[api 2.0] add collective op for cpu using gloo and paddle.distributed.* apis (#26552)
add collective op for cpu using gloo and paddle.distributed.* apisrevert-26856-strategy_example2
lilong12
5 years ago
committed by
GitHub
parent
07973c577e
commit
1c68138327
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/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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/operators/collective/barrier_op.h"
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#include <memory>
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namespace paddle {
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namespace operators {
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class BarrierOp : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext *ctx) const override {}
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};
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class BarrierOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() {
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AddInput("X", "(Tensor) Input data (only used in CUDAKernel).");
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AddOutput("Out", "(Tensor) Output data (only used in CUDAKernel).");
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AddAttr<int>("ring_id", "(int default 0) communication ring id.")
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.SetDefault(0);
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AddComment(R"DOC(
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Barrier Operator - Barrier among all pariticapitors.)DOC");
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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namespace plat = paddle::platform;
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REGISTER_OP_WITHOUT_GRADIENT(barrier, ops::BarrierOp, ops::BarrierOpMaker);
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REGISTER_OP_CPU_KERNEL(barrier, ops::BarrierOpCPUKernel<int>);
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/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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/operators/collective/barrier_op.h"
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#include <memory>
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#if defined(PADDLE_WITH_NCCL)
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#include "paddle/fluid/platform/collective_helper.h"
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#include "paddle/fluid/platform/nccl_helper.h"
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#endif
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namespace paddle {
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namespace operators {
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template <typename T>
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class BarrierOpCUDAKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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#if defined(PADDLE_WITH_NCCL)
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auto in = ctx.Input<framework::Tensor>("X");
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auto out = ctx.Output<framework::Tensor>("Out");
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auto place = ctx.GetPlace();
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ncclDataType_t dtype = platform::ToNCCLDataType(in->type());
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int64_t numel = in->numel();
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const void* sendbuff = in->data<void>();
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void* recvbuff = out->mutable_data<T>(place);
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int rid = ctx.Attr<int>("ring_id");
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auto comm = platform::NCCLCommContext::Instance().Get(rid, place);
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auto dev_ctx = platform::DeviceContextPool::Instance().Get(place);
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auto stream = static_cast<platform::CUDADeviceContext*>(dev_ctx)->stream();
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ncclRedOp_t nccl_red_type = ncclSum;
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PADDLE_ENFORCE_CUDA_SUCCESS(platform::dynload::ncclAllReduce(
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sendbuff, recvbuff, numel, dtype, nccl_red_type, comm->comm(), stream));
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auto comm_stream =
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platform::NCCLCommContext::Instance().Get(rid, place)->stream();
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PADDLE_ENFORCE_CUDA_SUCCESS(cudaStreamSynchronize(comm_stream));
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#else
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PADDLE_THROW(platform::errors::Unavailable(
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"PaddlePaddle should compile with NCCL."));
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#endif
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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namespace plat = paddle::platform;
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REGISTER_OP_CUDA_KERNEL(barrier, ops::BarrierOpCUDAKernel<int>);
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/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#pragma once
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#include <algorithm>
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#include <utility>
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#include <vector>
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#include "paddle/fluid/framework/data_type.h"
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#include "paddle/fluid/framework/ddim.h"
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#include "paddle/fluid/framework/lod_tensor.h"
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#include "paddle/fluid/framework/op_registry.h"
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#if defined(PADDLE_WITH_GLOO)
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#include <gloo/barrier.h>
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#include "paddle/fluid/framework/fleet/gloo_wrapper.h"
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#endif
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namespace paddle {
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namespace operators {
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template <typename T>
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class BarrierOpCPUKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext& ctx) const override {
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#if defined(PADDLE_WITH_GLOO)
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auto gloo = paddle::framework::GlooWrapper::GetInstance();
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PADDLE_ENFORCE_EQ(
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gloo->IsInitialized(), true,
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platform::errors::PreconditionNotMet(
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"You must initialize the gloo environment first to use it."));
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gloo::BarrierOptions opts(gloo->GetContext());
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gloo::barrier(opts);
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#else
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PADDLE_THROW(platform::errors::Unavailable(
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"PaddlePaddle should compile with GLOO by setting WITH_GLOO=ON"));
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#endif
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}
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};
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} // namespace operators
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} // namespace paddle
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// Copyright (c) 2020 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/platform/gloo_context.h"
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namespace paddle {
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namespace platform {
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#if defined(PADDLE_WITH_GLOO)
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void GlooParallelContext::Init() {
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auto gloo_ptr = paddle::framework::GlooWrapper::GetInstance();
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gloo_ptr->SetRank(strategy_.rank);
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gloo_ptr->SetSize(strategy_.rank_num);
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gloo_ptr->SetPrefix(strategy_.prefix);
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gloo_ptr->SetIface(strategy_.iface);
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gloo_ptr->SetTimeoutSeconds(strategy_.init_seconds, strategy_.run_seconds);
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gloo_ptr->SetHdfsStore(strategy_.path, strategy_.fs_name, strategy_.fs_ugi);
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gloo_ptr->Init();
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}
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#endif
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} // namespace platform
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} // namespace paddle
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// Copyright (c) 2020 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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#pragma once
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#include <string>
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#include "paddle/fluid/framework/fleet/gloo_wrapper.h"
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namespace paddle {
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namespace platform {
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#if defined(PADDLE_WITH_GLOO)
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struct GlooParallelStrategy {
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int rank{0};
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int rank_num{1};
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std::string iface;
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std::string prefix;
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int init_seconds{9999999};
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int run_seconds{9999999};
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std::string path;
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std::string fs_name;
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std::string fs_ugi;
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};
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class GlooParallelContext {
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public:
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explicit GlooParallelContext(const GlooParallelStrategy& strategy)
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: strategy_(strategy) {}
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virtual ~GlooParallelContext() {}
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virtual void Init();
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protected:
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GlooParallelStrategy strategy_;
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};
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#endif
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} // namespace platform
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} // namespace paddle
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/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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/pybind/gloo_context_py.h"
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#include <Python.h>
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#include <pybind11/chrono.h>
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#include <pybind11/complex.h>
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#include <pybind11/functional.h>
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#include <pybind11/stl.h>
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#include <memory>
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#include <set>
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#include <string>
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#include <unordered_map>
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#include <unordered_set>
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#include <utility>
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#include <vector>
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#include "paddle/fluid/memory/allocation/mmap_allocator.h"
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#include "paddle/fluid/platform/gloo_context.h"
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namespace paddle {
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namespace pybind {
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namespace py = ::pybind11;
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// Bind Methods
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void BindGlooContext(py::module *m) {
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// define parallel context for gloo
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#if defined(PADDLE_WITH_GLOO)
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py::class_<platform::GlooParallelStrategy> gloo_parallel_strategy(
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*m, "GlooParallelStrategy", "");
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gloo_parallel_strategy.def(py::init())
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.def_property("rank_num",
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[](const platform::GlooParallelStrategy &self) {
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return self.rank_num;
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},
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[](platform::GlooParallelStrategy &self, int nranks) {
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self.rank_num = nranks;
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})
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.def_property(
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"rank",
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[](const platform::GlooParallelStrategy &self) { return self.rank; },
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[](platform::GlooParallelStrategy &self, int rank) {
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self.rank = rank;
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})
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.def_property(
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"iface",
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[](const platform::GlooParallelStrategy &self) { return self.iface; },
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[](platform::GlooParallelStrategy &self, const std::string &iface) {
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self.iface = iface;
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})
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.def_property("prefix",
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[](const platform::GlooParallelStrategy &self) {
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return self.prefix;
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},
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[](platform::GlooParallelStrategy &self,
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const std::string &prefix) { self.prefix = prefix; })
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.def_property("init_seconds",
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[](const platform::GlooParallelStrategy &self) {
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return self.init_seconds;
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},
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[](platform::GlooParallelStrategy &self, int init_seconds) {
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self.init_seconds = init_seconds;
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})
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.def_property("run_seconds",
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[](const platform::GlooParallelStrategy &self) {
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return self.run_seconds;
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},
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[](platform::GlooParallelStrategy &self, int run_seconds) {
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self.run_seconds = run_seconds;
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})
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.def_property(
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"path",
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[](const platform::GlooParallelStrategy &self) { return self.path; },
