Class Executor

python/paddle/base/executor.py:1253–3091

:api_attr: Static Graph An Executor in Python, supports single/multiple-GPU running, and single/multiple-CPU running. Args: place(paddle.CPUPlace()|paddle.CUDAPlace(n)|str|None): This parameter represents which device the executor runs on. When this parameter i

class Executor:
    """
    :api_attr: Static Graph

    An Executor in Python, supports single/multiple-GPU running,
    and single/multiple-CPU running.

    Args:
        place(paddle.CPUPlace()|paddle.CUDAPlace(n)|str|None): This parameter represents
            which device the executor runs on. When this parameter is None, PaddlePaddle
            will set the default device according to its installation version. If Paddle
            is CPU version, the default device would be set to `CPUPlace()` . If Paddle is
            GPU version, the default device would be set to `CUDAPlace(0)` . Default is None.
            If ``place`` is string, it can be ``cpu``, and ``gpu:x``, where ``x``
            is the index of the GPUs. Note: users only pass one Place or None to initialize
            Executor when using multiple-cards. Other APIs will override the cards. See
            `document for multiple-cards <https://www.paddlepaddle.org.cn/documentation/docs/en/develop/guides/01_paddle2.0_introduction/update_en.html#stand-alone-multi-card-launch>`_

    Returns:
        Executor

    Examples:

        .. code-block:: pycon

            >>> import paddle
            >>> import numpy

            >>> # Executor is only used in static graph mode
            >>> paddle.enable_static()

            >>> # Set place explicitly.
            >>> # use_cuda = True
            >>> # place = paddle.CUDAPlace(0) if use_cuda else paddle.CPUPlace()
            >>> # exe = paddle.static.Executor(place)

            >>> # If you don't set place, PaddlePaddle sets the default device.
            >>> exe = paddle.static.Executor()

            >>> train_program = paddle.static.Program()
            >>> startup_program = paddle.static.Program()
            >>> with paddle.static.program_guard(train_program, startup_program):
            ...     data = paddle.static.data(name='X', shape=[None, 1], dtype='float32')
            ...     hidden = paddle.static.nn.fc(data, 10)
            ...     loss = paddle.mean(hidden)
            ...     paddle.optimizer.SGD(learning_rate=0.01).minimize(loss)
            >>> # Run the startup program once and only once.
            >>> # Not need to optimize/compile the startup program.
            >>> exe.run(startup_program)

            >>> # Run the main program.
            >>> x = numpy.random.random(size=(10, 1)).astype('float32')
            >>> (loss_data,) = exe.run(train_program, feed={"X": x}, fetch_list=[loss])
    """

    place: _Place

    def __init__(self, place: PlaceLike | None = None) -> None: