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93 lines
3.4 KiB
93 lines
3.4 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_scatter_op.h"
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namespace paddle {
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namespace operators {
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class CScatterOp : 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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OP_INOUT_CHECK(ctx->HasInput("X"), "Input", "X", "CScatter");
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OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "CScatter");
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int root_id = ctx->Attrs().Get<int>("root");
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int ring_id = ctx->Attrs().Get<int>("ring_id");
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int nranks = ctx->Attrs().Get<int>("nranks");
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PADDLE_ENFORCE_GE(nranks, 2,
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platform::errors::InvalidArgument(
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"The number of ranks (%d) must be greater than 1 "
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"to use collective op (c_scatter op).",
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nranks));
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PADDLE_ENFORCE_GE(
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root_id, 0,
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platform::errors::InvalidArgument(
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"The root_id (%d) for c_scatter_op must be non-negative.",
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root_id));
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PADDLE_ENFORCE_GE(
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ring_id, 0,
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platform::errors::InvalidArgument(
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"The ring_id (%d) for c_scatter_op must be non-negative.",
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root_id));
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framework::DDim dim = ctx->GetInputDim("X");
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dim[0] = dim[0] / nranks;
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if (dim[0] < 0) dim[0] = -1;
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ctx->SetOutputDim("Out", dim);
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}
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protected:
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framework::OpKernelType GetExpectedKernelType(
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const framework::ExecutionContext& ctx) const override {
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return framework::OpKernelType(
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OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace());
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}
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};
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class CScatterOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() {
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AddInput("X", "(Tensor) tensor to be broadcasted.");
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AddOutput("Out", "(Tensor) the result of broadcast.");
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AddAttr<int>("ring_id", "(int default 0) nccl communication ring id.")
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.SetDefault(0);
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AddAttr<int>("root", "(int default 0) root id for broadcasting.")
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.SetDefault(0);
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AddAttr<int>("nranks", "(int default 1) number of ranks.").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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AddComment(R"DOC(
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CScatter Operator
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Scatter the source to all participators.
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)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(c_scatter, ops::CScatterOp, ops::CScatterOpMaker);
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REGISTER_OP_CPU_KERNEL(c_scatter, ops::CScatterOpCPUKernel<float>,
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ops::CScatterOpCPUKernel<double>,
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ops::CScatterOpCPUKernel<int>,
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ops::CScatterOpCPUKernel<int64_t>,
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ops::CScatterOpCPUKernel<plat::float16>);
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