add nnunetv2 runner class (#5987)

Signed-off-by: dongy <dongy@nvidia.com>

### Description

Adding nnunetv2 runner class to launch different steps in nnunet via
Python APIs.

### Types of changes
<!--- Put an `x` in all the boxes that apply, and remove the not
applicable items -->
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [ ] Breaking change (fix or new feature that would cause existing
functionality to change).
- [ ] New tests added to cover the changes.
- [ ] Integration tests passed locally by running `./runtests.sh -f -u
--net --coverage`.
- [ ] Quick tests passed locally by running `./runtests.sh --quick
--unittests --disttests`.
- [ ] In-line docstrings updated.
- [ ] Documentation updated, tested `make html` command in the `docs/`
folder.

---------

Signed-off-by: dongy <dongy@nvidia.com>
Signed-off-by: Wenqi Li <wenqil@nvidia.com>
Co-authored-by: dongy <dongy@nvidia.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Wenqi Li <wenqil@nvidia.com>

docs/source/apps.rst

@@ -274,7 +274,13 @@ FastMRIReader
 
 `auto3dseg`
 -----------
-
 .. automodule:: monai.apps.auto3dseg
   :members:
   :imported-members:
+
+`nnUNet`
+--------
+.. automodule:: monai.apps.nnunet.__main__
+
+.. autoclass:: monai.apps.nnunet.nnUNetV2Runner
+  :members:

monai/__init__.py

@@ -50,6 +50,7 @@
         "(^(monai._C))",
         "(.*(__main__)$)",
         "(.*(video_dataset)$)",
+        "(.*(nnunet).*$)",
     ]
 )
 

monai/apps/nnunet/__init__.py

@@ -0,0 +1,15 @@
+# Copyright (c) MONAI Consortium
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#     http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from __future__ import annotations
+
+from .nnunetv2_runner import nnUNetV2Runner
+from .utils import NNUNETMode, analyze_data, create_new_data_copy, create_new_dataset_json

monai/apps/nnunet/__main__.py

@@ -0,0 +1,97 @@
+# Copyright (c) MONAI Consortium
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#     http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""
+Examples:
+    - User can use the one-liner to start the nnU-Net workflow
+
+    .. code-block:: bash
+
+        python -m monai.apps.nnunet nnUNetV2Runner run --input "./input.yaml"
+
+    - convert dataset
+
+    .. code-block:: bash
+
+        python -m monai.apps.nnunet nnUNetRunner convert_dataset --input "./input_new.yaml"
+
+    - convert msd datasets
+
+    .. code-block:: bash
+
+        python -m monai.apps.nnunet nnUNetRunner convert_msd_dataset \\
+            --input "./input.yaml" --data_dir "Task05_Prostate"
+
+    - experiment planning and data pre-processing
+
+    .. code-block:: bash
+
+        python -m monai.apps.nnunet nnUNetRunner plan_and_process --input "./input.yaml"
+
+    - single-gpu training for all 20 models
+
+    .. code-block:: bash
+
+        python -m monai.apps.nnunet nnUNetV2Runner train --input "./input.yaml"
+
+    - single-gpu training for a single model
+
+    .. code-block:: bash
+
+        python -m monai.apps.nnunet nnUNetV2Runner train_single_model --input "./input.yaml" \\
+            --config "3d_fullres" \\
+            --fold 0 \\
+            --trainer_class_name "nnUNetTrainer_5epochs" \\
+            --export_validation_probabilities true
+
+    - multi-gpu training for all 20 models
+
+    .. code-block:: bash
+
+        export CUDA_VISIBLE_DEVICES=0,1  # optional
+        python -m monai.apps.nnunet nnUNetV2Runner train --input "./input.yaml" --num_gpus 2
+
+    - multi-gpu training for a single model
+
+    .. code-block:: bash
+
+        export CUDA_VISIBLE_DEVICES=0,1 # optional
+        python -m monai.apps.nnunet nnUNetV2Runner train_single_model --input "./input.yaml" \\
+            --config "3d_fullres" \\
+            --fold 0 \\
+            --trainer_class_name "nnUNetTrainer_5epochs" \\
+            --export_validation_probabilities true \\
+            --num_gpus 2
+
+    - find best configuration
+
+    .. code-block:: bash
+
+        python -m monai.apps.nnunet nnUNetRunner find_best_configuration --input "./input.yaml"
+
+    - predict, ensemble, and post-process
+
+    .. code-block:: bash
+
+        python -m monai.apps.nnunet nnUNetRunner predict_ensemble_postprocessing --input "./input.yaml"
+
+"""
+
+
+from __future__ import annotations
+
+from monai.apps.nnunet.nnunetv2_runner import nnUNetV2Runner
+
+if __name__ == "__main__":
+    from monai.utils import optional_import
+
+    fire, _ = optional_import("fire")
+    fire.Fire({"nnUNetV2Runner": nnUNetV2Runner})