Function init_bundle

monai/bundle/scripts.py:1747–1834

Initialise a new bundle directory with some default configuration files and optionally network weights. Typical usage example: .. code-block:: bash python -m monai.bundle init_bundle /path/to/bundle_dir network_ckpt.pt Args: bundle_dir: directory name to create,

(
    bundle_dir: PathLike,
    ckpt_file: PathLike | None = None,
    network: torch.nn.Module | None = None,
    dataset_license: bool = False,
    metadata_str: dict | str | None = None,
    inference_str: dict | str | None = None,
)

def init_bundle(
    bundle_dir: PathLike,
    ckpt_file: PathLike | None = None,
    network: torch.nn.Module | None = None,
    dataset_license: bool = False,
    metadata_str: dict | str | None = None,
    inference_str: dict | str | None = None,
) -> None:
    """
    Initialise a new bundle directory with some default configuration files and optionally network weights.

    Typical usage example:

    .. code-block:: bash

        python -m monai.bundle init_bundle /path/to/bundle_dir network_ckpt.pt

    Args:
        bundle_dir: directory name to create, must not exist but parent direct must exist
        ckpt_file: optional checkpoint file to copy into bundle
        network: if given instead of ckpt_file this network's weights will be stored in bundle
        dataset_license: if `True`, a default license file called "data_license.txt" will be produced. This
            file is required if there are any license conditions stated for data your bundle uses.
        metadata_str: optional metadata string to write to bundle, if not given a default will be used.
        inference_str: optional inference string to write to bundle, if not given a default will be used.
    """
    if metadata_str is None:
        metadata_str = DEFAULT_METADATA
    if inference_str is None:
        inference_str = DEFAULT_INFERENCE

    bundle_dir = Path(bundle_dir).absolute()

    if bundle_dir.exists():
        raise ValueError(f"Specified bundle directory '{str(bundle_dir)}' already exists")

    if not bundle_dir.parent.is_dir():
        raise ValueError(f"Parent directory of specified bundle directory '{str(bundle_dir)}' does not exist")

    configs_dir = bundle_dir / "configs"
    models_dir = bundle_dir / "models"
    docs_dir = bundle_dir / "docs"

    bundle_dir.mkdir()
    configs_dir.mkdir()
    models_dir.mkdir()
    docs_dir.mkdir()

    if isinstance(metadata_str, dict):
        metadata_str = json.dumps(metadata_str, indent=4)

    if isinstance(inference_str, dict):
        inference_str = json.dumps(inference_str, indent=4)

    with open(str(configs_dir / "metadata.json"), "w") as o:
        o.write(metadata_str)

    with open(str(configs_dir / "inference.json"), "w") as o: