// Copyright (c) 2019 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. #include "paddle/fluid/imperative/nccl_context.h" #include "gtest/gtest.h" namespace imperative = paddle::imperative; namespace platform = paddle::platform; int nrings = 2; imperative::ParallelStrategy GetStrategy(int local_rank) { std::vector eps = {"127.0.0.1:9866", "localhost:9867"}; imperative::ParallelStrategy strategy; strategy.trainer_endpoints_ = eps; strategy.current_endpoint_ = eps[local_rank]; strategy.nranks_ = 2; strategy.local_rank_ = local_rank; strategy.nrings_ = nrings; return strategy; } #if defined(PADDLE_WITH_NCCL) void BcastNCCLId(int local_rank, std::vector* nccl_ids) { auto strategy = GetStrategy(local_rank); platform::CUDAPlace gpu(local_rank); imperative::NCCLParallelContext ctx(strategy, gpu); ctx.BcastNCCLId(*nccl_ids, 0); } TEST(BcastNCCLId, Run) { std::vector nccl_ids; nccl_ids.resize(nrings); for (int i = 0; i < nrings; ++i) { platform::dynload::ncclGetUniqueId(&nccl_ids[i]); } std::thread t(BcastNCCLId, 0, &nccl_ids); std::vector recv_nccl_ids; recv_nccl_ids.resize(nrings); for (int i = 0; i < nrings; ++i) { platform::dynload::ncclGetUniqueId(&recv_nccl_ids[i]); } BcastNCCLId(1, &recv_nccl_ids); t.join(); for (int i = 0; i < nrings; ++i) { EXPECT_EQ(0, std::memcmp(nccl_ids[i].internal, recv_nccl_ids[i].internal, NCCL_UNIQUE_ID_BYTES)); } } #endif