Cleaning up some very old and now obsolete infrastructure

docs/source/networks.rst

@@ -735,14 +735,9 @@ Nets
 .. autoclass:: VoxelMorphUNet
  :members:
 
-.. autoclass:: voxelmorphunet
- :members:
-
 .. autoclass:: VoxelMorph
  :members:
 
-.. autoclass:: voxelmorph
-
 Utilities
 ---------
 .. automodule:: monai.networks.utils

docs/source/utils.rst

@@ -17,12 +17,6 @@ Module utils
  :members:
 
 
-Aliases
--------
-.. automodule:: monai.utils.aliases
- :members:
-
-
 Misc
 ----
 .. automodule:: monai.utils.misc

monai/__init__.py

@@ -79,8 +79,6 @@ def filter(self, record):
  category=RuntimeWarning,
  )
 
-from .utils.module import load_submodules # noqa: E402
-
 # handlers_* have some external decorators the users may not have installed
 # *.so files and folder "_C" may not exist when the cpp extensions are not compiled
 excludes = "|".join(
@@ -96,11 +94,24 @@ def filter(self, record):
  ]
 )
 
-# load directory modules only, skip loading individual files
-load_submodules(sys.modules[__name__], False, exclude_pattern=excludes)
-
-# load all modules, this will trigger all export decorations
-load_submodules(sys.modules[__name__], True, exclude_pattern=excludes)
+from . import ( # noqa: E402
+ apps,
+ auto3dseg,
+ bundle,
+ config,
+ data,
+ engines,
+ fl,
+ handlers,
+ inferers,
+ losses,
+ metrics,
+ networks,
+ optimizers,
+ transforms,
+ utils,
+ visualize,
+)
 
 __all__ = [
  "apps",

monai/bundle/scripts.py

@@ -34,7 +34,7 @@
 from monai.bundle.config_parser import ConfigParser
 from monai.bundle.utils import DEFAULT_INFERENCE, DEFAULT_METADATA, merge_kv
 from monai.bundle.workflows import BundleWorkflow, ConfigWorkflow
-from monai.config import IgniteInfo, PathLike
+from monai.config import PathLike
 from monai.data import load_net_with_metadata, save_net_with_metadata
 from monai.networks import (
  convert_to_onnx,
@@ -45,6 +45,7 @@
  save_state,
 )
 from monai.utils import (
+ IgniteInfo,
  check_parent_dir,
  deprecated_arg,
  ensure_tuple,

monai/config/__init__.py

@@ -14,7 +14,6 @@
 from .deviceconfig import (
  USE_COMPILED,
  USE_META_DICT,
- IgniteInfo,
  get_config_values,
  get_gpu_info,
  get_optional_config_values,

monai/config/deviceconfig.py

@@ -45,7 +45,6 @@
  "print_debug_info",
  "USE_COMPILED",
  "USE_META_DICT",
- "IgniteInfo",
 ]
 
 
@@ -261,14 +260,5 @@ def print_debug_info(file: TextIO = 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

@@ -17,14 +17,14 @@
 import torch
 from torch.utils.data import DataLoader
 
-from monai.config import IgniteInfo, KeysCollection
+from monai.config import KeysCollection
 from monai.data import MetaTensor
 from monai.engines.utils import IterationEvents, default_metric_cmp_fn, 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, min_version, optional_import
+from monai.utils import ForwardMode, IgniteInfo, ensure_tuple, min_version, optional_import
 from monai.utils.enums import CommonKeys as Keys
 from monai.utils.enums import EngineStatsKeys as ESKeys
 from monai.utils.module import look_up_option, pytorch_after

monai/engines/trainer.py

@@ -18,13 +18,12 @@
 from torch.optim.optimizer import Optimizer
 from torch.utils.data import DataLoader
 
-from monai.config import IgniteInfo
 from monai.data import MetaTensor
 from monai.engines.utils import IterationEvents, default_make_latent, default_metric_cmp_fn, default_prepare_batch
 from monai.engines.workflow import Workflow
 from monai.inferers import Inferer, SimpleInferer
 from monai.transforms import Transform
-from monai.utils import AdversarialIterationEvents, AdversarialKeys, GanKeys, min_version, optional_import
+from monai.utils import AdversarialIterationEvents, AdversarialKeys, GanKeys, IgniteInfo, min_version, optional_import
 from monai.utils.enums import CommonKeys as Keys
 from monai.utils.enums import EngineStatsKeys as ESKeys
 from monai.utils.module import pytorch_after

monai/engines/utils.py

@@ -18,9 +18,8 @@
 import torch
 import torch.nn as nn
 
-from monai.config import IgniteInfo
 from monai.transforms import apply_transform
-from monai.utils import ensure_tuple, min_version, optional_import
+from monai.utils import IgniteInfo, ensure_tuple, min_version, optional_import
 from monai.utils.enums import CommonKeys, GanKeys
 
 if TYPE_CHECKING:

monai/engines/workflow.py

@@ -20,10 +20,9 @@
 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_metric_cmp_fn, default_prepare_batch
 from monai.transforms import Decollated
-from monai.utils import ensure_tuple, is_scalar, min_version, optional_import
+from monai.utils import IgniteInfo, ensure_tuple, is_scalar, min_version, optional_import
 
 from .utils import engine_apply_transform
 

monai/handlers/checkpoint_loader.py

@@ -17,9 +17,8 @@
 
 import torch
 
-from monai.config import IgniteInfo
 from monai.networks.utils import copy_model_state
-from monai.utils import min_version, optional_import
+from monai.utils import IgniteInfo, min_version, optional_import
 
 Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 Checkpoint, _ = optional_import("ignite.handlers", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Checkpoint")

monai/handlers/checkpoint_saver.py

@@ -17,8 +17,7 @@
 from collections.abc import Mapping
 from typing import TYPE_CHECKING, Any
 
-from monai.config import IgniteInfo
-from monai.utils import is_scalar, min_version, optional_import
+from monai.utils import IgniteInfo, is_scalar, min_version, optional_import
 
 Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 

monai/handlers/classification_saver.py

@@ -18,8 +18,8 @@
 
 import torch
 
-from monai.config import IgniteInfo
 from monai.data import CSVSaver, decollate_batch
+from monai.utils import IgniteInfo
 from monai.utils import ImageMetaKey as Key
 from monai.utils import evenly_divisible_all_gather, min_version, optional_import, string_list_all_gather
 

monai/handlers/decollate_batch.py

@@ -13,10 +13,10 @@
 
 from typing import TYPE_CHECKING
 
-from monai.config import IgniteInfo, KeysCollection
+from monai.config import KeysCollection
 from monai.engines.utils import IterationEvents
 from monai.transforms import Decollated
-from monai.utils import min_version, optional_import
+from monai.utils import IgniteInfo, min_version, optional_import
 
 Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 if TYPE_CHECKING:

monai/handlers/earlystop_handler.py

@@ -14,8 +14,7 @@
 from collections.abc import Callable
 from typing import TYPE_CHECKING
 
-from monai.config import IgniteInfo
-from monai.utils import min_version, optional_import
+from monai.utils import IgniteInfo, min_version, optional_import
 
 Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 EarlyStopping, _ = optional_import("ignite.handlers", IgniteInfo.OPT_IMPORT_VERSION, min_version, "EarlyStopping")

monai/handlers/garbage_collector.py

@@ -14,8 +14,7 @@
 import gc
 from typing import TYPE_CHECKING
 
-from monai.config import IgniteInfo
-from monai.utils import min_version, optional_import
+from monai.utils import IgniteInfo, min_version, optional_import
 
 if TYPE_CHECKING:
  from ignite.engine import Engine, Events

monai/handlers/ignite_metric.py

@@ -18,9 +18,8 @@
 import torch
 from torch.nn.modules.loss import _Loss
 
-from monai.config import IgniteInfo
 from monai.metrics import CumulativeIterationMetric, LossMetric
-from monai.utils import MetricReduction, min_version, optional_import
+from monai.utils import IgniteInfo, MetricReduction, min_version, optional_import
 
 idist, _ = optional_import("ignite", IgniteInfo.OPT_IMPORT_VERSION, min_version, "distributed")
 

monai/handlers/logfile_handler.py

@@ -15,8 +15,7 @@
 import os
 from typing import TYPE_CHECKING
 
-from monai.config import IgniteInfo
-from monai.utils import min_version, optional_import
+from monai.utils import IgniteInfo, min_version, optional_import
 
 Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 if TYPE_CHECKING:

monai/handlers/lr_schedule_handler.py

@@ -17,8 +17,7 @@
 
 from torch.optim.lr_scheduler import ReduceLROnPlateau, _LRScheduler
 
-from monai.config import IgniteInfo
-from monai.utils import ensure_tuple, min_version, optional_import
+from monai.utils import IgniteInfo, ensure_tuple, min_version, optional_import
 
 Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 if TYPE_CHECKING:

monai/handlers/metric_logger.py

@@ -17,8 +17,7 @@
 from threading import RLock
 from typing import TYPE_CHECKING, Any
 
-from monai.config import IgniteInfo
-from monai.utils import min_version, optional_import
+from monai.utils import IgniteInfo, min_version, optional_import
 from monai.utils.enums import CommonKeys
 
 Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")

monai/handlers/metrics_saver.py

@@ -14,9 +14,9 @@
 from collections.abc import Callable, Sequence
 from typing import TYPE_CHECKING
 
-from monai.config import IgniteInfo
 from monai.data import decollate_batch
 from monai.handlers.utils import write_metrics_reports
+from monai.utils import IgniteInfo
 from monai.utils import ImageMetaKey as Key
 from monai.utils import ensure_tuple, min_version, optional_import, string_list_all_gather
 

monai/handlers/mlflow_handler.py

@@ -22,8 +22,7 @@
 from torch.utils.data import Dataset
 
 from monai.apps.utils import get_logger
-from monai.config import IgniteInfo
-from monai.utils import CommonKeys, ensure_tuple, min_version, optional_import
+from monai.utils import CommonKeys, IgniteInfo, ensure_tuple, min_version, optional_import
 
 Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 mlflow, _ = optional_import("mlflow", descriptor="Please install mlflow before using MLFlowHandler.")

monai/handlers/nvtx_handlers.py

@@ -16,8 +16,7 @@
 
 from typing import TYPE_CHECKING
 
-from monai.config import IgniteInfo
-from monai.utils import ensure_tuple, min_version, optional_import
+from monai.utils import IgniteInfo, ensure_tuple, min_version, optional_import
 
 _nvtx, _ = optional_import("torch._C._nvtx", descriptor="NVTX is not installed. Are you sure you have a CUDA build?")
 if TYPE_CHECKING:

monai/handlers/parameter_scheduler.py

@@ -16,8 +16,7 @@
 from collections.abc import Callable
 from typing import TYPE_CHECKING
 
-from monai.config import IgniteInfo
-from monai.utils import min_version, optional_import
+from monai.utils import IgniteInfo, min_version, optional_import
 
 if TYPE_CHECKING:
  from ignite.engine import Engine, Events

monai/handlers/postprocessing.py

@@ -14,9 +14,8 @@
 from collections.abc import Callable
 from typing import TYPE_CHECKING
 
-from monai.config import IgniteInfo
 from monai.engines.utils import IterationEvents, engine_apply_transform
-from monai.utils import min_version, optional_import
+from monai.utils import IgniteInfo, min_version, optional_import
 
 Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 if TYPE_CHECKING:

monai/handlers/probability_maps.py

@@ -17,10 +17,10 @@
 
 import numpy as np
 
-from monai.config import DtypeLike, IgniteInfo
+from monai.config import DtypeLike
 from monai.data.folder_layout import FolderLayout
 from monai.utils import ProbMapKeys, min_version, optional_import
-from monai.utils.enums import CommonKeys
+from monai.utils.enums import CommonKeys, IgniteInfo
 
 Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 if TYPE_CHECKING:

monai/handlers/smartcache_handler.py

@@ -13,9 +13,8 @@
 
 from typing import TYPE_CHECKING
 
-from monai.config import IgniteInfo
 from monai.data import SmartCacheDataset
-from monai.utils import min_version, optional_import
+from monai.utils import IgniteInfo, min_version, optional_import
 
 Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 if TYPE_CHECKING:

monai/handlers/stats_handler.py

@@ -19,8 +19,7 @@
 import torch
 
 from monai.apps import get_logger
-from monai.config import IgniteInfo
-from monai.utils import is_scalar, min_version, optional_import
+from monai.utils import IgniteInfo, is_scalar, min_version, optional_import
 
 Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 if TYPE_CHECKING:

monai/handlers/tensorboard_handlers.py

@@ -18,8 +18,7 @@
 import numpy as np
 import torch
 
-from monai.config import IgniteInfo
-from monai.utils import is_scalar, min_version, optional_import
+from monai.utils import IgniteInfo, is_scalar, min_version, optional_import
 from monai.visualize import plot_2d_or_3d_image
 
 Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")

monai/handlers/trt_handler.py

@@ -13,9 +13,8 @@
 
 from typing import TYPE_CHECKING
 
-from monai.config import IgniteInfo
 from monai.networks import trt_compile
-from monai.utils import min_version, optional_import
+from monai.utils import IgniteInfo, min_version, optional_import
 
 Events, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Events")
 if TYPE_CHECKING:

monai/handlers/utils.py

@@ -19,8 +19,8 @@
 import numpy as np
 import torch
 
-from monai.config import IgniteInfo, KeysCollection, PathLike
-from monai.utils import ensure_tuple, look_up_option, min_version, optional_import
+from monai.config import KeysCollection, PathLike
+from monai.utils import IgniteInfo, ensure_tuple, look_up_option, min_version, optional_import
 
 idist, _ = optional_import("ignite", IgniteInfo.OPT_IMPORT_VERSION, min_version, "distributed")
 if TYPE_CHECKING: