Function create_parameter

python/paddle/pir/core.py:333–410

(
    dtype,
    shape,
    name=None,
    **kwargs,
)

def create_parameter(
    dtype,
    shape,
    name=None,
    **kwargs,
):
    if 'initializer' not in kwargs:
        raise ValueError(
            "initializer is None, if you want to create parameter, please pass its initializer."
        )
    if dtype is not None:
        if not isinstance(dtype, DataType):
            dtype = convert_np_dtype_to_dtype_(dtype)
    value_name = name
    if not value_name:
        value_name = unique_name.generate('parameter')
    startup_program = default_startup_program()
    main_program = default_main_program()
    parameter_meta = ParameterMeta(shape, dtype)

    is_dist = False
    if (
        'placements' in kwargs
        and kwargs['placements']
        and 'process_mesh' in kwargs
        and kwargs['process_mesh']
    ):
        is_dist = True

    def to_dist(value):
        import paddle
        import paddle.distributed as dist

        process_mesh = kwargs['process_mesh']
        dim_map, partial_status = dist.auto_parallel.placement_type.to_dim_map(
            kwargs['placements'], len(shape)
        )
        dist_attr = paddle.base.libpaddle.pir.create_tensor_dist_attribute(
            process_mesh, dim_map, partial_status
        )
        dist_type = paddle.base.libpaddle.pir.cvt_to_dist_type(
            value.type(), dist_attr
        )
        value.set_type(dist_type)
        op_dist_attr = paddle.base.libpaddle.pir.create_op_dist_attribute(
            process_mesh, [], [dist_attr]
        )
        value.get_defining_op().dist_attr = op_dist_attr

    with program_guard(startup_program):
        initializer = kwargs['initializer']
        init_result = initializer(
            parameter_meta, startup_program.global_block()
        )
        init_result.persistable = True
        if is_dist:
            to_dist(init_result)