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model_executor.cc 24 kB

4 years ago
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  1. /**
  2. * Copyright 2021 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 "graph/execute/model_executor.h"
  17. #include "graph/ge_context.h"
  18. #include "graph/debug/ge_attr_define.h"
  19. #include "common/ge_call_wrapper.h"
  20. #include "common/local_context.h"
  21. #include "graph/manager/graph_var_manager.h"
  22. #include "graph/manager/graph_mem_manager.h"
  23. #include "graph/manager/host_mem_manager.h"
  24. #include "graph/utils/tensor_adapter.h"
  25. #include "graph/load/graph_loader.h"
  26. #include "graph/load/model_manager/model_manager.h"
  27. #include "common/math/math_util.h"
  28. #include "common/formats/utils/formats_trans_utils.h"
  29. namespace {
  30. constexpr int32_t kBase = 10;
  31. constexpr uint8_t kNeverLoaded = 0;
  32. }
  33. namespace ge {
  34. ///
  35. /// @ingroup ge
  36. /// @brief graph executor init
  37. /// @param [in] options user config params
  38. /// @return Status result of function
  39. ///
  40. Status ModelExecutor::Initialize(const map<string, string> &options, uint64_t session_id) {
  41. graph_run_listener_ = MakeShared<GraphModelListener>(sync_run_mutex_, condition_);
  42. if (graph_run_listener_ == nullptr) {
  43. REPORT_CALL_ERROR("E19999", "New GraphModelListener fail");
  44. GELOGE(MEMALLOC_FAILED, "[New][GraphModelListener] failed");
  45. return MEMALLOC_FAILED;
  46. }
  47. const auto model_manager = ModelManager::GetInstance();
  48. GE_CHECK_NOTNULL(model_manager);
  49. Status status = model_manager->EnableExceptionDump(options);
  50. if (status != SUCCESS) {
  51. return status;
  52. }
  53. GE_CHK_STATUS_RET(HostMemManager::Instance().Initialize());
  54. const std::vector<rtMemType_t> mem_type({RT_MEMORY_HBM, RT_MEMORY_P2P_DDR});
  55. status = MemManager::Instance().Initialize(mem_type);
  56. if (status != SUCCESS) {
  57. GELOGE(status, "[Init][MemManager] MemoryAllocatorManager initialize failed.");
  58. REPORT_CALL_ERROR("E19999", "MemManager initialize failed.");
  59. return status;
  60. }
  61. VarManager::Instance(session_id)->SetMemManager(&MemManager::Instance());
  62. size_t total_mem_size = 0;
  63. GE_CHK_STATUS_RET_NOLOG(GetTotalMemorySize(total_mem_size));
  64. status = VarManager::Instance(session_id)->SetMemoryMallocSize(options, total_mem_size);
  65. if (status != SUCCESS) {
  66. GELOGE(status, "[Set][MemoryMallocSize] failed.");
  67. REPORT_CALL_ERROR("E19999", "VarManager SetMemoryMallocSize failed, InnerSession:%lu.", session_id_);
  68. return status;
  69. }
  70. session_id_ = session_id;
  71. train_graph_flag_ = ParseTrainGraphFlag();
  72. thread_run_flag_.store(true);
  73. run_thread_ = std::thread(&ModelExecutor::RunThread, this);
  74. init_flag_ = true;
  75. return SUCCESS;
  76. }
  77. ///
  78. /// @ingroup ge
  79. /// @brief graph executor finalize
  80. /// @return Status result of function
  81. ///
  82. Status ModelExecutor::Finalize() {
  83. if (!init_flag_) {
  84. GELOGW("ModelExecutor has not been initialized.");
  85. return SUCCESS;
  86. }
  87. StopQueue();
  88. if (run_thread_.joinable()) {
  89. run_thread_.join();
  90. }
  91. if (graph_executor_.FreeExecuteMemory() != SUCCESS) {
  92. GELOGW("Graph executor FreeExecuteMemory failed, resources may not be released correctly.");
  93. }
  94. GELOGI("VarManager free var memory.");
  95. (void)VarManager::Instance(session_id_)->FreeVarMemory();
  96. MemManager::Instance().FreeSessionMemory(session_id_);
  97. HostMemManager::Instance().Finalize();
  98. ModelManager::GetInstance()->DestroyAicpuSession(session_id_);
  99. return SUCCESS;
  100. }
  101. Status ModelExecutor::GetTotalMemorySize(size_t &total_mem_size) {
  102. rtError_t rt_ret = rtSetDevice(GetContext().DeviceId());
  103. if (rt_ret != RT_ERROR_NONE) {
  104. REPORT_CALL_ERROR("E19999", "Call rtSetDevice failed, device_id:%u, ret:0x%X",
  105. GetContext().DeviceId(), rt_ret);
  106. GELOGE(RT_FAILED, "[Call][RtSetDevice] failed, device_id:%u, ret:0x%X", GetContext().DeviceId(), rt_ret);
  107. return RT_FAILED;
  108. }
  109. size_t free_mem = 0;
  110. rt_ret = rtMemGetInfoEx(RT_MEMORYINFO_HBM, &free_mem, &total_mem_size);
  111. if (rt_ret != RT_ERROR_NONE) {
  112. REPORT_CALL_ERROR("E19999", "Call rtMemGetInfo failed, ret:0x%X", rt_ret);
  113. GELOGE(RT_FAILED, "[Call][RtMemGetInfo] failed, ret:0x%X", rt_ret);
  114. return RT_FAILED;
  115. }
  116. rt_ret = rtDeviceReset(GetContext().DeviceId());
  117. if (rt_ret != RT_ERROR_NONE) {
  118. REPORT_CALL_ERROR("E19999", "Call rtDeviceReset failed, device_id:%u, ret:0x%X",
  119. GetContext().DeviceId(), rt_ret);
  120. GELOGE(RT_FAILED, "[Call][RtDeviceReset] failed, device_id:%u, ret:0x%X", GetContext().DeviceId(), rt_ret);
  121. return RT_FAILED;
  122. }
  123. return SUCCESS;
  124. }
  125. // OPTION_GRAPH_RUN_MODE is supposed to be a session-level option, but it used to be set to global-level in the past.
  126. // If can not parse from session, it can parse from global by GetContext().
  127. bool ModelExecutor::ParseTrainGraphFlag() {
  128. string run_mode;
  129. if (GetContext().GetOption(OPTION_GRAPH_RUN_MODE, run_mode) == SUCCESS && !run_mode.empty()) {
  130. if (GraphRunMode(std::strtol(run_mode.c_str(), nullptr, kBase)) >= TRAIN) {
  131. GELOGI("Graph train flag set.");
  132. return true;
  133. }
  134. }
  135. return false;
  136. }
  137. void ModelExecutor::AddGraphNode(GraphId graph_id, const GraphNodePtr &graph_node) {
  138. std::lock_guard<std::mutex> lock(mutex_);
  139. graph_nodes_.emplace(graph_id, graph_node);
  140. }
  141. void ModelExecutor::RemoveGraphNode(GraphId graph_id) {
  142. std::lock_guard<std::mutex> lock(mutex_);
  143. graph_nodes_.erase(graph_id);
  144. }
  145. ///
  146. /// @ingroup ge
  147. /// @brief Load mode for graph.
  148. /// @param [in] GeRootModel: root model of graph compiled.
  149. /// @param [in] GraphNode: node of graph.
  150. /// @return Status result of function
  151. ///
  152. Status ModelExecutor::LoadGraph(const GeRootModelPtr &ge_root_model, const GraphNodePtr &graph_node) {
  153. GE_CHECK_NOTNULL(graph_node);
  154. if (ge_root_model == nullptr) {
  155. return SUCCESS;
  156. }
  157. UpdateLocalOmeContext(graph_node);
  158. return graph_node->IsAsync() ? ModelLoadAsync(ge_root_model, graph_node) : ModelLoadSync(ge_root_model, graph_node);
  159. }
  160. ///
  161. /// @ingroup ge
  162. /// @brief Unload mode for graph.
  163. /// @param [in] GeRootModel: root model of graph compiled.
  164. /// @param [in] graph_id: graph identifier.
  165. /// @return Status result of function
  166. ///
  167. Status ModelExecutor::UnloadGraph(const GeRootModelPtr &ge_root_model, uint32_t graph_id) {
  168. GE_CHECK_NOTNULL(ge_root_model);
  169. rtError_t rt_ret = rtSetDevice(GetContext().DeviceId());
  170. if (rt_ret != RT_ERROR_NONE) {
  171. GELOGW("[GraphExecutor] rtSetDevice failed, modelId=%u, graphId=%u.", ge_root_model->GetModelId(), graph_id);
  172. return FAILED;
  173. }
  174. RemoveGraphNode(graph_id);
  175. Status ret = UnloadModel(ge_root_model, graph_id);
  176. if (ret != SUCCESS) {
  177. GELOGW("[GraphExecutor] unload model failed, graph_id=%u.", graph_id);
  178. }
  179. rt_ret = rtDeviceReset(GetContext().DeviceId());
  180. if (rt_ret != RT_ERROR_NONE) {
  181. GELOGW("[GraphExecutor] rtDeviceReset failed, graphId=%u.", graph_id);
  182. }
  183. return ret;
  184. }
  185. Status ModelExecutor::UnloadModel(const GeRootModelPtr &ge_root_model, uint32_t graph_id) {
  186. GE_CHECK_NOTNULL(ge_root_model);
  187. for (size_t i = 0; i < ge_root_model->GetAllModelId().size(); ++i) {
  188. uint32_t model_id = ge_root_model->GetAllModelId()[i];
  189. GELOGI("Unload model %u.", model_id);
  190. Status ret = GraphLoader::UnloadModel(model_id);
  191. if (ret != SUCCESS) {
  192. GELOGE(ret, "[GraphExecutor] unload model failed, modelId=%u, graphId=%u.", model_id, graph_id);
  193. return ret;
  194. }
  195. }
  196. return SUCCESS;
  197. }
  198. void ModelExecutor::StopQueue() {
  199. thread_run_flag_.store(false);
  200. run_args_q_.Stop();
  201. }
  202. void ModelExecutor::ReturnError(RunAsyncCallback callback, Status ret, const string &log) {
  203. StopQueue();
  204. GELOGE(ret, "%s.", log.c_str());
  205. std::vector<ge::Tensor> outputs;
  206. if (callback != nullptr) {
  207. callback(ret, outputs);
  208. }
  209. }
  210. void ModelExecutor::UpdateLocalOmeContext(const GraphNodePtr &graph_node) {
  211. std::lock_guard<std::mutex> lock(mutex_);
  212. SetLocalOmeContext(graph_node->GetOmeContext());
  213. }
  214. ///
  215. /// @ingroup ge
  216. /// @brief Push model execution params to queue.
  217. /// @param [in] RunArgs of for model execution.
  218. /// @return Status result of function
  219. ///
  220. Status ModelExecutor::PushGraph(const RunArgs &args) {
  221. return run_args_q_.Push(args) ? SUCCESS : FAILED;
  222. }
  223. void ModelExecutor::RunThread() {
  224. ErrorManager::GetInstance().SetStage(error_message::kModelExecute, error_message::kModelExecute);
  225. if (mmSetCurrentThreadName("GE_Run") != EN_OK) {
  226. GELOGW("Set thread name failed.");
  227. }
  228. RunArgs args;
  229. while (thread_run_flag_) {
  230. if (!run_args_q_.Pop(args)) {
  231. continue;
  232. }
  233. GELOGI("[RunThread] A new loop start, graph_id:%u.", args.graph_id);
  234. ErrorManager::GetInstance().SetErrorContext(args.error_context);
  235. GetContext().SetSessionId(args.session_id);
  236. GetThreadLocalContext() = args.context;
  237. UpdateLocalOmeContext(args.graph_node);
  238. // parse inputs.dims to vector<vector<uint64_t>> dynamic_dims
  239. Status ret = ParseInputsDims(args.input_tensor);
  240. if (ret != SUCCESS) {
  241. ReturnError(args.callback, ret, "ParseInputsDims failed, thread exit.");
  242. args.graph_node->Unlock();
  243. return;
  244. }
  245. args.graph_node->UpdateLoadFlag();
  246. if (!args.graph_node->GetLoadFlag()) {
  247. ErrorManager::GetInstance().SetStage(error_message::kModelLoad, error_message::kModelLoad);
  248. args.ge_root_model->SetTrainFlag(train_graph_flag_);
  249. ret = ModelLoadAsync(args.ge_root_model, args.graph_node);
  250. if (ret != SUCCESS || args.ge_root_model == nullptr) {
  251. StopQueue();
  252. ReturnError(args.callback, ret, "LoadGraphAsync failed, thread exit.");
  253. args.graph_node->Unlock();
  254. return;
  255. }
  256. // control the times of graph loading in multi-thread scenario
  257. args.graph_node->DecreaseLoadCount();
  258. args.graph_node->IncreaseLoadRecord();
  259. args.graph_node->SetLoadFlag(true);
  260. GELOGI("LoadGraph[%u], model[%u] success and set LoadFlag to true.", args.graph_node->GetGraphId(),
  261. args.ge_root_model->GetModelId());
  262. }
  263. ErrorManager::GetInstance().SetStage(error_message::kModelExecute, error_message::kModelExecute);
  264. if (train_graph_flag_) {
  265. graph_executor_.SetTrainFlag(train_graph_flag_);
  266. }
  267. ret = graph_executor_.ExecuteGraphAsync(args.graph_id, args.graph_node->GetGeRootModel(),
  268. args.input_tensor, args.callback);
  269. args.graph_node->SetRunFlag(false);
  270. if (ret != SUCCESS) {
  271. ReturnError(args.callback, ret, "ExecuteGraphAsync failed, thread exit.");
  272. args.graph_node->Unlock();
  273. return;
  274. }
  275. args.graph_node->Unlock();
  276. GELOGI("[GraphExecutor] Run graph async success, graph_id=%u.", args.graph_id);
  277. }
  278. }
  279. ///
  280. /// @ingroup ge
  281. /// @brief Run graph for synchronize model.
  282. /// @param [in] graph_node: node of graph.
  283. /// @param [in] graph_id: graph identifier.
  284. /// @param [in] inputs: input data for the graph running.
  285. /// @param [out] outputs: output data of the graph running
  286. /// @return Status result of function
  287. ///
  288. Status ModelExecutor::RunGraph(const GraphNodePtr &graph_node, GraphId graph_id,
  289. const std::vector<GeTensor> &inputs, std::vector<GeTensor> &outputs) {
  290. Status ret = graph_executor_.SetCondition(&sync_run_mutex_, &condition_, graph_run_listener_);
  291. if (ret != SUCCESS) {
  292. GELOGE(GE_GRAPH_RUNGRAPH_FAILED, "[Set][Condition] failed, graph_id = %u.", graph_id);
  293. graph_node->SetRunFlag(false);
  294. return GE_GRAPH_RUNGRAPH_FAILED;
  295. }
  296. if (train_graph_flag_) {
  297. graph_executor_.SetTrainFlag(train_graph_flag_);
  298. }
  299. ret = graph_executor_.ExecuteGraph(graph_id, graph_node->GetGeRootModel(), inputs, outputs);
  300. graph_node->SetRunFlag(false);
  301. if (ret != SUCCESS) {
  302. GELOGE(ret, "[Execute][Graph] failed, graph_id = %u.", graph_id);
  303. return ret;
  304. }
  305. return SUCCESS;
  306. }
  307. ///
  308. /// @ingroup ge
  309. /// @brief Run graph for NN synchronize model.
  310. /// @param [in] graph_node: node of graph.
  311. /// @param [in] graph_id: graph identifier.
  312. /// @param [in] stream: Stream for model running.
  313. /// @param [in] inputs: input data for the graph running.
  314. /// @param [out] outputs: output data of the graph running
  315. /// @return Status result of function
  316. ///
  317. Status ModelExecutor::RunGraphWithStream(const GraphNodePtr &graph_node, GraphId graph_id, rtStream_t stream,
  318. const std::vector<GeTensor> &inputs, std::vector<GeTensor> &outputs) {
  319. auto ret = graph_executor_.SetCondition(&sync_run_mutex_, &condition_, graph_run_listener_);
  320. if (ret != SUCCESS) {
  321. GELOGE(GE_GRAPH_RUNGRAPH_FAILED, "[Set][Condition] failed, graph id = %u, stream = %p.", graph_id, stream);
  322. graph_node->SetRunFlag(false);
  323. return GE_GRAPH_RUNGRAPH_FAILED;
  324. }
  325. ret = graph_executor_.ExecuteGraphWithStream(graph_id, stream, graph_node->GetGeRootModel(), inputs, outputs);
  326. graph_node->SetRunFlag(false);
  327. graph_node->SetIsSpecificStream(false);
  328. if (ret != SUCCESS) {
  329. GELOGE(ret, "[Execute][Graph] With Stream failed, graph id = %u, stream = %p.", graph_id, stream);
  330. return ret;
  331. }
  332. GELOGI("[Run][GraphWithStreamAsync] run graph success, graph id = %u, stream = %p.", graph_id, stream);
  333. return SUCCESS;
  334. }
  335. Status ModelExecutor::ModelLoadSync(const GeRootModelPtr &ge_root_model, const GraphNodePtr &graph_node) {
  336. ge_root_model->SetIsSpecificStream(graph_node->IsSpecificStream());
  337. return ModelLoad(ge_root_model, graph_node, graph_run_listener_);
  338. }
  339. Status ModelExecutor::ModelLoadAsync(const GeRootModelPtr &ge_root_model, const GraphNodePtr &graph_node) {
  340. auto listener = MakeShared<RunAsyncListener>();
  341. GE_CHECK_NOTNULL(listener);
  342. return ModelLoad(ge_root_model, graph_node, listener);
  343. }
  344. Status ModelExecutor::ModelLoad(const GeRootModelPtr &ge_root_model, const GraphNodePtr &graph_node,
  345. const std::shared_ptr<ModelListener> &listener) {
  346. ge_root_model->SetTrainFlag(train_graph_flag_);
  347. bool is_unknown_shape = false;
  348. GE_CHK_STATUS_RET(ge_root_model->CheckIsUnknownShape(is_unknown_shape));
  349. if (!is_unknown_shape) {
  350. if (getenv(kEnvGeuseStaticMemory) != nullptr) {
  351. GELOGI("[LoadGraph] GE_USE_STATIC_MEMORY is seted.");
  352. } else {
  353. auto root_graph = ge_root_model->GetRootGraph();
  354. GE_CHECK_NOTNULL(root_graph);
  355. auto name_to_model = ge_root_model->GetSubgraphInstanceNameToModel();
  356. GeModelPtr ge_model = name_to_model[root_graph->GetName()];
  357. GE_CHK_STATUS_RET(CheckAndReleaseMemory(ge_model, graph_node));
  358. }
  359. }
  360. GE_TIMESTAMP_START(LoadModelOnline);
  361. uint32_t model_id = INVALID_MODEL_ID;
  362. Status ret = GraphLoader::LoadModelOnline(model_id, ge_root_model, listener);
  363. GE_TIMESTAMP_EVENT_END(LoadModelOnline, "GraphLoader::LoadModelOnline");
  364. if (ret != SUCCESS) {
  365. GELOGE(ret, "[Load][ModelOnline] Failed, model_id:%u", model_id);
  366. graph_node->SetRunFlag(false);
  367. return ret;
  368. }
  369. graph_node->SetLoadFlag(true);
  370. ge_root_model->SetModelId(model_id);
  371. graph_node->SetGeRootModel(ge_root_model);
  372. AddGraphNode(graph_node->GetGraphId(), graph_node);
  373. return SUCCESS;
  374. }
  375. void ModelExecutor::ReleaseMemory(const GeModelPtr &ge_model, const GraphNodePtr &graph_node,
  376. const std::vector<uint32_t> &model_ids, uint32_t graph_id, uint64_t session_id) {
  377. rtError_t rt_ret = rtSetDevice(GetContext().DeviceId());
  378. if (rt_ret != RT_ERROR_NONE) {
  379. REPORT_CALL_ERROR("E19999", "Call rtSetDevice failed, device_id:%u", GetContext().DeviceId());
  380. GELOGE(RT_FAILED, "[Call][RtSetDevice] failed, device_id=%u.", GetContext().DeviceId());
  381. return;
  382. }
  383. for (auto model_id : model_ids) {
  384. uint64_t max_memory_size = 0;
  385. Status result = GraphLoader::GetMaxUsedMemory(model_id, max_memory_size);
  386. if (result != SUCCESS) {
  387. continue;
  388. }
  389. GELOGI("try to UnloadGraph[%u], model[%u] which MaxUsedMemory[%lu].", graph_id, model_id, max_memory_size);
  390. if (model_ids.size() > 1) {
  391. result = ge_model->GetSessionId(model_id, session_id);
  392. if (result != SUCCESS) {
  393. GELOGW("[GraphExecutor:] get session failed when dynamic memory, modelId=%u, graphId=%u.", model_id,
  394. graph_id);
  395. continue;
  396. }
  397. }
  398. result = GraphLoader::DestroyAicpuKernel(session_id, model_id, 0);
  399. if (result != SUCCESS) {
  400. GELOGW("[GraphExecutor:] destroy aicpu kernel failed when dynamic memory, modelId=%u, graphId=%u.", model_id,
  401. graph_id);
  402. }
  403. result = GraphLoader::UnloadModel(model_id);
  404. if (result != SUCCESS) {
  405. GELOGW("[GraphExecutor:] unload model failed, modelId=%u, graphId=%u.", model_id, graph_id);
  406. }
  407. GELOGI("UnloadGraph[%u], model[%u] success.", graph_id, model_id);
  408. }
  409. graph_node->SetLoadFlag(false);
  410. // Allow model to be loaded agagin without adding graph again
  411. graph_node->SetLoadCount(graph_node->GetLoadRecord());
  412. graph_node->SetLoadRecord(kNeverLoaded);
  413. GeRootModelPtr ge_root_model = graph_node->GetGeRootModel();
  414. if (ge_root_model == nullptr) {
  415. GELOGW("ge_root_model is null, graph_id:%u", graph_id);
  416. return;
  417. }
  418. ge_root_model->ClearAllModelId();
  419. rt_ret = rtDeviceReset(GetContext().DeviceId());
  420. if (rt_ret != RT_ERROR_NONE) {
  421. REPORT_CALL_ERROR("E19999", "Call rtDeviceReset failed, device_id:%u", GetContext().DeviceId());
  422. GELOGE(RT_FAILED, "[Call][RtDeviceReset] failed, device_id:%u.", GetContext().DeviceId());
  423. return;
  424. }
  425. }
  426. Status ModelExecutor::CheckAndReleaseMemory(const GeModelPtr &ge_model, const GraphNodePtr &graph_node) {
  427. GELOGI("graph_id[%u]", graph_node->GetGraphId());
  428. int64_t free_memory = 0;
  429. Status result = GraphLoader::GetMemoryInfo(free_memory);
  430. if (result != SUCCESS) {
  431. return result;
  432. }
  433. int64_t value = 0;
  434. int64_t memory_size = AttrUtils::GetInt(ge_model, ATTR_MODEL_MEMORY_SIZE, value) ? value : 0;
  435. int64_t weight_size = AttrUtils::GetInt(ge_model, ATTR_MODEL_WEIGHT_SIZE, value) ? value : 0;
  436. int64_t session_id = AttrUtils::GetInt(ge_model, MODEL_ATTR_SESSION_ID, value) ? value : 0;
  437. GELOGI("Graph[%u] need memory_size[%ld], weight_size[%ld], Device[%u] free_memory_size[%ld]",
  438. graph_node->GetGraphId(), memory_size, weight_size, GetContext().DeviceId(), free_memory);
  439. if (CheckInt64AddOverflow(memory_size, weight_size) != SUCCESS) {
  440. REPORT_INNER_ERROR("E19999", "memory_size:%ld and weight_size:%ld will overflow after add, check invalid",
  441. memory_size, weight_size);
  442. GELOGE(INTERNAL_ERROR, "[Check][Param] memory_size:%ld and weight_size:%ld will overflow after add",
  443. memory_size, weight_size);
  444. return INTERNAL_ERROR;
  445. }
  446. if (free_memory >= (memory_size + weight_size)) {
  447. return SUCCESS;
  448. }
  449. std::lock_guard<std::mutex> lock(mutex_);
  450. for (const auto &it : graph_nodes_) {
  451. auto graph_id = it.second->GetGraphId();
  452. auto model = it.second->GetGeRootModel();
  453. if (model == nullptr) {
  454. continue;
  455. }
  456. auto model_id = model->GetModelId();
  457. auto model_ids = model->GetAllModelId();
  458. // unload model not release
  459. bool is_unknown_shape = false;
  460. GE_CHK_STATUS_RET(model->CheckIsUnknownShape(is_unknown_shape));
  461. if (is_unknown_shape) {
  462. GELOGD("model_id[%u] graph_id[%u] is unknown model, not release memory", model_id, graph_id);
  463. continue;
  464. }
  465. // not loaded,no need unload
  466. if (!it.second->GetLoadFlag()) {
  467. GELOGI("CheckAndReleaseMemory graph[%u] has not been loaded.", graph_id);
  468. continue;
  469. }
  470. ReleaseMemory(ge_model, it.second, model_ids, graph_id, static_cast<uint64_t>(session_id));
  471. }
  472. return SUCCESS;
  473. }
  474. void ModelExecutor::ParseInputsDimsForData(const std::vector<ge::Tensor> &input_tensor) {
  475. GELOGD("Start parse input dims from data.");
  476. for (size_t i = 0; i < input_tensor.size(); ++i) {
  477. const TensorDesc &tensor_desc = input_tensor[i].GetTensorDesc();
  478. const Shape &shape = tensor_desc.GetShape();
  479. const auto &shape_dims = shape.GetDims();
  480. GELOGD("Input tensor dims is %s.", formats::JoinToString(shape_dims).c_str());
  481. GetLocalOmeContext().user_real_input_dims.emplace_back(shape_dims);
  482. }
  483. }
  484. Status ModelExecutor::ParseInputsDimsForGetNextNoSinkAndData(const vector<NodePtr> &dynamic_nodes,
  485. const std::vector<ge::Tensor> &input_tensor) {
  486. GELOGD("Start parse inputs dims when coexist data and getnext sink.");
  487. for (size_t i = 0; i < dynamic_nodes.size(); ++i) {
  488. auto op_desc = dynamic_nodes.at(i)->GetOpDesc();
  489. if (op_desc == nullptr) {
  490. continue;
  491. }
  492. GeAttrValue::INT index = 0;
  493. if (!(AttrUtils::GetInt(op_desc, ATTR_NAME_INDEX, index))) {
  494. REPORT_CALL_ERROR("E19999", "Get Attr:%s from op:%s(%s) fail", ATTR_NAME_INDEX.c_str(),
  495. op_desc->GetName().c_str(), op_desc->GetType().c_str());
  496. GELOGE(PARAM_INVALID, "[Get][Attr] %s from op:%s(%s) fail", ATTR_NAME_INDEX.c_str(),
  497. op_desc->GetName().c_str(), op_desc->GetType().c_str());
  498. return PARAM_INVALID;
  499. }
  500. if (static_cast<size_t>(index) > input_tensor.size()) {
  501. REPORT_INNER_ERROR("E19999", "Attr:%s in op:%s(%s) value:%ld > param input_tensor.size:%zu, "
  502. "check invalid", ATTR_NAME_INDEX.c_str(),
  503. op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  504. index, input_tensor.size());
  505. GELOGE(PARAM_INVALID, "[Check][Param] Attr:%s in op:%s(%s) value:%ld > param input_tensor.size:%zu",
  506. ATTR_NAME_INDEX.c_str(), op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  507. index, input_tensor.size());
  508. return PARAM_INVALID;
  509. }
  510. const TensorDesc &tensor_desc = input_tensor[i].GetTensorDesc();
  511. const Shape &shape = tensor_desc.GetShape();
  512. const auto &shape_dims = shape.GetDims();
  513. GELOGI("Shape dims of %zu data is %s.", index, formats::JoinToString(shape_dims).c_str());
  514. GetLocalOmeContext().user_real_input_dims.emplace_back(std::move(shape_dims));
  515. }
  516. return SUCCESS;
  517. }
  518. Status ModelExecutor::ParseInputsDims(const std::vector<ge::Tensor> &input_tensor) {
  519. GELOGI("Start parse input dims of %zu input tensor.", input_tensor.size());
  520. GetLocalOmeContext().user_real_input_dims.clear();
  521. if (GetLocalOmeContext().dynamic_node_type.empty()) {
  522. return SUCCESS;
  523. }
  524. const vector<NodePtr> &data_nodes = GetLocalOmeContext().data_nodes;
  525. const vector<NodePtr> &getnext_nosink_nodes = GetLocalOmeContext().getnext_nosink_nodes;
  526. GELOGD("Data nodes count is %zu, getnext nosink nodes count is %zu.", data_nodes.size(),
  527. getnext_nosink_nodes.size());
  528. if (GetLocalOmeContext().dynamic_node_type == DATA) {
  529. if (getnext_nosink_nodes.empty()) {
  530. // just data or data+getnext_sink
  531. ParseInputsDimsForData(input_tensor);
  532. } else {
  533. // data+getnext_nosink, but only need to get shape_dims of data
  534. if (ParseInputsDimsForGetNextNoSinkAndData(data_nodes, input_tensor) != SUCCESS) {
  535. GELOGE(PARAM_INVALID, "[Parse][Dims] from data failed, when data coexist with getnext nosink.");
  536. return PARAM_INVALID;
  537. }
  538. }
  539. } else {
  540. if (getnext_nosink_nodes.empty()) {
  541. // just getnext_sink or getnext_sink+data, need to get shape_dims from aicpu op
  542. GELOGI("Need to get dims from aicpu op: GETDYNAMICDIMS.");
  543. return SUCCESS;
  544. } else {
  545. if (data_nodes.empty()) {
  546. // just getnext_nosink
  547. ParseInputsDimsForData(input_tensor);
  548. } else {
  549. // getnext_nosink + data, but only need to get shape_dims of getnext_nosink
  550. if (ParseInputsDimsForGetNextNoSinkAndData(getnext_nosink_nodes, input_tensor) != SUCCESS) {
  551. GELOGE(PARAM_INVALID, "[Parse][Dims] from getnext nosink failed, when data coexist with getnext nosink");
  552. return PARAM_INVALID;
  553. }
  554. }
  555. }
  556. }
  557. GELOGI("Parse %zu inputs dims success.", GetLocalOmeContext().user_real_input_dims.size());
  558. return SUCCESS;
  559. }
  560. } // 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