Function _get_net_io_info

monai/bundle/scripts.py:1108–1142

Get the input and output information defined in the metadata. Args: parser: a ConfigParser of the given bundle. prefix: a prefix for the input and output ID, which will be combined as `prefix#inputs` and `prefix#outputs` to parse the input and output information

(parser: ConfigParser | None = None, prefix: str = "_meta_#network_data_format")

def _get_net_io_info(parser: ConfigParser | None = None, prefix: str = "_meta_#network_data_format") -> tuple:
    """
    Get the input and output information defined in the metadata.

    Args:
        parser: a ConfigParser of the given bundle.
        prefix: a prefix for the input and output ID, which will be combined as `prefix#inputs` and
            `prefix#outputs` to parse the input and output information in the `metadata.json` file of
            a bundle, default to `meta_#network_data_format`.

    Returns:
        input_channels: the channel number of the `image` input.
        input_spatial_shape: the spatial shape of the `image` input.
        input_dtype: the data type of the `image` input.
        output_channels: the channel number of the output.
        output_dtype: the data type of the output.
    """
    if not isinstance(parser, ConfigParser):
        raise AttributeError(f"Parameter parser should be a ConfigParser, got {type(parser)}.")

    prefix_key = f"{prefix}#inputs"
    key = f"{prefix_key}#image#num_channels"
    input_channels = parser.get(key)
    key = f"{prefix_key}#image#spatial_shape"
    input_spatial_shape = tuple(parser.get(key))
    key = f"{prefix_key}#image#dtype"
    input_dtype = get_equivalent_dtype(parser.get(key), torch.Tensor)

    prefix_key = f"{prefix}#outputs"
    key = f"{prefix_key}#pred#num_channels"
    output_channels = parser.get(key)
    key = f"{prefix_key}#pred#dtype"
    output_dtype = get_equivalent_dtype(parser.get(key), torch.Tensor)

    return input_channels, input_spatial_shape, input_dtype, output_channels, output_dtype


def _get_fake_input_shape(parser: ConfigParser) -> tuple: