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53 lines
1.8 KiB
53 lines
1.8 KiB
6 years ago
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// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#include "paddle/fluid/imperative/nccl_context.h"
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#include "gtest/gtest.h"
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#include "paddle/fluid/platform/device_context.h"
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namespace imperative = paddle::imperative;
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namespace platform = paddle::platform;
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imperative::ParallelStrategy GetStrategy(int local_rank) {
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std::vector<std::string> eps = {"127.0.0.1:9866", "127.0.0.1:9867"};
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imperative::ParallelStrategy strategy;
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strategy.trainer_endpoints_ = eps;
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strategy.current_endpoint_ = eps[local_rank];
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strategy.nranks_ = 2;
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strategy.local_rank_ = local_rank;
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return strategy;
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}
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#if defined(PADDLE_WITH_CUDA) && !defined(_WIN32)
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void BcastNCCLId(int local_rank, ncclUniqueId *nccl_id) {
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auto strategy = GetStrategy(local_rank);
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platform::CUDAPlace gpu(local_rank);
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imperative::NCCLParallelContext ctx(strategy, gpu);
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ctx.BcastNCCLId(nccl_id, 0);
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}
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TEST(BcastNCCLId, Run) {
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ncclUniqueId nccl_id;
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platform::dynload::ncclGetUniqueId(&nccl_id);
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std::thread t(BcastNCCLId, 0, &nccl_id);
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ncclUniqueId recv_nccl_id;
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BcastNCCLId(1, &recv_nccl_id);
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t.join();
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EXPECT_EQ(0, std::memcmp(nccl_id.internal, recv_nccl_id.internal,
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NCCL_UNIQUE_ID_BYTES));
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}
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#endif
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