mindspore/serving/acl/acl_session.cc

244 lines
8.1 KiB
C++

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