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/* * SPDX-FileCopyrightText: Copyright (c) 2022-2023 NVIDIA CORPORATION & AFFILIATES. All rights reserved. * SPDX-License-Identifier: Apache-2.0 * * 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. */ #ifndef _HOLOSCAN_ONNX_INFER_CORE_H #define _HOLOSCAN_ONNX_INFER_CORE_H #include <cuda.h> #include <cuda_runtime.h> #include <cuda_runtime_api.h> #include <onnxruntime_c_api.h> #include <onnxruntime_cxx_api.h> #include <chrono> #include <cmath> #include <exception> #include <fstream> #include <iostream> #include <limits> #include <memory> #include <numeric> #include <string> #include <vector> #include <holoinfer_constants.hpp> #include <infer/infer.hpp> namespace holoscan { namespace inference { class OnnxInfer : public InferBase { public: OnnxInfer(const std::string& model_file_path, bool cuda_flag); InferStatus do_inference(const std::vector<std::shared_ptr<DataBuffer>>& input_data, std::vector<std::shared_ptr<DataBuffer>>& output_buffer); void populate_model_details(); void print_model_details(); int set_holoscan_inf_onnx_session_options(); std::vector<std::vector<int64_t>> get_input_dims() const; std::vector<std::vector<int64_t>> get_output_dims() const; std::vector<holoinfer_datatype> get_input_datatype() const; std::vector<holoinfer_datatype> get_output_datatype() const; void cleanup() { session_.reset(); env_.reset(); } private: std::string model_path_{""}; bool use_cuda_ = true; Ort::SessionOptions session_options_; OrtCUDAProviderOptions cuda_options_{}; std::unique_ptr<Ort::Env> env_ = nullptr; std::unique_ptr<Ort::Session> session_ = nullptr; Ort::AllocatorWithDefaultOptions allocator_; size_t input_nodes_{0}, output_nodes_{0}; std::vector<std::vector<int64_t>> input_dims_{}; std::vector<std::vector<int64_t>> output_dims_{}; std::vector<holoinfer_datatype> input_type_, output_type_; std::vector<const char*> input_names_; std::vector<const char*> output_names_; std::vector<Ort::Value> input_tensors_; std::vector<Ort::Value> output_tensors_; std::vector<Ort::Value> input_tensors_gpu_; std::vector<Ort::Value> output_tensors_gpu_; Ort::MemoryInfo memory_info_ = Ort::MemoryInfo::CreateCpu(OrtAllocatorType::OrtArenaAllocator, OrtMemType::OrtMemTypeDefault); Ort::MemoryInfo memory_info_cuda_ = Ort::MemoryInfo("Cuda", OrtAllocatorType::OrtArenaAllocator, 0, OrtMemTypeDefault); std::unique_ptr<Ort::Allocator> memory_allocator_cuda_; holoinfer_datatype get_holoinfer_datatype(ONNXTensorElementDataType datatype); Ort::Value create_tensor(const std::shared_ptr<DataBuffer>& input_buffer, const std::vector<int64_t>& dims); void transfer_to_output(std::vector<std::shared_ptr<DataBuffer>>& output_buffer, const size_t& index); }; } // namespace inference } // namespace holoscan #endif

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