Merge branch 'Project-MONAI:dev' into fix-6840

.github/workflows/cron.yml

@@ -13,17 +13,13 @@ jobs:
     strategy:
       matrix:
         environment:
-          - "PT113+CUDA118"
-          - "PT210+CUDA121"
+          - "PT230+CUDA121"
           - "PT240+CUDA126"
           - "PTLATEST+CUDA126"
         include:
           # https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes
-          - environment: PT113+CUDA118
-            pytorch: "torch==1.13.1 torchvision==0.14.1 --extra-index-url https://download.pytorch.org/whl/cu121"
-            base: "nvcr.io/nvidia/pytorch:22.10-py3"  # CUDA 11.8
-          - environment: PT210+CUDA121
-            pytorch: "pytorch==2.1.0 torchvision==0.16.0 --extra-index-url https://download.pytorch.org/whl/cu121"
+          - environment: PT230+CUDA121
+            pytorch: "pytorch==2.3.0 torchvision==0.18.0 --extra-index-url https://download.pytorch.org/whl/cu121"
             base: "nvcr.io/nvidia/pytorch:23.08-py3"  # CUDA 12.1
           - environment: PT240+CUDA126
             pytorch: "pytorch==2.4.0 torchvision==0.19.0 --extra-index-url https://download.pytorch.org/whl/cu121"

.github/workflows/pythonapp-gpu.yml

@@ -22,19 +22,21 @@ jobs:
     strategy:
       matrix:
         environment:
-          - "PT113+CUDA116"
-          - "PT210+CUDA121DOCKER"
+          - "PT230+CUDA124DOCKER"
+          - "PT240+CUDA125DOCKER"
+          - "PT250+CUDA126DOCKER"
         include:
           # https://docs.nvidia.com/deeplearning/frameworks/pytorch-release-notes
-          - environment: PT113+CUDA116
-            pytorch: "torch==1.13.1 torchvision==0.14.1"
-            base: "nvcr.io/nvidia/cuda:11.6.1-devel-ubuntu18.04"
-          - environment: PT210+CUDA121DOCKER
-            # 23.08: 2.1.0a0+29c30b1
+          - environment: PT230+CUDA124DOCKER
+            # 24.04: 2.3.0a0+6ddf5cf85e
             pytorch: "-h"  # we explicitly set pytorch to -h to avoid pip install error
-            base: "nvcr.io/nvidia/pytorch:23.08-py3"
-          - environment: PT210+CUDA121DOCKER
-            # 24.08: 2.3.0a0+40ec155e58.nv24.3
+            base: "nvcr.io/nvidia/pytorch:24.04-py3"
+          - environment: PT240+CUDA125DOCKER
+            # 24.06: 2.4.0a0+f70bd71a48
+            pytorch: "-h"  # we explicitly set pytorch to -h to avoid pip install error
+            base: "nvcr.io/nvidia/pytorch:24.06-py3"
+          - environment: PT250+CUDA126DOCKER
+            # 24.08: 2.5.0a0+872d972e41
             pytorch: "-h"  # we explicitly set pytorch to -h to avoid pip install error
             base: "nvcr.io/nvidia/pytorch:24.08-py3"
     container:
@@ -49,7 +51,7 @@ jobs:
         apt-get update
         apt-get install -y wget
 
-        if [ ${{ matrix.environment }} = "PT113+CUDA116" ]
+        if [ ${{ matrix.environment }} = "PT230+CUDA124" ]
         then
         PYVER=3.9 PYSFX=3 DISTUTILS=python3-distutils && \
         apt-get update && apt-get install -y --no-install-recommends \
@@ -114,7 +116,7 @@ jobs:
         # build for the current self-hosted CI Tesla V100
         BUILD_MONAI=1 TORCH_CUDA_ARCH_LIST="7.0" ./runtests.sh --build --disttests
         ./runtests.sh --quick --unittests
-        if [ ${{ matrix.environment }} = "PT113+CUDA116" ]; then
+        if [ ${{ matrix.environment }} = "PT230+CUDA124" ]; then
           # test the clang-format tool downloading once
           coverage run -m tests.clang_format_utils
         fi

.github/workflows/pythonapp-min.yml

@@ -124,7 +124,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        pytorch-version: ['1.13.1', '2.0.1', '2.2.2', '2.3.1', '2.4.1', 'latest']
+        pytorch-version: ['2.3.1', '2.4.1', '2.5.1', 'latest']
     timeout-minutes: 40
     steps:
     - uses: actions/checkout@v4

