Function serialize_program

python/paddle/static/io.py:305–359

Serialize default main program according to feed_vars and fetch_vars. Args: feed_vars(Tensor | list[Tensor]): Tensor needed by inference. fetch_vars(Tensor | list[Tensor]): Tensor returned by inference. kwargs: Supported keys including ``program``. Attention please

(
    feed_vars: Tensor | list[Tensor],
    fetch_vars: Tensor | list[Tensor],
    **kwargs: Unpack[_SerializeProgramKwargs],
)

@static_only
def serialize_program(
    feed_vars: Tensor | list[Tensor],
    fetch_vars: Tensor | list[Tensor],
    **kwargs: Unpack[_SerializeProgramKwargs],
) -> bytes:
    """

    Serialize default main program according to feed_vars and fetch_vars.

    Args:
        feed_vars(Tensor | list[Tensor]): Tensor needed by inference.
        fetch_vars(Tensor | list[Tensor]): Tensor returned by inference.
        kwargs: Supported keys including ``program``. Attention please, kwargs is used for backward compatibility mainly.

            - program(Program): specify a program if you don't want to use default main program.
            - legacy_format(bool): whether to save inference program in legacy format. Defaults to False.

    Returns:
        bytes: serialized program.

    Examples:
        .. code-block:: pycon

            >>> # doctest: +SKIP("paddle.static.serialize_program doesn't support PIR mode")
            >>> import paddle
            >>> paddle.enable_static()

            >>> path_prefix = "./infer_model"

            # User defined network, here a softmax regression example
            >>> image = paddle.static.data(name='img', shape=[None, 28, 28], dtype='float32')
            >>> label = paddle.static.data(name='label', shape=[None, 1], dtype='int64')
            >>> predict = paddle.static.nn.fc(image, 10, activation='softmax')

            >>> loss = paddle.nn.functional.cross_entropy(predict, label)

            >>> exe = paddle.static.Executor(paddle.CPUPlace())
            >>> exe.run(paddle.static.default_startup_program())

            # serialize the default main program to bytes.
            >>> serialized_program = paddle.static.serialize_program([image], [predict])

            # deserialize bytes to program
            >>> deserialized_program = paddle.static.deserialize_program(serialized_program)

    """
    # verify feed_vars
    _check_vars('feed_vars', feed_vars)
    # verify fetch_vars
    _check_vars('fetch_vars', fetch_vars)

    program = _get_valid_program(kwargs.get('program', None))
    program = normalize_program(program, feed_vars, fetch_vars)
    legacy_format = kwargs.get('legacy_format', False)
    return _serialize_program(program, legacy_format=legacy_format)


def _serialize_program(program: Program, legacy_format: bool = False) -> bytes: