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graph_execute.cc 28 kB

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  1. /**
  2. * Copyright 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 "graph/execute/graph_execute.h"
  17. #include <memory>
  18. #include <string>
  19. #include "graph/load/model_manager/model_manager.h"
  20. #include "graph/load/model_manager/davinci_model.h"
  21. #include "omm/csa_interact.h"
  22. namespace ge {
  23. using Uint32Pair = pair<uint32_t, uint32_t>;
  24. const uint32_t kInvalidModelId = UINT32_MAX;
  25. GraphExecutor::GraphExecutor()
  26. : init_flag_(false),
  27. train_graph_flag_(false),
  28. sync_run_mutex_(nullptr),
  29. condition_(nullptr),
  30. graph_run_listener_(nullptr),
  31. graph_context_(nullptr),
  32. last_graph_id_(UINT32_MAX),
  33. malloc_flag_(false) {}
  34. GraphExecutor::~GraphExecutor() {
  35. outputs_desc_.clear();
  36. if (malloc_flag_) {
  37. for (auto &buffer_addr : buffer_addr_) {
  38. rtError_t rt_ret;
  39. rt_ret = rtFreeHost(buffer_addr);
  40. if (rt_ret != RT_ERROR_NONE) {
  41. REPORT_CALL_ERROR("E19999", "Call rtFreeHost failed, ret:0x%X", rt_ret);
  42. GELOGE(RT_FAILED, "[GraphManager] subgraph free buffer failed, ret: 0x%X", rt_ret);
  43. }
  44. }
  45. }
  46. malloc_flag_ = false;
  47. buffer_addr_.clear();
  48. }
  49. Status GraphExecutor::SetCondition(std::mutex *mutex, std::condition_variable *cond,
  50. std::shared_ptr<GraphModelListener> listener) {
  51. if (mutex == nullptr) {
  52. REPORT_INNER_ERROR("E19999", "Check param mutex nullptr");
  53. GELOGE(GE_GRAPH_PARAM_NULLPTR, "[SetCondition] input param mutex is nullptr.");
  54. return GE_GRAPH_PARAM_NULLPTR;
  55. }
  56. if (cond == nullptr) {
  57. REPORT_INNER_ERROR("E19999", "Check param cond nullptr");
  58. GELOGE(GE_GRAPH_PARAM_NULLPTR, "[SetCondition] input param cond is nullptr.");
  59. return GE_GRAPH_PARAM_NULLPTR;
  60. }
  61. if (listener == nullptr) {
  62. REPORT_INNER_ERROR("E19999", "Check param listener nullptr");
  63. GELOGE(GE_GRAPH_PARAM_NULLPTR, "[SetCondition] input param listener is nullptr.");
  64. return GE_GRAPH_PARAM_NULLPTR;
  65. }
  66. sync_run_mutex_ = mutex;
  67. condition_ = cond;
  68. graph_run_listener_ = listener;
  69. init_flag_ = true;
  70. return SUCCESS;
  71. }
  72. Status GraphExecutor::SetGraphContext(GraphContextPtr graph_context_ptr) {
  73. if (graph_context_ptr == nullptr) {
  74. REPORT_INNER_ERROR("E19999", "Check param graph_context_ptr nullptr");
  75. GELOGE(GE_GRAPH_PARAM_NULLPTR, "[SetGraphContext] input param graph_context_ptr is nullptr");
  76. return GE_GRAPH_PARAM_NULLPTR;
  77. }
  78. graph_context_ = graph_context_ptr;
  79. return SUCCESS;
  80. }
  81. Status GraphExecutor::SetDynamicSize(uint32_t model_id, const std::vector<uint64_t> &batch_num, int32_t dynamic_type) {
  82. auto model_manager = ge::ModelManager::GetInstance();
  83. GE_CHECK_NOTNULL(model_manager);
  84. Status ret = model_manager->SetDynamicSize(model_id, batch_num, dynamic_type);
  85. if (ret != SUCCESS) {
  86. GELOGE(ret, "SetDynamicSize failed");
  87. return ret;
  88. }
  89. return SUCCESS;
  90. }
  91. void GraphExecutor::SetTrainFlag(bool is_train_graph) { train_graph_flag_ = is_train_graph; }
  92. Status GraphExecutor::FreeInOutBuffer() {
  93. if (malloc_flag_) {
  94. for (auto iter = buffer_addr_.begin(); iter != buffer_addr_.end(); ++iter) {
  95. rtError_t rt_ret;
  96. rt_ret = rtFreeHost(*iter);
  97. if (rt_ret != RT_ERROR_NONE) {
  98. REPORT_CALL_ERROR("E19999", "Call rtFreeHost failed, ret:0x%X", rt_ret);
  99. GELOGE(RT_FAILED, "[GraphManager] subgraph free buffer failed, ret: 0x%X", rt_ret);
  100. (void)buffer_addr_.erase(buffer_addr_.begin(), iter);
  101. return GE_GRAPH_FREE_FAILED;
  102. }
  103. }
  104. buffer_addr_.clear();
  105. malloc_flag_ = false;
  106. return SUCCESS;
  107. } else {
  108. GELOGD("[GraphManager] not malloc buffer.");
  109. return SUCCESS;
  110. }
  111. }
  112. Status GraphExecutor::MallocInOutBuffer(const std::vector<uint64_t> &buffer_size, std::vector<void *> &data_addr) {
  113. if (malloc_flag_) {
  114. auto all_size_same = true;
  115. if (buffer_size.size() == buffer_size_.size()) {
  116. for (size_t i = 0; i < buffer_size.size(); i++) {
  117. if (buffer_size[i] != buffer_size_[i]) {
  118. all_size_same = false;
  119. break;
  120. }
  121. }
  122. } else {
  123. all_size_same = false;
  124. }
  125. if (all_size_same) {
  126. data_addr = buffer_addr_;
  127. return SUCCESS;
  128. }
  129. buffer_size_.clear();
  130. auto rt_ret = FreeInOutBuffer();
  131. if (rt_ret != SUCCESS) {
  132. GELOGE(RT_FAILED, "[SubGraphInfo] MallocInOutBuffer free buffer failed, ret: 0x%X", rt_ret);
  133. return RT_FAILED;
  134. }
  135. }
  136. rtError_t rt_ret;
  137. for (size_t i = 0; i < buffer_size.size(); ++i) {
  138. void *tmp_buf = nullptr;
  139. rt_ret = rtMallocHost(&tmp_buf, buffer_size[i]);
  140. if (rt_ret != RT_ERROR_NONE) {
  141. REPORT_CALL_ERROR("E19999", "Call rtMallocHost failed, size:%lu, ret:0x%X",
  142. buffer_size[i], rt_ret);
  143. GELOGE(RT_FAILED, "[GraphManager] subgraph malloc buffer failed, ret: 0x%X", rt_ret);
  144. return GE_GRAPH_MALLOC_FAILED;
  145. }
  146. malloc_flag_ = true;
  147. data_addr.push_back(tmp_buf);
  148. buffer_addr_.push_back(tmp_buf);
  149. }
  150. buffer_size_ = buffer_size;
  151. return SUCCESS;
  152. }
  153. Status GraphExecutor::PrepareInputData(const std::vector<GeTensor> &input_tensor, InputData &graph_input_data,
  154. OutputData &graph_output_data, std::vector<InputOutputDescInfo> &output_desc) {
  155. // Preprocessing input data
  156. graph_input_data.index = 0;
  157. graph_input_data.timeout = 0;
  158. graph_input_data.timestamp = 0;
  159. std::size_t inputSize = input_tensor.size();
  160. std::size_t output_size = output_desc.size();
  161. std::vector<uint64_t> bufferSizeVec;
  162. std::vector<void *> addrVec;
  163. for (std::size_t i = 0; i < inputSize; ++i) {
  164. const GeTensor *InTensor = &input_tensor[i];
  165. GE_CHECK_NOTNULL(InTensor);
  166. bufferSizeVec.push_back(InTensor->GetData().size());
  167. }
  168. for (const auto &desc : output_desc) {
  169. bufferSizeVec.push_back(desc.size);
  170. }
  171. Status ret = MallocInOutBuffer(bufferSizeVec, addrVec);
  172. if (ret != SUCCESS) {
  173. GELOGE(GE_GRAPH_MALLOC_FAILED, "[GraphExecutor] Malloc mem failed");
  174. return GE_GRAPH_MALLOC_FAILED;
  175. }
  176. for (std::size_t i = 0; i < input_tensor.size() && i < addrVec.size(); ++i) {
  177. const GeTensor *in_tensor = &input_tensor[i];
  178. GE_CHECK_NOTNULL(in_tensor);
  179. if ((addrVec[i] != nullptr) && (in_tensor->GetData().data() != nullptr)) {
  180. rtError_t rt_ret = rtMemcpy(addrVec[i], bufferSizeVec[i], in_tensor->GetData().data(),
  181. in_tensor->GetData().size(), RT_MEMCPY_HOST_TO_HOST);
  182. if (rt_ret != RT_ERROR_NONE) {
  183. REPORT_CALL_ERROR("E19999", "Call rtMemcpy failed, dst_size:%lu, src_size:%zu, ret:0x%X",
  184. bufferSizeVec[i], in_tensor->GetData().size(), rt_ret);
  185. GELOGE(RT_FAILED, "Call rt api failed, ret: 0x%X", rt_ret);
  186. return RT_FAILED;
  187. }
  188. }
  189. DataBuffer in_data_buf;
  190. in_data_buf.data = reinterpret_cast<uint8_t *>(addrVec[i]);
  191. in_data_buf.length = in_tensor->GetData().size();
  192. in_data_buf.isDataSupportMemShare = false;
  193. graph_input_data.blobs.push_back(in_data_buf);
  194. }
  195. graph_output_data.index = 0;
  196. for (std::size_t j = 0; j < output_size; j++) {
  197. auto desc = output_desc[j];
  198. uint64_t buffer_size = desc.size;
  199. DataBuffer out_data_buf;
  200. out_data_buf.data = reinterpret_cast<uint8_t *>(addrVec[inputSize + j]);
  201. out_data_buf.length = buffer_size;
  202. out_data_buf.isDataSupportMemShare = false;
  203. graph_output_data.blobs.push_back(out_data_buf);
  204. }
  205. return SUCCESS;
  206. }
  207. Status GraphExecutor::SyncExecuteModel(uint32_t model_id, const std::vector<GeTensor> &input_tensor,
  208. std::vector<GeTensor> &output_tensor) {
  209. auto model_manager = ge::ModelManager::GetInstance();
  210. GE_CHECK_NOTNULL(model_manager);
  211. if (model_manager->IsDynamicShape(model_id)) {
  212. GELOGI("[ExecuteGraph] GetInputOutputDescInfo via dynamic shape model executor, modelId=%u", model_id);
  213. return model_manager->SyncExecuteModel(model_id, input_tensor, output_tensor);
  214. }
  215. // Prepare input and output
  216. std::vector<InputOutputDescInfo> inputs_desc;
  217. std::vector<InputOutputDescInfo> output_desc;
  218. GELOGI("[ExecuteGraph] GetInputOutputDescInfo via new ome begin.");
  219. Status ret = GetInputOutputDescInfo(model_id, inputs_desc, output_desc);
  220. if (ret != SUCCESS) {
  221. GELOGE(GE_GRAPH_GET_IN_OUT_FAILED, "[GraphExecutor] GetInputOutputDescInfo failed, modelId=%u.", model_id);
  222. return GE_GRAPH_GET_IN_OUT_FAILED;
  223. }
  224. outputs_desc_.assign(output_desc.begin(), output_desc.end());
  225. InputData input_data;
  226. OutputData output_data;
  227. input_data.model_id = model_id;
  228. ret = PrepareInputData(input_tensor, input_data, output_data, output_desc);
  229. if (ret != SUCCESS) {
  230. GELOGE(GE_GRAPH_PREPARE_FAILED, "[GraphExecutor] PrepareInputData failed, modelId=%u.", model_id);
  231. return GE_GRAPH_PREPARE_FAILED;
  232. }
  233. if (graph_run_listener_->ResetResult() != SUCCESS) {
  234. REPORT_CALL_ERROR("E19999", "Call graph_run_listener_.ResetResult fail, model_id:%u",
  235. model_id);
  236. GELOGE(GE_GRAPH_EXECUTE_FAILED, "Reset result failed");
  237. return GE_GRAPH_EXECUTE_FAILED;
  238. }
  239. // Run mode async
  240. GELOGI("[ExecuteGraph] DataInput via new ome begin.");
  241. ret = DataInput(input_data, output_data);
  242. if (ret != SUCCESS) {
  243. GELOGE(GE_GRAPH_DATA_INPUT_FAILED, "[GraphExecutor] push data failed, modelId=%u.", model_id);
  244. return GE_GRAPH_DATA_INPUT_FAILED;
  245. }
  246. GELOGI("[GraphExecutor] input data push to wrapper finish, waiting for result...");
  247. // Pending until async execute graph complete
  248. {
  249. std::unique_lock<std::mutex> ulock(*sync_run_mutex_);
  250. if (!graph_run_listener_->IsFinished()) {
  251. (*condition_).wait(ulock);
  252. }
  253. // Run graph return
  254. uint32_t result_code = graph_run_listener_->GetResultCode();
  255. if (result_code != SUCCESS && result_code != END_OF_SEQUENCE) {
  256. REPORT_CALL_ERROR("E19999", "Graph_run_listener_ run fail, result:%u, model_id:%u",
  257. result_code, model_id);
  258. GELOGE(GE_GRAPH_EXECUTE_FAILED, "[GraphExecutor] execute model failed, ret=%u, modelId=%u.", result_code,
  259. model_id);
  260. return GE_GRAPH_EXECUTE_FAILED;
  261. }
  262. }
  263. for (size_t i = 0; i < output_data.blobs.size(); ++i) {
  264. DataBuffer outputDataTmp = output_data.blobs[i];
  265. CHECK_FALSE_EXEC(outputDataTmp.length != 0,
  266. REPORT_INNER_ERROR("E19999", "Param output_data.length is 0 in model:%u, check invalid",
  267. model_id);
  268. GELOGE(GE_GRAPH_EXECUTE_FAILED, "Failed to allocate memory, length is 0.");
  269. return GE_GRAPH_EXECUTE_FAILED);
  270. std::unique_ptr<uint8_t> outBufTmp(new (std::nothrow) uint8_t[outputDataTmp.length]);
  271. if (outBufTmp == nullptr) {
  272. REPORT_CALL_ERROR("E19999", "New output buffer fail, length:%lu, model:%u",
  273. outputDataTmp.length, model_id);
  274. GELOGE(FAILED, "Failed to allocate memory.");
  275. return FAILED;
  276. }
  277. GE_PRINT_DYNAMIC_MEMORY(new, "the output memory of data on training.", sizeof(uint8_t) * outputDataTmp.length)
  278. rtError_t ret_value = rtMemcpy(outBufTmp.get(), outputDataTmp.length, outputDataTmp.data, outputDataTmp.length,
  279. RT_MEMCPY_HOST_TO_HOST);
  280. CHECK_FALSE_EXEC(ret_value == RT_ERROR_NONE,
  281. REPORT_CALL_ERROR("E19999", "Call rtMemcpy failed, dst_size:%lu, src_size:%zu, ret:0x%X",
  282. outputDataTmp.length, outputDataTmp.length, ret_value);
  283. GELOGE(GE_GRAPH_EXECUTE_FAILED, "Call rt api rtMemcpy failed, ret: 0x%X", ret);
  284. return GE_GRAPH_EXECUTE_FAILED);
  285. GeTensor outTensor;
  286. std::vector<int64_t> shapeDims;
  287. for (const auto &dim : output_desc[i].shape_info.dims) {
  288. shapeDims.push_back(dim);
  289. }
  290. GeShape outShape(shapeDims);
  291. outTensor.MutableTensorDesc().SetShape(outShape);
  292. outTensor.MutableTensorDesc().SetDataType((DataType)output_desc[i].data_type);
  293. (void)outTensor.SetData(outBufTmp.get(), outputDataTmp.length);
  294. output_tensor.push_back(outTensor);
  295. }
  296. GELOGI("[GraphExecutor] execute model success, modelId=%u.", model_id);
  297. return SUCCESS;
  298. }
  299. void GraphExecutor::InitModelIdInfo(std::vector<uint32_t> &out_model_id_info,
  300. std::vector<SubGraphInfoPtr> &sub_graph_vec, uint32_t output_size) {
  301. for (uint32_t i = 0; i < output_size; i++) {
  302. for (size_t j = 0; j < sub_graph_vec.size(); j++) {
  303. if (sub_graph_vec[j]->GetOutputFlag().size() == output_size && sub_graph_vec[j]->GetOutputFlag().at(i)) {
  304. out_model_id_info.push_back(sub_graph_vec[j]->GetModelIdInfo().model_id);
  305. }
  306. }
  307. }
  308. }
  309. Status GraphExecutor::FreeExecuteMemory() {
  310. auto ret = FreeInOutBuffer();
  311. if (ret != SUCCESS) {
  312. GELOGE(ret, "[FreeExecuteMemory] FreeInOutBuffer Error!");
  313. return ret;
  314. }
  315. return SUCCESS;
  316. }
  317. Status GraphExecutor::ExecuteGraph(GraphId graph_id, const GeRootModelPtr &ge_root_model,
  318. const std::vector<GeTensor> &input_tensor, std::vector<GeTensor> &output_tensor) {
  319. if (graph_id != last_graph_id_) {
  320. auto ret = FreeExecuteMemory();
  321. if (ret != SUCCESS) {
  322. return ret;
  323. }
  324. }
  325. last_graph_id_ = graph_id;
  326. if (!init_flag_) {
  327. REPORT_INNER_ERROR("E19999", "No SetCondition called before, graph:%u, check invalid",
  328. graph_id);
  329. GELOGE(GE_GRAPH_EXECUTE_NOT_INIT, "[GraphExecutor] AI Core Engine without calling SetCondition!");
  330. return GE_GRAPH_EXECUTE_NOT_INIT;
  331. }
  332. GE_CHECK_NOTNULL_EXEC(ge_root_model, return FAILED);
  333. Status ret = SyncExecuteModel(ge_root_model->GetModelId(), input_tensor, output_tensor);
