrA1tYWLVu2FHWYNm3ahFu3buHq1auYN28erl+/jnv37sHAwACKiorQ1tbGu3fvANTWM1NTU8PevXv/ne75r5SvvvoKoaGhUFFRwfr16wHUBgWHh4fD3d0dqampuHXrFmbNmgUNDQ0cO3YMbdu2RXBwsGCqq6sLCwsLqKmpfZRpeXk5fvrpJ9TU1MDQ0BBNmzaFubk5CgsLoauri+TkZMyZMwfff/+9qPogMc3OzkZhYSFKS0vh4+OD3r17w97eHi1btoSRkRHk5OSwefNmwXTu3Lm4ceMG7t+/L5hqaWl9wLS+JvO1trbGwIEDoaKigk2bNgGoDdofOXIk3NzcsG7dOty+fRuxsbHQ1NTEiRMn8M0332DQoEEgiV27dkFLSwvNmjWDjo4OysvLhdu+goICbty4gbKyMvzwww/Cdd/KygpmZmZ48OABtLW1sWTJEsTFxSEoKAhxcXEYMWIEDh48CF1dXZw4cQJFRUUoKyuDl5cXevbsCWdnZ7i6usLAwAANGjTAli1bcPPmTVy9ehU///wzbt26hcLCQujp6UFRURGampqC5/Xr16GqqooDBw58yW7/rGJiYgIvLy+oqKggMzMTQG1u1m7dusHOzg5TpkzBw4cPsWnTJmhoaCA/Px8DBw7E8OHDQRKpqanQ1NSEsbExtLS08OrVK5iZmcHAwAC6urooKChASUkJ/P39UVlZCWVlZXTs2BFqamq4e/cuFBUVsWnTJqxZswajRo1CYmIiQkNDceDAAairq+PSpUsoLi5GZWUlXF1d4evrCzs7O4SGhoo0crt378bFixdx7do1hIWFobCwEM+ePYOGhgbk5eXRpEkT1NTUAKgNVWncuLEIeP+U/F2C5nUAnAHkAfgOQMK/09l3797F6tWrUVlZifv372P8+PEwMTHBvXv3cOPGDXTv3h3Ozs548+YNIiMjERERgYEDB6KsrAxz587Fd999h2nTpuHYsWN4+fIlHj16BFNTUzg5OSE+Ph6mpqaIjY3FjBkzkJGRAV9fXwwaNAidO3dGy5YtoaioiA4dOoiM5Hv37oWcnByaN28Od3d3uLq6on379lBSUkJISAgAID8/HyShrq6O/fv3o127dmIiCwoKEoGRjx49QmJiIoqLi0UmheTkZJSVlSEiIgJDhgz5d7rov06GDRuGNWvWoLKyEnfu3EFkZCSMjY1x//593Lx5Ez179kTr1q1FNvPw8PAPmE6ZMgXHjh1DWVkZHj9+DBMTE8HUxMQEMTExmDVrFjIyMvDdd98hODgY3377LRwdHaGoqIhvvvkG/fr1g4GBAfbs2QM5OTlYWVnBzc1NMG3YsKFwfMnLywNJMVm1bdsW2traqKmpQUhICI4dOwaglmlCQgKeP38u4m0WLFiAsrIyhIeHIzQ09Iv1++eSMWPGiPyFeXl5GD16NAwNDVFYWIgbN24gMDAQTk5OePPmDaZMmYKRI0ciKCgIZWVliIuLg7+/PyIjI/Hbb7/h2bNnePz4MQwNDdGqVSvMnTsXhoaGiImJQXR0NDIzM0Xi82+++QYtWrSAnJwc2rZti549e0JXVxf79++HnJwcLCws4OLiAmdnZ3To0AFKSkqi5MrZs2dRVVWFJk2aYMeOHWjTpg20tLRAEsOHDxcJBp48eYLo6Gi8ePFC5ECdO3cuysvLMXLkSJkSLvVJkpKSkJGRgcrKSqSkpKBPnz7Q0tLC06dPUVBQgOnTp8PCwgLV1dVYvHgxunfvjv79++PVq1eIiYlB37590bt3b5w7dw43btzA48eP0aRJE7Rr1w4xMTFo1KgRfvrpJyxbtgxHjhxBq1at4O7uDmtraxgYGODNmzewsrJC27ZtoaqqihMnTkBOTg76+vqwtraGjY0N2rZtCyUlJfTs2RNA7SR89uxZyMnJYcaMGTAzM4OGhgZqamowd+5ckai5pKQEw4cPx8uXL0Wy9lGjRuHVq1fo0aMHvLy8Pt0xf7X9BZBX529FAL//O9tmAMJdVVtbW8RE6ejoUE5Ojjo6OuzXrx8BcMGCBfTx8eGiRYu4fPlyhoSE0MPDgwEBARw2bJiItdm9ezf79OnD/Px8AuDEiROFqiU7O5tOTk58/fq1ME4GBwczIiJC2NyGDBki8q3duHGD6enpTE5O5vXr10Uuyo0bN3Lnzp308fERRldzc3M2bdpURuVx+vRp+vv7MygoiDNmzBDbaMk4inqornyfqRRHpa2tLcNUTk6OSUlJ9PX1ZXJyMpctW/YBU8k2sGvXLvbp04eXL18mAOGAFBgYyKNHj9LJyYkVFRWCaVBQECMiIoTNbejQoYLp9evXuXPnzo8yTU9PZ5cuXWSYSqpnyeZ24sQJdu3alQMHDuS0adME03bt2tVL9db7PKU4Ny0tLcrLy1NXV5d9+vShoqIiExIS6OvrywULFnDx4sUMCQlh+/bt2atXLw4bNowaGhoEwLS0NPbp00eYGaRiqv369WNmZiadnJz47NkzArXxXAMGDGB4eLjgOWzYMBYUFJCsDQfZtWsXly5dyuvXr4v4uA0bNnDbtm309vYWKmUzMzOhupJsbgcPHqSPjw/79esn49hWJwToizP4HEylODZNTU1hs1JVVaWioiINDAzYrVs3amtrc8aMGfTz82NUVBRjY2MZEhJCb29v9uvXj2FhYaIfly1bxj59+nDnzp0EwBEjRlBFRYUBAQFcuXIlW7VqxaNHjwqm0jPu6+vLkpISRkREMCcnh2/evGFubi4zMjJEfuHMzEyWlpYyJSWFq1atYqdOnWhubk6gNrxMCjGTVNBJSUl0dXVlp06dOHDgQMFUCkX6ZL/8Taf9/lf//1STgnrft3cAYKNGjcQgIlUS7ty5M3v37s0pU6ZwyJAhLCsro4WFBZ89eyZ06EuXLuWkSZN48uRJTpw4UTygw4YN+yBoUZpQpcDy6dOn88iRI0xOTmavXr3YsWNHZmRkcOfOnSRrg7rfvHkjvAfbtWvHRo0asXXr1vT09GT37t0JgPr6+lRUVGSTJk2ooKBAOTk5Uf1aan/E49S7SU7q408xnTp1KgFw3rx5gmmvXr04efJkhoaG8sWLF7S0tOTjx48F08WLF3PixInMzs7mhAkTBNOwsLCPxR5SR0dHDFLTp09nVlYWk5OT2adPH3p6en7A9PXr17Szs2NoaCjd3d3ZqFEjtmrVip6enuzWrZsM08aNGwumkyZNkvldJyenTz5A/61NihuTjPbv85QmhpiYGAK1XpMBAQGcOHEiQ0NDWVRURCsrKxYUFLBXr16Ul5fnwoULOW7cOB46dIgRERGC56BBgz6IaZImV1dXVyooKHDatGk8dOgQk5OTGRgYSF9fX2ZmZgovvszMTJaXl9Pe3p4hISF0dXWliooKHR0d2b59e+EopKen9wHPiIgImd91dHSsdzxJQpr0DQwMPuhrFRUVDhw4kHJycgwPD6eCggI7dOhAf39/jhw5koGBgczKyqK9vT0zMzPp7+9PTU1NTp8+ncOGDePKlSsZGhoqFjT+/v4ysXVSU1NTo6OjIzU1NTl58mSxUAkPD2dYWBiPHj0qPGszMzN5+/Zturu7s1+/fnRwcKCSkhItLS3p4OAgnnVNTU0qKChQWVmZ8vLylJOTE05iUrOysvok07/sNADvIOtR+Rb/hndlw4YNCUDG3VxBQYEXLlyg9J60QgZq3VmtrKzErk1q0krw75q0qwMgs7NydXVlREQEw8LCOHbsWK5cuVJ4UaakpIhA0WPHjtHc3Jzjx4+nmZlZ3R0Zu3fvTisrK5nB3c3NjT/++KP4v7u7O0eMGFH3muvdJCeFcQwaNEiG6blz5/5XTN8fcD7Vxo8fL/6uu7NydXXl2LFjGRYWxoiICBmmGzZsEM4uR48epbm5OceNG0czMzOZc+vWrRutrKxkBng3NzeOGjVK5v/Dhg0TTL90//+nm7RirrsiVlBQ4LFjx6ikpCT6QHqvc+fOH+U5evTof4tneHi4+LvuzsrZ2Znh4eEcNmwYIyMjuWrVKsFz48aNgufhw4dpaWnJsWPH0sTERObcfH19aWFhIeN04uzszLCwMPF/FxcXMR79kbHoizP4TzcpsLuuy7+ioiIXL14smEq7HulZatq0qdj9SU46708gn2rSYvX9+8jBwYHDhg3jyJEjOX36dK5fv15MbNu3b+fx48f57Nkzpqen08nJiaGhoTQ0NKSdnZ3M82dkZCSTXMLW1lYsToFaz27Js/2PqiIf7ZfP0tmS94s0WUgPlNTmzJnDjRs3cujQoQTAxo0bU1tbW2RHqDtZ1Y1bkkBJbqTOzs5ChSh5FQG1kfjGxsbs16+fcCMnSX19fZ48eZIRERFcunQpz507R3t7eykVFwFQQ0ODY8eOFb81b948cf4KCgrs2LEj5eTkGBsbS6DW06dp06Y0NjYWO776OMlJKkaJqaTClVpUVBRTUlJEbKTEtO6CQZqsPsZUYt+6dWuhQqzLdPLkyYKpNAiSpJGREU+ePMnIyEguW7aMZ8+epb29vXCflpiOGTNG/FZcXJwM0w4dOlBOTo7R0dHiNYmp9FB96f7/XDwlbcf7nsPTpk3jypUrhSdt48aNqaWlJY4H/lxcSs87gA8WPE5OToKn9C8Ajhs3jsbGxuzbt6/YrZGkhYUFT506xYkTJ3LFihU8ffo0nZycOGXKFPFZNTU1jhgxQvzW7Nmzxf2ooKBADw8PysnJiTFEQUGBpqamNDQ0FBPAl+7/z9GkBYi0azY0NJRhGhoaykmTJok+UFFRoZqamvCyrTtZ1WUqZaCSJsi6C8S6C8XAwECamJgwICCAGzZsIFkb++bt7c0zZ85w7ty5XL9+PbOystihQweZ2MtGjRqxR48eIjPSkCFDxI5UXl6eDg4OlJOTEwsVBQUF6uvry2h3PtUvn6WzpROX1D51Z2MJgK6urlBn9O/fnwsWLBDHWFpaUlFRUWbXIB37sSbFw0hbaRMTEw4bNowHDhzgwoULRTArST58+JAkuWLFio9utyXgkh1RGgyGDBlCMzMzDhgwgBYWFnRwcBCTNFBrr0tLS6OKikq9nOSk65RW4X/HtF+/fkxMTBTHWFhYUFFRUYSU/B3TgICAjzLNzMwUTMPDw2WYLl++XGY1+D5TyY4oMQ0NDaWZmRkDAwNpbm5OBwcHGe2DtbU1t2zZQhUVlU8+QP+tTbpGaWddl6cUKlKXZ+/evRkXFyeOMTc3p6Kiogg/AP60B32sSYsFKaWUqakphw4dyr1793LhwoUMDg5mZGQkSQo76/Lly2V2HlKTbKtS4Lk0uA8cOJAmJibs06cPzc3N2aJFC5lgdysrK65fv57Kysr1jmddphITKZhaupeBWpur1F+dOnWS0V4YGxtTUVGRXl5e4rX3d+51m7SAlcxTZmZmDAkJ4caNG7lw4UKOHj2as2fPJllrY62oqOCSJUtEjGrdJi06JbOIsrKyGIf19PTo6elJAwODD4LdTU1NOW3aNCopKX2S6WfpbCmRa/v27T/IkAH8qYqaMmWK2JVJM3jdwa9Dhw5UV1cXKwnJ3iOt8Nu1ayezOuzTpw9DQ0N58OBBZmRkcNasWbx58yZJirgpsjauSllZmU2aNBET8fbt2wn8GQMmnYOCgoKMquuvWp3sHfVukpMchTw8PGQWH1KTVMuTJ08Wu7KPMW3fvr0MUylbhfQQuru7yzDt3bs3Q0NDeeDAAe7bt4+zZs3ijRs3Psq0UaNGbNKkiZiIpfel1WldpnV3JH/VOnbsKP3GF2fwn2zSIqJdu3YyqiapSavsyMhIcf9/jGe7du2opqYmeEZFRYkJBahViUlODEDt4iU4OJh79uzh7t27OWvWLJHfUOJVXV1NHx8fqqqqUlVVVUzEUtIBSZ1WV832sYHzrwbmL93/n6NJY6mTk9MHWU+k8VGaBKWFaV2m0oTm4ODAJk2aiPckta+0a7Ozs5PZwUl5K1etWsX169dz5syZPHPmDF+9eiWSRty/f5+9evWiqakptbS0ZGIzgT8XLNKEKS8vLxYzf9ekRdmn+uXvQgj+P8mLFy+gq6uLESNGYM2aNeL11q1bIyAgQJQvnzNnjnAHlcrvNGjQAGVlZQgMDISKigpKS0vx5s0bAMCvv/6Kdu3awcHBAQBw/Phx3Lx5E/r6+jA2NsbDhw9x7949NGnSBPv378f06dPRrl07REdH4/fffxchBa1bt0ZVVRUUFRURGxuLRo0aCVfV9evXw9bWFgoKClBQUMC7d+/w4MEDAMCsWbI1YlVVVdG4cWN4enoCALp27YqIiIjP0aVfxhB9HQAAG1pJREFUXFJTU6Grq4vhw4dj7dq14vVWrVqhR48egmlMTIxgKpXfkZj269fvA6Z79uyBu7u7YHrixAncunULenp6MDY2xqNHj3Dv3j00btwYBw8exPTp09GhQwcZppLrupSLce7cuWjUqBEuX74MoLbsk42NjQzTwsJCAMCMGTNkrlNi2rFjRwDAd999J1M3sL7Ijh07oKOjg8GDB+N//ud/xOtOTk7w9/cXPBMSEqCpqQkAIjxG4tmrVy+oqKigrKxM8Ny/fz9cXV1FiZbTp0/j1q1b0NXVhZGREZ48eYKioiI0adIER48exfTp0+Hj44OYmBhcvHgRAwcORLNmzWBvb4/y8nIoKCggMTERKioqyM/PBwBRVLkuz6KiIgDA5MmTZa5TVVUVjRo1goeHBwDZUl/1TY4ePQotLS107doV+/btE6/b2NjAw8NDMN20aRMaN24MACLHb4MGDfDq1St4enqiYcOGePnyJd6+fQuglmGLFi1gbm4OoLbAcGFhITQ0NKCvr4+Kigq8fPkSampquHTpEqZOnYpx48ZhyZIluHLlCsLCwuDj4wNtbW3cv38f7969w6ZNm6CkpIS7d+8CAA4dOgQTExPIy8tDQUEBNTU1ePr0KQAgKChI5jobNWoEZWVlODo6AqgtBxUQEPDJfvkskxxQm/jzwIEDUsJi/Pjjj3jx4gV27NiBuXPnioFwx44dAGpjzbp37y4elsOHD0NXVxeenp5YsGABAKCqqgrHjx/HixcvoKCggAkTJgAAHj9+jE6dOsHU1BStWrVCZmYm1q1bh71792Lo0KHo1asXampqUF1djQ4dOoiqxSUlJTA0NERFRQWmT5+OwMBAAEBNTQ3U1dXF5PXy5UsA+KBycnl5OdTV1dGkSRO0atUKT548QWJi4ufq0i8u7dq1w6FDh5CcnAygNk7l+fPnSE9Px7x58wTT9PR0AMAvv/yCbt26CaZHjhyBjo4OOnbsKPrp9evXOHHihGA6btw4kMSTJ0/w7bffCqYHDx7EunXr8Ouvv2Lw4MHo2bMnampqUFVVhW+++QZxcXEYM2YMSkpKYGBggIqKCsycOVMwfffuHdTV1dG+fXsAf81UTU0NjRs3hpOTE548eSLuv/ombdu2RVZWFubPnw+gNhaypKQEu3fvxoIFCwTPX3/9FQCwbNkydO3aVfDMzs6GtrY2PDw8EBMTA6D2GT19+rTgOWbMGADA06dP4enpKeJdjx49io0bN+LXX39FUFAQ/P398ebNG7x69Qpubm6YN28eRowYgZKSEujr66OyshIxMTGiYCZZG9MqTV6vXr0CAJlCn8CfPJs0aQJHR0c8e/ZMjEn1Uezt7fH777+LhVlAQADKy8vx22+/YcuWLWLBIsUUpqeno127doLpxYsXoa6uDkdHRwwfPhwAUF1djcuXL+Ply5eQl5dH7969QRIlJSVwc3ODqakpWrRogby8PBw+fBjp6enw8vJCmzZtUFZWhqdPn8LMzAzLly9HQEAASktLoaWlhdevXyMlJUWMsyTRuHFjfP311wBq7yUAuHDhgsw1ShXglZSUYGVlhZKSEjGPfFQ+x7YZqHX3ljxfJBWBFG8zcuRIYQ8LCQnhtWvXuGfPnk9uR9+3nRkbG7Nx48Ziyz106FDq6elx1KhRoo7VnTt3OHToUDo7O9PPz08c26NHD/E9kyZNooODg1BR1m2SHSc5OVmoX+qGKnzM9gPUuqSjHqorJaaSGkRiGh8fTx8fH44YMUJwCgoK4pUrV7hr165/m6mRkREbN24sVA9Dhgyhvr4+R40axRYtWlBVVZW3b99mWFjYB0zrOPxwwoQJtLe3/6gKTmK6cOFCwbRuqMLHbLQS0y/d/5+Lp2SnlIz3c+bMoZeXF4cOHSpUyIGBgTx37pxIf/exVtdJCKh1emjcuLGwqQ0aNIiGhoYcOXIkHR0dqaOjwxs3bnD48OF0c3OT4Vm3NmFERARbtGjxUY8/SZ0lJdy2tLSUCVV4/5ykpqenV+94Sky1tbWFKl56loYPH05XV1d269ZNOOhI5a0k9fLH2vvOSDo6OlRWVhb2sx49etDCwoLDhg1jhw4d6OjoyPPnzzMiIoK+vr7s3r274FHX5NOvXz+am5vLJPOWnNGk75a8do2MjGTMF++fk9S0tLQ+yfSz7OSaNWuGjh07Ql6+9uul6rSbNm3Cvn37oKioiJKSEgCAjo4ObGxs4OTkBF9fX8ycORMAYGRkhHnz5gGozaAyZMgQ2Nvbw9PTE4WFhaJas6enJ/Ly8hAUFAR3d3eEhoYiLy8PCgoKqK6uxrlz5/Drr7+KVUF6ejrmz58PDw8PtGnTBj4+Pjh48CAUFBTQrVs3ALUpyHJzcwEAo0ePBgD07t0b5eXlAABtbW3o6+uL65KuUapuXR9l7dq1+Oabb6CgoAAAIh3X5s2bkZGRAQUFBRmmdnZ2cHJygo+PD6ZPnw6glqlU4uPu3bsIDQ2Fvb09OnbsiKKiIhmmly5dwvfffw83NzcMGjQIFy9e/CTTnTt3Ij4+Hh4eHnB2doavry8OHz4MBQUF+Pv7A6hVY0lMpd1Fr169BFMtLS0YGBjA2tpaXHN9Zrp06VK0a9dOPKMSz61bt+LAgQOQl5dHaWkpgNr73dnZGV9//TW8vLwwadIkAIChoSGioqIA1FaODgoKgp2dHTw8PPDw4UO0bNkSANC+fXtcvXoV/fv3h5ubGwYOHIgTJ05AQUEBr1+/xqlTp/Drr7+isrISQK0KOyoqCm5ubmjZsiU6d+6MI0eOQEFBQZTniYyMFOro8ePHAwC6desmduiamprQ1dWFlZWVuGYrKytRsbw+SmRkpFATA7XPG1C7uz19+rQogQPU9s/gwYNhYWEBZ2dnoRLU0dERpZWePHkCHx8fmJubw8nJCc+ePZOpNP7o0SN4e3vj66+/hq+vL1asWAF5eXlUVFRg37592LlzJ168eAGgduc4bNgw2Nvbo3nz5mjTpg0uXLgAeXl5uLm5gSQCAwNRUFAAAEJb9M0334jnXE1NDVpaWjAxMRHXaGpqCkNDQ3HvfFQ+14oCqDV0mpmZMSIigu3atRO7qD88EBkSEsJu3brx9OnTVFBQEMbIVq1aiRl9+PDhBP50VqkbH6Ovr8+EhARxrOS+TtYWXpSOk1zH16xZI16TDNXW1taMiIiggYGBCOxWUlKimpqaOB9/f3927dqVWlpaVFZWlikPA9SWZJFWjb179663Oznp+szMzBgeHk53d3exi5KYBgUF0d/fnydOnKCioqJYgTs5OQlOkiFbclZ5n2l8fPxHmdb1BJOYrlq1SrwmZXiwtrbm2LFjaWBgIByLJKbS+fj5+dHX1/eTTKOjowXTXr16fXKV+N/apOvs0aMHTU1NOXLkSLq5uYldlMRTCsw+dOgQFRUVhfOCo6OjYCQ5IknOKnU1Hnp6eoyOjharcckjmaRMrKnEc9GiReI16XusrKw4atQo6unpCSeUhg0bUlVVVXhW+/j40Nvbm5qamlRSUpIJRwJqQ5Kkc+jWrVu941mXqaenJw0NDdm7d2/a29sLrYvE1MfHhx4eHkxOTqaCgoLYUVlbW/P9WDupHE9dLYempibDw8Npb29PDQ0NMdaWl5czIiJCeERLIR51452l75FCDTQ1NUX2qwYNGrBRo0bC2cvNzY0uLi5UVVVlw4YNP0goEBoaKuKX3d3dP8n0s3Z2YWEhNTQ0qK6uLjPpSB1lY2NDRUVFenp6yrgiA3+6jkdFRYmJrs4kItrAgQOZlJTE33//XcRVpKamkrUnQhUVFTGISv96eHjQ09OTVlZWtLOzY4sWLQQQyUNJAm1iYiKCTJWUlOjt7S3jLSbdQFLIwR+t3k5yd+/epYaGBjU0NEQA/KeYvq9ikphKVail16WBSmoDBgxgYmIiz58/L2J9Nm/eLMNUWqR8jKmtra0M07oDno+PD42NjWWYenl5fZSppMr7Y1D+4gw+B8/8/Hyqq6tTQ0NDJiRG4mltbU1FRUW2b9/+g2dP4jl16lQZL+q66mNpopQqjUjqMqmGGFDrLi5NaNK/bm5u9PDwoKWlJW1sbGhra/vRpAOdO3emkZGRuE+UlJTo6ekpE5sr3SN11WNfuv8/J9PNmzdTXV2d6urqH7DQ0NCgubk5GzRoQCcnJ9EnUlyc5LEaGhoqamfWfSakFhAQwJkzZ3LPnj10dnamuro6V69ezVevXgkO0oQm/Wtvb09HR0caGxvT1NRUnAcAmVg9Z2dn6ujoiBCIhg0bsnXr1jJxf5IavK654VP98lnUlVKS29atW6Nly5YoLS3F06dP4eHhAU9PTwwaNAgvXrzAtWvX8PbtW2RlZQnDJ1DrPVNSUgJnZ2dMmzZNRoUkbX8tLCxgb28POzs7lJWVITU1Fb169QJJvHjxQngSVVZW4tSpU7C1tcWpU6ego6OD3377DVlZWVBWVsaiRYvg7OyM6upqALKG6/z8fKipqcHOzg6zZ8+Gubk5MjMzoaGhIY756quvgNoexqBBgz5Hd/4/IZLXmqurK1q2bImSkhLBtGPHjggJCfm3mU6fPl2G6fPnzwHIMi0vL8eWLVs+yfT06dOwsbHBqVOnoK2tLZgqKSnhl19+QevWrQVTKREzUFtdQFVVFV999RVmzpwJc3NzHDhwQIappJIhKZI91zeJjIwEAHTs2BFOTk4oKSnBs2fP4O7ujvbt22PAgAF48eIFrl+/jrdv3+LYsWMf5dm6dWv8/PPPsLCwEO9Jamtzc3MZntu3b4e/vz9Iori4WPCsqqrCuXPnYG1tjXPnzkFbWxunTp3Cb7/9BiUlJcTHx6Nly5aCp+Q0AfxZXcDW1haTJ0+GqakpsrKyZHhK91pNTY1wRKqP0r9/fwC16vjmzZujtLQUpaWlcHJyQqtWreDr64uSkhIUFBTgzZs3uHjxovCgrKmpgYqKiqgmsWbNGqHuBP501DIwMICVlRUsLS3x+vVrUUn+4cOHKCwsFF6br1+/xtWrV2FmZoarV6+KKgQ5OTlo0KABRo0ahebNm4t7SjIlAH9WFzA1NUVwcDD09fVx/vx5qKqqimNMTU3F33+ZnBn4vDs5oNbAuWrVKk6aNIn6+vpiBt6+fbsIyh07dix37twpk/JJXl6eYWFhVFRUZExMDG1tbamlpSWzmujYsSM9PDzELvH27dsE/lRbxcfHMygoSCbmRzJoSmoZNzc3duvWTZxX3d9JT08n8Ge6m/dXM2pqamIHYGZmJmI8UI93cvhj9bxixQpOmDBBhunWrVsF0/DwcG7fvp1jx46VYTpkyBAqKipyzpw5/xbTmzdvyqzw4+LiOHDgQMExIiJCqDElFYubmxv9/f3FednY2IjfkeIh/7dMv3T/f06enp6eTE5OZkREBPX19YVDR0pKiuA5cuRIbty4UUZlrKCgwODgYCoqKnLGjBm0tramFCMrtfbt27N9+/bic1KCdWkFHhUVxX79+gmtwKhRo0Q6NakmmrOzM319fcV51f2dDRs2yPCsq/rGHzsTaVdnampab3m+z9TZ2Znjxo1jYGAgdXR0hKp21qxZIh6uV69enDVrlswOXVFRkb6+vmzYsCGHDBnCpk2bfpC0QUqSLKmbDx8+TOBPZ7ywsDB26tRJmKd69eolkgFIY7OtrS3d3NwopQts2rSpSBQgZSuSmL6fEKBx48ZiV6evry8Cxz/ZL5+js5s0acKRI0dSQ0ODfn5+tLa2prGxscyAIulXCwoKOHDgQA4aNEgEBk6ePJlaWlp0dnYW22lTU1M6OTlRXV2dmpqaDAwMpIGBAVVUVHjgwAHa29vTyMiIGhoa1NHREXnOpI6SmpTCS1VVVQx8db136rYePXoIW4HUFixYQD09PbEFl1Qnki67vk5y0sSjoaHBrl27CqZ1VUcS01u3bnHAgAEMCQkRds5JkyZRS0tLJL2WmDo6Ogqm/fr1o4GBARs1asTMzEwZptra2rS1taW/v/8HTKWHoi7TuurHuq179+4fME1MTKSenp6wwUneaXWZfun+/083d3d3hoWFUUNDgz4+PrSysqKxsbHMJCF55+Xl5bF///4cMGCAsI1HRERQS0uLTk5OwoZibGxMe3t7of7s1asXDQwMqKamxr1799LBwYHGxsbU0NCglpYWra2t6evr+wFPyY6qqqoqJrP3UwNKrWvXrh/wjI2Npa6urvAOla6pbuLiL93/n6M5ODgwICCAGhoadHd3p5mZGfX19WVUgdK4lZKSQi8vL/r4+AhTUWBgIDU0NGhtbS0lmqeenh6trKzYpEkTqqqqsmPHjjQ0NKSZmRk3btxINzc3mpubU0NDg2pqamzatCnd3d1lmMrJyYnMM40bNxaT5ntjpmju7u5CNS01aeyRvCulBU/drC6f6pfPoq58+fIlnj17BldXV5SXl6NRo0YoLCzEo0ePAADLly/HxYsX0blzZ0RFRUFFRQVr167F+fPnAdQGFD9//hwTJkyAg4MDAgMD4e3tjeDgYDRr1gwvXrzAu3fvoKCggMrKSmhoaGD8+PHo3r27ULs4OzvjypUrePfuHXR1dQEA+vr6SE9PR2hoKLy9vYXXjrOzM1q1avXBdTx69Ag9evSAjY0NdHR0ANSqvp48eQJnZ2cAtQViAUBFReVzdOX/M/Lbb7/h6dOncHFxwcuXLwXTx48fA6j11pOY/vzzz6Jg7sWLFwEAsbGxeP78OcaNGyeYdu7cGUFBQTA3N8eLFy9QU1MDBQUFVFRUQENDA5GRkejWrRtKSkpQXFyMli1bIj8//wOmu3btEvUE6zJ1cnL64DoePXqE7t27w9ra+gOm0j2gpKQEoH4zPXHihHhOXr58icaNG4sClUBtPb2cnBx4enoiPj4eysrK2LBhA3JycgAAiYmJeP78OcLDw/HVV1+hT58++PbbbxEYGAhTU1OUlJQInmVlZVBVVcWoUaPg4+ODkpISPH/+HE5OTrh27RrevXsnWOjp6WHv3r0YMGAAOnbsKHi2bt1aBP/WlcePH+O7776DlZUVtLW1xbU9ffpU8Jd4Ss9qfZXc3FyUlJTAxsYGFRUVUFFRwePHj4X6ODIyElevXoWzszM2btwIJSUlZGRk4M6dOwBqvd9LSkrQt29fNG3aFJ6enmjVqhU6deoEfX19lJeXo6amBnJycrh37x7k5eXh5eUFR0dHlJSUoKysDM2bN8fdu3fx7t07oTLW0NDAyZMn0aVLFxm1s42NjYzZQpKSkhK4u7vD1NQU6urqAGprQ5aUlAgv4AYNGgD4k+1fyudYUQDgpk2baGpqShcXF5GHEKj1xJJURlKrG9fUoUMHGhoaitW0tPqq61nj7u7OoUOHcubMmdTS0hLb2VWrVvHu3bs0NTVlw4YNxc5RWqlIxzVu3JitWrUShvOmTZsKNcagQYNkEjZ369aNgwYN4p49exgYGCi21JKnUlhYGH19fZmSklLv1ZUbNmygqampqBsl9VFISIhI31OX6YABAwjUqqwMDAzEivqPWEIZpm5ubgwNDeX06dOppaUlVmorVqzg7du3P2AqObXUZerk5CSY1lU1hoSEyCRs9vPzY3BwMHft2vVRpkOGDKGPjw/XrVtXb9VbALh69WqamJiwdevWMtndBwwYwJSUFBmeLVq0YN3UbgYGBsL5R+JZd8fg6urK4OBgTp48mdra2oJncnIy8/LyaGJiwoYNG4rnXFKZScdJMZMSz7qqxsDAQJlySL6+vgwMDGRqair79OnzAc/g4GB27tyZy5cvF6996f7/XEynTZtGIyMj2tnZiR221EezZs2SSeNlZWUlVMJOTk7U0dERz5OOjo44pu494Ovry9DQUBnNR2RkJDds2EB9fX02bNhQfIeksZFUkioqKrS2thZ8JE0cUOvkVTde2c3Njd7e3oyKiqKnp6dQm0uqSV9fX7q4uHDixIlfRl3ZuHFjMRjVDZq2t7dn06ZNaWdnJ6PmUlBQEIl762a6rpsctO73ODg40MDAgNOnT2enTp14/Phx6ujo0NLSkqtWrfogULtPnz4ysFq3bi0850aPHk19fX1qa2vzwIEDfPz4MZWUlGhmZkZLS0vxIEvqkrqDJVCrLqkbdPqHh1q9m+RcXFwE07ruxBJTW1tbmXyQioqK4qb9FNP3v0dfX59Tp06lp6cnjx07Rh0dHVpYWHw08XKvXr1kmLZq1Uo8sD/++KNgun//fhYVFQmmFhYWwi4gMZXU5HUHhLpM62OpHWdnZ7HoqMuhRYsWNDMzEzaTujylxaLEwtLSUoZn3T5r0aIF9fX1OXHiRHbs2JH79++ntrY2zc3NmZyc/EHgfY8ePWRUzHU9/4YPH049PT1qaWkxPT2dN27coJKSkvDQk+y1kudm3VI+0gBa914JCgqqdzzJ2npy0kJDmlik587Q0FAkIZdeb9iwoXhmpL43NTWVYVpXTWxhYUFtbW0GBwfT2dmZSUlJ1NDQoImJCSMjIz9QKXfo0EGmRJmNjY1g1atXL2ppaVFdXZ1xcXHcsmULGzZsSH19fRobG4v7Q7K9vZ/cwc3NTSYw3MvL65NMP0tnA7UxD4sXLxYTz61bt2ROUmp1dwCenp5iVpaav78/AcjsHOq29zu2a9eujIiI4ObNm9m1a1f6+voyODiYXl5eTE9PF84JycnJJMlWrVoJx5T3y8fUdT2OjIxkkyZNhE1oxYoV4jhdXV0xAfwBsd5NchLT5ORkWlpacvny5bx+/fpHmdTNjPExppLTT93sM3/F1NfXl2PHjuWGDRvo6+tLX19fDhw4kJ06dWJaWpoI31iwYIFgKhnF38+QIDH19PRkREQEmzRpQj8/PyooKHDZsmUyTKWFmLOz8ycfoP/WJg1yUpzpwoULRUXv99u6devE3x4eHh/w9PHxoZycnIzLed32/nPl7e3NUaNGceXKlfT29qa3tzf79+/Pjh07ClsRUJu8myQdHR1FGNH7RXulQbNDhw4cNWoUmzRpQh8fHyoqKspUNtHV1RXs62MRXImpsrIyR48eTWNjY44dO5arV6/+KJO6xZ4dHR0/sGu6ublRXl7+k4nMpclHylQiaewmTJhAZ2dnuri4sFOnTnRycuLUqVMFp5EjR/LWrVu0srJi9+7dqaCg8EGRV2k37+TkxF69erFx48Z0c3NjgwYNZMrz1NXiWVtbf5Kp3B+d8x8VOTm5pwDu/se/+L9HmpLU/dIn8Y/8I//IP/L/7/JZJrl/5B/5R/6Rf+Qf+X9BPlsVgn/kH/lH/pF/5B/50vLPJPeP/CP/yD/yj9Rb+WeS+0f+kX/kH/lH6q38M8n9I//IP/KP/CP1Vv6Z5P6Rf+Qf+Uf+kXor/z9fJNJVmdeXCgAAAABJRU5ErkJggg==\n",
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\n",
       "text/plain": [
-       "<Figure size 576x288 with 9 Axes>"
+       "<Figure size 800x400 with 9 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 40: 100%|██████████| 63/63 [00:48<00:00,  1.31it/s, loss=0.046] \n",
-      "Epoch 41: 100%|██████████| 63/63 [00:52<00:00,  1.21it/s, loss=0.0464]\n",
-      "Epoch 42: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.046] \n",
-      "Epoch 43: 100%|██████████| 63/63 [00:51<00:00,  1.22it/s, loss=0.0457]\n",
-      "Epoch 44: 100%|██████████| 63/63 [00:52<00:00,  1.19it/s, loss=0.0461]\n",
-      "Epoch 45: 100%|██████████| 63/63 [00:50<00:00,  1.24it/s, loss=0.045] \n",
-      "Epoch 46: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.045] \n",
-      "Epoch 47: 100%|██████████| 63/63 [00:52<00:00,  1.20it/s, loss=0.0453]\n",
-      "Epoch 48: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0452]\n",
-      "Epoch 49: 100%|██████████| 63/63 [00:52<00:00,  1.21it/s, loss=0.0459]\n",
-      "Epoch 49 - Validation set: 100%|██████████| 63/63 [00:18<00:00,  3.41it/s, val_loss=0.0452]\n",
-      "Epoch 49 - Sampling from DDPMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 147.48it/s]\n",
-      "Epoch 49 - Sampling from DDIMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 153.81it/s]\n",
-      "Epoch 49 - Sampling from DDIMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 155.44it/s]\n",
-      "Epoch 49 - Sampling from DDIMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 152.03it/s]\n",
-      "Epoch 49 - Sampling from DDIMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 154.95it/s]\n",
-      "Epoch 49 - Sampling from PNDMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 151.98it/s]\n",
-      "Epoch 49 - Sampling from PNDMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 154.47it/s]\n",
-      "Epoch 49 - Sampling from PNDMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 153.99it/s]\n",
-      "Epoch 49 - Sampling from PNDMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 156.32it/s]\n"
+      "Epoch 40: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.70it/s, loss=0.0473]\n",
+      "Epoch 41: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0479]\n",
+      "Epoch 42: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0471]\n",
+      "Epoch 43: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0467]\n",
+      "Epoch 44: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0476]\n",
+      "Epoch 45: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0462]\n",
+      "Epoch 46: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0464]\n",
+      "Epoch 47: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0465]\n",
+      "Epoch 48: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0464]\n",
+      "Epoch 49: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0467]\n",
+      "Epoch 49 - Validation set: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:11<00:00,  5.59it/s, val_loss=0.0459]\n",
+      "Epoch 49 - Sampling from DDPMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.69it/s]\n",
+      "Epoch 49 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 70.73it/s]\n",
+      "Epoch 49 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 69.73it/s]\n",
+      "Epoch 49 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 69.56it/s]\n",
+      "Epoch 49 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 68.71it/s]\n",
+      "Epoch 49 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 71.26it/s]\n",
+      "Epoch 49 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:06<00:00, 71.54it/s]\n",
+      "Epoch 49 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 69.39it/s]\n",
+      "Epoch 49 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 70.36it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 576x288 with 9 Axes>"
+       "<Figure size 800x400 with 9 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 50: 100%|██████████| 63/63 [00:49<00:00,  1.28it/s, loss=0.0441]\n",
-      "Epoch 51: 100%|██████████| 63/63 [00:52<00:00,  1.21it/s, loss=0.0455]\n",
-      "Epoch 52: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0439]\n",
-      "Epoch 53: 100%|██████████| 63/63 [00:51<00:00,  1.22it/s, loss=0.0458]\n",
-      "Epoch 54: 100%|██████████| 63/63 [00:53<00:00,  1.19it/s, loss=0.0451]\n",
-      "Epoch 55: 100%|██████████| 63/63 [00:52<00:00,  1.19it/s, loss=0.0443]\n",
-      "Epoch 56: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0451]\n",
-      "Epoch 57: 100%|██████████| 63/63 [00:53<00:00,  1.17it/s, loss=0.0446]\n",
-      "Epoch 58: 100%|██████████| 63/63 [00:52<00:00,  1.21it/s, loss=0.0439]\n",
-      "Epoch 59: 100%|██████████| 63/63 [00:51<00:00,  1.21it/s, loss=0.0454]\n",
-      "Epoch 59 - Validation set: 100%|██████████| 63/63 [00:16<00:00,  3.89it/s, val_loss=0.0437]\n",
-      "Epoch 59 - Sampling from DDPMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 145.94it/s]\n",
-      "Epoch 59 - Sampling from DDIMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 152.43it/s]\n",
-      "Epoch 59 - Sampling from DDIMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 151.33it/s]\n",
-      "Epoch 59 - Sampling from DDIMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 152.30it/s]\n",
-      "Epoch 59 - Sampling from DDIMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 150.82it/s]\n",
-      "Epoch 59 - Sampling from PNDMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 152.86it/s]\n",
-      "Epoch 59 - Sampling from PNDMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 153.71it/s]\n",
-      "Epoch 59 - Sampling from PNDMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 153.79it/s]\n",
-      "Epoch 59 - Sampling from PNDMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 148.56it/s]\n"
+      "Epoch 50: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.70it/s, loss=0.0453]\n",
+      "Epoch 51: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0468]\n",
+      "Epoch 52: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0452]\n",
+      "Epoch 53: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0466]\n",
+      "Epoch 54: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0462]\n",
+      "Epoch 55: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0457]\n",
+      "Epoch 56: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0461]\n",
+      "Epoch 57: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0459]\n",
+      "Epoch 58: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0449]\n",
+      "Epoch 59: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0466]\n",
+      "Epoch 59 - Validation set: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:11<00:00,  5.60it/s, val_loss=0.0449]\n",
+      "Epoch 59 - Sampling from DDPMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 70.89it/s]\n",
+      "Epoch 59 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 71.56it/s]\n",
+      "Epoch 59 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 71.16it/s]\n",
+      "Epoch 59 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 70.43it/s]\n",
+      "Epoch 59 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 70.59it/s]\n",
+      "Epoch 59 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 71.23it/s]\n",
+      "Epoch 59 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 69.66it/s]\n",
+      "Epoch 59 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 68.86it/s]\n",
+      "Epoch 59 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 68.66it/s]\n"
      ]
     },
     {
      "data": {
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\n",
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\n",
       "text/plain": [
-       "<Figure size 576x288 with 9 Axes>"
+       "<Figure size 800x400 with 9 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 60: 100%|██████████| 63/63 [00:49<00:00,  1.29it/s, loss=0.044] \n",
-      "Epoch 61: 100%|██████████| 63/63 [00:51<00:00,  1.23it/s, loss=0.0434]\n",
-      "Epoch 62: 100%|██████████| 63/63 [00:53<00:00,  1.17it/s, loss=0.0449]\n",
-      "Epoch 63: 100%|██████████| 63/63 [00:54<00:00,  1.16it/s, loss=0.0443]\n",
-      "Epoch 64: 100%|██████████| 63/63 [00:52<00:00,  1.19it/s, loss=0.0444]\n",
-      "Epoch 65: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0431]\n",
-      "Epoch 66: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0433]\n",
-      "Epoch 67: 100%|██████████| 63/63 [00:52<00:00,  1.20it/s, loss=0.0435]\n",
-      "Epoch 68: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0441]\n",
-      "Epoch 69: 100%|██████████| 63/63 [00:53<00:00,  1.19it/s, loss=0.044] \n",
-      "Epoch 69 - Validation set: 100%|██████████| 63/63 [00:16<00:00,  3.77it/s, val_loss=0.0443]\n",
-      "Epoch 69 - Sampling from DDPMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 146.63it/s]\n",
-      "Epoch 69 - Sampling from DDIMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 151.85it/s]\n",
-      "Epoch 69 - Sampling from DDIMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 154.85it/s]\n",
-      "Epoch 69 - Sampling from DDIMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 154.81it/s]\n",
-      "Epoch 69 - Sampling from DDIMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 158.06it/s]\n",
-      "Epoch 69 - Sampling from PNDMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 152.39it/s]\n",
-      "Epoch 69 - Sampling from PNDMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 151.40it/s]\n",
-      "Epoch 69 - Sampling from PNDMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 151.47it/s]\n",
-      "Epoch 69 - Sampling from PNDMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 154.99it/s]\n"
+      "Epoch 60: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.70it/s, loss=0.0454]\n",
+      "Epoch 61: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0447]\n",
+      "Epoch 62: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0456]\n",
+      "Epoch 63: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0452]\n",
+      "Epoch 64: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0457]\n",
+      "Epoch 65: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0444]\n",
+      "Epoch 66: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0445]\n",
+      "Epoch 67: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0451]\n",
+      "Epoch 68: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0454]\n",
+      "Epoch 69: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0453]\n",
+      "Epoch 69 - Validation set: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:11<00:00,  5.62it/s, val_loss=0.0457]\n",
+      "Epoch 69 - Sampling from DDPMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.20it/s]\n",
+      "Epoch 69 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 71.16it/s]\n",
+      "Epoch 69 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 71.09it/s]\n",
+      "Epoch 69 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 70.93it/s]\n",
+      "Epoch 69 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 70.93it/s]\n",
+      "Epoch 69 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 71.44it/s]\n",
+      "Epoch 69 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 71.13it/s]\n",
+      "Epoch 69 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 71.10it/s]\n",
+      "Epoch 69 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 71.06it/s]\n"
      ]
     },
     {
      "data": {
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\n",
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\n",
       "text/plain": [
-       "<Figure size 576x288 with 9 Axes>"
+       "<Figure size 800x400 with 9 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 70: 100%|██████████| 63/63 [00:47<00:00,  1.32it/s, loss=0.0435]\n",
-      "Epoch 71: 100%|██████████| 63/63 [00:52<00:00,  1.19it/s, loss=0.0429]\n",
-      "Epoch 72: 100%|██████████| 63/63 [00:52<00:00,  1.20it/s, loss=0.044] \n",
-      "Epoch 73: 100%|██████████| 63/63 [00:53<00:00,  1.17it/s, loss=0.043] \n",
-      "Epoch 74: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0438]\n",
-      "Epoch 75: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0428]\n",
-      "Epoch 76: 100%|██████████| 63/63 [00:53<00:00,  1.19it/s, loss=0.0419]\n",
-      "Epoch 77: 100%|██████████| 63/63 [00:52<00:00,  1.19it/s, loss=0.0425]\n",
-      "Epoch 78: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0426]\n",
-      "Epoch 79: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0433]\n",
-      "Epoch 79 - Validation set: 100%|██████████| 63/63 [00:16<00:00,  3.80it/s, val_loss=0.0438]\n",
-      "Epoch 79 - Sampling from DDPMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 147.40it/s]\n",
-      "Epoch 79 - Sampling from DDIMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 152.26it/s]\n",
-      "Epoch 79 - Sampling from DDIMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 150.01it/s]\n",
-      "Epoch 79 - Sampling from DDIMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 150.49it/s]\n",
-      "Epoch 79 - Sampling from DDIMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 151.66it/s]\n",
-      "Epoch 79 - Sampling from PNDMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 153.92it/s]\n",
-      "Epoch 79 - Sampling from PNDMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 152.94it/s]\n",
-      "Epoch 79 - Sampling from PNDMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 153.99it/s]\n",
-      "Epoch 79 - Sampling from PNDMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 150.45it/s]\n"
+      "Epoch 70: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.70it/s, loss=0.0442]\n",
+      "Epoch 71: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.044]\n",
+      "Epoch 72: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0449]\n",
+      "Epoch 73: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.044]\n",
+      "Epoch 74: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0447]\n",
+      "Epoch 75: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.044]\n",
+      "Epoch 76: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0427]\n",
+      "Epoch 77: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0439]\n",
+      "Epoch 78: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0438]\n",
+      "Epoch 79: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0446]\n",
+      "Epoch 79 - Validation set: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:11<00:00,  5.62it/s, val_loss=0.0447]\n",
+      "Epoch 79 - Sampling from DDPMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.35it/s]\n",
+      "Epoch 79 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.11it/s]\n",
+      "Epoch 79 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 68.91it/s]\n",
+      "Epoch 79 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 68.67it/s]\n",
+      "Epoch 79 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 68.69it/s]\n",
+      "Epoch 79 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.68it/s]\n",
+      "Epoch 79 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 69.03it/s]\n",
+      "Epoch 79 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 68.56it/s]\n",
+      "Epoch 79 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 68.85it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 576x288 with 9 Axes>"
+       "<Figure size 800x400 with 9 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 80: 100%|██████████| 63/63 [00:46<00:00,  1.36it/s, loss=0.0431]\n",
-      "Epoch 81: 100%|██████████| 63/63 [00:52<00:00,  1.19it/s, loss=0.0424]\n",
-      "Epoch 82: 100%|██████████| 63/63 [00:52<00:00,  1.20it/s, loss=0.0424]\n",
-      "Epoch 83: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0433]\n",
-      "Epoch 84: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0428]\n",
-      "Epoch 85: 100%|██████████| 63/63 [00:53<00:00,  1.18it/s, loss=0.0413]\n",
-      "Epoch 86: 100%|██████████| 63/63 [00:52<00:00,  1.19it/s, loss=0.0426]\n",
-      "Epoch 87: 100%|██████████| 63/63 [00:54<00:00,  1.16it/s, loss=0.0436]\n",
-      "Epoch 88: 100%|██████████| 63/63 [00:52<00:00,  1.21it/s, loss=0.0435]\n",
-      "Epoch 89: 100%|██████████| 63/63 [00:52<00:00,  1.20it/s, loss=0.043] \n",
-      "Epoch 89 - Validation set: 100%|██████████| 63/63 [00:16<00:00,  3.74it/s, val_loss=0.0442]\n",
-      "Epoch 89 - Sampling from DDPMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 146.65it/s]\n",
-      "Epoch 89 - Sampling from DDIMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 151.80it/s]\n",
-      "Epoch 89 - Sampling from DDIMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 152.14it/s]\n",
-      "Epoch 89 - Sampling from DDIMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 153.81it/s]\n",
-      "Epoch 89 - Sampling from DDIMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 151.57it/s]\n",
-      "Epoch 89 - Sampling from PNDMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 154.16it/s]\n",
-      "Epoch 89 - Sampling from PNDMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 152.50it/s]\n",
-      "Epoch 89 - Sampling from PNDMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 151.06it/s]\n",
-      "Epoch 89 - Sampling from PNDMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 153.94it/s]\n"
+      "Epoch 80: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.70it/s, loss=0.044]\n",
+      "Epoch 81: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.69it/s, loss=0.0438]\n",
+      "Epoch 82: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0436]\n",
+      "Epoch 83: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0442]\n",
+      "Epoch 84: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0443]\n",
+      "Epoch 85: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0424]\n",
+      "Epoch 86: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0438]\n",
+      "Epoch 87: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0444]\n",
+      "Epoch 88: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0443]\n",
+      "Epoch 89: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0442]\n",
+      "Epoch 89 - Validation set: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:11<00:00,  5.62it/s, val_loss=0.045]\n",
+      "Epoch 89 - Sampling from DDPMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 70.85it/s]\n",
+      "Epoch 89 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 71.54it/s]\n",
+      "Epoch 89 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:06<00:00, 71.49it/s]\n",
+      "Epoch 89 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 71.18it/s]\n",
+      "Epoch 89 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 71.28it/s]\n",
+      "Epoch 89 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 71.56it/s]\n",
+      "Epoch 89 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 71.34it/s]\n",
+      "Epoch 89 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 70.82it/s]\n",
+      "Epoch 89 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 70.76it/s]\n"
      ]
     },
     {
      "data": {
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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 576x288 with 9 Axes>"
+       "<Figure size 800x400 with 9 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 90: 100%|██████████| 63/63 [00:47<00:00,  1.32it/s, loss=0.0433]\n",
-      "Epoch 91: 100%|██████████| 63/63 [00:52<00:00,  1.19it/s, loss=0.0429]\n",
-      "Epoch 92: 100%|██████████| 63/63 [00:53<00:00,  1.19it/s, loss=0.0424]\n",
-      "Epoch 93: 100%|██████████| 63/63 [00:52<00:00,  1.21it/s, loss=0.0422]\n",
-      "Epoch 94: 100%|██████████| 63/63 [00:52<00:00,  1.19it/s, loss=0.0414]\n",
-      "Epoch 95: 100%|██████████| 63/63 [00:52<00:00,  1.21it/s, loss=0.0418]\n",
-      "Epoch 96: 100%|██████████| 63/63 [00:53<00:00,  1.19it/s, loss=0.0405]\n",
-      "Epoch 97: 100%|██████████| 63/63 [00:53<00:00,  1.19it/s, loss=0.0417]\n",
-      "Epoch 98: 100%|██████████| 63/63 [00:51<00:00,  1.23it/s, loss=0.0421]\n",
-      "Epoch 99: 100%|██████████| 63/63 [00:54<00:00,  1.15it/s, loss=0.0432]\n",
-      "Epoch 99 - Validation set: 100%|██████████| 63/63 [00:15<00:00,  3.96it/s, val_loss=0.0425]\n",
-      "Epoch 99 - Sampling from DDPMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 146.90it/s]\n",
-      "Epoch 99 - Sampling from DDIMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 149.68it/s]\n",
-      "Epoch 99 - Sampling from DDIMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 150.87it/s]\n",
-      "Epoch 99 - Sampling from DDIMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 153.43it/s]\n",
-      "Epoch 99 - Sampling from DDIMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 154.10it/s]\n",
-      "Epoch 99 - Sampling from PNDMScheduler...: 100%|██████████| 1000/1000 [00:06<00:00, 154.63it/s]\n",
-      "Epoch 99 - Sampling from PNDMScheduler...: 100%|██████████| 500/500 [00:03<00:00, 152.10it/s]\n",
-      "Epoch 99 - Sampling from PNDMScheduler...: 100%|██████████| 200/200 [00:01<00:00, 153.93it/s]\n",
-      "Epoch 99 - Sampling from PNDMScheduler...: 100%|██████████| 50/50 [00:00<00:00, 157.84it/s]\n"
+      "Epoch 90: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.70it/s, loss=0.0442]\n",
+      "Epoch 91: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0442]\n",
+      "Epoch 92: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0435]\n",
+      "Epoch 93: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0433]\n",
+      "Epoch 94: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0421]\n",
+      "Epoch 95: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0432]\n",
+      "Epoch 96: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0417]\n",
+      "Epoch 97: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0429]\n",
+      "Epoch 98: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0435]\n",
+      "Epoch 99: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0441]\n",
+      "Epoch 99 - Validation set: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 63/63 [00:11<00:00,  5.63it/s, val_loss=0.044]\n",
+      "Epoch 99 - Sampling from DDPMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 70.51it/s]\n",
+      "Epoch 99 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 71.25it/s]\n",
+      "Epoch 99 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 71.30it/s]\n",
+      "Epoch 99 - Sampling from DDIMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 70.60it/s]\n",
+      "Epoch 99 - Sampling from DDIMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 70.90it/s]\n",
+      "Epoch 99 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 71.17it/s]\n",
+      "Epoch 99 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 500/500 [00:07<00:00, 70.20it/s]\n",
+      "Epoch 99 - Sampling from PNDMScheduler...: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:02<00:00, 68.61it/s]\n",
+      "Epoch 99 - Sampling from PNDMScheduler...: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 50/50 [00:00<00:00, 68.93it/s]\n"
      ]
     },
     {
      "data": {
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\n",
+      "image/png": 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\n",
       "text/plain": [
-       "<Figure size 576x288 with 9 Axes>"
+       "<Figure size 800x400 with 9 Axes>"
       ]
      },
-     "metadata": {
-      "needs_background": "light"
-     },
+     "metadata": {},
      "output_type": "display_data"
     }
    ],
@@ -967,17 +933,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 13,
    "id": "af10be41",
    "metadata": {
     "lines_to_next_cell": 2
    },
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_6568/3570577212.py:1: MatplotlibDeprecationWarning: The seaborn styles shipped by Matplotlib are deprecated since 3.6, as they no longer correspond to the styles shipped by seaborn. However, they will remain available as 'seaborn-v0_8-<style>'. Alternatively, directly use the seaborn API instead.\n",
+      "  plt.style.use(\"seaborn\")\n"
+     ]
+    },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
-       "<Figure size 576x396 with 1 Axes>"
+       "<Figure size 800x550 with 1 Axes>"
       ]
      },
      "metadata": {},
@@ -1014,7 +988,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 14,
    "id": "78058049-f92b-42b8-96f2-1eafca11a384",
    "metadata": {},
    "outputs": [],
@@ -1051,7 +1025,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.9"
+   "version": "3.8.12"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.py b/tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.py
index 6a2e1d16..ca0f48e8 100644
--- a/tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.py
+++ b/tutorials/generative/2d_ddpm/2d_ddpm_compare_schedulers.py
@@ -125,7 +125,7 @@
     ]
 )
 train_ds = CacheDataset(data=train_datalist, transform=train_transforms)
-train_loader = DataLoader(train_ds, batch_size=128, shuffle=True, num_workers=4)
+train_loader = DataLoader(train_ds, batch_size=128, shuffle=True, num_workers=4, persistent_workers=True)
 
 # %%
 val_data = MedNISTDataset(root_dir=root_dir, section="validation", download=True, seed=0)
@@ -138,7 +138,7 @@
     ]
 )
 val_ds = CacheDataset(data=val_datalist, transform=val_transforms)
-val_loader = DataLoader(val_ds, batch_size=128, shuffle=False, num_workers=4)
+val_loader = DataLoader(val_ds, batch_size=128, shuffle=False, num_workers=4, persistent_workers=True)
 
 # %% [markdown]
 # ### Visualisation of the training images
@@ -146,7 +146,7 @@
 # %%
 check_data = first(train_loader)
 print(f"batch shape: {check_data['image'].shape}")
-image_visualisation = torch.concat(
+image_visualisation = torch.cat(
     [check_data["image"][0, 0], check_data["image"][1, 0], check_data["image"][2, 0], check_data["image"][3, 0]], dim=1
 )
 plt.figure("training images", (12, 6))
@@ -167,11 +167,10 @@
     spatial_dims=2,
     in_channels=1,
     out_channels=1,
-    model_channels=64,
-    attention_resolutions=[2, 4],
+    num_channels=(64, 128, 128),
+    attention_levels=(False, True, True),
     num_res_blocks=1,
-    channel_mult=[1, 2, 2],
-    num_heads=1,
+    num_head_channels=128,
 )
 model.to(device)
 
