mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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100 lines
3.1 KiB
C++
100 lines
3.1 KiB
C++
// 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 <iostream>
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#include <memory>
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#include <string>
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#include <vector>
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#include "fastdeploy/backends/backend.h"
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#include "onnxruntime_cxx_api.h" // NOLINT
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namespace fastdeploy {
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struct OrtValueInfo {
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std::string name;
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std::vector<int64_t> shape;
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ONNXTensorElementDataType dtype;
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};
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struct OrtBackendOption {
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// -1 means default
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// 0: ORT_DISABLE_ALL
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// 1: ORT_ENABLE_BASIC
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// 2: ORT_ENABLE_EXTENDED
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// 99: ORT_ENABLE_ALL (enable some custom optimizations e.g bert)
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int graph_optimization_level = -1;
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int intra_op_num_threads = -1;
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int inter_op_num_threads = -1;
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// 0: ORT_SEQUENTIAL
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// 1: ORT_PARALLEL
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int execution_mode = -1;
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bool use_gpu = false;
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int gpu_id = 0;
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void* external_stream_ = nullptr;
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// inside parameter, maybe remove next version
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bool remove_multiclass_nms_ = false;
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std::map<std::string, std::string> custom_op_info_;
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};
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class OrtBackend : public BaseBackend {
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public:
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OrtBackend() {}
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virtual ~OrtBackend() = default;
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void BuildOption(const OrtBackendOption& option);
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bool InitFromPaddle(const std::string& model_file,
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const std::string& params_file,
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const OrtBackendOption& option = OrtBackendOption(),
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bool verbose = false);
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bool InitFromOnnx(const std::string& model_file,
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const OrtBackendOption& option = OrtBackendOption(),
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bool from_memory_buffer = false);
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bool Infer(std::vector<FDTensor>& inputs,
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std::vector<FDTensor>* outputs,
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bool copy_to_fd = true) override;
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int NumInputs() const override { return inputs_desc_.size(); }
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int NumOutputs() const override { return outputs_desc_.size(); }
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TensorInfo GetInputInfo(int index) override;
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TensorInfo GetOutputInfo(int index) override;
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std::vector<TensorInfo> GetInputInfos() override;
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std::vector<TensorInfo> GetOutputInfos() override;
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static std::vector<OrtCustomOp*> custom_operators_;
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void InitCustomOperators();
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private:
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Ort::Env env_;
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Ort::Session session_{nullptr};
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Ort::SessionOptions session_options_;
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std::shared_ptr<Ort::IoBinding> binding_;
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std::vector<OrtValueInfo> inputs_desc_;
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std::vector<OrtValueInfo> outputs_desc_;
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#ifndef NON_64_PLATFORM
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Ort::CustomOpDomain custom_op_domain_ = Ort::CustomOpDomain("Paddle");
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#endif
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OrtBackendOption option_;
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void OrtValueToFDTensor(const Ort::Value& value, FDTensor* tensor,
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const std::string& name, bool copy_to_fd);
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};
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} // namespace fastdeploy
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