  334. if (ret != SUCCESS) {
  335. GELOGE(GE_GRAPH_SYNC_MODEL_FAILED, "[GraphExecutor] SyncExecuteModel Error!");
  336. return GE_GRAPH_SYNC_MODEL_FAILED;
  337. }
  338. return SUCCESS;
  339. }
  340. Status GraphExecutor::ExecuteGraphAsync(GraphId graph_id, const GeRootModelPtr &ge_root_model,
  341. const std::vector<InputTensorInfo> &input_tensor,
  342. const RunAsyncCallback& callback) {
  343. GELOGI("[GraphExecutor] Start to async execute graph, graph_id=%u", graph_id);
  344. if (graph_id != last_graph_id_) {
  345. auto ret = FreeExecuteMemory();
  346. if (ret != SUCCESS) {
  347. return ret;
  348. }
  349. }
  350. last_graph_id_ = graph_id;
  351. GE_CHECK_NOTNULL_EXEC(ge_root_model, return FAILED);
  352. Status ret = AsyncExecuteModel(ge_root_model, input_tensor, callback);
  353. if (ret != SUCCESS) {
  354. GELOGE(GE_GRAPH_SYNC_MODEL_FAILED, "[GraphExecutor] AsyncExecuteModel Error!");
  355. return GE_GRAPH_SYNC_MODEL_FAILED;
  356. }
  357. GELOGI("[GraphExecutor] Async execute graph success, graph_id=%u", graph_id);
  358. return SUCCESS;
  359. }
  360. bool CompareByLoad(const Uint32Pair &lhs, const Uint32Pair &rhs) {
  361. return lhs.second < rhs.second;
  362. }
  363. uint32_t GraphExecutor::GetExecuteModelId(const GeRootModelPtr &ge_root_model) {
  364. std::vector<uint32_t> model_ids = ge_root_model->GetAllModelId();
  365. if (model_ids.empty()) {
  366. return kInvalidModelId;
  367. }
  368. if (model_ids.size() == 1) {
  369. return ge_root_model->GetModelId();
  370. }
  371. std::vector<Uint32Pair> model_id_to_loads;
  372. auto model_manager = ModelManager::GetInstance();
  373. GE_CHECK_NOTNULL(model_manager);
  374. for (auto model_id : model_ids) {
  375. auto davinci_model = model_manager->GetModel(model_id);
  376. auto hybrid_model = model_manager->GetHybridModel(model_id);
  377. if (hybrid_model == nullptr) {
  378. GE_CHECK_NOTNULL(davinci_model);
  379. }
  380. uint32_t input_load = hybrid_model != nullptr ? hybrid_model->GetDataInputerSize() :
  381. davinci_model->GetDataInputerSize();
  382. uint32_t running_load = hybrid_model != nullptr ? static_cast<uint32_t>(hybrid_model->GetRunningFlag()) :
  383. static_cast<uint32_t>(davinci_model->GetRunningFlag());
  384. uint32_t load = input_load + running_load;
  385. if (load == 0) {
  386. return model_id;
  387. }
  388. model_id_to_loads.emplace_back(model_id, load);
  389. }
  390. sort(model_id_to_loads.begin(), model_id_to_loads.end(), CompareByLoad);
  391. if (model_id_to_loads.empty()) {
  392. return kInvalidModelId;
  393. }
  394. return model_id_to_loads.begin()->first;
  395. }
  396. Status GraphExecutor::SetCallback(uint32_t model_id, const GeRootModelPtr &ge_root_model,
  397. const RunAsyncCallback &callback) {
  398. auto model_manager = ge::ModelManager::GetInstance();
  399. GE_CHECK_NOTNULL(model_manager);
  400. if (model_manager->IsNeedHybridLoad(*ge_root_model)) {
  401. auto model = model_manager->GetHybridModel(model_id);
  402. GE_CHECK_NOTNULL(model);
  403. if (model->SetRunAsyncListenerCallback(callback) != SUCCESS) {
  404. GELOGE(FAILED, "SetRunAsyncListenerCallback failed.");
  405. return FAILED;
  406. }
  407. } else {
  408. auto model = model_manager->GetModel(model_id);
  409. GE_CHECK_NOTNULL(model);
  410. if (model->SetRunAsyncListenerCallback(callback) != SUCCESS) {
  411. GELOGE(FAILED, "SetRunAsyncListenerCallback failed.");
  412. return FAILED;
  413. }
  414. }
  415. return SUCCESS;
  416. }
