From 52b3ae55f4d4e84fcdd64ee2814c33ab9957d419 Mon Sep 17 00:00:00 2001
From: Wenqi Li <wenqil@nvidia.com>
Date: Tue, 25 Jan 2022 22:03:00 +0000
Subject: [PATCH 1/3] fixes grid_sample, interpolate URLs

Signed-off-by: Wenqi Li <wenqil@nvidia.com>
---
 monai/apps/deepgrow/transforms.py           |   2 +-
 monai/data/nifti_saver.py                   |   6 +-
 monai/data/nifti_writer.py                  |   6 +-
 monai/data/png_saver.py                     |   2 +-
 monai/data/png_writer.py                    |   2 +-
 monai/handlers/segmentation_saver.py        |   6 +-
 monai/networks/blocks/warp.py               |   2 +-
 monai/networks/layers/spatial_transforms.py |   6 +-
 monai/transforms/io/array.py                |   6 +-
 monai/transforms/io/dictionary.py           |   6 +-
 monai/transforms/spatial/array.py           | 120 ++++++++++----------
 monai/transforms/spatial/dictionary.py      |  54 ++++-----
 monai/utils/enums.py                        |   6 +-
 13 files changed, 112 insertions(+), 112 deletions(-)

diff --git a/monai/apps/deepgrow/transforms.py b/monai/apps/deepgrow/transforms.py
index a4daef70f6..310931d236 100644
--- a/monai/apps/deepgrow/transforms.py
+++ b/monai/apps/deepgrow/transforms.py
@@ -780,7 +780,7 @@ class RestoreLabeld(MapTransform):
             One of the listed string values or a user supplied function for padding. Defaults to ``"constant"``.
             See also: https://numpy.org/doc/1.18/reference/generated/numpy.pad.html
         align_corners: Geometrically, we consider the pixels of the input as squares rather than points.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             It also can be a sequence of bool, each element corresponds to a key in ``keys``.
         meta_keys: explicitly indicate the key of the corresponding meta data dictionary.
             for example, for data with key `image`, the metadata by default is in `image_meta_dict`.
diff --git a/monai/data/nifti_saver.py b/monai/data/nifti_saver.py
index f31926cb6c..a5acdd032e 100644
--- a/monai/data/nifti_saver.py
+++ b/monai/data/nifti_saver.py
@@ -60,13 +60,13 @@ def __init__(
             mode: {``"bilinear"``, ``"nearest"``}
                 This option is used when ``resample = True``.
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 This option is used when ``resample = True``.
                 Padding mode for outside grid values. Defaults to ``"border"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             align_corners: Geometrically, we consider the pixels of the input as squares rather than points.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             dtype: data type for resampling computation. Defaults to ``np.float64`` for best precision.
                 If None, use the data type of input data.
             output_dtype: data type for saving data. Defaults to ``np.float32``.
diff --git a/monai/data/nifti_writer.py b/monai/data/nifti_writer.py
index 35044977e0..4e7a99f557 100644
--- a/monai/data/nifti_writer.py
+++ b/monai/data/nifti_writer.py
@@ -87,13 +87,13 @@ def write_nifti(
         mode: {``"bilinear"``, ``"nearest"``}
             This option is used when ``resample = True``.
             Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
         padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
             This option is used when ``resample = True``.
             Padding mode for outside grid values. Defaults to ``"border"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
         align_corners: Geometrically, we consider the pixels of the input as squares rather than points.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
         dtype: data type for resampling computation. Defaults to ``np.float64`` for best precision.
             If None, use the data type of input data.
         output_dtype: data type for saving data. Defaults to ``np.float32``.
diff --git a/monai/data/png_saver.py b/monai/data/png_saver.py
index 2e31597837..a83a560e9f 100644
--- a/monai/data/png_saver.py
+++ b/monai/data/png_saver.py
@@ -52,7 +52,7 @@ def __init__(
             resample: whether to resample and resize if providing spatial_shape in the metadata.
             mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
                 The interpolation mode. Defaults to ``"nearest"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
             scale: {``255``, ``65535``} postprocess data by clipping to [0, 1] and scaling
                 [0, 255] (uint8) or [0, 65535] (uint16). Default is None to disable scaling.
             data_root_dir: if not empty, it specifies the beginning parts of the input file's
diff --git a/monai/data/png_writer.py b/monai/data/png_writer.py
index 6f3b2ef86e..f1aa5fc5c8 100644
--- a/monai/data/png_writer.py
+++ b/monai/data/png_writer.py
@@ -39,7 +39,7 @@ def write_png(
         output_spatial_shape: spatial shape of the output image.
         mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
             The interpolation mode. Defaults to ``"bicubic"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
         scale: {``255``, ``65535``} postprocess data by clipping to [0, 1] and scaling to
             [0, 255] (uint8) or [0, 65535] (uint16). Default is None to disable scaling.
 
diff --git a/monai/handlers/segmentation_saver.py b/monai/handlers/segmentation_saver.py
index 79ebfd3a22..40bb5f8bed 100644
--- a/monai/handlers/segmentation_saver.py
+++ b/monai/handlers/segmentation_saver.py
@@ -72,16 +72,16 @@ def __init__(
 
                 - NIfTI files {``"bilinear"``, ``"nearest"``}
                     Interpolation mode to calculate output values.
-                    See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                    See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 - PNG files {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
                     The interpolation mode.
-                    See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+                    See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
 
             padding_mode: This option is used when ``resample = True``. Defaults to ``"border"``.
 
                 - NIfTI files {``"zeros"``, ``"border"``, ``"reflection"``}
                     Padding mode for outside grid values.
-                    See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                    See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 - PNG files
                     This option is ignored.
 
diff --git a/monai/networks/blocks/warp.py b/monai/networks/blocks/warp.py
index 79fed14834..9fdaab0a48 100644
--- a/monai/networks/blocks/warp.py
+++ b/monai/networks/blocks/warp.py
@@ -38,7 +38,7 @@ def __init__(self, mode=GridSampleMode.BILINEAR.value, padding_mode=GridSamplePa
             - mode: ``"nearest"``, ``"bilinear"``, ``"bicubic"``.
             - padding_mode: ``"zeros"``, ``"border"``, ``"reflection"``
 
-        See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+        See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
 
         For MONAI C++/CUDA extensions, the possible values are:
 
diff --git a/monai/networks/layers/spatial_transforms.py b/monai/networks/layers/spatial_transforms.py
index 01e45b2e67..7aa3e110fc 100644
--- a/monai/networks/layers/spatial_transforms.py
+++ b/monai/networks/layers/spatial_transforms.py
@@ -446,11 +446,11 @@ def __init__(
                 coordinates.
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"zeros"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
-            align_corners: see also https://pytorch.org/docs/stable/nn.functional.html#grid-sample.
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
+            align_corners: see also https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html.
             reverse_indexing: whether to reverse the spatial indexing of image and coordinates.
                 set to `False` if `theta` follows pytorch's default "D, H, W" convention.
                 set to `True` if `theta` follows `scipy.ndimage` default "i, j, k" convention.
diff --git a/monai/transforms/io/array.py b/monai/transforms/io/array.py
index 19fafbcbf4..f8aa838439 100644
--- a/monai/transforms/io/array.py
+++ b/monai/transforms/io/array.py
@@ -248,16 +248,16 @@ class SaveImage(Transform):
 
             - NIfTI files {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             - PNG files {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
                 The interpolation mode.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
 
         padding_mode: This option is used when ``resample = True``. Defaults to ``"border"``.
 
             - NIfTI files {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             - PNG files
                 This option is ignored.
 
diff --git a/monai/transforms/io/dictionary.py b/monai/transforms/io/dictionary.py
index 96850ac0cd..cc6a67593f 100644
--- a/monai/transforms/io/dictionary.py
+++ b/monai/transforms/io/dictionary.py
@@ -170,16 +170,16 @@ class SaveImaged(MapTransform):
 
             - NIfTI files {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             - PNG files {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
                 The interpolation mode.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
 
         padding_mode: This option is used when ``resample = True``. Defaults to ``"border"``.
 
