forked from OSSInnovation/mindspore
244 lines
8.1 KiB
C++
244 lines
8.1 KiB
C++
/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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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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*/
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#include <memory>
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#include <algorithm>
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#include <fstream>
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#include "serving/acl/acl_session.h"
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#include "include/infer_log.h"
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namespace mindspore::inference {
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std::shared_ptr<InferSession> InferSession::CreateSession(const std::string &device, uint32_t device_id) {
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try {
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auto session = std::make_shared<AclSession>();
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auto ret = session->InitEnv(device, device_id);
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if (ret != SUCCESS) {
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return nullptr;
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}
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return session;
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} catch (std::exception &e) {
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MSI_LOG_ERROR << "Inference CreatSession failed";
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return nullptr;
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}
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}
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Status AclSession::LoadModelFromFile(const std::string &file_name, uint32_t &model_id) {
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Status ret = model_process_.LoadModelFromFile(file_name, model_id);
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if (ret != SUCCESS) {
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MSI_LOG_ERROR << "Load model from file failed, model file " << file_name;
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return FAILED;
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}
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std::string dvpp_config_file;
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auto index = file_name.rfind(".");
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if (index == std::string::npos) {
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dvpp_config_file = file_name;
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} else {
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dvpp_config_file = file_name.substr(0, index);
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}
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dvpp_config_file += "_dvpp_config.json";
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std::ifstream fp(dvpp_config_file);
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if (!fp.is_open()) {
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MSI_LOG_INFO << "Dvpp config file not exist, model will execute with tensors as inputs, dvpp config file "
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<< dvpp_config_file;
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return SUCCESS;
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}
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fp.close();
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if (dvpp_process_.InitWithJsonConfig(dvpp_config_file) != SUCCESS) {
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MSI_LOG_ERROR << "Dvpp config file parse error, dvpp config file " << dvpp_config_file;
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return FAILED;
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}
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execute_with_dvpp_ = true;
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MSI_LOG_INFO << "Dvpp config success";
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return SUCCESS;
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}
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Status AclSession::UnloadModel(uint32_t /*model_id*/) {
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model_process_.UnLoad();
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return SUCCESS;
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}
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Status AclSession::ExecuteModel(uint32_t /*model_id*/, const RequestBase &request,
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ReplyBase &reply) { // set d context
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aclError rt_ret = aclrtSetCurrentContext(context_);
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if (rt_ret != ACL_ERROR_NONE) {
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MSI_LOG_ERROR << "set the ascend device context failed";
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return FAILED;
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}
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return model_process_.Execute(request, reply);
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}
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Status AclSession::PreProcess(uint32_t /*model_id*/, const InferImagesBase *images_input,
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ImagesDvppOutput &dvpp_output) {
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if (images_input == nullptr) {
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MSI_LOG_ERROR << "images input is nullptr";
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return FAILED;
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}
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auto batch_size = images_input->batch_size();
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if (batch_size <= 0) {
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MSI_LOG_ERROR << "invalid batch size " << images_input->batch_size();
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return FAILED;
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}
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std::vector<const void *> pic_buffer_list;
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std::vector<size_t> pic_size_list;
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for (size_t i = 0; i < batch_size; i++) {
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const void *pic_buffer = nullptr;
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uint32_t pic_size = 0;
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if (!images_input->get(i, pic_buffer, pic_size) || pic_buffer == nullptr || pic_size == 0) {
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MSI_LOG_ERROR << "Get request " << 0 << "th buffer failed";
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return FAILED;
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}
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pic_buffer_list.push_back(pic_buffer);
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pic_size_list.push_back(pic_size);
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}
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auto ret = dvpp_process_.Process(pic_buffer_list, pic_size_list, dvpp_output.buffer_device, dvpp_output.buffer_size);
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if (ret != SUCCESS) {
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MSI_LOG_ERROR << "dvpp process failed";
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return ret;
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}
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return SUCCESS;
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}
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Status AclSession::ExecuteModel(uint32_t model_id, const ImagesRequestBase &images_inputs, // images for preprocess
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const RequestBase &request, ReplyBase &reply) {
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if (!execute_with_dvpp_) {
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MSI_LOG_ERROR << "Unexpected images as inputs, DVPP not config";
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return INFER_STATUS(INVALID_INPUTS) << "Unexpected images as inputs, DVPP not config";
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}
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aclError rt_ret = aclrtSetCurrentContext(context_);
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if (rt_ret != ACL_ERROR_NONE) {
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MSI_LOG_ERROR << "set the ascend device context failed";
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return FAILED;
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}
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if (images_inputs.size() != 1) {
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MSI_LOG_ERROR << "Only support one input to do DVPP preprocess";
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return INFER_STATUS(INVALID_INPUTS) << "Only support one input to do DVPP preprocess";
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}
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if (images_inputs[0] == nullptr) {
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MSI_LOG_ERROR << "Get first images input failed";
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return FAILED;
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}
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if (images_inputs[0]->batch_size() != model_process_.GetBatchSize()) {
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MSI_LOG_ERROR << "Input batch size " << images_inputs[0]->batch_size() << " not match Model batch size "
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<< model_process_.GetBatchSize();
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return INFER_STATUS(INVALID_INPUTS) << "Input batch size " << images_inputs[0]->batch_size()
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<< " not match Model batch size " << model_process_.GetBatchSize();
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}
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if (request.size() != 0) {
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MSI_LOG_ERROR << "only support one input, images input size is 1, tensor inputs is not 0 " << request.size();
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return INFER_STATUS(INVALID_INPUTS) << "only support one input, images input size is 1, tensor inputs is not 0 "
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<< request.size();
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}
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ImagesDvppOutput dvpp_output;
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Status ret = PreProcess(model_id, images_inputs[0], dvpp_output);
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if (ret != SUCCESS) {
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MSI_LOG_ERROR << "DVPP preprocess failed";
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return ret;
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}
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ret = model_process_.Execute(dvpp_output.buffer_device, dvpp_output.buffer_size, reply);
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if (ret != SUCCESS) {
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MSI_LOG_ERROR << "Execute model failed";
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return ret;
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}
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return SUCCESS;
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}
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Status AclSession::InitEnv(const std::string &device_type, uint32_t device_id) {
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device_type_ = device_type;
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device_id_ = device_id;
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auto ret = aclInit(nullptr);
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if (ret != ACL_ERROR_NONE) {
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MSI_LOG_ERROR << "Execute aclInit Failed";
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return FAILED;
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}
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MSI_LOG_INFO << "acl init success";
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ret = aclrtSetDevice(device_id_);
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if (ret != ACL_ERROR_NONE) {
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MSI_LOG_ERROR << "acl open device " << device_id_ << " failed";
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return FAILED;
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}
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MSI_LOG_INFO << "open device " << device_id_ << " success";
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ret = aclrtCreateContext(&context_, device_id_);
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if (ret != ACL_ERROR_NONE) {
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MSI_LOG_ERROR << "acl create context failed";
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return FAILED;
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}
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MSI_LOG_INFO << "create context success";
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ret = aclrtCreateStream(&stream_);
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if (ret != ACL_ERROR_NONE) {
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MSI_LOG_ERROR << "acl create stream failed";
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return FAILED;
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}
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MSI_LOG_INFO << "create stream success";
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aclrtRunMode run_mode;
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ret = aclrtGetRunMode(&run_mode);
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if (ret != ACL_ERROR_NONE) {
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MSI_LOG_ERROR << "acl get run mode failed";
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return FAILED;
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}
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bool is_device = (run_mode == ACL_DEVICE);
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model_process_.SetIsDevice(is_device);
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MSI_LOG_INFO << "get run mode success is device input/output " << is_device;
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if (dvpp_process_.InitResource(stream_) != SUCCESS) {
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MSI_LOG_ERROR << "dvpp init resource failed";
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return FAILED;
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}
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MSI_LOG_INFO << "Init acl success, device id " << device_id_;
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return SUCCESS;
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}
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Status AclSession::FinalizeEnv() {
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dvpp_process_.Finalize();
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aclError ret;
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if (stream_ != nullptr) {
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ret = aclrtDestroyStream(stream_);
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if (ret != ACL_ERROR_NONE) {
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MSI_LOG_ERROR << "destroy stream failed";
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}
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stream_ = nullptr;
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}
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MSI_LOG_INFO << "end to destroy stream";
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if (context_ != nullptr) {
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ret = aclrtDestroyContext(context_);
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if (ret != ACL_ERROR_NONE) {
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MSI_LOG_ERROR << "destroy context failed";
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}
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context_ = nullptr;
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}
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MSI_LOG_INFO << "end to destroy context";
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ret = aclrtResetDevice(device_id_);
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if (ret != ACL_ERROR_NONE) {
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MSI_LOG_ERROR << "reset devie " << device_id_ << " failed";
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}
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MSI_LOG_INFO << "end to reset device " << device_id_;
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ret = aclFinalize();
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if (ret != ACL_ERROR_NONE) {
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MSI_LOG_ERROR << "finalize acl failed";
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}
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MSI_LOG_INFO << "end to finalize acl";
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return SUCCESS;
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}
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AclSession::AclSession() = default;
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} // namespace mindspore::inference
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