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71 lines
2.6 KiB
71 lines
2.6 KiB
/* 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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#include "paddle/fluid/inference/tensorrt/plugin/prelu_op_plugin.h"
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namespace paddle {
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namespace inference {
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namespace tensorrt {
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/*
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* PRelu converter from fluid to tensorRT.
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*/
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class PReluOpConverter : 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, bool test_mode) override {
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VLOG(4) << "convert fluid prelu op to tensorrt prelu layer";
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framework::OpDesc op_desc(op, nullptr);
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// Declare inputs
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int input_num = op_desc.Input("X").size();
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PADDLE_ENFORCE(input_num == 1);
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auto* input = engine_->GetITensor(op_desc.Input("X")[0]);
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// Get output
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size_t output_num = op_desc.Output("Out").size();
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PADDLE_ENFORCE(output_num == 1);
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// Get attrs
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std::string mode = boost::get<std::string>(op_desc.GetAttr("mode"));
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//
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auto* alpha_var = scope.FindVar(op_desc.Input("Alpha")[0]);
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PADDLE_ENFORCE_NOT_NULL(alpha_var);
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auto* alpha_tensor = alpha_var->GetMutable<framework::LoDTensor>();
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platform::CPUPlace cpu_place;
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std::unique_ptr<framework::LoDTensor> alpha_tensor_temp(
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new framework::LoDTensor());
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alpha_tensor_temp->Resize(alpha_tensor->dims());
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TensorCopySync(*alpha_tensor, cpu_place, alpha_tensor_temp.get());
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float* alpha_data = alpha_tensor_temp->mutable_data<float>(cpu_place);
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plugin::PReluPlugin* plugin =
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new plugin::PReluPlugin(alpha_data, alpha_tensor_temp->numel(), mode);
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nvinfer1::IPluginLayer* layer =
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engine_->AddPlugin(&input, input_num, plugin);
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// keep alpha tensor to avoid release it's memory
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engine_->SetWeights(op_desc.Input("Alpha")[0],
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std::move(alpha_tensor_temp));
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auto output_name = op_desc.Output("Out")[0];
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RreplenishLayerAndOutput(layer, "prelu", {output_name}, test_mode);
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}
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};
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} // namespace tensorrt
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} // namespace inference
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} // namespace paddle
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REGISTER_TRT_OP_CONVERTER(prelu, PReluOpConverter);
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