  417. Status GraphExecutor::AsyncExecuteModel(const GeRootModelPtr &ge_root_model, const std::vector<InputTensorInfo> &inputs,
  418. const RunAsyncCallback &callback) {
  419. uint32_t model_id = GetExecuteModelId(ge_root_model);
  420. if (model_id == kInvalidModelId) {
  421. GELOGE(INTERNAL_ERROR, "No valid model id.");
  422. return INTERNAL_ERROR;
  423. }
  424. try {
  425. auto model_manager = ge::ModelManager::GetInstance();
  426. GE_CHECK_NOTNULL(model_manager);
  427. GELOGI("RunAsync begin.model_id %u", model_id);
  428. if (SetCallback(model_id, ge_root_model, callback) != SUCCESS) {
  429. GELOGE(FAILED, "RunAsync: SetCallBack for model fail");
  430. return FAILED;
  431. }
  432. Status ret = model_manager->DataInputTensor(model_id, inputs);
  433. if (ret != SUCCESS) {
  434. GELOGE(ret, "RunAsync: DataInput fail");
  435. return ret;
  436. }
  437. GELOGI("RunAsync success.");
  438. } catch (std::bad_alloc &) {
  439. REPORT_INNER_ERROR("E19999", "Bad memory allocation exception occur failed");
  440. GELOGE(MEMALLOC_FAILED, "RunAsync failed, bad memory allocation occur !");
  441. CsaInteract::GetInstance().WriteErrorCode(FAILED, ERROR_MODULE_FMK, JOBSUBSTATE_GRAPH_EXEC);
  442. return MEMALLOC_FAILED;
  443. } catch (...) {
  444. REPORT_INNER_ERROR("E19999", "Some exceptions occur failed");
  445. GELOGE(FAILED, "RunAsync failed, some exceptions occur !");
  446. CsaInteract::GetInstance().WriteErrorCode(FAILED, ERROR_MODULE_FMK, JOBSUBSTATE_GRAPH_EXEC);
  447. return FAILED;
  448. }
  449. return SUCCESS;
  450. }
  451. Status GraphExecutor::DataInput(const InputData &input_data, OutputData &output_data) {
  452. try {
  453. auto model_manager = ge::ModelManager::GetInstance();
  454. GE_CHECK_NOTNULL(model_manager);
  455. Status ret = model_manager->DataInput(input_data, output_data);
  456. if (ret != SUCCESS) {
  457. GELOGE(ret, "DataInput: DataInput failed.");
  458. CsaInteract::GetInstance().WriteErrorCode(ret, ERROR_MODULE_FMK, JOBSUBSTATE_GRAPH_EXEC);
  459. return ret;
  460. }
  461. } catch (std::bad_alloc &) {
  462. REPORT_INNER_ERROR("E19999", "Bad memory allocation exception occur failed");
  463. GELOGE(MEMALLOC_FAILED, "DataInput failed, bad memory allocation occur !");
  464. CsaInteract::GetInstance().WriteErrorCode(FAILED, ERROR_MODULE_FMK, JOBSUBSTATE_GRAPH_EXEC);
  465. return MEMALLOC_FAILED;
  466. } catch (...) {
  467. REPORT_INNER_ERROR("E19999", "Some exceptions occur failed");
  468. GELOGE(FAILED, "DataInput failed, some exceptions occur !");
  469. CsaInteract::GetInstance().WriteErrorCode(FAILED, ERROR_MODULE_FMK, JOBSUBSTATE_GRAPH_EXEC);
  470. return FAILED;
  471. }
  472. return SUCCESS;
  473. }
  474. Status GraphExecutor::GetInputOutputDescInfo(const uint32_t model_id, vector<InputOutputDescInfo> &input_desc,
  475. vector<InputOutputDescInfo> &output_desc) {
  476. try {
  477. auto model_manager = ge::ModelManager::GetInstance();
  478. GE_CHECK_NOTNULL(model_manager);
  479. Status ret = model_manager->GetInputOutputDescInfo(model_id, input_desc, output_desc);
  480. if (ret != SUCCESS) {
  481. GELOGE(ret, "GetInputOutputDescInfo failed.");
  482. CsaInteract::GetInstance().WriteErrorCode(ret, ERROR_MODULE_FMK, JOBSUBSTATE_GRAPH_EXEC);
  483. return ret;
  484. }
  485. } catch (std::bad_alloc &) {
  486. REPORT_INNER_ERROR("E19999", "Bad memory allocation exception occur failed");
  487. GELOGE(MEMALLOC_FAILED, "GetInputOutputDescInfo failed, bad memory allocation occur !");
  488. CsaInteract::GetInstance().WriteErrorCode(FAILED, ERROR_MODULE_FMK, JOBSUBSTATE_GRAPH_EXEC);
  489. return MEMALLOC_FAILED;
  490. } catch (...) {
  491. REPORT_INNER_ERROR("E19999", "Some exceptions occur failed");
  492. GELOGE(FAILED, "GetInputOutputDescInfo failed, some exceptions occur !");
  493. CsaInteract::GetInstance().WriteErrorCode(FAILED, ERROR_MODULE_FMK, JOBSUBSTATE_GRAPH_EXEC);
  494. return FAILED;
  495. }
  496. return SUCCESS;
  497. }
  498. Status GraphExecutor::GetInputOutputDescInfo(const uint32_t model_id, vector<InputOutputDescInfo> &input_desc,
  499. vector<InputOutputDescInfo> &output_desc,
  500. std::vector<uint32_t> &input_formats, std::vector<uint32_t> &out_formats,
  501. bool new_model_desc) {
  502. try {
  503. auto model_manager = ge::ModelManager::GetInstance();
  504. GE_CHECK_NOTNULL(model_manager);
  505. Status ret = model_manager->GetInputOutputDescInfo(model_id, input_desc, output_desc, input_formats, out_formats,
  506. new_model_desc);
  507. if (ret != SUCCESS) {
  508. GELOGE(ret, "GetInputOutputDescInfo failed.");
  509. CsaInteract::GetInstance().WriteErrorCode(ret, ERROR_MODULE_FMK, JOBSUBSTATE_GRAPH_EXEC);
  510. return ret;
  511. }
  512. } catch (std::bad_alloc &) {
  513. REPORT_INNER_ERROR("E19999", "Bad memory allocation exception occur failed");
  514. GELOGE(MEMALLOC_FAILED, "GetInputOutputDescInfo failed, bad memory allocation occur !");
  515. CsaInteract::GetInstance().WriteErrorCode(FAILED, ERROR_MODULE_FMK, JOBSUBSTATE_GRAPH_EXEC);
  516. return MEMALLOC_FAILED;
  517. } catch (...) {
  518. REPORT_INNER_ERROR("E19999", "Some exceptions occur failed");
  519. GELOGE(FAILED, "GetInputOutputDescInfo failed, some exceptions occur !");
  520. CsaInteract::GetInstance().WriteErrorCode(FAILED, ERROR_MODULE_FMK, JOBSUBSTATE_GRAPH_EXEC);
  521. return FAILED;
  522. }
  523. return SUCCESS;
  524. }
  525. ///
  526. /// @ingroup ge
  527. /// @brief Get dynamic batch_info
  528. /// @param [in] model_id
  529. /// @param [out] batch_info
  530. /// @param [out] dynamic_type
  531. /// @return execute result
  532. ///
  533. Status GraphExecutor::GetDynamicBatchInfo(uint32_t model_id, std::vector<std::vector<int64_t>> &batch_info,
  534. int32_t &dynamic_type) {
  535. auto model_manager = ge::ModelManager::GetInstance();
  536. GE_CHECK_NOTNULL(model_manager);
  537. Status ret = model_manager->GetDynamicBatchInfo(model_id, batch_info, dynamic_type);
  538. if (ret != SUCCESS) {
  539. GELOGE(ret, "GetDynamicBatchInfo failed.");
  540. return ret;
  541. }
  542. return SUCCESS;
  543. }
  544. ///
  545. /// @ingroup ge
  546. /// @brief Get combined dynamic dims info
  547. /// @param [in] model_id
  548. /// @param [out] batch_info
  549. /// @return execute result
  550. ///
  551. Status GraphExecutor::GetCombinedDynamicDims(uint32_t model_id, std::vector<std::vector<int64_t>> &batch_info) {
  552. auto model_manager = ge::ModelManager::GetInstance();
  553. GE_CHECK_NOTNULL(model_manager);
  554. Status ret = model_manager->GetCombinedDynamicDims(model_id, batch_info);
  555. if (ret != SUCCESS) {
  556. GELOGE(ret, "GetCombinedDynamicDims failed.");
  557. return ret;
  558. }
  559. return SUCCESS;
  560. }
  561. ///
  562. /// @ingroup ge
  563. /// @brief Get user designate shape order
  564. /// @param [in] model_id
  565. /// @param [out] user_input_shape_order
  566. /// @return execute result
  567. ///
  568. ge::Status GraphExecutor::GetUserDesignateShapeOrder(uint32_t model_id,
  569. std::vector<std::string> &user_input_shape_order) {
  570. auto model_manager = ge::ModelManager::GetInstance();
