Function load

torch/export/__init__.py:253–308

.. warning:: Under active development, saved files may not be usable in newer versions of PyTorch. Loads an :class:`ExportedProgram` previously saved with :func:`torch.export.save `. Args: ep (ExportedProgram): The exported program to sa

(
    f: Union[str, pathlib.Path, io.BytesIO],
    *,
    extra_files: Optional[Dict[str, Any]] = None,
    expected_opset_version: Optional[Dict[str, int]] = None,
)

def load(
    f: Union[str, pathlib.Path, io.BytesIO],
    *,
    extra_files: Optional[Dict[str, Any]] = None,
    expected_opset_version: Optional[Dict[str, int]] = None,
) -> ExportedProgram:
    """

    .. warning::
        Under active development, saved files may not be usable in newer versions
        of PyTorch.

    Loads an :class:`ExportedProgram` previously saved with
    :func:`torch.export.save <torch.export.save>`.

    Args:
        ep (ExportedProgram): The exported program to save.

        f (Union[str, pathlib.Path, io.BytesIO): A file-like object (has to
         implement write and flush) or a string containing a file name.

        extra_files (Optional[Dict[str, Any]]): The extra filenames given in
         this map would be loaded and their content would be stored in the
         provided map.

        expected_opset_version (Optional[Dict[str, int]]): A map of opset names
         to expected opset versions

    Returns:
        An :class:`ExportedProgram` object

    Example::

        import torch
        import io

        # Load ExportedProgram from file
        ep = torch.export.load('exported_program.pt2')

        # Load ExportedProgram from io.BytesIO object
        with open('exported_program.pt2', 'rb') as f:
            buffer = io.BytesIO(f.read())
        buffer.seek(0)
        ep = torch.export.load(buffer)

        # Load with extra files.
        extra_files = {'foo.txt': ''}  # values will be replaced with data
        ep = torch.export.load('exported_program.pt2', extra_files=extra_files)
        print(extra_files['foo.txt'])
        print(ep(torch.randn(5)))
    """
    from torch._export import load

    return load(
        f, extra_files=extra_files, expected_opset_version=expected_opset_version
    )