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[](platform::GlooParallelStrategy &self, const std::string &path) {
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self.path = path;
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})
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.def_property("fs_name",
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[](const platform::GlooParallelStrategy &self) {
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return self.fs_name;
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},
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[](platform::GlooParallelStrategy &self,
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const std::string &fs_name) { self.fs_name = fs_name; })
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.def_property("fs_ugi",
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[](const platform::GlooParallelStrategy &self) {
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return self.fs_ugi;
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},
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[](platform::GlooParallelStrategy &self,
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const std::string &fs_ugi) { self.fs_ugi = fs_ugi; });
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py::class_<platform::GlooParallelContext> gloo_ctx(*m, "GlooParallelContext");
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gloo_ctx.def(py::init<const platform::GlooParallelStrategy &>())
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.def("init", [](platform::GlooParallelContext &self) { self.Init(); });
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#endif
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}
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} // namespace pybind
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} // namespace paddle
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@ -0,0 +1,26 @@
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/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#pragma once
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#include <Python.h>
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#include "pybind11/pybind11.h"
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#include "pybind11/stl.h"
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namespace paddle {
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namespace pybind {
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void BindGlooContext(pybind11::module* m);
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} // namespace pybind
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} // namespace paddle
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# Copyright (c) 2020 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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from __future__ import print_function
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import numpy as np
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import argparse
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import os
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import sys
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import signal
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import time
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import socket
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from contextlib import closing
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from six import string_types
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import math
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import paddle
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import paddle.fluid as fluid
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import paddle.fluid.profiler as profiler
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import paddle.fluid.unique_name as nameGen
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from paddle.fluid import core
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import unittest
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from multiprocessing import Process
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import paddle.fluid.layers as layers
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from functools import reduce
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from test_collective_api_base import TestCollectiveAPIRunnerBase, runtime_main
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class TestCollectiveAllgatherAPI(TestCollectiveAPIRunnerBase):
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def __init__(self):
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self.global_ring_id = 0
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def get_model(self, main_prog, startup_program, rank):
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with fluid.program_guard(main_prog, startup_program):
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tensor_list = []
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tindata = layers.data(
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name="tindata", shape=[10, 1000], dtype='float32')
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paddle.distributed.all_gather(tensor_list, tindata)
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return tensor_list
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if __name__ == "__main__":
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runtime_main(TestCollectiveAllgatherAPI, "allgather")
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# Copyright (c) 2020 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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from __future__ import print_function
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import numpy as np
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import argparse
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import os
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import sys
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import signal
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import time
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import socket
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from contextlib import closing
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from six import string_types
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import math
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import paddle
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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_api_base import TestCollectiveAPIRunnerBase, runtime_main
|
||||
|
||||
|
||||
class TestCollectiveAllreduceAPI(TestCollectiveAPIRunnerBase):
|
||||
def __init__(self):
|
||||
self.global_ring_id = 0
|
||||
|
||||
def get_model(self, main_prog, startup_program, rank):
|
||||
with fluid.program_guard(main_prog, startup_program):
|
||||
tindata = layers.data(
|
||||
name="tindata", shape=[10, 1000], dtype='float32')
|
||||
paddle.distributed.all_reduce(tindata)
|
||||
return [tindata]
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
runtime_main(TestCollectiveAllreduceAPI, "allreduce")
|
||||
@ -0,0 +1,50 @@
|
||||
# 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.
|
||||
|
||||
from __future__ import print_function
|
||||
|
||||
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_api_base import TestCollectiveAPIRunnerBase, runtime_main
|
||||
|
||||
|
||||
class TestCollectiveBarrierAPI(TestCollectiveAPIRunnerBase):
|
||||
def __init__(self):
|
||||
self.global_ring_id = 0
|
||||
|
||||
def get_model(self, main_prog, startup_program, rank):
|
||||
with fluid.program_guard(main_prog, startup_program):
|
||||
paddle.distributed.barrier()
|
||||
return []
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
runtime_main(TestCollectiveBarrierAPI, "barrier")
|
||||
@ -0,0 +1,52 @@
|
||||
# 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.
|
||||
|
||||
from __future__ import print_function
|
||||
|
||||
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_api_base import TestCollectiveAPIRunnerBase, runtime_main
|
||||
|
||||
|
||||
class TestCollectiveBroadcastAPI(TestCollectiveAPIRunnerBase):
|
||||
def __init__(self):
|
||||
self.global_ring_id = 0
|
||||
|
||||
def get_model(self, main_prog, startup_program, rank):
|
||||
with fluid.program_guard(main_prog, startup_program):
|
||||
tindata = layers.data(
|
||||
name="tindata", shape=[10, 1000], dtype='float32')
|
||||
paddle.distributed.broadcast(tindata, src=1)
|
||||
return [tindata]
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
runtime_main(TestCollectiveBroadcastAPI, "broadcast")
|
||||
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Reference in new issue