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paddlepaddle--paddle/paddle/fluid/inference/tensorrt/plugin/custom_generic_plugin.h
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2026-07-13 12:40:42 +08:00

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// Copyright (c) 2023 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 <NvInfer.h>
#include <string>
#include <vector>
#include "paddle/fluid/framework/op_desc.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/framework/type_defs.h"
#include "paddle/fluid/inference/tensorrt/engine.h"
#include "paddle/fluid/inference/tensorrt/helper.h"
#include "paddle/fluid/inference/tensorrt/plugin/trt_plugin.h"
#include "paddle/fluid/inference/tensorrt/plugin/trt_plugin_utils.h"
#include "paddle/fluid/inference/tensorrt/plugin_arg_mapping_context.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/phi/api/ext/op_meta_info.h"
#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/core/kernel_context.h"
#include "paddle/phi/core/memory/allocation/cuda_allocator.h"
#include "paddle/phi/core/platform/device_context.h"
namespace paddle {
namespace inference {
namespace tensorrt {
namespace plugin {
enum class GenerateCustomGenericPluginDataType {
PLUGIN_BOOL,
PLUGIN_UINT8,
PLUGIN_INT8,
PLUGIN_INT16,
PLUGIN_INT32,
PLUGIN_INT64,
PLUGIN_FP16,
PLUGIN_FP32,
PLUGIN_FP64,
PLUGIN_BF16,
PLUGIN_SIZE_T,
PLUGIN_COMPLEX64,
PLUGIN_COMPLEX128,
PLUGIN_OPTIONAL,
};
GenerateCustomGenericPluginDataType
ProtoTypeToGenerateCustomGenericPluginDataType(
framework::proto::VarType_Type proto_type);
class CustomGenericPlugin : public DynamicPluginTensorRT {
public:
struct InputOutPutVarInfo {
std::vector<GenerateCustomGenericPluginDataType> inputs_data_type;
std::vector<GenerateCustomGenericPluginDataType> outputs_data_type;
};
public:
CustomGenericPlugin() = default;
CustomGenericPlugin(const paddle::framework::proto::OpDesc& proto_op_desc,
const InputOutPutVarInfo& in_out_info,
bool with_fp16_ = false);
CustomGenericPlugin(
const paddle::framework::proto::OpDesc& proto_op_desc,
const std::vector<GenerateCustomGenericPluginDataType>& inputs_data_type,
const std::vector<GenerateCustomGenericPluginDataType>& outputs_data_type,
bool with_fp16_ = false);
// It was used for tensorrt deserialization.
// It should not be called by users.
CustomGenericPlugin(void const* serialData, size_t serialLength);
// IPluginV2 method
const char* getPluginType() const TRT_NOEXCEPT override {
return "custom_generic_plugin";
}
int getNbOutputs() const TRT_NOEXCEPT override;
int getNbInputs() const TRT_NOEXCEPT;
// Initialize the layer for execution.
int initialize() TRT_NOEXCEPT override;
// Shutdown the layer. This is called when the engine is destroyed
void terminate() TRT_NOEXCEPT override;
void destroy() TRT_NOEXCEPT override{};
size_t getSerializationSize() const TRT_NOEXCEPT override {
size_t sum = 0;
sum += SerializedSize(inputs_data_type_);
sum += SerializedSize(outputs_data_type_);
sum += SerializedSize(with_fp16_);
sum += op_meta_data_.size();
return sum;
}
void serialize(void* buffer) const TRT_NOEXCEPT override;
// The Func in IPluginV2
nvinfer1::IPluginV2DynamicExt* clone() const TRT_NOEXCEPT override;
nvinfer1::DimsExprs getOutputDimensions(
int output_index,
const nvinfer1::DimsExprs* inputs,
int nb_inputs,
nvinfer1::IExprBuilder& expr_builder) // NOLINT
TRT_NOEXCEPT override;
bool supportsFormatCombination(int pos,
const nvinfer1::PluginTensorDesc* in_out,
int nb_inputs,
int nb_outputs) TRT_NOEXCEPT override;
void configurePlugin(const nvinfer1::DynamicPluginTensorDesc* in,
int nb_inputs,
const nvinfer1::DynamicPluginTensorDesc* out,
int nb_outputs) TRT_NOEXCEPT override;
int enqueue(const nvinfer1::PluginTensorDesc* input_desc,
const nvinfer1::PluginTensorDesc* output_desc,
const void* const* inputs,
void* const* outputs,
void* workspace,
cudaStream_t stream) TRT_NOEXCEPT override;
nvinfer1::DataType getOutputDataType(int index,
const nvinfer1::DataType* input_types,
int nb_inputs) const
TRT_NOEXCEPT override;
bool isFp16Supported() { return with_fp16_; }
private:
bool with_fp16_{false};
std::string op_meta_data_;
framework::proto::OpDesc proto_op_desc_;
framework::OpDesc op_desc_;
private:
std::vector<paddle::Tensor>* tensor_inputs_{nullptr};
std::vector<paddle::Tensor>* tensor_outputs_{nullptr};
private:
std::vector<GenerateCustomGenericPluginDataType> inputs_data_type_;
std::vector<GenerateCustomGenericPluginDataType> outputs_data_type_;
};
class CustomGenericPluginCreator : public TensorRTPluginCreator {
public:
const char* getPluginName() const TRT_NOEXCEPT override {
return "custom_generic_plugin";
}
const char* getPluginVersion() const TRT_NOEXCEPT override { return "1"; }
nvinfer1::IPluginV2DynamicExt* deserializePlugin(const char* name,
const void* serial_data,
size_t serial_length)
TRT_NOEXCEPT override {
return new CustomGenericPlugin(serial_data, serial_length);
}
};
REGISTER_TRT_PLUGIN_V2(CustomGenericPluginCreator);
} // namespace plugin
} // namespace tensorrt
} // namespace inference
} // namespace paddle