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runtime_model.cc 18 kB

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  1. /**
  2. * Copyright 2019-2020 Huawei Technologies Co., Ltd
  3. *
  4. * Licensed under the Apache License, Version 2.0 (the "License");
  5. * you may not use this file except in compliance with the License.
  6. * You may obtain a copy of the License at
  7. *
  8. * http://www.apache.org/licenses/LICENSE-2.0
  9. *
  10. * Unless required by applicable law or agreed to in writing, software
  11. * distributed under the License is distributed on an "AS IS" BASIS,
  12. * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  13. * See the License for the specific language governing permissions and
  14. * limitations under the License.
  15. */
  16. #include "ge_runtime/runtime_model.h"
  17. #include <set>
  18. #include "./model_context.h"
  19. #include "./task/task.h"
  20. #include "common/ge_inner_error_codes.h"
  21. #include "common/types.h"
  22. #include "common/util.h"
  23. #include "common/math/math_util.h"
  24. #include "framework/common/debug/ge_log.h"
  25. #include "framework/common/op/op_parser_util.h"
  26. #include "graph/types.h"
  27. #include "task/task_factory.h"
  28. namespace ge {
  29. namespace model_runner {
  30. namespace {
  31. const int kOffsetUnit = 8;
  32. const uint32_t kStringHeadElems = 2;
  33. } // namespace
  34. RuntimeModel::~RuntimeModel() {
  35. GELOGI("RuntimeModel destructor start");
  36. // Unbind rtModel from all task related streams
  37. RtModelUnbindStream();
  38. // Release task first, hccl task hold stream
  39. task_list_.clear();
  40. // Release all task related streams
  41. RtStreamDestory();
  42. // Release rtlabel resource
  43. RtLabelDestory();
  44. // Release rtEvent resourece
  45. RtEventDestory();
  46. GELOGI("Do RtModelDestory");
  47. // Release all rt_model
  48. RtModelDestory();
  49. }
  50. bool RuntimeModel::InitStream(std::shared_ptr<DavinciModel> &davinci_model) {
  51. if (davinci_model == nullptr) {
  52. GELOGE(PARAM_INVALID, "Davinci model is null.");
  53. return false;
  54. }
  55. std::set<int64_t> wait_active_streams;
  56. std::set<int64_t> force_copy_streams;
  57. for (const auto &stream_id : davinci_model->GetWaitActiveStreams()) {
  58. GELOGI("stream id %u is wait active stream.", stream_id);
  59. (void)wait_active_streams.insert(stream_id);
  60. }
  61. for (const auto &stream_id : davinci_model->GetForceCopyStreams()) {
  62. GELOGI("stream id %u is force copy stream.", stream_id);
  63. (void)force_copy_streams.insert(stream_id);
  64. }
  65. GELOGI("stream number:%u", davinci_model->GetStreamNum());
  66. for (uint32_t i = 0; i < davinci_model->GetStreamNum(); ++i) {
  67. rtStream_t stream = nullptr;
  68. uint32_t flag = (force_copy_streams.find(i) != force_copy_streams.end())
  69. ? (RT_STREAM_PERSISTENT | RT_STREAM_FORCE_COPY)
  70. : (RT_STREAM_PERSISTENT);
  71. rtError_t rt_ret = rtStreamCreateWithFlags(&stream, davinci_model->GetPriority(), flag);
  72. if (rt_ret != RT_ERROR_NONE) {
  73. GELOGE(RT_FAILED, "Call rt api rtStreamCreate failed, ret: 0x%X", rt_ret);
  74. return false;
  75. }
  76. GELOGI("rtStreamCreateWithFlags end.");
  77. stream_list_.emplace_back(stream);
  78. // Bind rt_model_handle_ to all task related streams
  79. flag = (wait_active_streams.find(i) != wait_active_streams.end()) ? (static_cast<uint32_t>(RT_INVALID_FLAG))
  80. : (static_cast<uint32_t>(RT_HEAD_STREAM));
  81. rt_ret = rtModelBindStream(rt_model_handle_, stream, flag);
  82. if (rt_ret != RT_ERROR_NONE) {
  83. GELOGE(RT_FAILED, "Call rt api rtModelBindStream failed, ret: 0x%X", rt_ret);
  84. return false;
  85. }
  86. GELOGI("stream index:%u, stream:%p.", i, stream);
  87. }
  88. return true;
  89. }
  90. bool RuntimeModel::InitEvent(uint32_t event_num) {
  91. GELOGI("event number:%u.", event_num);
  92. for (uint32_t i = 0; i < event_num; ++i) {
  93. rtEvent_t rt_event;
  94. rtError_t rt_ret = rtEventCreate(&rt_event);
  95. if (rt_ret != RT_ERROR_NONE) {
  96. GELOGE(RT_FAILED, "Call rt api rtEventCreate failed, i; %u; ret: 0x%X", i, rt_ret);
  97. return false;
  98. }
  99. event_list_.push_back(rt_event);
  100. }
  101. return true;
  102. }
  103. bool RuntimeModel::InitLabel(std::shared_ptr<DavinciModel> &davinci_model) {
  104. GELOGI("batch number:%u.", davinci_model->GetBatchNum());
  105. label_list_.resize(davinci_model->GetBatchNum());
  106. for (auto &task_info : davinci_model->GetTaskInfoList()) {
  107. if (task_info == nullptr) {
  108. GELOGE(PARAM_INVALID, "task_info is null.");
  109. continue;
  110. }
  111. if (task_info->type() != TaskInfoType::LABEL_SET) {
  112. continue;
  113. }
  114. auto label_set_task_info = std::static_pointer_cast<LabelSetTaskInfo>(task_info);
  115. if (label_set_task_info->stream_id() >= stream_list_.size()) {
  116. GELOGE(PARAM_INVALID, "Invalid stream id.");
  117. return false;
  118. }
  119. rtLabel_t rt_label = nullptr;
  120. rtError_t rt_ret = rtLabelCreateEx(&rt_label, stream_list_[label_set_task_info->stream_id()]);
  121. if (rt_ret != RT_ERROR_NONE) {
  122. GELOGE(RT_FAILED, "Call rt api rtLabelCreate failed, ret: 0x%X", rt_ret);
  123. return false;
  124. }
  125. label_list_[label_set_task_info->label_id()] = rt_label;
  126. }
  127. return true;
  128. }
  129. bool RuntimeModel::InitResource(std::shared_ptr<DavinciModel> &davinci_model) {
  130. GELOGI("InitResource start");
  131. if (davinci_model == nullptr) {
  132. GELOGE(PARAM_INVALID, "davinci model is null");
  133. return false;
  134. }
  135. rtError_t rt_ret = rtModelCreate(&rt_model_handle_, 0);
  136. if (rt_ret != RT_ERROR_NONE) {
  137. GELOGE(RT_FAILED, "Call rt api rtModelCreate failed, ret: 0x%X", rt_ret);
  138. return false;
  139. }
  140. // Create rtStream for rt_model_handle_
  141. rt_ret = rtStreamCreate(&rt_model_stream_, davinci_model->GetPriority());
  142. if (rt_ret != RT_ERROR_NONE) {
  143. GELOGE(RT_FAILED, "Call rt api rtStreamCreate failed, ret: 0x%X", rt_ret);
  144. return false;
  145. }
  146. GELOGI("rtStreamCreate end");
  147. if (!InitStream(davinci_model)) {
  148. return false;
  149. }
  150. if (!InitEvent(davinci_model->GetEventNum())) {
  151. return false;
  152. }
  153. if (!InitLabel(davinci_model)) {
  154. return false;
  155. }
  156. GELOGI("InitResource succ");
  157. return true;
  158. }
  159. void RuntimeModel::GenerateTask(uint32_t device_id, uint64_t session_id, std::shared_ptr<DavinciModel> &davinci_model) {
  160. GELOGI("GenerateTask start.");
  161. if (davinci_model == nullptr) {
  162. GELOGE(PARAM_INVALID, "davinci model is null");
  163. return;
  164. }
  165. auto task_infos = davinci_model->GetTaskInfoList();
  166. ModelContext model_context(device_id, session_id, davinci_model->GetPriority(), rt_model_handle_, rt_model_stream_,
  167. stream_list_, label_list_, event_list_);
  168. for (auto &task_info : task_infos) {
  169. auto task = TaskFactory::GetInstance().Create(model_context, task_info);
  170. task_list_.push_back(task);
  171. }
  172. GELOGI("GenerateTask succ.");
  173. }
  174. bool RuntimeModel::LoadTask() {
  175. GELOGI("LoadTask start.");
  176. for (auto &task : task_list_) {
  177. if (task == nullptr) {
  178. GELOGE(PARAM_INVALID, "task is null.");
  179. continue;
  180. }
  181. bool ret = task->Distribute();
  182. if (!ret) {
  183. GELOGE(FAILED, "task distribute fail.");
  184. return false;
  185. }
  186. uint32_t task_id = 0;
  187. uint32_t stream_id = 0;
  188. rtError_t rt_ret = rtModelGetTaskId(rt_model_handle_, &task_id, &stream_id);
  189. if (rt_ret != RT_ERROR_NONE) {
  190. GELOGE(RT_FAILED, "Call rt api failed, ret: 0x%X.", rt_ret);
  191. return false;
  192. }
  193. task_id_list_.push_back(task_id);
  194. stream_id_list_.push_back(stream_id);
  195. if (task->Args() != nullptr) {
  196. std::shared_ptr<RuntimeInfo> runtime_tuple = nullptr;
  197. GE_MAKE_SHARED(runtime_tuple = std::make_shared<RuntimeInfo>(task_id, stream_id, task->Args()), return false);
  198. auto emplace_ret = runtime_info_map_.emplace(task->task_name(), runtime_tuple);
  199. if (!emplace_ret.second) {
  200. GELOGW("Task name exist:%s", task->task_name().c_str());
  201. }
  202. }
  203. }
  204. if (task_list_.empty()) {
  205. GELOGE(FAILED, "Task list is empty");
  206. return false;
  207. }
  208. GELOGI("LoadTask succ.");
  209. return true;
  210. }
  211. bool RuntimeModel::LoadComplete() {
  212. uint32_t task_id = 0;
  213. uint32_t stream_id = 0;
  214. auto rt_ret = rtModelGetTaskId(rt_model_handle_, &task_id, &stream_id);
  215. if (rt_ret != RT_ERROR_NONE) {
  216. GELOGE(RT_FAILED, "Call rtModelGetTaskId failed, ret:0x%X", rt_ret);
  217. return RT_FAILED;
  218. }
  219. task_id_list_.push_back(task_id);
  220. stream_id_list_.push_back(stream_id);
  221. rt_ret = rtModelLoadComplete(rt_model_handle_);
  222. if (rt_ret != RT_ERROR_NONE) {
  223. GELOGE(RT_FAILED, "Call rt api rtModelLoadComplete failed, ret: 0x%X.", rt_ret);
  224. return false;
  225. }
  226. return true;
  227. }
  228. bool RuntimeModel::Load(uint32_t device_id, uint64_t session_id, std::shared_ptr<DavinciModel> &davinci_model) {
  229. bool status = InitResource(davinci_model);
  230. if (!status) {
  231. GELOGE(FAILED, "InitResource failed.");
  232. return status;
  233. }
  234. status = InitDataInfo(davinci_model);
  235. if (!status) {
  236. GELOGE(FAILED, "InitDataInfo failed.");
  237. return status;
  238. }
  239. status = InitOutputInfo(davinci_model);
  240. if (!status) {
  241. GELOGE(FAILED, "InitOutputInfo failed.");
  242. return status;
  243. }
  244. status = InitConstantInfo(davinci_model);
  245. if (!status) {
  246. GELOGE(FAILED, "InitConstantInfo failed.");
  247. return status;
  248. }
  249. GenerateTask(device_id, session_id, davinci_model);
  250. return status;
  251. }
  252. bool RuntimeModel::DistributeTask() {
  253. bool status = LoadTask();
  254. if (!status) {
  255. GELOGE(FAILED, "DistributeTask failed");
  256. return false;
  257. }
  258. return true;
  259. }
  260. bool RuntimeModel::Run() {
  261. GELOGI("Davinci task run start");
  262. rtError_t ret = rtModelExecute(rt_model_handle_, rt_model_stream_, 0);
  263. if (ret != RT_ERROR_NONE) {
  264. GELOGE(RT_FAILED, "Model execute failed, ret = 0x%X", ret);
  265. return false;
  266. }
  267. GELOGI("Run rtModelExecute success, ret = 0x%X", ret);
  268. ret = rtStreamSynchronize(rt_model_stream_);
  269. if (ret != RT_ERROR_NONE) {
  270. if (ret == ACL_ERROR_RT_END_OF_SEQUENCE) {
  271. GELOGI("Model stream ACL_ERROR_RT_END_OF_SEQUENCE signal received, ret = 0x%X", ret);
  272. return true;
  273. }
  274. GELOGE(RT_FAILED, "Model stream sync failed, ret = 0x%X", ret);
  275. return false;
  276. }
  277. GELOGI("Davinci task run succ.");
  278. return true;
  279. }
  280. void RuntimeModel::RtModelUnbindStream() noexcept {
  281. for (size_t i = 0; i < stream_list_.size(); i++) {
  282. if (rtModelUnbindStream(rt_model_handle_, stream_list_[i]) != RT_ERROR_NONE) {
  283. GELOGE(RT_FAILED, "Unbind stream from model failed! Index: %zu", i);
  284. return;
  285. }
  286. }
  287. }
  288. void RuntimeModel::RtStreamDestory() noexcept {
  289. if (rtStreamDestroy(rt_model_stream_) != RT_ERROR_NONE) {
  290. GELOGE(RT_FAILED, "Destroy stream for rt_model failed!");
  291. return;
  292. }
  293. for (size_t i = 0; i < stream_list_.size(); i++) {
  294. if (rtStreamDestroy(stream_list_[i]) != RT_ERROR_NONE) {
  295. GELOGE(RT_FAILED, "Destroy stream failed! Index: %zu", i);
  296. return;
  297. }
  298. }
  299. }
  300. void RuntimeModel::RtLabelDestory() noexcept {
  301. for (size_t i = 0; i < label_list_.size(); i++) {
  302. if (label_list_[i] == nullptr) {
  303. continue;
  304. }
  305. if (rtLabelDestroy(label_list_[i]) != RT_ERROR_NONE) {
  306. GELOGE(RT_FAILED, "Destroy label failed! Index: %zu.", i);
  307. return;
  308. }
  309. }
  310. }
  311. void RuntimeModel::RtModelDestory() noexcept {
  312. rtError_t ret = rtModelDestroy(rt_model_handle_);
  313. if (ret != RT_ERROR_NONE) {
  314. GELOGE(RT_FAILED, "Call rt api failed, ret: 0x%X", ret);
  315. return;
  316. }
  317. }
  318. void RuntimeModel::RtEventDestory() noexcept {
  319. for (size_t i = 0; i < event_list_.size(); i++) {
  320. if (rtEventDestroy(event_list_[i]) != RT_ERROR_NONE) {
  321. GELOGE(RT_FAILED, "Destroy event failed! Index: %zu", i);
  322. return;
  323. }
  324. }
  325. }
  326. bool RuntimeModel::InitDataInfo(std::shared_ptr<DavinciModel> &davinci_model) { return true; }
  327. bool RuntimeModel::InitOutputInfo(std::shared_ptr<DavinciModel> &davinci_model) {
  328. if (davinci_model == nullptr) {
  329. GELOGE(PARAM_INVALID, "davinci model is null");
  330. return false;
  331. }
  332. output_info_list_ = davinci_model->GetOutputInfoList();
  333. return true;
  334. }
  335. bool RuntimeModel::CopyInputData(const InputData &input_data) {
  336. if (input_data.blobs.size() != data_info_list_.size()) {
  337. GELOGE(PARAM_INVALID, "The input data list size (%zu) does not match the model input list size (%zu)",
  338. input_data.blobs.size(), data_info_list_.size());
  339. return false;
