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/**
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* Copyright 2019-2020 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 "ge_runtime/runtime_model.h"
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#include <set>
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#include "./model_context.h"
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#include "./task/task.h"
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#include "common/ge_inner_error_codes.h"
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#include "common/types.h"
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#include "common/util.h"
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#include "framework/common/debug/ge_log.h"
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#include "framework/common/op/op_parser_util.h"
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#include "graph/types.h"
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#include "task/task_factory.h"
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namespace ge {
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namespace model_runner {
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namespace {
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const int kOffsetUnit = 8;
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const uint32_t kStringHeadElems = 2;
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} // namespace
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RuntimeModel::~RuntimeModel() {
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GELOGI("RuntimeModel destructor start");
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// Unbind rtModel from all task related streams
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RtModelUnbindStream();
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// Release task first, hccl task hold stream
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task_list_.clear();
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// Release all task related streams
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RtStreamDestory();
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// Release rtlabel resource
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RtLabelDestory();
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// Release rtEvent resourece
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RtEventDestory();
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GELOGI("Do RtModelDestory");
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// Release all rt_model
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RtModelDestory();
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}
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bool RuntimeModel::InitStream(std::shared_ptr<DavinciModel> &davinci_model) {
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if (davinci_model == nullptr) {
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GELOGE(PARAM_INVALID, "Davinci model is null.");
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return false;
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}
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std::set<int64_t> wait_active_streams;
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std::set<int64_t> force_copy_streams;
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for (const auto &stream_id : davinci_model->GetWaitActiveStreams()) {
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GELOGI("stream id %u is wait active stream.", stream_id);
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(void)wait_active_streams.insert(stream_id);
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}
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for (const auto &stream_id : davinci_model->GetForceCopyStreams()) {
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GELOGI("stream id %u is force copy stream.", stream_id);
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(void)force_copy_streams.insert(stream_id);
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}
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GELOGI("stream number:%u", davinci_model->GetStreamNum());
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for (uint32_t i = 0; i < davinci_model->GetStreamNum(); ++i) {
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rtStream_t stream = nullptr;
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uint32_t flag = (force_copy_streams.find(i) != force_copy_streams.end())
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? (RT_STREAM_PERSISTENT | RT_STREAM_FORCE_COPY)
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: (RT_STREAM_PERSISTENT);
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rtError_t rt_ret = rtStreamCreateWithFlags(&stream, davinci_model->GetPriority(), flag);
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if (rt_ret != RT_ERROR_NONE) {
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GELOGE(RT_FAILED, "Call rt api rtStreamCreate failed, ret: 0x%X", rt_ret);
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return false;
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}
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GELOGI("rtStreamCreateWithFlags end.");
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stream_list_.emplace_back(stream);
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// Bind rt_model_handle_ to all task related streams
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flag = (wait_active_streams.find(i) != wait_active_streams.end()) ? (static_cast<uint32_t>(RT_INVALID_FLAG))
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: (static_cast<uint32_t>(RT_HEAD_STREAM));
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rt_ret = rtModelBindStream(rt_model_handle_, stream, flag);
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if (rt_ret != RT_ERROR_NONE) {
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GELOGE(RT_FAILED, "Call rt api rtModelBindStream failed, ret: 0x%X", rt_ret);
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return false;
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}
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GELOGI("stream index:%u, stream:%p.", i, stream);
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}
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return true;
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}
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bool RuntimeModel::InitEvent(uint32_t event_num) {
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GELOGI("event number:%u.", event_num);
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for (uint32_t i = 0; i < event_num; ++i) {
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rtEvent_t rt_event;
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rtError_t rt_ret = rtEventCreate(&rt_event);
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if (rt_ret != RT_ERROR_NONE) {
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GELOGE(RT_FAILED, "Call rt api rtEventCreate failed, i; %u; ret: 0x%X", i, rt_ret);
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return false;
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}
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event_list_.push_back(rt_event);
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}
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return true;
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}
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bool RuntimeModel::InitLabel(std::shared_ptr<DavinciModel> &davinci_model) {
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GELOGI("batch number:%u.", davinci_model->GetBatchNum());
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label_list_.resize(davinci_model->GetBatchNum());