diff --git a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb
index bdba4d85..ccbb9cb9 100644
--- a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb
+++ b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb
@@ -70,7 +70,7 @@
       "lmdb version: NOT INSTALLED or UNKNOWN VERSION.\n",
       "psutil version: 5.9.3\n",
       "pandas version: NOT INSTALLED or UNKNOWN VERSION.\n",
-      "einops version: 0.4.1\n",
+      "einops version: 0.6.0\n",
       "transformers version: NOT INSTALLED or UNKNOWN VERSION.\n",
       "mlflow version: NOT INSTALLED or UNKNOWN VERSION.\n",
       "pynrrd version: NOT INSTALLED or UNKNOWN VERSION.\n",
@@ -145,7 +145,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/tmp/tmp_ik9ng61\n"
+      "/tmp/tmpdha9uqf4\n"
      ]
     }
    ],
@@ -174,7 +174,7 @@
    },
    "outputs": [],
    "source": [
-    "set_determinism(0)"
+    "set_determinism(42)"
    ]
   },
   {
@@ -202,9 +202,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-25 18:48:31,660 - INFO - Downloaded: /tmp/tmp_ik9ng61/MedNIST.tar.gz\n",
-      "2022-11-25 18:48:31,731 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
-      "2022-11-25 18:48:31,732 - INFO - Writing into directory: /tmp/tmp_ik9ng61.\n"
+      "2022-11-25 22:04:40,336 - INFO - Downloaded: /tmp/tmpdha9uqf4/MedNIST.tar.gz\n",
+      "2022-11-25 22:04:40,408 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
+      "2022-11-25 22:04:40,408 - INFO - Writing into directory: /tmp/tmpdha9uqf4.\n"
      ]
     }
    ],
@@ -240,7 +240,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1803.07it/s]\n"
+      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1719.09it/s]\n"
      ]
     }
    ],
@@ -279,16 +279,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-25 18:48:54,399 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
-      "2022-11-25 18:48:54,400 - INFO - File exists: /tmp/tmp_ik9ng61/MedNIST.tar.gz, skipped downloading.\n",
-      "2022-11-25 18:48:54,400 - INFO - Non-empty folder exists in /tmp/tmp_ik9ng61/MedNIST, skipped extracting.\n"
+      "2022-11-25 22:05:04,646 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
+      "2022-11-25 22:05:04,646 - INFO - File exists: /tmp/tmpdha9uqf4/MedNIST.tar.gz, skipped downloading.\n",
+      "2022-11-25 22:05:04,647 - INFO - Non-empty folder exists in /tmp/tmpdha9uqf4/MedNIST, skipped extracting.\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1005/1005 [00:00<00:00, 1848.85it/s]\n"
+      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1005/1005 [00:00<00:00, 1744.49it/s]\n"
      ]
     }
    ],
@@ -333,7 +333,7 @@
     },
     {
      "data": {
-      "image/png": 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       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ]
@@ -380,16 +380,6 @@
    "source": [
     "device = torch.device(\"cuda\")\n",
     "\n",
-    "# model = DiffusionModelUNet(\n",
-    "#     spatial_dims=2,\n",
-    "#     in_channels=1,\n",
-    "#     out_channels=1,\n",
-    "#     model_channels=64,\n",
-    "#     attention_resolutions=[2, 4],\n",
-    "#     num_res_blocks=1,\n",
-    "#     channel_mult=[1, 2, 2],\n",
-    "#     num_heads=1,\n",
-    "# )\n",
     "model = DiffusionModelUNet(\n",
     "    spatial_dims=2,\n",
     "    in_channels=1,\n",
@@ -416,7 +406,7 @@
    "metadata": {},
    "source": [
     "### Model training\n",
-    "Here, we are training our model for 100 epochs (training time: ~40 minutes)."
+    "Here, we are training our model for 75 epochs (training time: ~50 minutes)."
    ]
   },
   {
@@ -434,17 +424,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 0: 100%|████████████| 63/63 [00:37<00:00,  1.69it/s, loss=0.863]\n",
-      "Epoch 1: 100%|████████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.568]\n",
-      "Epoch 2: 100%|████████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.343]\n",
-      "Epoch 3: 100%|████████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.202]\n",
-      "Epoch 4: 100%|████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.118]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 72.06it/s]\n"
+      "Epoch 0: 100%|████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.863]\n",
+      "Epoch 1: 100%|████████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.569]\n",
+      "Epoch 2: 100%|████████████| 63/63 [00:39<00:00,  1.59it/s, loss=0.343]\n",
+      "Epoch 3: 100%|██████████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.2]\n",
+      "Epoch 4: 100%|████████████| 63/63 [00:41<00:00,  1.53it/s, loss=0.116]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.03it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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XlslkMBqNcLlcKxphKpXKaW1lP8t6vR4ejwf9/f0wGAwwmUyQyWRIpVIc4zkcDkxNTcFqtXIrUSaTQa1W53iczCw5H2w2G9xuN5LJJOLxOEZHRzE+Pp7TZdHr9YLMtbq6mluG2aWkdDoNiUQCuVyOSCTCVQW9Xg+JRMLXKZlMYmFhAUajkUtADocDcrl82etIWLUR7tu3D7FYjLPR1eD69esQiUQYGxvL6UpMTEwIbvbw8DCGh4chl8tx5513Ih6PY3JyEl6vF8FgEHK5nEsPXV1dOcYHgJ9EnU4HpVKJVColOBK6uroglUqxefNmDtwJpaWlMBqNcDgcqK6uFngEu92e0w4rBJ1Oh9LSUvh8PtTW1mLXrl2IxWKYn5+Hz+fDwMAAQqEQNm/ejMrKSpw+fRpHjhyBVCrF+vXrodPpONEiyGQyDA0NCY7VxsZGRKNR/pzNzc2455570N3djZ6eHng8nrxtvmxD/sUvfgFgKcOXy+XYsGEDEokErly5gsHBQQwODjLRw2w284OUGd7E43GcPHkSN27cQCAQwIkTJ/B3f/d3SCaTuHnz5orXbNVGmN33VavV2LNnD44ePZrjVTIxPDwsuBj79u1DJBJBR0dH3tJHLBZDbW0tvF4vBgcHORkAwMXmfNDpdCgvL0d5eTl0Oh1CoRAikUhOPJRIJJBIJATZrEKh4OIzdRro5tbW1qKoqEhghBRjZnurTZs24Y477sDIyAgmJydht9uxb98+eL1enDx5EgsLCxwrU9xL75NIJLiqQO9RWVmJyclJyOVyeL1efj+324377rsPgUAA3/3udwEsZd/Nzc2Ym5tDX19fwTpdIW86MjKCqqoqPProo9DpdPjCF76Q4zjI+NLptMAICTMzMxgZGcHNmzfzViEK4X0nJouLi/B4PCgtLcX4+DhSqVSO58kGNeLFYjFkMlneGwkslYP8fj9mZ2cRDoe5IFpfX4/i4mK88847OX8TCARw6tQpnDp1io8Dk8kElUqV01bzer2QyWQoKiqC1+uF0+lkz0vkAcLIyAi8Xi+XepqamuB2u3Hx4sW8mb1arYbT6YRSqYRIJMK1a9cwPj6O48ePC0pAr732Gt577z1ByWtsbAwTExPw+XwQiUSorq5GdXU1ent7+Sgk0ANGpZsLFy4gFovh7NmzOH/+fF4vCCzV/fR6PbdA6TNFIhH09vaip6eH237ZRtjQ0ACHw4HGxkb4fD5+ADJx+fJlyOVytLe355w2hfDvyo5nZ2dRWVmJBx54AOFwGOPj44jH40gmk0gmk+jv78fMzAxX/h0OBz9BlAhkx1ZqtRrXr1/H4uJiToxiNpuxfv16GI1GPprlcjn6+voENzOVSmFychKTk5NoamrC/v378fbbb7PX8Xq9MBqNqKmpQX19PRv65ORkTjwYiUQQiURQWVmJhoYGOJ1OlJSUQKlUCozQ4XDAbrdDrVZDqVTCZrNhfn4enZ2dGBwczCkGx+PxnJorlX4IW7ZswR133IGpqakcI6SWW3l5Oebm5nD27FmcOHEib29fJBJBo9FwTF5bW4t7770XgUAAPp8Ply9fxqVLl5BMJnH9+nVOCG02myD8Wrt2LWpra/HRj34Uo6OjeY2Qvttf//Vfw2635/15NlZthFKplL0dAL4JIyMjXMK4fv06AKCoqAgajQZKpRJutxsKhQIymQyxWAwDAwOIRqMIBAJIpVJwOBxQKBSYnp5GNBpFOBzmi5ON3t5exGIxDA4OcoG3ubkZGo2mYG+7q6sLRqNRUPQOBAIYHx/PmzXS5zaZTEgkEpx1B4NBTExMcLCeHRbMzMxgcXGRyyzU8Fer1TnvUagLU15eDo/Hw8byxhtv4ObNmzkGSMlWOp2Gx+OB1+tFcXEx9Ho9rl+/nnMapdNpQVI4MjKC1157DW63G3V1dQIq2MDAAObn5zEyMpLjTUUiEaampvCLX/wip2Cd/X7/8i//Ap1Ohx/+8IcFf4+waiNsamqCVCpFcXEx1Go1rl27hhs3bmBycjKn4k43d/PmzdiwYQMcDgccDgeOHz8uYDOLRCJs3rwZ5eXleP311zE4OIh0Op234Q8I21bAUkgQj8dhMpkwOTlZMBQgqhUhkUgULFusW7cOVqsV5eXlCIfDePXVVzE1NYWZmRnMzs5ienoaXq83J/OjbJ34k5Tl2mw2QetMJpOhrKwM8/Pz3GZMpVIoLS3Fpk2b0NPTw63NZDKZl3KVTCYRCoWQTqfZGEpKStDW1gan04nu7m6o1WpYrVZcuHBBELPX1dWhr68PMzMzGB0dxaFDhwQGRSdINoqKigAsFcnfeuutvNcuE7/+9a8B4IM1Qq1WC6lUCofDAaPRiNHRUSgUimWr4pOTkxgfH2fWRjbbIp1Oo6urCzMzM4JjMJvCBEDQfsuETqdDOp1GaWkpgsHgqrPY5T5zOBxmahUdbxKJBBqNBqlUCh6PJy/72Ov1cvOe2pkqlUrg1ePxOLPL1Wo1FhYWuPwhlUpXXf6KRqOC5MDn82FiYkKQkKTTaahUKsF1y/z/iUQCPp8v76mTjZmZGa5gfNBYdbH6ox/9KJRKJXbs2IHi4mIcPnwY7733Hrq7uwuybQkmkwmtra05xdB8cDgcWL9+PWQyGSQSCYxGI7Zv3w6j0YibN29iZmYGExMTmJiYgNFoRElJCcRiMWeXdPz/5V/+JR/R1Nu1WCxMWrhdOJ1OtLS0oK+vb1mCbktLi6Cllo80CyyFN0VFRRgdHb3tzwIA27Ztg1qtxsWLFwWnA7AUKlF9T6lUwuFwIJ1Oo6enR+A0nE4n2tvb8fbbbxcsgi+H1tZW7Nixg/MACqMoDJFIJPj5z3++4uus2hMGAgHEYjEEg0EmR0YikRUNEFhi1czNza2qjZN5zFHspVQqoVarYTKZkE6nEYvFuGdtNpu5bCCVSmE2myGXy2EymdgII5EI5HI5ZDJZXo7gapBJlVoO2bFpIS+TSCRW3VvNB5lMxp5WpVIJPHMkEuFrJ5fLUV5ejlQqJXg4aFZobm7ufRkggYrvxAuQSqXQarU8krEarNoTLlet12g00Gq1cDqdEIlEPFuSebS43W44nU6sXbuWi6zj4+MC975r1y709PQU9FQ0OUaeqLS0FN/5zncgEonQ39+P2dlZPPvss+/ryCCW9kqQSCQoLS3lXjEla8lkMu/NzO5QZKO1tRX33nsvjh49inPnzgFYomkZDIYctnImnn76aUilUjz//POYnJxkltKlS5fYMezYsYOZ616vV+Aw2tvbmSjh8Xhykp+VrkG+frRKpUJdXR2sVitqamoglUrxT//0Tyu+3gdCYHA6nbDZbGhsbIRcLmdP+Zvf/IY9RzQahUqlQn19PTNOHA6HwGCKi4uXZYcEAgFBxjY2NgaLxQJg6cKEw+H3ZYB2ux2VlZVQq9UrHo/JZBIWi4VjK4VCwbMr+eqXK9XKysvL8bGPfQwSiYSNsLGxMW9WnQmn08lxqkqlQnFxMcxmM65fv85e0eFwwOfzCSoDBKqRTk1N8cwQZdqZUKvVMJvNAofS3t6O+fn5nJmWcDgMj8cDiUSCYDC46lPnfXtCl8vF8U92ur57926UlJTgxIkTOfGTVqstOG5YqHidCavVCrlcDrlcjrq6OuzatQsejwevv/56TmBOx7LNZoPH4xEQRD8o0CxMIpHI8eBUTaDRTWCJFKBSqQRtx6amJiwuLsLr9UKj0aCxsRGJRGLFqUC1Wg2LxQKJRILFxUUeTwWWrtPnPvc5zM3N4de//jWmp6eZB1lfX49169blnbvevXs3jEYjrl27htnZWZ6UzLzHtbW1SCaTAhKvy+XiTpJSqeT+MhGSl8P78oRGoxF/8id/gk9+8pN46qmn8Pzzzwt+Pjs7i6qqKjidTqRSKYGrXy7+yDbApqYmHkACli6sy+VCW1sb1q1bh9nZWVy5cgX9/f05pYyWlhbcf//9cLvdqK+vx/Hjx/EXf/EXOe+ZnXVn10NXAhXps2G326FQKKBUKqHT6VBTUwO73Y5PfepTsNls+C//5b8w35IMsrW1FVKpFCMjI6saxyRGeGlpaU5VwOl0oqamBjMzM3A6nRxDymQylJaWFiQXPPHEE2hoaMC3v/1tnD59GrFYLMdhzM/Pc3sRWPLce/bsQX9/P3p6erC4uAifz7eqfAF4H0ZIpNNbt27hhz/8IRKJBKqqqgRPRUVFBaqqqnD8+HGMjIxwbSwQCOQtoeh0upzCKPHSMss6VqsVtbW18Pl8ePfddzmWyWfYPT09CIVCcLlcPKGWr/STXfZJJBI8CUcdhPcD+p67d+/mxCqVSuH73/8+IpFI3iqBVqtFLBbjBkAmysrK8sZtlJhlJyddXV147rnnACwlMVqtlo09H/kDWLq33d3dmJiYwLFjxzA2NgaVSoWKigqEQiG+Rw6HA1KplBsMLpcLSqUSUqkU6XQaJSUl2LRp0wfPoiHU1dVhx44d+O1vf4tf/vKXOHToEF577TW88MIL+Mu//EsAS09Gc3Mzu3C73Y4vfvGL8Pv9XInv7+9HIpFAeXk5VCoVfvazn/EF+9nPfoapqSm88cYbAo9QWlqKtrY2vPnmm/jd734n+FxlZWVQKpWYmpriTL6/vx/9/f147733ACwlR1qtNm/i09raiqmpKZ7MO3jwIFKpVI4RElUskUjkqBV8/OMfx4EDB1jGA1iiSmm1WkgkEgwPDwsKvVqtNofe5vV6cwywsrISX/3qV/H222/jl7/8JQwGA5qamiAWizEzM4NoNIrKykqIRCKBgVFis3v37mUNQiKR4MCBA5DJZDh79izm5+c5BgyHw3A4HKisrOQuUjAYRCKRgMVigUgkQlVVFTQaDRthXV0dvvjFL+YMshXCbRuhWCwWULOmp6fR1dUlGIq+desWbDYbZ1DRaBSDg4Pw+/0YGxtjYmQsFsspYRgMBgwNDTGJMrN7Mjo6iuPHj8Pn88HhcGBmZoZd/vz8PEt+FILRaIRSqcxrhFTmAZaOuWzqFACuuRUXF2NiYiKns2MwGHLmT8iTUxaaiWwPnkwm8x5hYrEYIyMj8Pv90Gg0zEWk7lIikeCJwXze3mg0LlsuocI8dZKykxOSUaHRg1AohHg8jtnZWa4RRiIR3Lp1i0csXnrpJWi1WvzJn/xJwfclrDox+drXvoZIJIITJ05gZGQEY2NjSKVSUCgUWLNmDa5cucIXUCwWo76+Hjdv3kQ8HodUKoXdbmedkkJob29HJBJBMBgUHFeVlZUoLS1l76fRaPDoo4/ixo0bKwbvIpEIKpUKdrsd69atA7DUFSHCKYFmdKnwq1AoEI/HBbGh2+1Ga2srNm/ejNdff53bgXfeeSdqa2thNpshlUrxzDPP8NF51113IZlMcj92uY7Ojh07sLi4yDEwyWnQUFcikUA0GkVJSQl27dqFRCKBEydOcB9dLpfzTMj58+dx6tQpAMAXv/hF6PV6vPPOOxgdHc2rotDU1IRUKpVXxcFgMHCLtBCyyQ6E1ZjXbREYZDIZdDodTCYTfD4f/H4/kskkD+kQUqmUoDidSCSWbXgT7HY7D8lkYm5uTjCpFwqFMDQ0tKoWHQ1wUxGbhrqzhZOyj6t8LcJAIICFhQXMzc0JvBoF78PDw0zOAH7vXYnUWqgnTqBanlarRTweh06ng0wmQygUgt/vZxpcIBBgkQDynlQWI0mRzPIIPfg0h6PT6RAMBgX3bDnFMRqHWM4I/z2bSFbtCal2dejQIVRXV+OVV17BO++8w8bpdDqxfft2JBIJHDlyJC+1PBM0Y9LT04P5+XmsXbsWNTU16OjoWHEEcTl88pOfRF1dHf7pn/4JHo8HWq0WjzzyCFKpFNOyRkdH4fP52BPKZDKe4cg2FIlEwiSD94NDhw5henp6VaUKwhNPPAGtVosXX3yx4MPrcrmgUqkgk8mQSCQEXt3tdiMQCPC4aFFREeLxOJeo6uvrcdddd+HnP/95wQI9kTDWr1+PtWvXorOzc9nvsHfvXly9epW9IbVPV9K8AW7DEw4PD8NgMMBgMLA8h0aj4SNCrVZjw4YNTPVeSRaMAnyn0wmtVsszGCu19lbqQNTX12Pjxo0wm81cONXr9YjFYvD7/YhEIsyuJpCaVHZhWSqVQqVSQSQS3ZaiQCZIGu52QKMGyxV7JyYmuEid/XsejwepVIqJwyQtR5BIJCguLi7YJZLJZHC5XDAYDCgqKoLBYIBOpxP8PPs+abVa6PV6zM7OQqvVorq6OkdCsBBWbYShUAjRaBTnzp3DwsICRkdHIZVKmYg5PT2Nubk5loBbSZGJBIsIZrMZa9asyVvdz8RKxvDSSy+hu7ubp+oMBgPHTRQLkRYNIZlMwuVy4d5778X09DQCgQCGhoYwPz+/avm0QrJp2bqCbrcber1eoAyRidLSUva+LpcLwWAQfr8/r5xKOBzmNlkwGMTY2Bjq6+vR0tKC4eFhXLx4EVarFffddx/C4TDr/ly/fh0vvvgii01FIhFm/9AwvVar5Vj/+eefR3l5Oe6//37+nj6fjxUyNBoNJyXA0rHvcrlWFAQg3FZ2nEgkuC1GAXzmhacLq1KpIJfLmfqULf6YD4uLi1Aqlatupm/btg1dXV052fWVK1fg8/mg0+nQ2NiI+fl59Pf358xFZ8aEyWQSOp0OxcXF2LlzJ8bHx/Gb3/wmJ8ss5KnNZjMUCkVeHl4sFuPvLpPJ8MADD6CsrAzf+ta3BK0wsVgMu93Ojf90Og2DwcAnDrXEsmGxWFBaWori4mIEg0FUVFRwx+XixYvQaDTYuHEjQqGQQHzqypUrWL9+Pfbv349oNAqPx4Ph4WEuZ8lkMtjtdj7CZ2ZmsG7dOkilUgSDQfh8PgwNDWFychJKpRJer1eQA+h0OoH3XA6rjgmJwULSE8RIoWHpTGzZsgUGg4HnKyi+yDf8QlR4l8sFq9WK119/Pe/7F+IT5vs9tVrNyYLBYGCJNjLE7E4MsFT/rKysxObNmzE0NCS4YcDSEUa0fpVKBY/Hw0a0Y8cOAOAbSJBKpdi7dy8riJHsWyKRWDa++su//EsYDAZ8//vfR39/P/R6PY/AWq1WdHV1sUFKpVI4nU7Mzs4iGo2itbUV69atw8jICM6fPw+DwYA77rgDiURCoMBgMpngcDhQVlYGmUzGDuDChQsIhUKoq6uDxWJBV1cXZmdnIRKJUFZWBpFIhHg8zho4K+EDzY7dbjfC4TAnDTTLa7fb0dbWhrm5OZw7dw5qtRotLS0880t6fiaTSWCEZrMZJSUlaGxshNFoRG9vb8HuRPagfCZIQZZmkTMVDYAlj02CnnTRjEajoO0EAH19fRgeHobFYsnpZtjtdthsNuh0OpSUlLA45vnz56FWq9HY2IhYLJZjhBaLBQqFAmazGXV1dfD5fPj2t7+9opQaHd/Ud/f7/XC5XLjjjjtw//3349lnn+VRzUQiIfCok5OTsFqt8Pl8UKlUWFxcxJtvvgmpVMo6jzTpNz8/D4/Hw/M2SqUSe/bsQTKZRF9fH7q6upijOTQ09B9CaAVuwwjp+C0vL4dIJOLaFbAUL1IWt7i4iKtXr8Ln83EJZXFxMe9MRSgUwuDgIGQyWQ4FPxOkDpsNmt6LRqN87GXf4GQymfPat27dynk9YsNkz/wCS0eRz+eDzWbjscfp6WnMz88jGAzi6tWreY/p6elpnDt3DkqlEp2dnVxUJpVWhUKRt7ZGPMlNmzahq6sLGo2GZYTffvvtZWe/TSYTTCYTRCIRQqEQ8xZTqRSXiWj0gKRZwuEwBgcHudKRSqXQ09Pz7yq73A5ui0VjNBrxne98B/v378fU1BRmZ2dx8uRJ/OpXv8pJxQtlXsSAoRbPcoH/tm3bUFpainQ6zbrLcrmcs7Xu7m4cPnyY20i3C4qlHA4Hd3hSqRSmpqZw7NixvKRTqVSK8vJyLCwsrJhE5YPFYkFNTQ2qq6ths9lw9OhRQautvr4e/+t//S84nU709vbC6/Xi1KlTuHr1KkKhEItlPvzwwwCWNid4vV7uYjQ1NaGpqQkLCwsYGxtDPB5npS8iTNhsNpSXlyMYDGJhYaGgWlkhUAeGHNPWrVsFBAaDwYDy8nJIJBL8+Mc/XvH1bisxSSaTiEaj3DMNh8NQKBQoKyuD1+sVPKGF6k8UF1G7ZzmQ3AYlNqRuWl9fD6PRyPLF6XQaOp2On+R0Or0qpQgKnh0OB0pLSzE3N8f1zUKs50QiUVCHUCqVQqFQLHtDU6kUbzHInNojeWGlUokbN27wYBVpGKbTaSgUCv6OdPKQmCfpzjidTiwsLGBqago3b95EMpnk2J1AcT3Njq9WuIiQHQtOTk6ip6cHyWSS5YVXE78TbssTKhQK/PEf/zGampqYYGo2m1ld6t1338Xo6GhBlsbtwmazcbkiEokIvOaTTz6Jc+fOoaOjAwDwn//zf0ZRURE/JN/4xjdyXo+4fMR7o/nabdu2ob29HWfPnsWvfvUr9PT0rIplDSxltRaLBQaDAQcPHkRlZSV++MMfCsi5CoUCNTU1AJZ0GUnwSalUsq6fQqFgLZ6zZ88KNB1pjLSyshJr167FwMAAl0fsdjuUSqWAYdPU1LTiPaitrS0o91cIn/3sZ5dtlZaVleErX/kKrl+/jn/7t39DKBRaVYlr1Z6Q9F1IqZP6wCSpQcPtsVgs7wUoRAknyOVylJWVcQyT2VTP97e0IYBAfDlgydtkC4EDvyfmJhIJVm0Vi8XsCUgUqNCFk0qlgmOfDIdoTBqNBnq9HkVFRbhy5QoX5PV6PRwOB1KpFGZnZ5FKpRAMBhEMBlmhlT53LBbjz72wsICFhQX22DqdDjabTdBFIVJBJlYzyEUtwNsppJOQfSF4vV7BvprV7opZtSd86qmnEI/H0dPTg9nZWdZbyTQOenIpUcj8EKQynx271dfXc4xUXFyMvr4+VgOgo4SGs69cuYK5uTk0NjZi/fr16OzsZIO3Wq08lgpgVTtPCE1NTdi6dSvOnTvHcROBtG2IIEDfweVyYd26dfD5fHjppZfg8/ngdrthMpmwbds2rF+/HgsLC5idncXk5CROnjwJiUSCbdu2QavV4h/+4R8KFt6z98Ko1Wps2rQJFRUVaG5uRn9/P55//nn4fL73PSy1Y8cOmM1mOBwOXL9+fdnE0GazwWKxoKSkBB6Ph68RXZfljP4DLdE0NjYiFAqhs7OTSy/ZWFhYQDQaZVHvoaEhNkQK+rNRUlKChoYGVFRUoKioCD6fjzNI8jA0PlhTU4NAIMCM7cwv6PF4BLWz28GNGzeg1WoFPWsa3Nq/fz+cTifGx8d5JZrNZoPZbEZFRQXGx8dZ5nd4eBjT09O49957sWvXLkxNTWFgYAASiYSzalJoXW72hJS5MuNao9EInU7H3peW/SynPZgtt5wJlUqF8vJyrFu3DiqVipVqSbIlM05sbm5GJBLhGJVameXl5QWpcbeDVd+tM2fOYHFxERcuXMiZcyXs3r0bAPLGDIWC346ODsTjcVy9ehVqtRqnT5/mC1tXV4dgMChgeDgcDuj1eiSTyYJM45qaGqayDwwM5J0T1uv1KCsrg8FgwJkzZ3KKx6ST89vf/hZSqRStra0oLy9Hd3c3XnrpJTQ1NeGTn/wkxGIxNmzYgPLyckxMTCAYDOKNN95Ad3c3gsEg5ufnoVQq0dLSArFYzJR5ki5xOp0oKipikUyTyYSdO3cCWFIvIOayTqdjzezJyUnm8tXX1wNATnXC7XbjwIEDmJmZwYsvvij4GcXFHo8HV65cgdfrRW1tLe9nUSgULC8nlUq5RSuXy2GxWFBVVQW5XM5ZMs2Bv1+s2ghpdqCQAUqlUrS3t8Pn861qbRdhbm4Ovb29vH8t84gKBoM5w0kkxk7D1tnQ6/Wora2FwWBgMcxsI9y6dSuvMdNqtcy7I1AZidpZwNJNbWtrYwM4f/48Dh48CKVSidraWjidTq4YnD9/XnANSktL8ZnPfAZisRjPP/88JiYmYLVasXHjRpSUlKCkpIS/q81mYyM8deoULl++DKvVCpVKxXtRaIGQTCZDY2MjNBqNwAhpkGnHjh0IBALQarUYHx/H22+/zdcI+L2QPMmQ6HQ6bNq0iWdiFhYW0NHRgatXr3I8ajAYsHbtWqhUKo7VS0pK4PV6bysjzsSqjXBsbGzZ+CORSODq1au3PUhdVFSE2tpajI6O5vAD77nnHszMzAjmb+12O/r6+nJiNwKxsquqqlBdXZ03bKivr0dZWRnEYjEikQjMZrPg4YrFYqirq4NcLsfRo0e5YX/z5k1YrVaUlZWhrKyMpYqPHDnCvdN0Oo01a9agoqKCpebKy8u5/HLgwAH4/X5cuXIFY2NjqKysRF1dHW7cuIFTp05xL5YmBZubm2G32yESiTA5OYmhoSFEIhEWop+dnc27UaGzs5OL8iaTiWWIFxYWmI6fWVajPSVTU1M8YSeRSBAIBFhpTCaTYWZmBs8++yxSqRQzn0gF93bi8Eys2ggHBwchEolgMBi4LpWNU6dO5RgqxTAGgwEKhYLnKrq7u1kQiVqC1HLSarVoa2vDY489Bo/Hg6NHjyIUCrHXyPZsOp0O27ZtQygU4tbZwMAApqamuGZHsxAulwutra2w2+0YGhrC3Nwca/VloqWlBVarFYODg7h16xbm5uZw9epV1NfX4yMf+QgCgQAmJiZw8+bNnFJHW1sbPvWpT6GjowNHjhzhuWyTycRD50899RTOnDmD3bt3o6WlBTMzM+zNaK/LunXr+LhNpVIYHh7m0k9DQwPXC7O7RD6fTzA/vXv3brhcLuzfvx8ymYwrC0NDQ+jq6uKlkVQ/BJaqDST5S8sTpVKpQD6Pwian04l169b9xxshycgODQ3lGCCl+/kMU6FQwOl0oqKiAsFgkJfXyGQylhojPWba8kkq9devX+dgGACLcWaC4hRa7piJzKIx1Rpp7+/U1BRSqRREIlHeRIZUC5RKJYqKilBTUwOXywWRSIQbN25gYmICly5dyvFCFosF8/PzOHfuHGZnZ5n4QYyWmpoaZngTY4ZmZaqrqxGJRLiOSdc1m1qv0WjgcDgQj8fzigVkhykulwtOpxPAkjHfunVLQL0qFNrQvZDJZAgGgywWlY1kMpmTaJWVla04wE9YtRH+1//6X+H3+/Gtb31LEKfZ7Xbcf//9GBwc5JjDYrGwSkEikUBLSwv27NmDixcv4ty5c4jFYpxhnTt3Dul0Gu3t7di5cycrBszNzeHHP/5xzjKd7AC4srISRUVFKC0thUgkwpYtWzA2NpY3aaHuwC9/+UvI5XLs3bsXlZWVebmPr7/+OsRiMTZt2oSamhrs27cPTU1NeO655/CjH/0ox+O73W5ei9bX14d33nkHjY2N2LFjB4aHh/H3f//3SCaT2LJlC6xWKxKJBFpbWwEAnZ2dSKVSePDBB+Hz+XDp0iXEYjGIRCLe9+fz+SAWi3k1bWtra861yGYaqdVq1NTUoL29HUajkT0/7e9bDnQkk9bNrVu3+KF+9tlnkUgk8NhjjwEAjwxk6i5+7GMf++Cn7WiHBQX89IFI0TPzOKOtTDSO6Pf7MTU1xQLoVJQViUTQ6/XsiYgQQMcCTXgtB6KwezweZqyIxeK8eoVE7wfAivQ0rEX/ZrVaeVmiSCSCTqfjvXU9PT0YHx/PMUCSvlOr1VCpVJxg0d4TIi4A4I6Ow+GATqfjEyQWiwm2cMrlcoE3JIll8i5Uf8z+HJmgEhedAD6fr2BimQmZTMYGJJPJeIwg8zpmQiKRwO/3C06U2xF8WnWx+vHHH+ebIpVKceLECVy6dAk7duzAJz7xCfT39+P73/8+EokE7rzzTlgsFpw5c4bXhwFLta6Ghgb4fD6e6vqzP/szrF+/Hj/72c+4TEIMHafTCY/HI4gBN2/ezJot2RfC4XBgz549cDgceO2117jup1Qq89KnDhw4gPr6ety4cQO3bt2C0WhEcXExwuEwRkdHIZPJsH37dphMJnzjG99YNukqLy9HQ0MDrFYruru7MTAwAKfTiaqqKu4RZ65sPXjwIJqbm3H06FG8+eab6Orq4jiupaWFZYlJGGBxcZH3okxNTeWdmMsG8RDXrl0LiUSC3t5eLCwswGq1ssemk6a0tBTl5eX4zGc+A5PJhB//+Mfo6OhARUUFysrKcP36dd6WRbPU1BygKUXijSqVSl4PcuHChRU/5+q0u7AUIw0PD/NQk16v5wyKLi5NedFFT6fTAm9ER0rmU2W1WlFUVCQoPMfjcS7ZZMaAFouFFUOzkUwmMTs7C4lEwoE0sOSViU+YDZImJkk5yiLpAlN/l5TGCPmOb5LvzQRt4AyFQnxNiD6vUChgMBi4lZd5tGYSc0lEM7ODstpSCJVQSIdnYmICU1NTTISldqFKpYLFYuH1GcQtpCWTtN2J2p4klqnRaFBUVMTTlYlEAgaDgU+i1dYOb1sQqbq6GuvWrcO1a9fQ39+P6upqbNy4ETdu3BB4KJ1Ox10NksHweDzskf74j/8YJpMJ3d3drDoQjUZ51ezMzAyXYQwGA9RqNcrLy2E0GnHy5Mkcr0TLtTdu3AiLxYJz586hr6+PHwK5XI6PfvSjiEajOHr0qODvt2zZgo0bNzLzhEIIIjlQkZlw6NAhXsBNsx3A0tx0cXExLl26hKGhIUgkEthstrxCTPX19aitrcV7770nSOiMRiO+/OUvQ6VS4Utf+lLeI02tVqOoqAihUGhZkaf169dDJBIhHA7zQH82ysvL4ff7mQi8d+9e6HQ6vPvuu/D7/WhoaMCmTZswOzuLW7du8YNA338lfKBtO0J/fz+cTidrJgcCAdy6dSvnC1K2pdfrYTabeWiHjLC9vR1OpxNvvfUWrl+/jurqatTV1TEJILPv3NjYiKKiIhbmVCgUOUZIsSp1HmgEgYxQKpXiP/2n/4RAIMAPECEYDPLRPzExwSQCuoHZ5Im6ujqo1WpotVqMjY3hu9/9LsewmXv9aCY7H3p7e3O6HLQBq6GhgeeV8yESiaC+vh6pVAqnTp0q2IMmtTCfz1cwlLBarYJr/c477wgSDL/fj3g8DplMBqvVymtCbpf+tRxu2xPu378fTU1N6O7uRn9/P/cZl5s5oHkGWtgXCATQ2dkpSPdVKhV27dqFhYUFzMzMcPN/tSBKFRlCvov0zW9+E6lUCj/5yU8ErUA66paj3VNSUFVVhbq6Olatpb8Lh8OCDaOEbL2Z5dDW1ga73Y4dO3YgkUjgq1/9ag7ho6ysjDdrqVQqtLW1QaFQCDRu5HI5b5MKBAI4d+6coLeeiaKiIkGCQ+vVMq898STVajXbATHQ0+l0Xo9IKrGrYdKs2hPu3LmTNatLS0s5+xkdHcXQ0BBUKhWL9ExMTAgo/aQT09jYiC984Qt45513BMcbADbIzKB7JfpXJlKpFHw+37JPaGdnJ1f+rVYrt6p++9vfrvj6hw4dwgMPPIDLly/j3LlzvHHKYrHgoYceAoC8RiiTyWA2mwEs3Tiiz2d2h9xuN6xWKyorKyGTydDX14doNIra2lpMTU0JvCkp/FO1oampCRUVFQIjbGho4EU8s7Oz6OzsLHgs5tNUzK7vEXMos1Kh1+vx6U9/GpWVlfjWt76VMx901113ffB1QhokP3bsGFQqFaanpwUTZ+FwmNnS2U+czWZDUVERYrFYwSXP7e3tcLvdLLBIvdTbaQOutE2qr68P4XCYLxg147PbdvmQTCbh9XrR3d2N9957D3K5HA6HAxKJBK+99lrOE19XV4ebN29yrEWqqhS4ZxphPB7nXXQ0CyyXy3MM0GKxoK6uDoFAgL8DiZQXFxezd+/p6YHf72fRTNr/kg/ZxX9ifi+HoqIiOBwOAEuhTD6OYaGpyXxYtREODQ0x26UQKGbLBM1xEH3+Bz/4ARKJBGfYTz75JJqbm7kpT+jr62MlUerJUrZMpYDlLhatztq+fTvuvfdenDt3Lodt7fP5UFlZiW3btuHy5ctwuVxYs2YNBgYGBJNzNpsN8Xgct27dwrvvvgtgqb9cUVEhaLcRNm/ejF27duFb3/oW32Q6tvV6PZRKpSAmjUQigvCACALZD8aWLVuwfft2RKNRHDlyBMBSQmYwGNDW1sbLLEkFbTVlnGykUqkV2dAbNmxASUkJ0uk0vF4vS0UbjUaYTCYcOXLktmLGVRthW1sbIpEIzp8/X/B34vF4TvmApELm5uaYbUtrrtRqNe8eoYWIExMTuHXrFicLJpOJmTN0dMTj8ZyAOhsKhYLjGL1eD6PRyHvgCHq9ngNtUgObm5tj7h+19RYWFtDd3Y2pqSlBHEuyItkYGxvDjRs3cuI5KlxnI7tt2N3dnde7TE9P49SpUxgfH+eYbGxsDJFIBFNTU4hEIgW3RWWCZojzjXDmM57sOuv8/DwX+4Gl6cXBwUGUlZXxtb6deH7VicnVq1exsLCA//N//g9OnjwJnU4HjUbDk1terzdn6WB5eTncbjfGx8cxMTHBfVrqJ9NRQtonVquVl3sDwJe+9CXo9Xp0dXVheHhYwPnbunUrzpw5w57mO9/5Dmw2G/72b/8WV65cgc1mg9FoxJ49e/Dggw9ieHgYhw8fht/v534vFYUPHz7M5SCxWAy3241HHnkEiUSC222ZOHjwoKCEZLVaEY/HV6US5na7YTQaBSygQvMeZWVlKC0txeDgoCB5UKvV+PrXv45wOIynnnpKYCD33XcfPvnJT2J8fJxHb/v7+7mUlEgksGvXLrS2tqKzsxMnTpzISzam0QSNRgONRoOBgQF+H9LoUavVSKfTgu/d2toKk8kEl8sFiUSCn/70pytek1V7wvn5eW7NUDGYxi9LSko4e8xM3+kIorkD4qQRc5oC9FQqBY1GA6PRKCg30MqIfAtpKMgnz2s2m2E0GrlITqrzOp0OEomENQqpCEtzJlTHpNek7I/WK+RLjLRaLSseAOBC7mqMkEgBmchHCgCW4j29Xp+TVITDYWi1WqaiZYK+K83DZH4/k8mEWCwGhULBe1/oNMqG1WqFxWKBVquFRqOB3+/njk4ikUAgEMjrNWlxEbUcV4PbLtFIJBIu4IrFYm7Sh0Ih3Lx5ExMTEzlSvsDSk7Vx40Y88cQTmJ+fx3PPPcdrx4Dfxzs/+MEPOJj/+te/DpvNhsnJSczMzODb3/42vx6Jf5MsR3FxMWKxGI4cOYJUKoVPfOITuO+++3iOwu/3Y3h4GL29vfjrv/5rAEsUp23btrGxBQIBeDwejI+P52TvmcjWpKGpOZJGqaioQElJSY6UiMFgwJo1a2A0Gplj+Nvf/rbgZFxpaSlMJpMgDler1bDb7WhpaeEh9WAwyMJLNEM9NjbGhWyXy8VMchIvmpqaYg6kTCZDS0sLFAoFRCIREokERkdHsbCwgI997GO8Z+X73/++4PNRz5yM2Gg04plnnsHLL7+MX/7ylwD+g4rVNHxEIOOUyWSw2WwFn2oS+GlsbOSjJfPopidUq9WyEZIuoEQiyaEKzc/Ps4xIOBzmvigdLUajEW63m1uLdLxkqitkbho1m828H245XUUgN26KRCKIxWKorq6G3W5HeXk5iouLc2qE1AZUqVRoaGhATU3NssZOixQzUVpaCplMhtHRURYkIEm2QCCA6enpnFjP7/ezShkZdWanRaVSYePGjVAqlZiZmUEwGMTw8DBnvjU1Neju7s6RIs5Wq9BqtUzHux28L81qOgoA4Ny5c3jttdcALNG6svl1mzZtwtWrVxGJRHD16lV0d3fzsr5MzZjW1lZs27YNw8PD+OlPf8qtMuoKZItXBoNB9Pb25i3CqlQqHD58GGfOnMHGjRuxe/du3Lx5Ey+++CL8fj9sNhuAJeM5fvw4Nm7cyApYNHA1MTFxW3vwPB4P1Go1XC4XZmZmMDAwkKMyNj4+joaGBlRWVsJoNPIIQSHQerANGzbAbDZjZmYG4+PjMBgMrExBrcPp6emCZRgaLy20k4+O9HA4jM7OTng8Hr7e09PT6O7uxtzcXI6e0Jo1a1BVVYVXXnkFwFJCdvfdd8NkMmH37t2rHji7bSMk8XE68zOzoOyYSCqVYuvWrRgZGcHU1BRP6c3OzgoMh/rC9fX1aGxshMPhYPJotsxudXW1oLxRqAtA5Qkqw1y+fJmPtd27d8PpdKKzsxPd3d0oKytDMpnk+RS9Xo+9e/eyYFAoFMK5c+dWzDqJkj88PIyenh7m5GUaB+l30wRhplctKytDKpXi2itNv23fvh179uzBG2+8gZ/85CdQqVRMfiAlhXwG2NjYiNnZ2RVj1Xg8zuTZzAlJACwnEgwGodFoBA2E0tJS1NfXsxECv18H/KMf/YhriSvhtko0iUQCvb29uHjxIisvZJYE7HY7IpEIJxd6vR43btwQuP5oNAqNRoM9e/awdEU0GsWLL76It99+G9PT0wgGgzznm73yIZtCnj2QvnnzZjQ0NKC8vBzT09MoLi5mHT0CMUaIbUyTdR0dHezVaTeIxWKBRqNBaWkpbt26lbMlkwbmgSUPTCoKN27cgNPpZJItfe6ZmRmcPXsW/f390Gg0sNvtcLvdnLBEIhEWorRYLDCZTALxJpFIhOnpabz22mu8xqIQGhsb0d/fn9cIVSoVqqqq0NjYyCqrEokEa9aswfz8PJ90i4uLOHv2LCYnJzE/Pw+FQsH3Ox6PY3JyEhs2bMD4+DiThh0OB5577jmoVCr8/d//fcHPx/dwxd/4//E3f/M3mJmZYTYtKcaXlZWx1JrdbmetFlJnyA66aTvn3XffjVgshnPnzmFsbEygFQiAeWkrxRdlZWXQarWwWCzswVwuF5NK+/v7cfXqVcHMBdHHpqenWd5kcXERp0+fxuHDhyGTyfDoo4+yASaTSfh8PsH61rKyMmzduhWjo6P45je/CQBck8wMSXbv3g2/34+Ojg4m9w4NDXFid++99+LP//zPcfXqVbzwwguIxWKQy+UQiUSw2Wyw2WysfkYgWb7l0NzcjNbWVsTjcZZKIbhcLjQ3N+Oee+7BY489hpGRERw5cgRisZhnjGlOfHBwENevX2cxA71ej9bWVt51PTo6iieeeALt7e04efIk3nnnHYyPj+OZZ55BMpn8YI3Q6/UiGAxye0itVjNxMRgM8mQ+MYQL4c0330RZWRnuvfde6PV6RCIRwZEql8vR3t7OR8NKWn6Dg4O82NpkMsHj8bBCLHH2XC4XZmdnORMfGhpCIpHgzfVerxd9fX3MtaNiazwe5wFvKksRa/rGjRssLUxQKBS8epX+m9SraASUhorKy8thsViwuLiIU6dOYXR0lJnYlIzpdDpebjg/P4+rV6+uWlrj6tWrBWNam80Gh8MBj8eDw4cPw+PxMPmYstnBwUFmb5P3LyoqYsGnSCTCu1O6uroQCoVw4cIFXLhwAQaDAfv37//gY8Jr164hmUzyLCuBVAZWWo9AIK3qRx55hGUlhoaGcN9992HXrl2w2WwoLS3FkSNH8PTTT/Pf6fV6zi6BpToeBdrhcBgjIyMYGRlBZWUl0uk0F6uLi4u560Je+b333oPBYOAjOpN8SQyWrq4uaLVarF27lgfb5+bmMDExkbP2i8Tk9Xo94vE4azXTWGZmr5yUzdatW4eNGzfi9ddfx7PPPguxWAyDwcCsJIlEwgNihw8fzkuOAJY8ntlsxvnz53MMNJ8BUty7Zs0anDt3Dv/4j//IYxFarRY1NTU8mJWNhoYGRKNR9PX1IZlMwmazQSaT4dlnnxXUccPhMJ5//nkOd1bCqo3wvffeg0gk4iOKnobMTOp20N3dzWUFAEwHoyJ2Zhyp1Wp5mk4mk624EyQWi3FtkTRtMmO5QuwcqVQKi8XCygnhcBg+n483aRLrWq/XC4xwYWGBZUJMJhMzrynJyOb70aCXyWTi0pNUKmXRJIlEApFIxN5xufW3JATldDoxPT294kwOCVnRrAtpHi4sLECj0XAokA8ajQZKpZJZVMRezw6ZiD2+0ilGuO1itVqtxv79+1l3JTPgL6Rgn4ndu3fD6/UKCrA0vphMJlmDMBP79u1jrxkIBATFcKvVysahUqmwdu1aGAwGvPbaa5wMKBQKlJaWYufOnUgkErhy5QpisRj27duH6upqLvbSeGN3dzcXW7dt24bq6moe9llcXEQwGOSY8MqVK3jqqacALO1r3rZtG2ZmZnjb/fj4OJRKJZxOJ8dQAPC5z30ODz74IH71q1/h3/7t39DQ0IBDhw4hGo3i8uXLGBsbyztLkw3adlVXVwe73Y6f/exnKy7QNplM+MhHPoLx8XEMDAwsq2cDLN3X2tpabNmyBTabDS0tLRCJRLh27Ro8Hg9u3ryJyclJ9vgqlQpf+MIXoNPp8N//+39f8TvcdomGmDKk4J4JnU7HbOt8kMvlaGho4GSBoFQqMT8/X7DOReyM7BgMWMrIqYMRj8d5Wi2TlUJtOkqcSF2L2oK0uDsYDObUOcnoSIuFtlrZ7XbU19cLmC4UX9IMCXVikskkGhsbEY/H2QjJg9EOF0qWYrEYJiYmVq2cGovFuJ6oUqlQVFS0ohFS3TBz2H050GQg8Pt2KdWL4/E4LBYLx8q0hT7foshCeF9LtzO5a0DhaTYCEVqrq6uxa9cu3LhxA9/5zncALB21VE6Zm5vjFQiDg4Mcwz3++ONwOp34+te/zq/Z1NQEqVQKpVKJrq4uQVE4e+3qpz71KSwsLPDMCf2PPMC2bdtw8OBB3LhxgyXc7HY7twNJPXViYoIHoOhBJI4igVbKknos9b6rq6uRSqVw7do1RCIRPP7449iyZQu6u7vR3d2NoqIibsV5PB7MzMzg6aefXpFPSYNY9Bl2796Nhx9+GO+++y7voVar1RCLxfxaDocDa9aswZkzZzjLXu4e7tixg+vCExMT7PGeeOIJtLS0IJ1Oc4+axNppoc9XvvKVZT8/8D6XbmfWnTQaDe655x4cPXq0YJxmMBjQ0tKCoqIiGI1Gzqrp72m2lepxGzduhFwuZyOkGdxM7N+/H3NzcxgaGsq5UZlGodPp0NzcjOvXr6Ovrw/pdBomk0kQE166dAnbt2/H2NgY+vr6YLFYsHfvXpYkpqm3kZERmEwmWCwWjI2N5a2/ZSYHKpWKl8rQvHVxcTGSySQTKfR6PaqqqmAwGDgeI+/e3NyMy5cvC16TRm7Jm2d7bplMhkOHDmFhYYGNkFZmXL58mTeF0iYuQltbG6anp/NKeZjNZgQCAczOzgqSrPn5eY6RVSoVSktLUVFRgcHBQbzzzjur9oSrNkJ6wmlJX3l5OWprawGAa2j8ov+/xNjw8DDC4TCn9jdu3MDrr78uOFLT6TSCwSDa29tZGOm1115DKBSCw+GASqXKKeMAwNGjR3mUMR8cDgdMJhPGx8fxxS9+UfCz7IclHA7jjTfeQCAQ4FldSm6ee+45BINBVuXyer2YmJgoyJfL9MI+nw+9vb3QaDSYm5uDVCpFLBbjGWCfzwe73Y6SkhIoFApIJBJ4PB68++67CAaD2LFjBw4cOIB33nkHFy9eREtLC3bs2MEaNwS5XI6SkhIYjUbMzc3h/vvv5+1aSqWSQ5QDBw6w4isleceOHWM9xOx6JKG3t5fvJbBUmzWbzTAYDFyDnZ2d5dIPOZXVsmhWbYR33nknIpEIs1QaGhrw8Y9/HN3d3fjd734n8FSPPfYYGhoaeJLOZrNBLpdjeHiYvZtOp+OSRjAYRGtrKx566CH8+Mc/xs9+9jOo1Wps3bqV52/D4bBg+3l2EZwG86lVdtddd2Hjxo2rCoyBJRVYWphDe4s9Hg972bm5ORw8eBAdHR3o6urKm4DR8ZvZo52cnOSWGFGzZDIZBgcHMTExgS1btqC5uRkAWPLj2LFjiEaj+NjHPobt27ezF92zZw8efvhhJJNJgREaDAZ87GMfw6ZNm/AXf/EXzE0kAkc4HIZcLse2bdtQX1/Pi4YUCgWUSiVnskqlEvX19YhEIoLvkClgAABPP/00nE4nfvOb36Cvry9n04HL5cLdd9+dsyumEFZthLQNiDJRv9+PN998E4lEAjabDYuLi3w8HTt2DNevX2f2hlgsRjKZFBgq6UVTSeLmzZs4deoUenp6AICPKolEwjMTJDieL04i+j91cGQyGTweD6qrq5lAajKZEI1GBccbdU5obSsN9IyOjgpKK36/H7/4xS/ydiqInEuehLyhUqlESUkJ068SiQRu3brFD5RcLkd3dzemp6dhNBpRUlKCiYkJHh99+eWX0dnZiQsXLmBoaAjnzp3LqTsCS8b74osv4vXXXxeQY6nfa7VaYTKZIBaLEYvFMDg4iJmZGVy7dg0dHR3MfiG6fub3tlqtaGtrw9mzZ5mVfubMGZjNZk6gMg2woaGBWT2rZdPcdkyo0+lw4MABnDp1CqdOnUJVVRU+8pGPQCwW85QYaQQCS0PeJE6eeWTT+geRSASJRIILFy5genqaZSOSySSsViuzb4Dfb58sFKzH43HU1NTA7XYjFothbGwMGzZsQGtrKxYXFzE7O4vZ2Vn2ogcPHsQdd9yB3/zmN1ycpW30+XajZA4t0QOk1WqxZcsW5un5/X6sWbMGer2emTkqlQpmsxnz8/NcVCaNmxMnTmBsbAzFxcW4++67EQwGEY/HEQgE8POf/1zw/iMjIzhz5gwUCgWqqqoALD3M2UvK6Rik/ckNDQ2w2Wzskcn4rl27hmg0iunpaVRUVLAaRCZaW1s5MSSW9G9+8xveopVdbz106BCmpqbQ2dm5ai2a2zbCqakpnDlzhqvxpDVYSKlzZmYGXq8X165dy5u4kAdTKBQ8/RYIBFhCNxqNMrO6vLwcDodD0EoSfBmpFD6fjyUoSJqCNgBkD0f19fUhGAwKvEdxcTF7DGAptkwkEoKRRpfLxRInFFYoFAqW/SDixfz8PHw+H3ckaOENAK7PZQ6Zk/EX2qNCK29pRS8RULM9TlFRERfbvV4vL0Wn7VJEgSNmOlHz8r0neeVM7+jz+RCJRJiPmYne3l5IpdKC0iv58L6yY5ouo1LNcpy71ahAAUs3e+vWrdi+fTurkp46dQrJZBIHDx6ESqViGpler0dHRwdX+wFwp+LatWu4fPlywUxdLBajvLwcyWQSN27cEBigVqvFnXfeyatzFQoFtm7dCpPJhJdeegkXLlyAw+FAUVERH91EzYrFYpiammL1B6lUioGBgWUzxMwHIhAIYHBwkI0QWCq3VFdXs4otZeREAiHPlt2j3bRpE06fPs3vffnyZdYYzERlZSXuvvtuXlSUT7yAZlQydRCz18S5XC40Njbi2rVreOmll9Dc3Ix/+Id/4K0LK+F9GSFBp9Pl3RfyfkCi4CS+Q/opmctqaK9HIBBghrdKpeLto9mE23yg6bp8wz007kgsZK1Wi6KiIlgsFrhcLhQVFfG2TRJ/os9OPWOfz8fb2PO1Bo1GI0QiUc5DYjabOWnRaDRIp9MwGo0sN0ea1QBY6gRYIspmF7aj0WjOe+f7LJQ9h8NhXi+WjampKfT29i7bJhWLxYIl4bFYjMkNq8Gqi9X//M//DJ/Ph6997WuIRCKwWq3YsmULu+q+vj6+MNXV1XC73SyaaTKZcM8992BkZIS3FRF27NiBnTt34kc/+lGOilNpaSlcLhf+6I/+CHq9Hv/tv/23nKeVaPlkVPv27UN9fT2++93vruoCEDITHqVSiaeeegputxtr166FVqvF888/zwG51WqF0+lES0sLvF4vfv7zn2Nubg5NTU2wWCy4ePEirl+/DoVCwR68sbGRa6GpVAodHR0YHh5Ge3s7tmzZwgYhk8mg1WoRjUZx+PBh3Lp1i/fCZAu8Z8Jut+MTn/gEfve73wkm+RQKBW8hzay77ty5E6FQiMWQMpsPhbB//37Mz8/nJTc0NTVhfn6eNwHcc889fB1Xwqo9YWtrK7xeL0pKStDf38+MFoVCAaPRiIWFBTYQ0tYj1NbW4mMf+xhOnTqV0w+1WCw8MpoNijFpIWO+40IkEgm8mkqlYvr+akGtOzqaqQ1GU2k0fE/ej7Jhi8XC687m5+dRVFSEuro6nvHQarUoKSmByWTiLJlqcqlUCi6XixMnio1VKhXcbjdCoRCOHDkCj8fD3385OJ1ObN26FZ2dnfxvRGXL3lpqNptht9sxNjYGn89XUEMoG62trXm5nwD4AdbpdEgkEujv7//gPeHatWuxuLgomOqn5S6k7k6aKxRgE03d7XbjhRdewL/+67/ie9/73qo+GLBUm6S4IhwOC2jkyyFzIEen06G9vR3T09M56hGkwk/josPDw+js7IRGo0FtbS2r6IvFYpbVqKurw9q1a+Hz+bjUcfz4caRSKXz5y19mEc+rV6+yFuPo6CjPTD/44IOcvRPbhFg1tEHeZrMhEAjgG9/4Bu9r3rRpE8bGxjAwMACdTge3282rLIAlitaWLVvw5ptvLnttxGIxGhoaUFpaCq/Xi6mpKe7ahMNhnDlzRtBMkMvlLF9CazKGh4eRTCY5HHM6nTAajejp6ckZsvpAp+3yjSXSkkVg6Qi+7777kEgk8MwzzwiUmvx+PwwGgyB7Lisrg06nE2Sd2bvWSktLoVAocOrUqdua6A+FQtz2Wrt2LTZv3owrV67kNcKamhqeWKMugs/nw7Vr13gvCbCUOFmtViSTSajVaty6dQtHjhzB3Nwcx1tEjrBYLCgrK2OqVGZ77/r16xxzKhQKDAwM8HrW0tJSKJVKVmelpC4YDPJIQnt7O/R6PdcUaQWb3+9fdjUYsOSZackkzaWIxWLenRKPx6FUKnlXSjgcRmNjI+rq6tDf349z585BJBIx97CtrY2pb5FIJEcOZbV4XwQGAmkukwQukTJHRkYEAzzV1dXYu3cv5ubmcPPmTZbZCAQCgrWt2TIdxcXFAmUDkUiEkpISAb/Obrcvu+ONNsxTQpJZn2xqaoLdbkdnZ+eKGy8VCgU3/pubmwXFeVosQ/K5g4ODGB0dZQZNpui4zWZDZWUldu/ejbq6Ohw/fhzHjh3jEVWS943FYvjrv/5rhEIhlJaWsie8ceMGioqKsG3bNiSTSVy6dInF5gvVT2tra6FWq7nlSqs1ysvL0dTUBK/Xi97eXiSTSRY1cDqdMBgMaG1tRUNDA3p7e3HixAlmGqXTaf6+Go2GT0SNRoOFhQWMjo7ytoeVcNvZsUKhwL59+7iGR8XSkZERQalGJBLhox/9KNavX4/XX38d//Iv/4L9+/fj6NGjGB8fx5e+9KWc0o5erxdIkGUHyzqdDrt378aRI0f4b9euXcvLYxKJBGpqaqDRaJiJTNNfAPDAAw9AJpNhZGSEM7hQKLSqlauk3koZPO0FsVgs2LBhA1KpFL72ta/hxIkTmJycLEjFmp2dRSKRwEMPPYQNGzZwkZmK9gaDAevXrwcArFu3DmfPnoVYLMbw8DDHYkR7czgcaGtrg0wmwxtvvCEwwuLiYjQ1NaG8vByHDh1CKpXCP/3TP+Hy5cv82bxeL5qbm3H48GGOC+lkq6+vR319PZqamtDc3AypVIrp6WlMTU1hbGyMdyoTTCYTPv7xj+PP/uzPePTjP6xjQi0oGpJWqVRsPJleLZ1O4/LlyywyRCOOly9fRiQS4WU1L730ElOIlmMQA0vH3XvvvScwXp/PJxj80Wg0eetTEokEVquV9RNJ2HI1fDoaMtdqtVhcXMTw8DDzE71eL0ZHR7G4uIj33nsPAwMDMJvNKC8vR39/f46Hpq31v/vd7zAwMIDTp09jZGSERS8TiQROnDjBCyarq6u5fJO5MLG8vBwajQajo6M8G5JJnqABe6lUijfffBMLCws4d+5cztq23/3ud3m1pXt7e/kaTU5OIpFIoLi4mGVJvF6vYICKtLVpZ97ly5eRSCTw6KOPrnh9b9sIDQYD6urq+GaUlpZyaSJ7I/rAwAAGBgaYjCCXy/HTn/4UxcXFeOSRRyCTyWCxWHD58uW88YzVakVJSQkeeeQRaLVafO5zn8tx7yMjI4IamMViQXFxseB3xGIxmpqaUFVVhXg8jhs3bjB7B1h66uPxOHw+X06Wvm3bNl4RRpuS+vv7WQEhm+kN/F5A8nvf+15OO40Gp2i0lBAOh3Ht2jUoFAqcPHkSSqUSmzdvxu7du7lNSN0OOo79fj9+/OMfY2FhAS6XC7W1tejr62MJugMHDuDatWv4whe+UPB+kgLE+vXr4ff7+fOOjY1hbGwMJ0+ehFgsxr59+/Dnf/7nPEs+Pj6O7u5udiCpVIoNvKenB9/+9rcRDAb/Y4xwfHwcV65c4S1EVFqgrUzZIaZYLIZOp8Pk5CSvSyUhRqlUyu2qfKCsdXFxMUfJn5DZCgPA+0wyQRJz1MOmJYkWiwVqtZoHyNPpNPP0aGqOCs+0Ho1emzoc+Qq8EokkL8+RBIhoECrf3wFLpwiJthM/j2ZYqI02MzMjSAwpJrfZbBgdHUUqlcLFixeZELISyMizQe1UCgkAsJRzdp5ALVLq0xfS0s7GbRthPB5n8cr6+npWa8rMXh0OB4xGI5544gls2bIFTz/9NA4fPgy5XI4tW7ZAq9Xi9OnT8Pv9ePXVVwsaYWNjIxQKBZ5//vmCe3uzJ8w6OjoEtTK73Y6dO3fCaDSyAVIWF4lEmMVNBk5rKvbt28fEimvXrqGmpgZlZWVYXFzkmJJ2sRA2bNiAnTt34re//a1AvIlAvD+LxYJr165hZmYGRUVF2Lx5MxYWFjA5OckMZbPZjLvvvhvNzc348z//cxw+fJhfp7+/H11dXYLOj91uR01NDRMbTp06hf/5P/+n4P3VajXcbjcnKLS8iBjTarUau3fvhkKh4GRvw4YNaGlpQWdnJ77+9a9jbm6OQwypVCpIJkkZlpjhq8W/q20XCoX46fb7/ewFqZ1msVhYhxBYaufQ5BtNzC1XKCUi7c2bN1etXQ0Ia1PUb06n05idnRUE0yTWmflEEyeQdnwkEglmttBnslgseYvrRGYoNJieSqWgVqthMBig1+sxMzPDHRhaoEjD+LSNCcgl4QLI8bJU3qI5mHynBgkiUVJJJxdJzFG3RqvVQi6XIx6Po7S0FFVVVbh58yZmZ2cF9yH7dCLyyO0u4V51iaampgZ+vz+vhRcaoSwuLkZFRQUmJiYwPj4Oo9HIkm4KhSJn6o4/lEjEk2ujo6PLtquApRjs7rvvRiKRwAsvvJDz89bWVsHwO4FmS958800cP34cjY2N2Lt3L9LpNBYWFhAKhdDR0YH5+XnWOmxqasK6detw7tw5/PrXvwYA5gZmU+NpJVjmtfnyl7+Muro6/N3f/R170mypufb2dlitVr6u2fFjJnbt2gWTyYTBwUHeExOJRFBRUYEtW7ZgYGAA77zzjuBvXC4X7HY7j9LOzMzwBGIqlYJKpcKhQ4c4M16zZg3efvttfP/734dYLIbD4UAgEMgbx2dvA1iNea1aw6u9vR3r1q3L+7NCXmp8fBwnT57E7OwsSktLoVKpMD4+ztlgoQJ0RUUFHA4HkslkXv1ksVjMo57AUu1t37592LdvX97Xy2eAwFLYUFpaipKSEtbVdrvdsFgsvL4rGo0ysWFqaoo7MGvXrgWwdMRu3rwZbW1tgtd2uVysWZgJtVoNk8kkaGllS81RjH358uUcA8pGeXk5ampqEA6HMT4+Dq/XyxukDh48iL179+b8DZVoqDZpt9u5pplOp7G4uMjVBCrkk85jeXk5Nm3axMshs7HS+Gg+3JZw+molKLKRGUAD4IU5lLAA4GyQWkkUa2aWOCg5yJSDUygUkEqluHHjRsFjUKFQ5GX7BAIBJtG2tLRALpfj0qVLCIfDPKPx2GOPwWw2o6enBxMTE6isrITVakVLSwv+9E//FCKRCDU1NYjFYnjppZdYp/DAgQPo7+/HpUuXBFNsk5OTMJlM3HXIV2DO7s3SEU7D/JkoJMd75coVvPHGG3mNgpIrq9WKtWvXQqlUoru7mzdqAUtM+l/84hf4+Mc/jgcffBAejwfNzc1M+5JIJLjrrrvg8XgEn7e6uhrj4+OrHnICbsMIaT+wwWDIO6Ducrlw8OBBhMNh/OxnP1v2tWjlvVqt5qXSu3fvxrp16/Dee+/hxRdfFHyJJ598EqWlpbhw4QJu3bqVIysnlUq5VpcP1P+kz2y322EymbC4uIienh5YrVZUV1djenoavb29nOU5HA7cddddaGhowGuvvYZLly6huLgYBoMB1dXVuPfee5FMJiGXyxEMBrFp0yZcuXIFu3bt4gC/r68P8/Pz7O1o27perxeMHiyHtWvXYseOHSxMf+zYsVW1yM6cOZPXyClGNxgMqKysZCWtdDqNxsZGgZDVCy+8gKqqKm75UWlOLBbj4x//ONRqNf7mb/6Gtx9Qn76jo2PVCv6rNkKz2ZxDYACWPFh5eTl0Ol3evSMGg4GHu2ndAQXAALhH2dvbi5s3b8JkMuGP//iPcevWLW7GHzt2DBqNBteuXcsxfkpwSJSdPJ7T6YTT6eQVDyRfQW2rmZkZHhifmZlhzcSRkRGWAwmFQnjxxRdx7NgxLCwsIBaLobe3F6FQCIFAAOPj41hcXMTo6CgCgQCuXLmCQCDAJNL5+XmUlpbCaDRidHQU6XQaV69eRW9vL1KpVN7kQXBzpFKUl5dDpVJheHgYZrMZRUVFaGxsXJURhsNhqNVqXi9BHQwiT4RCIXi9XkQiEVgsFohEIh7yIlgsFsTjcajValRWVvJMSTwex9zcHObn57FmzRqW6Lt8+TL0ej327NnzwQsiOZ3OvCxpu92OLVu28CB4ZrZbWVmJuro6PPTQQ/j4xz/Os7vEsKFa29zcHF555RX4fD7cc889+OpXv4oTJ07gwoUL3NfMRnNzM7q6uvhGdnV1QaVSYc+ePSgpKcH27dvR2NiIb37zm3juuecQiUTwyCOPwOPxsJb01NQUioqKMD4+zqvM6Lgzm80IBoM8pN/W1obGxkZcunQJb775Jq8V83g8ORn+xYsXcfPmTVRVVaGtrY3Z4NPT0/jhD38ouD6Z2LRpExYXF9kL3Xnnnazs393djfXr1/NGdYlEwiyaUCiEqqoqWK1WgQfy+/2oqKjAww8/zMd5MBhER0cHBgYG4Pf7eVjJ6XRyHJhMJlFaWorR0VHWYNTr9WhubmbBdJ/Ph4GBAYRCIWzatAkHDx7Er371K7zyyiu8uesDX7pNPLhMuN1ulJSUQCKRYGFhQZDp0iLm7u5uTExM8BGeTqfh8/lw5MgR+Hw+uN1u2Gw2lJSU8Cra69evs8BlKpXKW6Kw2+2orKwUZKSZokXj4+Ms/EOflZYm0ob0lpYW1NbW8hwG7VimG5gZY05MTHDnQiqVIhgM8vfKB1I41Wq10Ol0KCoqykmysvfHEbOF1tLS0Pz4+Dg/cERTm56exsLCguD9s/fS0Z4/ItfKZDLOuElnm8Y95+bmEI1GMTAwwH1y+h50khDdi048koQhFQliRNF+5mweYyGs2giLi4shk8nw0EMPwWw2sxrX3NwcJicnBZX54uJitLW14dVXX2UNvF27dvHw/KVLl7jgff/99+OjH/0oS4XEYjF861vfgkqlws6dOzE9Pc2lEGDpeGhqakJNTQ2zlaenp/HWW28hmUxyl+WVV17BxYsXcccdd+Bv/uZv2OsqFAp89atfhdFoZDoZERhKSkrwt3/7t+jt7cWXv/xlwfefnJzE5OQkzGYzduzYAa/XyzHoJz7xCSiVSvzrv/6r4G9mZma4pFVdXQ2pVIri4mJEo1EWd7Lb7di6dSsmJyfR0dEBiUSC0tJSXrkrl8s5bqSbnQ+Li4tIpVIoKyuDw+FgGTsavFKpVLwyg/r5ZMQejwfXrl3D0NCQ4MGzWq08OXnlyhWOxYPBIHeUEokEKz0QRkdHc0Zml8NtKTDQE5qJQCCA0dFRwVFNU/4EWspM7j/zeKWVDTS5FQqF4PF4+CZk1pmUSiWXbsbGxmAwGHidBTF66Wgk4iXN3vr9foyPj0Mmk8FutyOdTvODRbIkRKvPjjszeY5zc3M5DBmiMi2HyclJznJ1Oh1z8EhHkfYri8ViKBQKyGQy1jJcDaRSKdf4iFAyMTHB5SVaOUaSvlSQpg0Bk5OTOe+VWdEIBAIIBoMs2CSRSFBXV5e31UdM8OzyVCGsulj9gx/8AIuLi3jllVeY02a1WnHx4kVB98BisWDLli2wWq0cxJI+9Ntvv12w8ExDSrQ2InNgfHBwEPF4HBs2bEB5eTleeeUVDp5pq1RbWxtSqRReffVVQRlDJBLhs5/9LLq6unKKq5/61Kdw4MABjI2NYWJiAhMTE+jp6WGlK7FYDKfTCbFYLPhbmUyGqqoq7N+/H+l0GsPDw6xcKhaLodFooFKp0NvbmzPOsHnzZlRWVrJ4p9/vx8LCAqanp9HT08NtO5lMBqfTCZlMxsIDwNIMTTgcxtDQEEQiEZxOJ4+bJpNJVFVVobKyEkNDQzh79iwUCgVqamoQj8d55qeyshIbN27kDsrp06f5vlDlIHvAXqfT4cEHH8TQ0BCOHz8OAPje976H9vZ23HvvvYJS0ObNm/G///f/hsFgwPbt25c3LNyGJ6Q4glZAkCp+pgHW19fD4XDwxBstb/H7/RgZGck5SkwmE8d7mSwM4PfEBBIwp9iKCAaZv5dKpaBUKllFIRM0vpmvXtbX14fW1lbI5XJUVlZiYmICV69eZQFxvV7P67EyQYP81dXVPJzv9/uxceNGnkkGcrcZAL+XC6bpvf7+fkxMTCCZTEKr1QrmiEk0NBOkduH1elnNValUsqBm5t5AtVqNZDKZU77y+/3spYj9TaisrERRUVFelYdoNCqofqjVathstpyVshKJhEcXVoNVe0La9p75IWj3Gbn/YDAIpVKJ9evX8847s9mMn//858sujVkJpGpKiVG+7gctccmccciWiCsEk8mE4uJiwQjDwYMHUV1djdraWsjlcnznO9/B5cuXIZFIeD9daWkpPB5PjofV6XQoKyvL2QEMLMXLpEQmEom4LgksdaUkEgkikQizZSKRiEBvUKvVwm63o7GxkQfNEokEjh49Cq/XC5fLhaamJl5cSQt2CqG9vZ05g/QwisVi9nb5IBaLWaTeYrHghRdeyFs5IWNcCav2hPm+iN/vR1lZGfbs2YPJyUm8+eabCIfDTN8nD7aSaONKoGHyycnJgk9XNiHW7XajoqICJ0+eXPGJzCc/bDab4Xa7UVNTA5VKhTVr1mBsbAwWi4VXz5JCaTYy9xETiGw7Pz+PqampvK1OGoyio9Xn8+WIghKZYseOHdBoNIhGo1zvA8BsGMJKMeXw8DAsFgu2bt3K14KYNYX805o1a6DT6dDV1ZWj7ZOJ1ZJOVu0JXS4XkskkHzG0LJHiJ6VSCavVCoPBgHXr1sFkMnHw/frrr3OR2263Y3Z2dlWN7eWQeZQDv5cNJo7jzMxMzg3IHqTK/G41NTUCcmprayvcbjcPH128eBEDAwOsgAD8vnaab76FykAEytrNZjPEYnHelb2bN29m7xiJRHh2JR+NjUYB6BTKHCwjPPHEE4jH4+ju7uZyCsXbtMcOALPDgd8nWcQ6pyI3fWedTod7770XCoUC3d3drPxfCB/otN1dd90FiUTCAj+3bt3C2NgYzp49y0/rHXfcwcwZhUKBmzdvor+/H3K5HC6XC+vWrcMf/dEfobe3F//3//5fweuLxWIUFxevSPEHlsodBw8exLFjx7h84XQ6YbVaWZEh83V27tzJcw9zc3Msq1ZVVYWKigoBD48MkUoWRAUDwMNCBJIGzgfqCJEhUv+ajtF8RkjSIpThy2Qy6PV66PV6iMViQU00mUwK5mfyYfv27VCpVFi/fj1rBgWDQTz22GPYs2cPDh8+jGeffVbAiA+FQgiFQjCbzfw/atX6fD4e+gfARNtM7Ny5kxVbP3B9QsrAnn/+eYyPj/NFzT4uMoeOpqenuThNjBTSlaayRKZnKtTGyuQjAkukzmeffZa3H0kkEoyNjWFychJSqTTn6fN6vZienobf7xfEiDR+kEwmUVRUJOh8qFQqKBQKjI+Pc9squwxjMBhYNjgb2XxDqjMuLCwULOdQy4y8aFlZGUwmE/eybxeXLl3iOJmkPlKpFPr6+mA0GnHkyBEBWTYTJMqUafikUT0+Po5UKoXr16/nzKfQQ0wdmNVg1UaoUqmwsLDAHyo74CdVAY/Hg7fffhuBQADl5eVwOp1MJPV6vXjrrbcAAH/2Z3/GS7apwh+LxeByuZhvaDQaYbfb8dBDD0Gn0+Hzn/88z5jQaz755JOYnJzEyy+/nPOZKysrecfJcoXTY8eOsboAwWAwQKlUcixMIkDFxcXYtGkTgsEgDwCl02lEIpG8m9SzkS+GFIlEqKiogMvlQiwWw5o1a5BOp9Hc3MwE2nyUtmxs2LBBwGj59a9/zdOQBNpffOvWLd5QkA3auZft5ak163Q6EY/H8w5IEQop6ObDbTGrl7PsdDqNaDQqiB9oIffIyEjOxSdFVXLZFouFSz4zMzOsak91QoVCkTfQpZ5vPgwNDa1IEgCWHjAqhJMHy5eBi0QiLlPRbE0qleKdILcL2o+cyWgOBAJMKqDyECntLwdqJWZCrVbn/B3ti1lune5yCQWVf97P9y2EVRthOp2GRqNBeXk5hoeH4Xa7UVZWhvfee49/Z2ZmBiaTiY/DTZs2Yc+ePaivr0dXVxfGxsbQ2dkJq9UK4PdjgsBSqeDQoUP45S9/if7+fvj9flitVgSDQT4ypFIpbDaboOf64osvQiqVoqGhAWKxWFBmWY0BAkvzvSRxW1xcjIsXL3LSU11dja1bt3Kv9PDhw3mp/ZnYt28fDhw4gOeff57lPwgSiQRVVVWw2+3Q6XS8+ZS2GNAkHwC89dZbKC8vX3Z+t7GxETqdDhcuXEBvby/sdjvWr1/Pxn3t2jXBkUoCnNnf4dOf/jTm5+fzMtMJe/fuhdlsRkVFxW0pYqyE2+IT0pbwzGA9EzMzM9w6isViXBClpr9Go4HD4YBer+fjjZ5e2iKe6W2pwU4gsUvaqEQ/o3iJjJRoV6uFWCxGNBqFTCZjwXUyQspo88mtFYJOp4NGoxFsKSCQJzGbzTCZTJidnWUyASD0QrTkkD5jPpAXp7+LxWK8T4ZChUyQ585uPVqt1py4M7tMQ+JP2W3afy/+XTIghbBv3z7U1dXxkj4ahAaWpOBo3Rb1k4GlwvehQ4dw/fp1dHR0QCQSweVycbM/E3K5HDU1NQgEAoKSCbCkslBXV4dvfOMbq/aEMpkM27ZtQyAQ4P0byWQSMpkMJSUlrHK/HDQaDZxOJ1QqFaampgpOBxLuv/9+tLe347nnnsPly5chlUrx6KOPYmxsjNtrGzZswIYNG1hHur+/HwMDA7BarTh48CCCwWAOeQDIr82dCdpWSqMLOp0OjY2NvG2AQAP3ZrM5rxJXPmQO6AMfcIlmOWQv1zGbzaisrMSFCxdw6dIlwQeheGJkZERgJH6/H8PDw4hGozCbzSyFm68EQk878PsNUwSr1Yr6+nqUlpauKlEAlo4o4jl6vV7YbDZWzR8aGlpxekyj0cBisXCJKN9mATIM8kB08+kaJBIJzM/PC2I1mlakfnppaSlEIhEqKyuxbt26golBduGdetHU4qT1bdSJIlWK7JiS5E5qampWbYQWi2XFBzAb/y5PSLO81CUhyOVyprzfDoiYSVni/Pw8RkZG8hZiJRIJb07KhFwuh91ux9zc3G3NxGQ/wffddx9kMhlefPHFgn+j1+uZ1kT/XVFRIZDWpeU79fX1iEajOHr0KIClASW32836gCqVClarFT6fj41Yr9ezYABR1kZHR+F2u/HQQw9hfHycKXGZKC4uxsTEBF8bUtSnrUw030LzPPT5g8EgVx8qKytRVlaGdevWoaWlBX/1V3+Vd9EOwW63806WW7duce/5A/WEhw4d4oFvr9eL9evXo7GxER0dHcwUKS8v5+n725UQps5AaWkpmpubEQqFMDQ0VHCIulB8Rqr9wJIalVgsZkWE5fbFZRts5u7fQmhvb8fIyAgfYbRBMxMmkwlOpxONjY2IRCLo7OyEx+PB8PAwRkZG0NLSgj179mB+fh6Dg4NMtScFXApXysvLBatxaRwhH4qKihAKhbjuSYwnqnWWl5fDbrejq6uLeYjZoUtRURHKy8tRX1+P5uZmuN3ugkaoVqvx4IMP8kw5leo+cPV+EqjcsGEDtmzZgqmpKZw+fVrw1M/NzUGpVPLKrOVuolKphFqt5gCXWBonTpzA8ePHUVpaio985CM57GkC0aAK6UJv2LAB1dXVuHbtGs6ePbtiUkHJEoFaVgSpVAq3242JiQkeiSRGNkGn06G2tlawzXNwcBCDg4OwWCyIxWICw5FKpUwoBX4/f5yZuRK/cH5+HiUlJYJlh4WSlUQigaqqKtaNJtF0Gni/ePEiPB4P714JhUI5LPGFhQUerSAdw0JQKBQYGhrC5OQkxsbGOHn9wDsmhNLSUjzxxBP41re+JTBAYKnKrlQqcc8998But3Ms8s///M85dannn38eVqsVd9xxB/9bZmw3OjrKu5WpwA2AxZfMZjP6+vpy6GFutxuf+MQnUFtbC5fLhenp6RwDJKZIpnFTB4cMkWhkLpcLfr8fjY2NvO1pYGAAEomEB6YIVVVVWL9+PaxWKyYnJznBAJB3abZcLucbZzKZUFdXJzAEiUSCjRs3YmBgALOzs2hra8MTTzyBubk5dHZ28qLu7DppJBLBxo0b8fDDD8Pj8eCll17C3NwcUqkUYrGYIL4jfcLsOJIcCknnkSjSyZMnBffJbDbzyGhmDL5p06Ycilch3LYR0v4MkrbNbNKTvC7tQtu6dSuKi4uxdu3aHCoX6fQth2vXrgmOCdqd5vV6eRYieztlKpXCxMQEy6zlm0+pqqqCXq8XGGH2MNXZs2ehUqkglUo5JpPL5XC73XA6nfD5fDnsoPn5eQwPD7NXyITX6835vhQekP53NrePitjkUbq6uvDTn/4UyWQSgUCAvz8xyAmZy4CoukBDTvmmFakSkJkEEskXWPK4lZWV2Lx5M6qqqgQMIRI0yMbo6OgHP2PyyCOPQKlUoq2tDYlEAvX19bj33ntx+vRpvuDV1dWIx+P8IRsaGtDc3AyRSMRUqIsXL8JgMODMmTNQq9W455574PV6c4q6ALhIbTKZmJ3jcrnwox/9iA3v0KFDCIVCOHHiBIt2/u53v8PQ0BDsdnteAcy9e/dizZo1ePTRR5FIJPClL30pR3KONA9lMhkaGhpgMpmg1+vR1NSEtrY2nD9/Ht/5zncEEijUo830jjqdDqFQaNmOR0NDAyu/ZhohrQQjI5ydnc1RZKiurkZRUZFgfnlqagojIyOsItHT0yN4GJuamrB//36cOXMGZ8+ehdFoxH333Qefz5dX8SGVSqG/vx+PP/44rFYrG3RpaSmkUmleI7wdJYZVGyENyXg8Hu6VarVagcudn58XPO1erxdDQ0MYGxvj6TAqvZC3Iona5fhrPp+PYyWlUikoaCeTSUgkEhQVFXEwT7tISNoiG2NjY1AoFFxSWW4+hCQwqHVGgklUtqFZEEK2EdXV1bG6aSHQBqbsYzUej2NhYWHZE4M+X+b1MxqNSCaTOHfuXF6mTyKRYGUuACyJt5LnonIYNRHyzeO8H6y6RENZZnFxMXQ6HSoqKlBSUlJQDcBgMAgU6rNBg+oU8OYr59A6sWw0NjaisbERMzMz6Ovr44wvEokIZjpkMhmKiopQVlbGksZ+v59vKomVe71e+Hw+mEwmuFwuDA8Pc1vqgQceQEtLC/7hH/4hx0jKysr4+E+lUjyAv23bNmzYsIEJGKdPn86ZxCNUV1fjf/yP/4H+/n68/fbbGB8fFzT/aY0FhSXpdFpg9I8//jhcLheefvppAEsjFp/73Ofw05/+lE8X6vpMTk7m9chGoxGbN29GJBLBmTNnEIvFUFRUJJhEBJZoWuPj48uWahobG3llhkQiwS9+8YuCv0u4rd4xkSdp0TLJjGWDdrstt6Alk55UaFJfrVbniGACYKMLhUKYnZ0V7O/Nfg8aoEqlUlAoFIIYk9p7RJm32WyoqKhAPB5nI6RZ43wkCZlMxq2+WCzGBk6zFwaDAWazuaAoJgDe2kRrOLJ/l+aGKQFQq9VMCaNrRO3OZDIJvV4Ph8ORU7fV6/UslJT5wItEImZzZ8b3xcXFcLlcAiMkCZPlQK9Hy8FXg1V7Qhr3tNlsUCqVy7JpC4FEGjPFlaxWKzZv3ozXX3+df6+lpQWhUAhjY2MCI9dqtdi4cSN6e3tzYo7HH38c6XSadXC0Wi0+/elP46WXXiqoIK/VarlIHQwGeXajq6trVQ36Rx55BDqdjhOKo0ePCm6wUqnEHXfcgWvXruVtPTqdTlZu1Wg0MJvNGBoaytGnaW9vx44dO3DlyhW89957Am+2b98+uFwuTExMwOfzwe/3IxAIcGhCcaxEIkFnZ6eA0lZeXs7Szx6PBxMTE/xzmhXKTCgtFgt8Pl/eECdflg58wNJwdKHoybtdrF+/Hhs2bEBdXR2zaIAlQ6iurhb87po1a1BSUpLjZalwmo+GRCu7CE6nE5s3by74eWQyGcxmM9RqNXtan8+HcDi8LM0pEy6XC6WlpaioqMjLdolEIjh9+nTeonJmAfvSpUvo7+9nMkI2ioqK0NraCpvNlnOc0s4Rt9uN7du389CSz+fDfffdh/3798NmswmocLRrpaioCFVVVbDZbLxiLPOzZ4dIwWAwrwEqlUrceeedq7pm+fC+2na07KUQ6LjO7m1SX3dqaorjCtKroUy4tLQUX/7yl9HZ2SnQbQGWRgyamppw9uxZXLhwYcUhnuw5FLfbDb/fvywDpLq6Oq+wUybcbjcXgmOxGEZGRt4X8zk7GcvsOBFIAYx2sSQSCfT09LB3b2ho4LGI+fn5nD43qfjrdDo4HA7I5XK8/PLLfP+oVVpfXw+v17usIKdarS7YCt2wYYOgrEP4DyMwrOQp/uiP/ghtbW144403cO3aNT66SVdQKpXC6XTyVN6tW7e4TrZu3Tps3rxZYCgKhYKHxWUyGdauXYvS0lL4fD5MTEzgxo0b7CE0Gg3WrFkj4AQeOnQIer0edrsd3d3dBSntwFKRlrJvkUiEvXv3wmaz4fTp0xgeHsb+/fvx8MMP49SpUyys9H6RfYOo2EuC7haLBQqFAiMjI+js7MSOHTvwwAMPcIcCWGovklpYPoTDYUxMTKCiogL79+9HeXk5Dh8+zPdwYGAAiUQCf/qnf8pJ5NDQUM7cMbA8qXl4eBiNjY145JFH8O677+Y0MpbDB8KiyUZ3dzcCgQDMZjP27t0Lj8fDrn5oaIhHQeVyOUvG0UUcHBzEzZs3cfPmTX69aDSK4eFh6PV6+Hw+3LhxgylN9fX1KC4uZs+6a9cu3kBE3oxajrt3716RJt/U1ITFxUV0dnYimUyio6MDKpUKRUVFqKmpgcFgwMWLF5fNEP89UCgU0Gq1XDxOJBIc/x4/fhyxWExQh6TZn0yQohZBr9cjlUrhpZdeyju9FwgE8PrrryOVSmFgYKCgjng+5+NwODA9PY3Z2VleQ3bz5s3/GCO8evUqfD4f/uqv/gonT57M65arq6t5DwcA/O///b/x0Y9+FOfPn+cPRZrKRH2qqKiARqPhYWuS68jusJB8bmbQ7vF44HA4OFnSarX4zGc+w8Xfl19+WZChHzt2DAaDAVu3bmW1g0QiIRj1vPPOOzE9PY1bt24JesN33HEHPvvZz+KVV17Bs88+u+q4kUSDCE1NTdi4cSOLFWVO3VGiQoyX7MEs4Pd7R+68806o1WpMTEwIPsuGDRvw2GOPoaOjA88//zyUSiWcTieP3mZ/Nq1Wy9J8maAGwZo1a1BbW4tf/epXOXMj9957L/bv34/Pfe5zAJZi6t27d2NgYGDZYz3nGq32F2nT+nKepL+/n5viVFT2+Xx5Gcak3kAsZLPZzDe8s7OzIFcuW1XBbrcjHo/j1q1biMViuHr1Koue22w2gRGKRCL2wIXEemj9avbPL168iJqaGnR2dq5I788EbTYgjI+PM8lDp9MJKGS0A4Ri3XzDRoRTp05Bo9EwpY0QDAZx+fJlXL9+ndnrNEyfifr6eszPzxdkKdFnIOnkfAThSCTCm6hIQvjs2bO3Tf1/X4nJStve77zzTmzZsoVjnvHxcYyOjiISicDv9/M+D41Gw33cvr4+jIyM4MSJE4KbptFoUFFRAbVazZ+BirdNTU246667MDY2hmeeeQaTk5P8t62trVi7di3ee+89jrW2bdsGpVLJ+4spMZiYmMD09DREIhFEIhHkcjlMJhN3eVYDuVyO2tpaGI1G3Lx5E9PT01AoFCwymd25sFgs2LdvH2ZmZngcdWpqqmCCU2hwn+B0OuFyuQSrvghlZWUwGo2sH3nw4EHcf//9+Ld/+7dlhdkzRS5DoVDOZyspKWHZY6fTicuXL+P8+fNwu934yEc+ApVKhX/8x38s+PqE9xUTrtSq0el0MBqNmJmZYaOwWq3ccKc9JzKZDNFoFIFAgEsmKpWK/4ak1EhdgVpN5EFJypYK0ZmBM8U1JpOJ40mabqMbSntV6FgmDysSiVBaWopYLLYqIyRCB7GGLBYLAAg8Lhk/gUoiRAimLaGBQCBvGWQ1owqFJuCyY7xEIoGpqakVl22r1WqWkgOWCuukOQQsFfvj8TgaGxsF+2puRzQduA1PSNt8vvGNb+T8jOZ7JycnodVq8dBDD6GoqAijo6MsJhkKhVhvWSQSMW2KSLIkP0HeaHJykj3YAw88AJfLhf7+fhb9cblcrApAK7F8Pp8g821tbeVSCo06arVabN68GWq1GleuXMHExETeXc5PPvkkUqkU/uVf/mXFa1NSUgK3282x8I4dO/DJT34Svb29nFVnxlP5ThKZTIZPfvKTiMfj6OrqYt3G5aDRaPCJT3wCRqMR3/zmNwU/o7UaIyMjLPvW1NSEyspKvPrqqyt+p/b2dqxZs0bQbnziiSdw5coVgbdVKBRobGxEWVkZn3y9vb3/MczqdevW5Z210Ov1qKurQywWg8lk4qeB4sf5+XlORhKJBG+JDAQCTGQYGxtjsUiXy4WqqipIJBI2QtqnnE6n2XsBS0zmW7duQa1Wo6mpKeez+f1+2O12VlcgQ6C24nIijpQcrAYke0GQy+VoaGiA3+/PSUxIqzE7e4zH47DZbEin01wmWs4Ia2trUVNTg5aWlpwCN7GWDhw4gI6ODjZCo9GYs3yyEBwOB2+1IpSVleV0n6hd6fF44HK5UFZWturZHv68txsTknIUaZQMDg7mPNXV1dWw2+2YmJjAwsICbDYb7HY7JBIJZDIZlxkoRqSpL5pt1ul0PHsB/H5Mko5eolmRIHkikRAQE4ClmlZbWxtsNhuKiopw8+ZNzoJJl2b//v2oqKjAV77ylZzvS8P5xIppaGjAmjVrmKUzPDzMD6VCoYBCoeAwwu12o7GxEVNTUzklj9WohZWUlEAqlRZsN+r1epSVlUEqlXKIkr1htaSkBLt27RKcOrTOYjWZvdPphFarFZSiHn30UYyPjwsmD0mYSa1WY/369Whvb8eNGzfw6quvIhwOr2rO57ZjQpPJJNgSlK+oScPrXq8XyWSSJXLn5+fR19eHxcVFQdynVCoxPz/PFLHs7JNEerJBKlP5YtTMhT2kAEugrFGv1+OOO+7Iy9bJzEzLy8vx+c9/Hg8++CBOnz6Nd999Fw0NDejv78fc3BwvoqEYdnp6uqABUR2QBM61Wm0OUWBsbAxWq5U9EWWwdrsd99xzD7Od5+bmBMTazJ1709PTuHr1KiorK/Hoo48iFovh05/+NBYXF2GxWNDa2ipISiwWC2QyGe+vyyfjQdpCZWVlLC9CMSKp8up0Orjdbuzbt++D32NCoN4x9TmrqqryFm4zU3/qXJDHynw6yCCIHkYzDQB43RVdWFLXz3y/QklSIBDA2NgYC0lmvqdarUZtbS2LmFNjvhCGh4fxgx/8gLdrXrp0CYuLizlJC30XGvTP9+CMjIxAJBJx8B4MBnOIt7t374bb7UZPTw8L1MfjcczMzOCtt97K+6AWFxdjx44d6OzsRG9vL6qqqnDPPfcglUrh5ZdfxsLCAi8Nj0QiLPiZOTQvlUqxYcMGyGQydHd357Q3aVKwra0NEokEFy9eFCRMXV1dSKfTzKxfLd6XEVJmajQa2SOIRCJs3boV4XA4Z56CblYsFivonnU6Hfbs2YPZ2VnuEDQ0NAAAF7KrqqpQX1+/qm4FaUnb7XaoVCpBL/jgwYPYuXMnDAYDotEobDZbznGWjfPnz+eVc8sH2gaVzwhpcRCpieXLhO+77z6sWbMGzz77LBKJhEBttVCcWF1djfvvvx+pVAq3bt3CmjVr8PDDD6Orqwvf+MY3kE6nUVlZicrKSt59Qiwfn8+Hvr4+qNVqbNmyBWazGbFYDD09PaxPmPmQFhUVwWg05lwPWtR9u7htI0yn0wiHwzh27BgPq1Oy0dHRUdDIaMVDIZCyq8FgYCOkhIZw5cqV21pjarfbEYlEcOXKFcHRMDY2hnPnzqG+vp6HqT4IkBa11WqFxWKByWRCT09P3u+9XCj+6quvoqurC1KplHfPqVSqgkc8sGQYWq2W24tarRbDw8MYHx/n96LJPwIlixRXTk9P491334VWq4Xf7+dl29lGeOrUKQFXUKFQoKqq6rb3HBNu2whTqRS8Xq+g1XXXXXeht7c370WigvBKI5ekMVNSUsJ9ZJ/Pl1N9LyQ5RkdPZommoaEBAwMDOH/+PFwuFz7zmc8gEAjg2WefxalTp3DgwAG0tLTAZDKhra2NJX0pNlWpVNiwYQM0Gg0+//nPr3htPv3pT2P37t3c8w0EApibm8PPf/7zvPrVJHKuUCgER9+xY8dw7NgxPPnkkzh06BA6Ojpw48YNHD16NMcT0sbT1tZWWCwWtLS0MG3r2LFjK0o1ZyaAADhrNxgM2LRpExtha2srTCYTLly4kMN3fOihh/DYY4/hzTffxEsvvXTb2fH7KlbnUz0oVM7I12AvBBohIBB1aTUgGbnsz5VJi7dYLILXJ09As73EXAZ+n5Hb7faC/EliEVNcSll3psARCUQt950LlYpIJIrmYPIxlSlGl8lkLDylVCpZdH2l5CBzdCATyWSSC/u0XcpqtbICbfZnMBqN0Gg0q2ZTZ2LVJZoP8SH+o7BqZvWH+BD/UfjQCD/EHxwfGuGH+IPjQyP8EH9wfGiEH+IPjg+N8EP8wfGhEX6IPzg+NMIP8QfHh0b4If7g+P8A6s9AwtAcbqYAAAAASUVORK5CYII=\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -456,17 +446,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 5: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0695]\n",
-      "Epoch 6: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0431]\n",
-      "Epoch 7: 100%|███████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0292]\n",
-      "Epoch 8: 100%|████████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.022]\n",
-      "Epoch 9: 100%|████████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.019]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 71.66it/s]\n"
+      "Epoch 5: 100%|███████████| 63/63 [00:40<00:00,  1.56it/s, loss=0.0701]\n",
+      "Epoch 6: 100%|███████████| 63/63 [00:39<00:00,  1.58it/s, loss=0.0428]\n",
+      "Epoch 7: 100%|███████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0291]\n",
+      "Epoch 8: 100%|███████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0221]\n",
+      "Epoch 9: 100%|███████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0182]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.07it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -478,17 +468,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 10: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0172]\n",
-      "Epoch 11: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0157]\n",
-      "Epoch 12: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0156]\n",
-      "Epoch 13: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0147]\n",
-      "Epoch 14: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0136]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.61it/s]\n"
+      "Epoch 10: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0165]\n",
+      "Epoch 11: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0165]\n",
+      "Epoch 12: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0156]\n",
+      "Epoch 13: 100%|███████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.015]\n",
+      "Epoch 14: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.015]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 66.87it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -500,17 +490,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 15: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0143]\n",
-      "Epoch 16: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0142]\n",
-      "Epoch 17: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0135]\n",
-      "Epoch 18: 100%|██████████| 63/63 [00:39<00:00,  1.62it/s, loss=0.0136]\n",
-      "Epoch 19: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0134]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.47it/s]\n"
+      "Epoch 15: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0141]\n",
+      "Epoch 16: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0142]\n",
+      "Epoch 17: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0143]\n",
+      "Epoch 18: 100%|██████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0134]\n",
+      "Epoch 19: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0133]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.04it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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hPNvJlXH9fh+tVgtnZ2dot9s4PT0NWeQE2MnJSaFccsRut4t2u13guLnJC8CBW8N5q+0A3/Dwfse4oP72jpFDtdvtMGM7nU6Y3cDjtsar1Spkc/DDDGibdkTrTl0LbCOBa3XbVqsVgPb27Vu0222cn58XQMiBpl9wv98H/yCfyfat12vMZrMAMHLEh4cHnJ6e4vz8HJ8/f8Yff/wRwoBKBBdFZ7fbxWg0QrPZDGKUHFFXxRGE5Hw//vgjer0eLi4uQniSIOO6m1ar9UQlIFfXMc6lyhsi5QamVdcipbif/V1WNrkJOSKdo3bBknLDVqtV4IgUaxw4DpSKEwJWY+YAwgTg4LTb7aC4E8DKdWIcFnhMFuVaXd14nBk7Z2dnQZdstVrBAifIKSKZeMtEXALMgpATzYJwNBoFsdrv9wOgm80m2u12oY9I7CO2E6i2m24lTpiT1u8ts6xigMT0QPufwDs9PUWz2USv1ws+Ns0HJBCY6cE0LRXxyrmoN1mdk+URkFS+VZmn+CXno06la1TIuZnQoCKUywZoXXMi//DDDzg/P8e7d+/w9u1b3N3dodPpBP8i/ZAMGbbb7WAodDodvHnzplA3EkFDXbDdbuPt27fodrs4OzsL4lYnkE4kTx/XDZFyKRuE1lr0KCdWmaKUe8Rep1ahXWxNq1d1I+qCFIkKQnIOBZ/taGaIkCj6qL9pvJR9xVV7BJkOJHVDFf3c/YGxZE5eBejJyQn2+z1Go1GYcAAwGAwKlmyv1wvc7eTkJPSP9iX7p9lsot/vh+QLcj/qkvrRien9tr7bHKoEQv2or5D/qzxYqUyHsA3bbreFbJbdbod+v496vY5+v49a7XE/ZVqtyqmswWD1VOWWurcKgCCW1NpU8AGPg6tuDRpQauGqXgZ8Bbomh65Wq9CO9XqNbreLv/zlL4HrrVYrTCYTbLdbvHv3DsPhECcnJ8GAaLVaQSfkf30m9VI91u/3Q91ZL8+hz7H3xocqDwC0Wq3S8c8Gofq72OEqdi0wq+gEKfJ0UBoXBCN1P6C4Mc9+vw9cgfqSLmwn6CgCyS3Vj6dimavuut1uAXTW99ZsNsMgE7DU+2gB2/apKKMbhwPJ9jebzQAktp2/z87OcHJygjdv3uDNmzcFvZk+O6ocajVTjeG4qSVtXXHWoLTjo+P0IjqhVlR/q3+N19HXZlOTbHm54tcSLchGo4HJZBKMDh10TaOnM5aDQu5FHVHdM9wirtVqFfxxFKvkrMqVaXVbkQQgiH91RisIWW9Su93G+/fvQ9oYud1isQjtWq/XaLVaAXwA8P79e4xGI5yenuL09DRwfOAREJxQNKQIauu2ojQo82qwrRaUHlhTVNkwUS6og6Qdb0GpDYmBr4o+SXZPkbzf70P8lcaIWqrklIxMUC9br9fY7XYF90y328VutwsOZ9ZZfWP9fj+0h2JTQajt5oDyWbzW0wW3222IxXLCcBMmtoOTRKVNo9EoiGO6Zuh/pMpCoFHv01xG1ZPZx9oGjwPynD2m7c6hg/yEygk19JUjhqsaLjGXEDnMYrHAdrsNCjYBpZYf3RfT6TRwM3WbKNj4TLZF3yaqOh+NIe7KwB28rGFCtxBQDGfqhKZKwXqyHBoLtVotcCwAIZWMbh29l5xVN61U1YMflWjKrUmqfuXo60oeqFN0UMSEDdOBeSnLmGVr+cpdyIkeHh6eKNTAoyFBLqcDNhwOg+VM/Y/PU8NFF/EACEF9in/ex4GjlFAQEtQEvRo8BOHx8XEhJEmO2G63w8J6qiFMITs+Pg4uKrZV3U2UDJr9o+PI/lQQsl4ewPQ+TwqyL18UhKyIduwh5FXQHrON864nl9JFRGpM0NLkwNFXR3Hb6XSw2WzCQibdGo4AsSE1KvBW/KqzlqQcRaWGJU4cDqCWTQt3s9mECcBNmJT7WheK9qMaRzRqeL0uTa3i4YiNiRc1S9FBnFCtJus3rNf9bUFyKhRzAVhRaXUUdqreo/4+FZGq39EhS2uWmTBMy1dRTTDe39/j5uYGvV4vOIFpsaoY5POsccDBJmelGqGxb7sij6lS5GZ87S8nHo0qinKS6owAgnHGJajqRfAW53tEnZpg8/RActUX54TPNS5IFnj8bTtBjRp7j72X38qxSRqOo8JO4PCVuWoZKzhYFjmeOovVIc06qL9M+4jfMe6l4Gc9VH+lyKWlDCBMJE9c6rN1YttneP1tqSxqVoWTkg7aJDMmhmMATIlS/o4pwdbKKgM5y7LvZ9ZBp1jV1W71ej3ETL1gP+OoOtsBhGgDQUBduVarBRFPFxFVAY2cWElCwwkAlstlIVSorqb379+HLe22223g4J6Tmb5PNYZSXE/73JMkWraSApzcMocqgVCt4m9FKW4W+x87boEcAzRFhepGHDiChWKOopbA0HLIhfitg60v3VEdkwCNtYlcDyiqPnq9gppiXSdBzLWSAlCKCcQMkVg5BO03ByE70GaTWCozVOwA2I6iBacRBK8TWY5VglOxTg6oWr5Acc/q2WwW9L12ux0SN5nSpNarcrP9fo/pdBqSUTWRVNUCGkckJowqd9SQF61v6n9UAdTRTp+i1S2pxyonA1DYK4bnbOhR+4x9qB/tRx0fe00OPSu9P5cs8LSSHghTcehYI7Vj1LGrIImRckJdnNTtdnFychLCW4zGWGuX/5lpQ46oCbe8TvdpqdVqIQmCOqX6JNVnSO6tXJzt1oiP1s0malhr2Pab9qUFn14bc81445FDlRMYvIemXDUKMHvMGhuqhNNCJXfw6qOsn45Zm1ygRD3R44Tq1hkOh/jb3/4WVpARKDEdisDQCUCOqavjYvcybq0RnlrtcW2I9qFa3VoWkzIUfNo/wKN1zLpoX9oMdY5TSg/0/nP8dIlDGVWyji33ivmWUjpZrFxVvpnxwVw8DooClY21C3SUs/CZ5K70rdn6Kgjr9TpOT0/x17/+FcPhED/88AO63W7BWc06k8NyJ3+Wq3l3VNDVULLqCNO6WKbm/lE8q49S/ZRaH3I5Pkud9gCCuLaGIEENPH0vTZnkUdVIueqLgFD1ppzCvcRW/R0zGpSbMIWfANEZTgAy+mFf+UDgqlHAlHhvrYm6ZJgqxeWZyqkJLPoFAQSXTsziB4ovntE+YDwZQFhpx+s0qmING5KWRz3PuqX0Ov4m11ROacfKils97nk0eKzMbrBUGYQqymwqV+w1UilDRI8zxER3ycXFRUHsMGph8/W4/JCRBcZTNXZMsbfdbsNaDup/3NiSgB0MBjg+Pkar1cJ8Pi+ISjqkm81mMCjIcTT3j8/S9SwKLNXt+Ooy9rO6UzjZNDucpADi8xhitG4aK37Zz57D2eOANuSndeB9vF4nQ86eNJXzCS34dJY+l1QkqcLNDmUMVEGo6x8IDv2mgUE3BjvSLk638WY1QNhOpd3u604Lei+BldqtVNul/jS2Sf2W1tqMGQqx/rNi1HJha9XqNR6Xs4kYvM4CVxM/cigbhKpg6wq2HLLGB8kq3LqegYPCsJhaiwQYlypSNKqOyOSCXq9X2C9wt/uaha3W5nK5DHFjbvurE0FjvqzvYrHAeDwu+AFZd7U+AYT6KAci0NkW9oHqe1QbNBrC8uwkUcvYTl4bsybHtO4sjhXvUZVBw4ksh7on26t6chWmdFDY7rlcL8dg0cYDj6JMuYX66VT30w7UGRwjtWJtEoLVmayhw2tozZJbW53QDjjbwklmJyNJ9WT1C3r95nE9+9v2ucdNrb5nDVF9Lo0hqhBWL86hbBDqckk703Wgcx9sK2pn3HK5xO3tbQiVUTdUEGgoi4Ojs3O1WoW9BIFHPZbZzboTv4pHBbjWTZdi0nEMoKAvEtAqdtVq12upRjCdjBRz0usyBk5O6+9jXT3XlopJCz71eap4JsD44TMUlDauXjWzqvJqOxuTzaEYMBWAFowEIoCQTm9fX8pZCOCJXzCmAnD9iLpsuAWGPt+7T61TTkbqQCruLABVzbDqBj9KFiDaN5wsuh5aVQI7uWMWri3fckAlDXXqR1cvEoRVAQgc4CfkQ1N0SEVIBAkAXF1dhdw5Xaikxoeu51VdSV07nr5DEKo7g5ERLkJXPUsdybqBEQ0RTgibysXnEohsA91A6/Ua0+m0sJuEciEFjRo0ugjKis4YqbTh5LVcl8/kf93JgllGBB0lCjcOVV2TTOGvf/1r6ZgftCGSdkoZ4Mr0A2ulqfU9mUzCgHPXAWYrU59aLBbBUlZxpwOmjl7We79/zBHkM/v9Pt68eRMcrQpq+g0tx1aDByjuumD7hgkHmoPIMijKFfgcdDU4WAd9nvavx8VtX6vItuNkxT3X8jAWreDjW69ms1kAIt9wYCM6KaokjlXv85yf/G0bxuOeIq3cwlpXTNsHvnb2bDYLg0yw0ZLVFyBa5V2BY31ru90ucFZ2drvdLqz70MRPzUjW5E7gq8Vs/WbA4wZOyn25y6tOFo1oKLF8+mLVDaOuEXJj1pU7PHBS0aOhWeg6VuTq6lOdTqcBZFzjzBQzLi7j+/1UNdDJVEYHbZKpwXmlXJ2AHWZBat0hXGnG7XOVI9hMFs48LgxiXUnKrdS5vN/vMRgM0O/3MZ/Pw14vzIYZDoeFZZEcLKoASuRquqSAGTUUyZxYNIh0HYr6YoFHf6W3NJWTTvue7iFOXGbsaOhQtxnRsWLdmZ/IvW5ub29xd3eHyWSCq6ursLjs4eEB4/E47LFNB3nOYndLz9qzWoETOw88VZKVSyiwVD+zs9Qe472ceSzDuhf4rW4TDhLrzUHRPWDoN6SepvFdgt9akmrBq7HAfWvIERnJof+Q4lnjt+qOYbsIwJgzW0nbrmFKckhN5rDRJIrY1WqFm5sb3N3dYTqdho3dKYan02nhVWKcVMqpc6hSUqvnI9L/ZWDU/zZcpByQna7i34JSc+EAhNVn9nm81xsodhSBUK/Xg75D8UguRU7CY0DxPXX1ej2sfOOWcWwXOYTqqryXmxgRmJbjsj3kpDbTJqYGqRFGbwA3YZrP5+EVumzXZDLBZrPBeDzGer3G9fU15vM5rq+vcXNzg/l8Hq6ZzWYFjqguGurDL/oKiW9Fqs/EXAP2Go88jhm7LgZC6pka/lPuxORS/qZLhyKRYNBdDVQtIIDUzcTBohVvdUHP3RJrn4pwz5WiIUT1xdLPyb0R1+s1xuMxVqtVgfvx7aXUYwk+gluljCaPvAgntHFjjzyR6R3nOc/I4fNiIPX8gZ7TVkWidgq5Lg2S4XCIi4uLsA+grhvhKx90DQfj1Xa7NQJL/X+MxNBC5+o+PpvizAYAtA02cmT1cVr61nfHcrmvDsePLwJiuQwMLJdLfPnyBYvFApeXl5hMJri7uyvofupC0z7XScONnayzPEbfjRN6pA2JGS+x3zGQA8UEWC2bOppuhUaAcXcqilZmVttdvrQeylmVu6rVqOCki8bGZL12Wu5mJ6ZyPP1QB1TVRg0URpT4csjb29vw+orJZBI+dNWok9/2r9ZLo0tlVFkn1EbbBluyoFKxYn97/z2DxnJH7QjtEHX5EBQ0MqiDkbtdXFzg/Py8sMUuE2qVI/b7fQwGg7Azgq2XtWKBYqSFBoBa2PxmOz1Dg+JTFX4bNmU6mhW31AV1vC4vL3Fzc4Plcon5fI7pdIo///wTs9kMf/75JxaLBe7u7oLrhSC2doGd3IqVFzFMrHHAh6nlmVtO7Df/W0B71i7JhvFsogA/3GOawOI338ehm0PqnjbU8xhNOT4+xnA4LNSZQKOfkXVRcUoVQNeY6ERSI8MbXKtu8BjLUfFL7kfxSQ7GiTAej3F3dxeMjclkgsvLS8znc1xeXmKxWAT9TxmMlVIxENZqtYKhWEbfTBxb7qWVthXU49YS5DX2HuDpwmv1F2pigOpeKmpHo1Eh0YBuE2523u/3w+o6viiG2d3kiDQ4aGXqIOsksroc683MG7poLMdWy5nnGTrjppfA4xvpFbi07pfLZQDher3Gzc0NVqsVPn/+jPl8ji9fvgTf33g8xmw2w9XVVWiThuh0zCz47Hjod5XQbeU3v3vHc7mh5zqxotzqbsDTdc6eqCX4KEaHw2F4BQJf7fDmzZtC+he5Hjv1+Pg4bO1xdnZWeBcdn6UWJjcp0p0c6DDmh2KUz10sFgAe1zcr97YTiXXTTTyZmGszeFgOrVaCcLFY4OrqCrPZDP/5z39wd3cXAEjDgzqhGnLsZ88fqZNHx+nFQWhFHf/nimFLVgfU1WnW664Kvyr3+ptcjb46itd+v/8EhJzV5Ij0dWlKFZ/F4D3rSi7BxAMNqQGPXgSbCq96IckuXrLWPJcWUDfrdDqFdTZAMbGU9WOI7fr6GpPJBL/88gtmsxl+++03TCaTsD6a79WzO8LqGGkAgUQ1wKpC/M4Vw6Rnv8eElBuys0YIB4w+OIIGeLr1iOpr+soHhtcoPvW1DnzLEtesEFj7/T74sxgf1XbR3cJdWDVjRN+HUq/XQ3a39dVpXxE86rOzERAe4/10HPM/s25Y7m63C3Xhhzu7fv78Gf/9739xe3uLf/7zn5hOp7i6ugrRDs2Ot5yOnIyTQgML1jK3+m1MT0zRs8VxFfK4JgeArhKChgOm1+ne07qni82sUYexJgWQa2hOpA66ZpBQbFK5V6uTep0N+6mhwoGzRhXwmAfp6ZFsE69TTmp1MdaZ0QtGPu7v73F3d4erq6vgdJ5OpyFiYhdf6bfW1QNSDGAekHMpG4SeAeFVxFqw9h61tOguqdfrODs7w3A4xGg0wtnZWSHcxGu5Ao6GBMum9cusF3JUZjOTg3358qWggxLUutqO4pmW7tXVFVarVYiY2GUFdLsAxaWkNuGABg0Hh5xVExzUOKFOqJk6fL7qbdT9Li8vMR6P8fnzZ3z+/BkfPnzAP/7xD0ynU3z+/LngalFd2xqKOpb8tta7Pa7n7UTJoRflhLZx9j/1PHIzDjT3jeYg87kaLmNqFAHKAVOQaDoROaFyWJbPAbIW38PDQ+Ag5IQaKaGhwvI1M8V6C5QzKsfUnD7tJ8uNNJ1M3T2sF8Nps9ksGB1UM6jXKudVThUDYhl5QHxRTmhFFo+VVdLz7QEozHaK2H6/H16DoLOUXFjXcDC5k3oUuYSGxfQZzP6gZUmFX10gKiJp3TJob9/xph1Ncc+BZkiOxhN1NfaDtgl41D816UGzn1kO3SycvMAj9+V7kj98+ICff/4ZX758wZcvX57kDlrdzv72jBP72+OSysm98U5RJU5Y5XhsdnkOWuWI1Ov4WzmXrrTjoh+Woet2VVzpb+p0KpZqtdqT9HTrhmGqP8mLypBzkoOTc7EPdGGSnZjqoiFAvf6krqqDzbKZ1TybzXB/fx/ekWz1P09dipEaIPZ/DIiebllGlXTCVGVjYTv1GdlKkUMwN03XEjNawWdT9wOKL8xRjgMUtz1joJ1Z09PptJD9oSDktawXB5Dck1ndmnzA+o5Go0LmDa1uzVRRtxANMcam7d6CTJblZOFu/QSq+iGZiPvvf/8bl5eX+Pnnn/Hbb79hPp8HL4C6jzguh7jXPDBreayfRohyqPImmVV9QLbStgF0EaxWKywWi/DRxfZ2ApDbqULPstkBGkCv1R73aSY4KcYBBMOEZXFw9VoAT/yZFM/60TUuTBBQfxvv1ZCg3qNLRsn9WD+6gXhss9ng9vYW8/kcnz59wuXlJT5//oybm5uC+0WNBMvddIzseCvxPgs+zzDh9d+cE2pFynyCsfMeu6Z4Ipeigq2JoPouOh0sZqMwrKaefHVFqBOXnEWTCagTqp9PF/dou6kT6hJRpi3p5u0EM+8lh2T4T1/2AyDohOq4JodeLBbBmmZcmJyOobiPHz8GC1mXowIIv9kXGnNmGw4hq0uqmvAinFCpKhAVfPwm+Cg+J5MJZrMZxuMxrq6uChyD4k4BaMWx7iEIIGQPkyuqZclvjZOSY+m1+k1Dh1k0BBOAsGApluJEgHGyaB6irpWh+sF60NrVlWy0dvnKsY8fP2I2m+HDhw+4uroKoUTPLWaNkjKjQ895x2PYsPpwGR20cXouWaB6YFRRyueoq4NRAftcG8qzu6hy4FTR17Ul5HYaOeBxD4TkdozYqN+P9/CjxhI5niZUMMcQKHJATgBy8fl8HkJrzGy+v78PIFwulyEFi++/s1vZAfFEY6smeZQjhq11rJlCOXTQxulqiJS5aTTs480oTW0nB6C+xoXUbJT6u1TUqoVKouiKDQbboMDTc/xvt2ID8MRXyH7QcBwnBsOJ5OZ0zrMtjBKp/qn6HiMg0+kUNzc3+PPPP7FarYL1+/vvv2M+n4eIiSUdK+0jOx4x0j72LGLriSBnf1GdsCrFQGrB6AGEjaEjWdPgCbCY7qFO7hhHsBws1V6KfYYX9S3r6ii3qf2634zVl9QBralXVCWY7XJ7extyAO/v70N8mGlb1F9T7rJU23JJuaIdt1xx7VElTqji1dM5eMyzrDwgpDqHYhlAwc3Bc6pkq9jUKIot3z47NRC8n+6W09PTsEPDxcUFzs7O8NNPPwVDhVxOfZnHx8eFt6/v93vc3Nxgs9mEt7RvNhvc398Xspk/ffqE+XyODx8+YDwe49OnT2ENCLNeuNEn3TgKkJT4jfV3LlCVs+q9nFRc/1Jlz6JnJbUealV5ZK21mO9Rz3sfTQSoUl8dBOv3qte/ZsocHx9jMBiExfK0ku3eiLqSTq1gjTrxw0gOs5wXiwVub28xm81we3uL+/t73N7ehjW/DDFqXD3WLk/c5jqTy87ZD8v2VLYyqrRTK1DkcqprxHREzwKLdZynAHszz97DOuz3j+s1LOkzOXiaVMqZTIucTmSuOeFqvPPzc1xcXKDb7YZ9a6jnceETgcdQ5H6/x93dXXh+o9HA3d1dEKvj8Rjz+Rw3NzeYTqf4+eefMZlM8OXLl2CY8L3O6gf12pcraVJkjSxPoqgBqckclEr6yrUyqvzmdyB/162YLmbPW/DFxECqg62l5l3vzVp2IC1f6nhMjj09PUW328X5+TkGgwHOzs5wenoaDArdkkP3x6H+yF3FqLdRVNPavbu7Cw5nJqF++vQpGCK0eDWxlmNgOY/2d8zVYvssNiYpspNZOTvP271uUvQscey5YKx/UCuuSm2sQzRxQWejlqPkiQQ9zmOsm/4nt1Pw0djgHjRchcfEWIplrszTCAH9jsfHx+j1esHIUA7NrJyPHz/i5uYGt7e3uL6+xnQ6xeXlJZbLJT59+hTutT4/219llLKAldPF9Gc7uZU4EVQFUibwzTlhijjAsfiyAiMmcvU6/k553T2dRMlOBOpq6uxmFna32w0hOH5zwdP5+XlYLKXhOYpatdoZetSt0dR/Rp8nFxt9+vQJNzc3Yb+X33//PeyGwGQKDq7VcS2nKzO0yihXV9Rr1YPBe3RSvjgIY05r5Ti2EsoJLTD5216nZMEb67ha7THXTkHId9Mxxkug0VLlO+y4Jpk6IUGq2T2MDXtij+E+Gh2MfiwWC3z48AGTyQS//vorrq+vMR6PMZ1Og6/Py3q27Yv1CfXi2MSNqTBaVhVxbH+relNlQhz00m0LGqLegkfBaEUxO8Az9/ltDRlv9qfEkp7TkBkztFW345KBwWBQSCQ4Pz9Hv98P4lotcCY96L4zAEKcmrHw+XyOP//8E5PJBP/6179wf3+PP/74I+z7wgwe2wc6mB4wvbamdHev/yzlgN0bfx7XePiL6YRWZJJsZITnPdHriWfbMHu/BWVM/KSAq6nzKibVwayxaOqK6nbhwGqaFvU2ZrtoQgN9e3/88UdwuzDaQYPDm4C2TfZcSk+M9b93re231DU8FqsDjTNvg6cUHZzAoA9OWV2qP9hzVagMgNZnZpVlWr8ayVBfoEZCut0u3r59G5YSqAjWVCpmrDDDhaDignLuZDCdTvH7779juVzi+vq6sA+0ZzBpm2MGmjfBtZ+8Y2UqjpYb00H1t2UM9AzQX5pLz+KE/F+mFLOjyzhl7JilGHfktzVY1A1jM3DsyjzNF6T3X/MTdcUdRS51OQJrOp0G3x+/mXDAuLDmKMasz1S/53KZFOfMfVYuaT+XtUfpIE5odT0gbZDofdbiLZvBHigt8PQ4dTYmMFDXI8g0GfXk5ATD4RCnp6cYjUahHE21YnIrxSyjFuSEunUGfXq6u+nd3V3YfNKzeL22xNrn9YFSStdTUCjjiIE05rFIkao8VehgccyOtH7C1PGcMsuOkWIqgIpj1sFLKlCfIEUx7yE4mGtIoDFThen23DJN47nr9Trs6ccUKw2zkcoGKkeExvRnrz88KpNKOWSB7bmTyqgSCJXVAo8NtA5qC8RDgWSPp8rQkJF68BnRGA6HePfuXVgTQiuZ0Q7uudzpdLDdbnF5eRkSBLjqjjoeDQtywslkEtaw0BrWXRoIpFh4U3VXbXPKAPP6p8wY8ADtPdPrf0+88r817nSpbQ59000yyzos13kZK9uSFWH6UcOEXG84HKLT6YRNk5j1QldRrVYL70a5v78vpI7d399jPp+HMBtByC12NdvZa6f3Xg9PBMcGr8zK9YwF779n4NjnWHUoRpb7qSh+cZ0wRTliwJttsXP6P4ejkgOyc9rtNo6Pj9Hv94P1y9QrWrzcHIgdSb2OonW1WgUQMrtZrWL7rjxLyqFsJrnX9hzOnyrDkrW4+R3THXVCWHFry6MeaJfs6rqgMnq2dUyyemAu5YI1B4DWnVGr1UIcmCBkyI0r2gCENHqKX+p3y+USHz58CAbGYrEIC4+U29rn22xxoLiTVUxilHFDpRygWtCoeE8ZhzEPSAqEdqe0FwWhPryKIuvph4cownqvdcsAj5xGc/roeuEidma0qKjlOzn0bUXL5TK8PoGWr9300lKuJEiVoeee20cp8X6oK8YSgaiTrApVeq0YH1iV65W5H1Limfpa6l4lciFuDafGByMb7Chau9fX12GzSDqgCUouLGJdPFHluTeU81l9NeVK8dqv/VPVX8j2xu6pChhPtFvdUA2lHPquu/fHfFOWdPDLxDI7xEY5aDkDX8Uv8JhWpRtHEph8/VfVtRuxOqasUnvcG+jnUC5HLOO8qTp74U+beBujg95tV+Uaz9z3RKknWlP32efxOMUCfX80PPb7fUhA4KuzmEbPDBeK4/3+MSmTnMTqmpYTWn2LH8vBlDvEBj0WDCgzXFLg9yxmT0f0rOvYxOC3biw/GAyw2WwKC7vKqPL7joHnuVpemlQv0dVsurs9V7NNp9NgbFAXpMj2nO0eN/OMADtonhslVndbjgeeKn1xKKWe5U02GwywL/xJUaX0fpX93ixN3evdA1TzS3nP8sSwhsS4RrfRaIQIx+3tLVarVeCIuhNXLCtcOViMi+s5y/G87xTFwJcS61XKT13ngcybWOxnblo6HA5xcnKC3W6Hk5OT7BV3B60xybk2JmZ0bYSKg9R9uc/Uj13RxgTUh4eHEOEg91N3S5lospNGKeVisYOYqr8tL7f9VShnspcdIxDVN0g32Iu8dFsBU7bU0FY0h63zGanne9dY8UXgEWC6zyHdMkyfV6PD+vW0zfY59h5bF69+ZaTl2Gyjsn72uGHqWq/OORPEHrOxeI0b6yafZfRNdmB4jgUX65QyQ8Ver8o8xbC+dHq3K+7GxUQFq4fZ2G6O/lbWPm1PWftTRl2qfK+uh0wKy4k9caxGoCb8MgQKvCAIbQXLDBSrB5Yp2THR7HGEWFm6DBFA2M+Gx3S3AktVOUQVDmXvi4HH6scpEZ/zLHuNvU6BpsfK7rW5g8oEdAu7HPomOqEHGB7LdWx7oEy5cWy9eN5m0eg1XrZwjHt4g5Wqey5pG3JFYaoOsclkjQsArnEV45YeF9S1I3pct/9QT8Q3B2GKexwijmOD7HGCHG6kHe2JjzLx6U0ir745FrxHMbWjjGL3VBXVvMcCPzUZyiaeB1J+qrjxnqUTWmU6da2CJHe9SUokK/itmGB9eI3XIdr5NhHBq7dXp9g1+oyy66qKewtErw+snpt6TmotiS2r7BqbzpXLnA4O28UGVisW0/limdeeTpjSYzzyOt12iqeTVdUHq5732lWV2Bee3uzVJ9aOnMmQukafr8xFjZQqiQyVXyGhjab1UzWdWyk1KNqJqhemuCO/FXgx3VLblgKe57apwsW13JwJFHt26jqP+8Xu8a7zxDS/tc0WgFxhRx9hv98PH938PkWVtwtmynxKFKcoJc5i+pg3cFZntJw0txyvHrHneNeUlReTBjn1iLXbuzYFrCrXV5lcVh/UJAY1VsqoMgiBx9lhd4byKgw8DcjrrIrphzHRbkVcjo5m6+Fxwm9hXOVQGdf3yk1xw9S5MnFcxh09C5nX1GrFjGo1CHWnshyqDEI2WlemlXG3lC6Yox96Zeq19neMvA62z61CZSCMASTXsMmpW4oB5OiEVUS4jo1ObA+kL8IJ6fTlQzyfU6zyHhAVUHZhvO10Tx+1z0txmCp6VdkzYvfmlJF6tnfcE8u5ZR+iI+bUTfs65ne0oCyjg8RxVTEUA6JXVmwQYyIzhxs9l9PkgC91PnY8lyOmdMTU9TFOn8MJPa5nJzuBSLXKqlDfHIRqJdlQTQ7FuFwZMFNGSZXn5lzHsmPPqgpGb+LYtsXuTV1TRs/RBWN9r4BT7wPDdF5K3Dffn9DuHuCx/TLyWLmKZu9Y7P4yfZGUY2Fa8srIIQ9gVUGYqkuZAZUCWdm1ZfdqhoyqTrvd15dk6iZP+smhygkM1hryyOOQMS6nZdtj3vUx/c8aKFVVBvvM5xgpZe6isjpa8ZsyvlIiNud/DnC9/7Xa05xNNV5fhBMSeMwh4waRQHElntex+/0++BYVjPyou4flWUNFB8AzWsrAHSMLhhQXzC1XVZcyv553zisvVr8cKhPPZfWx1ylH5EZQrVYr7D5BUL7YQidSTkaKnvPEMM+xvBgQY/RcfVHrZ+uac21ZmV5dqtbtuVxdn1kVhDxeNgaaIgcUX56ZQ5Veus2CNSnUa0COOI7tUKBc0RPRFpgpzvXcwSvjgrHBVU7onfc2i/KepQNrOX4VXdzW2/sfM770OV7Cb61WK+y4QO7IxWQ5VNkwsWnxKfGi5KX3qJjV8x635PM8sR6jb8FBcnQuO+nslh+xewjWVOIvj8X0MntdrB2pY2Wi2KpHKtU0aqJM5EXFMZFOUxx4usmPTesuA0NssGPWMjsgxj2+BZUNaBnALMWAqlwmZglX0deqTDzveq8ttVotrCHm+UajgcFggFarhbdv32I0GqHX6x008Q8CoX68NCkLBLuWwyM74+z9Xj282ezpdN8CmHZyeO3x1BPr8PX8bGy7fTXuofWrorfaupOsyOU1BOTR0REGg0HYcm8wGKDb7bocuowqieP9fh8WC/GYPtDOllQlYguKcpNe+SwPcCkQ50YpeG2qLCsGvcReKxXsGher88X00CpWdpkPVdUge53H6fmfH66u45Z7fNXacDgsvHAolyoZJrVaLezRQn1AZ7rqCJZTqP6jHe6J3Kp6nw5qCnD2eJUZm3qZtN2vRiWFfQUu1zmzf+xH26X11T7z6p0CswWhpuDbXcYIPqZj0b1mQagc8Pz8HOfn54U3YrVarWyOng1C7ufHLR7Uac2NhyxLT1mXuk+JmvmeGOA1OWBhRwIoqAuxa/UbeCpSLWdgXdlenVysp4LOU08ssW8UELYc3e1fvz2OWsYJdTtfq9fblCwFpqpM3CZ5u92i2WxiPp9jOBxiNBrh/v4es9ns21vH/X4fAMJGN/oeXx105QBKBBHTe6xizzdh5ojjlC6mXLhMF7XcjfeQoyug7caX2pYUqR7Fe/SZGnvlXjk0+vifITDlrOxfCzD9HfM20J0S6zeWoRNIfYEcq48fP6LRaOD3339Hs9nEu3fv8NNPP+Hy8jK8JDKHKm+cbvWGQ1ZXAdUiBykOaKM1CkAFkJLVjfS3tkmBTBByIBSoto62fAWfblcHfOV+ymWVIxFozGbn71qt9qS/Y0aaEsuwdde+8tSjWNBAN4XnpKFrhh6UHKrtDzHFXumVviEdvkLplV7pG9ErCF/pu9MrCF/pu9MrCF/pu9MrCF/pu9MrCF/pu9MrCF/pu9MrCF/pu9MrCF/pu9P/ATgAZdZJITOBAAAAAElFTkSuQmCC\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -522,17 +512,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 20: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0142]\n",
-      "Epoch 21: 100%|██████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0126]\n",
-      "Epoch 22: 100%|██████████| 63/63 [00:39<00:00,  1.62it/s, loss=0.0133]\n",
-      "Epoch 23: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0127]\n",
-      "Epoch 24: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0118]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 71.66it/s]\n"
+      "Epoch 20: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0135]\n",
+      "Epoch 21: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0133]\n",
+      "Epoch 22: 100%|██████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0128]\n",
+      "Epoch 23: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0132]\n",
+      "Epoch 24: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0122]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.15it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -544,17 +534,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 25: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0125]\n",
-      "Epoch 26: 100%|███████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.013]\n",
-      "Epoch 27: 100%|██████████| 63/63 [00:39<00:00,  1.59it/s, loss=0.0119]\n",
-      "Epoch 28: 100%|██████████| 63/63 [00:39<00:00,  1.60it/s, loss=0.0127]\n",
-      "Epoch 29: 100%|██████████| 63/63 [00:39<00:00,  1.59it/s, loss=0.0123]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.62it/s]\n"
+      "Epoch 25: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0132]\n",
+      "Epoch 26: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0125]\n",
+      "Epoch 27: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0119]\n",
+      "Epoch 28: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.012]\n",
+      "Epoch 29: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0125]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.35it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -566,17 +556,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 30: 100%|██████████| 63/63 [00:41<00:00,  1.50it/s, loss=0.0119]\n",
-      "Epoch 31: 100%|██████████| 63/63 [00:41<00:00,  1.51it/s, loss=0.0122]\n",
-      "Epoch 32: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0122]\n",
-      "Epoch 33: 100%|██████████| 63/63 [00:40<00:00,  1.57it/s, loss=0.0123]\n",
-      "Epoch 34: 100%|██████████| 63/63 [00:39<00:00,  1.59it/s, loss=0.0121]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.46it/s]\n"
+      "Epoch 30: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0127]\n",
+      "Epoch 31: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0119]\n",
+      "Epoch 32: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0121]\n",
+      "Epoch 33: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0115]\n",
+      "Epoch 34: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.012]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.99it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -588,17 +578,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 35: 100%|███████████| 63/63 [00:39<00:00,  1.60it/s, loss=0.012]\n",
-      "Epoch 36: 100%|██████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0113]\n",
-      "Epoch 37: 100%|██████████| 63/63 [00:40<00:00,  1.56it/s, loss=0.0114]\n",
-      "Epoch 38: 100%|██████████| 63/63 [00:40<00:00,  1.57it/s, loss=0.0115]\n",
-      "Epoch 39: 100%|██████████| 63/63 [00:40<00:00,  1.57it/s, loss=0.0115]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 72.46it/s]\n"
+      "Epoch 35: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0121]\n",
+      "Epoch 36: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0115]\n",
+      "Epoch 37: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.012]\n",
+      "Epoch 38: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0122]\n",
+      "Epoch 39: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0112]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.77it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -610,17 +600,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 40: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0117]\n",
-      "Epoch 41: 100%|██████████| 63/63 [00:39<00:00,  1.60it/s, loss=0.0112]\n",
-      "Epoch 42: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0121]\n",
-      "Epoch 43: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0112]\n",
-      "Epoch 44: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0119]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 72.22it/s]\n"
+      "Epoch 40: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0113]\n",
+      "Epoch 41: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0113]\n",
+      "Epoch 42: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0118]\n",
+      "Epoch 43: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0119]\n",
+      "Epoch 44: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0113]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.69it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -632,17 +622,127 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 45: 100%|██████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0116]\n",
-      "Epoch 46: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0111]\n",
-      "Epoch 47: 100%|██████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.0116]\n",
-      "Epoch 48: 100%|██████████| 63/63 [00:39<00:00,  1.61it/s, loss=0.0111]\n",
-      "Epoch 49: 100%|██████████| 63/63 [00:39<00:00,  1.62it/s, loss=0.0115]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.82it/s]\n"
+      "Epoch 45: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0112]\n",
+      "Epoch 46: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0106]\n",
+      "Epoch 47: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0102]\n",
+      "Epoch 48: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0113]\n",
+      "Epoch 49: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0114]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.84it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
+      "text/plain": [
+       "<Figure size 200x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Epoch 50: 100%|███████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.011]\n",
+      "Epoch 51: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0111]\n",
+      "Epoch 52: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0109]\n",
+      "Epoch 53: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0109]\n",
+      "Epoch 54: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0107]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.07it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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ZbnXqZOviWZ7Mk+eu0FDZbDZhmc+KQjtwvV6vJKoJQssZGVrG31z+45IigMAtuZJD4Fouzvpr2+yktaqK10f2ZTr6oZ81h04yTLwKe5WMpbH37OzUPLT8VONivi59vo5Oq76/fr8fRKQChf91S6guw3U6HVxcXKDdbqPX6wWOCgC3t7e4uLgITmrlXGpw6DfzZmCF6o3q/J5MJlitVhiPx6UIHgLH9plHqicrJ280Xk651W9+qCvn0NHi2BN3ChLVDThQJM8C9fxK5BreaVcx7mbzznnGtk/bqOKFHMh7Vlc16NNrt9theY7504LW4IZerxeiu9vtdugvtZi1bbSyKf73+33wMfb7/RAH2Wq1QvnqMGcdmKd+e22zfcE+oCFGUJNLc7/2qxsmCkTlaJwhzWYznPGinVqlsFqdDUBodOzlLSrKCGb9z98UTVbcaQerXsOQrXa7HZbqrq+vMRwO0Ww2wyCoHkmDgKIZQDjVge4choMpIMlNGNWt3M66YLT9qp+SG19eXmK9XuP29hbb7TYsA9IdpBLKUgw42jcUtQQe/1MNoFfg1UAIfGs96XXg5WUqg8Eg6Dsap6dpPc5llWU+QzHATtH0CjAdOF2lsIaHhlxxhhNYer41Q/q5stHr9b7Re6yOqBue+OYATgTds8LfPNOP/cR9K1p/lsMJoJY1OR33SK/Xa1xcXJQmKOvkiXir6ljua61+bT+XKTUNI89z6ChxbEWxilJyj16vh8vLy/D6BnY+dQU9bBIoA8zqg/bjWbv2rGlyBjqXOajKEVXxJyDYoRQrenYhxQxFjRXNlpNqfVmHyWQSuBWBSaKIpV9S/ZMWhBx09j25praDot1Tk2JGoXI51cctyKw1nMv1PDo6gMGbRQDCLjXuVKPSzYgSngmoooidQjBoY73ydUCsK4HAWK1WWK/XYb1VA0ntkpcq0xS/KkJVjdDABD2CmPd0lUR1uMViEfx/enC71pt7nQkoGkHWylUuxOe5Fs1lQPa31o1GEeupxLqSy/d6vVCG6oIe2FTlUfUgl046JNNLY810Woqq4JPTqH5hFdyUma+h8XYBn/oWB44TgL/1WT5DEFJfU52G9eIz9r1tFOvAi6JOV0mj0QjX+KGqQMc26+MBk0DhhLV6N9OyXvqf/VAabKMCeFKGQGU/2DH19Hp1tisIU1gp1SsrFfKsJ9tIujVUF2LjdLFfxS9nnHIj7WDg5R0lBADB2263cXl5GQZAjQVPHHNwVS+zr9HlWwC4jZMTSNtPzkoRqNanJdZjMplgsVig3++H821Go1GJ41jfG9vBNKoDs18ICE4qWzaAUmS4Fb/k/Pq2A2UQAEpjpt+qn6b2X1uqBcKYSLaV8Z7N4aTqlrAWrC1T9SYqwgSIch+SKvzsIOW47HQOHNvbarVK4NPBJcA56ynKVB/TOquRwPZq0KpawZbzsK7KwZkn02jcIeuheinzV3+ernfzGWu5W8+BTlTrIeGY1KGjTmq1QIrpCTYNOYue8ccO01lOrhprkOo0qqvZmcvrLIvij/VToFFn4hHC7OjlchkAogdpclB3ux3m83nJ/zYYDMJynQJgv98HzqqcQsP+1UKniNYJwH7RN08RyADChCA3U58ddU1VjVSFULeTGibsY8+w0fFX/dHDSYxO2m3nFaKcy7vPTtBznwkOteL0FQTWCuWA633LbbRDlGJWNoFPjkpORqBRb6ObRg0GukdUpHHgyb10CY9WO9/BnJIUygk1eEHdOQSq6qeqXxPMnidD81Z1xBqNluvpt62v9nMOHfW+Yy2Qsw5A6XWu1ihQv1ez2QyefBVJqu/QWrWiwdPhVIdhwCmvUzwr2agVRkJrmzRyWd0i3qoJB1BP76KVrVxNLV/qmOxX5SBqtDWbLy6vFBeiB4BR3wwt07qyvdY4swsJnnTReqbA5alQVXTSHhOgrCuqEQCUw53sRh2mVU6iDm12Pi01BaPqfQQbwa0WrKYFXpze7EQvUoRkgeoZCaq/UddSw4yck/5G4GX5jEEO1r2hHgPV01QP1bawPqyj+mTJ4RQ0OkYqxnWyaV46vvytjCeGlVcBoUdaKTZkt9uFM/4YAk9uqBVU7mgX15XjkTNYvUgtcPWBWWezulQ4i60SrjqkPnM4HAL3Vj203W4HTq8DqZzCijpd9GffcJ8y9Ts7UZVUNKpFznrrEiLraJmC5sE2qdO72Xw5GpmTmvq7cmpPVyR9N07o6S/qPmFkR7PZDABUbqcKuvdKBh1MgpCc0YKQ13guDAGrR/pSX2KdCFgebKRii7/JubjSoWqCGipskxWRVpdT0UYwKvdWzss+UN2Wk4eGiQ448DJ5PK5lxS3vU1qoZFDAan/EXEeeeH41EFqxm0K8ukC8AVO3BhtuZxO/G41GsB6B8qpEq9UKOqBalmoZ2s5XHyUPwiQA9Qg4choFIUUUjQqG5bN+m80m1GU+nwfnN8UxObZyEHVF2QFlOk5Wcnm2wzMCrSNeOZfmq0t81lDjt6786HWWY20CxUkdIB71lk9WyHIwEt+IRN1Eweftg/CsLW0EFXi+k45plUOoGLazVP1b5HJ8XcRoNAoisd/vh+2btG51QikX0IlkV0ysKsD8Op0OLi8vg66ofkediHb1Q9+vZ99Yb4HDdlqrVvuWwNe+sSC0IliB6Hk4gHL8aAwbHtXmhFpZe1+JFVFLLOW64fUchVfrwt/kUuprtCAkMAhYdXXQIa1HeFjxpVai1tW6gVRPZBrqfbRiOSHJdbW+qX6wk9em83Q2Wz/LeZmW4OO31QFtmZ4PN1bXFNXed2yVb69QDoCGUOl9r+OsCPbS2XI0v+Vy+c1z+k0x2+12Q2SMLuep85xgbLfbIZSLXEvDv3QNOVZPckqKcG6K0jV0DaBQb4BdJQHwjX6n3Mdat2pBa33sOGp++oxyQ6//bTuVXoUTHkPaaGtJxQDJeymOmCpPn7d6lvUz6myPkTUwGo1yFLg3SCRVCzSNumSoh3ruIq27p5fpda/enijWZ7w0Vvf2no9RHWNE6ag9JrEOsddS4jfFDWP56HN2BntKfaPRCMZBt9sNgakfPnwIJ/FzoxF1NA01o0GhOpx1JdHQUcClOIPWWy3nbreL4XAYyrarGGo86T2S+mJZjuWA2jf8jhkfVj+PkWek1uGCwInOao9jpURoalZpXqnZbmdvzGdFUHDjea/XCycbMDq61+uVIl8IVgWCGg9c9bAgpOWr4tN+FLxAeTWC5TDggN82zE37JiVBtG/UqW77kGVrfnW4mZe2LgCBE84n1IADdpa12Oyqg+ZlGxCz6BqNb609HXAdKPshmDqdTtgf0u12cX19Hd74zsFnGgYw0D9GXyKBqxE+1M80ENT6BTUqR7m9N3nZDl3h8fRjdUrrfdXhtA7e4Zv2u0rkpsZPV8j0/tkNk1glOPvUR8fOtqFKXj7At/sYdFGe4LaOXrV0gfIuNivSqPQTfJeXlyVHN7ndcDjE5eVlyXCgS+Xi4gL9fj+IPfrudFIQzOSo6uqJuVS0jxjQoE5kKxZjKk5sIqY4k6cLWrVIx9iCywOiV9cqOjqAgeKPYfycwVTctVLeGqXqSABKYpDWoa4Zq2GgxoWGIOmAWd2NOmCn08HV1VUApoKX2xKYH58jR2K7NFzKgoZp1IFtDSCrXthr7Gtr2NjVmZiKE1NnUlZtbMHAe87mC5Qjnai3vjonZAddXl7il19+Kc12Oni183R9mG4L5gMgvMhQ93kMBgM0Go1ShLU6njXSxsbM8WwWErlZp9PB9fV1ad2ZbRsMBsEw0V13anDQzaKcWo0EpiGpy0R1ME1vjSyd6Pqc3QwfA6AHOuVwsTQpvdwT56n/r+qiYWU0CICKuYJQY91i+Wjn80U1yt0IANU5yaX4YdkUy3QE8wg1jSqhuOSH5SiHsXooAcV9xCo2CS76/nSrAcukC4bAVWBZzmN14Zgep/poTJ/zxKPmFXMr5XDAGCnIv4ufkFzo8vIS7969C9wDKEf3Mi3Fqa7tKhdRsceZRECRaCzw3cMsX7mwikyu7y4WiwBedUDTkOA7jtWypjuGL03kaamqj5JbesGp1kq1ei7bq2Fp7BsFqK4AqbVLce95KLgubC1jqwZ4qkBK56xKq54Au6SXoqNBqI1QUQm8hBFZQ0L1PBsPaINPNb5NIzu0LM8RrPWzrg3PZcJ7ni4HoPT+Et01yPrE1mEVgOpJUFDpc6yHktZPNzSxffo7JS6PIQ/gMSNJ/2sdz64TpmYCkW9dNfxPn5xyD7WkFYQ6071TrZR4VJrXOQQNX/3QbH4NK/NEMWMe+Vy73Q7HA1OkKwhYZ90LDOCbiWV1WP2mukIdkz5INb6YL7kKVRP+5reKaDUQ2B/WR2lFuL1nx1x/a36W21lg5k6Gk/eYqD4Vi1tTXUj/e/qMVaBT5VIU6jPaQSqWCQDgZWMRJwnXdnXwWS97dIb+trNfnyWX1D7Qj/aZftgWT9R5IPI4vddf6g6z92z/e9e1Hl4kVNWYpehoEJJLzedzPD09BWevFbUECl0VNpKFjabOqCCiMUBQc9D0RTTkZjZSWyNk1J/X6Xx9WaIGMrB+zKPZbAYOq3oa66kAUK5uneoxX5+nm+k16+RXtYOnKhCs6jhn/haMHie0FnxsfHUrqkoZ7QsyGOat3zl0NAjZsPV6jcViEaxT5QYEI9PTWlSRpHql6n8ae6iWaqvVClxLOREjuFV86nG5BAmNC3YyVQB2rIo7djCvWQDqfQ9MSilxF9O17I5EBbrn9iJgPd1X81Wx7Vmy5HbsQz1WzvYnJYqnD+fS0fGEbNx8PsfDw0NYcaC7RV0t5IA6cDZMiBxSB8WKEG20plVOyKM+7ExmmcoJLy4uSue1aAArO5YAsGu9OggcfLbRplV3k24p5X1raOn+EavOqK5IQGh7ScybE1RdQFqeJXI9jXn0xC/HTOtly86loyOrObjcHE5lXl0g9jwT4Fv/lTbEhlfZGaVgVIDopKCzWi1a1QH1jJjD4RAOECJnZp3oBKd4VsBooALrqGKTA62Tj/mpT9XqzsyTg245rAKSRBBaK551UXHK59nPnqqgBprq1tbgUA6oxhHv6zbaKqotjhUIOnisABVyG25kZ53Vq5TDaONsWZZbkqyCb61kruPa5SQFj16zHFu3D+jvVutlpx+/1S+qgQzU6VRf1Amk68gqddhe3tP01GcXi0VJt7WeC7aTY2HHQyeAFeeqb+q3zYNpqfM3Gg38/e9/TwMKR4LQOk9pQfKVBjG/nd6zs1DZuh04FR9WHFm9R8vTQdbtnbZTWT4HmuUpkBhPyI3t/M0YRN1H4rVFI2K07npQwGKxCP2pFjcnOkWj7tfhEXiLxaJ0cr+Cz7qWWDbv6eS2a/oKSKtnsh46eahz8xiUf/zjH5WYqr12rLOzKq13TcWCvc8Osd+eDsZndMazfkDZclMORp8llwn1lFEGr/KELFUpqOfyeY3CUR+oFVFqzFjXS0zckXiP9fNWIghOnujAbwJby9RJyP62e2EUuMoJFdR6IppKHtaFnodc4+Sk9x2r6a/fOSCN+af0t/1WbhXLg2k0PKvf7+Pi4gK3t7cYDoe4vb0N12z0DuMGb29vS2C0XFkd3nat29abuqoOoBVzOokoLZQjUpxqtNDhcAjLkjy9n+/CW61W4V142ifNZrPkQVAdWrkwlysJap54y2es6FbicqonET2qBUILNguA2D2bTyp/TePpIDqTlaNafZLcajgc4uLiIoRp8VwXcjzlhGpM6DtBYvF9WnfV17z71uqMcUU1TCynUYc2ULaMyfn0o/5UWt2NxtfTv8gtaYisVqswWWhwKgD5W0GotoASI5rOzgnZWZbUqrMArOKImodWWjmqFbl0oZDzEGx8TwjPgh6NRuGINoaJMZL65uYmuGh0qdCzbjlYGhlEw0PPrta2W9BYa1PB53ELy03VUidYCAYCarFYhHcnz+dzrFYrzGazErB4LN90Og0gUwCrs1+PZ1GureMam5CdTqe0+7GKjtIJSdZ6s9zMcrYq8vJWA0NdFFwDpjFAQN3e3gZxQPDxBFRyNuqD+oZOPeVB68LO54Axrs/6PdlO5YpWibcgtM/rt04EHQNyR+tIJlfja8dosNB42W63mM/n4VW2tKb1UHl+A/iGY+uksB+tHz92TT9FRx0XHAOVBYv3jP0mWR1JXTd0rRA0FxcXYdMSjwfmzrmrq6twTLEGK7B+rVYrLNeRixKAqictl8sSCNQqVSeuchqvf2LttW4h6zZpNBqhbbrnmUePsE4E32w2C+/J41HE4/G49BLv2WxWOkjes3hjejZ/ewC0PmAbEVVFZ9l3bDmiXvf0PDtIVj/it8YaEnwE2s3NDQaDQQDdzc0N2u12COG3e0yYp/r8mMazArkhnnUgANWK5DW6VrRdVr0gqXtLB1eNEzrIlRsyDdfB1VomR1sul5jP55jNZpjNZhiPxyiKAl++fMFms8F0Oi2JWY9ZKHf2QGfB54FR65xD32XzO38rWV1I9Ty73VJFLXfN6WYltWK5IqEdpJusGo1GiXPpOrL98NnD4RCsRR0gckn6SflfRWjVINu+UqNKTwsDyq9q4ESZTqdYLBaYTqeYTqf48uUL/vrrL8znczw+PgYfIsGqRp7WJyZutX5K9FKoPcB0lBTfFYQpi1dBmNIr1BnMY944GNyq+eHDhyCKR6MRgJdZp+8dYcewQ+w7NZQLKBe0zlcAAbCTySTEGBKAup1TweO11aopatBpHdTprQ5urRcjxlerFabTKebzOabTKZ6fn/Hw8IBPnz4FTqgWu+Vc+q2gtGMUG2sC0dKrgTA3Q03LztflL10n1lURdSLrZqNWqxV0I1q8+ooIr6NidSYX0QV5FWvUBymiVQzT98bydO2V4l7Fkn6ULBBUDKuKoCsu1AUZfEtrmAG7fKPneDzG09MTxuNxmDw6IepSzBti73n9zPXrHDqLYUKwWQ7AStjIajUOKGq5HEZOqH47ptVlMa8zUqSOWHUC8x6VfO4XeXp6KrWBIFV/JIDQJtZXdVHP2LD9yAHjeiuVehXH5Hr0161Wq/B6ssfHR8xmM/z555+4u7vDp0+fcHd3V5oo5KgqmTwOpxw7Jd08Tqr5sT/PDkIlW0n724Zc8YUxdAJrpA3dKFypYFpd+rJh8woOO9MpBqj/0AdGLkddSkGoAbDsPBv9w7I0jExnux1UnSQet7bWqHJ1G/rmGU6r1arECWmM6NF2MUlhdVRtnwLRXk+Rl8YT1R6d5bVi6qSlqKUYpTVLq5UOY3JA5YQ8buPy8jLMpt1uFxRr4GVjNfUxBeN2uw1p6bDlh1xkv98HN4fW27NMNX9yNu5N5qSy/aN9oktxlhtxQnixi1zV0bbpJOGLtOfzOf788088Pz/jjz/+wN3dXSmCScv06pgiK25j0s/75vPf3Tq2qwAECrkbrViC0H4ThFzl4OoAOaJauBxgKsbqxKUPTNdTi6II3IP56qqG5x8DymJGo8QJSO43phPbuj60P6yXQA0RFeUa6+c9Q85Of99sNsN0Oi1tW63Slf/X6CSd0PP50a/HVYuLi4vw0agUjTWk2NN9y1TGdblJVy8ITF2S4ponFXcN+VddkJyQwFbHrRUhdilvMBiEdvGI4e3269s16cfUvcR81k4itpmqCB3ufEaX0oCv67HT6RR3d3eYzWb4/Pkznp+f8a9//Qvj8RjT6bTUl2q5Wt0sxRm9ex5XO8XgsXTSu+20QpqOs1oPB6KS7Tky9Xm7JKUf6xDmpnQV2bpZXZekgJelKLsZygYJ6ORS57Lqmvv9HsPhENvtNrzTWSNc1BOgIGBZeswIV3iGw2GpnlRHVBrQGT2fz0sWMdtouXCKUuIzph/G8vB031yj8ahjQGKZW7cDZzMPI9d1V3JNHsu7WCwCUBl6z+CByWQSdCF9AY1GEpMTcvVCF+dt/Jv+t0q/Lh2yTfph0CgX6Kk6kCOSq9m1bfueZ7qaaIjRIa5BCjSAnp+fMZ/P8ddff+Hh4QHj8Ri///47np+fMZvNQnovjCwGJE9cH2OQ2LE/hk46vV+v66CpaCNQiqIondqlIqnRaIQN6lwj1ufH4zG22y1ms1kpqkU5JEHIqGLdb6GL/srt9Nty2RhpeBPdRo1GIzjYt9ttkACMLgZejhZR15QG1tLxTEc0gHBy63w+x5cvX/D4+Ijn52c8Pj7iv//9L+bzeTj4yao33nh514+hGDhT0jJFZ1+2I4ehXga8iNhWqxWMDd3Pq+4YXlOxSfDRYWudyxqcqfcVZKwH62g/QNoDoKSAJYB1cgwGg2BF39zcBH1R96GQy6kDmuCjs5ygvLu7w93dHR4eHvDx40eMx2M8Pz8H3db2n2fJpsbrnAbMMUA/CoQxS5IDSiC0Wq0gKouiCIq4uiw02kKdt9vtNuzko2FiI1k88KU4WspiVK4M4BtDQuuodQAQggr4whsexHl1dYVff/21tHtPN8oDCIEHbANdNPv9Hk9PT5jNZvjjjz/w8eNHfP78Gf/5z3+wXC5xf3+P3e7lFDDWXQ0f63g+l3Fh/YwpP2QOncwJ7cxTq5MiUjmhbmdULsgBVSczjQ670mHXUatcLVpX/Y6Rx0lYTz1ondHZ1AM1TpG6HkUyOTcHnpNQ68/JxxPA7u7uMJ1OcX9/Hyzg5XJZCufKbeexut4p9CrLdnaQvdlGTgi8vIFJ/V/qF1M3gopGCzAb5eKJUq2T999arUoWwLaNwNcDNPmu49FoFM63HgwG+Pnnn9Hv9/HTTz9hMBjg3bt3uL29xfX1Na6vr7HZbPD09FTaVESRzHI52YqiwMePHzGbzfB///d/eHp6CrrgbDbD4+NjKQ9b5zqcKceXmDNhrV/SSpUqOqtOaIFKccHKakwexZH1OerHs2Jj4PPqYn/ndHqMC+puPV3n1o99I4BGyXj11j7ZbDbB0Hh8fAxRMZPJBPP5PDjere+vjjFQlwPmSI5zcNSjjobzOIX+V2Cp4q5pYg20oNRrOfXzrtuyVG/SNKpKEHwaTnZxcYHr6+uwheDq6gr9fv8bTkgOeTgcMJlMSst31k3EPSHPz8+BA/773//GcrkMQamz2SzojZbrpIDl3dNrVeP4veikQzJT91IisyqfU0CXumc5tQWixwXpdCe3o+Wb4ojqLrF7NVRH3u/3pTCsh4cHzGYzfPnyJWzlpJ9VI6q9NsUoZpT8L1E2CK0T14oVSzpjz8XVUmlsZ6fAHauX6jdczbi6usJgMMD79+9xc3MTxK4GMlxfXweA8oCl+XweYiPX6zWen5+xXq/x+PhY2oT08PAQwrHu7+9RFEVYAdGXMXrh9kD5la+pPqojinPFcErNeRUXTQw8Flwed/H0Mw/EsYbk+L1yrjEfdWd4dVAg0hi5vLwMWwr4Uae0xjrSyKBuyIADilhuUF+v17i/v8f9/T2WyyWen5+Df1U3m6sfkKRh9Z5xmAuC3LS5ngXvmSo6q2GSw+2qZqyXtq4oqQKvN3F4nyKYIvf9+/dhSwGXFQk8ywFp8dL5rMtqFLFPT0/hm6B8enoKgaq6DVPrZNugu/vsvWOB4unPMQPPez6WbxWd3U+oFBvs16SYGLaiyfsNvJwLfXFxgcFgEFwt9vUT5I7kghqCRcczj+LghqT1eh2Mjb/++iusCTMYdTablZztng5IUpAe0yfnJMuhPc6dolfdbWepSomOGQfnKDf2X39rRAstX13f5VqxumTIHTXmkXt+CUIGoVIn1LB8Dd3XMLJUu+saenX7Jzcvez/XOW3p6PMJAd/Ej4nbWMedyzVQZahUPdtoNAKHu7i4wC+//BL2NROIjBbnteFwWIod5EoHAwwIwqIo8PDwgPV6jYeHBxRFEQJRuUrCOlvxG3OpVLW/6nrVM7GJGhPXNoLHM1Zi9F04YWyVpQ7VAXLqvgdW6nJcgiPodNMRHdFciut2u8EZz62g3FLAvcA8D6YoinCP33oy1v+yGyXXAo7pljn0KoaJ/W3pWEPjGIXb06vsoUQ0RK6vrwMH5KFJNFA+fPgQjhoZDAbBgCDYttst7u/vg9+Pqx88kuPh4SGcgmA5n62zWvG8HgNALgeMleOlS+XtpY/pf6+62+7/J9LoZt37rFxQ7+teEz1hlQDjCghPyKI41uPYuKNPpUIumHKkSK6Kk5IQVQA8J9c+y5ZPwHeHqJipYxmf2+KL+TK5JPf+/Xvc3t7i8vISP/30E/r9fuCE1PtoiDC4li6V9XodnMvc/0HXDMUwI2NoeNhdejlcLldkVwHF0+ks98vRAas45nezjuuCKye/c6YjxVxE5HBc7+XeZ8sNaQGr+4UuGC6vcY1XP9QBuVYMlM+peQ2VJSdNCnC5ACTVAVuMvot17N2P/a9TZh1iMEWj8fKGzZ9//jkEJTBEi6e6vnv3LgCQ4GM0C0Xuw8MDlssl7u7uggWs+5019CxHv4pdP1ZsVvVpFfdL5RXL2zv6pIqOAmGur89Lm9uY3PQ53JhpCAZauzc3N3j37l0Iv9JAVJ5/ww7lshtPO+AJWIvFAp8/f8ZyuQyrIAxQqBJZdegcUsKrS+7vGBdU+m5+QlYkxtFSaevkn0tVqzUsny6YdrtdOhSd4pd6n26+12BacrjxeIzxeIzJZIJPnz6VAg641gt8K6Zy3Es54i+WNpZnKo0Hrtxr9re15OuM4UmhXJ7/LydtKs9jKRYbR+7XarXC5vQPHz4EPVBXPgaDQQjVPxzKWwweHx+DCOaS28ePH0M0tEYZ6eGbMQMuNtixPjmGE1ZxthzgpTggr8X0wrMbJh7HiwExJYbrBDAcSzr43pEkekqCxguSUwIIe3npfiH3e3x8DIDUtydZV0sV56sDvCrdsQoAuTpmjo6YkycpVwIebZjEwKhA9CpyCuBS4s2WR2CQw9EZze2X1Pu4/KYrIdzrvNlsMJlMsFqt8PHjx7D39/7+Phg6FvCshz1OJDawscHMNQhywWbzjP2O7V22R9yRYlzwVc8n9MCW8hF+T/LKpDNa4//U9ULup8e96Un4PFhpOp2GMHtuVcgVlTmcxcuvDqiqyvTyiIlbm9Y7/q4O+Kvo6JNaLQBTopnp65aRS57exQ7WE17JAfnNQARuSqIBQndLURS4u7sLR7Bxxxzz97iG1w96L9XmOqI69by9b41Ib1LEyvaOFiHpmUKnWMpnddGcwgHrAjBWlgUA9UHLAXU5jsSAAn09F32C3O9L8MXEmdYtF4A5Yjr2bOp/Kv9UHjng90B2LBPJBqFuX/Q69dglurpk848FzpK70fE8Go3w4cOHYIRoECpF8Hw+D6ce/Pnnn1gulyEimgcg2VdS2D44hfPFrsWejz3r9VeK89kPkA6eiFnH+p/7YnLoqAORUhZuFXeK0THhXbF8WB/6BvX1YvYgykajEXyBRVFgPB6XdrxxfVj3+9L9oiH2HOxYZIylUwF4bk6Y0/cx4yRG1jiL0VmOCz4XxXx9No21gL16aRQ0w7G4ksHzb7jmO5lMwmbzz58/h6BTdcHo7LcR0FWiWSl1P0cUV3HCnPXoKn0wpQfG6uA9m0u1jwGxeo/+ztEVY1y0agXGXq/iuFyaYwgWz0TUNHy/2/39PR4eHjCdTkPcn679AmWRk5IEdUBYxc1S14/R53I4aY4rJnZdf9dhVrXF8TEhWyng2OsxsezpgbH7wMs7QXR/CPVEvipVX8PAQFSukNjTvTxvQBXgLFUBM/b/mLS5XDUGWgs0r7xzRNAARx4DYivD/57fsAqAHuWuS6fypj7IwASK58PhEMKsPn36hMlkgslkEna8MVSfHZ+a3VXLVXV0Qy+N/q/SNXPqEePCqXyrOKDlgvyfqw8CJ4hjvfajqUpEkhiUwE1GGvfH3W45Oho7uy4oqvJMPVtHR0uVb9NYIOmzMevWc14fUz6plosGKB+jFuNEOSL6VKrKUztBj5hbLpf4/fffMZ1Ow2kIGvNn3S9W7KZ0uTr6YJ30qbblXItxwhwA2mc97u+dsvsqILQNy0n3vRzXHrFsPVr4cDgEJ7S++VzLrQLOqddz6RSOl+LmsYmUqnOKM8ZA+arimL8th7Ci+hx+P/t8zIXjgZ2vD+Oh4zz/b7Va4fn5OVi/9qAhOuXtMRw53KuOqD2HeM1RB2Lgs8BSgFn9LnaN6+28pi8BqgPEo53VrFBq7Zhpj6E6APbSEkj6ThMexUEOqO2wnWwHz17zvk9pxzlAGcsr9l0lWlNlpixjBWIOnRTUysEDEAo9V2RNrBNi7hl7j5xwsVig2WyG49kYIcPwe+0o7xCiHMB5XD/GpVKcqQ64vbxzygPyfH56zaazL59ULOh22Fw6ebedrSBwviW4VL5eZIhe15AsHrXLtz5RP1TxYY0szzeWEn+x6ykwx4BYB4SpsjVPUozTee311o9jwRu8xyVN3VVYRScfkukNoBXTvJfihqeK8pioIUekCyZnZSYFhBQQU1wy1RZPvUnlmSrbS2/1vpjlq+lzOaVXr5g4j1E2CO15eFWHmFvw8bdSFSC953KXzBSEXAWx+dr68d6xIIy1IdVOLSs2EXOAn8Pt7DsFmTanXZ5z2ktThwOSanNCUgqAStpJOelTZLluCgR0zbBsgtCrg2fZx9oR+19FHtDr/Lb5xMQ72x4DjOVmMQvWS2eDOOhTVR3xmG2f2SCkosnGeW9OSokOBaHX2TEuZcV+CkiaTjlf7PmYDgV8y/lzQFdnQlpOlRKjOSC0y4z64TXv/Xex+tuDLvm8fgMovTaYm8mAV1q2i1WW/1MD6v2Pdab+Vn3KirUqzmWBmsuBYxOrSuWoKicllmP3PF27qt6pfIAXjhariw1GteqUjgfrpBPB3s+hxuEU+fhGb3QGOu7chjd6ozPSGwjf6IfTGwjf6IfTGwjf6IfTGwjf6IfTGwjf6IfTGwjf6IfTGwjf6IfTGwjf6IfT/wOf3+FEjdkeDwAAAABJRU5ErkJggg==\n",
+      "text/plain": [
+       "<Figure size 200x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Epoch 55: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0111]\n",
+      "Epoch 56: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0113]\n",
+      "Epoch 57: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0107]\n",
+      "Epoch 58: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.011]\n",
+      "Epoch 59: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0107]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.97it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 200x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Epoch 60: 100%|█████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.00995]\n",
+      "Epoch 61: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0105]\n",
+      "Epoch 62: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0103]\n",
+      "Epoch 63: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0103]\n",
+      "Epoch 64: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.011]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.43it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 200x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Epoch 65: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0108]\n",
+      "Epoch 66: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0104]\n",
+      "Epoch 67: 100%|█████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.00969]\n",
+      "Epoch 68: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0108]\n",
+      "Epoch 69: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0102]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.69it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 200x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Epoch 70: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0101]\n",
+      "Epoch 71: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0106]\n",
+      "Epoch 72: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0104]\n",
+      "Epoch 73: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.011]\n",
+      "Epoch 74: 100%|████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.01]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.73it/s]\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -654,12 +754,12 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "train completed, total time: 2105.790970802307.\n"
+      "train completed, total time: 3098.574437856674.\n"
      ]
     }
    ],
    "source": [
-    "n_epochs = 50\n",
+    "n_epochs = 75\n",
     "val_interval = 5\n",
     "epoch_loss_list = []\n",
     "val_epoch_loss_list = []\n",
@@ -749,7 +849,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 800x550 with 1 Axes>"
       ]
@@ -799,12 +899,12 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.73it/s]\n"
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.90it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
diff --git a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py
index d2f3f6e9..0bf59a7f 100644
--- a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py
+++ b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py
@@ -86,7 +86,7 @@
 # ## Set deterministic training for reproducibility
 