  340. }
  341. for (const auto &data_info : data_info_list_) {
  342. if (data_info == nullptr) {
  343. GELOGE(PARAM_INVALID, "data info is null.");
  344. return false;
  345. }
  346. bool ret = CopyInputDataToModel(input_data.blobs, data_info);
  347. if (!ret) {
  348. GELOGE(FAILED, "Copy input data to model ret fail, data_info: %s, model id: %u", data_info->name.c_str(),
  349. input_data.model_id);
  350. return false;
  351. }
  352. }
  353. return true;
  354. }
  355. bool RuntimeModel::CopyInputDataToModel(const std::vector<DataBuffer> &data, const std::shared_ptr<OpInfo> &data_info) {
  356. return true;
  357. }
  358. bool RuntimeModel::CopyHostData(const std::vector<DataBuffer> &data, const std::shared_ptr<OpInfo> &data_info) const {
  359. GELOGI("Start CopyHostData.");
  360. if (data.empty()) {
  361. GELOGE(PARAM_INVALID, "data buffer is empty.");
  362. return false;
  363. }
  364. if (data_info == nullptr) {
  365. GELOGE(PARAM_INVALID, "data info is null.");
  366. return false;
  367. }
  368. void *host_data_addr = data[data_info->index].data;
  369. uint32_t copy_size = data[data_info->index].length;
  370. GELOGD("data output tensor is aipp tensor,copy data only.");
  371. const std::vector<uintptr_t> &outputs = data_info->output_addrs;
  372. if (outputs.empty()) {
  373. GELOGE(PARAM_INVALID, "Output addrs is empty.");
  374. return false;
  375. }
  376. // Copy input data to data nodes
  377. void *data_out_addr = reinterpret_cast<void *>(outputs[0]);
  378. rtError_t rt_ret = rtMemcpy(data_out_addr, copy_size, host_data_addr, copy_size, RT_MEMCPY_HOST_TO_DEVICE);
  379. if (rt_ret != RT_ERROR_NONE) {
  380. GELOGE(RT_FAILED, "Call rt api failed, ret: 0x%X", rt_ret);
  381. return false;
  382. }
  383. return true;
  384. }
  385. bool RuntimeModel::CopyTransData(const std::vector<DataBuffer> &data, const std::shared_ptr<OpInfo> &data_info) {
  386. return true;
  387. }
  388. bool RuntimeModel::InitConstantInfo(std::shared_ptr<DavinciModel> &davinci_model) {
  389. // Const no input, only 1 output, and this output has no data
  390. // weight data copy to output mem
  391. if (davinci_model == nullptr) {
  392. GELOGE(PARAM_INVALID, "Davinci model is null.");
  393. return false;
  394. }
  395. constant_info_list_ = davinci_model->GetConstantInfoList();
  396. for (const auto &constant : constant_info_list_) {
  397. if (constant == nullptr) {
  398. GELOGE(PARAM_INVALID, "constant is null");
  399. continue;
  400. }
  401. if (constant->output_tensors.empty()) {
  402. GELOGE(PARAM_INVALID, "Output tensors is empty");
  403. return false;
  404. }
  405. if (constant->weight_tensors.empty()) {
  406. GELOGE(PARAM_INVALID, "Weight tensors is empty");
  407. return false;
  408. }
  409. if (constant->output_tensors[0].size < constant->weight_data.size()) {
  410. GELOGE(PARAM_INVALID, "Output size:%u is less than weight data size:%zu", constant->output_tensors[0].size,
  411. constant->weight_data.size());
  412. return false;
  413. }
  414. if (constant->weight_data.empty()) {
  415. GELOGW("Const op:%s has no weight data.", constant->name.c_str());
  416. continue;
  417. }
  418. if (constant->weight_tensors[0].datatype == DT_STRING) {
  419. /// If tensor is a scaler, it's shape size if zero, according ge_tensor.cc.
  420. /// The logic of GetShapeSize is wrong, the scaler tensor's GetShapeSize is zero
  421. /// and that of unknown shape is zero too.
  422. /// Unknown shape will not appear here, so we can use zero judge a tensor is scaler or not.
  423. int64_t elem_num =
  424. (constant->weight_tensors[0].GetShapeSize() == 0) ? 1 : constant->weight_tensors[0].GetShapeSize();
  425. if (constant->weight_data.size() < sizeof(uint64_t)) {
  426. GELOGE(FAILED, "weight_data size is smaller than sizeof(uint64_t)");
  427. return false;
  428. }
  429. uint64_t *buff = reinterpret_cast<uint64_t *>(const_cast<char *>(constant->weight_data.data()));
  430. uint32_t head_len = kOffsetUnit * kStringHeadElems;
  431. if (ge::CheckInt64Uint32MulOverflow(elem_num, head_len) != SUCCESS) {
  432. GELOGE(FAILED, "Shape size is invalid");
  433. return false;
  434. }
  435. int64_t offset = elem_num * head_len;
  436. uintptr_t hbm_raw_data_base_addr = reinterpret_cast<uintptr_t>(constant->output_addrs[0]) + offset;
  437. for (int64_t i = elem_num - 1; i >= 0; --i) {
  438. buff[i * kStringHeadElems] = hbm_raw_data_base_addr + (buff[i * kStringHeadElems] - buff[0]);
  439. }
  440. }
  441. rtError_t rt_ret = rtMemcpy(reinterpret_cast<void *>(constant->output_addrs[0]), constant->output_tensors[0].size,
  442. constant->weight_data.data(), constant->weight_data.size(), RT_MEMCPY_HOST_TO_DEVICE);
  443. if (rt_ret != RT_ERROR_NONE) {
  444. GELOGE(RT_FAILED, "rtGetFunctionByName failed, ret: 0x%X", rt_ret);
  445. return false;
  446. }
  447. }
  448. return true;
  449. }
  450. bool RuntimeModel::GetInputOutputDescInfo(bool zero_copy, std::vector<InputOutputDescInfo> *input_desc,
  451. std::vector<InputOutputDescInfo> *output_desc,
  452. std::vector<uint32_t> *input_format, std::vector<uint32_t> *output_format) {
  453. return true;
  454. }
  455. bool RuntimeModel::GetInputDescInfo(std::vector<InputOutputDescInfo> *input_desc, std::vector<uint32_t> *formats) {
  456. return true;
  457. }
  458. bool RuntimeModel::GetOutputDescInfo(std::vector<InputOutputDescInfo> *output_desc, std::vector<uint32_t> *formats) {
  459. return true;
  460. }
  461. void RuntimeModel::CreateOutput(uint32_t index, const OpInfo &op_info, InputOutputDescInfo *output,
  462. uint32_t *format_result) {}
  463. const std::vector<uint32_t> &RuntimeModel::GetTaskIdList() const { return task_id_list_; }
  464. const std::vector<uint32_t> &RuntimeModel::GetStreamIdList() const { return stream_id_list_; }
  465. } // namespace model_runner
  466. } // namespace ge

图引擎模块(GE)是MindSpore的一个子模块,其代码由C++实现,位于前端模块ME和底层硬件之间,起到承接作用。图引擎模块以ME下发的图作为输入,然后进行一系列的深度图优化操作,最后输出一张可以在底层硬件上高效运行的图。GE针对昇腾AI处理器的硬件结构特点,做了特定的优化工作,以此来充分发挥出昇腾AI处理器的强大算力。在进行模型训练/推理时,GE会被自动调用而用户并不感知。GE主要由GE API和GE Core两部分组成,详细的架构图如下所示