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f5c94e5471
* Add poros backend * Add torch lib * Add python3 lib * set c++ 14 for poros * fixed bugs * fixed grammer bugs * fixed grammer bugs * fixed code bugs * fixed code bugs * fixed CreatePorosValue bug * Add AtType2String for Log * fixed trt_option * fixed poros.cmake path * fixed grammer bug * fixed grammer bug * fixed ambiguous reference * fixed ambiguous reference * fixed reference error * fixed include files * rm ENABLE_TRT_BACKEND in poros * update CMakeLists.txt * fixed CMakeLists.txt * Add libtorch.so in CMakeLists.txt * Fixed CMakeLists.txt * Fixed CMakeLists.txt * Fixed copy bug * Fixed copy bug * Fixed copy bug * Fixed Cmake * Fixed Cmake * debug * debug * debug * debug * debug * debug * debug utils * debug utils * copy to cpu * rm log info * test share mem * test share mem * test share mem * test multi outputs * test multi outputs * test multi outputs * test multi outputs * test multi outputs * test multi outputs * test multi outputs * time cost * time cost * fixed bug * time collect * mem copy * mem copy * rm time log * rm share mem * fixed multi inputs bug * add set_input_dtypes func * add SetInputDtypes * fixed bug * fixed bug * fixed prewarm data order * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * debug * fixed bug * Add compile func * Add compile func * Add compile func * Add is_dynamic option * Add is_dynamic option * Add is_dynamic option * Add is_dynamic option * rm infer log * add cuda11.6 poros lib * fixed bug * fixed bug * fixed multi outputs * fixed multi outputs * fixed multi outputs * fixed multi outputs * fixed multi outputs * fixed multi outputs * fixed multi outputs * fixed multi outputs * fixed multi outputs * fixed multi outputs * fixed multi outputs * rm logs * test * test * test * add test log * add test log * add test log * add test log * support cpu * support cpu * support cpu * support cpu * support member variable definition * rm useless log * fixed name * resolve conflict * resolve conflict * resolve conflict * fixed cmake * add GetInputInfos&GetOutputInfos * add GetInputInfos&GetOutputInfos * fixed bug * fixed runtime.py * add compile func * add np * deal with comments * rm to_inter func * add property
85 lines
2.4 KiB
C++
Executable File
85 lines
2.4 KiB
C++
Executable File
// Copyright (c) 2022 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 <string>
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//from pytorch
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#include "torch/script.h"
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#include "torch/csrc/jit/ir/ir.h"
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#include "ATen/core/interned_strings.h"
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#include "plugin_create.h"
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namespace baidu {
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namespace mirana {
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namespace poros {
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/**
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* the base engine class
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* every registered engine should inherit from this IEngine
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**/
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struct PorosGraph {
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torch::jit::Graph* graph = NULL;
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torch::jit::Node* node = NULL;
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};
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typedef uint64_t EngineID;
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class IEngine : public IPlugin, public torch::CustomClassHolder{
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public:
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virtual ~IEngine() {}
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/**
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* @brief init, initialization must be successful if the init is successful
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* @return int
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* @retval 0 => success, <0 => fail
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**/
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virtual int init() = 0;
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/**
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* @brief During compilation, the subgraph is converted into the graph structure of the corresponding engine and stored inside the engine, so that the execute_engine at runtime can be called
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* @param [in] sub_graph : subgraph
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* @return [res]int
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* @retval 0 => success, <0 => fail
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**/
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virtual int transform(const PorosGraph& sub_graph) = 0;
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/**
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* @brief Subgraph execution period logic
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* @param [in] inputs : input tensor
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* @return [res] output tensor
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**/
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virtual std::vector<at::Tensor> excute_engine(const std::vector<at::Tensor>& inputs) = 0;
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virtual void register_module_attribute(const std::string& name, torch::jit::Module& module) = 0;
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// Logo
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virtual const std::string who_am_i() = 0;
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// Whether the node is supported by the current engine
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bool is_node_supported(const torch::jit::Node* node);
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public:
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std::pair<uint64_t, uint64_t> _num_io; // Number of input/output parameters
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EngineID _id;
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};
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} // namespace poros
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} // namespace mirana
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} // namespace baidu
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