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124 lines
4.2 KiB
124 lines
4.2 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/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 SwishPlugin : public PluginTensorRT {
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private:
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float beta_;
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protected:
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size_t getSerializationSize() override {
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return getBaseSerializationSize() + SerializedSize(beta_);
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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, beta_);
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}
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public:
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explicit SwishPlugin(const float beta) : beta_(beta) {}
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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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SwishPlugin(void const* serialData, size_t serialLength) {
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deserializeBase(serialData, serialLength);
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DeserializeValue(&serialData, &serialLength, &beta_);
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}
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~SwishPlugin() {}
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int initialize() override;
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SwishPlugin* clone() const override { return new SwishPlugin(beta_); }
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const char* getPluginType() const override { return "swish_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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#if IS_TRT_VERSION_GE(6000)
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class SwishPluginDynamic : public DynamicPluginTensorRT {
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public:
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explicit SwishPluginDynamic(const float beta) : beta_(beta) {}
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SwishPluginDynamic(void const* serialData, size_t serialLength) {}
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nvinfer1::IPluginV2DynamicExt* clone() const override {
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return new SwishPluginDynamic(beta_);
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}
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const char* getPluginType() const override { return "swish_plugin"; }
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int getNbOutputs() const override { return 1; }
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int initialize() override;
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size_t getSerializationSize() const override;
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void serialize(void* buffer) const override;
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nvinfer1::DimsExprs getOutputDimensions(
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int output_index, const nvinfer1::DimsExprs* inputs, int nb_inputs,
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nvinfer1::IExprBuilder& expr_builder) override;
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bool supportsFormatCombination(int pos,
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const nvinfer1::PluginTensorDesc* inOut,
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int nbInputs, int nbOutputs) override;
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void configurePlugin(const nvinfer1::DynamicPluginTensorDesc* in,
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int nbInputs,
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const nvinfer1::DynamicPluginTensorDesc* out,
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int nbOutputs) override {}
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size_t getWorkspaceSize(const nvinfer1::PluginTensorDesc* inputs,
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int nbInputs,
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const nvinfer1::PluginTensorDesc* outputs,
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int nbOutputs) const override {
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return 0;
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}
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int enqueue(const nvinfer1::PluginTensorDesc* inputDesc,
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const nvinfer1::PluginTensorDesc* outputDesc,
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const void* const* inputs, void* const* outputs, void* workspace,
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cudaStream_t stream) override;
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nvinfer1::DataType getOutputDataType(int index,
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const nvinfer1::DataType* inputTypes,
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int nbInputs) const override;
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void destroy() override { delete this; }
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private:
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float beta_;
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};
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#endif
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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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