Merge branch 'dev' into 8094-modify-dice-loss

.github/workflows/blossom-ci.yml

@@ -34,8 +34,7 @@ jobs:
       (
         github.actor == 'Nic-Ma' ||
         github.actor == 'wyli' ||
-        github.actor == 'pxLi' ||
-        github.actor == 'YanxuanLiu' ||
+        github.actor == 'wendell-hom' ||
         github.actor == 'KumoLiu'
       )
     steps:

.github/workflows/cron.yml

@@ -16,7 +16,8 @@ jobs:
           - "PT110+CUDA113"
           - "PT113+CUDA118"
           - "PT210+CUDA121"
-          - "PTLATEST+CUDA124"
+          - "PT240+CUDA126"
+          - "PTLATEST+CUDA126"
         include:
           # https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes
           - environment: PT110+CUDA113
@@ -28,9 +29,12 @@ jobs:
           - environment: PT210+CUDA121
             pytorch: "pytorch==2.1.0 torchvision==0.16.0 --extra-index-url https://download.pytorch.org/whl/cu121"
             base: "nvcr.io/nvidia/pytorch:23.08-py3"  # CUDA 12.1
-          - environment: PTLATEST+CUDA124
+          - environment: PT240+CUDA126
+            pytorch: "pytorch==2.4.0 torchvision==0.19.0 --extra-index-url https://download.pytorch.org/whl/cu121"
+            base: "nvcr.io/nvidia/pytorch:24.08-py3"  # CUDA 12.6
+          - environment: PTLATEST+CUDA126
             pytorch: "-U torch torchvision --extra-index-url https://download.pytorch.org/whl/cu121"
-            base: "nvcr.io/nvidia/pytorch:24.08-py3"  # CUDA 12.4
+            base: "nvcr.io/nvidia/pytorch:24.10-py3"  # CUDA 12.6
     container:
       image: ${{ matrix.base }}
       options: "--gpus all"
@@ -80,7 +84,7 @@ jobs:
     if: github.repository == 'Project-MONAI/MONAI'
     strategy:
       matrix:
-        container: ["pytorch:23.08", "pytorch:24.08"]
+        container: ["pytorch:23.08", "pytorch:24.08", "pytorch:24.10"]
     container:
       image: nvcr.io/nvidia/${{ matrix.container }}-py3  # testing with the latest pytorch base image
       options: "--gpus all"
@@ -129,7 +133,7 @@ jobs:
     if: github.repository == 'Project-MONAI/MONAI'
     strategy:
       matrix:
-        container: ["pytorch:24.08"]
+        container: ["pytorch:24.10"]
     container:
       image: nvcr.io/nvidia/${{ matrix.container }}-py3  # testing with the latest pytorch base image
       options: "--gpus all"
@@ -233,7 +237,7 @@ jobs:
     if: github.repository == 'Project-MONAI/MONAI'
     needs: cron-gpu  # so that monai itself is verified first
     container:
-      image: nvcr.io/nvidia/pytorch:24.08-py3  # testing with the latest pytorch base image
+      image: nvcr.io/nvidia/pytorch:24.10-py3  # testing with the latest pytorch base image
       options: "--gpus all --ipc=host"
     runs-on: [self-hosted, linux, x64, integration]
     steps:

.gitignore

@@ -149,6 +149,9 @@ tests/testing_data/nrrd_example.nrrd
 # clang format tool
 .clang-format-bin/
 
+# ctags
+tags
+
 # VSCode
 .vscode/
 *.zip

.pre-commit-config.yaml

@@ -9,7 +9,7 @@ ci:
 
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.6.0
+    rev: v5.0.0
     hooks:
       - id: end-of-file-fixer
       - id: trailing-whitespace
@@ -26,33 +26,30 @@ repos:
         args: ['--autofix', '--no-sort-keys', '--indent=4']
       - id: end-of-file-fixer
       - id: mixed-line-ending
-  - repo: https://github.com/charliermarsh/ruff-pre-commit
-    rev: v0.3.5
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.7.0
     hooks:
     -   id: ruff
         args:
         - --fix
 
   - repo: https://github.com/asottile/pyupgrade
-    rev: v3.3.1
+    rev: v3.19.0
     hooks:
       - id: pyupgrade
-        args: [--py37-plus]
-        name: Upgrade code excluding monai networks
+        args: [--py39-plus, --keep-runtime-typing]
+        name: Upgrade code with exceptions
         exclude: |
           (?x)(
               ^versioneer.py|
               ^monai/_version.py|
-              ^monai/networks/|  # no PEP 604 for torchscript tensorrt
-              ^monai/losses/  # no PEP 604 for torchscript tensorrt
+              ^monai/networks/| # avoid typing rewrites
+              ^monai/apps/detection/utils/anchor_utils.py| # avoid typing rewrites
+              ^tests/test_compute_panoptic_quality.py # avoid typing rewrites
           )
-      - id: pyupgrade
-        args: [--py37-plus, --keep-runtime-typing]
-        name: Upgrade monai networks
-        files: (?x)(^monai/networks/)
 