 # %% jupyter={"outputs_hidden": false}
-set_determinism(0)
+set_determinism(42)
 
 # %% [markdown]
 # ## Setup MedNIST Dataset and training and validation dataloaders
@@ -163,16 +163,6 @@
 # %% jupyter={"outputs_hidden": false}
 device = torch.device("cuda")
 
-# model = DiffusionModelUNet(
-#     spatial_dims=2,
-#     in_channels=1,
-#     out_channels=1,
-#     model_channels=64,
-#     attention_resolutions=[2, 4],
-#     num_res_blocks=1,
-#     channel_mult=[1, 2, 2],
-#     num_heads=1,
-# )
 model = DiffusionModelUNet(
     spatial_dims=2,
     in_channels=1,
@@ -193,10 +183,10 @@
 inferer = DiffusionInferer(scheduler)
 # %% [markdown]
 # ### Model training
-# Here, we are training our model for 100 epochs (training time: ~40 minutes).
+# Here, we are training our model for 75 epochs (training time: ~50 minutes).
 
 # %% jupyter={"outputs_hidden": false}
-n_epochs = 50
+n_epochs = 75
 val_interval = 5
 epoch_loss_list = []
 val_epoch_loss_list = []
diff --git a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial_ignite.ipynb b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial_ignite.ipynb
index 97614701..c5aa36f8 100644
--- a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial_ignite.ipynb
+++ b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial_ignite.ipynb
@@ -44,7 +44,6 @@
    "execution_count": 2,
    "id": "dd62a552",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -54,24 +53,24 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "MONAI version: 1.1.dev2239\n",
-      "Numpy version: 1.23.4\n",
-      "Pytorch version: 1.9.0+cu102\n",
+      "MONAI version: 1.1.dev2246\n",
+      "Numpy version: 1.23.3\n",
+      "Pytorch version: 1.8.0+cu111\n",
       "MONAI flags: HAS_EXT = False, USE_COMPILED = False, USE_META_DICT = False\n",
-      "MONAI rev id: 13b24fa92b9d98bd0dc6d5cdcb52504fd09e297b\n",
-      "MONAI __file__: /home/mark/Envs/gen2/lib/python3.8/site-packages/monai/__init__.py\n",
+      "MONAI rev id: c81b9467b43bb14e77956729d10f2aef4d69deec\n",
+      "MONAI __file__: /media/walter/Storage/Projects/GenerativeModels/venv/lib/python3.8/site-packages/monai/__init__.py\n",
       "\n",
       "Optional dependencies:\n",
       "Pytorch Ignite version: 0.4.10\n",
-      "Nibabel version: NOT INSTALLED or UNKNOWN VERSION.\n",
+      "Nibabel version: 4.0.2\n",
       "scikit-image version: NOT INSTALLED or UNKNOWN VERSION.\n",
-      "Pillow version: 9.3.0\n",
-      "Tensorboard version: NOT INSTALLED or UNKNOWN VERSION.\n",
+      "Pillow version: 9.2.0\n",
+      "Tensorboard version: 2.11.0\n",
       "gdown version: NOT INSTALLED or UNKNOWN VERSION.\n",
-      "TorchVision version: 0.10.0+cu102\n",
+      "TorchVision version: 0.9.0+cu111\n",
       "tqdm version: 4.64.1\n",
       "lmdb version: NOT INSTALLED or UNKNOWN VERSION.\n",
-      "psutil version: 5.9.4\n",
+      "psutil version: 5.9.3\n",
       "pandas version: NOT INSTALLED or UNKNOWN VERSION.\n",
       "einops version: 0.6.0\n",
       "transformers version: NOT INSTALLED or UNKNOWN VERSION.\n",
@@ -98,25 +97,25 @@
     "import os\n",
     "import shutil\n",
     "import tempfile\n",
+    "from typing import Dict, Mapping, Optional, Union\n",
     "\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
     "import torch\n",
+    "from ignite.contrib.handlers import ProgressBar\n",
     "from monai import transforms\n",
     "from monai.apps import MedNISTDataset\n",
     "from monai.config import print_config\n",
     "from monai.data import CacheDataset, DataLoader\n",
-    "from monai.utils import first, set_determinism\n",
-    "from monai.engines import SupervisedEvaluator, SupervisedTrainer, PrepareBatch, default_prepare_batch\n",
+    "from monai.engines import PrepareBatch, SupervisedEvaluator, SupervisedTrainer, default_prepare_batch\n",
     "from monai.handlers import MeanAbsoluteError, MeanSquaredError, StatsHandler, ValidationHandler, from_engine\n",
-    "from ignite.contrib.handlers import ProgressBar\n",
+    "from monai.utils import first, set_determinism\n",
+    "\n",
+    "from generative.inferers import DiffusionInferer\n",
     "\n",
     "# TODO: Add right import reference after deployed\n",
     "from generative.networks.nets import DiffusionModelUNet\n",
     "from generative.schedulers import DDPMScheduler\n",
-    "from generative.inferers import DiffusionInferer\n",
-    "\n",
-    "from typing import Dict, Mapping, Optional, Union\n",
     "\n",
     "print_config()"
    ]
@@ -140,7 +139,6 @@
    "execution_count": 3,
    "id": "8fc58c80",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -150,7 +148,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/tmp/tmpfkfmzhbz\n"
+      "/tmp/tmp4s7ozrr7\n"
      ]
     }
    ],
@@ -173,7 +171,6 @@
    "execution_count": 4,
    "id": "ad5a1948",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -199,7 +196,6 @@
    "execution_count": 5,
    "id": "65e1c200",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -209,9 +205,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-23 23:53:01,298 - INFO - Downloaded: /tmp/tmpfkfmzhbz/MedNIST.tar.gz\n",
-      "2022-11-23 23:53:01,372 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
-      "2022-11-23 23:53:01,372 - INFO - Writing into directory: /tmp/tmpfkfmzhbz.\n"
+      "2022-11-26 00:25:55,677 - INFO - Downloaded: /tmp/tmp4s7ozrr7/MedNIST.tar.gz\n",
+      "2022-11-26 00:25:55,746 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
+      "2022-11-26 00:25:55,746 - INFO - Writing into directory: /tmp/tmp4s7ozrr7.\n"
      ]
     }
    ],
@@ -238,7 +234,6 @@
    "execution_count": 6,
    "id": "e2f9bebd",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -248,7 +243,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Loading dataset: 100%|███████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1816.33it/s]\n"
+      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1792.22it/s]\n"
      ]
     }
    ],
@@ -270,7 +265,7 @@
     "    ]\n",
     ")\n",
     "train_ds = CacheDataset(data=train_datalist, transform=train_transforms)\n",
-    "train_loader = DataLoader(train_ds, batch_size=8, shuffle=True, num_workers=4)"
+    "train_loader = DataLoader(train_ds, batch_size=8, shuffle=True, num_workers=4, persistent_workers=True)"
    ]
   },
   {
@@ -278,7 +273,6 @@
    "execution_count": 7,
    "id": "938318c2",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -288,16 +282,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-23 23:53:23,922 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
-      "2022-11-23 23:53:23,922 - INFO - File exists: /tmp/tmpfkfmzhbz/MedNIST.tar.gz, skipped downloading.\n",
-      "2022-11-23 23:53:23,923 - INFO - Non-empty folder exists in /tmp/tmpfkfmzhbz/MedNIST, skipped extracting.\n"
+      "2022-11-26 00:26:19,327 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
+      "2022-11-26 00:26:19,327 - INFO - File exists: /tmp/tmp4s7ozrr7/MedNIST.tar.gz, skipped downloading.\n",
+      "2022-11-26 00:26:19,328 - INFO - Non-empty folder exists in /tmp/tmp4s7ozrr7/MedNIST, skipped extracting.\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Loading dataset: 100%|███████████████████████████████████████████████████| 1005/1005 [00:00<00:00, 1835.72it/s]\n"
+      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1005/1005 [00:00<00:00, 1773.89it/s]\n"
      ]
     }
    ],
@@ -312,7 +306,7 @@
     "    ]\n",
     ")\n",
     "val_ds = CacheDataset(data=val_datalist, transform=val_transforms)\n",
-    "val_loader = DataLoader(val_ds, batch_size=8, shuffle=False, num_workers=4)"
+    "val_loader = DataLoader(val_ds, batch_size=8, shuffle=False, num_workers=4, persistent_workers=True)"
    ]
   },
   {
@@ -328,7 +322,6 @@
    "execution_count": 8,
    "id": "b698f4f8",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -343,7 +336,7 @@
     },
     {
      "data": {
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       "text/plain": [
        "<Figure size 1200x600 with 1 Axes>"
       ]
@@ -381,7 +374,6 @@
    "execution_count": 9,
    "id": "2c52e4f4",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     },
@@ -395,11 +387,10 @@
     "    spatial_dims=2,\n",
     "    in_channels=1,\n",
     "    out_channels=1,\n",
-    "    model_channels=64,\n",
-    "    attention_resolutions=[2, 4],\n",
+    "    num_channels=(64, 128, 128),\n",
+    "    attention_levels=(False, True, True),\n",
     "    num_res_blocks=1,\n",
-    "    channel_mult=[1, 2, 2],\n",
-    "    num_heads=1,\n",
+    "    num_head_channels=128,\n",
     ")\n",
     "model.to(device)\n",
     "\n",
@@ -434,10 +425,10 @@
     "    Assuming a supervised training process, it will generate a noise field using `get_noise` for an input image, and\n",
     "    return the image and noise field as the image/target pair plus the noise field the kwargs under the key \"noise\".\n",
     "    This assumes the inferer being used in conjunction with this class expects a \"noise\" parameter to be provided.\n",
-    "    \n",
+    "\n",
     "    If the `condition_name` is provided, this must refer to a key in the input dictionary containing the condition\n",
     "    field to be passed to the inferer. This will appear in the keyword arguments under the key \"condition\".\n",
-    "    \n",
+    "\n",
     "    \"\"\"\n",
     "\n",
     "    def __init__(self, condition_name: Optional[str] = None):\n",
@@ -472,7 +463,7 @@
    "metadata": {},
    "source": [
     "### Model training\n",
-    "Here, we are training our model for 50 epochs (training time: ~20 minutes)."
+    "Here, we are training our model for 75 epochs (training time: ~50 minutes)."
    ]
   },
   {
@@ -480,7 +471,6 @@
    "execution_count": 11,
    "id": "0f697a13",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     },
@@ -491,13 +481,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-23 23:53:29,033 - Engine run resuming from iteration 0, epoch 0 until 20 epochs\n"
+      "2022-11-26 00:26:23,940 - Engine run resuming from iteration 0, epoch 0 until 75 epochs\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "1c2f0dbbb33c44768695b86f48bd12e0",
+       "model_id": "48e16011b2cc4b0fa78c7c0d92db431d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -512,7 +502,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/home/mark/Envs/gen2/lib/python3.8/site-packages/ignite/contrib/handlers/base_logger.py:172: UserWarning: Logger output_handler can not log metrics value type <class 'list'>\n",
+      "/media/walter/Storage/Projects/GenerativeModels/venv/lib/python3.8/site-packages/ignite/contrib/handlers/base_logger.py:172: UserWarning: Logger output_handler can not log metrics value type <class 'list'>\n",
       "  warnings.warn(f\"Logger output_handler can not log metrics value type {type(value)}\")\n"
      ]
     },
@@ -520,14 +510,14 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-23 23:54:25,703 - Got new best metric of train_acc: 0.15793311595916748\n",
-      "2022-11-23 23:54:25,706 - Epoch[1] Complete. Time taken: 00:00:56.527\n"
+      "2022-11-26 00:27:34,129 - Got new best metric of train_acc: 0.1597186028957367\n",
+      "2022-11-26 00:27:34,130 - Epoch[1] Complete. Time taken: 00:01:10.146\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "7f43fab678014e8da03a0db4718694a2",
+       "model_id": "f22412df96b5457cbcc067bdb39af189",
        "version_major": 2,
        "version_minor": 0
       },
@@ -542,13 +532,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-23 23:55:23,181 - Epoch[2] Complete. Time taken: 00:00:57.474\n"
+      "2022-11-26 00:28:44,143 - Epoch[2] Complete. Time taken: 00:01:10.012\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "562e9c0b5aec42c581d7c983679090b7",
+       "model_id": "bc286a2b836c4c758fc880fa2a514828",
        "version_major": 2,
        "version_minor": 0
       },
@@ -563,13 +553,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-23 23:56:23,205 - Epoch[3] Complete. Time taken: 00:01:00.023\n"
+      "2022-11-26 00:29:54,370 - Epoch[3] Complete. Time taken: 00:01:10.227\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "72709e36766c46bd9d67f3a16dfd7448",
+       "model_id": "fcb4b4ecac6646f9a3463f8483591770",
        "version_major": 2,
        "version_minor": 0
       },
@@ -584,13 +574,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-23 23:57:26,955 - Epoch[4] Complete. Time taken: 00:01:03.749\n"
+      "2022-11-26 00:31:04,980 - Epoch[4] Complete. Time taken: 00:01:10.609\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "6e3dc837642847ed94ad5d602b0c67b2",
+       "model_id": "42d68ee36a8d4872aa77e12ef871029d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -605,19 +595,19 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-23 23:58:33,124 - Engine run resuming from iteration 0, epoch 4 until 5 epochs\n",
-      "2022-11-23 23:58:35,442 - Got new best metric of val_mean_abs_error: 0.05780790001153946\n",
-      "2022-11-23 23:58:35,443 - Epoch[5] Metrics -- val_mean_abs_error: 0.0578 \n",
-      "2022-11-23 23:58:35,443 - Key metric: val_mean_abs_error best value: 0.05780790001153946 at epoch: 5\n",
-      "2022-11-23 23:58:35,443 - Epoch[5] Complete. Time taken: 00:00:02.191\n",
-      "2022-11-23 23:58:35,444 - Engine run complete. Time taken: 00:00:02.319\n",
-      "2022-11-23 23:58:35,488 - Epoch[5] Complete. Time taken: 00:01:08.533\n"
+      "2022-11-26 00:32:16,051 - Engine run resuming from iteration 0, epoch 4 until 5 epochs\n",
+      "2022-11-26 00:32:19,550 - Got new best metric of val_mean_abs_error: 0.0573042631149292\n",
+      "2022-11-26 00:32:19,551 - Epoch[5] Metrics -- val_mean_abs_error: 0.0573 \n",
+      "2022-11-26 00:32:19,551 - Key metric: val_mean_abs_error best value: 0.0573042631149292 at epoch: 5\n",
+      "2022-11-26 00:32:19,552 - Epoch[5] Complete. Time taken: 00:00:03.388\n",
+      "2022-11-26 00:32:19,552 - Engine run complete. Time taken: 00:00:03.500\n",
+      "2022-11-26 00:32:19,553 - Epoch[5] Complete. Time taken: 00:01:14.573\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "77085d52b319448f9def918931730561",
+       "model_id": "b58d9bf3fd1e4177a91442e1fa76987e",
        "version_major": 2,
        "version_minor": 0
       },
@@ -632,13 +622,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-23 23:59:41,974 - Epoch[6] Complete. Time taken: 00:01:06.486\n"
+      "2022-11-26 00:33:30,367 - Epoch[6] Complete. Time taken: 00:01:10.813\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "943682a208bd4579bfe50f7d678dc66a",
+       "model_id": "2aaac4758fa74c5eb9745672cd3c26c5",
        "version_major": 2,
        "version_minor": 0
       },
@@ -653,13 +643,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-24 00:00:49,149 - Epoch[7] Complete. Time taken: 00:01:07.174\n"
+      "2022-11-26 00:34:41,475 - Epoch[7] Complete. Time taken: 00:01:11.107\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b3badfcf429a419d8149e8d1e903d22f",
+       "model_id": "f5091bee9e854c6ca8a4e848d5ff8767",
        "version_major": 2,
        "version_minor": 0
       },
@@ -674,13 +664,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-24 00:01:56,545 - Epoch[8] Complete. Time taken: 00:01:07.395\n"
+      "2022-11-26 00:35:52,513 - Epoch[8] Complete. Time taken: 00:01:11.038\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "97c0cb2814a94ed489383a0af3fcf51f",
+       "model_id": "2eeaf023cd324bea980453c225de19e0",
        "version_major": 2,
        "version_minor": 0
       },
@@ -695,13 +685,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-24 00:03:04,458 - Epoch[9] Complete. Time taken: 00:01:07.912\n"
+      "2022-11-26 00:37:03,482 - Epoch[9] Complete. Time taken: 00:01:10.969\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f3c3af0145bd4c239a6c456c42c8df4a",
+       "model_id": "8822fe034b83469b98ad60890d2b8b12",
        "version_major": 2,
        "version_minor": 0
       },
@@ -716,18 +706,18 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-24 00:04:12,058 - Engine run resuming from iteration 0, epoch 9 until 10 epochs\n",
-      "2022-11-24 00:04:14,424 - Epoch[10] Metrics -- val_mean_abs_error: 0.0528 \n",
-      "2022-11-24 00:04:14,425 - Key metric: val_mean_abs_error best value: 0.05780790001153946 at epoch: 5\n",
-      "2022-11-24 00:04:14,426 - Epoch[10] Complete. Time taken: 00:00:02.239\n",
-      "2022-11-24 00:04:14,426 - Engine run complete. Time taken: 00:00:02.367\n",
-      "2022-11-24 00:04:14,470 - Epoch[10] Complete. Time taken: 00:01:10.011\n"
+      "2022-11-26 00:38:14,229 - Engine run resuming from iteration 0, epoch 9 until 10 epochs\n",
+      "2022-11-26 00:38:17,527 - Epoch[10] Metrics -- val_mean_abs_error: 0.0528 \n",
+      "2022-11-26 00:38:17,527 - Key metric: val_mean_abs_error best value: 0.0573042631149292 at epoch: 5\n",
+      "2022-11-26 00:38:17,528 - Epoch[10] Complete. Time taken: 00:00:03.298\n",
+      "2022-11-26 00:38:17,528 - Engine run complete. Time taken: 00:00:03.299\n",
+      "2022-11-26 00:38:17,529 - Epoch[10] Complete. Time taken: 00:01:14.046\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "89a0ccc4ccdc47c4ad2b132a1caf4b03",
+       "model_id": "01192e9b35c549658abb74d1372deb77",
        "version_major": 2,
        "version_minor": 0
       },
@@ -742,13 +732,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-24 00:05:22,720 - Epoch[11] Complete. Time taken: 00:01:08.249\n"
+      "2022-11-26 00:39:28,385 - Epoch[11] Complete. Time taken: 00:01:10.855\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "dda8b077fe634383bd4c2de84a617d79",
+       "model_id": "5866d03af54945008bda50f90d664b18",
        "version_major": 2,
        "version_minor": 0
       },
@@ -763,13 +753,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-24 00:06:30,514 - Epoch[12] Complete. Time taken: 00:01:07.794\n"
+      "2022-11-26 00:40:39,532 - Epoch[12] Complete. Time taken: 00:01:11.147\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "63c87eb8c69b4ba58c63de772cb65656",
+       "model_id": "5543fe654b9346bf9a7161507a7ac62d",
        "version_major": 2,
        "version_minor": 0
       },
@@ -784,13 +774,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-24 00:07:38,712 - Epoch[13] Complete. Time taken: 00:01:08.197\n"
+      "2022-11-26 00:41:50,419 - Epoch[13] Complete. Time taken: 00:01:10.887\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "db5e4a5d88e9448184c8d2fb5c1aa272",
+       "model_id": "5f4e14dc963846c7af33e3fd1cdd3ac2",
        "version_major": 2,
        "version_minor": 0
       },
@@ -805,13 +795,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-24 00:08:47,334 - Epoch[14] Complete. Time taken: 00:01:08.621\n"
+      "2022-11-26 00:43:01,559 - Epoch[14] Complete. Time taken: 00:01:11.139\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "9c32b98a346848de88a8794200277011",
+       "model_id": "01bc8966f7db4e52a49922fc0f06de48",
        "version_major": 2,
        "version_minor": 0
       },
@@ -826,18 +816,18 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-24 00:09:55,864 - Engine run resuming from iteration 0, epoch 14 until 15 epochs\n",
-      "2022-11-24 00:09:58,163 - Epoch[15] Metrics -- val_mean_abs_error: 0.0474 \n",
-      "2022-11-24 00:09:58,163 - Key metric: val_mean_abs_error best value: 0.05780790001153946 at epoch: 5\n",
-      "2022-11-24 00:09:58,164 - Epoch[15] Complete. Time taken: 00:00:02.170\n",
-      "2022-11-24 00:09:58,164 - Engine run complete. Time taken: 00:00:02.299\n",
-      "2022-11-24 00:09:58,208 - Epoch[15] Complete. Time taken: 00:01:10.873\n"
+      "2022-11-26 00:44:12,669 - Engine run resuming from iteration 0, epoch 14 until 15 epochs\n",
+      "2022-11-26 00:44:15,938 - Epoch[15] Metrics -- val_mean_abs_error: 0.0470 \n",
+      "2022-11-26 00:44:15,938 - Key metric: val_mean_abs_error best value: 0.0573042631149292 at epoch: 5\n",
+      "2022-11-26 00:44:15,939 - Epoch[15] Complete. Time taken: 00:00:03.269\n",
+      "2022-11-26 00:44:15,939 - Engine run complete. Time taken: 00:00:03.270\n",
+      "2022-11-26 00:44:15,940 - Epoch[15] Complete. Time taken: 00:01:14.381\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3eeb253253af4c6f9abd633e9583ff26",
+       "model_id": "c8e68e3d04044f09a57898378c9eb68f",
        "version_major": 2,
        "version_minor": 0
       },
@@ -852,13 +842,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-24 00:11:07,747 - Epoch[16] Complete. Time taken: 00:01:09.538\n"
+      "2022-11-26 00:45:26,876 - Epoch[16] Complete. Time taken: 00:01:10.936\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "eaecb6706b684898873de8357befd01f",
+       "model_id": "c40a53dc18a0476ea0883d8b1b704886",
        "version_major": 2,
        "version_minor": 0
       },
@@ -873,13 +863,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-24 00:12:16,801 - Epoch[17] Complete. Time taken: 00:01:09.054\n"
+      "2022-11-26 00:46:37,964 - Epoch[17] Complete. Time taken: 00:01:11.087\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "f0ecbb4cb39941d7af2cb1f9969828ca",
+       "model_id": "9e99b0dcd5e7448ca8f11491b74d7e9e",
        "version_major": 2,
        "version_minor": 0
       },
@@ -894,13 +884,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-24 00:13:25,639 - Epoch[18] Complete. Time taken: 00:01:08.837\n"
+      "2022-11-26 00:47:49,189 - Epoch[18] Complete. Time taken: 00:01:11.224\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "b77e543bcb534bbb95b6ad0fb34277d8",
+       "model_id": "0c3812d0fa18463eb0241c4ec8a4537c",
        "version_major": 2,
        "version_minor": 0
       },
@@ -915,13 +905,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-24 00:14:34,932 - Epoch[19] Complete. Time taken: 00:01:09.293\n"
+      "2022-11-26 00:49:00,416 - Epoch[19] Complete. Time taken: 00:01:11.227\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "6ade132a68b042bbb9585d30b57642a1",
+       "model_id": "fa2bcd9a85014e118c97a47f2c3bc3b2",
        "version_major": 2,
        "version_minor": 0
       },
@@ -936,57 +926,1267 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-24 00:15:44,839 - Engine run resuming from iteration 0, epoch 19 until 20 epochs\n",
-      "2022-11-24 00:15:47,132 - Epoch[20] Metrics -- val_mean_abs_error: 0.0461 \n",
-      "2022-11-24 00:15:47,133 - Key metric: val_mean_abs_error best value: 0.05780790001153946 at epoch: 5\n",
-      "2022-11-24 00:15:47,133 - Epoch[20] Complete. Time taken: 00:00:02.166\n",
-      "2022-11-24 00:15:47,133 - Engine run complete. Time taken: 00:00:02.294\n",
-      "2022-11-24 00:15:47,178 - Epoch[20] Complete. Time taken: 00:01:12.245\n",
-      "2022-11-24 00:15:47,179 - Engine run complete. Time taken: 00:22:18.146\n"
+      "2022-11-26 00:50:11,760 - Engine run resuming from iteration 0, epoch 19 until 20 epochs\n",
+      "2022-11-26 00:50:15,123 - Epoch[20] Metrics -- val_mean_abs_error: 0.0468 \n",
+      "2022-11-26 00:50:15,123 - Key metric: val_mean_abs_error best value: 0.0573042631149292 at epoch: 5\n",
+      "2022-11-26 00:50:15,123 - Epoch[20] Complete. Time taken: 00:00:03.362\n",
+      "2022-11-26 00:50:15,124 - Engine run complete. Time taken: 00:00:03.363\n",
+      "2022-11-26 00:50:15,125 - Epoch[20] Complete. Time taken: 00:01:14.708\n"
      ]
-    }
-   ],
-   "source": [
-    "n_epochs = 20\n",
-    "val_interval = 5\n",
-    "\n",
-    "val_handlers = [StatsHandler(name=\"train_log\", output_transform=lambda x: None)]\n",
-    "\n",
-    "evaluator = SupervisedEvaluator(\n",
-    "    device=device,\n",
-    "    val_data_loader=val_loader,\n",
-    "    network=model,\n",
-    "    inferer=inferer,\n",
-    "    prepare_batch=DiffusionPrepareBatch(),\n",
-    "    key_val_metric={\"val_mean_abs_error\": MeanAbsoluteError(output_transform=from_engine([\"pred\", \"label\"]))},\n",
-    "    val_handlers=val_handlers,\n",
-    ")\n",
-    "\n",
-    "\n",
-    "train_handlers = [\n",
-    "    ValidationHandler(validator=evaluator, interval=val_interval, epoch_level=True),\n",
-    "    #StatsHandler(name=\"train_log\", tag_name=\"train_loss\", output_transform=from_engine([\"loss\"], first=True)),\n",
-    "]\n",
-    "\n",
-    "trainer = SupervisedTrainer(\n",
-    "    device=device,\n",
-    "    max_epochs=n_epochs,\n",
-    "    train_data_loader=train_loader,\n",
-    "    network=model,\n",
-    "    optimizer=optimizer,\n",
-    "    loss_function=torch.nn.MSELoss(),\n",
-    "    inferer=inferer,\n",
-    "    prepare_batch=DiffusionPrepareBatch(),\n",
-    "    key_train_metric={\"train_acc\": MeanSquaredError(output_transform=from_engine([\"pred\", \"label\"]))},\n",
-    "    train_handlers=train_handlers,\n",
-    ")\n",
-    "ProgressBar(\n",
-    "            persist=True,\n",
-    "            bar_format=\"[{n_fmt}/{total_fmt}] {percentage:3.0f}%|{postfix} [{elapsed}<{remaining}]\",\n",
-    "        ).attach(\n",
-    "            trainer,\n",
-    "            output_transform=from_engine([\"loss\"]),\n",
-    "        )\n",
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2ed23d7c604c4f45a803b488d03a5da0",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 00:51:26,335 - Epoch[21] Complete. Time taken: 00:01:11.210\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "fa31e5aae36c41778a1007f4ebdb68a9",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 00:52:37,801 - Epoch[22] Complete. Time taken: 00:01:11.465\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3f2a5eab0b924a82a3d9a36230632d24",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 00:53:49,044 - Epoch[23] Complete. Time taken: 00:01:11.243\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "002c5cfd999b4002a230c1305021921f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 00:55:00,790 - Epoch[24] Complete. Time taken: 00:01:11.745\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d86a0f4d339e44acbf7764dde03a03ff",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 00:56:12,200 - Engine run resuming from iteration 0, epoch 24 until 25 epochs\n",
+      "2022-11-26 00:56:15,475 - Epoch[25] Metrics -- val_mean_abs_error: 0.0490 \n",
+      "2022-11-26 00:56:15,475 - Key metric: val_mean_abs_error best value: 0.0573042631149292 at epoch: 5\n",
+      "2022-11-26 00:56:15,475 - Epoch[25] Complete. Time taken: 00:00:03.274\n",
+      "2022-11-26 00:56:15,476 - Engine run complete. Time taken: 00:00:03.275\n",
+      "2022-11-26 00:56:15,477 - Epoch[25] Complete. Time taken: 00:01:14.686\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "34868b5e86c04be8ade85560ed48d6a8",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 00:57:26,521 - Epoch[26] Complete. Time taken: 00:01:11.044\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6afae505bb174baaa18aa8acae482e4b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 00:58:37,524 - Epoch[27] Complete. Time taken: 00:01:11.002\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a6aab7d6b93c483ba3e0e18d6ee7ff3b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 00:59:48,512 - Epoch[28] Complete. Time taken: 00:01:10.988\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "696e371d7fc44608a506ec7f5b309f3e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:00:59,538 - Epoch[29] Complete. Time taken: 00:01:11.025\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f7558ba71863413da30c0104c3ed35d2",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:02:10,587 - Engine run resuming from iteration 0, epoch 29 until 30 epochs\n",
+      "2022-11-26 01:02:13,952 - Epoch[30] Metrics -- val_mean_abs_error: 0.0476 \n",
+      "2022-11-26 01:02:13,953 - Key metric: val_mean_abs_error best value: 0.0573042631149292 at epoch: 5\n",
+      "2022-11-26 01:02:13,953 - Epoch[30] Complete. Time taken: 00:00:03.365\n",
+      "2022-11-26 01:02:13,953 - Engine run complete. Time taken: 00:00:03.366\n",
+      "2022-11-26 01:02:13,955 - Epoch[30] Complete. Time taken: 00:01:14.417\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "909c69ff0478434da3d280631040ad27",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:03:25,258 - Epoch[31] Complete. Time taken: 00:01:11.303\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "308657a05ab04fe98911c8df639b5c0e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:04:36,718 - Epoch[32] Complete. Time taken: 00:01:11.459\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7ec0b111d5b648b98031637963872685",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:05:47,919 - Epoch[33] Complete. Time taken: 00:01:11.201\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "4d361d7b7c9d4781b342bdb1237b742c",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:06:59,125 - Epoch[34] Complete. Time taken: 00:01:11.205\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0fb1af0fa61d46be972940f224664310",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:08:09,914 - Engine run resuming from iteration 0, epoch 34 until 35 epochs\n",
+      "2022-11-26 01:08:13,284 - Epoch[35] Metrics -- val_mean_abs_error: 0.0436 \n",
+      "2022-11-26 01:08:13,285 - Key metric: val_mean_abs_error best value: 0.0573042631149292 at epoch: 5\n",
+      "2022-11-26 01:08:13,285 - Epoch[35] Complete. Time taken: 00:00:03.370\n",
+      "2022-11-26 01:08:13,285 - Engine run complete. Time taken: 00:00:03.371\n",
+      "2022-11-26 01:08:13,287 - Epoch[35] Complete. Time taken: 00:01:14.161\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "b3caa94897584b7a9b7751516f9a6856",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:09:24,518 - Epoch[36] Complete. Time taken: 00:01:11.231\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "68c95a6f69af43e88b6b15741c0b2221",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:10:35,634 - Epoch[37] Complete. Time taken: 00:01:11.115\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6cfa40c05bdc43038604f1de967e562d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:11:47,111 - Epoch[38] Complete. Time taken: 00:01:11.476\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "df5d39658d0a411a8ef6b88e851d3b58",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:12:58,463 - Epoch[39] Complete. Time taken: 00:01:11.351\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "82ff2f8bf70e479596b55e20e522e801",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:14:09,898 - Engine run resuming from iteration 0, epoch 39 until 40 epochs\n",
+      "2022-11-26 01:14:13,281 - Epoch[40] Metrics -- val_mean_abs_error: 0.0445 \n",
+      "2022-11-26 01:14:13,281 - Key metric: val_mean_abs_error best value: 0.0573042631149292 at epoch: 5\n",
+      "2022-11-26 01:14:13,282 - Epoch[40] Complete. Time taken: 00:00:03.382\n",
+      "2022-11-26 01:14:13,282 - Engine run complete. Time taken: 00:00:03.384\n",
+      "2022-11-26 01:14:13,283 - Epoch[40] Complete. Time taken: 00:01:14.820\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "c1ab2ed23d8e4130a6a463e0618d2554",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:15:24,442 - Epoch[41] Complete. Time taken: 00:01:11.158\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "ae7d8578d19f487c86e4e333e262bba1",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:16:35,218 - Epoch[42] Complete. Time taken: 00:01:10.776\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "ce90aa8c55d749199edacd928f06c8c9",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:17:46,576 - Epoch[43] Complete. Time taken: 00:01:11.357\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "5fa3f59052e94d7b953db03990a9308d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:18:57,745 - Epoch[44] Complete. Time taken: 00:01:11.168\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1e9325a745394d1d889822eda5001d06",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:20:09,205 - Engine run resuming from iteration 0, epoch 44 until 45 epochs\n",
+      "2022-11-26 01:20:12,526 - Epoch[45] Metrics -- val_mean_abs_error: 0.0430 \n",
+      "2022-11-26 01:20:12,527 - Key metric: val_mean_abs_error best value: 0.0573042631149292 at epoch: 5\n",
+      "2022-11-26 01:20:12,527 - Epoch[45] Complete. Time taken: 00:00:03.321\n",
+      "2022-11-26 01:20:12,528 - Engine run complete. Time taken: 00:00:03.322\n",
+      "2022-11-26 01:20:12,529 - Epoch[45] Complete. Time taken: 00:01:14.783\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f5edf1eb3ee941de8e47bc16807b9a79",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:21:23,615 - Epoch[46] Complete. Time taken: 00:01:11.086\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6e21803c98694da2b44adb5c31e58472",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:22:34,740 - Epoch[47] Complete. Time taken: 00:01:11.124\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "42f48de3ab5d4da8ade21ded9c7d64cb",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:23:45,542 - Epoch[48] Complete. Time taken: 00:01:10.801\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "77ae5a5fa2d3458492e9c79ff55abbc5",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:24:56,862 - Epoch[49] Complete. Time taken: 00:01:11.320\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "fb906210c4f04d42af314f54e59785b3",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:26:08,171 - Engine run resuming from iteration 0, epoch 49 until 50 epochs\n",
+      "2022-11-26 01:26:11,453 - Epoch[50] Metrics -- val_mean_abs_error: 0.0414 \n",
+      "2022-11-26 01:26:11,454 - Key metric: val_mean_abs_error best value: 0.0573042631149292 at epoch: 5\n",
+      "2022-11-26 01:26:11,454 - Epoch[50] Complete. Time taken: 00:00:03.282\n",
+      "2022-11-26 01:26:11,454 - Engine run complete. Time taken: 00:00:03.283\n",
+      "2022-11-26 01:26:11,455 - Epoch[50] Complete. Time taken: 00:01:14.593\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "977c9d1772be48b485d0aeef486248cb",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:27:22,426 - Epoch[51] Complete. Time taken: 00:01:10.970\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8c2369a861804b2d8263eb2cbd3d67fc",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:28:33,860 - Epoch[52] Complete. Time taken: 00:01:11.434\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3db3c83393e64cbd8d0d06551919fb48",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:29:45,043 - Epoch[53] Complete. Time taken: 00:01:11.183\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f27d595670c54bd8b316b877b23dc978",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:30:56,524 - Epoch[54] Complete. Time taken: 00:01:11.480\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "28154cb2b4b443bcb40689e55c6ad1c5",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:32:07,343 - Engine run resuming from iteration 0, epoch 54 until 55 epochs\n",
+      "2022-11-26 01:32:10,662 - Epoch[55] Metrics -- val_mean_abs_error: 0.0443 \n",
+      "2022-11-26 01:32:10,662 - Key metric: val_mean_abs_error best value: 0.0573042631149292 at epoch: 5\n",
+      "2022-11-26 01:32:10,662 - Epoch[55] Complete. Time taken: 00:00:03.318\n",
+      "2022-11-26 01:32:10,663 - Engine run complete. Time taken: 00:00:03.319\n",
+      "2022-11-26 01:32:10,664 - Epoch[55] Complete. Time taken: 00:01:14.139\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "327df14f09f74dc7bf810ba96c59fd78",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:33:21,591 - Epoch[56] Complete. Time taken: 00:01:10.927\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9206b11c3b2443bfa1b08f1b11eb5b8f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:34:33,068 - Epoch[57] Complete. Time taken: 00:01:11.477\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "12d89956aed447e3b51ab863f9793aac",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:35:45,167 - Epoch[58] Complete. Time taken: 00:01:12.098\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "df756d00ceea4c449345888b42fc5364",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:36:58,554 - Epoch[59] Complete. Time taken: 00:01:13.387\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "930639b45dab468d89dda52dfdd24a9b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:38:09,436 - Engine run resuming from iteration 0, epoch 59 until 60 epochs\n",
+      "2022-11-26 01:38:12,735 - Epoch[60] Metrics -- val_mean_abs_error: 0.0421 \n",
+      "2022-11-26 01:38:12,736 - Key metric: val_mean_abs_error best value: 0.0573042631149292 at epoch: 5\n",
+      "2022-11-26 01:38:12,736 - Epoch[60] Complete. Time taken: 00:00:03.299\n",
+      "2022-11-26 01:38:12,736 - Engine run complete. Time taken: 00:00:03.300\n",
+      "2022-11-26 01:38:12,738 - Epoch[60] Complete. Time taken: 00:01:14.183\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "4d133db4a7cf4c54afa75a234d8f3e14",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:39:23,324 - Epoch[61] Complete. Time taken: 00:01:10.586\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9f45092358dd464a888e683c41373fcd",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:40:34,426 - Epoch[62] Complete. Time taken: 00:01:11.102\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7023c1eef2b3495ea75181333876f8b1",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:41:45,340 - Epoch[63] Complete. Time taken: 00:01:10.913\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "62e5f00157d54e9a9361bc73e29dafa1",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:42:56,288 - Epoch[64] Complete. Time taken: 00:01:10.948\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "dda8ac7db76c486e8adb5314526732b4",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:44:07,447 - Engine run resuming from iteration 0, epoch 64 until 65 epochs\n",
+      "2022-11-26 01:44:10,838 - Epoch[65] Metrics -- val_mean_abs_error: 0.0397 \n",
+      "2022-11-26 01:44:10,838 - Key metric: val_mean_abs_error best value: 0.0573042631149292 at epoch: 5\n",
+      "2022-11-26 01:44:10,838 - Epoch[65] Complete. Time taken: 00:00:03.390\n",
+      "2022-11-26 01:44:10,839 - Engine run complete. Time taken: 00:00:03.392\n",
+      "2022-11-26 01:44:10,840 - Epoch[65] Complete. Time taken: 00:01:14.551\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "fcc6769dc4434f5488b01101af552164",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:45:22,015 - Epoch[66] Complete. Time taken: 00:01:11.174\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "577609d899d94589ab0ad71913f3318e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:46:33,106 - Epoch[67] Complete. Time taken: 00:01:11.091\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "313e54710c5c40fca9c64544aa181fb7",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:47:44,752 - Epoch[68] Complete. Time taken: 00:01:11.645\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "aa89eebca97148839dfdaa638d9a1d38",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:48:55,902 - Epoch[69] Complete. Time taken: 00:01:11.150\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "bd5d8822d7274262b6507d4e9de08911",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:50:06,985 - Engine run resuming from iteration 0, epoch 69 until 70 epochs\n",
+      "2022-11-26 01:50:10,242 - Epoch[70] Metrics -- val_mean_abs_error: 0.0420 \n",
+      "2022-11-26 01:50:10,242 - Key metric: val_mean_abs_error best value: 0.0573042631149292 at epoch: 5\n",
+      "2022-11-26 01:50:10,243 - Epoch[70] Complete. Time taken: 00:00:03.256\n",
+      "2022-11-26 01:50:10,243 - Engine run complete. Time taken: 00:00:03.258\n",
+      "2022-11-26 01:50:10,244 - Epoch[70] Complete. Time taken: 00:01:14.342\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "632dcadb1d77441dab4cb525c39d1d65",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:51:21,570 - Epoch[71] Complete. Time taken: 00:01:11.325\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "85ce1f5a88c5423294262b29987de20b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:52:32,568 - Epoch[72] Complete. Time taken: 00:01:10.997\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1c378d67e8f04301961a62158858b7a4",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:53:43,276 - Epoch[73] Complete. Time taken: 00:01:10.707\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "451e291d031d49d3b3b0100434ed0c59",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:54:54,425 - Epoch[74] Complete. Time taken: 00:01:11.148\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "12d11dfbe7844ba898a3949173f724f7",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "[1/1000]   0%| [00:00<?]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2022-11-26 01:56:05,890 - Engine run resuming from iteration 0, epoch 74 until 75 epochs\n",
+      "2022-11-26 01:56:09,271 - Epoch[75] Metrics -- val_mean_abs_error: 0.0420 \n",
+      "2022-11-26 01:56:09,271 - Key metric: val_mean_abs_error best value: 0.0573042631149292 at epoch: 5\n",
+      "2022-11-26 01:56:09,272 - Epoch[75] Complete. Time taken: 00:00:03.380\n",
+      "2022-11-26 01:56:09,272 - Engine run complete. Time taken: 00:00:03.382\n",
+      "2022-11-26 01:56:09,273 - Epoch[75] Complete. Time taken: 00:01:14.848\n",
+      "2022-11-26 01:56:09,274 - Engine run complete. Time taken: 01:29:45.333\n"
+     ]
+    }
+   ],
+   "source": [
+    "n_epochs = 75\n",
+    "val_interval = 5\n",
+    "\n",
+    "val_handlers = [StatsHandler(name=\"train_log\", output_transform=lambda x: None)]\n",
+    "\n",
+    "evaluator = SupervisedEvaluator(\n",
+    "    device=device,\n",
+    "    val_data_loader=val_loader,\n",
+    "    network=model,\n",
+    "    inferer=inferer,\n",
+    "    prepare_batch=DiffusionPrepareBatch(),\n",
+    "    key_val_metric={\"val_mean_abs_error\": MeanAbsoluteError(output_transform=from_engine([\"pred\", \"label\"]))},\n",
+    "    val_handlers=val_handlers,\n",
+    ")\n",
+    "\n",
+    "\n",
+    "train_handlers = [\n",
+    "    ValidationHandler(validator=evaluator, interval=val_interval, epoch_level=True),\n",
+    "    # StatsHandler(name=\"train_log\", tag_name=\"train_loss\", output_transform=from_engine([\"loss\"], first=True)),\n",
+    "]\n",
+    "\n",
+    "trainer = SupervisedTrainer(\n",
+    "    device=device,\n",
+    "    max_epochs=n_epochs,\n",
+    "    train_data_loader=train_loader,\n",
+    "    network=model,\n",
+    "    optimizer=optimizer,\n",
+    "    loss_function=torch.nn.MSELoss(),\n",
+    "    inferer=inferer,\n",
+    "    prepare_batch=DiffusionPrepareBatch(),\n",
+    "    key_train_metric={\"train_acc\": MeanSquaredError(output_transform=from_engine([\"pred\", \"label\"]))},\n",
+    "    train_handlers=train_handlers,\n",
+    ")\n",
+    "ProgressBar(\n",
+    "    persist=True,\n",
+    "    bar_format=\"[{n_fmt}/{total_fmt}] {percentage:3.0f}%|{postfix} [{elapsed}<{remaining}]\",\n",
+    ").attach(\n",
+    "    trainer,\n",
+    "    output_transform=from_engine([\"loss\"]),\n",
+    ")\n",
     "\n",
     "\n",
     "trainer.run()"
@@ -1005,7 +2205,6 @@
    "execution_count": 12,
    "id": "1427e5d4",
    "metadata": {
-    "collapsed": false,
     "jupyter": {
      "outputs_hidden": false
     }
@@ -1015,12 +2214,12 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|█████████████████████████████████████████████████████████████████████| 1000/1000 [00:06<00:00, 157.42it/s]\n"
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.58it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -1076,7 +2275,7 @@
    "formats": "ipynb,py:percent"
   },
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -1090,7 +2289,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.13"
+   "version": "3.8.12"
   }
  },
  "nbformat": 4,
diff --git a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial_ignite.py b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial_ignite.py
index b0a56ba6..ecc54ce5 100644
--- a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial_ignite.py
+++ b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial_ignite.py
@@ -8,7 +8,7 @@
 #       format_version: '1.3'
 #       jupytext_version: 1.14.1
 #   kernelspec:
-#     display_name: Python 3 (ipykernel)
+#     display_name: Python 3
 #     language: python
 #     name: python3
 # ---
@@ -127,7 +127,7 @@
     ]
 )
 train_ds = CacheDataset(data=train_datalist, transform=train_transforms)
-train_loader = DataLoader(train_ds, batch_size=8, shuffle=True, num_workers=4)
+train_loader = DataLoader(train_ds, batch_size=8, shuffle=True, num_workers=4, persistent_workers=True)
 
 # %% jupyter={"outputs_hidden": false}
 val_data = MedNISTDataset(root_dir=root_dir, section="validation", download=True, progress=False, seed=0)
@@ -140,7 +140,7 @@
     ]
 )
 val_ds = CacheDataset(data=val_datalist, transform=val_transforms)
-val_loader = DataLoader(val_ds, batch_size=8, shuffle=False, num_workers=4)
+val_loader = DataLoader(val_ds, batch_size=8, shuffle=False, num_workers=4, persistent_workers=True)
 
 # %% [markdown]
 # ### Visualisation of the training images
@@ -170,11 +170,10 @@
     spatial_dims=2,
     in_channels=1,
     out_channels=1,
-    model_channels=64,
-    attention_resolutions=[2, 4],
+    num_channels=(64, 128, 128),
+    attention_levels=(False, True, True),
     num_res_blocks=1,
-    channel_mult=[1, 2, 2],
-    num_heads=1,
+    num_head_channels=128,
 )
 model.to(device)
 
@@ -232,10 +231,10 @@ def __call__(
 
 # %% [markdown]
 # ### Model training
-# Here, we are training our model for 50 epochs (training time: ~20 minutes).
+# Here, we are training our model for 75 epochs (training time: ~50 minutes).
 
 # %% jupyter={"outputs_hidden": false}
-n_epochs = 20
+n_epochs = 75
 val_interval = 5
 
 val_handlers = [StatsHandler(name="train_log", output_transform=lambda x: None)]

From da9c2c01743685e1003fcd953b834ff592fbfbab Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Sun, 27 Nov 2022 14:18:32 +0000
Subject: [PATCH 23/28] Improve tests for DiffusionModelUNet (#53)

---
 tests/test_diffusion_model_unet.py | 60 +++++++++++++++++++++++++-----
 1 file changed, 50 insertions(+), 10 deletions(-)

diff --git a/tests/test_diffusion_model_unet.py b/tests/test_diffusion_model_unet.py
index f2e30c0c..08317175 100644
--- a/tests/test_diffusion_model_unet.py
+++ b/tests/test_diffusion_model_unet.py
@@ -19,6 +19,17 @@
 from generative.networks.nets import DiffusionModelUNet
 
 UNCOND_CASES_2D = [
+    [
+        {
+            "spatial_dims": 2,
+            "in_channels": 1,
+            "out_channels": 1,
+            "num_res_blocks": 1,
+            "num_channels": (8, 8, 8),
+            "attention_levels": (False, False, False),
+            "norm_num_groups": 8,
+        },
+    ],
     [
         {
             "spatial_dims": 2,
@@ -27,6 +38,7 @@
             "num_res_blocks": 1,
             "num_channels": (8, 8, 8),
             "attention_levels": (False, False, True),
+            "num_head_channels": 8,
             "norm_num_groups": 8,
         },
     ],
@@ -38,13 +50,24 @@
             "num_res_blocks": 1,
             "num_channels": (8, 8, 8),
             "attention_levels": (False, False, True),
-            "num_head_channels": 1,
+            "num_head_channels": 4,
             "norm_num_groups": 8,
         },
     ],
 ]
 
 UNCOND_CASES_3D = [
+    [
+        {
+            "spatial_dims": 3,
+            "in_channels": 1,
+            "out_channels": 1,
+            "num_res_blocks": 1,
+            "num_channels": (8, 8, 8),
+            "attention_levels": (False, False, False),
+            "norm_num_groups": 8,
+        },
+    ],
     [
         {
             "spatial_dims": 3,
@@ -53,7 +76,8 @@
             "num_res_blocks": 1,
             "num_channels": (8, 8, 8),
             "attention_levels": (False, False, True),
-            "norm_num_groups": 4,
+            "num_head_channels": 8,
+            "norm_num_groups": 8,
         },
     ],
     [
@@ -64,8 +88,8 @@
             "num_res_blocks": 1,
             "num_channels": (8, 8, 8),
             "attention_levels": (False, False, True),
-            "num_head_channels": 1,
-            "norm_num_groups": 4,
+            "num_head_channels": 4,
+            "norm_num_groups": 8,
         },
     ],
 ]
@@ -88,7 +112,7 @@ def test_shape_with_different_in_channel_out_channel(self):
             out_channels=out_channels,
             num_res_blocks=1,
             num_channels=(8, 8, 8),
-            attention_levels=(False, False, True),
+            attention_levels=(False, False, False),
             norm_num_groups=8,
         )
         with eval_mode(net):
@@ -99,12 +123,12 @@ def test_model_channels_not_multiple_of_norm_num_group(self):
         with self.assertRaises(ValueError):
             DiffusionModelUNet(
                 spatial_dims=2,
-                in_channels=3,
-                out_channels=3,
+                in_channels=1,
+                out_channels=1,
                 num_res_blocks=1,
-                num_channels=(8, 8, 24),
-                attention_levels=(False, False, True),
-                norm_num_groups=16,
+                num_channels=(8, 8, 12),
+                attention_levels=(False, False, False),
+                norm_num_groups=8,
             )
 
     def test_shape_conditioned_models(self):
@@ -119,6 +143,7 @@ def test_shape_conditioned_models(self):
             transformer_num_layers=1,
             cross_attention_dim=3,
             norm_num_groups=8,
+            num_head_channels=8,
         )
         with eval_mode(net):
             result = net.forward(
@@ -128,6 +153,21 @@ def test_shape_conditioned_models(self):
             )
             self.assertEqual(result.shape, (1, 1, 16, 32))
 
+    def test_with_conditioning_cross_attention_dim_none(self):
+        with self.assertRaises(ValueError):
+            DiffusionModelUNet(
+                spatial_dims=2,
+                in_channels=1,
+                out_channels=1,
+                num_res_blocks=1,
+                num_channels=(8, 8, 8),
+                attention_levels=(False, False, True),
+                with_conditioning=True,
+                transformer_num_layers=1,
+                cross_attention_dim=None,
+                norm_num_groups=8,
+            )
+
     def test_script_unconditioned_2d_models(self):
         net = DiffusionModelUNet(
             spatial_dims=2,

From 5fd1700599036f7a61ebe64f602c8a3fce786f90 Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Sun, 27 Nov 2022 14:29:44 +0000
Subject: [PATCH 24/28] Fix typos in error message (#53)

---
 generative/networks/nets/diffusion_model_unet.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index d1a7f1bb..4505e17d 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -1460,12 +1460,12 @@ def __init__(
             )
         if cross_attention_dim is not None and with_conditioning is False:
             raise ValueError(
-                "DiffusionModelUNet expects use_spatial_transformer=True when specifying the " "cross_attention_dim."
+                "DiffusionModelUNet expects with_conditioning=True when specifying the cross_attention_dim."
             )
 
-        # The number of channels should be multiple of num_groups
+        # All number of channels should be multiple of num_groups
         if any((out_channel % norm_num_groups) != 0 for out_channel in num_channels):
-            raise ValueError("DiffusionModelUNet expects all block_out_channels being multiple of norm_num_groups")
+            raise ValueError("DiffusionModelUNet expects all num_channels being multiple of norm_num_groups")
 
         self.in_channels = in_channels
         self.block_out_channels = num_channels

From 2aeec395860c9ff14c0fbd2847f70b4b88a3098f Mon Sep 17 00:00:00 2001
From: Warvito <ianonimato@hotmail.com>
Date: Sun, 27 Nov 2022 18:44:09 +0000
Subject: [PATCH 25/28] Fix l1_loss in the validation step and use AMP (#53)

---
 .../generative/2d_ddpm/2d_ddpm_tutorial.ipynb | 278 +++++++++---------
 .../generative/2d_ddpm/2d_ddpm_tutorial.py    |  42 +--
 2 files changed, 166 insertions(+), 154 deletions(-)

diff --git a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb
index ccbb9cb9..24e02aad 100644
--- a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb
+++ b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.ipynb
@@ -107,6 +107,7 @@
     "from monai.data import CacheDataset, DataLoader\n",
     "from monai.utils import first, set_determinism\n",
     "from tqdm import tqdm\n",
+    "from torch.cuda.amp import GradScaler, autocast\n",
     "\n",
     "from generative.inferers import DiffusionInferer\n",
     "\n",
@@ -145,7 +146,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "/tmp/tmpdha9uqf4\n"
+      "/tmp/tmpzcc0l1by\n"
      ]
     }
    ],
@@ -202,9 +203,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-25 22:04:40,336 - INFO - Downloaded: /tmp/tmpdha9uqf4/MedNIST.tar.gz\n",
-      "2022-11-25 22:04:40,408 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
-      "2022-11-25 22:04:40,408 - INFO - Writing into directory: /tmp/tmpdha9uqf4.\n"
+      "2022-11-27 17:51:01,361 - INFO - Downloaded: /tmp/tmpzcc0l1by/MedNIST.tar.gz\n",
+      "2022-11-27 17:51:01,429 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
+      "2022-11-27 17:51:01,430 - INFO - Writing into directory: /tmp/tmpzcc0l1by.\n"
      ]
     }
    ],
@@ -240,7 +241,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1719.09it/s]\n"
+      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 7999/7999 [00:04<00:00, 1772.93it/s]\n"
      ]
     }
    ],
@@ -279,16 +280,16 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-11-25 22:05:04,646 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
-      "2022-11-25 22:05:04,646 - INFO - File exists: /tmp/tmpdha9uqf4/MedNIST.tar.gz, skipped downloading.\n",
-      "2022-11-25 22:05:04,647 - INFO - Non-empty folder exists in /tmp/tmpdha9uqf4/MedNIST, skipped extracting.\n"
+      "2022-11-27 17:51:24,712 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.\n",
+      "2022-11-27 17:51:24,712 - INFO - File exists: /tmp/tmpzcc0l1by/MedNIST.tar.gz, skipped downloading.\n",
+      "2022-11-27 17:51:24,713 - INFO - Non-empty folder exists in /tmp/tmpzcc0l1by/MedNIST, skipped extracting.\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1005/1005 [00:00<00:00, 1744.49it/s]\n"
+      "Loading dataset: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1005/1005 [00:00<00:00, 1757.40it/s]\n"
      ]
     }
    ],
@@ -384,10 +385,10 @@
     "    spatial_dims=2,\n",
     "    in_channels=1,\n",
     "    out_channels=1,\n",
-    "    num_channels=(64, 128, 128),\n",
+    "    num_channels=(128, 256, 256),\n",
     "    attention_levels=(False, True, True),\n",
     "    num_res_blocks=1,\n",
-    "    num_head_channels=128,\n",
+    "    num_head_channels=256,\n",
     ")\n",
     "model.to(device)\n",
     "\n",
@@ -424,17 +425,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 0: 100%|████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.863]\n",
-      "Epoch 1: 100%|████████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.569]\n",
-      "Epoch 2: 100%|████████████| 63/63 [00:39<00:00,  1.59it/s, loss=0.343]\n",
-      "Epoch 3: 100%|██████████████| 63/63 [00:38<00:00,  1.62it/s, loss=0.2]\n",
-      "Epoch 4: 100%|████████████| 63/63 [00:41<00:00,  1.53it/s, loss=0.116]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.03it/s]\n"
+      "Epoch 0: 100%|█████████████| 63/63 [00:37<00:00,  1.69it/s, loss=0.74]\n",
+      "Epoch 1: 100%|████████████| 63/63 [00:37<00:00,  1.69it/s, loss=0.289]\n",
+      "Epoch 2: 100%|███████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0926]\n",
+      "Epoch 3: 100%|███████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0348]\n",
+      "Epoch 4: 100%|███████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0204]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 71.29it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -446,17 +447,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 5: 100%|███████████| 63/63 [00:40<00:00,  1.56it/s, loss=0.0701]\n",
-      "Epoch 6: 100%|███████████| 63/63 [00:39<00:00,  1.58it/s, loss=0.0428]\n",
-      "Epoch 7: 100%|███████████| 63/63 [00:38<00:00,  1.63it/s, loss=0.0291]\n",
-      "Epoch 8: 100%|███████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0221]\n",
-      "Epoch 9: 100%|███████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0182]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.07it/s]\n"
+      "Epoch 5: 100%|███████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0178]\n",
+      "Epoch 6: 100%|███████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0153]\n",
+      "Epoch 7: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0155]\n",
+      "Epoch 8: 100%|███████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0146]\n",
+      "Epoch 9: 100%|███████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0138]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 73.70it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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oyZOTkwAEs1dVC8jNzAaDQQipqLOFisbm5fflcmnT6dQ2m01IU1MgqJetalSfg0GBjclAgvnVvuZ1H9Qj1zd1QJOTXCwyJbVtwhSw9Lcq3pK3JT0wUx4ekgKietIay+MaVDcZMajZTqdjl5eXtlwu7eTkxBqNRpi/9jZmp9Oxfr9vX758CW2z37+Gc6bTqc1mM1ssFjaZTGy9Xtt0OrX1em3fv38PAMHjxYlBTV9eXgbbFJVPYoNm8qzXa+v1erZarezq6ioEs2HE6+trm81mdnNzE35jcGr7xhxO7YdY+3vR2OlP846rShnLefsjZxvm4lCpMnP2KaKzAzDLdru1drttk8nEzCyAxuw1YQKmglE1JtloNII6xtNmqk4TJTSlS+OOOoWoNhj3hOGwJWFzwlqEpwhH7ff7EHcdjUYBzMq+MUl5x/6alHedc3BSctC6Y63Efr8vqC1fAe9AxOaDc9fqvX0jpBhW76U2ildxzELAEvP53CaTifX7fRuNRtbtdu3q6sq63a6dnp6G5AWyfE5PTwuMCgiwjUjTWq1WNhwOC3YkrKmzRhj00+k0gBUgm/0ZiP/y5UshAaLX69l6vQ4e9nQ6tel0aoPBwHq9ni0WC7u4uLDFYmFPT082n89tNBqFWRjitD5Yr32T+vg296bFT/OOy9SqnovEaF9/8+XnHjBWh1Q9c6re7DVjhg6AEVerlXU6nTCnvVqtClN/MKAGiDUxl04AbKvVytrttq1Wq+BQDIfDoF69Y4DK1Dghnn+n0wm/wa7EBQnOq+Oh6WtmFsJAtIXmVGqf0E4xL90fi/XBT/GOfSd6damd7rNJ8Cy1cgCAWYyYXZICnXYYHwUUjertQx8v8+D0OX+EYrrdbrDhmG7sdDq2XC5DqAdHQ+tL+a1Wyy4uLmy/3weHZzqdFmaL9BvQd7vd0M4AEgfk4uLCzMxOT09tu93aaDSy+Xwe7NvlchmYkLnowWBg6/XafvvtN1ssFjabzWw0GoVpVP0mSK99FcNCDidV5SCb0Ntl3s7wo5tsGUaeAhh1pDaXF3UsfD10lkDjenSqf2GjmgSU50FAGahCAAZD4ahwDp1MvM7H5AiUm/0Jmv1+X8im1mC1DgbPtHjxrL/hGHHM6XQa2nO5XAYnCtXNAABg0+nUxuNxUNWaw+iTRmi/MknZlDk5OJ8wpmI9A+BRXl5e2uXlZWGuFKAACM2W9mo7Vj6dpSAkLIL6IV6n02K+gbSBCUTrzIuZhfKxHQkqkwP49PQUGJ3lCmSNDwaDgmMDoxEigq2Wy2UIZus0IWq23++HAQTQdRDCnHjSzNIsl8tgGsBytNvp6aldXl4G73q9XgebFcan/bTdNQmD9tH2hEmryruSWtUtjyUTdLtd6/f79vXrV/vtt98KmdA+VOCzXMzeJhEgGosDYIBPwyTz+TwY3xjvXk3rswBCOljvD7MwAwMIm82mzWYzazQaNh6PA2C63a5dXFyE6UeA46cVsRkXi0XIntH1Ms1m03q9XmBZgMoHEMLItCVtsl6vrd/v23q9Ds6ROhBmFsI/fvDqR8Hn30eoJhERAEyNKlIbhDkHxFcMQOE5kkzAg+v1mmEMA/l78zcdoB3GMcDY6/VCkgSJAoBQEwUQGIaVdNyL5aZnZ2fW6/Ws1+uFOWfWmtD5eMmAd71ehzAJzoQmJmiHkvhAiEftWHWadCZFgUpbo5rJ2uY3jrOUAWD55QeaAQTB+P6I9TUMCGh51ipSO1jtqdh7rfo/Nglzsxrg1RkNMwvTbMTfAAvlaGdzX9ZomL3alt6u439d6AR7ql2qCapaHt+wm2bfaGa1Aob7wsbYhK1WKyxnPT09DaDlvldXVwVWAnBHR0fB5tVQCtOTaoMTGtLZF4LvsNzDw4ONRqPCSr+Ura7mgyaJaMqbEgAZPePx+OOZMCW5G2m8iL81jV9HiiYaAEK1F2OReBpAgYBg+6iqwJnQhAM6EwbWhe1a736/XwCNfgjL8MHm8nYTA0BDLKhYBoLZKwB8G9GmCkKfnY7WARga4Ma+HAwGwcTAXtSBq7Y2fazgo63Vxuccjuv1ZfIum9CHaZQdNRyio4okAE0zwu6hk3VREGUoy3ENniKjnWsbjUYhBUvtld1uF3Zt0NmPVKfCxoBQG59rut1uYQZFWdjbyszIvLy8BIYli6bf7we1jArUWQ5+MyvmTzYajYIZ0uv1gqlClg5tvN/vrd/vBxacz+eBwfCOmWakDTXaoOqf5+XZut1uaLOTk5Oq0Pq503a5Y2aviZvaoXy86HSWngcb6bwuv3mDWvMCPQh1DbGaHkyBMV+LqL3kFzwxQLwxTwxQbTpd16KzIz6mqff07aXtSR0YtNRRTRkIAWZjylKXv6oZoFObGk7jegaamjC5fvdSe39CjQP5b4DCedgnTIepikUdoooAiS78gYU87WtMEQOcRoCV/LoUngGvnXozggESnQlbAgy8WRqchAPNlkZURWuHoPLUHtVYoo+V6nMp83CNOjawoqpVBava0tyLaAVeMdk9ugaIstAkCizqoM8EK6divjH5MCb0zgkgxGPC/phOp4VzMOQ9IwJg9SYROkUD0jAAv+tqNOqlZoEOJpwm/tepMDXU8fhgSM2w4Tn8/ZTd6DD/7KSDqdnBPT1AvVmkc+OU5xegK2jN3r7yC4+csNN2uw2zRRpXTIVqUNsqsfSxlNSaO/ZASx2n8fBeR6NRsJ2YP4XKl8ulNRoNm81mBfVKh2mjeUZTFeHtMkSNfViXNSfMDVNPH/oxs0J5dBZ2qDojGthWVeqZXweKJjsow/loAOcoWyuz6v86cCgDkCsb+ggH5gx16vV6oS100ybaX8tR2xFWfXl5+TkgjB2LqTulZRpju91av98PrIXxra6+etCMuFx9CAuYWUH9eXsJVQb4zs7OCrsoaPhD5489a8LYyrpmRWZWoQ56nOsYEP55eAb1kKmTHxDUSZ0gQkjc3+x1rbM+Cx+NLlAvFXVMALPWTUGITal5i1Xk4FSunAPCiFS69sFQHZ06egGiglCBjngm9HE97sW5qj5JJt1sNoXEUsrjedWBUYcD21WdAAWbqj+O+VkGdRxoB40ZKnMBMjpaARB7Tq0Tx/U8jvnrY/2pQAbEPnitWkDt/g8HYcpJ8M4JlUH8QxBIVWOe8nw4Q0eghn28B6vlxEJG/KbLOTudji0WC7u6ugprTChPY4B+Hlf3iEGFsehJB4L3FL1gfzEAvI2pINQpSdoUxgL8fPs9fXKiIIv9RptjC/sBHysHc8y3f05qMaE3imMA1N8AlW7roSzhy+M6rlUbTcXbN2b5NTDe3sLInkwmwZZUx0idGg3rwF6evbXOKjE7VsGpDoc3IdS+03BI6l4cB9xah5QtGDvHl5c6T8tSMwZRrVImlUGoRqk2BhVKXcMHG4vJfm3gmJ2i3pc+TMwhUtEwjnYw0mw2w9JNttlgBoX1Jt6uhRFhKphGp680MM3AUTVIXQj14BSpB0zgmeflf5hSZzMAKdejshuNRtA2Oh1pZgXb19fLM6L2g/a7trFu9KlEoWuyq8hBO7Xyv37reSmgeGYwe+v5amyPv9U21HLLnCVVrfzWbDbDgNANKvHSeU4fxlCW8czlz1Xm5VkBLeqS6TR+jzE7z+ED0rFn946Gfnv20nLU3o0xXayvlQEZGLo2XI9VkYOm7XKdH6usAslnz+TUaBngzV7tT/Wu9X+vOhX0w+GwEPs6OzsLDHV+fl4w8FWdAybd0sODUu0mtfdOTk4KnrlqC7SERg00sExkQTdCUlBhswE8QKBqUu1vgtGNxuumAbCumk2UwWwPrKvb2yngXl5e7PHx8eNBmJMytazHPVgVhB6Q/rrY31488LyXqMylWR+azh6LBcIcGsvErlNQeRXHh3lx1LEfHGr76vPj0HlPV0Mg3o727avqVxkWZ4dz1O7UgaB1oZ4aQ+QD2GnXDwehTqT7jwIgZszyEP5YHUcndm+Ow1CAxwPBz3WS/Uw61dXVlV1fX9vp6WmYwvO2Eh0Aa5C0CjOqaMjFJz3AGuqU4A372Q8FlP+b87R+OvMRs/PUwWIAaUxWF+trah3mDPdTgGJe6DQhqwA/HIQx0FVlp5j4WFKurJiq1t+0YXQTJWU9VJpm3JycnISlmyStYq/FbD11BnBs1Kv22eJkamv7wRiqqmFGz24KNhU/96zHdbDERL17bxJwT2+CqHrWvoMYGEAAezKZhMmDKlJ7xsQ7CYga9fyuo9Sfz8N6R4WH9GzHcVWpmkSge89oyMV7n8fHx2HrjIuLC+t2u/bly5fCO1OU2bDleIbBYBAC3D54S701mdYL7bdYLAperTpE1JnrNTyktrXvB2WuWMBYywU0BOn1GRqNxpvcSdpc1bJqJ9/GVQFodkCcUBssdyNVBVxHo6RUtH48E9DZMAdrOQDPYDB4M1uijMZ1CkI2JTo5OQk78psVV/fptm6ocla6MdXlbTgNW6jXqOpTA/GoSZ4P9YzQTpqkq2Es3z6xYDL1BEj6rEz30W4McA8+b3tq4iplMDjryEHesQdRzLaDCX3jewAraJTptOO858ZakF6vF/ZtYVNLGk7VqjZmo9EIqfaXl5dh43bNFVTbkgZmEOKlmlmYvuM51Bbk+WNeO2XSiWpPUa6yuLa7mheqfmOhG21jZViNKKj6NbNCm2k/K/C9neoBylKK2K5qMam9U6v3sLwog2knxGwY36jeYFYbjsxjVDAf3vrEyEU9kwlNg2pncy7leiaDjVCX+lKbZrMZwjgwhOb98UzeA9Z2gAG105SlWDeDKaDleHDE1qOoF8/zahmewbSO3BPRwZLy3hWUZCS9vLxUXvb5oZnVnvWwK7w60HN9LE7tOgCF+iQNHuYiD1CnwLin34jS7DUVC5XFUkwa1LM3x1X9xEIhHmRcx7cOQLWdfRgnpVFSbawmTipaEatX7Fwt298/dm7sf8+YfmoxJQdvnO47TdUeTMHGQQos3clK7TZVyz7M4rfaRdVqCIQ6EH4hHufLUUbQrG7fmABOd02FwXwGkM9hJKdO243flfF5Fr+blu4p41ktBkKzV8ZS1lMHQUGisxnKhCrqMOWiIlq2d1qrOie1320Xq4S3PWAYdiEFMLryS9dlaAdqyEJjUYDbe8Ga/6Ys5+1AAO/NAt/IMYM+ZXqk2idmo/nEBx8G8hrC3zc2UPjbz4iUMWDMc4+Fo3LPnAofHSIHb4ik/6uzcXR0ZOfn59bv9+23334LG/dgrwAwGAwwquEOI2gYgms8q7I9ht5fOxeG0FkDhMAxi8FbrVaIITJ4NMALeMxed2XA3uReBH3VKFc2po48l85C+OwXdSQ0U4V78LeyLDv8K7DVjKBdsY+5lwesXk8ZPiEBIOrMEuX5NsjJwRsipUYmLMerYlnQTWP5mQ2/eBsA0dBqRCsAAaFeTwPot6pW9Tox6lmItVgsQrY3nrd2hGcWH6IwKyafensIp8Pbf4BDQydqmii4Cf3wrWVrPJSBomZTysNFYipZ25G6xkSJA9GYZpm862U6HoiatkWqNyuvvD2mD+k7VxvKMyTMo2sa/CjkfGUR/Q1hhRlZNGyp1ul0QjqUZ3pSlDAF8CjxOpXxGXR6ri6z9Oo7NdOh5gTnAzC1G2MaarvdhiWcanKQCEE7Yud684hr/CIuJQzuu1wu32zCWUXe9QoJPa4epO5JslqtgqPC+b6hvd2i4QO15VBpqFDNJtHGMXsLQg0xcB/NWGYjS9TyZrOJbvNG3VqtVsg1BASEXXRnLk1c0A4j7KNt51W/tpce1+t4fmVt3yd+SSaOHX2l7UcdtP18X1M3AMs57ETLwvmfoo49AyqgdGRiKw2Hw9AppM/DBMoIhHG4PpYMqddgy2nDp9QMbKAMy7eywHr958sMeT8Im/po/LHdfn2xt04NImrv6mboGjeEXQGheroAxXvCuqiJOvvt7qiHJhBzrSbtAizWq3CuTul51vSkobYl7bjb7cKODkQUPlwd+471akoryAi4vb21l5eX8EZ3ndlgFBEcVRAqY6l4O0pVuGYN+9ACjaEzHdp4Gt6Auc7Ozt5M8bHBJeBUE8PsdVMnZmF0v0Ofo8eKNLUFtU3VWdPOxoTQF+UoaFjXzSDhOrPixk8AFDanfbXNlIHVSaL9GDw4dtPp1EajUXi2D8+s9upBj3Fc1ZyZhbW8VB51p94xqlqZSrNJYqPJhxkUhHyrd+3rp8yiZWnsDrWMmibcBBvhAfqUMe+dxzxPOlBjpLHEg5i6joV/cnZkobMTiQUKMh881/ahH1XN0g7kEGILxhbEp+Rd6liZSO2H6XRqzWbTFotFIUYYy3rxTOjtPLMig/Ht1azfLNPHwrTTYiqb5wEcpGlpjmGv1wvvosMkUPbUBeQKSs/gsClawXu1qhH84NTtTczevpWU62lrJQzu5dWwzjhhflBv1CtlbDYbm0wmtt/vg7MFE45GI3t+fraXl5fCKzjKpPbcsT+mneg9Kb+oHIo+Pn5dd6wr8cxet3RTiTGBqtEYE8YCsqnQhLd/YAw6Rp0YtSv1HjG7Sb1Oz0qqhjVwHQuDaFm55RE8i/dctX94llhGjtpxTHFqf6hJQL0A4Wbz5/414/E47Mv44Uzot2tTiXm3jDizYh6gxrO0A3yDe+byKtjbe/7/WL18nWNGOA2vL3dkc3N1nPwsj4aOcDwojz0BdSkA94OFEC0X7cLryIhpNhqNwqsqtO58YFYGprcnNbtbU9Jms5mZWTiHZ1uv12FDTd69R/syQP/v//7P/vGPf9jT05N9+/bt40EII8QYxot2rjov+vEGb0xleZCobeLv48WXqd8xAGq5Zq9MABhV9WtZsefW5Zf+t1Q7+LrrM+gWG7xeQmdg9Hn0elXrgFC3T9aXRmoMcrfbBSZjcT4xQDZV1z7C02eB03A4DECtIpVBSCVRdynxINHjMTXi1ZQvy5cTO+7vQ/neKfD18nE1Fc+osBFJtACT3DnWJatNBSsRslHHwHvLWn9APB6Pbblc2uPjo41GozdTZ6pJNBMatY76pn580xea6MGuZDiT6kCh1bSc3W4X7D484v/+97/273//O7zT78NBCBPGvCuVmBcdAwniK1ql/BQL+f+1EX3d+D9mM8VYXPMK1dYizIEzsNsVN/70CRf6HH4AqnO22by+gWA0GtnLy0s4T2OpunhLs3E8aMjs0frj/VPv/X4f9pFUMMN2gI92GA6Htlgs7OHhwcbjsd3e3trz83PwlMs0JlIrvd93Tkp8p5YB00vKC/fqM3ZPrZe/b6w8X656yHiwLIDSaAAZQWyCTg6jz4b2dUJQe+rxwly8jnY0GtlyubTn52cbDoeF5FXv1Eyn04KDg+3H/b0zpeEWnAszC1EGgAor6ybrk8nEVquVPTw82GKxsOfnZ5tOp/bw8GDT6bQwk1NFam8DkvMIzfIpQCkWSx1PSewent1S1/jf1QZVBwoGIz7oQdhoNEJi7dnZWWHReCyBIeU9Y2sBGl7GiCOwWq1C2INjZsUNNDXmaGYFU0HX32hc1Ox1dgUQaz2VlTmPcA3gu729Da8mWywW4eWOOQzE5KCXbntbK2brxa71jBQ7p+xYbgBo/XL3iHnKfOOtslPCxcVFeH2EZmirZvAdBxh06zhNbuBcGIbOnUwm4VsdifF4HLbvZUcwPro5qJ/uA6QMIO5NXA8wqnr3bYMTM5vNwkshefXY09NTeEceDo+PbFSRWu8x8TaWdmLMy8ypXm8nltmC/n76reV5posxo/dwNbDMVNvXr1+t2+3a3/72tzDtyDQYc+P6DBrrRFXr/LJmY3unZjgc2mQysZubm8A4sORms7HhcBicAPbMUdARrvFhG0BPUBzn8vHxMZTDANFXzuoz8fLwp6cn++OPP2w+n9vDw0MYHLotMKbFTwNhLpyhkgMeYE2pzDpATNWjiq2K0Fl+Rqff74dloHwPBoNCZrd2tA+4m706crEIATYTqhg1BqMAQtQ0cUrd+xtHSAeSfrQeunKQeijYfMKsmigEn19eXoKNqi/g0XhhlT6ISe1NMpVFcjfzv3k1mgvNeInZf2psp0Ct18aYFzDxguqTkxO7vLy0wWBgv//+u/X7fbu+vrZer2fn5+fBSSFVy8xCiEKZcTAYBJCYFcMxqKvRaGSj0chubm7s+/fvNpvNgmc5m81su93aeDwObIm9uFgsrN1uh82bLi8vA+NqiIb7dTqdcA5siqrH1tMgO6YGzsfd3Z3d39/bZDKx5+fnQjRA+5r+ULavKu/es7ou6nMSU69V6pOqR8oG1flaVcEAEQYEcPzGDq/YWMpqmlyr9iKepgavUX/KgsxJ+9AKzINtRuiDBAttOz6ajKBLKgCZbmLETlt4sxynPuPx2CaTSVDL6th4+1M/Px2E3gbMnavX6G8eHDk70+cMqmgsi/JjLEnnqDGve9Fg911fX4etQTqdjp2fn1un0wnn6v7WdBweJl6yzkTgfMAe/P3t2zd7fHy0+/t7u7u7KzAhIRpVx/p2ATx2HA1AjjdMIgXnwMCPj482Ho/t4eHBXl5eCqoXhoQtCbdMJpPgKGkCr7fBvc+Q005eaucTqlNQx/hMlVW1jJh6T9UFUMYaSjN4YLmTk5PCh4X1vMUJ9tOdqtRuIrhrVrTN9BzUMGw3Ho+DnYU9OJlMQhxO53oBIUIcMPbMDDYGgg5gZjJYU4PoQJnNZqF+k8kk2H8KvlT7xj5VpNaMCRXmob2o4xET/1vKSUmVk/J8Y0yoE/m6jYiuh76+vrZ+v29nZ2dBDV9eXobAs9pYlGP2GjPVNdSkfcGA+lpb2G29/vOdw8vl0n78+GEvLy9hnpV4GzamMiH2IB58t9t940DA1r1eLyTiDgaD4OAAJjUVtGwdAKvVKiRM+GlC/Y6p5Z/KhJp6lGMv/T0GuNT/en6VyqccHwUhoQzmVUm5R7VeXFzY6elpUMe9Xs/Ozs4CYHUOWDNlsP9wBvwOEbrpJnYcYRFibI+Pj0HdzWaz8CFOCCuhJjXzW2N6fMhax8nCzgXUpPirSYMnzqyH2qOwcCzork6IEskhLGh24Gq7OmrYs5q3CXOhnpxtmRJ1NrRjFCy8c/jr16/W7/dtMBgE1Xx6ehpAF5sjjtWFe5JNTEgFpgF0y+Uy7NFCbHA0GgUg8mZ2Jv99zI3BBVOzjID3MGuCqpoDqGhNywL0OEWk5LNsQHMXY/a29iV/18VG6LM6J+uNYqrQix8RHoz6e4w9Y+Xp36qOwgP9f7WpzHZ+fm7dbjeA7/LyMoQ58Hj56BZxeI26eMiHQHS2QjOMx+NxeLsRU10AbLVa2dPTU7C7SARAHZMqpWBSew9Vq/FM3URA3wKgmkGTG4j/8fJtzdJBVau69X0fw0TOWc1JbSb0KvOjQjRejVd5ED2HRgZUp6enIdRCij7eK5tcejXq99ajM2LProOQqTTNtyMEgyMAy9HppMBPJhObTqeFV1n4gaX2Vmz5gKaIMQh9tjR2qWY+8+YCVL4Gq6uQgraTJ5c6QDx4V66Y3s/d2P8We7iULRHzgn0cDg/269evNhgM7OrqKgR0CWlcX18HBtQ1wdhRqF3uRedh/2iOIP/vdjt7fHwMsT/CHIvFwobDod3f39t8Prf7+/s36hjjXwPHas96MDBg9AVAqGOdRTk5OQksTGb2fD63Hz9+2O3trd3c3NjDw0OIU6KGfcQhF33IyU9jQpUYC8bsPn++ih/psXvkPHD+VoZg2o3AMjaT/k/oQud3AZVfv8E9fAYzdhbMgRcJCLGxsPkI+qIGYSXUt7IQ96ONqI9mousyCR9+Qg3rempepE0AWtnP237e5NG+ivXJR2jCD2PCmDrNgS9nP/jrY9/qoaFie72e/eUvf7Hz83M7OzsLdhO/EX4hiKuJpqhCnA+Oa3IARj0vjGTXVhiNLJiHhwd7fn62h4cH+/HjR9g0kpVqgCOm+nTul6lSguQMKDYAJRy03++Dfbjb7ezl5SUw4XQ6tdvbWxuPx3Z3dxcC1dimmnPo2Y+yU9EO7S++NXG3qhwUrC5jsVT8T+2F3HW5sjmuD44xrh2li881+KxxQ75hDl1DooDw64HxHgkas/aDabbxeGzD4TBkRBN3IySCnanMF7OrNAGVQaP7M2oCLQ6LbmuCnYnt6VlQ18JUZbQqGqquHBSi4aZ+9KQSOVMMmQNdjvpVBZlZsI0ItwwGAzs7Owvbj+jrZLXj6Ey1+3ReWe+hz9dsNoNzsV6v7fn52ZbLZZjo/+OPP+zHjx/BIfHbdqQWQfHRVWrYgoPBwL58+WK///57eIMAm4Zi3/Z6vWBfTqdT+/btmw2HQ/vnP/9po9HI7u/vgy3K6sFYP8T6u8wmjIVrqsrBc8d8xyjcS270xMr3v8fAqPclLuiZTzdF143U1YZiYyAfeNVMauqg9SDLBTuPWCBrLW5ubgI76rUKZN9e6tHqOUdHRyF8xGsvUNE6M6QhHZYFvLy82N3dXZgDZocE3a+G5yvrD388pxHrAPFdIZoYCMtGSUpSajrmscXUh3YGgWrid2YWpq9UvZLyzryp3g828gvhAdZwOLS7u7sw27BYLOzbt282Ho9DxjGee9UBSCICIMT2+/Lli11fX4f3rRDzZON4klZJgH18fAwDgV0RsA9h5LoOhfZPKlznz696j4NA6IFX1R4oOyf1MIi3nfw56iUDRJ3z5gU22IKa4ew3YVK7TGNy2+02zPPe3t4GEM7nc/v+/XsIwZB8Ghs0scCu2oYcwwm5uLgogJA4qIKx2WyGuekfP36EPEBAqDFBD8IqDMh5OcbU3+uAvParZn2l9Fv/9qMl5Yxo+b6s2P1j3huiNmlsAT1lwGp+ZRxxQlWJqC3d7u7p6SmoOpY8EpzWpZipeqYGrjohR0dHweNlfhuvnkA73rGaBvf39yExgulA1K+2oTpauXb3EnNMY0TxU23ClDr0FUwxZSrmVAbQ1H1VReiHRAPYTu/DXKt/HlQzzoHGALnXy8uLPT092cvLi93c3NhsNrPv37+HGOF2+7qLK/XQ5/S5ePocMBT1+/Lli52fn9v19bVdX1+HGR4yqrFbV6uV/ec//wmhodFoZE9PTyEgTSIEotqhLmB8vb0pxndugwQv736PiQcbosBJhWZSjkfuHqnfYDFicIRdYD6tn2ZB6/114p5vwIUtxbywhjz8TlmxOqY8/Zihj13b7XYLa1uIDeq+N4R8NDub/ETq54PwPkJxqPh+iZFQFTnotWKp33zmhr8uZTvGyq7qzKBaAM50Oi2sRNO3OqG+ptNpIVjN/VlBppsGkQbFzIfOhjw8PASw+mf0O0vEQh46EGBugun9ft/++te/2tevX+3y8jKoZV4Gjn2nwfDZbGYPDw92d3dnLy8vdnt7W0hK8Cn3MXvuvUJ//M9tQn/Ms54fIXW85SrnUT/UKCpUPzgZHgRaL3L/yKfTLBjYhUXefuI/xmhVBmCMIXGsWFyvuY2oUmZuNBcRu5S/YW+9/0cwYFX5cO+YjvS7aHGzqvZd7veqDRNT/WxnMZlMzMzCJD8MCXvAiM1mM3jLAIqljcT+NpvNm5Qs1B2zIGqH6rOl1G/MLNH1yt1uNyRfnJ+fB3Wsm5Rrpg5bcBAov7u7s7u7u2CSmL19/UWVvqgiVWKJVeRdq+3M6geoc1LHRvQgxAxguspvV4sdFduKDtsJNauJBnwDVFSyLvSOdXCuw/Vbp+Y0YZUYod/NC7VNyIUPaVp4xJoQ8bPFaxWOVZWD3/IZM+xj12glq1Yu5gGn/ufh8f5gMALL+vZ1XwYxM1TXcrksLEDXNHdAzaLvWMiojA39efo7uZBMO+oaZ4C42WwCUw+HQ5vNZnZ7e2uTySQwoe4dmGvDWHuUSRWn4xA1XxuEsU+Va1MPUBYcrXIejkCj0ShkJW+3W+t2u2/mbfkfz5EJf7UnsQ25xm+xm2K/KkCMCQuYsAHVG8aBguExBWazWVixxx6BpOf7OhzaBznJ2fk/hQk9A8ZUYt2bm+U7K2Zn+mPqiWkSqtmf6VnE1QAqSZ77/esbPAGgApWPzziu+zxVVRS2KutcSFBg83PqjxPCumDWqMDmsf0eq4CuijYrO9fHaati4SAQ+iTPVIN/pD2iBn1qMOz3++BsMG2mu+LTMLqLgXrQGl5K7cBFXfR5tS1UUgPTO3WNRiPYgmQA4ZT0+/0CS0+nUxsOh3Zzc2PT6TSs3gOEZe1HfVKO5KFMrtfrxgBV5ODF73XPK3NUYqM1ZezHQOgbFjCRgMoxDHvCOcqQ3Jdz9f/Us1cxSXKqUBcnkflDxg8sTYKFbssxHo8Lr7LwKtjXucycqdL+KWLxg62uVjzofccpx6Qs9FL1QVNl+fsThFb6Z9rNg5JztOyU42D2Njcytu5Dz0+xiR98KRCyLoY10LzsUR2nh4cH+/79u43HY/vx40dYTupnRFKmkn/OMhUbcyjLwOzT0arIQS/TiR0vY7lch8eOVR1FXsXEPvzuQZhijTr1fK+oyaA5gY1GIzA1WTm6Qk7t2BQ5fITUUcc/nQl1pydlIu3cQ70sREdeijUVWDraYsDzbB3L7fP3ywHTe8VVjfVYuRqgJiSjibdmf04vbrfbME99f38ftuhlTYzXJlVY8BApY0C+D0mKeNdCp9j/sU4u83Kr3i+nvsvqV1afFAhj1+Skipep5+haYgVQo1F8ZxwzJH5PmdRzvFfKTCw9p+r/KakNQl2HoQ+eq3RVtVv1gXMjXVd7edDG1MShjlYObN5E8M7Tfl98Xa2ZhS3rdK6YWRxWyBELjC1NrVPHOlLFbtS/YcOfEqJR8V4px3zFFGhV2KQOS6aAqA6E1lXPq6JaUs9TV9X4OnO97hlDvf37TmBB5rRTmxTlnuOQupZdkwOjH4BV5KAQjWfBMg/Qq9LUuf68KsDNgSZ2np7rjx2q7ut0tG527t8KCiAJOBMTJGFCZ210ztnXt8zTLZNYu+dA7RmwDguavXMHhrJjWsnYubGGiRnZnvLr2j1V7cYyJq5iJ5WdC+BI19K1zZxL8Hw8HgcVDAj98gM/GHIMdCiDpwDoWe8QVWz2jje/x/7OSRUWzJWZYqpUGfp/HcfCn1/XpPD39syOCtbNNwEj5TP9Rs6gzmHHHJC6g6mOlGmVj5DaIPQjrYrtUea4+PNyQKsqKZMgdk7OyK+q7lP3UvOl0Xh9/4guWtctPXa71zdsaoIqGdzUA9Wd8rqrSlXWjPVzjAkPkXczIZJij6qS87QPKafOee9ljqoAB4i68F63GNFpRM3y1qlG75SUDf4q51R97ioa8JA2rJ3KBeKr2IU5FRxjmKpMmLPx3hMnq9ohsfqk6uiZEBuQjBnsQxZRmb2+9ousaV2yGfP6y+pdZq+nogdVgOb/Vqfpp3nHMalrc3FN7P+qoZyPtkv+VxKrN0zHvLd/Y5LuyqAgrGunfnS9q6joKnLwdsGxxiirdEyqMGGsHofeL3d//39O/ZQZ7L6DeDYYjXfL6X1JxsAZAYy6e1aqju/RAFoHBXYqVJN69kMAaHbgajtVyf6b38vkI5yP914fGwCx38uepypANZUs9u5in/kdY8GPANtHSUpt1yWEg2zCQyqVGlm5mKE/J3aeZwJvF8bsUf9MsXN93fVv/ywpsKZUr5mFV3SpswETqjOijkgdD90/Z0zqOCQ5T5i/NVhdRw5a/F7W2Kn/ywz4Q8SzWUxlpa7xA6vsb3XMckZ7zlSgg1jHoqDWTkwFfauElVJ1qctQ/llj//tz6wLQrAYI2bslttYEyTECDZICSS7elXNiYt/+3rlyFFhl4m1if00sfOI7DGDpS6/5TUM0ek6s/WLP4dsipR1y9cvZfGUDGyZPJVikpDII2+32m5tqwDSn2mKNmNqSItYwMfDoxH9ZCEK3xE11YmqEa52qMEFOK9BB3C+2Ibt2Ymxti283ZWkFnc92ikUfYs9FW8WYLQVEJRBeTO4XXOWkMghZRMMD+Z1NfWVSdhSSAo8/1zeeZwY/EDzzaV38LENsl/ycmo3ZQbFj+n9qkZS+MVO3U/NgLnOOOK7bnXjg+eeOPVOKCVPnpL7rzhub1QDhZDKxRqM49+n394sBJTXSUtuJ8K3nkHOHoc5kfooZtAwah/L0HF9/f70XHXRVmE89YH0/ipm9mUM2K24XrEyZWsSk1/gwjjoIqc069Zn886eA65/R9+1PdUxio1Qr5Gk+dk1uVKXURaoRfNxMy8mZBb6clAOSa4cydvLnx5411Q6xclP1SYFByQAQq/bKPZM/5n9L1bcu+xWeb/+eqz/lUz5Aqr8j/lM+5SfJJwg/5ZfLJwg/5ZfLJwg/5ZfLJwg/5ZfLJwg/5ZfLJwg/5ZfLJwg/5ZfLJwg/5ZfL/wMdJAQwSSTfBQAAAABJRU5ErkJggg==\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -468,17 +469,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 10: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0165]\n",
-      "Epoch 11: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0165]\n",
-      "Epoch 12: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0156]\n",
-      "Epoch 13: 100%|███████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.015]\n",
-      "Epoch 14: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.015]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 66.87it/s]\n"
+      "Epoch 10: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0134]\n",
+      "Epoch 11: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0139]\n",
+      "Epoch 12: 100%|██████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0132]\n",
+      "Epoch 13: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0132]\n",
+      "Epoch 14: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0128]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 71.68it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -490,17 +491,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 15: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0141]\n",
-      "Epoch 16: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0142]\n",
-      "Epoch 17: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0143]\n",
-      "Epoch 18: 100%|██████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0134]\n",
-      "Epoch 19: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0133]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.04it/s]\n"
+      "Epoch 15: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0124]\n",
+      "Epoch 16: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0118]\n",
+      "Epoch 17: 100%|██████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0125]\n",
+      "Epoch 18: 100%|███████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.012]\n",
+      "Epoch 19: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0117]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 74.46it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -512,17 +513,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 20: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0135]\n",
-      "Epoch 21: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0133]\n",
-      "Epoch 22: 100%|██████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0128]\n",
-      "Epoch 23: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0132]\n",
-      "Epoch 24: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0122]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.15it/s]\n"
+      "Epoch 20: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0118]\n",
+      "Epoch 21: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0117]\n",
+      "Epoch 22: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0113]\n",
+      "Epoch 23: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0109]\n",
+      "Epoch 24: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0118]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 74.26it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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ZoFarYT6f4+bmBqPRCLe3t6hUKiFXcrVaJYL31iHR7BLWU3li2+IB0FOnnqPjmSd6rX0e60s7uV6v4+LiImQ19Xq9YAcyI75araLT6YRlGnTyrHOmmwZk0ZOC1XnJ2i0xVRRTF2yUXWPCsjy7yHMG9Lka8Z9MJkEdM2jNOWeOck4/bbfbxFpazn0vl8uQ2s7EC3VMLO/SnBfLuzz8TgsLkayw4D2UYrVaLQDt5OQkTL9xfyDOiNTr9bBJgX50Fw7b3jy0tyS0HqI+UBnH3woErZhKPHphOop0JmU2myWkoAc0kpftw2cTyNPpNNw/HA6DZz4ej7FarYJdWKvVcHFxgWKxiLOzMyyXSwyHQ/T7fQwGA7Tb7RDGYYCbSRiaOEEpruYEgUHniFLTC+vEzA4bhrGhHd6rEYXdbhekF8NWnU4HP/30E5rNJl6/fo1ms4ler4dmsxmA2Gg00O12g8NYLpfRarUSIS+Lh7xA3Du9XwtXYNmA7r5S05JNME0LUluyg8ESAUCJOJ/PMZlMQseUSiUsFotgK9FQB77MvjSbzeDklEqlADIubSAQt9tt4puAsEDUeqoGSGsDr7W/rUTUMhg+oUTrdrs4OjpCt9sNQWbG+w4ODkJbGf+jdlDpp3P6th55aa8QjXqcaeI/Td2S7IilVwYgEfqwc8HaSXxGzI6KqW9KRUrE3W6H6XQaVvx1Oh0UCgW022386U9/Ch41wcjsnIuLiwTgNF+RHwbXF4tFQqovFotwry7oUv5ZJ8szQaydZ0NpzLGsVCro9Xqo1+s4Pz8PwHv9+jXa7TbOz8+DWq5Wq0HaURXXarUQRYjtZfNU2nvu2DoWXohAf6d5akCcmWnXxcqy52PAJ7HDKPUAhEj/aDTCZrNBr9cLyZq68RONeW6DolKOg2a9Xj8CYbVaDXPknE7ULGXbNjvPq7yNtdXynU4EU6x6vR5OTk5wenqKi4sLtFotnJ6eolqt4uDgIGxOQM1Qq9VCO60NGxMC+9DeIAS+Gv+UVKo2LehiHy0HQOhYbqTJEbfb7UJH9vv9IEk0MB4LBam3lsYoTvVxOepwOMRms0G73cZ6vcbBwUEw3Fl2pVLB8fFxqDuAIN0YQ+RH7TKqZTox3OaOQN1utyGUpAvFGKZSqalmikYFdFPSRqOBV69eodls4p/+6Z/Q6XRCmlun0wmBe4KP5ghBqDafTUjIUr15pguBJ3jH6op75z0A6n8rQQkONpJBao5eACGhgNNodtsxz3DfJyhMtagqtFqtYjabodFoYD6fh+tZR8bUuIirWCyG+hGEmp9oVSy/CbD1eo3ZbIbNZoP5fJ5Q2bPZLOyMqw6WdXRYPwb9Dw4OQm5lp9PBn//8Z3S7XZydnYVBxZQrmhyMl3KvSLsFnuV3lt2ah/aeMSFZaeipXU/6xVaz0XAm+KrVKg4PD8P0IJ/BAPJ8Pg8qj5LGktbRi8spYBUUu90Ot7e3GI/HAIBmsxmm/xqNRnBIOFj4n/YTAUgQWntRZ5YY/tlsNuh0OolF/7xH9+KhB07AUqKSuJ9Po9HA4eEh2u02/vznP6PVauHNmzdhaS0dD+YEMvxE80AD0BqVUIoJArv8Iov2AiEro5sg2gVNaarYjiarljmKmSp+fHycWHO8Wq1QqVQwmUyC1GFnWEeE5QKPN4m051k3PoPJrZwZoRpeLBbodrvBeNdyKBmVV+qkcNBwrpx10txD1sUumSUo5/N5CLhzaz2qbAKGaVQMLrfb7RB+OT8/DzFALsmk5LPSTvs9xlf9byMl3wWEnsrjA+35LK85do6VV2lBCQkg2IoMHTBGp8mstJU8JqTZMDpQ2C52MgDc3d0B+LoEkskV2+0Ws9ksqC86LjQlWBa3wqN9q8H3mIRhnXg9Jdd6vUar1Qrlqb3OaygJbdhFwy0MtahtnmZCWdJBbuu9T0htrxCNLdQDIMl6b3rcNoLlc9aB0ojX0gY7OzvD0dFR2Dx9MplgMBiEIDJVFjuHZXievTLXeuhU74VCAePxGPP5HLvdlzlnLsLigKCHS0egUqmg2+2GNxHo8oHdbhfqR4nGdqv6S0tKUAmrIGT/0KamTciEAzp8PEc71q7Xsc+x9dBvzY63+aPfRRIq5ckVS3NeYnE9NeYJRg1f6A6hDJwWCoWwNmW5XIaUKxr1asCTMSotY6NcJ+Rpp9Fwn8/nqFarYR5aN3Ri8JplsIPUEdOkAUo5jzyJpNKRNrLa5WpXM9BM0KmnqxKf39bb9kBoHT/+jvV3HtrbO1aGWtIKKgO9SloRTqYyaQFAWBVXKCTfhUKVo8Hs8XiMh4eHsLE7vUndrkxDIXrcBnhZZ+2M8XicqNvDw0PIpaOJwEGh5dG7pKfJQDh5pQOPth9NAAWdtaFtYoSVTkzSpYOnyby8Rx0+DgTLB37Y7zQ3ADzao1y1S5oat/TkreHyUtYUmk5RsfEaG6PKA5J7JXMajZKyVCoFUGmIRzdk0kAxnQVKXbv1nNo01tZRz1dBpKGTGHhsR1YqlXA/eUFpaQHCOhQKhfAWBOt08Td5pKEWT4CoRlDw2TbYvvOygfL4BR7tHaKJdY5tGCltpGgjeE5To5g2tVwug01Dh4AhEkbxuc91q9UKGdCcGwaQAB09a+6BPZ/Pw56JXGXHmJzapcyq4eo9hkh47Wq1CjMhPAZ8NR9KpVKw/2g/UkJtt9sw80JbloDQtypxcsAuY+V/8lvBY6dDyXMFGk0XvlVB+492o0pDOwBsCIyDNQ89acbEA592mD2nDfKcFb2HjKZ9R7Wy3W6DMU3JpeqAr7bY7XYhFYuhC6ZaUQ1Xq9UAhul0GrxESlW7oIn2m0oW3eeGJoHannx2uVwONiCfsd1uE89kWRyMtCsVdGo2sL0Es4Kc/IjF6nSGS/tVJbzGVQnAGNi8/rVYyKInbZL5lOtYObtWgudIZPxiscBgMAhp9eVyGfP5HK1WK0yvMezBiXZG+glCDbLqCO31enh4eMDp6SlWq1VY1MRtjSk1FYi6ioyA5PZ2DFbTHuTbpsrlMtbrdUJy6Z451WoVzWYzeNK0L2lqaCyWUpTS1i6HsMmldmCwb9RBU5NCJSAHjNqylLaeBPT6/ruEaNIMTWvXeZLSqzCP2+dY1UPGA0i8QoI7KTCEo9m+6vmyE7n+QR2Ah4cH3N/fB9XMuKPuxEAvVOdQdQcqSiEAwaQAkJBwtgM5sFgXerHqdOiA1UGkmw9RMqs65nXkp24oZdW8zkkDCPXUnbW0zdb29HDC72cHoef1ZIler5I87klEls9vGuuqQrg/zWQyQavVwmQyQa1WQ7fbRbVaDelK7CT1IslEfb/KbrdDp9MJNiE3SaIk5DUEOtuvthE7jh8N7zC0o8F3ACG+SMeo0Whgs9mEaUAb1mHd6WBwQFhnww58AKHeNmTFazRoTTDzOxZmSgPjd5WEMcfCoj/N7rPxpdjI0RHLDuTbAQaDQQjTMAuE4FssFmi1Wjg8PAzTaGo7MiNYExHYLqZecT2KSn4Cjk6Hto91573sGE1g0LCI1mk2m2E0GoX56VqthpOTk8R8LsFnBxXbY4PFrA8HOgeyXQ/DepAXard69p/33/atSuLvEqLxCs2LdjW8AX9BFInnyEQrhakuASQYSFuQi5C44dHDw0NwXNQ2A5ILcVQV0hnis9Xo5z02PEIQarjDzgNbZ4HtWa1WYWaG9plKJA3vKD89M0f7SZ+tZWgdsjxe3hvTbPbZdoYqi/aettMpIyu5YpW0tqKqLAJTy7MjWMX7brcLANQlmP1+H9VqFXd3d2g2mxgOhzg5OUGz2Qyrw5gxwv+cxNddRQm2ZrOZqJdNY2fgnB5qsVhMpGAxzslQjc2m0WWs+i4YOix0ONRBoGrUgLrVLJ70ZR9oGzjYtE9iHz2v5Vrb38ZOn10SktKckxhZAHqqN1ae2lkqEe2H87D0brl+mLFCpkzRfqPzQrVHiaOdox/bMZr1w/lhOg2sNyWMnTJUEBLousOpl/Vj7cOsGJwnuVgXnTXxnMcstav3WT6pzfl/oo49m8BWzPsPPE5bj3nVatvofwUkbbhCoRDWjfT7/ZBJcnp6GuxH9ShpE3JulWsrvJAKHQGGaHSkq61G1c/AM+N6Vt3pUgBNtGBKmGYyq4NhgUkNYSW51y92DbCnMtPCL7bvVEtRylMDULrnoW9a/L4PeQDz/sfOKVOs6tcBsl6vw7UMO/BN8pRcum2FrqOo1WphSzqqWEo5drTNOmFdVM3xv0p/Sh/Nj2THacKr1iuN1DSwFANhmsPoSXtbRky4cEBqsPu7quM0gzPLK47ZkHrOzlnaZwPJ+JlG95WY7sVgdK1WQ6fTCd6xSjtNiedid353u93wQkjmCFqnhirfhktsnFIlK9uja5M1fU3LYNBdyyKY00BjKdZ3aapXAad9w0HDNnAKU9fqPDsI8xb4LaTA0u9YKMACWcvgqGQqPFOvdAbGLl1sNBrhWr7+lrE8gocM529OkanK5cezD20SKQFFoLFTlRfqcbLsPNtrWN562sg6Nnq9/W/tPpvbyAFlE0Ky6FkloVfhtHtixm3sOuCxRPVGsKpI4Oumm9z2g1t36IcqeD6fh5kLSj7d0YvJDupd6zw28FhVKtA5u0LvV6Un55lZZy/lnpI/BhKP/5ZHlocx8hxAnQ5kSEoHPAP+o9Ho+4DQVtzzdGPX6yi2xz0A5imTdQAev+BP7TK1vYAvrzYDvhrx6uUuFouEjUhHg/PJVPOUrJVKJTGtyLp4IOSccblcDguN6MTwPt5r2xFz+njczlCw3ToYPbW9j0CxQGRCCCUis5e4H+R3dUzsrImtLMmCVEdvlqOSRypm1clKDPtMdpLN2Ka00tgc72Ngebf7EnejU6FSy4ZY1GGhg8TZEX0enSBrJlgAKuC8QemZKracNN5bvlL1EnAEH9eAM9VsNpthOp1iOp3i5uYml7QFvnHjdB5LA2BaWVkSMTaSYvYNn6sdqOEce6+GWGhn6Q5UmroFIDBcJUCx+GW9MZCcVbFhGes9azYNkxe44VC73Q6euQJxt/s6hckBFGt7Ft/zSEAgufaHSya4O4VdH31/f4+7uztMJhNcX18/fz5hXoqBQ897gPP+5xHnVtWoU6Aq2mM8O5GzFO12O6jJdrsdPGnuTKA5hZpIqs9nnexg8Ow71ok2FUGtCRvedJp9XhblMXNINgaoGzzp+mebJMydK7hLxv39vbsW3KO9QGgZaL3YmLrwABZLI4/dw+dbSaNZJQo+DYV4NhrwVXJxCenR0RFev36Ner0e1mVwewyCU4GmoRZtk+WZgojXKoio7hjXJE9sG0nWE9c6aH+QYqaKtdHZBjodVL2Ugny9BrdJ4azP1dVVAOD19TUWiwXu7++/nzqOHfMkjaduY8zIuh9AQqpYsOkOAlR3OovAZ2lZ7FiuSuO2GTZeSDDSgWBZFoQaWrHtYx2siuJMjKaeKUBU0sb6QJ/l8dDy3StLHQ46crR/uV8O0924dGI+n2O9XmM4HIYXEnFxms1CSqMnvcdER7M2xI44lYwq8axtZO0m/ifQCDCqQQKsUCg86kQ7G6Ll2nqyg2kDcp8WbpGmmct8BYUGii0IPQmmuYaWf5ZYT50qVGASHPztgdTjv+YyWj7wvDoX2+02sd0Iw1LT6TQk/i6XS3z69AmTyQQfP34M2+pRAur6nix6kk2YJRG9c5bx7CidtbCxO53b5bytneinVFQPU8u1QFe1qbE77sVMiWe3SKPDwgGgktTaUZr5ohnVeo1+vNQnz8HybDsO6jx95tmjNAUIQkpA2n+6GRMX7E+nU8znc/T7fYxGI9zc3ISXITGNLq8qBvYEoY4+O4UTk4geAMvlcsITZGjC2kAEn25XRmlnQajXEIQ6V6wq0cbWKKl18RE/bDM7iJ2pzgPbqrMavFdnQqwdneXEKc+VnzbtzYZg2Ea1Xz2HTxMOuG6bzgbf+zKZTELYZTAYYDab4dOnT5jNZnj37h0mk0mIn+oiqX1mdL5p3bFlrL3Ws0cIHEqWbrebCNbq+g0FIaWSglDtQruvHiWWLgu1apRMIxO1jjZArN4rv734neWDznAAXweo5gSSYo6f5+WzXL1GJSfL04+VwrT5dLcvC0IuAhuNRri+vsZ4PMbbt2+DGp7NZo+iAjb3MoueHKJRgOlI90Y3maYbNx4eHoZ3E1NS0cbT9bhql+k2Zsx81iWQjK3RFuO3rpdQR8juI6iDgNfa0InurqpxQQAJSenF6qxjBCDxLNaR0jiPSrNet64wVOCr58s2MZubjsdqtQp7+lxdXWE2m2EwGASH4+rqKrxOgxJUbWC2cZ/wEfDEhU4xnZ91nBKw3W7j+Pg48UI+Vpw5fZybVSlHwNKGo+GspJt7eyBkfXTynR9dTWdByPrzfoKFA6dQKCTS+7XDeY86ZOp06OIiSn61ia2tyLIUuHYHCc8O1f0OCUJ6vHQ+BoMB5vM5Pnz4gOFwiKurK9zc3OD+/h6fP39OLPa3AXmt4z70zQkMWaBkpVhRXUqo4FBHhR+dMQCQWH2nkXztFCZTEjS8VuupnqBu7au5g5TO3PWKklIZrXPPABLbvtm1JRqqoVRl4gOn/YAvgCF/NDvHOi+2D1QiqllgEw4IPiYbzOdzzOfzYO99/vwZ0+kUl5eXGA6HuL29Dec0UdWTdmoGfDd17DkhPG6PWYZwxHMDR24mpHYd7T7OYFAisAzGqrzRz2Pcl0bDOLyWkf7JZJKYflP1z5R/2lxkvA3reCEaShh+PBXLgUcpR/uWoCMYOUj5LEplHUzkjZoG2kc0NfSNAVzoTvtvOp3i/v4eb9++xWg0wt///neMx2O8f/8eo9EoOCZAcq5dQejFXzWrKIv2loTsaKU8qlkNarVLaPtoqIAqiA3xpIqGW5QxXnYyj7MTptNpYs6T6n2324WMGTLQZghbY1/bppnF+5AtU00Hy0svTKPlqPfOOmngWeeAp9MpRqMR7u/vMRgMMB6PMRwOA/go/eyaac+Z8tqQl/YGoQ3RqJRQ5uiIVJtkPp+jVCqFiDrT6HkfG6VTVbpWlqrLzizwmJ3iYieoWuI3O0Pnjo+OjlCtVkP2tWW0lm/jhLQNGTCnhOK16qHrOhf+pj1LO1ltUPWmyQf1jpUfOg3IF0EyDLNarULQ+fb2FldXV+j3+/jb3/4WPN75fB5MFe1zyw9toz5fZ6vy0DclMNjRmSZ+CUbacdz2jVJLZ1Us6ao0glCdGRX/dm2Gpl4pmKk+OUFPe7BerydsMQt2ldDWEQDwqFPUJFAQU92qjaxLPHm/8s+TiNYG1OvUbiYgme/HnD9Ot93d3WE6nYb5YUpAHXRWAsakoPIiD+UGodpmVtXaYKjG2/S/qsLLy8tg/9GBUKDy+t1ul9g00pOEGnohKdjUQ1XJTFDqHs/A14Xvdt2vtdG8pAkCT++hlGMIiTahlq92o0pSq/LVnCGPi8Uv2eJcisDEA90yZblc4v7+HovFAp8+fcJgMMCnT5/wxx9/YDQa4cOHD8FZob2pA9oDnQ0tPSU8AzxjnJDHLGmlGGfb7XaJEVcqfV1HS09VDWv1eFmmetRaBzsj4UlXPQcg2ErlcjnMnXLHL7bLdoiqft1EyIJQY5w6BenNzqi0tHaVBaG2U9tP84O2ny7B5F6M9/f3uLm5wc3NTfCGh8NhcHLYBjW7tO1e/z4VgMAeILTeoJIXptFjqq4IsNFolIiRKZNp/9jvWEggVl/Ww1NXQHIel/sWzmazADAG1gkizr7QjlXQqedrPX5vTtt61upRq2ftSXf+VpDQVOAgpvqdz+cYDoeYz+ch4eCPP/7A58+fcX19jdvb25AUYTWMNTOsxvE0kK1vHtoLhDHyJCCP26knDRLrqLc2jgfstJiZmgDagXYwaH1VIq7X67ApkW45p4Fz7idIqWbtPG92JiYtFWDanjQPk3VV55Bg1ClF3XNwPp+HqTcGnT99+oSPHz9iOBxiOBwC+OoIan/EeBrzkq0Nm1cqPjlY7YUMFEweeY5DGkiApHEbk4T6XMsYrz4sk3VhxjS9ZIZsaLNWKl/e7KnSUJ+hHq9KQpWWdlBo7qGteywOp0DV8BWBWSgUgonDGOBkMsFwOMR4PMbNzQ3u7u5C9gttbR00ll/WVLB1SlPPeWnvzGo1+NO84tg5z9D2pJ5KAjLAindeY+/V5+h9Vo3olrt85YK+jKbRaIRF771eL7E9h86ieOlovI7OjLXp9F0tBJbaY5ZskJwdbRMkGNDXmN/V1VUISPf7fVxeXmIwGKTan3yWVdEej3mPp57z0JO84zTypJMeB7LXOeh1tpzYvbHrFIAKEHqqtPeYQ3hwcJDYrcsmGHgMtm3TTBmm7NtBR6eLxMFElWo9UTtjo89TM4evz2Ayqq6AG4/HIVZoVf9T6TnK2AuEwFfbIbaeQm2BNAnp3acSQa/3psxUonrlWK/OZuWUSl82HmLqfqvVQq/XCy/Z5vZxdhte66HyPwcpVaQuBqfU9CS9zqGritVBE+tobStT7e/v73F/fx/U73A4xKdPnzAcDvH+/XsMBoMEnzUgrn2mzkla1CMGwLwxQuAbQjSeB/Wt5Bm3SlnPihnMVJmalcOEWr5outVqBbuP6WDKSDt/rCC3YSHNUuZeinbPQE5NqoYhiL02qyTWwah1sPvBUArSMWECA9uQh3//F7S3JLQjwFO7ViV79iO/bfwPeOz85BmV7CBdj0IPl2EVrqDjO946nU6wAWu1WljsRAlENQcgGPEMu6iEpm2nb4zi9ay7escWRCpZaYexXOWH7tagK/+0HE7L3d3d4cOHD7i5ucHf/vY3jEajkPbGGKb1trWflWL2tp7/P1HHVrrYc2mOgQ0/aMXtOc+ui6l1qzqo0hiXI/gYViEIDw8Pw2br9HjVQwaSMS6CUedSVeUTQJwGZKKo1kdjg15b+EzLI32ODU9Zk0TrabOiuXmo8kvvTTv+VMoLzL1AqPaDZQRJwaUg8VRIbARZiWclIu/RgDBnJmjn8Z2+TKLlJpn1eh29Xi+8801zFtXApw3HTtf34xEM+uYl/ue9m80meLkqcTwTww5IgsVqBHrzwNd9GFk2s6Opfm9vb/Hu3TsMh8OQPRSbXiUvlexMlOLAXhvznJ8dhGR8bDTnkYZaMW86TRlkyYYAqNroPDDGd3BwEEIq9HT5ytWTkxPUajUcHx8HSVir1RKqjGssFGhqb5F0OtEmRtj2eG3xjtmBQD7Za/h8vZ5TdQxQTyYT9Pv9kDvJvrPxSttPWTZ32rXWds1L32wTWrWQpyH6zd82/hiz8zQrmxKQwWS193q9XpCAdEDo8TIYDXzNPNaprs3m68uxmRCqe0xrIoeSDWExM8cu/dQpO72H/LTbZ+j0n4IJQMh2IQCZhk/PWFPxPXte+zTWT/a8/a3/VXs8uyTUBFHbAD7cA6XXIHuMwNPkVZ1GsvO3jOsx7EKAlcvlAMKjoyO0Wq0QdNbd9jntRvDbSX7deUp3FNAXXNO4p0mgnaDSystEIYB0yk15ZlPENNdQ+UNJzbqzvp8+fcL19TWGw2EAtEonD4hp/ZMGXAtA+z8PPSmBIXZegWgpFk1XoNpcu2azGaScrlGmo0Hvl3O6Clh90bRmhAAIuYycv9YF3uPxOLH0kepsPp8HqWMTDDSli6Ah+Pj+FKaHqVnDQeAFoC3PWD6fpd50ofBlum4ymeD+/h7D4TCxDYcnxdLAZ/vQA2YMA97vLNpLEmYBUQ1fkqpWVk69Pr23WCwGR6Jerwcbjm9tYkil1WqFKTSb08fGU+USqJS0npfLd9sxwMssZM3K5ko6XVylSwk0/khJ3Wq1sN1+zR4nIDV7KC0YTUAT1BxsaquSt9wJ4fLyMixKV686BkR73DqfadIzVue0cI9Hzz5tF6MsUU3A8JVgXBhPZ4Mp94znaUBZI/98hjJTN/nhMXUA7u7uwixDv98Pi78VhPryG/0muAqFQtixVafkCDy+nId2ouYqelpCfxPonsSkvcpsGZXYLCet7Ng1ejx2j3cd/3+XGRNdK2HJGzH62wZF1f4jkI6Pj3F0dITj42O8evUqgK5cLgdVq69V1cQAfZ7akqVSKSQKMHamC3/48u3r6+vgSY5GoxDwZVqUAo/P9JwK2m1HR0dhHno+n6PZbKJQKCReS6FmgtqUVs0DX6T6wcEBCoXCo03Vh8MhJpMJ3r59i/fv34dF63zFrdcnXmzQU8N6jX7H7o3Zj1m0l02YNSrULtRzaQYqmU7HgctB1ZGwiQTA4+xoEqUSJYxu6sisab7egOnug8EgscaCNqCCUFOmSHa6jbFBrlkuFovhpTqz2SzEG5WX6rhwKo/ndTDxnA6AzWYTUrYYH+RA87RWDIhZfZolSfW6tGti9ORNMj2kpwVCtTFk7m63S6zBoKSwSwy57pWhGn0er7VMp/1HdcWwy273dW6XO0kNBgOMRqPE7gI2UGz/e22mhOXyycFggOvra7TbbUynU7RaLazX6xAyogmi6551fphz2rRpyRMF37t373B3d4fLy8uQJ6ivyfWkk3fc9nHMFkyTeHbgPLsk9JwOrax2SOx+7z41zvmt603sN+tBSWAXhBOMlH66sTc9Sh5j2jvtQYJW6+sx0oaeeEyfrZtLrlYrtFotrFYrHB0dAfgy98tdH3if7gDB/41GI3GMz2TZo9Eo7BM9m82CA+X1UwxgMcoDurz2ZRo9afG7SisbH4wFKb2ZBL2Oi7Ep3bx1xwSpAouJAnYKzb7AkEY8f1MtU1J6+Xox88Nrk2W+Pm+73eLjx4+J10ccHx+HaUXWidKReyQyxskBxrqOx2N8+PAhJKze3d3h6uoqLFpSjaP1iUnALKBZfsTu0Wu+iyS0FfEkYJ6HxqasON1kp5NU5fIcU9i5jkK9WILTJo3ymJZvHQvgscS37c0y3FVqKfhXq1UI20yn08Q2GQQMvWtNvtCXOfJ7Pp+HbOnBYBC+B4NBwgGkw6OqWYHo1T0GKk/6xfrbppxl0V67clkbybuG57Ki5WQImUaPVN+sbsu16lTBZzvKGucesGiXxurl1dkrT88rEFVjcIBQ7TN5gnvQbLfbxDx4vV4P8UmWvVgswhqR29tbDIdDfP78Odi2NiyjQW+vHVnASlO9dgCRn3zed9mBgR3jdSwbHPtYpmgjKOmYGWwZoffoElBVq54jkTZ/aYO3nrPhgdPGSm17PPWnbdztdri7u8N8Pg+xUH0tLaUgg/UcYHTeZrMZrq6ucHV1hQ8fPuDu7g7/+Mc/cH9/H0Bo56btwLCUBUAPfPajz7QL+fPQN20DEgOfnk+7l6SOhmc76jXqgKjESgs5eMaz9z9W99ggyprGtGVrh2mMUN/sZDcMpTSlFO33++j3+2HzSuYwUvKm2Xq2PXnUrr3XtlHPW2fu2W3CNIBZYPCYVtCqcR2tKt1U2lqAqeS1oPDs0pidZ8m2RQGmz8oLQr1HvzXZlqBrt9s4PDxEt9sN0pH3MDmDGTFv377FL7/8gqurK/zyyy/hRYYMTNugt0oqr35PBZ7yhiEZ69B9F8cky8bLItuRaZIq5ryk1cMrL6aOs455Xm+aQ5LH/mVn6bpmzv7om+dtIiztwslkEhIURqNRWEKgSQoxe87WNwtkae3IKsubpcmiJ6tjlVhWQnkq0lbKhkTSKmztvjyNs8+K2T5aN32GzUCxQfLYM71ymAtZr9dxcXGBTqeDk5MT9Ho9nJ2d4eLiIiTfMrtnu91iPB6jUCjgw4cPeP/+PX799Vf8+uuvIdnC2oBeXdLaq21JA43yXKVrbFMq3aA0D33TNiB5pGMMNLEwSNoI9v5bybqPxPZGc5qk9iSi7SB7jtdzOo8L6rm2WdWzLvnUGChfUjMej8OCJd0mL4+W0bp70j0vYGyZ9ridfMhDT5o71mMxTxJ4PI2n13lGLCsec3ZiajQWEvJsHq9NaSDP6pwYT0i73Zcg9MnJCTqdDi4uLtDtdnF0dBRe6MjsIN167uHhAdfX15jNZvjtt9/w+++/4927d7i9vU3kM1qtoxLJ0zKedko7b79j/CD41PGyW77EaG8QZjVMr0+z49JUIs956ytiUtB2fEwa2Ps8KQgkHSeP9pEcpVIpvC1Kd3mwibeapAAgbOVxfX2Nz58/o9/vh3l0AtZbq6Nt8/jj8WXfwaZkMeE5K2n0zXPHHlkJqJQmzfSerPssGLOkl+0UC0A7yLKea+OAXt2ZFdTtdvH69euwHbF+M12NanWz2eDm5gaz2SzsmPDx40dcXl5iPB6Hsq1D4rXJq3dM+ln+7TPIvGfFbFWP9k5qtZX1bCT95nX2vEeeU6AM8iRYmilg7bWYE2RNAa88r642JGWlErPDe70eXr16FRJ2ufy00+mEXEmmrC2XS/T7fdzf3+PDhw/o9/thzYhmU1te2AA862QHmsenrPamOYNZYao89M1rTKw6s8DJC0D7HAsiLduWF5NWadLR67B9JL2VhFoXhloODg5weHgYlqEyK8bbcIlJtgxIUw1TBXPeW8GW1dGxc1m8yFuOCoy893i0tzpWKaTS0RstManEY7GKe85JDID2Xg+Aseeo7ZnlBNm2WAnIawqFQtjX5uTkBK9fvw7ecKPRQKfTSex1SCByR9XhcIgPHz5gMBjgf//3f3FzcxMC0uRNTPV64ZY0IOYxYyx5ZgjDULa8vOo4/0IApEuyb7Eh0sgy+lttlTQpuU/Zng1FlcqYIBc88cU5XOBE8BUKhRCMns/n4Z0iBCNf9aA5jhoCSWtfnvbklagxSltz9F0koc7taoqU2mYxGy5WuX3UpUpCTyLGbNC8HaPhDmt6eFKXqlG1Az3dw8ND9Ho99Hq9kC3D3EF6x5qUwLcqUQL++uuv4b1yk8kkMdesSb1aNyshY231JGiWOeNJ2BhvvPuzKLckTAu3pD1w3+vzVNxjRp7RnPXMWBlpx7RTdR20SkGbyq9Baa6U45Qcg9JchOWtmksbZHnqnHZsH3Mmb1lZtPfcsZcIqiPG2m72vy0vL7PsfbzOgiGvdxuTrLajrRRQD1ht41KphMPDQ7TbbfzpT3/C+fk5Wq1W2PmLbzXl2unxeIzlconr6+uQFf3f//3fGI1G+PTpU1iMpVk11v6032lSLksD5RmglmJmQdY5S3u/YFG/taJWHXuAfA7y1IFVn7a+WWXEztnBFbte31miL5DkSyTtrhF8bwu3F6ENeHt7m3innF1haNvkDcK8bdLfTwGgAt7mL2bVx1JuEHqLikie5LP2YZqdaO/V/2nn08I1Mc8vi7GxesWoWCyGabeLiwscHh6GlCxuO8yAdaVSCftIc/Pyt2/f4o8//sBgMMDl5WVQwTrr4PEkjxrNkxySFyjeQCCPdSuTpwidvRwTL/HUVjQGSK20NiavDWivz7rXA31WB2qdFdReiInEtcXchPP4+DixblolY7FYDNv29vt9XF9f4/LyEh8/fkysEbGbtVsTSKWPt9+M19a8fLYDex+1GgvVZNE35RNqA70Ym1XJWZIudsyeyyojVl4ac2Imhv5We5Aea71eT+wAZt9rx004uVPq3d0dZrMZ3r17h8+fP4fZkOVyGVR77D0mnt2XZ8ZiHzX9HFJz3+uflE+oYQkrnfadLUkDogWd/rcSIFa+Pe45RHqN5h7a59kNnLh67uzsLNiA6gHTS9bdHt6/f4/JZILffvstTMvd3NwEAOq3BZoHwn1it1n/81DWPbGEijTae6GTV6k0yZQmYXg+j5q0x/ImVNjnaRnWfs0qR+tjs6RtQJprjLnKjg4H54W5hwy3/bXgss/0+OoZ/2lRB9v+LHoKSJ9y/5NfK8bAqSY12IfGFiFpWXqv52VZipkA9nyeMJF3zrMPrR1WKBTCS7qZCdNsNkOwmutGuEPXdDrFp0+fMBqN8Ne//hWDwQBXV1cYjUYAkHh3M8vn8zw+pDl+Hi/Sfntlax3sPWmDVcN438Um1Mp86wjJ84ys8/s6Jvsw1DtvBx9tQs5kUALatSKz2exRIHo6nSYyYjzpFwNNlqNlB47XLntsXzs9TXORR/vQk2zC2AjVxAOtlAeIGKOyKA+DbQjBUlpneJ4wTZHNZpN4+SITU3lNt9tFt9sN2dLcQb/f7+Ovf/0rxuMxrq6uws5Zuv2vgs9LUtDpupjKtsditnUWL+xx5Y1XL7vSrlD46mDlof0gi/ja0n3surTj+1IaILNsrLxtsGXrC7eVHzY5YbVaBfvv7u4urJLju+XsYPakoNfxsWuzeJMXcLE65e2zPHxUepI6tshXJ8GKY44gHcFpKjLP8+1/T+KpmtlHLdkdX2nX0mOl50unA0BiWzsAYW+Yf/zjH/iv//qvsHERVbB6v1byefVT7WKFgBc52Id/9njaACBZL56miUYQvktmta2sFyyNgUGzbrLK3ifkkHVfHmDHwKqdwnbpFhd6rV3iyPfK9ft9fP78GbPZDOPxGNvtNvHynrySymtTnsG3L8XUuqdu+dtqA9J3mTvWhtnV9WoveIFprXiMcVlqxStHz9lr83hxWdexPEYB2E7dOpi03X7Z+3o8Hof3iFxeXmI4HIbXzSrwdEouawCl5Q/G6px1PC1sFSNbJx5THul047OvtrMelDJGQzExZnkqxjYmRip9s6SelRT2tz7bfqc9n2V4O34BX/eP3mw2+P333/H+/fuwWs4OGPLPbgHsXWfbnebR23amDcg8EjPNVmS9Ytd9FxB6D7YPjwWQPW9Tr/VUUqwcS3lHrgdKnee0nRcbTGqGcG/r29tbVKvVsLPYzc1N2D8aSGZEM6STx059ajzQ8ntfKReTwjEtllV2Fu2dyqVSUNG+2+0SbybiMe3s5wjRkPIC9yn3emqfcT+2ndvZLZfLsP6D+wRyI3OVCrQF7ZSckuVTzMzReqVpnizexuxK1sUrPzYgVCVbTZlFe2+crtLAM1IBP7PDxguzVEcedWGfkTZilfIGumPSgQOOOX/cmZ95gLpDgoZy0sDhmRH7UKyu+9yXVifgsRAixdRyXtp7Lxq7MztVjDJOR7QNrtrjaVIpLUctDUh2oGgZsbKyHB0th87JeDxOHOOiJL5zRT1pHcBq31keaD09wMbsxjQA2FBJlq0YK8d7v6E6ITYK8uySUBkYszfsYiHg8aL5GHPz2Eh5zseYaFWPJ4Xzlgskl4lqsi+Q3AbDxh3zmiBWy2RJT6+OMfDt29bYBIVKRD0GJAd2Fu39qlnmypGsavWkIG0o3m8rl6Ue81CMGd41+ty08yzHk1QKQraffPHe9M7facsQyDMvmzqNPzH7Lese740FsWd6sUIOMh1wrHfe2DDwjTYh8DWbVr+tFExr4LcA0JMEMSBpfe393rUx6aLH1fZTCa+Z0WnSSQevHbB5BoRXL49iIIuFUCz4PE3h2bl63T6ZNE9a6GRVhXrACkRrJ7Jy/J8W8/KeG7suTQJYJtpAuwVLGghVwrMsHXyqeu1bUT3b0rZPy9X/SrGBnUeaxa7znuWpWpLn4WvslCZKXvqm9H4ao7HKeqRg9NRcmu2Tdq1Xh5hNZIGngInZPfoqCKpiAsJbhqnqOCbBLPjsQI4BJg/fPD7ENMVut3OlogdgK4B4f6FQSJgo30UScof4PFLJMs9KRmvveMHstAak2UixEWzVoJIFg16vDCaT7ct90rxC65jY56aB0yPb9jQ+eNfnpSxtoYNW7UPyhO+ZyUO5Qcj0I3qCtlLWNlRHhUDbZwenvIb4UzrBdrKts0o+He1sgwKSx7wBWigU3HezeHXNsmfzDLqs63jeG3R56mZ/W7tQpd9qtYpKckt7rTu2xI16bGPSRrKdEfCOe/cAXxmc9kJpUl5JQCbm6RAAqRLRa1OamvTaaK/1bDV7X5aksw6jlp3Wbr3POiTAYzOGr27jyx+fXR0r4GzlrcGeRmpb8T7vw3J5rUee4a/ndMR6cUG12bypRVuubWdsDY0dUNbejNE+EoqUJinT2mIdnLRgPu/1+AZ8BeN2m3zl27NLwn0pb6BSG28ZkcUYIDsUEJNS/O95q/o/dv7/FYotONfB4gHVEyL2uJIX5iIwrd2sr3zLQ4Xd/6vcfaH/39Dea0xe6IWem15A+EI/nF5A+EI/nF5A+EI/nF5A+EI/nF5A+EI/nF5A+EI/nF5A+EI/nF5A+EI/nP4/PpZbjW36EDwAAAAASUVORK5CYII=\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -534,17 +535,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 25: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0132]\n",
-      "Epoch 26: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0125]\n",
-      "Epoch 27: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0119]\n",
-      "Epoch 28: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.012]\n",
-      "Epoch 29: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0125]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.35it/s]\n"
+      "Epoch 25: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0109]\n",
+      "Epoch 26: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0115]\n",
+      "Epoch 27: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0116]\n",
+      "Epoch 28: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0103]\n",
+      "Epoch 29: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0108]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 72.30it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
+      "image/png": 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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -556,17 +557,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 30: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0127]\n",
-      "Epoch 31: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0119]\n",
-      "Epoch 32: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0121]\n",
-      "Epoch 33: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0115]\n",
-      "Epoch 34: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.012]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.99it/s]\n"
+      "Epoch 30: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0111]\n",
+      "Epoch 31: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0101]\n",
+      "Epoch 32: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0106]\n",
+      "Epoch 33: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0107]\n",
+      "Epoch 34: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0109]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 74.68it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -578,17 +579,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 35: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0121]\n",
-      "Epoch 36: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0115]\n",
-      "Epoch 37: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.012]\n",
-      "Epoch 38: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0122]\n",
-      "Epoch 39: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0112]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.77it/s]\n"
+      "Epoch 35: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0109]\n",
+      "Epoch 36: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0102]\n",
+      "Epoch 37: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0105]\n",
+      "Epoch 38: 100%|█████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.00989]\n",
+      "Epoch 39: 100%|██████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0103]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 72.96it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -600,17 +601,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 40: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0113]\n",
-      "Epoch 41: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0113]\n",
-      "Epoch 42: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0118]\n",
-      "Epoch 43: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0119]\n",
-      "Epoch 44: 100%|██████████| 63/63 [00:38<00:00,  1.64it/s, loss=0.0113]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.69it/s]\n"
+      "Epoch 40: 100%|███████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.011]\n",
+      "Epoch 41: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0105]\n",
+      "Epoch 42: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0105]\n",
+      "Epoch 43: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0105]\n",
+      "Epoch 44: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0101]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 71.74it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -622,17 +623,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 45: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0112]\n",
-      "Epoch 46: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0106]\n",
-      "Epoch 47: 100%|██████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.0102]\n",
-      "Epoch 48: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0113]\n",
-      "Epoch 49: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0114]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.84it/s]\n"
+      "Epoch 45: 100%|█████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.00984]\n",
+      "Epoch 46: 100%|█████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.00985]\n",
+      "Epoch 47: 100%|█████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.00913]\n",
+      "Epoch 48: 100%|█████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.00973]\n",
+      "Epoch 49: 100%|█████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.00984]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 72.44it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -644,17 +645,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 50: 100%|███████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.011]\n",
-      "Epoch 51: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0111]\n",
-      "Epoch 52: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0109]\n",
-      "Epoch 53: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0109]\n",
-      "Epoch 54: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0107]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 69.07it/s]\n"
+      "Epoch 50: 100%|█████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.00967]\n",
+      "Epoch 51: 100%|█████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.00993]\n",
+      "Epoch 52: 100%|█████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.00998]\n",
+      "Epoch 53: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0101]\n",
+      "Epoch 54: 100%|████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.01]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 74.17it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -666,17 +667,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 55: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0111]\n",
-      "Epoch 56: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0113]\n",
-      "Epoch 57: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0107]\n",
-      "Epoch 58: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.011]\n",
-      "Epoch 59: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0107]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.97it/s]\n"
+      "Epoch 55: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0102]\n",
+      "Epoch 56: 100%|██████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0103]\n",
+      "Epoch 57: 100%|█████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.00881]\n",
+      "Epoch 58: 100%|█████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.00952]\n",
+      "Epoch 59: 100%|█████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.00885]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 72.40it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -688,17 +689,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 60: 100%|█████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.00995]\n",
-      "Epoch 61: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0105]\n",
-      "Epoch 62: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0103]\n",
-      "Epoch 63: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0103]\n",
-      "Epoch 64: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.011]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 68.43it/s]\n"
+      "Epoch 60: 100%|█████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.00897]\n",
+      "Epoch 61: 100%|█████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.00899]\n",
+      "Epoch 62: 100%|█████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.00957]\n",
+      "Epoch 63: 100%|█████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.00976]\n",
+      "Epoch 64: 100%|█████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.00967]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 74.57it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -710,17 +711,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 65: 100%|██████████| 63/63 [00:37<00:00,  1.68it/s, loss=0.0108]\n",
-      "Epoch 66: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0104]\n",
-      "Epoch 67: 100%|█████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.00969]\n",
-      "Epoch 68: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0108]\n",
-      "Epoch 69: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0102]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.69it/s]\n"
+      "Epoch 65: 100%|█████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.00951]\n",
+      "Epoch 66: 100%|██████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.0102]\n",
+      "Epoch 67: 100%|█████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.00983]\n",
+      "Epoch 68: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0087]\n",
+      "Epoch 69: 100%|█████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.00939]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 74.47it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -732,17 +733,17 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Epoch 70: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0101]\n",
-      "Epoch 71: 100%|██████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.0106]\n",
-      "Epoch 72: 100%|██████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.0104]\n",
-      "Epoch 73: 100%|███████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.011]\n",
-      "Epoch 74: 100%|████████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.01]\n",
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.73it/s]\n"
+      "Epoch 70: 100%|█████████| 63/63 [00:37<00:00,  1.67it/s, loss=0.00935]\n",
+      "Epoch 71: 100%|█████████| 63/63 [00:37<00:00,  1.66it/s, loss=0.00897]\n",
+      "Epoch 72: 100%|█████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.00981]\n",
+      "Epoch 73: 100%|█████████| 63/63 [00:38<00:00,  1.65it/s, loss=0.00908]\n",
+      "Epoch 74: 100%|█████████| 63/63 [00:38<00:00,  1.66it/s, loss=0.00885]\n",
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 73.58it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 200x200 with 1 Axes>"
       ]
@@ -754,7 +755,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "train completed, total time: 3098.574437856674.\n"
+      "train completed, total time: 3079.6518034934998.\n"
      ]
     }
    ],
@@ -764,6 +765,7 @@
     "epoch_loss_list = []\n",
     "val_epoch_loss_list = []\n",
     "\n",
+    "scaler = GradScaler()\n",
     "total_start = time.time()\n",
     "for epoch in range(n_epochs):\n",
     "    model.train()\n",
@@ -774,16 +776,19 @@
     "        images = batch[\"image\"].to(device)\n",
     "        optimizer.zero_grad(set_to_none=True)\n",
     "\n",
-    "        # Generate random noise\n",
-    "        noise = torch.randn_like(images).to(device)\n",
+    "        with autocast(enabled=True):\n",
+    "            # Generate random noise\n",
+    "            noise = torch.randn_like(images).to(device)\n",
+    "\n",
+    "            # Get model prediction\n",
+    "            noise_pred = inferer(inputs=images, diffusion_model=model, noise=noise)\n",
     "\n",
-    "        # Get model prediction\n",
-    "        noise_pred = inferer(inputs=images, diffusion_model=model, noise=noise)\n",
+    "            loss = F.mse_loss(noise_pred.float(), noise.float())\n",
     "\n",
-    "        loss = F.mse_loss(noise_pred.float(), noise.float())\n",
+    "        scaler.scale(loss).backward()\n",
+    "        scaler.step(optimizer)\n",
+    "        scaler.update()\n",
     "\n",
-    "        loss.backward()\n",
-    "        optimizer.step()\n",
     "        epoch_loss += loss.item()\n",
     "\n",
     "        progress_bar.set_postfix(\n",
@@ -798,12 +803,11 @@
     "        val_epoch_loss = 0\n",
     "        for step, batch in enumerate(val_loader):\n",
     "            images = batch[\"image\"].to(device)\n",
-    "            timesteps = torch.randint(0, scheduler.num_train_timesteps, (images.shape[0],), device=device).long()\n",
-    "            noise = torch.randn_like(images).to(device)\n",
     "            with torch.no_grad():\n",
-    "                # Get model prediction\n",
-    "                noise_pred = inferer(inputs=images, diffusion_model=model, noise=noise)\n",
-    "                val_loss = F.l1_loss(noise_pred.float(), noise.float())\n",
+    "                with autocast(enabled=True):\n",
+    "                    noise = torch.randn_like(images).to(device)\n",
+    "                    noise_pred = inferer(inputs=images, diffusion_model=model, noise=noise)\n",
+    "                    val_loss = F.mse_loss(noise_pred.float(), noise.float())\n",
     "\n",
     "            val_epoch_loss += val_loss.item()\n",
     "            progress_bar.set_postfix(\n",
@@ -817,7 +821,8 @@
     "        noise = torch.randn((1, 1, 64, 64))\n",
     "        noise = noise.to(device)\n",
     "        scheduler.set_timesteps(num_inference_steps=1000)\n",
-    "        image = inferer.sample(input_noise=noise, diffusion_model=model, scheduler=scheduler)\n",
+    "        with autocast(enabled=True):\n",
+    "            image = inferer.sample(input_noise=noise, diffusion_model=model, scheduler=scheduler)\n",
     "\n",
     "        plt.figure(figsize=(2, 2))\n",
     "        plt.imshow(image[0, 0].cpu(), vmin=0, vmax=1, cmap=\"gray\")\n",
@@ -849,7 +854,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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iqnVJSUnlhgtb48ePlydo6Nq1KxYuXIh58+bh2LFjGDp0KFq0aAG1Wo0bN27IXRV69+6NV155xe44L730Ep599lnk5uZi7NixaN68OQRBwLVr16BUKrFkyRLExMRg5cqVMBgMeOaZZxAeHo74+HhERkY6vwLqyEsvvYQjR44gNTUVS5YswfLly9GsWTPcuHEDeXl5eOGFFyBJkjylcHVMmjQJ4eHheOedd5Camoq3334bCxYsQEhICAICAnD79m05/CqVSowbNw6vvvpqqVbMrl27YsCAAdi9eze2bt2KPXv2oEWLFtDpdEhNTUWnTp3w17/+FRMmTKhRnQDmVu+IiAhcuXIFR44cKTU9cEnTpk1Damoqvv76a3z11Vf47rvv0KJFC+j1ety8eVNunZ0+fTqGDRsm79e7d28888wzWLFiBb788kt8/fXXcr3k5OTIw+P5+Phg6dKldt9CEFHtYdglolpXVFQkT6NakZJDgY0ZMwZdu3bFp59+ioMHD+L69eswGAxo3LgxevbsiQceeADDhg0rNUzXwIEDsXr1anz88cc4efIkbty4gaCgIIwaNQpTpkyRZzZ7++23ER8fj5s3b0KSJLebMMFRISEh+P7777F8+XLs3LkTaWlpyM7Oxt13343Jkyejb9++WLZsGYCaDZk2ePBg9OvXD5s2bcKePXtw+vRppKenIz09HX5+foiJiUHPnj3x4IMPonXr1uUeJz4+HitXrsSWLVtw9epVuaV05syZmDx5Mi5evFjtMpY0atQofPTRRwDMrcphYWHlbqtQKDB//nwMHz4c33zzDX7//Xdcu3YNgiDIXWwee+wx3H333aX2nT17NgYOHIgNGzbg4MGDSEtLw61bt+Dj44O77roLvXv3xhNPPOF2M9EReTJBqunYLkREVG8sWrQIa9asgZ+fnzxdLhGRJ2OfXSIiDyJJUoVDdllbS1u0aFFXRSIicimGXSIiD/Hqq68iJiYG48aNK3OM2OvXr+PQoUMAgJ49e9Z18YiIXIJhl4jIQ3Tr1g06nQ6XL1/Ga6+9ZjdKQmJiIp577jkYDAZ4eXnJs4kREXk69tklIvIQkiThb3/7G9atWwfAPIVw8+bNYTQa5bFsNRoNFi9eLI89S0Tk6Rh2iYg8zPbt2/Hdd9/h1KlTyMzMhEajQWhoKHr06IEJEyagbdu2ri4iEVGdYdglIiIiIo/FPrtERERE5LE4qUQZbt0qf9ie6lAoBAQF+SIjIx+iyIb0yrC+HMP6cgzry3GsM8ewvhzD+nIM66tYSIh/lbZjy24dUCgECIIAhaL6MxY1JKwvx7C+HMP6chzrzDGsL8ewvhzD+nIcwy4REREReSyGXSIiIiLyWAy7REREROSxGHaJiIiIyGMx7BIRERGRx2LYJSIiIiKPxbBLRERERB6LYZeIiIiIPBbDLhERERF5LIZdIiIiIvJYDLtERERE5LEYdomIiIjIYzHsEhEREZHHYtglIiIiIo/FsEtEREREHothl4iIiIg8lsrVBWjojl+8jXV7EjHg7uYYdE9LVxeHiIiIyvDOO29h8+afqrTt3/72JoYPH1Xjc/bt2w13330P4uM/rvGxGjKGXRfbeuQKrt7Mw3e7LiE2pgUEQXB1kYiIiKiEKVOextixj9gtmzZtAlq3boO//32+3fKwsOZOOecnn3wGHx8fpxyrIWPYdTFJMj8W6k0wGEVo1ErXFoiIiIhKCQtrXmaI9fLSokOHjrVyzto6bkPDPrsu5u1VfL2hKzK6sCRERETkDKtWrUTfvt3w228JmDPnBQwe3Af79++V12/e/BOmT5+M++7rh8GD++Dxx8fi44+Xo6Ag3+44fft2w/PPP2133J4978GpU6ewZs0nePTRBzFoUB888sgDWL36Y5hMpjp7j/UJW3ZdzC7s6k1o5MKyEBERkfN8/PFy3HNPN0yZ8jRatDDfl/Ptt19h2bKlGDhwMKZOnQ61Wo19+/bgs89W48qVZCxYsLjS47733nvw8fHDrFl/hSAo8Pnna7B69ccICWmKUaMerOV3Vf8w7LqYt1dxtwW27BIREXmOgIBGePrpGXbLMjMz0KtXH7z11jtQqcwxLCamK44f/x27d/+KgoKCSvvpiqKIhQuXwGgUAQBNm4ZiwoRHsWvXrwy7ZWDYdTHblt0Chl0iIqqnjp69iQ17E1God/yrdIVCgChKtVCqYlqNEmP6RaJbh6a1eh5bPXv2LrVs+vTnyty2VatWOHv2T6Sl3UCbNpEVHnf48OF2r8PDIwAAOTlZ1Suoh2PYdTEf224MhQy7RERUP205nIzr6QWuLkaFNh++UqdhNzi4SallGRnp+PrrL3DgwF6kpaVBp7OvM0kSKz1uaGio3Wu1Wg0AtX7BUF8x7LqY1q7PLsMuERHVT8N6tMJ6N2/ZHdYjolbPUZK1m4JVUVEhnn12Kq5fv4aHH34MPXv2RkBAIygUAj75ZIXdTWwV4TCljmHYdTH7Pru8i5KIiOqnbh2aVqvVVKVSIDDQF5mZ+XIfVE+VkHAUqakpGDduPF54YbbdOp1O56JSeT4OPeZiPhx6jIiIqEGwDg0WGBhot/zUqZM4fvx3u23Iediy62JaDcMuERFRQxAd3Qne3j5Yt24twsNbITi4Cf744xg2b/4JY8c+gm+//QpbtmyCRuOFVq1au7q4HoNh18XYsktERNQwBAUFY9Gipfj3vz/EwoVvQav1Rteu3fCvfy2HSqXCb78dw7p136KgoACvvvq6q4vrMQRJknjrXgm3buU69XgV9UdKzy7Ey/8+AADo1j4EM8Z0cuq566OG1H/LGVhfjmF9OY515hjWl2NYX45hfRULCfGv0nbss+tiJWdQIyIiIiLnYdh1Ma2GM6gRERER1RaGXRdTKAQ58DLsEhERETkXw64bsHZl4HTBRERERM7FsOsGrGG3kJNKEBERETkVw64bsM6iVmQwwSQ27DsriYiIiJyJYdcN2I3IwNZdIiIiIqdh2HUD3jazqBWy3y4RERGR0zDsugHbll3epEZERETkPAy7boBTBhMRERHVDrcOu2vXrsXw4cMRHR2Nfv36YfHixTAYDOVun5mZibfeeguDBw9GdHQ0Bg0ahOXLl0Ov19dhqR1nvUEN4CxqRERERM6kqnwT19iwYQPmzZuHuXPnYvDgwTh37hzmzZuHgoICzJ8/v9T2kiTh2WefRUZGBhYsWICWLVvixIkT+Pvf/4709HTMmzfPBe+iarRs2SUiIiKqFW7bshsfH48RI0Zg0qRJCA8Px5AhQzBz5kx8++23SEtLK7V9YmIifv/9d8yYMQO9evVCeHg4RowYgdGjR+OHH35wwTuoOnZjICIiIqodbhl2L1++jKtXr2LAgAF2y/v37w9RFLF3795y91Uo7N+SRqOplTI6kzfDLhEREVGtcMuwm5SUBACIiIiwWx4WFga1Wo3ExMRS+7Rt2xY9evTAJ598gpSUFADA6dOnsWnTJowfP772C10D3hqbPrscZ5eIiMitvPrqbPTt2w1nz56pcLsLF86hb99u+OtfX6zSca9fv4a+fbvhnXfekpeNGzcK48aNqtL+I0YMrvK2VfHbbwno27cbVq1a6bRjugO37LObl5cHAPD19bVbLggCfH195fUlLV++HC+++CIGDx4MjUYDvV6Pxx9/HC+99JJD51coBCgUQvUKXwalUmH3WJKfb3Hrc6HBBJXKLa9B6kxl9UX2WF+OYX05jnXmGNaXY+pDfT388KPYv38vNm5ch+jo8u8B2rhxPQDgkUfGV+n/cut7FgRB3v6f//wXAJS7v319CRVuW5G8vFzcf/8gLFv2b3Tt2g0AcNddd2HNmv+hSZMQj8oibhl2q0OSJLz88su4cuUKli1bhoiICJw4cQJLly5FQEAAZs+eXeVjBQX5QhCcF3atAgK8y1yuM0nyc5MIBAb6lrldQ1NefVHZWF+OYX05jnXmGNaXY9y5vuLihqB169bYvn0r3nzz7/Dz8yu1TX5+Pn75ZTMiIiIwfPjQKuWI/Hzze/byUsn/93fvfneVyhQQ4A1BMIfe6uSGY8cOwmQywd9fK+8fGOiLli2bOnwsd+eWYTcgIAAASrXgSpKE/Px8eb2tXbt24ddff8UXX3yBbt3MVyh33nknCgsLsWjRIjz++OMIDQ2t0vkzMvKd3rIbEOCNnBwdTCax1HpDYfFwatl5hcjMzHfaueujyuqL7LG+HMP6chzrzDGsL8fUl/oaM2YcPvjgn/jqq28xbtyjpdZv2PA98vPzMXXqdNy4kY4vvvgcv/yyBdeupcLLywstWrTEQw89jAceGCPvk52tAwAUFRnl//sffHCE5Xg/y9udOfMnli37AH/+eRpqtQrdu3fHCy/MhiQBJpNolxsuXbqITz9djaNHjyA3NweBgUHo2PEuTJs2HXfcEQUAePvtN7Fp048AgAkTJgAA1q37CdevX8Nzzz2NqVOfxlNPPSMf848/fsenn67G6dMnUVBQgMDAINx7bw9MmzYdYWHN5e0efHAE/P39sWTJ+1i27AP8/vsx6PUGREZG4tlnX5BbkJ2lqiHfLcNuZGQkACA5ORkxMTHy8pSUFBgMBrRr167UPpcuXQIAREVF2S1v06YNRFHE1atXqxx2RVGCKEqVb+ggk0mE0Vj6H7La5qubAp2hzG0aovLqi8rG+nIM68txrDPHsL4c4+71df/9I7FixUdYv/57PPjgw6XWr1v3PbRaLeLiRmLevNexb99uTJgwBffe2xOFhYX45psv8e67/0BhYRHGjn0EAORwL0lSqfdufX3zZhqee246tFotZs58Ca1aReDq1SS8/PIc6PV6eHt7y9veuHEd06dPhZ+fH154YTbCwprj6tUrWLEiHjNmPI1PP/0KTZuGYvLkp6BUqvDjj+vx17++hg4d7kRgYLB8z5MoFpfn0KEDePXV2bjjjvaYPfsVhIQ0xeXLifjkkxU4dOgg/vvfLxEYGCSXOz8/H7Nnv4i4uOF46KFHkJp6FfHx/8Krr87BN99sQKNGjZ37i6kCtwy74eHhiIyMxM6dO/Hggw/Ky3fs2AGVSoV+/fqV2qd5c/OVxcWLF3HPPffIy603s7Vo0aJ2C10DapUCKqUCRpOIAt6gRkRE9dBvN0/gp8RfUGQqcnhfhUKolUYmW15KL4yMHIp7mnau1v5+fn4YOnQYfvhhHU6ePI5OnbrI686cOY3z589i1KgH4eWlgUqlwiOPPI6nnnpW3uauuzphxIjB2Lz5JznsVsX69d+hoCAfr7/+JgYMGASVSoEhQwZCpfLCggXz0ahRI3nbq1eT0bnz3Rg79hH06NELANCpUxfodDp88MES7N27G2PHPoKwsOZo0qQJACAiohU6dOhY7vnj4/8FrVaL99//EAEB5nPdffc9aNw4EH//+6v45psv8cwzz8vbX7uWitdffwvDho0EAMTEdEVycjK++upzJCQcweDBQ6v83p3FLcMuAMycOROzZs3CmjVrMHToUJw5cwYfffQRJkyYgODgYJw4cQKvvPIKFixYgG7duiE2Nhbh4eF444038Prrr6Nly5b4888/sXLlSvTt2xdhYWGufksV8vFSIqdARKGeQ48REVH9sz15N9IKbrq6GBXafmV3tcMuAIwd+wh++GEdNmz43i7s/vDDOgDAQw89Ai8vLf7xj0Wl9vXz80NwcBPcuHHdoXOePHkcgiCgR4/edstjYwfjnXfetlvWvXtPdO/es9QxWrVqDQBIS3Ps3DdvpuHy5UT07x8rB12rPn36Q6lU4tixo3bLBUHAoEFD7Ja1bBkOAMjOznbo/M7itmE3Li4OS5YswcqVK7F06VI0adIEEydOxIwZMwAAOp0OSUlJKCgoAAB4e3tjzZo1+Oc//4lZs2YhLy8PwcHBGDFiBGbNmuXCd1I1Wi8VcgoMHGeXiIjqpSGtBrh9y+6QiAGVb1iByMh2uPvue7Bz5w7MnPkSAgIaIT8/Dzt2/IJOnbrIfWLPnz+L7777BseOHUVmZgb0er18DNuW2KpIT78NX19faLVau+W+vn7w8fGxWyZJEjZt+hFbtvyMpKRLyMnJgSgWd49wtI5v3jRfvDRtWrobqFqtRuPGgbh9+5bdcn//AHh5aUttay6fa7qpuG3YBYDRo0dj9OjRZa7r0aMHzp07Z7csPDwc//d//1cXRXM668QSuiITJEmqldEgiIiIass9TTtXq9VUpTKPJpCZme/WfXatHnroEfzxx1xs2vQjxo9/Alu2bIJOp5O7Jly8eAHPPDMVXl5emDRpKjp06CiH0r/+dSaMRkNFhy9FqiCflgyvH3+8HJ9/vgZdusRg9uxX5fkJzp49g8WLFzj2RgGbLFJ+IUrmFXeML24ddhsS65TBoiRBbxDhZTPRBBEREbmH/v0HokmTEPz880aMH/8Efv55I4KDgzFw4GAAwJYtP0OvL8Kbby7AgAGx8n5GoxG5uTnw9nZsiLXAwECkpl5FUVERvLy85OVZWZnQ6QrsWoo3blyHxo0D8a9/LZdbUwFzAK+OZs2aAQDS0m6UWldUVISsrEx07HhXtY5dlzxnxOB6TmsTbgvYlYGIiMgtqVQqPPDAQ0hKSsSuXTtw/vxZjB79EFQqc6OVyWS+0TwwMNBuv2+++QJ6vV5eX1UdO0ZDkiQcPLjPbvmvv+4ota3JZIKfn59d0DUYDFi79iu7sgHFLbIVlSc4uAmiojogIeEosrKy7Nbt27cHJpOpVF9id8Sw6yasLbsA2G+XiIjIjY0ePQYqlQpLliyUw69V9+49AAD//vcyHD16GEePHsa7776NY8eOolu3e5GXl4dfftmMW7eqdjPfgw+OhUbjhX/+cxF+/nkjjh1LwMqVK/HNN1+WummsW7ceSEm5io8/Xo4TJ/7A9u1bMW3aBAwZcj8AICHhMI4f/x1GoxEhIebJIzZuXI/du38ts/UWAF54YTYMBj3++tcXsXPndvzxx29Yu/Zr/POf76Jly3CMGzfe4fqrawy7bsKbYZeIiKheCA5ugoEDByMnJxv9+8eiSZMQeV3v3n0xa9ZfkZmZiVdfnY1Fi/6BRo0a4d13/4knn5yM4OAmWLLkHSQkHKnSucLDI/DBB/Fo2TIcS5cuxiuvzMGxY8fwz3/+C40bN7bb9qWX5uK+++KwceN6vPTSC/jmmy8xZcpTePzxCRg37lFcv34Nb7wxF4WFhRg8eCi6dbsX+/btxrvv/qPcUSJiYroiPv5jNGrUGIsXv4OZM5/F11//D/fddz/+/e/VZc4m524ESaqo63PDdOtWrlOPV5XO9+v2JOKnA5cBAHMe7YLoNsFOLUN9Ut9uVnA11pdjWF+OY505hvXlGNaXY1hfxUJC/Ku0HVt23YR9NwZOLEFERETkDAy7bsLbq/gGNXZjICIiInIOhl03wT67RERERM7HsOsmGHaJiIiInI9h103Yhl2Os0tERETkHAy7bsI27BbyBjUiIiIip2DYdRPeGt6gRkRERORsDLtugt0YiIiIiJyPYddNaDVKCJbnbNklIiIicg6GXTchCAK0ltZdnZ59domIiIicgWHXjfhYJpZgyy4RERGRczDsuhFrv12GXSIiIiLnYNh1I9awazCKMJpEF5eGiIiIqP5j2HUjnEWNiIiIyLkYdt0Iwy4RERGRczHsuhH7sMsRGYiIiIhqimHXjXAWNSIiIiLnYth1I+zGQERERORcDLtuxC7s6hl2iYiIiGqKYdeNeHvZdmNgn10iIiKimmLYdSO2LbsF7MZAREREVGMMu27Eh312iYiIiJyKYdeN2LbsFjLsEhEREdUYw64b0bIbAxEREZFTMey6ER9OKkFERETkVAy7bkRrO6kEhx4jIiIiqjGGXTeiUiqgUZl/JbxBjYiIiKjmGHbdjPUmNYZdIiIioppj2HUzxWGXfXaJiIiIaoph181YZ1ErLDJClCQXl4aIiIiofmPYdTPWll0JQJGerbtERERENcGw62a8OYsaERERkdMw7LoZhl0iIiIi52HYdTPeGk4sQUREROQsDLtuxnqDGsApg4mIiIhqimHXzdhOGVzIWdSIiIiIaoRh181obcIuW3aJiIiIaoZh18348AY1IiIiIqdh2HUz9qMx8AY1IiIioppg2HUzWpsb1NiyS0RERFQzDLtuht0YiIiIiJyHYdfNcFIJIiIiIudh2HUzDLtEREREzsOw62Y0KgUUggCAN6gRERER1RTDrpsRBEGeRY0tu0REREQ1w7DrhqxdGXScQY2IiIioRhh23ZAcdtmyS0RERFQjDLtuyBp2jSYJBiP77RIRERFVF8OuG/LhLGpERERETsGw64Y4ixoRERGRczDsuiHbsXYLGHaJiIiIqo1h1w3ZdmMoZNglIiIiqjaGXTdk37LLPrtERERE1cWw64a8NeyzS0REROQMDLtuyNtuNAaGXSIiIqLqYth1Q3Zhl7OoEREREVUbw64bYssuERERkXMw7Lohhl0iIiIi52DYdUPedpNKcDQGIiIioupi2HVDbNklIiIicg6GXTfkrWHYJSIiInIGhl03pFAI8LKMtavTsxsDERERUXUx7Lop65TBbNklIiIiqj6GXTeltbTsFjDsEhEREVUbw66bsrbsFulNEEXJxaUhIiIiqp8Ydt2U7YgMhZxFjYiIiKhaGHbdlNYm7LIrAxEREVH1MOy6KR9OLEFERERUYwy7booTSxARERHVHMOum2LYJSIiIqo5hl03xVnUiIiIiGqOYddN2bXschY1IiIiompx67C7du1aDB8+HNHR0ejXrx8WL14Mg8FQ4T6HDh3Co48+is6dO6Nv375YsGAB9Hp9HZXYediNgYiIiKjm3DbsbtiwAfPmzcMjjzyCzZs3480338SGDRuwYMGCcvc5fvw4pk2bht69e+Pnn3/GP/7xD/z444/4xz/+UYcldw5vu9EYGHaJiIiIqkNV+SauER8fjxEjRmDSpEkAgPDwcNy+fRvz58/HjBkzEBoaWmqf999/H/3798fMmTPlfeLj42E01r+wyJZdIiIioppzy5bdy5cv4+rVqxgwYIDd8v79+0MURezdu7fUPllZWThy5AhGjhxpt7x79+7o1atXrZa3Nvgw7BIRERHVmFuG3aSkJABARESE3fKwsDCo1WokJiaW2ufcuXMQRRH+/v6YM2cO+vTpg9jYWPzrX/+qtJ+vO9LahV3eoEZERERUHW7ZjSEvLw8A4Ovra7dcEAT4+vrK622lp6cDABYsWIDJkyfjqaeewpEjR/Dee+8hJycHb7zxRpXPr1AIUCiEGrwDe0qlwu6xKvx91fJznd4Ilcotr0tqRXXqqyFjfTmG9eU41pljWF+OYX05hvXlOLcMu9Vhbb0dPnw4xo8fDwC48847cf36dXz++ed4/vnnERQUVKVjBQX5QhCcF3atAgK8HdpepVTAaBJhMEoIDPStfAcP42h9NXSsL8ewvhzHOnMM68sxrC/HsL6qzi3DbkBAAACUasGVJAn5+fnyelv+/v4AgOjoaLvl3bp1w5o1a3DhwgX06NGjSufPyMh3estuQIA3cnJ0MJnEKu/n7aVEboGI3AI9MjPznVYed1fd+mqoWF+OYX05jnXmGNaXY1hfjmF9FatqQ6Bbht3IyEgAQHJyMmJiYuTlKSkpMBgMaNeuXal9WrduDQDIzs62Wy5JEgDAz8+vyucXRQmiKDla7EqZTCKMRgfCrkaF3AIDCgoNDu3nKRytr4aO9eUY1pfjWGeOYX05hvXlGNZX1bllh4/w8HBERkZi586ddst37NgBlUqFfv36ldonMjIS4eHh2LZtm93yhIQEeHl5yWG4PrEOP1aoN8mhnYiIiIiqzi3DLgDMnDkTW7duxZo1a5Camort27fjo48+woQJExAcHIwTJ04gLi4OCQkJ8j6zZs3Cr7/+imXLluHq1atYu3YtvvrqK0ycOLHUzW71gXViCZMoQc+rNyIiIiKHuWU3BgCIi4vDkiVLsHLlSixduhRNmjTBxIkTMWPGDACATqdDUlISCgoK5H1GjhwJSZKwcuVKfPzxxwgODsbzzz+PadOmuept1EjJiSW81MoKtiYiIiKiktw27ALA6NGjMXr06DLX9ejRA+fOnSu1fNSoURg1alRtF61OlAy7jf28XFgaIiIiovrHbbsxUMmwy4kliIiIiBzFsOvGrH12AU4ZTERERFQdDLturGQ3BiIiIiJyDMOuG2PYJSIiIqoZhl035sOwS0RERFQjDLtuTKspDrsFDLtEREREDmPYdWO2LbuFeo7GQEREROQohl035q0tDrv5hQYXloSIiIiofmLYdWN+3mr5eb6O3RiIiIiIHMWw68Z8bVp283Rs2SUiIiJyFMOuG1MpFfLEErkMu0REREQOY9h1c75ac1eGfIZdIiIiIocx7Lo5a7/d/EIDRElycWmIiIiI6heGXTdnDbuSBBQU8iY1IiIiIkcw7Lo5+xEZ2JWBiIiIyBEMu27O1ybsckQGIiIiIscw7Lo5P4ZdIiIiompj2HVzDLtERERE1cew6+bYZ5eIiIio+hh23Zxdy24hwy4RERGRIxh23Zx9NwYOPUZERETkCIZdN+frrZKfs88uERERkWMYdt0c++wSERERVR/DrpvzUiuhUgoA2LJLRERE5CiGXTcnCII8sQTDLhEREZFjGHbrAT+GXSIiIqJqYditB/y05rBrMIooMphcXBoiIiKi+oNhtx7gTWpERERE1cOwWw/4cspgIiIiomph2K0H/Bh2iYiIiKqFYbceYNglIiIiqh6G3XqAfXaJiIiIqodhtx5gyy4RERFR9TDs1gP2YdfowpIQERER1S8Mu/WAr7dKfs6WXSIiIqKqY9itB+z67BYy7BIRERFVFcNuPeCrVUOwPGfLLhEREVHVMezWAwqFAB+tuStDXgHDLhEREVFVMezWE9ZZ1NiyS0RERFR1DLv1hLXfbkGRESZRdHFpiIiIiOoHht16wv4mNQ4/RkRERFQVDLv1hK+Ws6gREREROYpht57gLGpEREREjmPYrSf8OLEEERERkcMYdusJtuwSEREROY5ht57w89HIz/N1vEGNiIiIqCoYdusJPy27MRARERE5qlbDbmZmJoxGtkI6gy+7MRARERE5rMZhd/fu3Xj++eftlh04cACxsbHo3bs3evbsiTVr1tT0NA2e3Ti7DLtEREREVaKqfJPyJSQk4LnnnoMgCBBFEQqFAjdv3sRzzz0HnU6Hjh07IiUlBUuWLEHr1q0RGxvrrHI3OLxBjYiIiMhxNWrZ/eyzz+Dt7Y3vv/8eCoX5UN988w10Oh1efPFFrFu3Dr/88gtCQ0Px9ddfO6XADZVGrYRGZa5jhl0iIiKiqqlR2D1x4gSGDh2KqKgoednOnTuh1WoxYcIEAEDjxo0xZMgQnDp1qmYlJbnfLsMuERERUdXUKOymp6ejVatW8uvs7GycOXMGXbt2hZ+fn7y8adOmyM7OrsmpCMVdGfJ0BkiS5OLSEBEREbm/GoVdjUaDvLw8+fX+/fshSRL69Oljt11eXh58fX1rcipCcdg1iRIK9SYXl4aIiIjI/dUo7LZt2xY7d+6E0WiEKIr47LPPIAhCqRvRjhw5ghYtWtSooGQ//BhHZCAiIiKqXI3C7siRI3HhwgUMHToUQ4YMwfHjx9G/f3+0adMGAFBQUIDFixfj+PHjGDJkiFMK3JDZjchQyLBLREREVJkaDT32xBNP4OLFi1i3bh2MRiM6deqERYsWyevT09OxZs0a3HnnnZg8eXKNC9vQ+XlzFjUiIiIiR9Qo7CoUCrz99tv429/+hvz8fAQHB9utDw8Px+uvv46HHnoI3t7eNSooAX5ajrVLRERE5IgahV0rrVYLrVZb5ronn3zSGacglOyzy2mYiYiIiCpT4+mC//zzTyxcuNBu2dmzZ/HEE08gJiYGI0aMwJYtW2p6GgJnUSMiIiJyVI3C7rlz5/DEE0/gyy+/hCiKAICcnBxMmTIFCQkJ0Gg0SExMxJw5c3Ds2DGnFLgh8/Nh2CUiIiJyRI3C7urVq2E0GrF8+XJ5uuC1a9ciIyMDjz/+OA4fPoytW7ciICAAn332mVMK3JD5cegxIiIiIofUKOwePXoUQ4cORf/+/eVl27Ztg0qlwvPPPw8AiIiIwNChQ/H777/XrKTEbgxEREREDqpR2L19+zbatWsnv87Pz8epU6fQpUsXBAUFyctbtGiBjIyMmpyKAHh7qSAI5ue5DLtERERElapR2FUqlSgqKpJfHzlyBEajsdR0wTqdjkOPOYFCEOBrGX6M3RiIiIiIKlejsNuqVSscPHhQfv3VV19BEAQMHDjQbruTJ08iNDS0JqciC2tXBnZjICIiIqpcjcbZHTp0KJYtW4bx48dDoVDg999/x913342OHTsCAEwmE7766iscPHgQU6ZMcUqBGzpr2C3Um2A0iVApazx6HBEREZHHqlHYnTp1Ko4dO4b9+/cDAMLCwrBkyRJ5/eXLl7FgwQI0b96cYddJSo7I0MjPy4WlISIiInJvNQq7Xl5eWLVqFS5fvoycnBx06NABGo1GXh8ZGYlJkyZh8uTJdjesUfX5ehf/yvIYdomIiIgq5JTpglu3bl3mckEQMHfuXGecgiw4/BgRERFR1Tkl7N64cQNbtmzBn3/+iczMTAiCgODgYERHR2P48OEIDAx0xmkIJcOu0YUlISIiInJ/NQ67//3vf7F06VIYjUZIkmS3bsOGDVi6dCnefvttjBw5sqanIgC+tn12C9myS0RERFSRGoXd3bt3Y9GiRfD29sYDDzyAzp07IygoCKIoIiMjA8eOHcPWrVsxd+5cREREoHPnzs4qd4Plp2U3BiIiIqKqqlHY/fzzz9GoUSN8++23aNWqVan148ePx1NPPYXHHnsMn3zyCZYtW1aT0xHYZ5eIiIjIETUapPXUqVO4//77ywy6VlFRUbj//vvx22+/1eRUZOHnw7BLREREVFU1Crt5eXlo1qxZpdu1bNkSWVlZNTkVWZQcZ5eIiIiIylejsBsQEICrV69Wut21a9cQEBBQk1ORBbsxEBEREVVdjcJuly5d8Msvv+DcuXPlbnP27Fls3rwZd999d01ORRYqpQJeGiUAhl0iIiKiytToBrXJkydj165dePjhhzFixAjExMTIM6Wlp6cjISEBW7duhclkwtSpUx0+/tq1a7FmzRpcuXIFgYGBGDlyJObMmQO1Wl3pvllZWRgxYgS8vLzw66+/Onxud+anVaNIb2LYJSIiIqpEjcLuvffei7fffhvvvPMO1q9fjw0bNtitlyQJ3t7eWLBgAbp27erQsTds2IB58+Zh7ty5GDx4MM6dO4d58+ahoKAA8+fPr3T/hQsXIisrC6GhoQ6dtz7w81YjPacQ+Trz2MaCILi6SERERERuqcaTSjz88MOIjY3Fpk2bcOrUKaSnp8szqHXq1AkjRoyo1gxq8fHxGDFiBCZNmgQACA8Px+3btzF//nzMmDGjwhC7Z88ebN26FaNHj8bhw4er+9bclp+3+dcmShJ0RUb4aCtv6SYiIiJqiJwyXXCTJk0wYcKEctfv2LED69evR3x8fJWOd/nyZVy9ehUvvvii3fL+/ftDFEXs3bsX48aNK3PfvLw8vPnmm3jhhReg0+mq/ibqEd8SN6kx7BIRERGVzSlhtzLJycnYsWNHlbdPSkoCAERERNgtDwsLg1qtRmJiYrn7Ll26FIGBgZg8eTKWL19erfIqFAIUCud1DVAqFXaPNRXgq5Gf6/QmqFTOOa67cHZ9eTrWl2NYX45jnTmG9eUY1pdjWF+Oq5Ow66i8vDwAgK+vr91yQRDg6+srry8pISEBa9euxbfffgulUlnt8wcF+dZKP9iAAG+nHKdJoE29KJUIDPQtf+N6zFn11VCwvhzD+nIc68wxrC/HsL4cw/qqOrcMu9VRVFSE119/HZMmTULHjh1rdKyMjHynt+wGBHgjJ0cHk0ms8fFUgiQ/v3ErF5nN/Gp8THfi7PrydKwvx7C+HMc6cwzryzGsL8ewvopVtbHPLcOudQKKki24kiQhPz+/zAkqPvzwQ6hUKrzwwgs1Pr8oShBFqfINHWQyiTAaa/7B9PYq/rXl5Omdckx35Kz6aihYX45hfTmOdeYY1pdjWF+OYX1VnVuG3cjISADmvr4xMTHy8pSUFBgMBrRr167UPps2bcL169ftthdFEZIkoWPHjpgxYwaef/752i98HeAsakRERERV45ZhNzw8HJGRkdi5cycefPBBefmOHTugUqnQr1+/UvusWrUKBoN98Pvyyy+xY8cOrFq1CsHBwbVd7DpjF3YLGXaJiIiIyuO2t/LNnDkTW7duxZo1a5Camort27fjo48+woQJExAcHIwTJ04gLi4OCQkJAIA2bdogKirK7ic4OBhqtVp+7ilsw24+W3aJiIiIyuVwy26vXr0cPklhYaHD+8TFxWHJkiVYuXIlli5diiZNmmDixImYMWMGAECn0yEpKQkFBQUOH7u+YzcGIiIioqpxOOxmZmZW60TVGcpr9OjRGD16dJnrevTogXPnzlW4/wsvvOCUG9bcjVajhFIhwCRKyCtg2CUiIiIqj8Nh15HJIah2CIIAX281cvL17LNLREREVAGHw26LFi1qoxzkID9r2GU3BiIiIqJyue0NalQxP635OkVvEGEwmlxcGiIiIiL3xLBbT/na3aRmdGFJiIiIiNwXw249xREZiIiIiCrHsFtPMewSERERVY5ht57ixBJERERElWPYrad82bJLREREVCmG3XqK3RiIiIiIKsewW08x7BIRERFVjmG3nvJln10iIiKiSjHs1lP+bNklIiIiqhTDbj3l61080zPDLhEREVHZGHbrKaVCAW8vc+Bl2CUiIiIqG8NuPebnzbBLREREVBGG3XrMOiJDQaERoii5uDRERERE7odhtx6zjsggASgoMrq2MERERERuiGG3HuNYu0REREQVY9itx/y9NfLznHy9C0tCRERE5J4YduuxoAAv+Xl6TqELS0JERETknhh267HgAK38PINhl4iIiKgUht16LLhRcdhNzylyYUmIiIiI3BPDbj0WZNOym57Nll0iIiKikhh267EAHzVUSvOvkN0YiIiIiEpj2K3HBEFAsOUmtds5hZAkTixBREREZItht56zdmUo0ps4sQQRERFRCQy79ZzdTWrst0tERERkh2G3nrMffowjMhARERHZYtit5zixBBEREVH5GHbruSa2w48x7BIRERHZYdit54IacRY1IiIiovIw7NZzQf423Rh4gxoRERGRHYbdek6tUqKRrwYAuzEQERERlcSw6wGsY+1m5+lhNIkuLg0RERGR+2DY9QDWWdQkABm5HH6MiIiIyIph1wPYTiyRwX67RERERDKGXQ8QxOHHiIiIiMrEsOsBghl2iYiIiMrEsOsB7KcMZtglIiIismLY9QC2fXbTc3iDGhEREZEVw64H8NWqoFGbf5WcWIKIiIioGMOuBxAEQe7KkJFTCEmSXFwiIiIiIvfAsOshrGFXbxSRpzO4uDRERERE7oFh10Nw+DEiIiKi0hh2PYTdTWrZvEmNiIiICGDY9RjWKYMBDj9GREREZMWw6yE4sQQRERFRaQy7HoJhl4iIiKg0hl0P0djfC4LlOcfaJSIiIjJj2PUQKqUCjf3N/XbZZ5eIiIjIjGHXg1i7MuQUGKA3mFxcGiIiIiLXY9j1IEG2IzLkcvgxIiIiIoZdD8Kb1IiIiIjsMex6ENuJJTJ4kxoRERERw64n4ZTBRERERPYYdj0IuzEQERER2WPY9SC2YTcjhzeoERERETHsehAfrQreXkoAnFiCiIiICGDY9TjWfrsZuYUQJcnFpSEiIiJyLYZdD2PtymA0ScjN17u4NERERESuxbDrYWz77d7mTWpERETUwDHsehi7WdR4kxoRERE1cAy7HsZ2YgnepEZEREQNHcOuh+FYu0RERETFGHY9jP1Yuwy7RERE1LAx7HqYxn5eUAgCALbsEhERETHsehiFQkCgv/kmNfbZJSIiooaOYdcDBVtGZMgvNKJQb3RxaYiIiIhch2HXA9mOyMDhx4iIiKghY9j1QEFVHJEhT5+PrKLsuigSERERkUuoXF0Acr6qDD+WrsvEwiMfwCSZ8GznyWgf1K6uikdERERUZ9iy64HsuzGUHXYLjAUoNBXCIBrwzfn1MImmuioeERERUZ1h2PVAdt0YyhmRoaVfc0Q2ag0ASCu4hT2pB+uiaERERER1imHXA1lHYwCA9HJuUBMEAePuGCW//jlpG/L0+bVeNiIiIqK6xLDrgbQaFXy15u7YFc2i1iogHD2adQUA6Iw6/Jy0rU7KR0RERFRXGHY9lPUmtczcIoiiVO52o9vGQaPUAAD2XTuEa3k36qR8RERERHWBYddDWfvtmkQJWXnlj7Xb2KsR7m81CAAgSiK+v/AjJKn8cExERERUn7h12F27di2GDx+O6Oho9OvXD4sXL4bBYCh3+4KCAixduhT3338/unTpgri4OKxYsaLCfTyVIxNLDArvhyBtIADgbOYFnEo/U6tlIyIiIqorbht2N2zYgHnz5uGRRx7B5s2b8eabb2LDhg1YsGBBufvMmTMH3333HV566SX8+OOPmDx5Mj788EPEx8fXYcndg+1Yu7dzdBVuq1GqMabdCPn1ugs/wShymmEiIiKq/9w27MbHx2PEiBGYNGkSwsPDMWTIEMycORPffvst0tLSSm1/6dIl7Ny5E6+88gqGDh2KiIgIPProo4iLi8OXX37pgnfgWkE2IzJUZcrgmJBOaNuoDQDgpu429qQcqLWyEREREdUVtwy7ly9fxtWrVzFgwAC75f3794coiti7d2+pfdq0aYN9+/ZhxIgRdstDQ0Oh0+kgimKtltnd2HZjqGjKYCtBEDAuahQECACATZe3I1efV2vlIyIiIqoLbhl2k5KSAAARERF2y8PCwqBWq5GYmFhqH4VCgZCQEGg0GnmZ0WjEnj170LlzZygUbvlWa01wFSaWKCnCvyV6hnUDAOiMhfgp6ZdaKRsRERFRXVG5ugBlycsztyj6+vraLRcEAb6+vvL6yixduhSJiYn47LPPHDq/QiFAoRAc2qciSqXC7rEuBDXSQqUUYDRJuJWlg0pVtXOPiRqG326eQJGpCPtTD2NQRB+08A+r5dLac0V91WesL8ewvhzHOnMM68sxrC/HsL4c55Zht6YkScLixYvx3//+F/Pnz0e3bt0c2j8oyBeC4LywaxUQ4O30Y1YkolkAElOzkZZRAK2PF7y9Kv91B8IXY+8ahi9PbIAECesTf8LfB8yslfqoTF3XV33H+nIM68txrDPHsL4cw/pyDOur6twy7AYEBABAqRZcSZKQn58vry+LwWDA3LlzsXXrVixZsgSjR492+PwZGflOb9kNCPBGTo4OJlPd9R2OaOqHxNRsiBJw/Gwa2kc0rtJ+vUN64BfvPbity8DJtHPYff4oujS9q3YLa8NV9VVfsb4cw/pyHOvMMawvx7C+HMP6KhYY6Fv5RnDTsBsZGQkASE5ORkxMjLw8JSUFBoMB7dq1K3M/SZLw6quvYteuXfjPf/6DXr16Vev8oihVOOtYdZlMIozGOgy7oX7y88TUbLRtXv5Fgi0BSjzYdgQ+OfU5AGDtuY2IanwH1Iq6/bjUdX3Vd6wvx7C+HMc6cwzryzGsL8ewvqrOLTt8hIeHIzIyEjt37rRbvmPHDqhUKvTr16/M/T766CPs2LGjRkHXk7Ru5i8/v3wjx6F97w6Jxh2NzRcdt3Tp2J2y36llIyIiIqoLbhl2AWDmzJnYunUr1qxZg9TUVGzfvh0fffQRJkyYgODgYJw4cQJxcXFISEgAAFy/fh0rVqzAE088gYiICNy6dcvuR6/Xu/gd1b0WTfygUpq7Y1y+kevQvoIgYOwdxUORbU7awaHIiIiIqN5xy24MABAXF4clS5Zg5cqVWLp0KZo0aYKJEydixowZAACdToekpCQUFBQAAA4dOgSDwYBPPvkEn3zySanjffbZZ+jRo0edvgdXU6sUaBHih+QbubiRXgBdkbFKN6lZhfu3QK+w7jhw/QgKTYX4MXErHu8wthZLTERERORcbht2AWD06NHl3mDWo0cPnDt3Tn49ZswYjBkzpq6KVm+0aeaP5Bu5kABcSctF+4hAh/Yf1fZ+/HbzOApNRThw7Qj6t+iFlv7Na6ewRERERE7mtt0YyDlahxXflOZoVwYACND4I671YACABAnfX/gRkuT8m/eIiIiIagPDrodrFVp8k1pyNcIuAAwM74sm2iAAwPmsSzh++7RTykZERERU2xh2PVyLEF+oLLOsJFUz7KoVKoy5Y6T8ev2Fn2AQjU4pHxEREVFtYtj1cCqlAuFNzePtpmWYb1Krji5N7kJU47YAgNuFGdh1dZ/TykhERERUWxh2GwDb8Xar25VBEASMixotD0W25fIO5OirdywiIiKiusKw2wDYTy5R/YDawi8MvZvfCwAoNBXhx0tba1w2IiIiotrEsNsA2I/I4NhMaiWNirwfWqUWAHDw+lFczU2t0fGIiIiIahPDbgPQvIkP1Crzr7omLbsA4K/xw7A2HIqMiIiI6geG3QZAqVAgwnKT2s1MHQoKDTU63sCWfRDiHQwAuJCViD9unapxGYmIiIhqA8NuA9G6WXFXhurepGalUqjwUDubocgu/gSDqWYBmoiIiKg2MOw2EK2cdJOaVacmHdE+sB0AIL0wEzs5FBkRERG5IYbdBqJ1mHPDriAIGHvHqOKhyJJ3ILuoZje/ERERETkbw24DERbsA43aepOac0JpC78w9G3REwBQZNLjx0QORUZERETuhWG3gTDfpGZu3b2VVYg8nXP62I5ocx+8VeahyA5dT8CV3BSnHJeIiIjIGRh2GxC7mdTSnDP7mb/GD8NbDwFgHorsu/MbORQZERERuQ2G3QbErt/udef1r+3fsjea+jQBAFzKvozfb5102rGJiIiIaoJhtwFp1cx2JjXntOwCZQ1F9jP0HIqMiIiI3ADDbgMSFuQDL7USQM3H2i0pOvhO3BkUBQDIKMzEr1f3OvX4RERERNXBsNuAKBQCIkLNM6ndznbeTWqAeSiyh9qNhEIwf6S2Jv+KrKJspx2fiIiIqDoYdhuY1nZdGZw7Lm5zv2bo29w8FJnepMfGS1ucenwiIiIiRzHsNjD2N6k5tysDYB2KzBsAcPjGMSTnXHX6OYiIiIiqimG3gWnt5GmDS/LT+GJEm/vk199d+JFDkREREZHLMOw2MKFBPvDSWG9Sq53pffu36IVQnxAAQGL2ZRy7ebxWzkNERERUGYbdBkYhCGgdam7dTc8pQk6+3unnUCqUdkORbbi4iUORERERkUsw7DZArWq5KwMARDe5Ex2D2gMAMouysOPK7lo5DxEREVFFGHYbINub1GqrKwMAjL2jeCiyX5J3cigyIiIiqnMMuw1Qm1qaSa2kZr6h6NeiFwBALxrww6XNtXYuIiIiorIw7DZAIYHe8PYy36RWm2EXMA9F5mMZiuzIjd+QlH2lVs9HREREZIthtwFSCAJaWW5Sy8wtQnZeUa2dy1ftgxFthsqvv7+wkUORERERUZ1h2G2gWofVTVcGAOjXoiea+TQFACTlXEFC2h+1ej4iIiIiK4bdBqqNTdg9mZheq+dSKpQYe8co+fWGS5ugNzl/yDMiIiKikhh2G6joNkFQq8y//sN/psFoEmv1fB2D2+Ou4A4AgKyibGzjUGRERERUBxh2GyhvLxXuiTLPcpZfaMTJS7XbugsAD7UrHopsW/IuZBZm1fo5iYiIqGFj2G3Aekc3k58fOHWj1s/XzLcpBrToDQAwcCgyIiIiqgMMuw1Yx9aBCPDVAACOX7qNPF3tT+k7vM0Q+Kp9AABH035HUnZyrZ+TiIiIGi6G3QZMqVCgZ8dQAIDRJOHo2Zu1fk4ftQ9G2gxFtvbCRohS7fYXJiIiooaLYbeBs+/KcL1OztmneQ+E+ZpDdnLOVQ5FRkRERLWGYbeBC2/qh5YhvgCAS6k5SMssqPVzlhyK7IdLm1HEociIiIioFjDsNnCCIKCXTevuwTq4UQ0A7gyKQnTwnQAsQ5El76qT8xIREVHDwrBL6NmxGQTB/PzAqRt1Np3vQ3eMhFJQAgC2X9mFjMLMOjkvERERNRwMu4RAfy90bBUIALidXYgLKdl1ct5QnxAMaGkdisyIDRc31cl5iYiIqOFg2CUAQO/oMPl5XYy5azWs9RD4qc19ho/dPI7E7Mt1dm4iIiLyfAy7BAC4JyoEXmpzl4KjZ2/CYDTVyXl91N4YGWkzFNl5DkVGREREzsOwSwAAL40SXdubpw/WFRnxx8Xanz7YqnfYvWjua75J7kpuCg5f/63Ozk1ERESejWGXZL1dMCoDUHoosvUXNqHQUFhn5yciIiLPxbBLsg4RgQj09wIAnExMR05+3Y192yHoDnRuchcAILsoBxvObq2zcxMREZHnYtglmUIhoOdd5pnNTKKEw2fS6vT8Y9oNl4ci+/HsdmxO3IHE7MswisY6LQcRERF5DpWrC0DupfddzbD50BUA5q4M93ULr7NzN/UJwcDwPthxZY9lKLLNAAC1QoU2Aa3QrnEbtGsciTaNIqBRauqsXERERFR/MeySnRYhfmgV6o/ktFxcvpGLa7fz0byJb52df1jrIUjJu4ZzGRflZQbRiPNZl3A+6xIAQCEo0Mo/3BJ+2yCyUWv4qL3rrIxERERUfzDsUim9opshOS0XAHDw9A2MHdC2zs7trdJidtfpKFTn49jl0zifkYiLWYlIt5ldTZREJOUkIyknGduu7IIAAS38wuSW33aN28Bf41dnZSYiIiL3xbBLpfToGIpvf70IUZJw4NQNjO7TBmpV3XXvFgQBzf1D4d3SDz2bdQcAZBRm4mJWkvyTVnBT3l6ChJS8a0jJu4ZdKfsBAKE+TeWW3zsaRyJQ27jOyk9ERETug2GXSmnkq0GnyCAcv5SOzNwibDmcjFF92ri0TEHaQNzbLBD3NrsHAJCjz8WlrMu4mJWIi1lJSM27DgmSvH1awU2kFdzE/muHAQDB2kC51bdt4zZo6t0EgiC45L0QERFR3WHYpTI9NKAtTiZmQJQk/HggGfd2DEVooI+riyUL0PgjpmknxDTtBAAoMOiQmH3Z0vKbiOTcFLuZ2NILM5F+4xgO3zgGAPDX+Mnh947GkQjzDYVC4OAkREREnoZhl8oU3tQPQ7uHY8uRKzCaRPzvl/OY80gXt20N9VF7I7rJnYhucicAoMikR1J2Mi5Zuj0k5STDYDOEWa4+D7/fPIHfb54w76/yRtvGreUAHO7XAkqF0iXvhYiIiJyHYZfKNbpvaxw5m4aMnCKcTsrA0bM3ce+doa4uVpV4KTXoEHQHOgTdAcA8osPV3BRczEzChexEJGZdRqGpSN6+wKjDydtncPL2GQCARqlBZEArOfy2DgiHWql2yXshIiKi6mPYpXJpNSr8ZUgUPlx3EgDw1Y4LiG4TDB9t/fvYqBUqRDZqjchGrTEUsTCJJqTmX7e56S0R+YYCeXu9SY+zmRdwNvMCAEAlKNEqIAKtAlpCo9RAJaigUiihUqjkH7Vg/1qlUEFtfV7GOpWgZOsxERFRLat/qYXqVExUCO5u1wR/XLyN7Dw91u9JxF+GRrm6WDWmVCgR4d8SEf4tMSi8H0RJRFrBLfmGt4tZScgqypa3N0omXMpOwqXsJKeWQ4BgE4CVUAk2AdnuRwm1YP/aHJhV0KjU8PXRQqcrgskkQoQESZIgQoQk2T8XJRGSdb0kQULxMlGybGNZL0E0byOV2AaSvLyy/QHAW+kNb5UW3mpv+Ki08FZ5w1tlfu6j8oa3uvi1dZ1aoXLbLjOOkiQJRSY9Ck2FKDQWQmcsRKGxCDq714XQmQpRZNRDqVDafQbUChXUCrXdxZP5UW1ZV94yNVQKJfuiE1GDx7BLlXr8vjvwZ3IG9AYRv/6Wgt6dmqFNWICri+VUCkGBMN9QhPmGol+LXpAkCemFGbhgafW9lJWEW7p0p59XggSDaIBBNDj92PWZSlCag69aCx+VD7ytwdgSiH0s64qDsyUsq4vDsjMYTAYUmoqgM+rMAdVYiEKTTWC1e11oCbBFxSHW8tp2pJC6phSUNoHYHIBtw7N1WVlBWW1ZplGpEXjbH6JegEpQQ6v0gpdSAy+lF7yUXtCqzK9VTqr3+sYkmlBk0kMv6qE36WESTMhX+EFfKEENDbyUGo+5eCOqjwRJklz3V9hN3bqV69TjqVQKBAb6IjMzH0ajWPkObmjz4WSs3WmewaxVqD/mTewGhaJ2/ni7a31lFWXjVkE6jJIRRtEIo2iCUTTCIFpey8uL15Xc1igaYZDsX8vL5e2L17kyJFWVQlBAgABBEKCwPlqWSZBcEvbUCpVdC7K3yhs+liDsq/FGYz8/ZOXloUBvG0qtgbVIfm6UTHVa7vpOJSjhpbIEYNtArPIqNyB7WZZrVdpS6zUKtVNCoiiJ0JsMchgtMpkfrcusr+XloqHEduZltq+LbLYzVfI5ESBAq9LCW6WFVulluWjTQmv58VZq5fW222hV3vBWecnbuGO3J+s3F+afotKPxtLLCu3Wmy8SBAUgiRIAAQoooBAECIL50fxaYfe3RSHYbCO/Vtj8HVLI2yhQvK/Csr0g72vZxub4xee37lu8Talj25XHsh9KrLd5D4oS5y1+TzbnKOsYljID7vt/pCuEhPhXabuGeRlODruvWzgOnLqB1Fv5SE7Lxa+/pWBIt3BXF6tONfZqhMZejer0nCbRBKNUOhhblxlEIyRBhI+vGvl5RRBFyH8ozX9EBfmPqGD7HMV/hOXnEEr88bX/I2u3jc3+lRElEUUmPXRGHQoMOvOjsRA6ow46YyEKjOZlOkOhZZ3Osqx4G0cZRCMM+lzk6J174VpVaoXaEla84K30Nj+qtNAqtfJy25BjDTpeSg1ESbRcQBlgEE2WR6PNMqPdRZbBusxkvlgyWJYZTZXv4+yLEKNkgtFQYNf/vSYECJYArCk7RCs1MEmiOXyKNsHUZLBrabUdicUVJEiWz7KuRsfRKNTFoblESDZ/1kqEaJvPnHV5cTi1DaGW58ZyAqlNMLXb3lQEvclQLy7KPYFtyFcpVFAICsu9H8Xd4JQKpXyPiFJQQqWwrLdbZt7eur70ctv1ZT0vPp/5+Eq7+1LcsesUW3bLwJbdsl1IycK7//sNAKDVKPHOUz0R6O/l9PN4Sn3VFU+vL1ESLV0GikNygVEHXQXB2RyqzcttR92ojEJQmINBiRChVdq3sMlh1RImSgYOd2yBK8naF7tUaLaGZdFkeTTCBCNUWgEZOTnQ6a1ByCYQGYuXWQNToanII7vnKAUlNJYArlGq4aXQQKO0+VFooFVroFQJyCrIRYHB5lsDy7cIrg7f7kYhKKBWqGCSRLnvPwN0/dRIE4CnOk1Am0YRdXI+tuyS093RsjH6dwnDnuPXUag34esdF/Dsg9GuLhZ5OIWggI/a3A0huBr7m0ST3O+2wKiDXiyCyluAQSdBI2jsQqsn3RhXGUEQoJRHBKn4orW6F1TmVn1L+DUW2bUKWl+XGZgtrYiFJVofq9IlRoAAjVJtDqQlgqiXUg2NwhpUi8Opl2X74hBrXi7vY12u0FTpQqay+jKKRpsbFXWWIGzf11tnLNkXvLifuM5YiCKTa/qCqwQlvJRe5jop1T1FY9d1xX65tbuKV+llGk2p+rJejJlveBXtbo4VJcvNsxDl5+aQXGIbmxtz5W1sb7y12V+ynEu0Cdy25xZL3OhbvE1lx7Avn2izj+17tN3e9hzF79P+PUoKCQajEQbLNzq23wLaTqhU17L1Ofgz/Wydhd2qYtglh4wb2A6/nb+NPJ0BR8/eRLezN9G9Q1NXF4uoXEqFEr4KH/iqzTMAenpLuDsxt5Sb+0pXkqerRJIkGESjXWhWCgq74FofLlhUChX8NX7w1/hV+xjW7kHlBuQSfdCt33QoBEVx2CwvkFr6TXupSq+rq5sQ5YuxOjlb/VLZ3zBREmGSRJis94uUCMPW59Vdb15nKrHO/NjYqxH6tOjhglqpGMMuOcTPW41HB7XDqp/Nky+s2HAKtwe2RVyPCLf/D4aI6jdBsLbaquGP6gdFTyB3uVFpEejqwpBbsd4s56xRaTyB+/UiJrfXO7oZ7r3T3JorAVi76xI+/vFPFBl45zoRERG5F4ZdcpggCHh69F0Y3ae1vOzwn2lY9L/fkJ7t+J3zRERERLWFYZeqRSEIeLBfJJ4b0wleanOvquS0XPzj06M4fzXLtYUjIiIismDYpRrp2j4Erz/ZFSGNtQCAnAID3vvqd+z6I9XFJSMiIiJi2CUnaNnUD/MmdkfH1ubbJEyihM+2nMPqn8/gZlbNBlEnIiIiqgmGXXIKP281Zj/SBffZzKq27+R1vLbiID749jj+uHgboshBwomIiKhucVwKchqlQoHHhtyBiFA/fL71HPRGERKAk4npOJmYjuAALQbGNEe/Ls0R4KNxdXGJiIioAWDYJafr0ykMndoGY+/xa9j1+zWk55hHaEjPKcT3uxPxw74kdOvQFPfcEYJ2LRuhsZ/zpxwmIiIiAhh2qZYE+GgwoldrDOvRCicS07Hzt1ScSkyHBMBoknDodBoOnU4DAIQ01uKOlo3RrmUj3NGyMcJDG/Zg8UREROQ8DLtUqxQKAXe3a4K72zXBzcwC7PrjGvYev4b8QqO8za2sQtzKuoEDp24AAHy1KtwREQh/rQoBvho09vNCYz8NGlkffb2gVpXubi5JxX2COZsbERERAQy7VIeaBvrgkdh2eLBvG5xJzsSFlGxcTMlC4vVcGE3F83vnFxrxx/lbFR5LgHn2tvJoNUp4e6nMPxoltJZHby8VvNRKqNUKaFRKaFQKqFQKaFTm12qVAhXlZIUgQGs9npfKfB6NChq1ggGbiIjIDTHsUp3TqJXo0q4JurRrAgAwGEUkp+XiQkoWLqZk40JKNvJ0hgqPUdm4DoV6Ewr1JmTmFjmp1BUTBECrUUGpEOQWZkmyllMqfi6ZW6BFqbglWpTM65UKS5DWqKD1UspB2rpMqRQgCAIEAVDA/CgIApRKAVqtGgU6PUxGCaJk+RGLHwEBCgEQFOZHhWA+lkIQICgAtVIBtUoBjVppfq42XwCoVUooBAFGk2jzI8nPTSYJapUC3loVfCwXAPKjVgWNSoFCvQm6IiN0RSYUFBktz80/oiRBo1bCS22+8NColdCoFZbX5ue2j2q1AgoHLiokyVxWg1GEwSTBYDRBApClMyIrqwB6gyjXkSRJMFnqTCEI8LL+LtRKy3MlVErPGsBG/pyIEpRKAUqFZ70/IiIAECTb734JAHDrVq5Tj6dSKRAY6IvMzHwYjWLlOzRwSqUApUaN5NQspGfrkJWrR3Z+EbLy9MjKK0J2vh4mk/lja809cvwRAFGUigOW3oQivckl74Nqh0qpgJdaAaVSAUgSJFguLCTrRYX50RrKncl6QSIIgjkgo/jCRRSLL2BUKoV8AaG2PFdZnkMCDNYLB6P50WCSzM9FEda/yJLl6sj2L7QgwHJMpeVipPhHo1JCFC3h3npRYhSLz2WyvwAyl9+eRq2At0Ylfyvi46W0XLioodWqUVRkgEk0X7lJsD4CFf8vYr6IMBhF6I2WCw/5xwSjSZTrUCrjYlAQBHipLRdCKmXxc7X5uUIQAAEQ5AtAAJbnCkGwqR9LvdlcQKmUCigV5gtGlUIhB36V0nwhqNMbUVBoREGR5bHQgHzLa73BBNHy5iXJfOEg/94EQOulMl9ECIBSaT6XSiFApTKf07qtZPkMw+azC5i7gCkEAQqF+X2YL0wtF60VXPAJljpTWC9s5eOY68T8b8P8eTCVuoCV5N+DCAmSKNn9bqyfP+u3YLYXoRqVApJkHmddFM2/c5NJhEmSYDIVX0TalkdpKaNKpUDjRt4wGkxQKwVo1Sp4aSwXmZYLYJMoQW8QoTeaYDBYP0smFBlEiKJkdzzzc4W8rOJPZ/Fx9QYReoMJemPxo8kkymU2NxDY16/5dytYPksKqFWCeZnld+2lUkKjUcLL5mLe9qLSaBLNn6lCg91nTac3QqUw17G1zq31rdWqEBzoi5ycAphMEiwfefnfAAAYRcu/f+vfGOvfAqMIo2jex/qZsP18KAQBoiSV+HdaXN9Gk2T+O2Fp2NBqrA0c5r8V/j6aMrsZ1paQEP8qbefWYXft2rVYs2YNrly5gsDAQIwcORJz5syBWq0uc3u9Xo8PPvgAP//8MzIyMhAeHo5p06Zh7NixDp2XYde1nF1f5vBrblnUFRlRZPkjZrD8cbP+EdAbTDCUdT6bv5Umk2RpNTYfr1BvtAvWkihZ/ugAEATLfzyWw1haZQVLKyusfzQtf6lMomg+dpH5mHp+VoiIPI5SIUCjVsJkEj3u77yvVoUXxnZGVHjjOjlfVcOu23Zj2LBhA+bNm4e5c+di8ODBOHfuHObNm4eCggLMnz+/zH3efPNN7Ny5EwsXLkTbtm2xa9cu/P3vf4e3tzeGDx9ex++A3IVCIcBHq4aPtuyLJHdlEkUU6U1yqLZtYRFtWsEUCgF+/lrk5xWZX1u7OsgtHea0LVpbzCyte9bjWFsDza0ZIgwm25YT89f8KqUCaqW5xUKtNLeAmR8VMBhN5paIIkurRJEROpvWL61NS6G3l1Lu5uDtpYIgCOaLDqNovggxmORWliKDCEOJVhbb1hejSZJb8gSbbh3WiwuVsrhV1a4FVK2Er48GBoMJgmRp+VLYtm6YW22LDOZvBQotj0V6o/xcQvGFirW+rd1CJEgwWrpMmB+LW0esrX8KQYBKZa5DlfVHZW4hsm2dsW2xgWD+3ZkvzMwXaAajydJyY99mobS0KqltWp2srZi2LWsKBaC0PDeaJPl3qLNccNUma8u0SqmQW5WsrZLy7xKwaRU2oUhfXIdE9ZVJNP9b80T5hUacSc6ss7BbVW7bsjtkyBB06dIFS5culZd9/fXXmD9/Pnbt2oXQ0FC77VNTUzF48GDMnz8fjz76qLx8zpw5OH36NLZu3Vrlc7Nl17VYX45hfTnGlfVlEkVzy34lX606SrQEQoXC/LWqI/2aKzpmod4cfg0mCf7+WuTmFsJkEuUgavetRQXHUioEqK39wa2hvhpltPar1hvMF0PmrgS2feKLn1svDPWWiymD9Stw61eyBhMMJtHydbsEo2jug26yfAUviqL8Fa2P1vqjll9r1Uq7YA7A8o2NueuEf4A30tPzUKQ3FXcVsJzDaBLtgr21DmFTp6KlC4EoSfIFqiiiVNgv+T+4JJW+mJVf23zdL19kyRdD5q/+BdtuE4L9xYckSsXfilkvjq31axTtLrJVNt0IlApzFwz5fUjmfwuSzftRe6mRmVWAgkLzt2+FepN8wVlkMEGpFOSbiuWuFJbuE0qlApJY3OfetitFpTN3CoCXbbeMEvcQKORyF9et+XcC+VxGm+4Btvc2GGy+QbRezBdZLt6LDCJUSsH8ebJ0FfLRquBruf9B66WSW35LfhNpNIlQKJUo0hvk92f3bwCQf6dqldLSjUqQ//0pFQpzFyyx5OfE/B4FQbCpZ+tN3Er5367eIJa4/8L67aYRAb4ajO7TBo1862biqHrdsnv58mVcvXoVL774ot3y/v37QxRF7N27F+PGjbNbt3//fkiShIEDB5ba5+eff8bVq1cRHh4OIiJXqa0bwBQK8w11zj6m9RuR4gsElUsvqARBkMOZj9ZlxaiUSqVAYIAWgsnEC9Aq4AW7Y1hfjnPLW2+TkpIAABEREXbLw8LCoFarkZiYWOY+Go2mVIuv9Rhl7UNEREREns0tW3bz8vIAAL6+vnbLBUGAr6+vvL7kPiW3BwA/P/NsXLm5Ve+aoFA492tGpWW4IusjVYz15RjWl2NYX45jnTmG9eUY1pdjWF+Oc8uw62pBQb61MkFAQIC304/pyVhfjmF9OYb15TjWmWNYX45hfTmG9VV1bhl2AwICAKBUC64kScjPz5fX2/L390d+fn6p5dYW3bL2KU9GRr7TW3YDAryRk6ODycnjfnoi1pdjWF+OYX05jnXmGNaXY1hfjmF9FQsMLP2NflncMuxGRkYCAJKTkxETEyMvT0lJgcFgQLt27crcR6/X4/r16wgLC5OXX758GQDK3Kc8YlXu4KwGk+WOTaoa1pdjWF+OYX05jnXmGNaXY1hfjmF9VZ1bdvgIDw9HZGQkdu7cabd8x44dUKlU6NevX6l9+vXrB4VCgV9//dVu+fbt29G+fXs0b968VstMRERERO7HLcMuAMycORNbt27FmjVrkJqaiu3bt+Ojjz7ChAkTEBwcjBMnTiAuLg4JCQkAgNDQUDz++ONYtmwZfv31V6SmpuI///kPdu7cidmzZ7v43RARERGRK7hlNwYAiIuLw5IlS7By5UosXboUTZo0wcSJEzFjxgwAgE6nQ1JSEgoKCuR9XnvtNfj5+eGtt95CRkYG2rRpgw8++ACxsbGuehtERERE5EJuO4OaK3EGNddifTmG9eUY1pfjWGeOYX05hvXlGNZXsarOoOa23RiIiIiIiGqKYZeIiIiIPBbDLhERERF5LIZdIiIiIvJYDLtERERE5LEYdomIiIjIYzHsEhEREZHHYtglIiIiIo/FSSWIiIiIyGOxZZeIiIiIPBbDLhERERF5LIZdIiIiIvJYDLtERERE5LEYdomIiIjIYzHsEhEREZHHYtglIiIiIo/FsEtEREREHothl4iIiIg8FsNuLVu7di2GDx+O6Oho9OvXD4sXL4bBYHB1sdzGf//7X0RHR2P27Nml1iUkJOAvf/kLunTpgm7dumHWrFlIS0tzQSndx3fffYcHHngAMTExiI2Nxd///nekp6fL6y9cuIBp06YhJiYGMTExeOqpp3Dp0iUXlth1RFHE6tWrMXLkSHTu3Bk9evTAzJkzkZqaKm/Dz1j5pkyZgvbt2yMlJUVexvoqNmjQILRv377Uz8iRI+VtWF+lpaSk4Pnnn8c999yD7t27Y8aMGbh27Zq8nnVmlpKSUubny/qzbt06AKyvKpOo1qxfv15q3769tGbNGunKlSvStm3bpJ49e0pvvPGGq4vmcpmZmdL06dOlvn37Svfcc480a9Ysu/WXLl2SOnfuLL366qvSpUuXpISEBOnhhx+WRo4cKen1eheV2rVWr14tdejQQVq1apV0+fJlaffu3VL//v2lxx57TBJFUcrIyJB69uwpTZ06VTp79qx08uRJafr06VKfPn2k7OxsVxe/zi1cuFC6++67pQ0bNkhXrlyR9u3bJw0ePFgaNGiQVFRUxM9YBdauXSt17NhRioqKkq5evSpJEv9NlhQbGystWrRIunnzpt1PRkaGJEmsr7JkZ2dLsbGx0jPPPCOdP39eOn78uDRmzBgpLi5OMplMrDMbRqOx1Gfr5s2b0g8//CBFR0dLycnJrC8HMOzWosGDB0tz5syxW/bVV19JHTp0kG7cuOGiUrmHzz//XHryySel27dvS7GxsaXC7ty5c6UBAwZIBoNBXnbp0iUpKipK+vHHH+u6uC4niqLUp08fae7cuXbLv/nmGykqKko6c+aM9OGHH0pdunSRsrKy5PVZWVlS586dpRUrVtR1kV3KYDBIAwcOlOLj4+2Wb9iwQYqKipJOnDjBz1g50tLSpG7duknz58+3C7usL3uxsbHSsmXLyl3P+iotPj5e6tOnj6TT6eRlSUlJ0ubNm6XCwkLWWSX0er0UFxcnvffee5Ik8TPmCHZjqCWXL1/G1atXMWDAALvl/fv3hyiK2Lt3r4tK5h4GDBiANWvWIDg4uMz1+/btQ9++faFSqeRlkZGRaNmyJfbs2VNXxXQbgiDgp59+wt/+9je75aGhoQCA/Px87Nu3DzExMWjUqJG8vlGjRujSpUuDqzOVSoWdO3fiueees1uuUJj/5KnVan7GyvH2228jJiYG999/v91y1pdjWF+l/fLLLxgyZAi0Wq28rHXr1oiLi4OXlxfrrBKffvopcnJy8MwzzwDgZ8wRDLu1JCkpCQAQERFhtzwsLAxqtRqJiYmuKJbbCA8Ph1KpLHNdfn4+bt68WaruAKBVq1YNtu4aN24Mf39/u2U7duyAj48PoqKikJSUhPDw8FL7NeQ6s/Xnn39i+fLliI2NRXh4OD9jZdi8eTP279+P+fPn2y3nv0nHsL5KMxgMuHjxIsLDw/H+++9j0KBB6NWrF1566SVkZGSwzipRUFCATz75BFOmTIGfnx/ry0EMu7UkLy8PAODr62u3XBAE+Pr6yuuptPLqDgD8/PyQm5tb10VyS7/++iu+/fZbTJ8+Hf7+/sjPz2edleG9995DdHQ0xo4diz59+uDDDz/kZ6wMWVlZWLBgAV566SWEhYXZrWN9le306dOYNm0a+vbtiwEDBuCNN95Aeno666sM2dnZMBqN+PTTT1FUVIT4+HjMnz8fR48exaRJk1hnlfj2228hiiIeffRRAPw36ShV5ZsQkbvZvHkzXn75ZYwaNQrTp093dXHc2tSpUzFmzBj8+eefeP/995GUlISFCxe6ulhuZ+HChQgPD8fjjz/u6qLUC4GBgcjLy8OUKVPQsmVLnDlzBkuXLsWxY8ewevVqVxfP7RiNRgDmb/Vee+01AEDHjh2hUqnw7LPP4vDhw64sntv77LPPMHbsWPj5+bm6KPUSw24tCQgIAIBSLbiSJCE/P19eT6VZv6ovq/U7NzfXrk9qQ/T5559j4cKFePzxx/H6669DEAQAkFt3S2rodRYUFISgoCC0a9cObdq0wbhx43DgwAEA/IxZ7dmzB7/88gu+//57uV+zLf6bLO3777+3ex0VFYWQkBBMnjyZn68yWENadHS03fLu3bsDAM6cOQOAdVaWkydPIjU1FYMHD5aX8d+kYxh2a0lkZCQAIDk5GTExMfLylJQUGAwGtGvXzlVFc3s+Pj4ICwtDcnJyqXWXL19Gz549XVAq9/DVV1/hnXfewUsvvYSnnnrKbl1kZGS5dda2bdu6KqJbyMjIwKFDh9C9e3eEhITIy6OiogCY/x3yM1Zs8+bNKCwsxKhRo+RlkiQBAIYOHYru3buzvqqgQ4cOAICbN2+yvkrw8/NDSEgIsrOz7ZaLoggAaNq0KeusHNu3b0ejRo3ssgT/n3QM++zWkvDwcERGRmLnzp12y3fs2AGVSoV+/fq5qGT1w4ABA7B37167CTj+/PNPXLt2DYMGDXJhyVzn4MGDePvttzF37txSQRcw19nvv/+OzMxMednt27fxxx9/NLg6KyoqwuzZs7Fhwwa75WfPngVgHsWCn7Fis2bNwsaNG7Fhwwb5Z8GCBQCAjz/+GAsWLGB92bh06RJeeeWVUhO2nDx5EoB5hAHWV2n9+/fHnj17UFRUJC9LSEgAALRv3551Vo5Dhw6hc+fOpW7qZn05wNVjn3myzZs3S+3bt5dWr14tpaSkSNu2bZO6desmLVq0yNVFc7nMzEx5kOz+/ftLzz77rPxap9NJV65ckWJiYqSXX35ZSkxMlI4fPy6NHj1aevjhhyWTyeTq4tc5URSlYcOGSY899liZA43n5eVJOTk5Ur9+/aQpU6ZIZ8+elc6ePStNnDhRio2NlfLz8139Furc3LlzpZiYGOm7776TkpOTpQMHDkgjR46UJ9ngZ6xihw4dshtnl/VVLC8vTxo4cKA0cuRIad++ffKkQQMHDpRGjBgh6fV61lcZkpKSpJiYGOmZZ56RLl26JO3bt0+KjY2VHn30UUmS+Bkrj3Xc65JYX1UnSJLluyqqFRs3bsTKlSuRnJyMJk2aYNy4cZgxY0aZ/eIakieffBJHjhwpc927776Lhx56CCdPnsTixYtx4sQJaLVaxMbGYu7cuQgMDKzj0rpeampqhVfqzz//PF544QUkJydj4cKFOHLkCARBQK9evfDaa6+hZcuWdVha96DX6/HRRx/hp59+QlpaGpo0aYKuXbti9uzZcn3wM1a+w4cPY8KECdixYwfrqwwpKSn4v//7Pxw+fBgZGRlo3LgxYmNjMXv2bAQFBQFgfZXl1KlTcp1oNBrcd999+Nvf/ib36WWd2RNFEXfeeSeeeeYZzJ49u9R61lfVMOwSERERkcdq2M2LREREROTRGHaJiIiIyGMx7BIRERGRx2LYJSIiIiKPxbBLRERERB6LYZeIiIiIPBbDLhERERF5LIZdIiKq0JNPPon27dvL0+ESEdUnKlcXgIjIU6WkpGDw4MFV3t46Ex4RETkPwy4RUS3z9vauUoiNiYmpg9IQETUsDLtERLXMy8sLU6dOdXUxiIgaJIZdIiI3M3fuXKxfvx6LFy9GSEgI4uPjce7cOUiShPbt2+OZZ57BwIEDS+23fft2fPHFF/jzzz+Rn5+PRo0aISYmBlOnTi2z1fjGjRtYvnw59uzZg9u3b6NRo0aIjY3F888/j2bNmpVZtoMHD2LZsmU4e/YsAOCuu+7CnDlzcM8999ht9/vvv+OTTz7B8ePHkZmZCT8/P4SHh2PUqFF44oknoFQqa15RRERVwLBLROSmDh8+jM2bN+O+++5D3759kZKSgo0bN+KZZ57B8uXLMWjQIHnbZcuW4aOPPkJgYCCGDh2K0NBQXLlyBVu3bsWvv/6KpUuXYtiwYfL2iYmJGD9+PHQ6HUaPHo2WLVvi4sWL+P7777Ft2zasXbsWERERduU5cOAAVq9ejdGjR2PAgAE4ePAgDh06hKlTp2LTpk0ICwsDACQkJGDixInQarUYNmwYWrRogdzcXOzevRsLFy7E8ePH8f7779dNJRIRSUREVCuuXr0qRUVFSffee69D+7366qtSVFSU1L59e2nv3r1267777jspKipKiouLk5edPn1aat++vXTvvfdK169ft9v+6NGjUocOHaTu3btLBQUF8vKHHnpIioqKKnX8//3vf1JUVJQ0ffp0edkTTzwhRUVFST179pSSkpLk5aIoSpMmTZKioqKkNWvWyMvnzJkjRUVFSbt27bI7tl6vlx577DGpa9eu0rVr1xyqEyKi6mLLLhFRLZMkCSkpKRVuo1arERoaarcsJiYGffv2tVv24IMPYvHixUhMTMTVq1cRHh6ODRs2QJIkPP7446W6H3Tr1g09evTAwYMHsXfvXgwdOhRnzpzBqVOn0KFDh1LHHzt2LFJTU9G0adNSZXzkkUfQunVr+bUgCOjXrx8OHDiA1NRUeXl2djYAlOqqoFar8dlnn0Gl4n89RFR3+BeHiKiWZWdnVzoEWYcOHfDDDz/YLSvZDxYwB8g2bdrgjz/+QGJiIsLDw3Hq1KlytweAzp074+DBgzh9+jSGDh0qj5d75513ltpWq9XilVdeKfM40dHRpZYFBAQAAPLy8uRlsbGx2Lt3L+bMmYOpU6diyJAhaNu2LQAw6BJRneNfHSKiWubr64slS5ZUuI2fn1+pZcHBwWVu27hxYwBATk4OACA9Pb3C7YOCggAAmZmZdttbg2pVlbW9QmGem0iSJHnZX/7yF+Tn52PFihV4//338f777yMkJAR9+/bFmDFj0KNHD4fOS0RUEwy7RES1TK1WY8iQIQ7vZw2SJYmiCMA8pBlg7k4A2AfOsra3bmc9rl6vd7hMVfX000/jsccew65du7Bv3z7s378f69evx/r16/Hwww9jwYIFtXZuIiJbnC6YiMhNWVtiS8rKygJQ3JJrfbS22JaUkZFR5vbW5bXF398fo0aNwuLFi7F3716sWrUKoaGhWLt2LQ4ePFir5yYismLYJSJyU8ePHy+1zGg0IikpCQDQsmVLAECnTp0AAMeOHSvzOL/99pvddtbHhIQEmEwmu21FUcSsWbPw4osvwmg0Vqvc2dnZdjesAeZW5b59+2LatGkAgNOnT1fr2EREjmLYJSJyU4cPH8bRo0ftlq1btw65ubno2LGjPHrD2LFjoVAo8PXXX+P69et22+/fvx/Hjh1DaGioPPJC+/btcddddyE9PR3r1q2z237Tpk3YvHkz8vPzq3UzWWZmJnr37o3JkyfLozLYsoZc65i8RES1jX12iYhqWVFREVatWlXpdl5eXnjiiSfk1w888ACefvppDB48GG3atJEnlVAqlXj55Zfl7e644w7MmjUL77//Ph566CHExcUhODgYiYmJ2LZtG7RaLRYvXgy1Wi3v88477+DJJ5/EG2+8gcOHD6Nt27a4dOkSNm/eDD8/v3JHZKhMYGAgnn32WXz44YcYMWIEhgwZgmbNmkGn0+G3337DkSNHcNddd+G+++6r1vGJiBzFsEtEVMt0Ol2lozEA5j6utmE3OjoaY8eORXx8PHbu3AlRFNG5c2e88MIL6N27t92+06dPR7t27fD555/jp59+gk6nQ1BQEOLi4uR1tu68806sX78e8fHxOHDgALZs2YJGjRphxIgReP7550vNnuaI559/Hu3bt8e3336L7du3IysrC2q1Gq1bt8aLL76IiRMnQqPRVPv4RESOEKTybt8lIiKXmDt3LtavX4958+bZhV8iInIc++wSERERkcdi2CUiIiIij8WwS0REREQei2GXiIiIiDwWb1AjIiIiIo/Fll0iIiIi8lgMu0RERETksRh2iYiIiMhjMewSERERkcdi2CUiIiIij8WwS0REREQei2GXiIiIiDwWwy4REREReSyGXSIiIiLyWP8P7c1cZ1LAfoQAAAAASUVORK5CYII=\n",
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\n",
       "text/plain": [
        "<Figure size 800x550 with 1 Axes>"
       ]
@@ -899,12 +904,12 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:14<00:00, 67.90it/s]\n"
+      "100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1000/1000 [00:13<00:00, 72.86it/s]\n"
      ]
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -918,9 +923,10 @@
     "noise = torch.randn((1, 1, 64, 64))\n",
     "noise = noise.to(device)\n",
     "scheduler.set_timesteps(num_inference_steps=1000)\n",
-    "image, intermediates = inferer.sample(\n",
-    "    input_noise=noise, diffusion_model=model, scheduler=scheduler, save_intermediates=True, intermediate_steps=100\n",
-    ")\n",
+    "with autocast(enabled=True):\n",
+    "    image, intermediates = inferer.sample(\n",
+    "        input_noise=noise, diffusion_model=model, scheduler=scheduler, save_intermediates=True, intermediate_steps=100\n",
+    "    )\n",
     "\n",
     "chain = torch.cat(intermediates, dim=-1)\n",
     "\n",
diff --git a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py
index 0bf59a7f..71c4139b 100644
--- a/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py
+++ b/tutorials/generative/2d_ddpm/2d_ddpm_tutorial.py
@@ -58,6 +58,7 @@
 from monai.config import print_config
 from monai.data import CacheDataset, DataLoader
 from monai.utils import first, set_determinism
+from torch.cuda.amp import GradScaler, autocast
 from tqdm import tqdm
 
