Merge branch 'dev' into 8134-add-realtime-infer

.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:

.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

CHANGELOG.md

@@ -5,7 +5,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ## [Unreleased]
 
-## [1.4.0] - 2024-10-14
+## [1.4.0] - 2024-10-17
 ## What's Changed
 ### Added
 * Implemented Conjugate Gradient Solver to generate confidence maps. (#7876)

CITATION.cff

@@ -6,7 +6,7 @@ title: "MONAI: Medical Open Network for AI"
 abstract: "AI Toolkit for Healthcare Imaging"
 authors:
   - name: "MONAI Consortium"
-date-released: 2024-10-14
+date-released: 2024-10-17
 version: "1.4.0"
 identifiers:
   - description: "This DOI represents all versions of MONAI, and will always resolve to the latest one."

CONTRIBUTING.md

@@ -383,3 +383,8 @@ then make PRs to the `releasing/[version number]` to fix the bugs via the regula
 If any error occurs after the release process, first check out a new hotfix branch from the `main` branch,
 make a patch version release following the semantic versioning, for example, `releasing/0.1.1`.
 Make sure the `releasing/0.1.1` is merged back into both `dev` and `main` and all the test pipelines succeed.
+
+
+<p align="right">
+  <a href="#introduction">⬆️ Back to Top</a>
+</p>

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

README.md

@@ -16,11 +16,11 @@
 [![codecov](https://codecov.io/gh/Project-MONAI/MONAI/branch/dev/graph/badge.svg?token=6FTC7U1JJ4)](https://codecov.io/gh/Project-MONAI/MONAI)
 [![monai Downloads Last Month](https://assets.piptrends.com/get-last-month-downloads-badge/monai.svg 'monai Downloads Last Month by pip Trends')](https://piptrends.com/package/monai)
 
-MONAI is a [PyTorch](https://pytorch.org/)-based, [open-source](https://github.com/Project-MONAI/MONAI/blob/dev/LICENSE) framework for deep learning in healthcare imaging, part of [PyTorch Ecosystem](https://pytorch.org/ecosystem/).
-Its ambitions are:
-- developing a community of academic, industrial and clinical researchers collaborating on a common foundation;
-- creating state-of-the-art, end-to-end training workflows for healthcare imaging;
-- providing researchers with the optimized and standardized way to create and evaluate deep learning models.
+MONAI is a [PyTorch](https://pytorch.org/)-based, [open-source](https://github.com/Project-MONAI/MONAI/blob/dev/LICENSE) framework for deep learning in healthcare imaging, part of the [PyTorch Ecosystem](https://pytorch.org/ecosystem/).
+Its ambitions are as follows:
+- Developing a community of academic, industrial and clinical researchers collaborating on a common foundation;
+- Creating state-of-the-art, end-to-end training workflows for healthcare imaging;
+- Providing researchers with the optimized and standardized way to create and evaluate deep learning models.
 
 
 ## Features

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/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

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_
 
 

monai/bundle/workflows.py

@@ -16,10 +16,11 @@
 import sys
 import time
 from abc import ABC, abstractmethod
+from collections.abc import Sequence
 from copy import copy
 from logging.config import fileConfig
 from pathlib import Path
-from typing import Any, Sequence
+from typing import Any
 
 from monai.apps.utils import get_logger
 from monai.bundle.config_parser import ConfigParser
@@ -316,8 +317,8 @@ def __init__(
                 else:
                     raise FileNotFoundError(f"Cannot find the logging config file: {logging_file}.")
             else:
-                logger.info(f"Setting logging properties based on config: {logging_file}.")
                 fileConfig(str(logging_file), disable_existing_loggers=False)
+                logger.info(f"Setting logging properties based on config: {logging_file}.")
 
         self.parser = ConfigParser()
         self.parser.read_config(f=config_file)

monai/config/type_definitions.py

@@ -12,7 +12,8 @@
 from __future__ import annotations
 
 import os
-from typing import Collection, Hashable, Iterable, Sequence, TypeVar, Union
+from collections.abc import Collection, Hashable, Iterable, Sequence
+from typing import TypeVar, Union
 
 import numpy as np
 import torch