.github/workflows/pythonapp.yml

@@ -94,7 +94,7 @@ jobs:
     - if: runner.os == 'windows'
       name: Install torch cpu from pytorch.org (Windows only)
       run: |
-        python -m pip install torch==1.13.1+cpu torchvision==0.14.1+cpu -f https://download.pytorch.org/whl/torch_stable.html
+        python -m pip install torch==2.4.1 torchvision==0.19.1+cpu --index-url https://download.pytorch.org/whl/cpu
     - if: runner.os == 'Linux'
       name: Install itk pre-release (Linux only)
       run: |
@@ -103,7 +103,7 @@ jobs:
     - name: Install the dependencies
       run: |
         python -m pip install --user --upgrade pip wheel
-        python -m pip install torch==1.13.1 torchvision==0.14.1
+        python -m pip install torch==2.4.1 torchvision==0.19.1
         cat "requirements-dev.txt"
         python -m pip install -r requirements-dev.txt
         python -m pip list
@@ -155,7 +155,7 @@ jobs:
         # install the latest pytorch for testing
         # however, "pip install monai*.tar.gz" will build cpp/cuda with an isolated
         # fresh torch installation according to pyproject.toml
-        python -m pip install torch>=1.13.1 torchvision
+        python -m pip install torch>=2.3.0 torchvision
     - name: Check packages
       run: |
         pip uninstall monai

README.md

@@ -18,12 +18,13 @@
 
 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
+
 > _Please see [the technical highlights](https://docs.monai.io/en/latest/highlights.html) and [What's New](https://docs.monai.io/en/latest/whatsnew.html) of the milestone releases._
 
 - flexible pre-processing for multi-dimensional medical imaging data;
@@ -32,7 +33,6 @@ Its ambitions are as follows:
 - customizable design for varying user expertise;
 - multi-GPU multi-node data parallelism support.
 
-
 ## Installation
 
 To install [the current release](https://pypi.org/project/monai/), you can simply run:
@@ -53,30 +53,34 @@ Technical documentation is available at [docs.monai.io](https://docs.monai.io).
 
 ## Citation
 
-If you have used MONAI in your research, please cite us! The citation can be exported from: https://arxiv.org/abs/2211.02701.
+If you have used MONAI in your research, please cite us! The citation can be exported from: <https://arxiv.org/abs/2211.02701>.
 
 ## Model Zoo
+
 [The MONAI Model Zoo](https://github.com/Project-MONAI/model-zoo) is a place for researchers and data scientists to share the latest and great models from the community.
 Utilizing [the MONAI Bundle format](https://docs.monai.io/en/latest/bundle_intro.html) makes it easy to [get started](https://github.com/Project-MONAI/tutorials/tree/main/model_zoo) building workflows with MONAI.
 
 ## Contributing
+
 For guidance on making a contribution to MONAI, see the [contributing guidelines](https://github.com/Project-MONAI/MONAI/blob/dev/CONTRIBUTING.md).
 
 ## Community
+
 Join the conversation on Twitter/X [@ProjectMONAI](https://twitter.com/ProjectMONAI) or join our [Slack channel](https://forms.gle/QTxJq3hFictp31UM9).
 
 Ask and answer questions over on [MONAI's GitHub Discussions tab](https://github.com/Project-MONAI/MONAI/discussions).
 
 ## Links
-- Website: https://monai.io/
-- API documentation (milestone): https://docs.monai.io/
-- API documentation (latest dev): https://docs.monai.io/en/latest/
-- Code: https://github.com/Project-MONAI/MONAI
-- Project tracker: https://github.com/Project-MONAI/MONAI/projects
-- Issue tracker: https://github.com/Project-MONAI/MONAI/issues
-- Wiki: https://github.com/Project-MONAI/MONAI/wiki
-- Test status: https://github.com/Project-MONAI/MONAI/actions
-- PyPI package: https://pypi.org/project/monai/
-- conda-forge: https://anaconda.org/conda-forge/monai
-- Weekly previews: https://pypi.org/project/monai-weekly/
-- Docker Hub: https://hub.docker.com/r/projectmonai/monai
+
+- Website: <https://monai.io/>
+- API documentation (milestone): <https://docs.monai.io/>
+- API documentation (latest dev): <https://docs.monai.io/en/latest/>
+- Code: <https://github.com/Project-MONAI/MONAI>
+- Project tracker: <https://github.com/Project-MONAI/MONAI/projects>
+- Issue tracker: <https://github.com/Project-MONAI/MONAI/issues>
+- Wiki: <https://github.com/Project-MONAI/MONAI/wiki>
+- Test status: <https://github.com/Project-MONAI/MONAI/actions>
+- PyPI package: <https://pypi.org/project/monai/>
+- conda-forge: <https://anaconda.org/conda-forge/monai>
+- Weekly previews: <https://pypi.org/project/monai-weekly/>
+- Docker Hub: <https://hub.docker.com/r/projectmonai/monai>

