merge master

.github/workflows/cron-mmar.yml

@@ -0,0 +1,42 @@
+name: cron-mmar
+
+on:
+  schedule:
+    - cron: "0 2 * * *"  # at 02:00 UTC
+  # Allows you to run this workflow manually from the Actions tab
+  workflow_dispatch:
+
+concurrency:
+  # automatically cancel the previously triggered workflows when there's a newer version
+  group: mmar-tests-${{ github.event.pull_request.number || github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  cron-load:
+    if: github.repository == 'Project-MONAI/MONAI'
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python 3.8
+      uses: actions/setup-python@v2
+      with:
+        python-version: 3.8
+    - name: cache weekly timestamp
+      id: pip-cache
+      run: echo "::set-output name=datew::$(date '+%Y-%V')"
+    - name: cache for pip
+      uses: actions/cache@v2
+      id: cache
+      with:
+        path: ~/.cache/pip
+        key: ${{ runner.os }}-pip-${{ steps.pip-cache.outputs.datew }}
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip wheel
+        python -m pip install -r requirements-dev.txt
+    - name: Loading MMARs
+      run: |
+        # clean up temporary files
+        $(pwd)/runtests.sh --clean
+        # run tests
+        python -m tests.ngc_mmar_loading

.github/workflows/cron.yml

@@ -215,7 +215,7 @@ jobs:
         which python
         python -m pip install --upgrade pip wheel
         python -m pip install -r requirements-dev.txt
-        BUILD_MONAI=0 python setup.py develop  # install monai
+        BUILD_MONAI=1 python setup.py develop  # install monai
         nvidia-smi
         export CUDA_VISIBLE_DEVICES=$(python -m tests.utils)
         echo $CUDA_VISIBLE_DEVICES
@@ -234,5 +234,7 @@ jobs:
         trap 'if pgrep python; then pkill python; fi;' ERR
         python -c $'import torch\na,b=torch.zeros(1,device="cuda:0"),torch.zeros(1,device="cuda:1");\nwhile True:print(a,b)' > /dev/null &
         cd /opt/tutorials
+        python -c 'import monai; monai.config.print_debug_info()'
         $(pwd)/runner.sh
+        python -c 'import monai; monai.config.print_debug_info()'
         if pgrep python; then pkill python; fi

.github/workflows/integration.yml

@@ -34,7 +34,7 @@ jobs:
         which python
         python -m pip install --upgrade pip wheel
         python -m pip uninstall -y torch torchvision
-        python -m pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111 -f https://download.pytorch.org/whl/torch_stable.html
+        python -m pip install torch==1.9.1+cu111 torchvision==0.10.1+cu111 -f https://download.pytorch.org/whl/torch_stable.html
         python -m pip install -r requirements-dev.txt
     - name: Run integration tests
       run: |

.github/workflows/pythonapp-gpu.yml

@@ -47,7 +47,7 @@ jobs:
             pytorch: "-h"
             base: "nvcr.io/nvidia/pytorch:21.08-py3"
           - environment: PT19+CUDA102
-            pytorch: "torch==1.9.0 torchvision==0.10.0"
+            pytorch: "torch==1.9.1 torchvision==0.10.1"
             base: "nvcr.io/nvidia/cuda:10.2-devel-ubuntu18.04"
     container:
       image: ${{ matrix.base }}
@@ -100,6 +100,8 @@ jobs:
       run: |
         which python
         python -m pip install --upgrade pip wheel
+        # fixes preinstalled ruamel_yaml error from the docker image
+        rm -rf $(python -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())")/ruamel*
         python -m pip install ${{ matrix.pytorch }}
         python -m pip install -r requirements-dev.txt
         python -m pip list

.github/workflows/pythonapp.yml

@@ -87,10 +87,10 @@ jobs:
     - if: runner.os == 'windows'
       name: Install torch cpu from pytorch.org (Windows only)
       run: |
-        python -m pip install torch==1.9.0+cpu torchvision==0.10.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
+        python -m pip install torch==1.9.1+cpu torchvision==0.10.1+cpu -f https://download.pytorch.org/whl/torch_stable.html
     - name: Install the dependencies
       run: |
-        python -m pip install torch==1.9.0 torchvision==0.10.0
+        python -m pip install torch==1.9.1 torchvision==0.10.1
         cat "requirements-dev.txt"
         python -m pip install -r requirements-dev.txt
         python -m pip list
@@ -138,11 +138,11 @@ jobs:
     - if: runner.os == 'windows'
       name: Install torch cpu from pytorch.org (Windows only)
       run: |
-        python -m pip install torch==1.9.0+cpu -f https://download.pytorch.org/whl/torch_stable.html
+        python -m pip install torch==1.9.1+cpu -f https://download.pytorch.org/whl/torch_stable.html
     - name: Install the dependencies
       run: |
         # min. requirements
-        python -m pip install torch==1.9.0
+        python -m pip install torch==1.9.1
         python -m pip install -r requirements-min.txt
         python -m pip list
         BUILD_MONAI=0 python setup.py develop  # no compile of extensions
@@ -152,6 +152,7 @@ jobs:
         python -c 'import torch; print(torch.__version__); print(torch.rand(5,3))'
         python -c "import monai; monai.config.print_config()"
         ./runtests.sh --min
+      shell: bash
       env:
         QUICKTEST: True
 
@@ -187,7 +188,7 @@ jobs:
     - name: Install the dependencies
       run: |
         # min. requirements
-        python -m pip install torch==1.9.0
+        python -m pip install torch==1.9.1
         python -m pip install -r requirements-min.txt
         python -m pip list
         BUILD_MONAI=0 python setup.py develop  # no compile of extensions

.github/workflows/release.yml

@@ -144,6 +144,17 @@ jobs:
         run: |
           # get tag info for versioning
           mv _version.py monai/
+          # version checks
+          target="\"version\": \"$RELEASE_VERSION\""
+          echo $target
+          local=`grep "\"version\"" monai/_version.py
+          echo $local
+          if [ "$local" = "$target" ]; then
+            echo "matched version string"
+          else
+            echo "unmatched version string, please check the main branch"
+            exit 1
+          fi
           # remove flake package as it is not needed on hub.docker.com
           sed -i '/flake/d' requirements-dev.txt
           docker build -t projectmonai/monai:"$RELEASE_VERSION" -f Dockerfile .

.github/workflows/weekly-preview.yml

@@ -33,7 +33,7 @@ jobs:
         export YEAR_WEEK=$(date +'%y%U')
         echo "Year week for tag is ${YEAR_WEEK}"
         if ! [[ $YEAR_WEEK =~ ^[0-9]{4}$ ]] ; then echo "Wrong 'year week' format.  Should be 4 digits."; exit 1 ; fi
-        git tag "0.7.dev${YEAR_WEEK}"
+        git tag "0.8.dev${YEAR_WEEK}"
         git log -1
         git tag --list
         python setup.py sdist bdist_wheel

.gitignore

@@ -135,3 +135,4 @@ tests/testing_data/*.tiff
 
 # VSCode
 .vscode/
+*.zip

.pre-commit-config.yaml

@@ -22,18 +22,30 @@ repos:
         args: ['--maxkb=1024']
       - id: detect-private-key
 
-  #- repo: https://github.com/asottile/pyupgrade
-  #  rev: v2.23.2
-  #  hooks:
-  #    - id: pyupgrade
-  #      args: [--py36-plus]
-  #      name: Upgrade code
+  - repo: https://github.com/asottile/pyupgrade
+    rev: v2.29.0
+    hooks:
+      - id: pyupgrade
+        args: [--py36-plus]
+        name: Upgrade code
+        exclude: |
+          (?x)^(
+              versioneer.py|
+              monai/_version.py
+          )$
 
-  #- repo: https://github.com/asottile/yesqa
-  #  rev: v1.2.3
-  #  hooks:
-  #    - id: yesqa
-  #      name: Unused noqa
+  - repo: https://github.com/asottile/yesqa
+    rev: v1.2.3
+    hooks:
+      - id: yesqa
+        name: Unused noqa
+        additional_dependencies:
+          - flake8>=3.8.1
+          - flake8-bugbear
+          - flake8-comprehensions
+          - flake8-executable
+          - flake8-pyi
+          - pep8-naming
 
   #- repo: https://github.com/PyCQA/isort
   #  rev: 5.9.3

CHANGELOG.md

@@ -5,7 +5,50 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/)
 and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.html).
 
 ## [Unreleased]
-* renamed model's `n_classes` to `num_classes`
+
+## [0.7.0] - 2021-09-24
+### Added
+* Overview of [new features in v0.7](docs/source/whatsnew_0_7.md)
+* Initial phase of major usability improvements in `monai.transforms` to support input and backend in PyTorch and NumPy
+* Performance enhancements, with [profiling and tuning guides](https://github.com/Project-MONAI/tutorials/blob/master/acceleration/fast_model_training_guide.md) for typical use cases
+* Reproducing [training modules and workflows](https://github.com/Project-MONAI/tutorials/tree/master/kaggle/RANZCR/4th_place_solution) of state-of-the-art Kaggle competition solutions
+* 24 new transforms, including
+  * `OneOf` meta transform
+  * DeepEdit guidance signal transforms for interactive segmentation
+  * Transforms for self-supervised pre-training
+  * Integration of [NVIDIA Tools Extension](https://developer.nvidia.com/blog/nvidia-tools-extension-api-nvtx-annotation-tool-for-profiling-code-in-python-and-c-c/) (NVTX)
+  * Integration of [cuCIM](https://github.com/rapidsai/cucim)
+  * Stain normalization and contextual grid for digital pathology
+* `Transchex` network for vision-language transformers for chest X-ray analysis
+* `DatasetSummary` utility in `monai.data`
+* `WarmupCosineSchedule`
+* Deprecation warnings and documentation support for better backwards compatibility
+* Padding with additional `kwargs` and different backend API
+* Additional options such as `dropout` and `norm` in various networks and their submodules
+
+### Changed
+* Base Docker image upgraded to `nvcr.io/nvidia/pytorch:21.08-py3` from `nvcr.io/nvidia/pytorch:21.06-py3`
+* Deprecated input argument `n_classes`, in favor of `num_classes`
+* Deprecated input argument `dimensions` and `ndims`, in favor of `spatial_dims`
+* Updated the Sphinx-based documentation theme for better readability
+* `NdarrayTensor` type is replaced by `NdarrayOrTensor` for simpler annotations
+* Self-attention-based network blocks now support both 2D and 3D inputs
+
+### Removed
+* The deprecated `TransformInverter`, in favor of `monai.transforms.InvertD`
+* GitHub self-hosted CI/CD pipelines for nightly and post-merge tests
+* `monai.handlers.utils.evenly_divisible_all_gather`
+* `monai.handlers.utils.string_list_all_gather`
+
+### Fixed
+* A Multi-thread cache writing issue in `LMDBDataset`
+* Output shape convention inconsistencies of the image readers
+* Output directory and file name flexibility issue for `NiftiSaver`, `PNGSaver`
+* Requirement of the `label` field in test-time augmentation
+* Input argument flexibility issues for  `ThreadDataLoader`
+* Decoupled `Dice` and `CrossEntropy` intermediate results in `DiceCELoss`
+* Improved documentation, code examples, and warning messages in various modules
+* Various usability issues reported by users
 
 ## [0.6.0] - 2021-07-08
 ### Added
@@ -25,6 +68,7 @@ and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.
 * Fully compatible with PyTorch 1.9
 * `--disttests` and `--min` options for `runtests.sh`
 * Initial support of pre-merge tests with Nvidia Blossom system
+
 ### Changed
 * Base Docker image upgraded to `nvcr.io/nvidia/pytorch:21.06-py3` from
   `nvcr.io/nvidia/pytorch:21.04-py3`
@@ -34,11 +78,13 @@ and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.
 * Unified the terms: `post_transform` is renamed to `postprocessing`, `pre_transform` is renamed to `preprocessing`
 * Unified the postprocessing transforms and event handlers to accept the "channel-first" data format
 * `evenly_divisible_all_gather` and `string_list_all_gather` moved to `monai.utils.dist`
+
 ### Removed
 * Support of 'batched' input for postprocessing transforms and event handlers
 * `TorchVisionFullyConvModel`
 * `set_visible_devices` utility function
 * `SegmentationSaver` and `TransformsInverter` handlers
+
 ### Fixed
 * Issue of handling big-endian image headers
 * Multi-thread issue for non-random transforms in the cache-based datasets
@@ -269,9 +315,11 @@ the postprocessing steps should be used before calling the metrics methods
 * Optionally depend on PyTorch-Ignite v0.4.2 instead of v0.3.0
 * Optionally depend on torchvision, ITK
 * Enhanced CI tests with 8 new testing environments
+
 ### Removed
 * `MONAI/examples` folder (relocated into [`Project-MONAI/tutorials`](https://github.com/Project-MONAI/tutorials))
 * `MONAI/research` folder (relocated to [`Project-MONAI/research-contributions`](https://github.com/Project-MONAI/research-contributions))
+
 ### Fixed
 * `dense_patch_slices` incorrect indexing
 * Data type issue in `GeneralizedWassersteinDiceLoss`
@@ -302,6 +350,7 @@ the postprocessing steps should be used before calling the metrics methods
 * Cross-platform CI tests supporting multiple Python versions
 * Optional import mechanism
 * Experimental features for third-party transforms integration
+
 ### Changed
 > For more details please visit [the project wiki](https://github.com/Project-MONAI/MONAI/wiki/Notable-changes-between-0.1.0-and-0.2.0)
 * Core modules now require numpy >= 1.17
@@ -311,9 +360,11 @@ the postprocessing steps should be used before calling the metrics methods
 * Base Docker image upgraded to `nvcr.io/nvidia/pytorch:20.03-py3` from `nvcr.io/nvidia/pytorch:19.10-py3`
 * Enhanced local testing tools
 * Documentation website domain changed to https://docs.monai.io
+
 ### Removed
 * Support of Python < 3.6
 * Automatic installation of optional dependencies including pytorch-ignite, nibabel, tensorboard, pillow, scipy, scikit-image
+
 ### Fixed
 * Various issues in type and argument names consistency
 * Various issues in docstring and documentation site
@@ -336,7 +387,8 @@ the postprocessing steps should be used before calling the metrics methods
 
 [highlights]: https://github.com/Project-MONAI/MONAI/blob/master/docs/source/highlights.md
 
-[Unreleased]: https://github.com/Project-MONAI/MONAI/compare/0.6.0...HEAD
+[Unreleased]: https://github.com/Project-MONAI/MONAI/compare/0.7.0...HEAD
+[0.7.0]: https://github.com/Project-MONAI/MONAI/compare/0.6.0...0.7.0
 [0.6.0]: https://github.com/Project-MONAI/MONAI/compare/0.5.3...0.6.0
 [0.5.3]: https://github.com/Project-MONAI/MONAI/compare/0.5.0...0.5.3
 [0.5.0]: https://github.com/Project-MONAI/MONAI/compare/0.4.0...0.5.0

CONTRIBUTING.md

@@ -289,9 +289,9 @@ When major features are ready for a milestone, to prepare for a new release:
   repository's artifacts (e.g. the file at https://github.com/Project-MONAI/MONAI/actions/runs/66570977).
 - Check the release test at [TestPyPI](https://test.pypi.org/project/monai/), download the artifacts when the CI finishes.
 - Optionally run [the cron testing jobs](https://github.com/Project-MONAI/MONAI/blob/dev/.github/workflows/cron.yml) on `releasing/[version number]`.
+- Rebase `releasing/[version number]` to `main`, make sure all the test pipelines succeed.
 - Once the release candidate is verified, tag and push a milestone, for example, `git push origin 0.1.0`.
   The tag must be with the latest commit of `releasing/[version number]`.
-- Rebase `releasing/[version number]` to `main`, make sure all the test pipelines succeed.
 - Upload the packages to [PyPI](https://pypi.org/project/monai/).
   This could be done manually by ``twine upload dist/*``, given the artifacts are unzipped to the folder ``dist/``.
 - Merge `releasing/[version number]` to `dev`, this step must make sure that the tagging commit unchanged on `dev`.

README.md

@@ -19,7 +19,7 @@ Its ambitions are:
 
 ## Features
 > _The codebase is currently under active development._
-> _Please see [the technical highlights](https://docs.monai.io/en/latest/highlights.html) and [What's New in 0.6](https://docs.monai.io/en/latest/whatsnew_0_6.html) of the current milestone release._
+> _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 current milestone release._
 
 - flexible pre-processing for multi-dimensional medical imaging data;
 - compositional & portable APIs for ease of integration in existing workflows;

docs/requirements.txt

@@ -1,6 +1,6 @@
 -f https://download.pytorch.org/whl/cpu/torch-1.6.0%2Bcpu-cp37-cp37m-linux_x86_64.whl
 torch>=1.5
-pytorch-ignite==0.4.5
+pytorch-ignite==0.4.6
 numpy>=1.17
 itk>=5.2
 nibabel
@@ -20,3 +20,4 @@ sphinxcontrib-serializinghtml
 sphinx-autodoc-typehints==1.11.1
 pandas
 einops
+transformers

docs/source/conf.py

@@ -18,7 +18,7 @@
 sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..")))
 print(sys.path)
 
-import monai  # noqa: E402
+import monai
 
 # -- Project information -----------------------------------------------------
 project = "MONAI"

docs/source/handlers.rst

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