/* 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/operators/collective/c_broadcast_op.h" namespace paddle { namespace operators { class CBroadcastOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; void InferShape(framework::InferShapeContext* ctx) const override { ctx->SetOutputDim("Out", ctx->GetInputDim("X")); } protected: phi::KernelKey GetExpectedKernelType( const framework::ExecutionContext& ctx) const override { return phi::KernelKey(OperatorWithKernel::IndicateVarDataType(ctx, "X"), ctx.GetPlace()); } }; class CBroadcastOpMaker : public framework::OpProtoAndCheckerMaker { public: void Make() { AddInput("X", "(Tensor) tensor to be broadcasted."); AddOutput("Out", "(Tensor) the result of broadcast."); AddAttr("ring_id", "(int default 0) nccl communication ring id.") .SetDefault(0); AddAttr("root", "(int default 0) root id for broadcasting.") .SetDefault(0); AddAttr( "use_calc_stream", "(bool default false) eject CUDA operations to calculation stream.") .SetDefault(false); AddComment(R"DOC( CBroadcast Operator Reference: https://docs.nvidia.com/deeplearning/sdk/nccl-developer-guide/docs/usage/operations.html#broadcast )DOC"); } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; namespace plat = paddle::platform; REGISTER_OP_WITHOUT_GRADIENT(c_broadcast, ops::CBroadcastOp, ops::CBroadcastOpMaker); PD_REGISTER_STRUCT_KERNEL(c_broadcast, CPU, ALL_LAYOUT, ops::CBroadcastOpCPUKernel, float, double, int, int64_t, plat::float16) {}