docs/requirements.txt

@@ -1,5 +1,5 @@
--f https://download.pytorch.org/whl/cpu/torch-1.13.1%2Bcpu-cp39-cp39-linux_x86_64.whl
-torch>=1.13.1
+-f https://download.pytorch.org/whl/cpu/torch-2.3.0%2Bcpu-cp39-cp39-linux_x86_64.whl
+torch>=2.3.0
 pytorch-ignite==0.4.11
 numpy>=1.20
 itk>=5.2

docs/source/handlers.rst

@@ -53,6 +53,12 @@ ROC AUC metrics handler
     :members:
 
 
+Average Precision metric handler
+--------------------------------
+.. autoclass:: AveragePrecision
+    :members:
+
+
 Confusion matrix metrics handler
 --------------------------------
 .. autoclass:: ConfusionMatrix

docs/source/metrics.rst

@@ -80,6 +80,13 @@ Metrics
 .. autoclass:: ROCAUCMetric
     :members:
 
+`Average Precision`
+-------------------
+.. autofunction:: compute_average_precision
+
+.. autoclass:: AveragePrecisionMetric
+    :members:
+
 `Confusion matrix`
 ------------------
 .. autofunction:: get_confusion_matrix

environment-dev.yml

@@ -5,8 +5,8 @@ channels:
   - nvidia
   - conda-forge
 dependencies:
-  - numpy>=1.24,<2.0
-  - pytorch>=1.13.1
+  - numpy>=1.24,<3.0
+  - pytorch>=2.3.0
   - torchio
   - torchvision
   - pytorch-cuda>=11.6

monai/bundle/scripts.py

@@ -15,6 +15,7 @@
 import json
 import os
 import re
+import urllib
 import warnings
 import zipfile
 from collections.abc import Mapping, Sequence
@@ -58,7 +59,7 @@
 validate, _ = optional_import("jsonschema", name="validate")
 ValidationError, _ = optional_import("jsonschema.exceptions", name="ValidationError")
 Checkpoint, has_ignite = optional_import("ignite.handlers", IgniteInfo.OPT_IMPORT_VERSION, min_version, "Checkpoint")
-requests_get, has_requests = optional_import("requests", name="get")
+requests, has_requests = optional_import("requests")
 onnx, _ = optional_import("onnx")
 huggingface_hub, _ = optional_import("huggingface_hub")
 
@@ -206,6 +207,16 @@ def _download_from_monaihosting(download_path: Path, filename: str, version: str
     extractall(filepath=filepath, output_dir=download_path, has_base=True)
 
 
+def _download_from_bundle_info(download_path: Path, filename: str, version: str, progress: bool) -> None:
+    bundle_info = get_bundle_info(bundle_name=filename, version=version)
+    if not bundle_info:
+        raise ValueError(f"Bundle info not found for {filename} v{version}.")
+    url = bundle_info["browser_download_url"]
+    filepath = download_path / f"{filename}_v{version}.zip"
+    download_url(url=url, filepath=filepath, hash_val=None, progress=progress)
+    extractall(filepath=filepath, output_dir=download_path, has_base=True)
+
+
 def _add_ngc_prefix(name: str, prefix: str = "monai_") -> str:
     if name.startswith(prefix):
         return name
@@ -222,7 +233,7 @@ def _get_all_download_files(request_url: str, headers: dict | None = None) -> li
     if not has_requests:
         raise ValueError("requests package is required, please install it.")
     headers = {} if headers is None else headers
-    response = requests_get(request_url, headers=headers)
+    response = requests.get(request_url, headers=headers)
     response.raise_for_status()
     model_info = json.loads(response.text)
 
