2399 update ignite to v0.4.5

docs/requirements.txt

@@ -1,6 +1,6 @@
 -f https://download.pytorch.org/whl/cpu/torch-1.6.0%2Bcpu-cp37-cp37m-linux_x86_64.whl
 torch>=1.5
-pytorch-ignite==0.4.4
+pytorch-ignite==0.4.5
 numpy>=1.17
 itk>=5.0, <=5.1.2
 nibabel

monai/apps/pathology/handlers.py

@@ -15,14 +15,14 @@
 
 import numpy as np
 
-from monai.config import DtypeLike
-from monai.utils import exact_version, optional_import
+from monai.config import DtypeLike, IgniteInfo
+from monai.utils import min_version, optional_import
 
-Events, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Events")
+Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 if TYPE_CHECKING:
     from ignite.engine import Engine
 else:
-    Engine, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Engine")
+    Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
 
 
 class ProbMapProducer:

monai/config/__init__.py

@@ -11,6 +11,7 @@
 
 from .deviceconfig import (
     USE_COMPILED,
+    IgniteInfo,
     get_gpu_info,
     get_system_info,
     print_config,

monai/config/deviceconfig.py

@@ -46,6 +46,7 @@
     "print_gpu_info",
     "print_debug_info",
     "USE_COMPILED",
+    "IgniteInfo",
 ]
 
 
@@ -252,5 +253,14 @@ def print_debug_info(file=sys.stdout) -> None:
     print_gpu_info(file)
 
 
+class IgniteInfo:
+    """
+    Config information of the PyTorch ignite package.
+
+    """
+
+    OPT_IMPORT_VERSION = "0.4.4"
+
+
 if __name__ == "__main__":
     print_debug_info()

monai/engines/evaluator.py

@@ -14,21 +14,22 @@
 import torch
 from torch.utils.data import DataLoader
 
+from monai.config import IgniteInfo
 from monai.engines.utils import IterationEvents, default_prepare_batch
 from monai.engines.workflow import Workflow
 from monai.inferers import Inferer, SimpleInferer
 from monai.networks.utils import eval_mode, train_mode
 from monai.transforms import Transform
-from monai.utils import ForwardMode, ensure_tuple, exact_version, optional_import
+from monai.utils import ForwardMode, ensure_tuple, min_version, optional_import
 from monai.utils.enums import CommonKeys as Keys
 
 if TYPE_CHECKING:
     from ignite.engine import Engine, EventEnum
     from ignite.metrics import Metric
 else:
-    Engine, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Engine")
-    Metric, _ = optional_import("ignite.metrics", "0.4.4", exact_version, "Metric")
-    EventEnum, _ = optional_import("ignite.engine", "0.4.4", exact_version, "EventEnum")
+    Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
+    Metric, _ = optional_import("ignite.metrics", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Metric")
+    EventEnum, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "EventEnum")
 
 __all__ = ["Evaluator", "SupervisedEvaluator", "EnsembleEvaluator"]
 

monai/engines/multi_gpu_supervised_trainer.py

@@ -16,18 +16,23 @@
 from torch.nn.parallel import DataParallel, DistributedDataParallel
 from torch.optim.optimizer import Optimizer
 
+from monai.config import IgniteInfo
 from monai.engines.utils import get_devices_spec
-from monai.utils import exact_version, optional_import
-
-create_supervised_trainer, _ = optional_import("ignite.engine", "0.4.4", exact_version, "create_supervised_trainer")
-create_supervised_evaluator, _ = optional_import("ignite.engine", "0.4.4", exact_version, "create_supervised_evaluator")
-_prepare_batch, _ = optional_import("ignite.engine", "0.4.4", exact_version, "_prepare_batch")
+from monai.utils import min_version, optional_import
+
+create_supervised_trainer, _ = optional_import(
+    "ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "create_supervised_trainer"
+)
+create_supervised_evaluator, _ = optional_import(
+    "ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "create_supervised_evaluator"
+)
+_prepare_batch, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "_prepare_batch")
 if TYPE_CHECKING:
     from ignite.engine import Engine
     from ignite.metrics import Metric
 else:
-    Engine, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Engine")
-    Metric, _ = optional_import("ignite.metrics", "0.4.4", exact_version, "Metric")
+    Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
+    Metric, _ = optional_import("ignite.metrics", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Metric")
 
 __all__ = [
     "create_multigpu_supervised_trainer",

monai/engines/trainer.py

@@ -15,20 +15,21 @@
 from torch.optim.optimizer import Optimizer
 from torch.utils.data import DataLoader
 
+from monai.config import IgniteInfo
 from monai.engines.utils import GanKeys, IterationEvents, default_make_latent, default_prepare_batch
 from monai.engines.workflow import Workflow
 from monai.inferers import Inferer, SimpleInferer
 from monai.transforms import Transform
-from monai.utils import exact_version, optional_import
+from monai.utils import min_version, optional_import
 from monai.utils.enums import CommonKeys as Keys
 
 if TYPE_CHECKING:
     from ignite.engine import Engine, EventEnum
     from ignite.metrics import Metric
 else:
-    Engine, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Engine")
-    Metric, _ = optional_import("ignite.metrics", "0.4.4", exact_version, "Metric")
-    EventEnum, _ = optional_import("ignite.engine", "0.4.4", exact_version, "EventEnum")
+    Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
+    Metric, _ = optional_import("ignite.metrics", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Metric")
+    EventEnum, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "EventEnum")
 
 __all__ = ["Trainer", "SupervisedTrainer", "GanTrainer"]
 

monai/engines/utils.py

@@ -13,14 +13,15 @@
 
 import torch
 
+from monai.config import IgniteInfo
 from monai.transforms import apply_transform
-from monai.utils import exact_version, optional_import
+from monai.utils import min_version, optional_import
 from monai.utils.enums import CommonKeys
 
 if TYPE_CHECKING:
     from ignite.engine import EventEnum
 else:
-    EventEnum, _ = optional_import("ignite.engine", "0.4.4", exact_version, "EventEnum")
+    EventEnum, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "EventEnum")
 
 __all__ = [
     "IterationEvents",

monai/engines/workflow.py

@@ -16,22 +16,23 @@
 from torch.utils.data import DataLoader
 from torch.utils.data.distributed import DistributedSampler
 
+from monai.config import IgniteInfo
 from monai.engines.utils import IterationEvents, default_prepare_batch
-from monai.utils import ensure_tuple, exact_version, optional_import
+from monai.utils import ensure_tuple, min_version, optional_import
 
 from .utils import engine_apply_transform
 
-IgniteEngine, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Engine")
-State, _ = optional_import("ignite.engine", "0.4.4", exact_version, "State")
-Events, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Events")
+IgniteEngine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
+State, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "State")
+Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 
 if TYPE_CHECKING:
     from ignite.engine import Engine, EventEnum
     from ignite.metrics import Metric
 else:
-    Engine, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Engine")
-    Metric, _ = optional_import("ignite.metrics", "0.4.4", exact_version, "Metric")
-    EventEnum, _ = optional_import("ignite.engine", "0.4.4", exact_version, "EventEnum")
+    Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
+    Metric, _ = optional_import("ignite.metrics", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Metric")
+    EventEnum, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "EventEnum")
 
 
 class Workflow(IgniteEngine):  # type: ignore[valid-type, misc] # due to optional_import

monai/handlers/checkpoint_loader.py

@@ -14,15 +14,16 @@
 
 import torch
 
+from monai.config import IgniteInfo
 from monai.networks.utils import copy_model_state
-from monai.utils import exact_version, optional_import
+from monai.utils import min_version, optional_import
 
-Events, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Events")
-Checkpoint, _ = optional_import("ignite.handlers", "0.4.4", exact_version, "Checkpoint")
+Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
+Checkpoint, _ = optional_import("ignite.handlers", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Checkpoint")
 if TYPE_CHECKING:
     from ignite.engine import Engine
 else:
-    Engine, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Engine")
+    Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
 
 
 class CheckpointLoader:

monai/handlers/checkpoint_saver.py

@@ -13,17 +13,18 @@
 import warnings
 from typing import TYPE_CHECKING, Dict, Optional
 
-from monai.utils import exact_version, optional_import
+from monai.config import IgniteInfo
+from monai.utils import min_version, optional_import
 
-Events, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Events")
-Checkpoint, _ = optional_import("ignite.handlers", "0.4.4", exact_version, "Checkpoint")
+Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
+Checkpoint, _ = optional_import("ignite.handlers", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Checkpoint")
 
 if TYPE_CHECKING:
     from ignite.engine import Engine
     from ignite.handlers import DiskSaver
 else:
-    Engine, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Engine")
-    DiskSaver, _ = optional_import("ignite.handlers", "0.4.4", exact_version, "DiskSaver")
+    Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
+    DiskSaver, _ = optional_import("ignite.handlers", IgniteInfo.OPT_IMPORT_VERSION, min_version, "DiskSaver")
 
 
 class CheckpointSaver:

monai/handlers/classification_saver.py

@@ -15,22 +15,23 @@
 
 import torch
 
+from monai.config import IgniteInfo
 from monai.data import CSVSaver
 from monai.utils import ImageMetaKey as Key
 from monai.utils import (
     evenly_divisible_all_gather,
-    exact_version,
     issequenceiterable,
+    min_version,
     optional_import,
     string_list_all_gather,
 )
 
-idist, _ = optional_import("ignite", "0.4.4", exact_version, "distributed")
-Events, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Events")
+idist, _ = optional_import("ignite", IgniteInfo.OPT_IMPORT_VERSION, min_version, "distributed")
+Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 if TYPE_CHECKING:
     from ignite.engine import Engine
 else:
-    Engine, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Engine")
+    Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
 
 
 class ClassificationSaver:

monai/handlers/earlystop_handler.py

@@ -11,15 +11,16 @@
 
 from typing import TYPE_CHECKING, Callable, Optional
 
-from monai.utils import exact_version, optional_import
+from monai.config import IgniteInfo
+from monai.utils import min_version, optional_import
 
-Events, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Events")
-EarlyStopping, _ = optional_import("ignite.handlers", "0.4.4", exact_version, "EarlyStopping")
+Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
+EarlyStopping, _ = optional_import("ignite.handlers", IgniteInfo.OPT_IMPORT_VERSION, min_version, "EarlyStopping")
 
 if TYPE_CHECKING:
     from ignite.engine import Engine
 else:
-    Engine, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Engine")
+    Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
 
 
 class EarlyStopHandler:

monai/handlers/garbage_collector.py

@@ -12,13 +12,14 @@
 import gc
 from typing import TYPE_CHECKING
 
-from monai.utils import exact_version, optional_import
+from monai.config import IgniteInfo
+from monai.utils import min_version, optional_import
 
 if TYPE_CHECKING:
     from ignite.engine import Engine, Events
 else:
-    Engine, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Engine")
-    Events, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Events")
+    Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
+    Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 
 
 class GarbageCollector:

monai/handlers/ignite_metric.py

@@ -14,16 +14,19 @@
 
 import torch
 
+from monai.config import IgniteInfo
 from monai.metrics import CumulativeIterationMetric
-from monai.utils import exact_version, optional_import
+from monai.utils import min_version, optional_import
 
-idist, _ = optional_import("ignite", "0.4.4", exact_version, "distributed")
-Metric, _ = optional_import("ignite.metrics", "0.4.4", exact_version, "Metric")
-reinit__is_reduced, _ = optional_import("ignite.metrics.metric", "0.4.4", exact_version, "reinit__is_reduced")
+idist, _ = optional_import("ignite", IgniteInfo.OPT_IMPORT_VERSION, min_version, "distributed")
+Metric, _ = optional_import("ignite.metrics", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Metric")
+reinit__is_reduced, _ = optional_import(
+    "ignite.metrics.metric", IgniteInfo.OPT_IMPORT_VERSION, min_version, "reinit__is_reduced"
+)
 if TYPE_CHECKING:
     from ignite.engine import Engine
 else:
-    Engine, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Engine")
+    Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
 
 
 class IgniteMetric(Metric):  # type: ignore[valid-type, misc] # due to optional_import

monai/handlers/lr_schedule_handler.py

@@ -14,13 +14,14 @@
 
 from torch.optim.lr_scheduler import ReduceLROnPlateau, _LRScheduler
 
-from monai.utils import ensure_tuple, exact_version, optional_import
+from monai.config import IgniteInfo
+from monai.utils import ensure_tuple, min_version, optional_import
 
-Events, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Events")
+Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 if TYPE_CHECKING:
     from ignite.engine import Engine
 else:
-    Engine, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Engine")
+    Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
 
 
 class LrScheduleHandler:

monai/handlers/metric_logger.py

@@ -14,14 +14,15 @@
 from threading import RLock
 from typing import TYPE_CHECKING, Callable, DefaultDict, List, Optional
 
-from monai.utils import exact_version, optional_import
+from monai.config import IgniteInfo
+from monai.utils import min_version, optional_import
 from monai.utils.enums import CommonKeys
 
-Events, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Events")
+Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 if TYPE_CHECKING:
     from ignite.engine import Engine
 else:
-    Engine, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Engine")
+    Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
 
 
 def _get_loss_from_output(output, loss_key: str = CommonKeys.LOSS):

monai/handlers/metrics_saver.py

@@ -11,16 +11,17 @@
 
 from typing import TYPE_CHECKING, Callable, List, Optional, Sequence, Union
 
+from monai.config import IgniteInfo
 from monai.handlers.utils import write_metrics_reports
 from monai.utils import ImageMetaKey as Key
-from monai.utils import ensure_tuple, exact_version, issequenceiterable, optional_import, string_list_all_gather
+from monai.utils import ensure_tuple, issequenceiterable, min_version, optional_import, string_list_all_gather
 
-Events, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Events")
-idist, _ = optional_import("ignite", "0.4.4", exact_version, "distributed")
+Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
+idist, _ = optional_import("ignite", IgniteInfo.OPT_IMPORT_VERSION, min_version, "distributed")
 if TYPE_CHECKING:
     from ignite.engine import Engine
 else:
-    Engine, _ = optional_import("ignite.engine", "0.4.4", exact_version, "Engine")
+    Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
 
 
 class MetricsSaver: