Function create_workflow

monai/bundle/scripts.py:1921–1975

Specify `bundle workflow` to create monai bundle workflows. The workflow should be subclass of `BundleWorkflow` and be available to import. It can be MONAI existing bundle workflows or user customized workflows. Typical usage examples: .. code-block:: python # Specify

(
    workflow_name: str | BundleWorkflow | None = None,
    config_file: str | Sequence[str] | None = None,
    args_file: str | None = None,
    **kwargs: Any,
)

def create_workflow(
    workflow_name: str | BundleWorkflow | None = None,
    config_file: str | Sequence[str] | None = None,
    args_file: str | None = None,
    **kwargs: Any,
) -> Any:
    """
    Specify `bundle workflow` to create monai bundle workflows.
    The workflow should be subclass of `BundleWorkflow` and be available to import.
    It can be MONAI existing bundle workflows or user customized workflows.

    Typical usage examples:

    .. code-block:: python

        # Specify config_file path to create workflow:
        workflow = create_workflow(config_file="/workspace/spleen_ct_segmentation/configs/train.json", workflow_type="train")

        # Set the workflow to other customized BundleWorkflow subclass to create workflow:
        workflow = create_workflow(workflow_name=CustomizedWorkflow)

    Args:
        workflow_name: specified bundle workflow name, should be a string or class, default to "ConfigWorkflow".
        config_file: filepath of the config file, if it is a list of file paths, the content of them will be merged.
        args_file: a JSON or YAML file to provide default values for this API.
            so that the command line inputs can be simplified.
        kwargs: arguments to instantiate the workflow class.

    """
    _args = update_kwargs(args=args_file, workflow_name=workflow_name, config_file=config_file, **kwargs)
    workflow_name, config_file = _pop_args(
        _args, workflow_name=ConfigWorkflow, config_file=None
    )  # the default workflow name is "ConfigWorkflow"
    if isinstance(workflow_name, str):
        workflow_class, has_built_in = optional_import("monai.bundle", name=str(workflow_name))  # search built-in
        if not has_built_in:
            workflow_class = locate(str(workflow_name))  # search dotted path
        if workflow_class is None:
            raise ValueError(f"cannot locate specified workflow class: {workflow_name}.")
    elif issubclass(workflow_name, BundleWorkflow):  # type: ignore
        workflow_class = workflow_name
    else:
        raise ValueError(
            "Argument `workflow_name` must be a bundle workflow class name"
            f"or subclass of BundleWorkflow, got: {workflow_name}."
        )

    if config_file is not None:
        workflow_ = workflow_class(config_file=config_file, **_args)
    else:
        workflow_ = workflow_class(**_args)

    workflow_.initialize()
    _log_input_summary(tag="run", args=_args)
    return workflow_


def download_large_files(bundle_path: str | None = None, large_file_name: str | None = None) -> None: