wehub-resource-sync
51 lines
1.9 KiB
C++
51 lines
1.9 KiB
C++
/* Copyright (c) 2018 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/inference/tensorrt/convert/op_converter.h"
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namespace paddle::inference::tensorrt {
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class SumOpConverter : public OpConverter {
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public:
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void operator()(const framework::proto::OpDesc& op,
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const framework::Scope& scope,
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bool test_mode) override {
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VLOG(4) << "convert a sum op to tensorrt sum layer";
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framework::OpDesc op_desc(op, nullptr);
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nvinfer1::ILayer* layer = nullptr;
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// Declare the first input
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auto* sum_tmp = engine_->GetITensor(op_desc.Input("X")[0]);
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if (op_desc.Input("X").size() == 1) {
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layer = TRT_ENGINE_ADD_LAYER(engine_, Identity, *sum_tmp);
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} else {
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for (size_t i = 1; i < op_desc.Input("X").size(); i++) {
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auto* input_i = engine_->GetITensor(op_desc.Input("X")[i]);
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layer = TRT_ENGINE_ADD_LAYER(engine_,
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ElementWise,
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*input_i,
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*sum_tmp,
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nvinfer1::ElementWiseOperation::kSUM);
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sum_tmp = layer->getOutput(0);
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}
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}
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auto output_name = op_desc.Output("Out")[0];
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ReplenishLayerAndOutput(layer, "sum", {output_name}, test_mode);
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}
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};
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} // namespace paddle::inference::tensorrt
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REGISTER_TRT_OP_CONVERTER(sum, SumOpConverter);
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