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88 lines
2.9 KiB
88 lines
2.9 KiB
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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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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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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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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#pragma once
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#include <algorithm>
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#include <string>
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#include <vector>
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#include "paddle/fluid/framework/tensor.h"
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#include "paddle/fluid/framework/tensor_util.h"
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#include "paddle/fluid/inference/tensorrt/engine.h"
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#include "paddle/fluid/inference/tensorrt/plugin/trt_plugin.h"
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namespace paddle {
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namespace inference {
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namespace tensorrt {
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namespace plugin {
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class PReluPlugin : public PluginTensorRT {
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std::vector<float> weight_;
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float *p_gpu_weight_;
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std::string mode_;
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protected:
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size_t getSerializationSize() override {
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return getBaseSerializationSize() + SerializedSize(mode_.c_str()) +
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SerializedSize(weight_) + SerializedSize(getPluginType());
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}
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// TRT will call this func when we need to serialize the configuration of
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// tensorrt.
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// It should not be called by users.
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void serialize(void *buffer) override {
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SerializeValue(&buffer, getPluginType());
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serializeBase(buffer);
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SerializeValue(&buffer, weight_);
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SerializeValue(&buffer, mode_.c_str());
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}
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public:
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PReluPlugin(const float *weight, const int weight_num,
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std::string const &mode)
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: mode_(mode) {
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weight_.resize(weight_num);
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std::copy(weight, weight + weight_num, weight_.data());
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}
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// It was used for tensorrt deserialization.
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// It should not be called by users.
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PReluPlugin(void const *serialData, size_t serialLength) {
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deserializeBase(serialData, serialLength);
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DeserializeValue(&serialData, &serialLength, &weight_);
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const char *prelu_mode;
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DeserializeValue(&serialData, &serialLength, &prelu_mode);
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mode_ = std::string(prelu_mode);
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}
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~PReluPlugin() { cudaFree(p_gpu_weight_); }
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int initialize() override;
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PReluPlugin *clone() const override {
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return new PReluPlugin(weight_.data(), weight_.size(), mode_);
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}
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const char *getPluginType() const override { return "prelu_plugin"; }
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int getNbOutputs() const override { return 1; }
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nvinfer1::Dims getOutputDimensions(int index, const nvinfer1::Dims *inputs,
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int nbInputDims) override;
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int enqueue(int batchSize, const void *const *inputs, void **outputs,
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void *workspace, cudaStream_t stream) override;
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};
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} // namespace plugin
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} // namespace tensorrt
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} // namespace inference
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} // namespace paddle
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