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87 lines
3.1 KiB
87 lines
3.1 KiB
/* Copyright (c) 2019 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/c_allgather_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 CAllGatherOp : 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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PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) should not be null");
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PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) should not be null.");
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int nranks = ctx->Attrs().Get<int>("nranks");
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PADDLE_ENFORCE_GE(nranks, 2, "nranks should be >=2");
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framework::DDim dim = ctx->GetInputDim("X");
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dim[0] = dim[0] * nranks;
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ctx->SetOutputDim("Out", dim);
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}
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};
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class CAllGatherOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() {
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AddInput("X", "(Tensor) tensor to be allgather");
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AddOutput("Out", "(Tensor) the allgather result");
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AddAttr<int>("ring_id", "(int default 0) communication ring id.")
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.SetDefault(0);
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AddAttr<bool>(
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"use_calc_stream",
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"(bool default false) eject CUDA operations to calculation stream.")
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.SetDefault(false);
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AddAttr<int>("nranks",
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"Total trainer count of the distributed training job");
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AddComment(R"DOC(
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CAllGather Operator
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each rank receives the aggregation of data from all ranks in the order of the ranks
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reference: https://docs.nvidia.com/deeplearning/sdk/nccl-developer-guide/docs/usage/operations.html#allgather
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)DOC");
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}
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};
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class CAllGatherOpGradMaker : public framework::SingleGradOpDescMaker {
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public:
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using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
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protected:
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std::unique_ptr<framework::OpDesc> Apply() const override {
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std::unique_ptr<framework::OpDesc> retv(new framework::OpDesc());
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retv->SetType("c_reducescatter");
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retv->SetInput("X", OutputGrad("Out"));
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retv->SetOutput("Out", InputGrad("X"));
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retv->SetAttrMap(Attrs());
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return retv;
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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_OPERATOR(c_allgather, ops::CAllGatherOp, ops::CAllGatherOpGradMaker,
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ops::CAllGatherOpMaker);
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REGISTER_OP_CPU_KERNEL(c_allgather, ops::CAllGatherOpCPUKernel<float>,
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ops::CAllGatherOpCPUKernel<double>,
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ops::CAllGatherOpCPUKernel<int>,
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ops::CAllGatherOpCPUKernel<int64_t>,
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ops::CAllGatherOpCPUKernel<plat::float16>);
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