// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. #pragma once #include #include #include #include "paddle/fluid/inference/tensorrt/engine.h" #include "paddle/fluid/inference/tensorrt/plugin/trt_plugin.h" namespace paddle { namespace inference { namespace tensorrt { namespace plugin { #if IS_TRT_VERSION_GE(6000) class SlicePluginDynamic : public DynamicPluginTensorRT { public: explicit SlicePluginDynamic(std::vector starts, std::vector ends, std::vector axes, bool ban_fp16) : starts_(starts), ends_(ends), axes_(axes), ban_fp16_(ban_fp16) {} SlicePluginDynamic(void const* serialData, size_t serialLength) {} nvinfer1::IPluginV2DynamicExt* clone() const override { return new SlicePluginDynamic(starts_, ends_, axes_, ban_fp16_); } const char* getPluginType() const override { return "slice_plugin"; } int getNbOutputs() const override { return 1; } int initialize() override; size_t getSerializationSize() const override; void serialize(void* buffer) const override; nvinfer1::DimsExprs getOutputDimensions( int output_index, const nvinfer1::DimsExprs* inputs, int nb_inputs, nvinfer1::IExprBuilder& expr_builder) override; bool supportsFormatCombination(int pos, const nvinfer1::PluginTensorDesc* inOut, int nbInputs, int nbOutputs) override; void configurePlugin(const nvinfer1::DynamicPluginTensorDesc* in, int nbInputs, const nvinfer1::DynamicPluginTensorDesc* out, int nbOutputs) override {} size_t getWorkspaceSize(const nvinfer1::PluginTensorDesc* inputs, int nbInputs, const nvinfer1::PluginTensorDesc* outputs, int nbOutputs) const override { return 0; } int enqueue(const nvinfer1::PluginTensorDesc* inputDesc, const nvinfer1::PluginTensorDesc* outputDesc, const void* const* inputs, void* const* outputs, void* workspace, cudaStream_t stream) override; nvinfer1::DataType getOutputDataType(int index, const nvinfer1::DataType* inputTypes, int nbInputs) const override; void destroy() override { delete this; } private: std::vector starts_; std::vector ends_; std::vector axes_; bool ban_fp16_{false}; }; #endif } // namespace plugin } // namespace tensorrt } // namespace inference } // namespace paddle