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113 lines
4.0 KiB
113 lines
4.0 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/fused/fusion_group_op.h"
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namespace paddle {
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namespace operators {
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class FusionGroupOp : 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->HasInputs("Inputs"), "Input", "Inputs", "FusionGroup");
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OP_INOUT_CHECK(ctx->HasOutputs("Outs"), "Output", "Outs", "FusionGroup");
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auto input_names = ctx->Inputs("Inputs");
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auto output_names = ctx->Outputs("Outs");
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const size_t num_ins = input_names.size();
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const size_t num_outs = output_names.size();
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PADDLE_ENFORCE_GE(
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num_ins, 1UL,
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platform::errors::InvalidArgument(
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"Expected the number of inputs >= 1. Received %d.", num_ins));
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PADDLE_ENFORCE_GE(
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num_outs, 1UL,
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platform::errors::InvalidArgument(
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"Expected the number of outputs >= 1. Recived %d.", num_outs));
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int type = ctx->Attrs().Get<int>("type");
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PADDLE_ENFORCE_EQ(type, 0UL,
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platform::errors::InvalidArgument(
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"Only support fusion of elementwise operations."));
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std::vector<framework::DDim> x_dims = ctx->GetInputsDim("Inputs");
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if (type == 0) {
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for (size_t i = 1; i < num_ins; ++i) {
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PADDLE_ENFORCE_EQ(
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x_dims[0], x_dims[i],
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platform::errors::InvalidArgument(
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"All the inputs' dims is expected to be the same. "
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"But recieved [%s] (name: %s) vs [%s] (name: %s).",
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x_dims[0], input_names[0], x_dims[i], input_names[i]));
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}
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std::vector<framework::DDim> out_dims;
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for (size_t j = 0; j < num_outs; ++j) {
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out_dims.push_back(x_dims[0]);
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}
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ctx->SetOutputsDim("Outs", out_dims);
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}
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// Only lod of Inputs[0] would be shared with Outs.
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for (size_t j = 0; j < num_outs; ++j) {
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ctx->ShareLoD("Inputs", /*->*/ "Outs", 0, j);
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}
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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(framework::proto::VarType::FP32,
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platform::CUDAPlace(0));
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};
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};
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class FusionGroupOpMaker : public framework::OpProtoAndCheckerMaker {
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public:
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void Make() override {
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AddInput("Inputs",
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"(std::vector<LoDTensor>) The inputs of fusion_group op.")
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.AsDuplicable();
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AddOutput("Outs",
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"(std::vector<LoDTensor>) The outputs of fusion_group op.")
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.AsDuplicable();
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AddAttr<std::vector<int>>("outs_dtype",
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"The data type of Outputs in fusion_group op.")
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.SetDefault({});
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AddAttr<std::vector<int>>("inputs_dtype",
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"The data type of Inputs in fusion_group op.")
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.SetDefault({});
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AddAttr<int>("type", "Fusion type.").SetDefault(0);
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AddAttr<std::string>("func_name", "Name of the generated functions.")
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.SetDefault("");
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AddComment(R"DOC(
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fusion_group Operator.
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It is used to execute a generated CUDA kernel which fuse the computation of
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multiple operators into one. It supports several types:
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0, fused computation of elementwise operations in which all the dims of inputs
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and outputs should be exactly the same.
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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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REGISTER_OPERATOR(fusion_group, ops::FusionGroupOp, ops::FusionGroupOpMaker);
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