@@ -266,7 +277,7 @@ def _download_from_ngc_private(
     request_url = _get_ngc_private_bundle_url(model_name=filename, version=version, repo=repo)
     if has_requests:
         headers = {} if headers is None else headers
-        response = requests_get(request_url, headers=headers)
+        response = requests.get(request_url, headers=headers)
         response.raise_for_status()
     else:
         raise ValueError("NGC API requires requests package. Please install it.")
@@ -289,7 +300,7 @@ def _get_ngc_token(api_key, retry=0):
     url = "https://authn.nvidia.com/token?service=ngc"
     headers = {"Accept": "application/json", "Authorization": "ApiKey " + api_key}
     if has_requests:
-        response = requests_get(url, headers=headers)
+        response = requests.get(url, headers=headers)
         if not response.ok:
             # retry 3 times, if failed, raise an error.
             if retry < 3:
@@ -303,14 +314,17 @@ def _get_ngc_token(api_key, retry=0):
 
 def _get_latest_bundle_version_monaihosting(name):
     full_url = f"{MONAI_HOSTING_BASE_URL}/{name.lower()}"
-    requests_get, has_requests = optional_import("requests", name="get")
     if has_requests:
-        resp = requests_get(full_url)
-        resp.raise_for_status()
-    else:
-        raise ValueError("NGC API requires requests package. Please install it.")
-    model_info = json.loads(resp.text)
-    return model_info["model"]["latestVersionIdStr"]
+        resp = requests.get(full_url)
+        try:
+            resp.raise_for_status()
+            model_info = json.loads(resp.text)
+            return model_info["model"]["latestVersionIdStr"]
+        except requests.exceptions.HTTPError:
+            # for monaihosting bundles, if cannot find the version, get from model zoo model_info.json
+            return get_bundle_versions(name)["latest_version"]
+
+    raise ValueError("NGC API requires requests package. Please install it.")
 
 
 def _examine_monai_version(monai_version: str) -> tuple[bool, str]:
@@ -388,14 +402,14 @@ def _get_latest_bundle_version_ngc(name: str, repo: str | None = None, headers:
     version_header = {"Accept-Encoding": "gzip, deflate"}  # Excluding 'zstd' to fit NGC requirements
     if headers:
         version_header.update(headers)
-    resp = requests_get(version_endpoint, headers=version_header)
+    resp = requests.get(version_endpoint, headers=version_header)
     resp.raise_for_status()
     model_info = json.loads(resp.text)
     latest_versions = _list_latest_versions(model_info)
 
     for version in latest_versions:
         file_endpoint = base_url + f"/{name.lower()}/versions/{version}/files/configs/metadata.json"
-        resp = requests_get(file_endpoint, headers=headers)
+        resp = requests.get(file_endpoint, headers=headers)
         metadata = json.loads(resp.text)
         resp.raise_for_status()
         # if the package version is not available or the model is compatible with the package version
@@ -585,7 +599,16 @@ def download(
             name_ver = "_v".join([name_, version_]) if version_ is not None else name_
             _download_from_github(repo=repo_, download_path=bundle_dir_, filename=name_ver, progress=progress_)
         elif source_ == "monaihosting":
-            _download_from_monaihosting(download_path=bundle_dir_, filename=name_, version=version_, progress=progress_)
+            try:
+                _download_from_monaihosting(
+                    download_path=bundle_dir_, filename=name_, version=version_, progress=progress_
+                )
+            except urllib.error.HTTPError:
+                # for monaihosting bundles, if cannot download from default host, download according to bundle_info
+                _download_from_bundle_info(
+                    download_path=bundle_dir_, filename=name_, version=version_, progress=progress_
+                )
+
         elif source_ == "ngc":
             _download_from_ngc(
                 download_path=bundle_dir_,
@@ -792,9 +815,9 @@ def _get_all_bundles_info(
 
         if auth_token is not None:
             headers = {"Authorization": f"Bearer {auth_token}"}
-            resp = requests_get(request_url, headers=headers)
+            resp = requests.get(request_url, headers=headers)
         else:
-            resp = requests_get(request_url)
+            resp = requests.get(request_url)
         resp.raise_for_status()
     else:
         raise ValueError("requests package is required, please install it.")

monai/engines/evaluator.py

@@ -28,7 +28,7 @@
 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
+from monai.utils.module import look_up_option
 
 if TYPE_CHECKING:
     from ignite.engine import Engine, EventEnum
@@ -269,13 +269,8 @@ def __init__(
             amp_kwargs=amp_kwargs,
         )
         if compile:
-            if pytorch_after(2, 1):
-                compile_kwargs = {} if compile_kwargs is None else compile_kwargs
-                network = torch.compile(network, **compile_kwargs)  # type: ignore[assignment]
-            else:
-                warnings.warn(
-                    "Network compilation (compile=True) not supported for Pytorch versions before 2.1, no compilation done"
-                )
+            compile_kwargs = {} if compile_kwargs is None else compile_kwargs
+            network = torch.compile(network, **compile_kwargs)  # type: ignore[assignment]
         self.network = network
         self.compile = compile
         self.inferer = SimpleInferer() if inferer is None else inferer