             - NIfTI files {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             - PNG files
                 This option is ignored.
 
diff --git a/monai/transforms/spatial/array.py b/monai/transforms/spatial/array.py
index ee5d179b00..60e4f564c8 100644
--- a/monai/transforms/spatial/array.py
+++ b/monai/transforms/spatial/array.py
@@ -121,12 +121,12 @@ def __init__(
                 of the original data.
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"border"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             align_corners: Geometrically, we consider the pixels of the input as squares rather than points.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             dtype: data type for resampling computation. Defaults to ``np.float64`` for best precision.
                 If None, use the data type of input data. To be compatible with other modules,
                 the output data type is always ``np.float32``.
@@ -157,12 +157,12 @@ def __call__(
             affine (matrix): (N+1)x(N+1) original affine matrix for spatially ND `data_array`. Defaults to identity.
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``self.mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``self.padding_mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             align_corners: Geometrically, we consider the pixels of the input as squares rather than points.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             dtype: data type for resampling computation. Defaults to ``self.dtype``.
                 If None, use the data type of input data. To be compatible with other modules,
                 the output data type is always ``np.float32``.
@@ -389,10 +389,10 @@ class Resize(Transform):
             #albumentations.augmentations.geometric.resize.LongestMaxSize.
         mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
             The interpolation mode. Defaults to ``"area"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
         align_corners: This only has an effect when mode is
             'linear', 'bilinear', 'bicubic' or 'trilinear'. Default: None.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
     """
 
     backend = [TransformBackends.TORCH]
@@ -420,10 +420,10 @@ def __call__(
             img: channel first array, must have shape: (num_channels, H[, W, ..., ]).
             mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
                 The interpolation mode. Defaults to ``self.mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
             align_corners: This only has an effect when mode is
                 'linear', 'bilinear', 'bicubic' or 'trilinear'. Defaults to ``self.align_corners``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
 
         Raises:
             ValueError: When ``self.spatial_size`` length is less than ``img`` spatial dimensions.
@@ -469,12 +469,12 @@ class Rotate(Transform, ThreadUnsafe):
             input array is contained completely in the output. Default is True.
         mode: {``"bilinear"``, ``"nearest"``}
             Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
         padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
             Padding mode for outside grid values. Defaults to ``"border"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
         align_corners: Defaults to False.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
         dtype: data type for resampling computation. Defaults to ``np.float64`` for best precision.
             If None, use the data type of input data. To be compatible with other modules,
             the output data type is always ``np.float32``.
@@ -512,14 +512,14 @@ def __call__(
             img: channel first array, must have shape: [chns, H, W] or [chns, H, W, D].
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``self.mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``self.padding_mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 align_corners: Defaults to ``self.align_corners``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             align_corners: Defaults to ``self.align_corners``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             dtype: data type for resampling computation. Defaults to ``self.dtype``.
                 If None, use the data type of input data. To be compatible with other modules,
                 the output data type is always ``np.float32``.
@@ -578,7 +578,7 @@ def get_rotation_matrix(self) -> Optional[NdarrayOrTensor]:
 class Zoom(Transform):
     """
     Zooms an ND image using :py:class:`torch.nn.functional.interpolate`.
-    For details, please see https://pytorch.org/docs/stable/nn.functional.html#interpolate.
+    For details, please see https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html.
 
     Different from :py:class:`monai.transforms.resize`, this transform takes scaling factors
     as input, and provides an option of preserving the input spatial size.
@@ -589,7 +589,7 @@ class Zoom(Transform):
             If a sequence, zoom should contain one value for each spatial axis.
         mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
             The interpolation mode. Defaults to ``"area"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
         padding_mode: available modes for numpy array:{``"constant"``, ``"edge"``, ``"linear_ramp"``, ``"maximum"``,
             ``"mean"``, ``"median"``, ``"minimum"``, ``"reflect"``, ``"symmetric"``, ``"wrap"``, ``"empty"``}
             available modes for PyTorch Tensor: {``"constant"``, ``"reflect"``, ``"replicate"``, ``"circular"``}.
@@ -599,7 +599,7 @@ class Zoom(Transform):
             https://pytorch.org/docs/stable/generated/torch.nn.functional.pad.html
         align_corners: This only has an effect when mode is
             'linear', 'bilinear', 'bicubic' or 'trilinear'. Default: None.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
         keep_size: Should keep original size (padding/slicing if needed), default is True.
         kwargs: other arguments for the `np.pad` or `torch.pad` function.
             note that `np.pad` treats channel dimension as the first dimension.
@@ -636,7 +636,7 @@ def __call__(
             img: channel first array, must have shape: (num_channels, H[, W, ..., ]).
             mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
                 The interpolation mode. Defaults to ``self.mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
             padding_mode: available modes for numpy array:{``"constant"``, ``"edge"``, ``"linear_ramp"``, ``"maximum"``,
                 ``"mean"``, ``"median"``, ``"minimum"``, ``"reflect"``, ``"symmetric"``, ``"wrap"``, ``"empty"``}
                 available modes for PyTorch Tensor: {``"constant"``, ``"reflect"``, ``"replicate"``, ``"circular"``}.
@@ -646,7 +646,7 @@ def __call__(
                 https://pytorch.org/docs/stable/generated/torch.nn.functional.pad.html
             align_corners: This only has an effect when mode is
                 'linear', 'bilinear', 'bicubic' or 'trilinear'. Defaults to ``self.align_corners``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
 