   - repo: https://github.com/asottile/yesqa
-    rev: v1.4.0
+    rev: v1.5.0
     hooks:
       - id: yesqa
         name: Unused noqa

Dockerfile

@@ -11,7 +11,7 @@
 
 # To build with a different base image
 # please run `docker build` using the `--build-arg PYTORCH_IMAGE=...` flag.
-ARG PYTORCH_IMAGE=nvcr.io/nvidia/pytorch:24.08-py3
+ARG PYTORCH_IMAGE=nvcr.io/nvidia/pytorch:24.10-py3
 FROM ${PYTORCH_IMAGE}
 
 LABEL maintainer="[email protected]"
@@ -41,6 +41,10 @@ RUN cp /tmp/requirements.txt /tmp/req.bak \
 COPY LICENSE CHANGELOG.md CODE_OF_CONDUCT.md CONTRIBUTING.md README.md versioneer.py setup.py setup.cfg runtests.sh MANIFEST.in ./
 COPY tests ./tests
 COPY monai ./monai
+
+# TODO: remove this line and torch.patch for 24.11
+RUN patch -R -d /usr/local/lib/python3.10/dist-packages/torch/onnx/ < ./monai/torch.patch
+
 RUN BUILD_MONAI=1 FORCE_CUDA=1 python setup.py develop \
   && rm -rf build __pycache__
 
@@ -57,4 +61,6 @@ RUN apt-get update \
 # append /opt/tools to runtime path for NGC CLI to be accessible from all file system locations
 ENV PATH=${PATH}:/opt/tools
 ENV POLYGRAPHY_AUTOINSTALL_DEPS=1
+
+
 WORKDIR /opt/monai

docs/source/networks.rst

@@ -630,6 +630,11 @@ Nets
 .. autoclass:: ViTAutoEnc
   :members:
 