  571. GE_CHECK_NOTNULL(model_manager);
  572. Status ret = model_manager->GetUserDesignateShapeOrder(model_id, user_input_shape_order);
  573. if (ret != SUCCESS) {
  574. GELOGE(ret, "GetUserDesignateShapeOrder failed.");
  575. return ret;
  576. }
  577. return SUCCESS;
  578. }
  579. Status GraphExecutor::GetCurShape(const uint32_t model_id, std::vector<int64_t> &batch_info, int32_t &dynamic_type) {
  580. auto model_manager = ge::ModelManager::GetInstance();
  581. GE_CHECK_NOTNULL(model_manager);
  582. Status ret = model_manager->GetCurShape(model_id, batch_info, dynamic_type);
  583. if (ret != SUCCESS) {
  584. GELOGE(ret, "GetCurShape failed");
  585. return ret;
  586. }
  587. return SUCCESS;
  588. }
  589. Status GraphExecutor::GetModelAttr(uint32_t model_id, std::vector<string> &dynamic_output_shape_info) {
  590. auto model_manager = ge::ModelManager::GetInstance();
  591. GE_CHECK_NOTNULL(model_manager);
  592. Status ret = model_manager->GetModelAttr(model_id, dynamic_output_shape_info);
  593. if (ret != SUCCESS) {
  594. GELOGE(FAILED, "GetModelAttr failed");
  595. return ret;
  596. }
  597. return SUCCESS;
  598. }
  599. Status GraphExecutor::GetAippInfo(uint32_t model_id, uint32_t index, AippConfigInfo &aipp_info) {
  600. auto model_manager = ge::ModelManager::GetInstance();
  601. GE_CHECK_NOTNULL(model_manager);
  602. Status ret = model_manager->GetAippInfo(model_id, index, aipp_info);
  603. if (ret != SUCCESS) {
  604. GELOGW("GetAIPPInfo is not success.");
  605. return ret;
  606. }
  607. return SUCCESS;
  608. }
  609. Status GraphExecutor::GetAippType(uint32_t model_id, uint32_t index, InputAippType &type, size_t &aipp_index) {
  610. auto model_manager = ge::ModelManager::GetInstance();
  611. GE_CHECK_NOTNULL(model_manager);
  612. Status ret = model_manager->GetAippType(model_id, index, type, aipp_index);
  613. if (ret != SUCCESS) {
  614. GELOGW("Get aipp type is not success.");
  615. return ret;
  616. }
  617. return SUCCESS;
  618. }
  619. Status GraphExecutor::GetOrigInputInfo(uint32_t model_id, uint32_t index, OriginInputInfo &orig_input_info) {
  620. auto model_manager = ge::ModelManager::GetInstance();
  621. GE_CHECK_NOTNULL(model_manager);
  622. Status ret = model_manager->GetOrigInputInfo(model_id, index, orig_input_info);
  623. if (ret != SUCCESS) {
  624. GELOGE(ret, "GetOrigInputInfo failed.");
  625. return ret;
  626. }
  627. return SUCCESS;
  628. }
  629. Status GraphExecutor::GetAllAippInputOutputDims(uint32_t model_id, uint32_t index,
  630. std::vector<InputOutputDims> &input_dims,
  631. std::vector<InputOutputDims> &output_dims) {
  632. auto model_manager = ge::ModelManager::GetInstance();
  633. GE_CHECK_NOTNULL(model_manager);
  634. Status ret = model_manager->GetAllAippInputOutputDims(model_id, index, input_dims, output_dims);
  635. if (ret != SUCCESS) {
  636. GELOGE(ret, "GetAllAippInputOutputDims failed.");
  637. return ret;
  638. }
  639. return SUCCESS;
  640. }
  641. Status GraphExecutor::GetOpDescInfo(uint32_t device_id, uint32_t stream_id, uint32_t task_id,
  642. OpDescInfo &op_desc_info) {
  643. auto model_manager = ge::ModelManager::GetInstance();
  644. GE_CHECK_NOTNULL(model_manager);
  645. Status ret = model_manager->GetOpDescInfo(device_id, stream_id, task_id, op_desc_info);
  646. if (ret != SUCCESS) {
  647. GELOGE(ret, "GetOpDescInfo failed.");
  648. return ret;
  649. }
  650. return SUCCESS;
  651. }
  652. } // 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