         """
         img_t: torch.Tensor
@@ -778,12 +778,12 @@ class RandRotate(RandomizableTransform):
             If it is True, the output shape is the same as the input. Default is True.
         mode: {``"bilinear"``, ``"nearest"``}
             Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
         padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
             Padding mode for outside grid values. Defaults to ``"border"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
         align_corners: Defaults to False.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
         dtype: data type for resampling computation. Defaults to ``np.float64`` for best precision.
             If None, use the data type of input data. To be compatible with other modules,
             the output data type is always ``np.float32``.
@@ -847,12 +847,12 @@ def __call__(
             img: channel first array, must have shape 2D: (nchannels, H, W), or 3D: (nchannels, H, W, D).
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``self.mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``self.padding_mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             align_corners: Defaults to ``self.align_corners``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             dtype: data type for resampling computation. Defaults to ``self.dtype``.
                 If None, use the data type of input data. To be compatible with other modules,
                 the output data type is always ``np.float32``.
@@ -965,7 +965,7 @@ class RandZoom(RandomizableTransform):
             If 2 values provided for 3D data, use the first value for both H & W dims to keep the same zoom ratio.
         mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
             The interpolation mode. Defaults to ``"area"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
         padding_mode: available modes for numpy array:{``"constant"``, ``"edge"``, ``"linear_ramp"``, ``"maximum"``,
             ``"mean"``, ``"median"``, ``"minimum"``, ``"reflect"``, ``"symmetric"``, ``"wrap"``, ``"empty"``}
             available modes for PyTorch Tensor: {``"constant"``, ``"reflect"``, ``"replicate"``, ``"circular"``}.
@@ -975,7 +975,7 @@ class RandZoom(RandomizableTransform):
             https://pytorch.org/docs/stable/generated/torch.nn.functional.pad.html
         align_corners: This only has an effect when mode is
             'linear', 'bilinear', 'bicubic' or 'trilinear'. Default: None.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
         keep_size: Should keep original size (pad if needed), default is True.
         kwargs: other arguments for the `np.pad` or `torch.pad` function.
             note that `np.pad` treats channel dimension as the first dimension.
@@ -1033,7 +1033,7 @@ def __call__(
             img: channel first array, must have shape 2D: (nchannels, H, W), or 3D: (nchannels, H, W, D).
             mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
                 The interpolation mode. Defaults to ``self.mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
             padding_mode: available modes for numpy array:{``"constant"``, ``"edge"``, ``"linear_ramp"``, ``"maximum"``,
                 ``"mean"``, ``"median"``, ``"minimum"``, ``"reflect"``, ``"symmetric"``, ``"wrap"``, ``"empty"``}
                 available modes for PyTorch Tensor: {``"constant"``, ``"reflect"``, ``"replicate"``, ``"circular"``}.
@@ -1043,7 +1043,7 @@ def __call__(
                 https://pytorch.org/docs/stable/generated/torch.nn.functional.pad.html
             align_corners: This only has an effect when mode is
                 'linear', 'bilinear', 'bicubic' or 'trilinear'. Defaults to ``self.align_corners``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
             randomize: whether to execute `randomize()` function first, default to True.
 
         """
@@ -1348,10 +1348,10 @@ def __init__(
         Args:
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"border"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             device: device on which the tensor will be allocated.
 
         .. deprecated:: 0.6.0
@@ -1375,10 +1375,10 @@ def __call__(
             grid: shape must be (3, H, W) for 2D or (4, H, W, D) for 3D.
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``self.mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``self.padding_mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
         """
         if grid is None:
             raise ValueError("Unknown grid.")
@@ -1484,10 +1484,10 @@ def __init__(
                 to `(32, 64)` if the second spatial dimension size of img is `64`.
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"reflection"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             device: device on which the tensor will be allocated.
             image_only: if True return only the image volume, otherwise return (image, affine).
 
@@ -1526,10 +1526,10 @@ def __call__(
                 if `img` has three spatial dimensions, `spatial_size` should have 3 elements [h, w, d].
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``self.mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``self.padding_mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
         """
         sp_size = fall_back_tuple(spatial_size or self.spatial_size, img.shape[1:])
         grid, affine = self.affine_grid(spatial_size=sp_size)
@@ -1596,10 +1596,10 @@ def __init__(
                 to `(32, 64)` if the second spatial dimension size of img is `64`.
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"reflection"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             cache_grid: whether to cache the identity sampling grid.
                 If the spatial size is not dynamically defined by input image, enabling this option could
                 accelerate the transform.
@@ -1701,10 +1701,10 @@ def __call__(
                 if `img` has three spatial dimensions, `spatial_size` should have 3 elements [h, w, d].
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``self.mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``self.padding_mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             randomize: whether to execute `randomize()` function first, default to True.
 
         """
@@ -1786,10 +1786,10 @@ def __init__(
                 to `(32, 64)` if the second spatial dimension size of img is `64`.
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"reflection"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             device: device on which the tensor will be allocated.
 
         See also:
@@ -1849,10 +1849,10 @@ def __call__(
                 the transform will use the spatial size of `img`.
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``self.mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``self.padding_mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             randomize: whether to execute `randomize()` function first, default to True.
         """
         sp_size = fall_back_tuple(spatial_size or self.spatial_size, img.shape[1:])
@@ -1942,10 +1942,10 @@ def __init__(
                 to `(32, 32, 64)` if the third spatial dimension size of img is `64`.
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"reflection"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             device: device on which the tensor will be allocated.
 
         See also:
@@ -2009,10 +2009,10 @@ def __call__(
                 the transform will use the spatial size of `img`.
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``self.mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``self.padding_mode``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             randomize: whether to execute `randomize()` function first, default to True.
         """
         sp_size = fall_back_tuple(spatial_size or self.spatial_size, img.shape[1:])
@@ -2057,10 +2057,10 @@ def __init__(
                 Each value in the tuple represents the distort step of the related cell.
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"border"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             device: device on which the tensor will be allocated.
 
         """
@@ -2084,10 +2084,10 @@ def __call__(
                 Each value in the tuple represents the distort step of the related cell.
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"border"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
 
         """
         distort_steps = self.distort_steps if distort_steps is None else distort_steps
@@ -2145,10 +2145,10 @@ def __init__(
                 Defaults to (-0.03, 0.03).
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"border"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             device: device on which the tensor will be allocated.
 
         """
@@ -2184,10 +2184,10 @@ def __call__(
             img: shape must be (num_channels, H, W[, D]).
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"border"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             randomize: whether to shuffle the random factors using `randomize()`, default to True.
         """
         if randomize:
diff --git a/monai/transforms/spatial/dictionary.py b/monai/transforms/spatial/dictionary.py
index 0ab9210aaf..963015f420 100644
--- a/monai/transforms/spatial/dictionary.py
+++ b/monai/transforms/spatial/dictionary.py
@@ -183,14 +183,14 @@ def __init__(
                 axes against the original ones.
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 It also can be a sequence of string, each element corresponds to a key in ``keys``.
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"border"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 It also can be a sequence of string, each element corresponds to a key in ``keys``.
             align_corners: Geometrically, we consider the pixels of the input as squares rather than points.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 It also can be a sequence of bool, each element corresponds to a key in ``keys``.
             dtype: data type for resampling computation. Defaults to ``np.float64`` for best precision.
                 If None, use the data type of input data. To be compatible with other modules,
@@ -526,11 +526,11 @@ class Resized(MapTransform, InvertibleTransform):
             #albumentations.augmentations.geometric.resize.LongestMaxSize.
         mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
             The interpolation mode. Defaults to ``"area"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
             It also can be a sequence of string, each element corresponds to a key in ``keys``.
         align_corners: This only has an effect when mode is
             'linear', 'bilinear', 'bicubic' or 'trilinear'. Default: None.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
             It also can be a sequence of bool or None, each element corresponds to a key in ``keys``.
         allow_missing_keys: don't raise exception if key is missing.
     """
@@ -639,11 +639,11 @@ def __init__(
                 to `(32, 64)` if the second spatial dimension size of img is `64`.
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 It also can be a sequence of string, each element corresponds to a key in ``keys``.
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"reflection"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 It also can be a sequence of string, each element corresponds to a key in ``keys``.
             device: device on which the tensor will be allocated.
             allow_missing_keys: don't raise exception if key is missing.
@@ -769,11 +769,11 @@ def __init__(
                 This allows 0 to correspond to no change (i.e., a scaling of 1.0).
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 It also can be a sequence of string, each element corresponds to a key in ``keys``.
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"reflection"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 It also can be a sequence of string, each element corresponds to a key in ``keys``.
             cache_grid: whether to cache the identity sampling grid.
                 If the spatial size is not dynamically defined by input image, enabling this option could
@@ -939,11 +939,11 @@ def __init__(
                 This allows 0 to correspond to no change (i.e., a scaling of 1.0).
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 It also can be a sequence of string, each element corresponds to a key in ``keys``.
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"reflection"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 It also can be a sequence of string, each element corresponds to a key in ``keys``.
             device: device on which the tensor will be allocated.
             allow_missing_keys: don't raise exception if key is missing.
@@ -1075,11 +1075,11 @@ def __init__(
                 This allows 0 to correspond to no change (i.e., a scaling of 1.0).
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 It also can be a sequence of string, each element corresponds to a key in ``keys``.
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"reflection"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 It also can be a sequence of string, each element corresponds to a key in ``keys``.
             device: device on which the tensor will be allocated.
             allow_missing_keys: don't raise exception if key is missing.
@@ -1311,14 +1311,14 @@ class Rotated(MapTransform, InvertibleTransform):
             If it is True, the output shape is the same as the input. Default is True.
         mode: {``"bilinear"``, ``"nearest"``}
             Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             It also can be a sequence of string, each element corresponds to a key in ``keys``.
         padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
             Padding mode for outside grid values. Defaults to ``"border"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             It also can be a sequence of string, each element corresponds to a key in ``keys``.
         align_corners: Defaults to False.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             It also can be a sequence of bool, each element corresponds to a key in ``keys``.
         dtype: data type for resampling computation. Defaults to ``np.float64`` for best precision.
             If None, use the data type of input data. To be compatible with other modules,
@@ -1422,14 +1422,14 @@ class RandRotated(RandomizableTransform, MapTransform, InvertibleTransform):
             If it is True, the output shape is the same as the input. Default is True.
         mode: {``"bilinear"``, ``"nearest"``}
             Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             It also can be a sequence of string, each element corresponds to a key in ``keys``.
         padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
             Padding mode for outside grid values. Defaults to ``"border"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
             It also can be a sequence of string, each element corresponds to a key in ``keys``.
         align_corners: Defaults to False.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
             It also can be a sequence of bool, each element corresponds to a key in ``keys``.
         dtype: data type for resampling computation. Defaults to ``np.float64`` for best precision.
             If None, use the data type of input data. To be compatible with other modules,
@@ -1548,7 +1548,7 @@ class Zoomd(MapTransform, InvertibleTransform):
             If a sequence, zoom should contain one value for each spatial axis.
         mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
             The interpolation mode. Defaults to ``"area"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
             It also can be a sequence of string, each element corresponds to a key in ``keys``.
         padding_mode: available modes for numpy array:{``"constant"``, ``"edge"``, ``"linear_ramp"``, ``"maximum"``,
             ``"mean"``, ``"median"``, ``"minimum"``, ``"reflect"``, ``"symmetric"``, ``"wrap"``, ``"empty"``}
@@ -1559,7 +1559,7 @@ class Zoomd(MapTransform, InvertibleTransform):
             https://pytorch.org/docs/stable/generated/torch.nn.functional.pad.html
         align_corners: This only has an effect when mode is
             'linear', 'bilinear', 'bicubic' or 'trilinear'. Default: None.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
             It also can be a sequence of bool or None, each element corresponds to a key in ``keys``.
         keep_size: Should keep original size (pad if needed), default is True.
         allow_missing_keys: don't raise exception if key is missing.
@@ -1648,7 +1648,7 @@ class RandZoomd(RandomizableTransform, MapTransform, InvertibleTransform):
             If 2 values provided for 3D data, use the first value for both H & W dims to keep the same zoom ratio.
         mode: {``"nearest"``, ``"linear"``, ``"bilinear"``, ``"bicubic"``, ``"trilinear"``, ``"area"``}
             The interpolation mode. Defaults to ``"area"``.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
             It also can be a sequence of string, each element corresponds to a key in ``keys``.
         padding_mode: available modes for numpy array:{``"constant"``, ``"edge"``, ``"linear_ramp"``, ``"maximum"``,
             ``"mean"``, ``"median"``, ``"minimum"``, ``"reflect"``, ``"symmetric"``, ``"wrap"``, ``"empty"``}
@@ -1659,7 +1659,7 @@ class RandZoomd(RandomizableTransform, MapTransform, InvertibleTransform):
             https://pytorch.org/docs/stable/generated/torch.nn.functional.pad.html
         align_corners: This only has an effect when mode is
             'linear', 'bilinear', 'bicubic' or 'trilinear'. Default: None.
-            See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
             It also can be a sequence of bool or None, each element corresponds to a key in ``keys``.
         keep_size: Should keep original size (pad if needed), default is True.
         allow_missing_keys: don't raise exception if key is missing.
@@ -1779,11 +1779,11 @@ def __init__(
                 Each value in the tuple represents the distort step of the related cell.
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 It also can be a sequence of string, each element corresponds to a key in ``keys``.
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"reflection"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 It also can be a sequence of string, each element corresponds to a key in ``keys``.
             device: device on which the tensor will be allocated.
             allow_missing_keys: don't raise exception if key is missing.
@@ -1829,11 +1829,11 @@ def __init__(
                 Defaults to (-0.03, 0.03).
             mode: {``"bilinear"``, ``"nearest"``}
                 Interpolation mode to calculate output values. Defaults to ``"bilinear"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 It also can be a sequence of string, each element corresponds to a key in ``keys``.
             padding_mode: {``"zeros"``, ``"border"``, ``"reflection"``}
                 Padding mode for outside grid values. Defaults to ``"reflection"``.
-                See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
                 It also can be a sequence of string, each element corresponds to a key in ``keys``.
             device: device on which the tensor will be allocated.
             allow_missing_keys: don't raise exception if key is missing.
diff --git a/monai/utils/enums.py b/monai/utils/enums.py
index e1fff184fc..93a6d8f49e 100644
--- a/monai/utils/enums.py
+++ b/monai/utils/enums.py
@@ -58,7 +58,7 @@ class NumpyPadMode(Enum):
 
