# Copyright (c) 2020 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 paddle class TestNewGroupAPI: def __init__(self): paddle.distributed.init_parallel_env() d1 = np.array([1, 2, 3]) d2 = np.array([2, 3, 4]) self.tensor1 = paddle.to_tensor(d1) self.tensor2 = paddle.to_tensor(d2) def test_all(self): gp = paddle.distributed.new_group([0, 1]) print("gp info:", gp) print("test new group api ok") tmp = np.array([0, 0, 0]) result = paddle.to_tensor(tmp) paddle.distributed.scatter( result, [self.tensor2, self.tensor1], src=0, group=gp, sync_op=True ) if gp.rank == 0: assert np.array_equal(result, self.tensor2) elif gp.rank == 1: assert np.array_equal(result, self.tensor1) print("test scatter api ok") paddle.distributed.broadcast(result, src=1, group=gp, sync_op=True) assert np.array_equal(result, self.tensor1) print("test broadcast api ok") paddle.distributed.reduce(result, dst=0, group=gp, sync_op=True) if gp.rank == 0: assert np.array_equal( result, paddle.add(self.tensor1, self.tensor1) ) elif gp.rank == 1: assert np.array_equal(result, self.tensor1) print("test reduce api ok") paddle.distributed.all_reduce(result, sync_op=True) assert np.array_equal( result, paddle.add(paddle.add(self.tensor1, self.tensor1), self.tensor1), ) print("test all_reduce api ok") paddle.distributed.wait(result, gp, use_calc_stream=True) paddle.distributed.wait(result, gp, use_calc_stream=False) print("test wait api ok") result = [] paddle.distributed.all_gather( result, self.tensor1, group=gp, sync_op=True ) assert np.array_equal(result[0], self.tensor1) assert np.array_equal(result[1], self.tensor1) print("test all_gather api ok") paddle.distributed.barrier(group=gp) print("test barrier api ok") return if __name__ == "__main__": gpt = TestNewGroupAPI() gpt.test_all()