187 lines
6.1 KiB
C++
187 lines
6.1 KiB
C++
// Copyright (c) 2023 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 <NvInfer.h>
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#include <string>
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#include <vector>
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#include "paddle/fluid/framework/op_desc.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/framework/operator.h"
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#include "paddle/fluid/framework/scope.h"
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#include "paddle/fluid/framework/type_defs.h"
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#include "paddle/fluid/inference/tensorrt/engine.h"
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#include "paddle/fluid/inference/tensorrt/helper.h"
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#include "paddle/fluid/inference/tensorrt/plugin/trt_plugin.h"
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#include "paddle/fluid/inference/tensorrt/plugin/trt_plugin_utils.h"
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#include "paddle/fluid/inference/tensorrt/plugin_arg_mapping_context.h"
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#include "paddle/fluid/platform/enforce.h"
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#include "paddle/phi/api/ext/op_meta_info.h"
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#include "paddle/phi/backends/gpu/gpu_context.h"
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#include "paddle/phi/core/kernel_context.h"
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#include "paddle/phi/core/memory/allocation/cuda_allocator.h"
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#include "paddle/phi/core/platform/device_context.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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enum class GenerateCustomGenericPluginDataType {
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PLUGIN_BOOL,
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PLUGIN_UINT8,
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PLUGIN_INT8,
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PLUGIN_INT16,
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PLUGIN_INT32,
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PLUGIN_INT64,
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PLUGIN_FP16,
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PLUGIN_FP32,
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PLUGIN_FP64,
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PLUGIN_BF16,
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PLUGIN_SIZE_T,
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PLUGIN_COMPLEX64,
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PLUGIN_COMPLEX128,
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PLUGIN_OPTIONAL,
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};
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GenerateCustomGenericPluginDataType
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ProtoTypeToGenerateCustomGenericPluginDataType(
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framework::proto::VarType_Type proto_type);
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class CustomGenericPlugin : public DynamicPluginTensorRT {
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public:
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struct InputOutPutVarInfo {
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std::vector<GenerateCustomGenericPluginDataType> inputs_data_type;
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std::vector<GenerateCustomGenericPluginDataType> outputs_data_type;
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};
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public:
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CustomGenericPlugin() = default;
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CustomGenericPlugin(const paddle::framework::proto::OpDesc& proto_op_desc,
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const InputOutPutVarInfo& in_out_info,
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bool with_fp16_ = false);
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CustomGenericPlugin(
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const paddle::framework::proto::OpDesc& proto_op_desc,
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const std::vector<GenerateCustomGenericPluginDataType>& inputs_data_type,
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const std::vector<GenerateCustomGenericPluginDataType>& outputs_data_type,
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bool with_fp16_ = false);
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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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CustomGenericPlugin(void const* serialData, size_t serialLength);
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// IPluginV2 method
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const char* getPluginType() const TRT_NOEXCEPT override {
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return "custom_generic_plugin";
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}
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int getNbOutputs() const TRT_NOEXCEPT override;
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int getNbInputs() const TRT_NOEXCEPT;
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// Initialize the layer for execution.
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int initialize() TRT_NOEXCEPT override;
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// Shutdown the layer. This is called when the engine is destroyed
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void terminate() TRT_NOEXCEPT override;
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void destroy() TRT_NOEXCEPT override{};
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size_t getSerializationSize() const TRT_NOEXCEPT override {
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size_t sum = 0;
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sum += SerializedSize(inputs_data_type_);
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sum += SerializedSize(outputs_data_type_);
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sum += SerializedSize(with_fp16_);
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sum += op_meta_data_.size();
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return sum;
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}
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void serialize(void* buffer) const TRT_NOEXCEPT override;
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// The Func in IPluginV2
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nvinfer1::IPluginV2DynamicExt* clone() const TRT_NOEXCEPT override;
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nvinfer1::DimsExprs getOutputDimensions(
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int output_index,
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const nvinfer1::DimsExprs* inputs,
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int nb_inputs,
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nvinfer1::IExprBuilder& expr_builder) // NOLINT
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TRT_NOEXCEPT override;
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bool supportsFormatCombination(int pos,
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const nvinfer1::PluginTensorDesc* in_out,
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int nb_inputs,
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int nb_outputs) TRT_NOEXCEPT override;
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void configurePlugin(const nvinfer1::DynamicPluginTensorDesc* in,
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int nb_inputs,
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const nvinfer1::DynamicPluginTensorDesc* out,
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int nb_outputs) TRT_NOEXCEPT override;
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int enqueue(const nvinfer1::PluginTensorDesc* input_desc,
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const nvinfer1::PluginTensorDesc* output_desc,
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const void* const* inputs,
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void* const* outputs,
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void* workspace,
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cudaStream_t stream) TRT_NOEXCEPT override;
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nvinfer1::DataType getOutputDataType(int index,
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const nvinfer1::DataType* input_types,
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int nb_inputs) const
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TRT_NOEXCEPT override;
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bool isFp16Supported() { return with_fp16_; }
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private:
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bool with_fp16_{false};
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std::string op_meta_data_;
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framework::proto::OpDesc proto_op_desc_;
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framework::OpDesc op_desc_;
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private:
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std::vector<paddle::Tensor>* tensor_inputs_{nullptr};
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std::vector<paddle::Tensor>* tensor_outputs_{nullptr};
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private:
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std::vector<GenerateCustomGenericPluginDataType> inputs_data_type_;
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std::vector<GenerateCustomGenericPluginDataType> outputs_data_type_;
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};
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class CustomGenericPluginCreator : public TensorRTPluginCreator {
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public:
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const char* getPluginName() const TRT_NOEXCEPT override {
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return "custom_generic_plugin";
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}
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const char* getPluginVersion() const TRT_NOEXCEPT override { return "1"; }
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nvinfer1::IPluginV2DynamicExt* deserializePlugin(const char* name,
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const void* serial_data,
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size_t serial_length)
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TRT_NOEXCEPT override {
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return new CustomGenericPlugin(serial_data, serial_length);
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}
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};
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REGISTER_TRT_PLUGIN_V2(CustomGenericPluginCreator);
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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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