Class Program

python/paddle/base/framework.py:6017–7679

Create Python Program. It has at least one :ref:`api_guide_Block_en`, when the control flow op like conditional_block, while :ref:`api_paddle_base_layers_While` is included, it will contain nested block. Please reference the `framework.proto <https://github.com/PaddlePaddle/Pa

class Program:
    """
    Create Python Program.  It has at least one :ref:`api_guide_Block_en`, when the
    control flow op like conditional_block, while :ref:`api_paddle_base_layers_While` is included,
    it will contain nested block.

    Please reference the
    `framework.proto <https://github.com/PaddlePaddle/Paddle/blob/develop/paddle/phi/core/framework/framework.proto>`_
    for details.

    A set of Program usually contains startup program and main program.
    A startup program is set to contain some initial work, eg. initialize the ``Parameter``, and the main
    program will contain the network structure and vars for train.

    A set of Program can be used for test or train, in train program ,
    Paddle will contain all content to build a train network,  in test
    program Paddle will prune some content which is irrelevant to test, eg.
    backward ops and vars.

    **Notes**:
        **we have** :ref:`api_paddle_base_framework_default_startup_program` **and** :ref:`api_paddle_base_framework_default_main_program`
        **by default, a pair of them will shared the parameters. The** :ref:`api_paddle_base_framework_default_startup_program` **only run once to initialize parameters,**
        :ref:`api_paddle_base_framework_default_main_program` **run in every mini batch and adjust the weights.**

    Returns:
        Program: An empty Program.

    Examples:
        .. code-block:: pycon

            >>> import paddle
            >>> import paddle.static as static

            >>> paddle.enable_static()

            >>> main_program = static.Program()
            >>> startup_program = static.Program()
            >>> with static.program_guard(main_program=main_program, startup_program=startup_program):
            ...     x = static.data(name="x", shape=[-1, 784], dtype='float32')
            ...     y = static.data(name="y", shape=[-1, 1], dtype='int32')
            ...     z = static.nn.fc(name="fc", x=x, size=10, activation="relu")

            >>> print("main program is: {}".format(main_program))
            >>> print("start up program is: {}".format(startup_program))

    """

    def __init__(self):
        self.desc = core.ProgramDesc()
        self.blocks = [Block(self, 0)]
        self.current_block_idx = 0
        global global_prog_seed
        self._seed = global_prog_seed
        self._current_role = core.op_proto_and_checker_maker.OpRole.Forward
        self.__op_role_var = []

        # for distribute training
        # _is_distributed = True if under distributed training