+`MaskedAutoEncoderViT`
+~~~~~~~~~~~~~~~~~~~~~~
+.. autoclass:: MaskedAutoEncoderViT
+  :members:
+
 `FullyConnectedNet`
 ~~~~~~~~~~~~~~~~~~~
 .. autoclass:: FullyConnectedNet

docs/source/transforms.rst

@@ -1180,6 +1180,18 @@ Utility
     :members:
     :special-members: __call__
 
+`TorchIO`
+"""""""""
+.. autoclass:: TorchIO
+    :members:
+    :special-members: __call__
+
+`RandTorchIO`
+"""""""""""""
+.. autoclass:: RandTorchIO
+    :members:
+    :special-members: __call__
+
 `MapLabelValue`
 """""""""""""""
 .. autoclass:: MapLabelValue
@@ -2253,6 +2265,18 @@ Utility (Dict)
     :members:
     :special-members: __call__
 
+`TorchIOd`
+""""""""""
+.. autoclass:: TorchIOd
+    :members:
+    :special-members: __call__
+
+`RandTorchIOd`
+""""""""""""""
+.. autoclass:: RandTorchIOd
+    :members:
+    :special-members: __call__
+
 `MapLabelValued`
 """"""""""""""""
 .. autoclass:: MapLabelValued

environment-dev.yml

@@ -7,6 +7,7 @@ channels:
 dependencies:
   - numpy>=1.24,<2.0
   - pytorch>=1.9
+  - torchio
   - torchvision
   - pytorch-cuda>=11.6
   - pip

monai/__init__.py

@@ -11,12 +11,12 @@
 
 from __future__ import annotations
 
+import logging
 import os
 import sys
-import logging
 import warnings
-from ._version import get_versions
 
+from ._version import get_versions
 
 old_showwarning = warnings.showwarning
 

monai/apps/detection/networks/retinanet_network.py

@@ -42,7 +42,7 @@
 import math
 import warnings
 from collections.abc import Callable, Sequence
-from typing import Any, Dict
+from typing import Any
 
 import torch
 from torch import Tensor, nn
@@ -330,7 +330,7 @@ def forward(self, images: Tensor) -> Any:
         features = self.feature_extractor(images)
         if isinstance(features, Tensor):
             feature_maps = [features]
-        elif torch.jit.isinstance(features, Dict[str, Tensor]):
+        elif torch.jit.isinstance(features, dict[str, Tensor]):
             feature_maps = list(features.values())
         else:
             feature_maps = list(features)

monai/apps/detection/transforms/array.py

@@ -15,7 +15,8 @@
 
 from __future__ import annotations
 
-from typing import Any, Sequence
+from collections.abc import Sequence
+from typing import Any
 
 import numpy as np
 import torch

monai/apps/generation/maisi/networks/autoencoderkl_maisi.py

@@ -13,7 +13,7 @@
 
 import gc
 import logging
-from typing import Sequence
+from collections.abc import Sequence
 
 import torch
 import torch.nn as nn

monai/apps/generation/maisi/networks/controlnet_maisi.py

@@ -11,7 +11,7 @@
 
 from __future__ import annotations
 
-from typing import Sequence
+from collections.abc import Sequence
 
 import torch
 

monai/apps/pathology/engines/utils.py

@@ -11,7 +11,8 @@
 
 from __future__ import annotations
 
-from typing import Any, Sequence
+from collections.abc import Sequence
+from typing import Any
 
 import torch
 

monai/apps/pathology/inferers/inferer.py

@@ -11,7 +11,8 @@
 
 from __future__ import annotations
 
-from typing import Any, Callable, Sequence
+from collections.abc import Sequence
+from typing import Any, Callable
 
 import numpy as np
 import torch

monai/apps/pathology/metrics/lesion_froc.py

@@ -11,7 +11,8 @@
 
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Any, Iterable
+from collections.abc import Iterable
+from typing import TYPE_CHECKING, Any
 
 import numpy as np
 

monai/apps/pathology/transforms/post/array.py

@@ -12,7 +12,8 @@
 from __future__ import annotations
 
 import warnings
-from typing import Callable, Sequence
+from collections.abc import Sequence
+from typing import Callable
 
 import numpy as np
 import torch

monai/apps/tcia/utils.py

@@ -12,7 +12,7 @@
 from __future__ import annotations
 
 import os
-from typing import Iterable
+from collections.abc import Iterable
 
 import monai
 from monai.config.type_definitions import PathLike

monai/apps/utils.py

@@ -136,10 +136,7 @@ def check_hash(filepath: PathLike, val: str | None = None, hash_type: str = "md5
         return True
     actual_hash_func = look_up_option(hash_type.lower(), SUPPORTED_HASH_TYPES)
 
-    if sys.version_info >= (3, 9):
-        actual_hash = actual_hash_func(usedforsecurity=False)  # allows checks on FIPS enabled machines
-    else:
-        actual_hash = actual_hash_func()
+    actual_hash = actual_hash_func(usedforsecurity=False)  # allows checks on FIPS enabled machines
 
     try:
         with open(filepath, "rb") as f:

monai/apps/vista3d/transforms.py

@@ -12,7 +12,7 @@
 from __future__ import annotations
 
 import warnings
-from typing import Sequence
+from collections.abc import Sequence
 
 import numpy as np
 import torch

monai/bundle/__init__.py

@@ -43,4 +43,4 @@
     MACRO_KEY,
     load_bundle_config,
 )
-from .workflows import BundleWorkflow, ConfigWorkflow
+from .workflows import BundleWorkflow, ConfigWorkflow, PythonicWorkflow

monai/bundle/reference_resolver.py

@@ -13,8 +13,8 @@
 
 import re
 import warnings
-from collections.abc import Sequence
-from typing import Any, Iterator
+from collections.abc import Iterator, Sequence
+from typing import Any
 
 from monai.bundle.config_item import ConfigComponent, ConfigExpression, ConfigItem
 from monai.bundle.utils import DEPRECATED_ID_MAPPING, ID_REF_KEY, ID_SEP_KEY
@@ -192,6 +192,16 @@ def get_resolved_content(self, id: str, **kwargs: Any) -> ConfigExpression | str
         """
         return self._resolve_one_item(id=id, **kwargs)
 
+    def remove_resolved_content(self, id: str) -> Any | None:
+        """
+        Remove the resolved ``ConfigItem`` by id.
+
+        Args:
+            id: id name of the expected item.
+
+        """
+        return self.resolved_content.pop(id) if id in self.resolved_content else None
+
     @classmethod
     def normalize_id(cls, id: str | int) -> str:
         """

monai/bundle/scripts.py

@@ -1589,6 +1589,8 @@ def trt_export(
     """
     Export the model checkpoint to the given filepath as a TensorRT engine-based TorchScript.
     Currently, this API only supports converting models whose inputs are all tensors.
+    Note: NVIDIA Volta support (GPUs with compute capability 7.0) has been removed starting with TensorRT 10.5.
+    Review the TensorRT Support Matrix for which GPUs are supported.
 
     There are two ways to export a model:
     1, Torch-TensorRT way: PyTorch module ---> TorchScript module ---> TensorRT engine-based TorchScript.
@@ -1945,7 +1947,6 @@ def create_workflow(
 
     """
     _args = update_kwargs(args=args_file, workflow_name=workflow_name, config_file=config_file, **kwargs)
-    _log_input_summary(tag="run", args=_args)
     (workflow_name, config_file) = _pop_args(
         _args, workflow_name=ConfigWorkflow, config_file=None
     )  # the default workflow name is "ConfigWorkflow"
@@ -1969,7 +1970,7 @@ def create_workflow(
         workflow_ = workflow_class(**_args)
 
     workflow_.initialize()
-
+    _log_input_summary(tag="run", args=_args)
     return workflow_