2914 remove the deprecated API for v0.7

docs/source/handlers.rst

@@ -150,11 +150,6 @@ GarbageCollector handler
 .. autoclass:: GarbageCollector
     :members:
 
-Transform inverter
-------------------
-.. autoclass:: TransformInverter
-    :members:
-
 Post processing
 ---------------
 .. autoclass:: PostProcessing

monai/handlers/__init__.py

@@ -32,13 +32,5 @@
 from .stats_handler import StatsHandler
 from .surface_distance import SurfaceDistance
 from .tensorboard_handlers import TensorBoardHandler, TensorBoardImageHandler, TensorBoardStatsHandler
-from .transform_inverter import TransformInverter
-from .utils import (
-    evenly_divisible_all_gather,
-    from_engine,
-    stopping_fn_from_loss,
-    stopping_fn_from_metric,
-    string_list_all_gather,
-    write_metrics_reports,
-)
+from .utils import from_engine, stopping_fn_from_loss, stopping_fn_from_metric, write_metrics_reports
 from .validation_handler import ValidationHandler

monai/handlers/segmentation_saver.py

@@ -26,7 +26,7 @@
     Engine, _ = optional_import("ignite.engine", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Engine")
 
 
-@deprecated(since="0.6.0", removed="0.7.0", msg_suffix="Please consider using `SaveImage[d]` transform instead.")
+@deprecated(since="0.6.0", removed="0.8.0", msg_suffix="Please consider using `SaveImage[d]` transform instead.")
 class SegmentationSaver:
     """
     Event handler triggered on completing every iteration to save the segmentation predictions into files.

monai/handlers/utils.py

@@ -11,13 +11,13 @@
 
 import os
 from collections import OrderedDict
-from typing import TYPE_CHECKING, Dict, List, Optional, Sequence, Union
+from typing import TYPE_CHECKING, Dict, Optional, Sequence, Union
 
 import numpy as np
 import torch
 
 from monai.config import IgniteInfo, KeysCollection
-from monai.utils import deprecated, ensure_tuple, get_torch_version_tuple, look_up_option, min_version, optional_import
+from monai.utils import ensure_tuple, look_up_option, min_version, optional_import
 
 idist, _ = optional_import("ignite", IgniteInfo.OPT_IMPORT_VERSION, min_version, "distributed")
 if TYPE_CHECKING:
@@ -28,8 +28,6 @@
 __all__ = [
     "stopping_fn_from_metric",
     "stopping_fn_from_loss",
-    "evenly_divisible_all_gather",
-    "string_list_all_gather",
     "write_metrics_reports",
     "from_engine",
 ]
@@ -57,78 +55,6 @@ def stopping_fn(engine: Engine):
     return stopping_fn
 
 
-@deprecated(since="0.6.0", removed="0.7.0", msg_suffix="The API had been moved to monai.utils module.")
-def evenly_divisible_all_gather(data: torch.Tensor) -> torch.Tensor:
-    """
-    Utility function for distributed data parallel to pad at first dim to make it evenly divisible and all_gather.
-
-    Args:
-        data: source tensor to pad and execute all_gather in distributed data parallel.
-
-    Note:
-        The input data on different ranks must have exactly same `dtype`.
-
-    .. versionchanged:: 0.6.0
-        The API had been moved to `monai.utils`.
-
-    """
-    if not isinstance(data, torch.Tensor):
-        raise ValueError("input data must be PyTorch Tensor.")
-
-    if idist.get_world_size() <= 1:
-        return data
-
-    # make sure the data is evenly-divisible on multi-GPUs
-    length = data.shape[0]
-    all_lens = idist.all_gather(length)
-    max_len = max(all_lens)
-    if length < max_len:
-        size = [max_len - length] + list(data.shape[1:])
-        data = torch.cat([data, data.new_full(size, 0)], dim=0)
-    # all gather across all processes
-    data = idist.all_gather(data)
-    # delete the padding NaN items
-    return torch.cat([data[i * max_len : i * max_len + l, ...] for i, l in enumerate(all_lens)], dim=0)
-
-
-@deprecated(since="0.6.0", removed="0.7.0", msg_suffix="The API had been moved to monai.utils module.")
-def string_list_all_gather(strings: List[str]) -> List[str]:
-    """
-    Utility function for distributed data parallel to all gather a list of strings.
-    Note that if the item in `strings` is longer than 1024 chars, it will be truncated to 1024:
-    https://pytorch.org/ignite/v0.4.5/distributed.html#ignite.distributed.utils.all_gather.
-
-    Args:
-        strings: a list of strings to all gather.
-
-    .. versionchanged:: 0.6.0
-        The API had been moved to `monai.utils`.
-
-    """
-    world_size = idist.get_world_size()
-    if world_size <= 1:
-        return strings
-
-    result: List[List[str]] = [[] for _ in range(world_size)]
-    # get length of strings
-    length = len(strings)
-    all_lens = idist.all_gather(length)
-    max_len = max(all_lens)
-    # pad the item to make sure the same length
-    if length < max_len:
-        strings += ["" for _ in range(max_len - length)]
-
-    if get_torch_version_tuple() <= (1, 6):
-        raise RuntimeError("string all_gather can not be supported in PyTorch < 1.7.0.")
-
-    for s in strings:
-        gathered = idist.all_gather(s)
-        for i, g in enumerate(gathered):
-            if len(g) > 0:
-                result[i].append(g)
-    return [i for k in result for i in k]
-
-
 def write_metrics_reports(
     save_dir: str,
     images: Optional[Sequence[str]],

monai/networks/nets/netadapter.py

@@ -37,6 +37,9 @@ class NetAdapter(torch.nn.Module):
         bias: the bias value when replacing the last layer. if False, the layer will not learn an additive bias,
             default to True.
 
+    .. deprecated:: 0.6.0
+        ``n_classes`` is deprecated, use ``num_classes`` instead.
+
     """
 
     @deprecated_arg("n_classes", since="0.6")

monai/networks/nets/resnet.py

@@ -168,6 +168,10 @@ class ResNet(nn.Module):
             - 'B': kernel_size 1 conv + norm.
         widen_factor: widen output for each layer.
         num_classes: number of output (classifications)
+
+    .. deprecated:: 0.6.0
+        ``n_classes`` is deprecated, use ``num_classes`` instead.
+
     """
 
     @deprecated_arg("n_classes", since="0.6")

monai/transforms/post/array.py

@@ -129,6 +129,9 @@ class AsDiscrete(Transform):
         rounding: if not None, round the data according to the specified option,
             available options: ["torchrounding"].
 
+    .. deprecated:: 0.6.0
+        ``n_classes`` is deprecated, use ``num_classes`` instead.
+
     """
 
     @deprecated_arg("n_classes", since="0.6")
@@ -181,6 +184,9 @@ def __call__(
             rounding: if not None, round the data according to the specified option,
                 available options: ["torchrounding"].
 
+        .. deprecated:: 0.6.0
+            ``n_classes`` is deprecated, use ``num_classes`` instead.
+
         """
         # in case the new num_classes is default but you still call deprecated n_classes
         if n_classes is not None and num_classes is None:

monai/transforms/post/dictionary.py

@@ -158,6 +158,9 @@ def __init__(
                 each element corresponds to a key in ``keys``.
             allow_missing_keys: don't raise exception if key is missing.
 
+        .. deprecated:: 0.6.0
+            ``n_classes`` is deprecated, use ``num_classes`` instead.
+
         """
         # in case the new num_classes is default but you still call deprecated n_classes
         if n_classes is not None and num_classes is None: