Class ConfigWorkflow

monai/bundle/workflows.py:361–666

Specification for the config-based bundle workflow. Standardized the `initialize`, `run`, `finalize` behavior in a config-based training, evaluation, or inference. Before `run`, we add bundle root directory to Python search directories automatically. For more information: https://mo

class ConfigWorkflow(BundleWorkflow):
    """
    Specification for the config-based bundle workflow.
    Standardized the `initialize`, `run`, `finalize` behavior in a config-based training, evaluation, or inference.
    Before `run`, we add bundle root directory to Python search directories automatically.
    For more information: https://monai.readthedocs.io/en/latest/mb_specification.html.

    Args:
        config_file: filepath of the config file, if this is a list of file paths, their contents will be merged in order.
        meta_file: filepath of the metadata file, if this is a list of file paths, their contents will be merged in order.
            If None, default to "configs/metadata.json", which is commonly used for bundles in MONAI model zoo.
        logging_file: config file for `logging` module in the program. for more details:
            https://docs.python.org/3/library/logging.config.html#logging.config.fileConfig.
            If None, default to "configs/logging.conf", which is commonly used for bundles in MONAI model zoo.
            If False, the logging logic for the bundle will not be modified.
        init_id: ID name of the expected config expression to initialize before running, default to "initialize".
            allow a config to have no `initialize` logic and the ID.
        run_id: ID name of the expected config expression to run, default to "run".
            to run the config, the target config must contain this ID.
        final_id: ID name of the expected config expression to finalize after running, default to "finalize".
            allow a config to have no `finalize` logic and the ID.
        tracking: if not None, enable the experiment tracking at runtime with optionally configurable and extensible.
            if "mlflow", will add `MLFlowHandler` to the parsed bundle with default tracking settings,
            if other string, treat it as file path to load the tracking settings.
            if `dict`, treat it as tracking settings.
            will patch the target config content with `tracking handlers` and the top-level items of `configs`.
            for detailed usage examples, please check the tutorial:
            https://github.com/Project-MONAI/tutorials/blob/main/experiment_management/bundle_integrate_mlflow.ipynb.
        workflow_type: 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.
        properties_path: the path to the JSON file of properties. If `workflow_type` is specified, properties will be
            loaded from the file based on the provided `workflow_type` and meta. If no `workflow_type` is specified,
            properties will default to loading from "train". If `properties_path` is None, default properties
            will be sourced from "monai/bundle/properties.py" based on the workflow_type:
            For a training workflow, properties load from `TrainProperties` and `MetaProperties`.
            For a inference workflow, properties load from `InferProperties` and `MetaProperties`.
            For workflow_type = None : only `MetaProperties` will be loaded.
        override: id-value pairs to override or add the corresponding config content.
            e.g. ``--net#input_chns 42``, ``--net %/data/other.json#net_arg``

    """

    def __init__(
        self,
        config_file: str | Sequence[str],
        meta_file: str | Sequence[str] | None = None,
        logging_file: str | bool | None = None,
        init_id: str = "initialize",
        run_id: str = "run",
        final_id: str = "finalize",
        tracking: str | dict | None = None,
        workflow_type: str | None = "train",
        properties_path: PathLike | None = None,
        **override: Any,
    ) -> None:
        if config_file is not None: