Merge branch 'dev' into feature/7405-mlflow-system-metrics

Author: uditmahato

.github/workflows/cicd_tests.yml

@@ -56,7 +56,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        opt: ["codeformat", "mypy"]  #  "pytype" omitted for being essentially deprecated, see #8865
+        opt: ["codeformat", "pyrefly"]
     steps:
     - name: Clean unused tools
       run: |
@@ -80,8 +80,7 @@ jobs:
       run: |
         # clean up temporary files
         $(pwd)/runtests.sh --build --clean
-        # Github actions have multiple cores, so parallelize pytype
-        $(pwd)/runtests.sh --build --${{ matrix.opt }} -j $(nproc --all)
+        $(pwd)/runtests.sh --build --${{ matrix.opt }}
 
   min-dep:  # Test with minumum dependencies installed for different OS, Python, and PyTorch combinations
     runs-on: ${{ matrix.os }}

.github/workflows/cron.yml

@@ -214,7 +214,7 @@ jobs:
         python -c "import torch; print(torch.__version__); print('{} of GPUs available'.format(torch.cuda.device_count()))"
         python -c 'import torch; print(torch.rand(5,3, device=torch.device("cuda:0")))'
         ngc --version
-        BUILD_MONAI=1 ./runtests.sh --build --coverage --unittests --disttests  # unit tests with pytype checks, coverage report
+        BUILD_MONAI=1 ./runtests.sh --build --coverage --pyrefly --unittests --disttests  # unit tests with pyrefly checks, coverage report
         BUILD_MONAI=1 ./runtests.sh --build --coverage --net  # integration tests with coverage report
         coverage xml --ignore-errors
         if pgrep python; then pkill python; fi

.github/workflows/weekly-preview.yml

@@ -12,7 +12,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        opt: ["codeformat", "mypy"]
+        opt: ["codeformat", "pyrefly"]
     steps:
     - name: Clean unused tools
       run: |

.gitignore

@@ -110,12 +110,17 @@ venv.bak/
 # pytype cache
 .pytype/
 
+# pyrefly cache
+.pyrefly_cache/
+
 # mypy
 .mypy_cache/
+.dmypy.json
+
 examples/scd_lvsegs.npz
 temp/
 .idea/
-.dmypy.json
+.plans/
 
 *~
 

CHANGELOG.md

@@ -5,6 +5,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 ## [Unreleased]
 ### Added
+* `NaViT` (`monai.networks.nets.NaViT`): Native Resolution Vision Transformer with Patch n' Pack, supporting variable-resolution 2D and 3D inputs. Implements factorized positional embeddings, token dropout, attention pooling, and QK normalization, based on ["Patch n' Pack: NaViT, a Vision Transformer for any Aspect Ratio and Resolution"](https://arxiv.org/abs/2307.06304).
 * `HyenaMixer`, `HyenaTransformerBlock`, and `DepthwiseFFTConv{2,3}d` in `monai.networks.blocks`: subquadratic O(N log N) alternatives to windowed self-attention, backed by the HyenaND operator from the optional `nvsubquadratic` package.
 * `HyenaNDUNETR` (`monai.networks.nets.HyenaNDUNETR`): thin `SwinUNETR` subclass with a `get_variant(name)` classmethod for the three Hyena variants (`HHHH`, `HAHA`, `HHAA`) from the NeurIPS 2026 paper "Native Multi-Dimensional Subquadratic Operators via Input Dependent Long Convolutions" (paper id 26539).
 * `SwinUNETR.use_hyena` and `SwinUNETR.hyena_stages` kwargs to thread HyenaND blocks through any subset of Swin stages. Default `use_hyena=False` preserves bit-identical forward behavior of the existing code path.

CONTRIBUTING.md

@@ -38,7 +38,7 @@ Please note that, as per PyTorch, MONAI uses American English spelling. This mea
 ### Preparing pull requests
 
 To ensure the code quality, MONAI relies on several linting tools ([black](https://github.com/psf/black), [isort](https://github.com/timothycrosley/isort), [ruff](https://github.com/astral-sh/ruff)),
-static type analysis tools ([mypy](https://github.com/python/mypy), [pytype](https://github.com/google/pytype)), as well as a set of unit/integration tests.
+static type analysis tools ([pyrefly](https://github.com/facebook/pyrefly)), as well as a set of unit/integration tests.
 
 This section highlights all the necessary preparation steps required before sending a pull request.
 To collaborate efficiently, please read through this section and follow them.

docs/source/networks.rst

@@ -662,6 +662,11 @@ Nets
 .. autoclass:: VarAutoEncoder
   :members:
 
+`NaViT`
+~~~~~~~
+.. autoclass:: NaViT
+  :members:
+
 `ViT`
 ~~~~~
 .. autoclass:: ViT

monai/apps/auto3dseg/auto_runner.py

@@ -790,6 +790,7 @@ def _train_algo_in_nni(self, history: list[dict[str, Any]]) -> None:
             nni_config_filename = os.path.abspath(os.path.join(self.work_dir, f"{name}_nni_config.yaml"))
             ConfigParser.export_config_file(nni_config, nni_config_filename, fmt="yaml", default_flow_style=None)
 
+            # pyrefly: ignore [redundant-cast]
             max_trial = min(self.hpo_tasks, cast(int, default_nni_config["maxTrialNumber"]))
             cmd = "nnictl create --config " + nni_config_filename + " --port 8088"
 
@@ -805,6 +806,7 @@ def _train_algo_in_nni(self, history: list[dict[str, Any]]) -> None:
                 n_trainings = len(import_bundle_algo_history(self.work_dir, only_trained=True))
 
             cmd = "nnictl stop --all"
+            # pyrefly: ignore [bad-argument-type]
             run_cmd(cmd.split(), check=True)
             logger.info(f"NNI completes HPO on {name}")
             last_total_tasks = n_trainings

monai/apps/deepedit/transforms.py

@@ -434,6 +434,7 @@ def _randomize(self, d, key_label):
         else:
             logger.info(f"Not slice IDs for label: {key_label}")
             sid = None
+        # pyrefly: ignore [unsupported-operation]
         self.sid[key_label] = sid
 
     def __call__(self, data: Mapping[Hashable, np.ndarray]) -> dict[Hashable, np.ndarray]:
@@ -561,6 +562,7 @@ def __init__(
         self.guidance: dict[str, list[list[int]]] = {}
 
     def randomize(self, data=None):
+        # pyrefly: ignore [unsupported-operation]
         probability = data[self.probability]
         self._will_interact = self.R.choice([True, False], p=[probability, 1.0 - probability])
 
@@ -885,6 +887,7 @@ def _randomize(self, d, key_label):
         else:
             logger.info(f"Not slice IDs for label: {key_label}")
             sid = None
+        # pyrefly: ignore [unsupported-operation]
         self.sid[key_label] = sid
 
     def __call__(self, data: Mapping[Hashable, np.ndarray]) -> dict[Hashable, np.ndarray]:

monai/apps/deepgrow/dataset.py

@@ -175,6 +175,7 @@ def _save_data_2d(vol_idx, vol_image, vol_label, dataset_dir, relative_path):
             continue
 
         # For all Labels
+        # pyrefly: ignore [missing-attribute]
         unique_labels = np.unique(label.flatten())
         unique_labels = unique_labels[unique_labels != 0]
         unique_labels_count = max(unique_labels_count, len(unique_labels))