Fix nnUNet runner store_true flag command construction (#8941) (#8944)

### Description

`nnUNetV2Runner.train_single_model_command` builds the `nnUNetv2_train`
argv by iterating `kwargs` and always appending `str(_value)`, so
documented `store_true` flags were emitted with a value instead of bare.
Passing `c=True` produced `--c True`, `val=True` produced `--val True`,
and likewise for `use_compressed` and `disable_checkpointing`.
`nnUNetv2_train` declares these as `store_true`, so the trailing `True`
is parsed as a positional argument and the command fails. A falsy
`pretrained_weights` was similarly emitted as `-pretrained_weights
False` instead of being omitted.

The builder now appends `store_true` flags only when their value is
truthy and skips them otherwise, and includes `pretrained_weights`/`-p`
only when given a real path. Regular value kwargs and the existing
`--npz` handling are unchanged.

Fixes #8941, originally flagged in a review thread on #8887.

### Types of changes
- [x] Non-breaking change (fix or new feature that would not break
existing functionality).
- [x] 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.

---------

Signed-off-by: Soumya Snigdha Kundu <soumya_snigdha.kundu@kcl.ac.uk>

Author: aymuos15

monai/apps/nnunet/nnunetv2_runner.py

@@ -596,9 +596,16 @@ def train_single_model_command(
         if self.export_validation_probabilities:
             cmd.append("--npz")
 
+        store_true_flags = {"c", "val", "use_compressed", "disable_checkpointing"}
         for _key, _value in kwargs.items():
-            prefix = "-" if _key in {"p", "pretrained_weights"} else "--"
-            cmd += [f"{prefix}{_key}", str(_value)]
+            if _key in store_true_flags:
+                if _value:
+                    cmd.append(f"--{_key}")
+            elif _key in {"p", "pretrained_weights"}:
+                if _value:
+                    cmd += [f"-{_key}", str(_value)]
+            else:
+                cmd += [f"--{_key}", str(_value)]
 
         cmd_str: list[str] = [str(c) for c in cmd]
 
@@ -758,7 +765,7 @@ def validate_single_model(self, config: str, fold: int, **kwargs: Any) -> None:
             kwargs: this optional parameter allows you to specify additional arguments defined in the
                 ``train_single_model`` method.
         """
-        self.train_single_model(config=config, fold=fold, only_run_validation=True, **kwargs)
+        self.train_single_model(config=config, fold=fold, val=True, **kwargs)
 
     def validate(
         self, configs: tuple = (M.N_3D_FULLRES, M.N_2D, M.N_3D_LOWRES, M.N_3D_CASCADE_FULLRES), **kwargs: Any

tests/apps/nnunet/__init__.py

@@ -0,0 +1,10 @@
+# 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.

tests/apps/nnunet/test_nnunetv2_runner_command.py

@@ -0,0 +1,78 @@
+# 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
+
+import unittest
+from unittest import mock
+
+from monai.apps.nnunet.nnunetv2_runner import nnUNetV2Runner
+
+
+def _make_runner(export_validation_probabilities=False):
+    runner = nnUNetV2Runner.__new__(nnUNetV2Runner)
+    runner.dataset_name_or_id = "001"
+    runner.trainer_class_name = "nnUNetTrainer"
+    runner.export_validation_probabilities = export_validation_probabilities
+    return runner
+
+
+class TestTrainSingleModelCommand(unittest.TestCase):
+    def test_store_true_flags_emit_bare(self):
+        runner = _make_runner()
+        cmd, _ = runner.train_single_model_command(
+            "3d_fullres", 0, 0, {"c": True, "val": True, "use_compressed": True, "disable_checkpointing": True}
+        )
+        for flag in ("--c", "--val", "--use_compressed", "--disable_checkpointing"):
+            self.assertIn(flag, cmd)
+        self.assertNotIn("True", cmd)
+
+    def test_store_true_flags_false_omitted(self):
+        runner = _make_runner()
+        cmd, _ = runner.train_single_model_command(
+            "3d_fullres", 0, 0, {"c": False, "val": False, "use_compressed": False, "disable_checkpointing": False}
+        )
+        for flag in ("--c", "--val", "--use_compressed", "--disable_checkpointing"):
+            self.assertNotIn(flag, cmd)
+        self.assertNotIn("False", cmd)
+
+    def test_pretrained_weights_truthy_included(self):
+        runner = _make_runner()
+        cmd, _ = runner.train_single_model_command("3d_fullres", 0, 0, {"pretrained_weights": "/path/to/weights.pth"})
+        self.assertIn("-pretrained_weights", cmd)
+        self.assertIn("/path/to/weights.pth", cmd)
+
+    def test_pretrained_weights_falsy_omitted(self):
+        runner = _make_runner()
+        cmd, _ = runner.train_single_model_command("3d_fullres", 0, 0, {"pretrained_weights": False})
+        self.assertNotIn("-pretrained_weights", cmd)
+        self.assertNotIn("False", cmd)
+
+    def test_value_kwargs_unaffected(self):
+        runner = _make_runner()
+        cmd, _ = runner.train_single_model_command("3d_fullres", 0, 0, {"npz": "something"})
+        self.assertIn("--npz", cmd)
+        self.assertIn("something", cmd)
+
+
+class TestValidateSingleModelCommand(unittest.TestCase):
+    def test_validate_emits_bare_val_flag(self):
+        runner = _make_runner()
+        with mock.patch("monai.apps.nnunet.nnunetv2_runner.run_cmd") as run_cmd:
+            runner.validate_single_model("3d_fullres", 0)
+        cmd = run_cmd.call_args.args[0]
+        self.assertIn("--val", cmd)
+        self.assertNotIn("--only_run_validation", cmd)
+        self.assertNotIn("True", cmd)
+
+
+if __name__ == "__main__":
+    unittest.main()