 from generative.inferers import DiffusionInferer
@@ -167,10 +168,10 @@
     spatial_dims=2,
     in_channels=1,
     out_channels=1,
-    num_channels=(64, 128, 128),
+    num_channels=(128, 256, 256),
     attention_levels=(False, True, True),
     num_res_blocks=1,
-    num_head_channels=128,
+    num_head_channels=256,
 )
 model.to(device)
 
@@ -191,6 +192,7 @@
 epoch_loss_list = []
 val_epoch_loss_list = []
 
+scaler = GradScaler()
 total_start = time.time()
 for epoch in range(n_epochs):
     model.train()
@@ -201,16 +203,19 @@
         images = batch["image"].to(device)
         optimizer.zero_grad(set_to_none=True)
 
-        # Generate random noise
-        noise = torch.randn_like(images).to(device)
+        with autocast(enabled=True):
+            # Generate random noise
+            noise = torch.randn_like(images).to(device)
+
+            # Get model prediction
+            noise_pred = inferer(inputs=images, diffusion_model=model, noise=noise)
 
-        # Get model prediction
-        noise_pred = inferer(inputs=images, diffusion_model=model, noise=noise)
+            loss = F.mse_loss(noise_pred.float(), noise.float())
 
-        loss = F.mse_loss(noise_pred.float(), noise.float())
+        scaler.scale(loss).backward()
+        scaler.step(optimizer)
+        scaler.update()
 
-        loss.backward()
-        optimizer.step()
         epoch_loss += loss.item()
 
         progress_bar.set_postfix(
@@ -225,12 +230,11 @@
         val_epoch_loss = 0
         for step, batch in enumerate(val_loader):
             images = batch["image"].to(device)
-            timesteps = torch.randint(0, scheduler.num_train_timesteps, (images.shape[0],), device=device).long()
-            noise = torch.randn_like(images).to(device)
             with torch.no_grad():
-                # Get model prediction
-                noise_pred = inferer(inputs=images, diffusion_model=model, noise=noise)
-                val_loss = F.l1_loss(noise_pred.float(), noise.float())
+                with autocast(enabled=True):
+                    noise = torch.randn_like(images).to(device)
+                    noise_pred = inferer(inputs=images, diffusion_model=model, noise=noise)
+                    val_loss = F.mse_loss(noise_pred.float(), noise.float())
 
             val_epoch_loss += val_loss.item()
             progress_bar.set_postfix(
@@ -244,7 +248,8 @@
         noise = torch.randn((1, 1, 64, 64))
         noise = noise.to(device)
         scheduler.set_timesteps(num_inference_steps=1000)
-        image = inferer.sample(input_noise=noise, diffusion_model=model, scheduler=scheduler)
+        with autocast(enabled=True):
+            image = inferer.sample(input_noise=noise, diffusion_model=model, scheduler=scheduler)
 
         plt.figure(figsize=(2, 2))
         plt.imshow(image[0, 0].cpu(), vmin=0, vmax=1, cmap="gray")
@@ -283,9 +288,10 @@
 noise = torch.randn((1, 1, 64, 64))
 noise = noise.to(device)
 scheduler.set_timesteps(num_inference_steps=1000)
-image, intermediates = inferer.sample(
-    input_noise=noise, diffusion_model=model, scheduler=scheduler, save_intermediates=True, intermediate_steps=100
-)
+with autocast(enabled=True):
+    image, intermediates = inferer.sample(
+        input_noise=noise, diffusion_model=model, scheduler=scheduler, save_intermediates=True, intermediate_steps=100
+    )
 
 chain = torch.cat(intermediates, dim=-1)
 

From 7688a43de37b3a01fc1ee32a29cd2501d2f20aea Mon Sep 17 00:00:00 2001
From: Walter Hugo Lopez Pinaya <ianonimato@hotmail.com>
Date: Wed, 30 Nov 2022 22:39:37 +0000
Subject: [PATCH 26/28] Add reference (#53)

Signed-off-by: Walter Hugo Lopez Pinaya <ianonimato@hotmail.com>
---
 generative/networks/nets/diffusion_model_unet.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index 4505e17d..2cfa4829 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -409,7 +409,8 @@ def forward(self, x: torch.Tensor) -> torch.Tensor:
 
 def get_timestep_embedding(timesteps: torch.Tensor, embedding_dim: int, max_period: int = 10000) -> torch.Tensor:
     """
-    This matches the implementation in Denoising Diffusion Probabilistic Models: Create sinusoidal timestep embeddings.
+    Create sinusoidal timestep embeddingsfollowing the implementation in Ho et al. "Denoising Diffusion Probabilistic
+    Models" https://arxiv.org/abs/2006.11239.
 
     Args:
         timesteps: a 1-D Tensor of N indices, one per batch element.

From b59171a6256096d2ae1c5b4ec0b9b59d1690555e Mon Sep 17 00:00:00 2001
From: Walter Hugo Lopez Pinaya <ianonimato@hotmail.com>
Date: Wed, 30 Nov 2022 22:45:23 +0000
Subject: [PATCH 27/28] Remove redundant update (#53)

Signed-off-by: Walter Hugo Lopez Pinaya <ianonimato@hotmail.com>
---
 generative/networks/nets/diffusion_model_unet.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index 2cfa4829..0cdd1ce3 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -1563,7 +1563,6 @@ def __init__(
             )
 
             self.up_blocks.append(up_block)
-            prev_output_channel = output_channel
 
         # out
         self.out = nn.Sequential(

From 359f10a97ed3a89893bc2243190730522385214f Mon Sep 17 00:00:00 2001
From: Walter Hugo Lopez Pinaya <ianonimato@hotmail.com>
Date: Wed, 30 Nov 2022 23:01:32 +0000
Subject: [PATCH 28/28] Delete context when it should be ignored (#53)

Signed-off-by: Walter Hugo Lopez Pinaya <ianonimato@hotmail.com>
---
 generative/networks/nets/diffusion_model_unet.py | 5 +++++
 1 file changed, 5 insertions(+)

diff --git a/generative/networks/nets/diffusion_model_unet.py b/generative/networks/nets/diffusion_model_unet.py
index 0cdd1ce3..3a287774 100644
--- a/generative/networks/nets/diffusion_model_unet.py
+++ b/generative/networks/nets/diffusion_model_unet.py
@@ -693,6 +693,7 @@ def __init__(
     def forward(
         self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
     ) -> Tuple[torch.Tensor, List[torch.Tensor]]:
+        del context
         output_states = []
 
         for resnet in self.resnets:
@@ -778,6 +779,7 @@ def __init__(
     def forward(
         self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
     ) -> Tuple[torch.Tensor, List[torch.Tensor]]:
+        del context
         output_states = []
 
         for resnet, attn in zip(self.resnets, self.attentions):
@@ -938,6 +940,7 @@ def __init__(
     def forward(
         self, hidden_states: torch.Tensor, temb: torch.Tensor, context: Optional[torch.Tensor] = None
     ) -> torch.Tensor:
+        del context
         hidden_states = self.resnet_1(hidden_states, temb)
         hidden_states = self.attention(hidden_states)
         hidden_states = self.resnet_2(hidden_states, temb)
@@ -1071,6 +1074,7 @@ def forward(
         temb: torch.Tensor,
         context: Optional[torch.Tensor] = None,
     ) -> torch.Tensor:
+        del context
         for i, resnet in enumerate(self.resnets):
             # pop res hidden states
             res_hidden_states = res_hidden_states_list[-1]
@@ -1159,6 +1163,7 @@ def forward(
         temb: torch.Tensor,
         context: Optional[torch.Tensor] = None,
     ) -> torch.Tensor:
+        del context
         for resnet, attn in zip(self.resnets, self.attentions):
             # pop res hidden states
             res_hidden_states = res_hidden_states_list[-1]