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for (auto &task_info : davinci_model->GetTaskInfoList()) {
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if (task_info == nullptr) {
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GELOGE(PARAM_INVALID, "task_info is null.");
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continue;
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}
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if (task_info->type() != TaskInfoType::LABEL_SET) {
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continue;
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}
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auto label_set_task_info = std::static_pointer_cast<LabelSetTaskInfo>(task_info);
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if (label_set_task_info->stream_id() >= stream_list_.size()) {
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GELOGE(PARAM_INVALID, "Invalid stream id.");
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return false;
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}
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rtLabel_t rt_label = nullptr;
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rtError_t rt_ret = rtLabelCreateEx(&rt_label, stream_list_[label_set_task_info->stream_id()]);
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if (rt_ret != RT_ERROR_NONE) {
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GELOGE(RT_FAILED, "Call rt api rtLabelCreate failed, ret: 0x%X", rt_ret);
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return false;
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}
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label_list_[label_set_task_info->label_id()] = rt_label;
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}
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return true;
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}
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bool RuntimeModel::InitResource(std::shared_ptr<DavinciModel> &davinci_model) {
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GELOGI("InitResource start");
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if (davinci_model == nullptr) {
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GELOGE(PARAM_INVALID, "davinci model is null");
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return false;
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}
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rtError_t rt_ret = rtModelCreate(&rt_model_handle_, 0);
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if (rt_ret != RT_ERROR_NONE) {
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GELOGE(RT_FAILED, "Call rt api rtModelCreate failed, ret: 0x%X", rt_ret);
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return false;
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}
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// Create rtStream for rt_model_handle_
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rt_ret = rtStreamCreate(&rt_model_stream_, davinci_model->GetPriority());
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if (rt_ret != RT_ERROR_NONE) {
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GELOGE(RT_FAILED, "Call rt api rtStreamCreate failed, ret: 0x%X", rt_ret);
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return false;
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}
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GELOGI("rtStreamCreate end");
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if (!InitStream(davinci_model)) {
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return false;
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}
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if (!InitEvent(davinci_model->GetEventNum())) {
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return false;
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}
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if (!InitLabel(davinci_model)) {
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return false;
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}
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GELOGI("InitResource succ");
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return true;
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}
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void RuntimeModel::GenerateTask(uint32_t device_id, uint64_t session_id, std::shared_ptr<DavinciModel> &davinci_model) {
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GELOGI("GenerateTask start.");
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if (davinci_model == nullptr) {
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GELOGE(PARAM_INVALID, "davinci model is null");
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return;
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}
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auto task_infos = davinci_model->GetTaskInfoList();
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ModelContext model_context(device_id, session_id, davinci_model->GetPriority(), rt_model_handle_, rt_model_stream_,
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stream_list_, label_list_, event_list_);
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for (auto &task_info : task_infos) {
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auto task = TaskFactory::GetInstance().Create(model_context, task_info);
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task_list_.push_back(task);
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}
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GELOGI("GenerateTask succ.");
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}
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bool RuntimeModel::LoadTask() {
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GELOGI("LoadTask start.");
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for (auto &task : task_list_) {
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if (task == nullptr) {
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GELOGE(PARAM_INVALID, "task is null.");
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continue;
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}
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bool ret = task->Distribute();
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if (!ret) {
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GELOGE(FAILED, "task distribute fail.");
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return false;
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}
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uint32_t task_id = 0;
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uint32_t stream_id = 0;
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rtError_t rt_ret = rtModelGetTaskId(rt_model_handle_, &task_id, &stream_id);
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if (rt_ret != RT_ERROR_NONE) {
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GELOGE(RT_FAILED, "Call rt api failed, ret: 0x%X.", rt_ret);
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return false;
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}
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task_id_list_.push_back(task_id);
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stream_id_list_.push_back(stream_id);
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if (task->Args() != nullptr) {
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std::shared_ptr<RuntimeInfo> runtime_tuple = nullptr;
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GE_MAKE_SHARED(runtime_tuple = std::make_shared<RuntimeInfo>(task_id, stream_id, task->Args()), return false);
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auto emplace_ret = runtime_info_map_.emplace(task->task_name(), runtime_tuple);
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if (!emplace_ret.second) {
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GELOGW("Task name exist:%s", task->task_name().c_str());
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}
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}
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}
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if (task_list_.empty()) {
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GELOGE(FAILED, "Task list is empty");
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return false;
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}
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GELOGI("LoadTask succ.");
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return true;
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}
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bool RuntimeModel::LoadComplete() {
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uint32_t task_id = 0;
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uint32_t stream_id = 0;
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auto rt_ret = rtModelGetTaskId(rt_model_handle_, &task_id, &stream_id);
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if (rt_ret != RT_ERROR_NONE) {
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GELOGE(RT_FAILED, "Call rtModelGetTaskId failed, ret:0x%X", rt_ret);
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return RT_FAILED;
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}
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task_id_list_.push_back(task_id);
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stream_id_list_.push_back(stream_id);
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rt_ret = rtModelLoadComplete(rt_model_handle_);
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if (rt_ret != RT_ERROR_NONE) {
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GELOGE(RT_FAILED, "Call rt api rtModelLoadComplete failed, ret: 0x%X.", rt_ret);
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return false;
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}
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return true;
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}
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bool RuntimeModel::Load(uint32_t device_id, uint64_t session_id, std::shared_ptr<DavinciModel> &davinci_model) {
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bool status = InitResource(davinci_model);
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if (!status) {
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GELOGE(FAILED, "InitResource failed.");
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return status;
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}
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status = InitDataInfo(davinci_model);
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if (!status) {
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GELOGE(FAILED, "InitDataInfo failed.");
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return status;
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}
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status = InitOutputInfo(davinci_model);
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if (!status) {
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GELOGE(FAILED, "InitOutputInfo failed.");
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return status;
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}
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status = InitConstantInfo(davinci_model);
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if (!status) {
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GELOGE(FAILED, "InitConstantInfo failed.");
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return status;
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}
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GenerateTask(device_id, session_id, davinci_model);
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return status;
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}
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bool RuntimeModel::DistributeTask() {
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bool status = LoadTask();
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if (!status) {
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GELOGE(FAILED, "DistributeTask failed");
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return false;
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}
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return true;
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}
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bool RuntimeModel::Run() {
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GELOGI("Davinci task run start");
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rtError_t ret = rtModelExecute(rt_model_handle_, rt_model_stream_, 0);
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if (ret != RT_ERROR_NONE) {
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GELOGE(RT_FAILED, "Model execute failed, ret = 0x%X", ret);
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return false;
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}
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GELOGI("Run rtModelExecute success, ret = 0x%X", ret);
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ret = rtStreamSynchronize(rt_model_stream_);
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if (ret != RT_ERROR_NONE) {
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if (ret == ACL_ERROR_RT_END_OF_SEQUENCE) {
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GELOGI("Model stream ACL_ERROR_RT_END_OF_SEQUENCE signal received, ret = 0x%X", ret);
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return true;
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}
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GELOGE(RT_FAILED, "Model stream sync failed, ret = 0x%X", ret);
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return false;
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}
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GELOGI("Davinci task run succ.");
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return true;
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}
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void RuntimeModel::RtModelUnbindStream() noexcept {
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for (size_t i = 0; i < stream_list_.size(); i++) {
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if (rtModelUnbindStream(rt_model_handle_, stream_list_[i]) != RT_ERROR_NONE) {
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GELOGE(RT_FAILED, "Unbind stream from model failed! Index: %zu", i);
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return;
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}
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}
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}
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void RuntimeModel::RtStreamDestory() noexcept {
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if (rtStreamDestroy(rt_model_stream_) != RT_ERROR_NONE) {
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GELOGE(RT_FAILED, "Destroy stream for rt_model failed!");
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return;
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}
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for (size_t i = 0; i < stream_list_.size(); i++) {
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if (rtStreamDestroy(stream_list_[i]) != RT_ERROR_NONE) {
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GELOGE(RT_FAILED, "Destroy stream failed! Index: %zu", i);
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return;
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}
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}
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}
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void RuntimeModel::RtLabelDestory() noexcept {
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for (size_t i = 0; i < label_list_.size(); i++) {
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if (label_list_[i] == nullptr) {
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continue;
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}
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if (rtLabelDestroy(label_list_[i]) != RT_ERROR_NONE) {
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GELOGE(RT_FAILED, "Destroy label failed! Index: %zu.", i);
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return;
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}
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}
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}
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|
|
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|
|
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|
void RuntimeModel::RtModelDestory() noexcept {
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|
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|
rtError_t ret = rtModelDestroy(rt_model_handle_);
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|
|
|
if (ret != RT_ERROR_NONE) {
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|
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|
GELOGE(RT_FAILED, "Call rt api failed, ret: 0x%X", ret);
|
|
|
|
return;
|
|
|
|
}
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|
|
|
}
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|
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|
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|
void RuntimeModel::RtEventDestory() noexcept {
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|
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|
for (size_t i = 0; i < event_list_.size(); i++) {
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|
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|
if (rtEventDestroy(event_list_[i]) != RT_ERROR_NONE) {
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|
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|
GELOGE(RT_FAILED, "Destroy event failed! Index: %zu", i);
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|
|
|
return;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
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|
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|
bool RuntimeModel::InitDataInfo(std::shared_ptr<DavinciModel> &davinci_model) { return true; }
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|
bool RuntimeModel::InitOutputInfo(std::shared_ptr<DavinciModel> &davinci_model) {
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|
|
|
if (davinci_model == nullptr) {
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|
|
|
GELOGE(PARAM_INVALID, "davinci model is null");
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|
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|
return false;
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|
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|
}
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|
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|
output_info_list_ = davinci_model->GetOutputInfoList();
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|
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|
return true;
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|
|
|
}
|
|
|
|
|
|
|
|
bool RuntimeModel::CopyInputData(const InputData &input_data) {
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|
|
|
if (input_data.blobs.size() != data_info_list_.size()) {
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|
|
|
GELOGE(PARAM_INVALID, "The input data list size (%zu) does not match the model input list size (%zu)",
|
|
|
|
input_data.blobs.size(), data_info_list_.size());
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|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
for (const auto &data_info : data_info_list_) {
|
|
|
|
if (data_info == nullptr) {
|
|
|
|
GELOGE(PARAM_INVALID, "data info is null.");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
bool ret = CopyInputDataToModel(input_data.blobs, data_info);
|
|
|
|
if (!ret) {
|
|
|
|
GELOGE(FAILED, "Copy input data to model ret fail, data_info: %s, model id: %u", data_info->name.c_str(),
|
|
|
|
input_data.model_id);
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
bool RuntimeModel::CopyInputDataToModel(const std::vector<DataBuffer> &data, const std::shared_ptr<OpInfo> &data_info) {
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
bool RuntimeModel::CopyHostData(const std::vector<DataBuffer> &data, const std::shared_ptr<OpInfo> &data_info) const {
|
|
|
|
GELOGI("Start CopyHostData.");
|
|
|
|
if (data.empty()) {
|
|
|
|
GELOGE(PARAM_INVALID, "data buffer is empty.");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
if (data_info == nullptr) {
|
|
|
|
GELOGE(PARAM_INVALID, "data info is null.");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
void *host_data_addr = data[data_info->index].data;
|
|
|
|
uint32_t copy_size = data[data_info->index].length;
|
|
|
|
GELOGD("data output tensor is aipp tensor,copy data only.");
|
|
|
|
|
|
|
|
const std::vector<uintptr_t> &outputs = data_info->output_addrs;
|
|
|
|
if (outputs.empty()) {
|
|
|
|
GELOGE(PARAM_INVALID, "Output addrs is empty.");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Copy input data to data nodes
|
|
|
|
void *data_out_addr = reinterpret_cast<void *>(outputs[0]);
|
|
|
|
|
|
|
|
rtError_t rt_ret = rtMemcpy(data_out_addr, copy_size, host_data_addr, copy_size, RT_MEMCPY_HOST_TO_DEVICE);
|
|
|
|
if (rt_ret != RT_ERROR_NONE) {
|
|
|
|
GELOGE(RT_FAILED, "Call rt api failed, ret: 0x%X", rt_ret);
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
bool RuntimeModel::CopyTransData(const std::vector<DataBuffer> &data, const std::shared_ptr<OpInfo> &data_info) {
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
bool RuntimeModel::InitConstantInfo(std::shared_ptr<DavinciModel> &davinci_model) {
|
|
|
|
// Const no input, only 1 output, and this output has no data
|
|
|
|
// weight data copy to output mem
|
|
|
|
if (davinci_model == nullptr) {
|
|
|
|
GELOGE(PARAM_INVALID, "Davinci model is null.");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
constant_info_list_ = davinci_model->GetConstantInfoList();
|
|
|
|
|
|
|
|
for (const auto &constant : constant_info_list_) {
|
|
|
|
if (constant == nullptr) {
|
|
|
|
GELOGE(PARAM_INVALID, "constant is null");
|
|
|
|
continue;
|
|
|
|
}
|
|
|
|
if (constant->output_tensors.empty()) {
|
|
|
|
GELOGE(PARAM_INVALID, "Output tensors is empty");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
if (constant->weight_tensors.empty()) {
|
|
|
|
GELOGE(PARAM_INVALID, "Weight tensors is empty");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
if (constant->output_tensors[0].size < constant->weight_data.size()) {
|
|
|
|
GELOGE(PARAM_INVALID, "Output size:%u is less than weight data size:%zu", constant->output_tensors[0].size,
|
|
|
|
constant->weight_data.size());
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
|
|
|
|
if (constant->weight_data.empty()) {
|
|
|
|
GELOGW("Const op:%s has no weight data.", constant->name.c_str());
|
|
|
|
continue;
|
|
|
|
}
|
|
|
|
|
|
|
|
if (constant->weight_tensors[0].datatype == DT_STRING) {
|
|
|
|
/// If tensor is a scaler, it's shape size if zero, according ge_tensor.cc.
|
|
|
|
/// The logic of GetShapeSize is wrong, the scaler tensor's GetShapeSize is zero
|
|
|
|
/// and that of unknown shape is zero too.
|
|
|
|
/// Unknown shape will not appear here, so we can use zero judge a tensor is scaler or not.
|
|
|
|
int64_t elem_num =
|
|
|
|
(constant->weight_tensors[0].GetShapeSize() == 0) ? 1 : constant->weight_tensors[0].GetShapeSize();
|
|
|
|
if (constant->weight_data.size() < sizeof(uint64_t)) {
|
|
|
|
GELOGE(FAILED, "weight_data size is smaller than sizeof(uint64_t)");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
uint64_t *buff = reinterpret_cast<uint64_t *>(const_cast<char *>(constant->weight_data.data()));
|
|
|
|
uint32_t head_len = kOffsetUnit * kStringHeadElems;
|
|
|
|
if (ge::CheckInt64Uint32MulOverflow(elem_num, head_len) != SUCCESS) {
|
|
|
|
GELOGE(FAILED, "Shape size is invalid");
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
int64_t offset = elem_num * head_len;
|
|
|
|
uintptr_t hbm_raw_data_base_addr = reinterpret_cast<uintptr_t>(constant->output_addrs[0]) + offset;
|
|
|
|
for (int64_t i = elem_num - 1; i >= 0; --i) {
|
|
|
|
buff[i * kStringHeadElems] = hbm_raw_data_base_addr + (buff[i * kStringHeadElems] - buff[0]);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
rtError_t rt_ret = rtMemcpy(reinterpret_cast<void *>(constant->output_addrs[0]), constant->output_tensors[0].size,
|
|
|
|
constant->weight_data.data(), constant->weight_data.size(), RT_MEMCPY_HOST_TO_DEVICE);
|
|
|
|
if (rt_ret != RT_ERROR_NONE) {
|
|
|
|
GELOGE(RT_FAILED, "rtGetFunctionByName failed, ret: 0x%X", rt_ret);
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
bool RuntimeModel::GetInputOutputDescInfo(bool zero_copy, std::vector<InputOutputDescInfo> *input_desc,
|
|
|
|
std::vector<InputOutputDescInfo> *output_desc,
|
|
|
|
std::vector<uint32_t> *input_format, std::vector<uint32_t> *output_format) {
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
bool RuntimeModel::GetInputDescInfo(std::vector<InputOutputDescInfo> *input_desc, std::vector<uint32_t> *formats) {
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
bool RuntimeModel::GetOutputDescInfo(std::vector<InputOutputDescInfo> *output_desc, std::vector<uint32_t> *formats) {
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
void RuntimeModel::CreateOutput(uint32_t index, const OpInfo &op_info, InputOutputDescInfo *output,
|
|
|
|
uint32_t *format_result) {}
|
|
|
|
|
|
|
|
const std::vector<uint32_t> &RuntimeModel::GetTaskIdList() const { return task_id_list_; }
|
|
|
|
|
|
|
|
const std::vector<uint32_t> &RuntimeModel::GetStreamIdList() const { return stream_id_list_; }
|
|
|
|
} // namespace model_runner
|
|
|
|
} // namespace ge
|