Avoid breaking change in creating BundleWorkflow (#6950)

Fixes # .

### Description
Avoid breaking changes introduced by
#6835
- when creating `BundleWorkflow`
- when using `load` API, add `return_state_dict` when `model` and
`net_name` are both `None`.

### 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: KumoLiu <[email protected]>
Signed-off-by: YunLiu <[email protected]>
Co-authored-by: Eric Kerfoot <[email protected]>

monai/bundle/scripts.py

@@ -28,6 +28,7 @@
 
 from monai.apps.mmars.mmars import _get_all_ngc_models
 from monai.apps.utils import _basename, download_url, extractall, get_logger
+from monai.bundle.config_item import ConfigComponent
 from monai.bundle.config_parser import ConfigParser
 from monai.bundle.utils import DEFAULT_INFERENCE, DEFAULT_METADATA
 from monai.bundle.workflows import BundleWorkflow, ConfigWorkflow
@@ -247,7 +248,7 @@ def _process_bundle_dir(bundle_dir: PathLike | None = None) -> Path:
     return Path(bundle_dir)
 
 
-@deprecated_arg_default("source", "github", "monaihosting", since="1.3", replaced="1.4")
+@deprecated_arg_default("source", "github", "monaihosting", since="1.3", replaced="1.5")
 def download(
     name: str | None = None,
     version: str | None = None,
@@ -375,8 +376,9 @@ def download(
             )
 
 
-@deprecated_arg("net_name", since="1.3", removed="1.4", msg_suffix="please use ``model`` instead.")
-@deprecated_arg("net_kwargs", since="1.3", removed="1.3", msg_suffix="please use ``model`` instead.")
+@deprecated_arg("net_name", since="1.3", removed="1.5", msg_suffix="please use ``model`` instead.")
+@deprecated_arg("net_kwargs", since="1.3", removed="1.5", msg_suffix="please use ``model`` instead.")
+@deprecated_arg("return_state_dict", since="1.3", removed="1.5")
 def load(
     name: str,
     model: torch.nn.Module | None = None,
@@ -395,8 +397,10 @@ def load(
     workflow_name: str | BundleWorkflow | None = None,
     args_file: str | None = None,
     copy_model_args: dict | None = None,
+    return_state_dict: bool = True,
+    net_override: dict | None = None,
     net_name: str | None = None,
-    **net_override: Any,
+    **net_kwargs: Any,
 ) -> object | tuple[torch.nn.Module, dict, dict] | Any:
     """
     Load model weights or TorchScript module of a bundle.
@@ -441,7 +445,12 @@ def load(
         workflow_name: specified bundle workflow name, should be a string or class, default to "ConfigWorkflow".
         args_file: a JSON or YAML file to provide default values for all the args in "download" function.
         copy_model_args: other arguments for the `monai.networks.copy_model_state` function.
-        net_override: id-value pairs to override the parameters in the network of the bundle.
+        return_state_dict: whether to return state dict, if True, return state_dict, else a corresponding network
+            from `_workflow.network_def` will be instantiated and load the achieved weights.
+        net_override: id-value pairs to override the parameters in the network of the bundle, default to `None`.
+        net_name: if not `None`, a corresponding network will be instantiated and load the achieved weights.
+            This argument only works when loading weights.
+        net_kwargs: other arguments that are used to instantiate the network class defined by `net_name`.
 
     Returns:
         1. If `load_ts_module` is `False` and `model` is `None`,
@@ -452,9 +461,15 @@ def load(
         3. If `load_ts_module` is `True`, return a triple that include a TorchScript module,
             the corresponding metadata dict, and extra files dict.
             please check `monai.data.load_net_with_metadata` for more details.
+        4. If `return_state_dict` is True, return model weights, only used for compatibility
+            when `model` and `net_name` are all `None`.
 
     """
+    if return_state_dict and (model is not None or net_name is not None):
+        warnings.warn("Incompatible values: model and net_name are all specified, return state dict instead.")
+
     bundle_dir_ = _process_bundle_dir(bundle_dir)
+    net_override = {} if net_override is None else net_override
     copy_model_args = {} if copy_model_args is None else copy_model_args
 
     if device is None:
@@ -466,7 +481,7 @@ def load(
         if remove_prefix:
             name = _remove_ngc_prefix(name, prefix=remove_prefix)
     full_path = os.path.join(bundle_dir_, name, model_file)
-    if not os.path.exists(full_path) or model is None:
+    if not os.path.exists(full_path):
         download(
             name=name,
             version=version,
@@ -477,34 +492,52 @@ def load(
             progress=progress,
             args_file=args_file,
         )
-        train_config_file = bundle_dir_ / name / "configs" / f"{workflow_type}.json"
-        if train_config_file.is_file():
-            _net_override = {f"network_def#{key}": value for key, value in net_override.items()}
-            _workflow = create_workflow(
-                workflow_name=workflow_name,
-                args_file=args_file,
-                config_file=str(train_config_file),
-                workflow_type=workflow_type,
-                **_net_override,
-            )
-        else:
-            _workflow = None
 
     # loading with `torch.jit.load`
     if load_ts_module is True:
         return load_net_with_metadata(full_path, map_location=torch.device(device), more_extra_files=config_files)
     # loading with `torch.load`
     model_dict = torch.load(full_path, map_location=torch.device(device))
+
     if not isinstance(model_dict, Mapping):
         warnings.warn(f"the state dictionary from {full_path} should be a dictionary but got {type(model_dict)}.")
         model_dict = get_state_dict(model_dict)
 
-    if model is None and _workflow is None:
+    if return_state_dict:
         return model_dict
-    model = _workflow.network_def if model is None else model
-    model.to(device)
 
-    copy_model_state(dst=model, src=model_dict if key_in_ckpt is None else model_dict[key_in_ckpt], **copy_model_args)
+    _workflow = None
+    if model is None and net_name is None:
+        bundle_config_file = bundle_dir_ / name / "configs" / f"{workflow_type}.json"
+        if bundle_config_file.is_file():
+            _net_override = {f"network_def#{key}": value for key, value in net_override.items()}
+            _workflow = create_workflow(
+                workflow_name=workflow_name,
+                args_file=args_file,
+                config_file=str(bundle_config_file),
+                workflow_type=workflow_type,
+                **_net_override,
+            )
+        else:
+            warnings.warn(f"Cannot find the config file: {bundle_config_file}, return state dict instead.")
+            return model_dict
+        if _workflow is not None:
+            if not hasattr(_workflow, "network_def"):
+                warnings.warn("No available network definition in the bundle, return state dict instead.")
+                return model_dict
+            else:
+                model = _workflow.network_def
+    elif net_name is not None:
+        net_kwargs["_target_"] = net_name
+        configer = ConfigComponent(config=net_kwargs)
+        model = configer.instantiate()  # type: ignore
+
+    model.to(device)  # type: ignore
+
+    copy_model_state(
+        dst=model, src=model_dict if key_in_ckpt is None else model_dict[key_in_ckpt], **copy_model_args  # type: ignore
+    )
+
     return model
 
 

monai/bundle/workflows.py

@@ -43,6 +43,10 @@ class BundleWorkflow(ABC):
             or "infer", "inference", "eval", "evaluation" for a inference workflow,
             other unsupported string will raise a ValueError.
             default to `None` for common workflow.
+        workflow: specifies the workflow type: "train" or "training" for a training workflow,
+            or "infer", "inference", "eval", "evaluation" for a inference workflow,
+            other unsupported string will raise a ValueError.
+            default to `None` for common workflow.
 
     """
 
@@ -56,7 +60,8 @@ class BundleWorkflow(ABC):
         new_name="workflow_type",
         msg_suffix="please use `workflow_type` instead.",
     )
-    def __init__(self, workflow_type: str | None = None):
+    def __init__(self, workflow_type: str | None = None, workflow: str | None = None):
+        workflow_type = workflow if workflow is not None else workflow_type
         if workflow_type is None:
             self.properties = copy(MetaProperties)
             self.workflow_type = None
@@ -198,6 +203,10 @@ class ConfigWorkflow(BundleWorkflow):
             or "infer", "inference", "eval", "evaluation" for a inference workflow,
             other unsupported string will raise a ValueError.
             default to `None` for common workflow.
+        workflow: specifies the workflow type: "train" or "training" for a training workflow,
+            or "infer", "inference", "eval", "evaluation" for a inference workflow,
+            other unsupported string will raise a ValueError.
+            default to `None` for common workflow.
         override: id-value pairs to override or add the corresponding config content.
             e.g. ``--net#input_chns 42``, ``--net %/data/other.json#net_arg``
 
@@ -221,8 +230,10 @@ def __init__(
         final_id: str = "finalize",
         tracking: str | dict | None = None,
         workflow_type: str | None = None,
+        workflow: str | None = None,
         **override: Any,
     ) -> None:
+        workflow_type = workflow if workflow is not None else workflow_type
         super().__init__(workflow_type=workflow_type)
         if config_file is not None:
             _config_files = ensure_tuple(config_file)

tests/ngc_bundle_download.py

@@ -83,7 +83,12 @@ def test_ngc_download_bundle(self, bundle_name, version, remove_prefix, download
                 self.assertTrue(check_hash(filepath=full_file_path, val=hash_val))
 
                 model = load(
-                    name=bundle_name, source="ngc", version=version, bundle_dir=tempdir, remove_prefix=remove_prefix
+                    name=bundle_name,
+                    source="ngc",
+                    version=version,
+                    bundle_dir=tempdir,
+                    remove_prefix=remove_prefix,
+                    return_state_dict=False,
                 )
                 assert_allclose(
                     model.state_dict()[TESTCASE_WEIGHTS["key"]],

tests/test_bundle_download.py

@@ -146,6 +146,7 @@ def test_load_weights(self, bundle_files, bundle_name, repo, device, model_file)
                     source="github",
                     progress=False,
                     device=device,
+                    return_state_dict=True,
                 )
 
                 # prepare network
@@ -174,21 +175,44 @@ def test_load_weights(self, bundle_files, bundle_name, repo, device, model_file)
                     bundle_dir=tempdir,
                     progress=False,
                     device=device,
-                    net_name=model_name,
                     source="github",
+                    return_state_dict=False,
                 )
                 model_2.eval()
                 output_2 = model_2.forward(input_tensor)
                 assert_allclose(output_2, expected_output, atol=1e-4, rtol=1e-4, type_test=False)
 
+                # test compatibility with return_state_dict=True.
+                model_3 = load(
+                    name=bundle_name,
+                    model_file=model_file,
+                    bundle_dir=tempdir,
+                    progress=False,
+                    device=device,
+                    net_name=model_name,
+                    source="github",
+                    return_state_dict=False,
+                    **net_args,
+                )
+                model_3.eval()
+                output_3 = model_3.forward(input_tensor)
+                assert_allclose(output_3, expected_output, atol=1e-4, rtol=1e-4, type_test=False)
+
     @parameterized.expand([TEST_CASE_7])
     @skip_if_quick
     def test_load_weights_with_net_override(self, bundle_name, device, net_override):
         with skip_if_downloading_fails():
             # download bundle, and load weights from the downloaded path
             with tempfile.TemporaryDirectory() as tempdir:
                 # load weights
-                model = load(name=bundle_name, bundle_dir=tempdir, source="monaihosting", progress=False, device=device)
+                model = load(
+                    name=bundle_name,
+                    bundle_dir=tempdir,
+                    source="monaihosting",
+                    progress=False,
+                    device=device,
+                    return_state_dict=False,
+                )
 
                 # prepare data and test
                 input_tensor = torch.rand(1, 1, 96, 96, 96).to(device)
@@ -209,7 +233,8 @@ def test_load_weights_with_net_override(self, bundle_name, device, net_override)
                     source="monaihosting",
                     progress=False,
                     device=device,
-                    **net_override,
+                    return_state_dict=False,
+                    net_override=net_override,
                 )
 
                 # prepare data and test