 class GridSampleMode(Enum):
     """
-    See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+    See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
 
     interpolation mode of `torch.nn.functional.grid_sample`
 
@@ -76,7 +76,7 @@ class GridSampleMode(Enum):
 
 class InterpolateMode(Enum):
     """
-    See also: https://pytorch.org/docs/stable/nn.functional.html#interpolate
+    See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.interpolate.html
     """
 
     NEAREST = "nearest"
@@ -119,7 +119,7 @@ class PytorchPadMode(Enum):
 
 class GridSamplePadMode(Enum):
     """
-    See also: https://pytorch.org/docs/stable/nn.functional.html#grid-sample
+    See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.grid_sample.html
     """
 
     ZEROS = "zeros"

From a77c902cb5302b6f15f173f98c7dbb18fe8c6721 Mon Sep 17 00:00:00 2001
From: Wenqi Li <wenqil@nvidia.com>
Date: Wed, 26 Jan 2022 10:31:29 +0000
Subject: [PATCH 2/3] update based on comments

Signed-off-by: Wenqi Li <wenqil@nvidia.com>
---
 monai/inferers/inferer.py              | 2 +-
 monai/inferers/utils.py                | 2 +-
 monai/networks/blocks/upsample.py      | 2 +-
 monai/transforms/croppad/dictionary.py | 4 ++--
 monai/utils/enums.py                   | 2 +-
 5 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/monai/inferers/inferer.py b/monai/inferers/inferer.py
index 0b700d7c2e..f275480352 100644
--- a/monai/inferers/inferer.py
+++ b/monai/inferers/inferer.py
@@ -110,7 +110,7 @@ class SlidingWindowInferer(Inferer):
             spatial dimensions.
         padding_mode: {``"constant"``, ``"reflect"``, ``"replicate"``, ``"circular"``}
             Padding mode when ``roi_size`` is larger than inputs. Defaults to ``"constant"``
-            See also: https://pytorch.org/docs/stable/nn.functional.html#pad
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.pad.html
         cval: fill value for 'constant' padding mode. Default: 0
         sw_device: device for the window data.
             By default the device (and accordingly the memory) of the `inputs` is used.
diff --git a/monai/inferers/utils.py b/monai/inferers/utils.py
index b27e13eef6..65a81378fa 100644
--- a/monai/inferers/utils.py
+++ b/monai/inferers/utils.py
@@ -65,7 +65,7 @@ def sliding_window_inference(
             spatial dimensions.
         padding_mode: {``"constant"``, ``"reflect"``, ``"replicate"``, ``"circular"``}
             Padding mode for ``inputs``, when ``roi_size`` is larger than inputs. Defaults to ``"constant"``
-            See also: https://pytorch.org/docs/stable/nn.functional.html#pad
+            See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.pad.html
         cval: fill value for 'constant' padding mode. Default: 0
         sw_device: device for the window data.
             By default the device (and accordingly the memory) of the `inputs` is used.
diff --git a/monai/networks/blocks/upsample.py b/monai/networks/blocks/upsample.py
index 6a8498fe6f..c72d1bc518 100644
--- a/monai/networks/blocks/upsample.py
+++ b/monai/networks/blocks/upsample.py
@@ -72,7 +72,7 @@ def __init__(
                 If ends with ``"linear"`` will use ``spatial dims`` to determine the correct interpolation.
                 This corresponds to linear, bilinear, trilinear for 1D, 2D, and 3D respectively.
                 The interpolation mode. Defaults to ``"linear"``.
-                See also: https://pytorch.org/docs/stable/nn.html#upsample
+                See also: https://pytorch.org/docs/stable/generated/torch.nn.Upsample.html
             align_corners: set the align_corners parameter of `torch.nn.Upsample`. Defaults to True.
                 Only used in the "nontrainable" mode.
             bias: whether to have a bias term in the default preconv and deconv layers. Defaults to True.
diff --git a/monai/transforms/croppad/dictionary.py b/monai/transforms/croppad/dictionary.py
index 482247bbe9..d62d6fbdcb 100644
--- a/monai/transforms/croppad/dictionary.py
+++ b/monai/transforms/croppad/dictionary.py
@@ -287,8 +287,8 @@ def __init__(
                 ``"mean"``, ``"median"``, ``"minimum"``, ``"reflect"``, ``"symmetric"``, ``"wrap"``, ``"empty"``}
                 available modes for PyTorch Tensor: {``"constant"``, ``"reflect"``, ``"replicate"``, ``"circular"``}.
                 One of the listed string values or a user supplied function. Defaults to ``"constant"``.
-                See also: https://numpy.org/doc/1.18/reference/generated/numpy.pad.html
-                https://pytorch.org/docs/stable/generated/torch.nn.functional.pad.html
+                See also: https://numpy.org/doc/1.18/reference/ghttps://pytorch.orgenerated/numpy.pad.html
+                /docs/stable/generated/torch.nn.functional.pad.html
                 It also can be a sequence of string, each element corresponds to a key in ``keys``.
             method: {``"symmetric"``, ``"end"``}
                 Pad image symmetrically on every side or only pad at the end sides. Defaults to ``"symmetric"``.
diff --git a/monai/utils/enums.py b/monai/utils/enums.py
index 93a6d8f49e..f88a606fb2 100644
--- a/monai/utils/enums.py
+++ b/monai/utils/enums.py
@@ -108,7 +108,7 @@ class BlendMode(Enum):
 
 class PytorchPadMode(Enum):
     """
-    See also: https://pytorch.org/docs/stable/nn.functional.html#pad
+    See also: https://pytorch.org/docs/stable/generated/torch.nn.functional.pad.html
     """
 
     CONSTANT = "constant"

From 9a584ebeda02a7d780a9a6f4b2d7e811fcc51909 Mon Sep 17 00:00:00 2001
From: Wenqi Li <wenqil@nvidia.com>
Date: Wed, 26 Jan 2022 11:05:01 +0000
Subject: [PATCH 3/3] skip if pretrained downloading failed

Signed-off-by: Wenqi Li <wenqil@nvidia.com>
---
 tests/utils.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/tests/utils.py b/tests/utils.py
index 17297e53f3..232c9c9030 100644
--- a/tests/utils.py
+++ b/tests/utils.py
@@ -101,6 +101,8 @@ def test_pretrained_networks(network, input_param, device):
     except RuntimeError as r_error:
         if "unexpected EOF" in f"{r_error}":  # The file might be corrupted.
             raise unittest.SkipTest(f"{r_error}") from r_error
+        if "network issue" in f"{r_error}":  # The network is not available.
+            raise unittest.SkipTest(f"{r_error}") from r_error
         raise