collective_reduce_op.py

# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import numpy as np
import argparse
import os
import sys
import signal
import time
import socket
from contextlib import closing
from six import string_types
import math
import paddle
import paddle.fluid as fluid
import paddle.fluid.profiler as profiler
import paddle.fluid.unique_name as nameGen
from paddle.fluid import core
import unittest
from multiprocessing import Process
import paddle.fluid.layers as layers
from functools import reduce
from test_collective_base_mlu import TestCollectiveRunnerBase, runtime_main

paddle.enable_static()


class TestCollectiveReduce(TestCollectiveRunnerBase):

    def __init__(self):
        self.global_ring_id = 0

    def get_model(self, main_prog, startup_program, col_type):
        ring_id = 0
        rootid = 1
        with fluid.program_guard(main_prog, startup_program):
            tindata = layers.data(name="tindata",
                                  shape=[10, 1000],
                                  dtype='float32')
            toutdata = main_prog.current_block().create_var(
                name="outof" + col_type,
                dtype='float32',
                type=core.VarDesc.VarType.LOD_TENSOR,
                persistable=False,
                stop_gradient=False)
            main_prog.global_block().append_op(type="c_" + col_type,
                                               inputs={'X': tindata},
                                               attrs={
                                                   'ring_id': ring_id,
                                                   'root_id': rootid
                                               },
                                               outputs={'Out': toutdata})
            main_prog.global_block().append_op(type="c_sync_comm_stream",
                                               inputs={'X': toutdata},
                                               outputs={'Out': toutdata},
                                               attrs={'ring_id': ring_id})
            return toutdata


if __name__ == "__main__":
    runtime_main(TestCollectiveReduce)