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