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profiling_manager.cc 32 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 "common/profiling/profiling_manager.h"
  17. #include "framework/common/debug/ge_log.h"
  18. #include "framework/common/debug/log.h"
  19. #include "framework/common/string_util.h"
  20. #include "graph/ge_context.h"
  21. #include "runtime/base.h"
  22. #include "graph/load/new_model_manager/davinci_model.h"
  23. namespace {
  24. const char *const kTrainingTrace = "training_trace";
  25. const char *const kFpPoint = "fp_point";
  26. const char *const kBpPoint = "bp_point";
  27. const size_t kReportMaxLen = 2048;
  28. const int32_t kMaxDeviceNum = 256;
  29. const std::string kConfigNumsdev = "devNums";
  30. const std::string kConfigDevIdList = "devIdList";
  31. const std::string kProfStart = "prof_start";
  32. const std::string kProfStop = "prof_stop";
  33. const std::string kProfModelSubscribe = "prof_model_subscribe";
  34. const std::string kProfModelUnsubscribe = "prof_model_cancel_subscribe";
  35. } // namespace
  36. namespace ge {
  37. ProfilingManager::ProfilingManager()
  38. : is_load_profiling_(false), is_execute_profiling_(false), is_training_trace_(false), subscribe_count_(0) {
  39. prof_cb_.msprofCtrlCallback = nullptr;
  40. prof_cb_.msprofReporterCallback = nullptr;
  41. }
  42. ProfilingManager::~ProfilingManager() {}
  43. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY ProfilingManager &ProfilingManager::Instance() {
  44. static ProfilingManager profiling_manager;
  45. return profiling_manager;
  46. }
  47. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY ge::Status ProfilingManager::Init(const Options &options) {
  48. #ifdef DAVINCI_SUPPORT_PROFILING
  49. vector<int32_t>().swap(device_id_);
  50. subscribe_count_ = 0;
  51. GELOGI("ProfilingManager::Init job_id:%s", options.job_id.c_str());
  52. struct MsprofGeOptions prof_conf = {{ 0 }};
  53. Status ret = InitFromOptions(options, prof_conf);
  54. if (ret != SUCCESS) {
  55. GELOGE(ret, "Failed to init profiling.");
  56. return ret;
  57. }
  58. if (is_execute_profiling_) {
  59. if (prof_cb_.msprofCtrlCallback == nullptr) {
  60. GELOGE(ge::PARAM_INVALID, "MsprofCtrlCallback callback is nullptr.");
  61. return ge::PARAM_INVALID;
  62. }
  63. int32_t cb_ret = prof_cb_.msprofCtrlCallback(
  64. static_cast<uint32_t>(MsprofCtrlCallbackType::MSPROF_CTRL_INIT_GE_OPTIONS),
  65. static_cast<void *>(&prof_conf), sizeof(MsprofGeOptions));
  66. if (cb_ret != 0) {
  67. GELOGE(FAILED, "Call msprofCtrlCallback failed, type:%u, return:%d",
  68. static_cast<uint32_t>(MsprofCtrlCallbackType::MSPROF_CTRL_INIT_GE_OPTIONS), cb_ret);
  69. return FAILED;
  70. }
  71. GELOGI("Profiling init success");
  72. } else {
  73. GELOGI("The profiling is off, skip the initialization");
  74. }
  75. #endif
  76. return SUCCESS;
  77. }
  78. ge::Status ProfilingManager::InitFromOptions(const Options &options, MsprofGeOptions &prof_conf) {
  79. #ifdef DAVINCI_SUPPORT_PROFILING
  80. // enable profiling by env
  81. char env_profiling_mode[MMPA_MAX_PATH] = { 0x00 };
  82. is_execute_profiling_ = false;
  83. if (options.profiling_mode == "1" && !options.profiling_options.empty()) {
  84. // enable profiling by ge option
  85. if (strncpy_s(prof_conf.options, MSPROF_OPTIONS_DEF_LEN_MAX, options.profiling_options.c_str(),
  86. MSPROF_OPTIONS_DEF_LEN_MAX - 1) != EOK) {
  87. GELOGE(INTERNAL_ERROR, "copy profiling_options failed.");
  88. return INTERNAL_ERROR;
  89. }
  90. is_execute_profiling_ = true;
  91. GELOGI("The profiling in options is %s, %s. origin option: %s", options.profiling_mode.c_str(), prof_conf.options,
  92. options.profiling_options.c_str());
  93. } else {
  94. (void)mmGetEnv("PROFILING_MODE", env_profiling_mode, MMPA_MAX_PATH);
  95. (void)mmGetEnv("PROFILING_OPTIONS", prof_conf.options, MSPROF_OPTIONS_DEF_LEN_MAX);
  96. // The env is invalid
  97. if ((strcmp("true", env_profiling_mode) != 0) || (strcmp(prof_conf.options, "\0") == 0)) {
  98. return SUCCESS;
  99. }
  100. // enable profiling by env
  101. is_execute_profiling_ = true;
  102. GELOGI("The profiling in env is %s, %s", env_profiling_mode, prof_conf.options);
  103. }
  104. if (!is_execute_profiling_) {
  105. return SUCCESS;
  106. }
  107. // Parse json str for bp fp
  108. Status ret = ParseOptions(prof_conf.options);
  109. if (ret != ge::SUCCESS) {
  110. GELOGE(ge::PARAM_INVALID, "Parse training trace param failed.");
  111. return ge::PARAM_INVALID;
  112. }
  113. if (strncpy_s(prof_conf.jobId, MSPROF_OPTIONS_DEF_LEN_MAX, options.job_id.c_str(), MSPROF_OPTIONS_DEF_LEN_MAX - 1) !=
  114. EOK) {
  115. GELOGE(INTERNAL_ERROR, "copy job_id failed.");
  116. return INTERNAL_ERROR;
  117. }
  118. GELOGI("Job id: %s, original job id: %s.", prof_conf.jobId, options.job_id.c_str());
  119. #endif
  120. return ge::SUCCESS;
  121. }
  122. ge::Status ProfilingManager::ParseOptions(const std::string &options) {
  123. if (options.empty()) {
  124. GELOGE(ge::PARAM_INVALID, "Profiling options is empty.");
  125. return ge::PARAM_INVALID;
  126. }
  127. try {
  128. Json prof_options = Json::parse(options);
  129. if (options.find(kTrainingTrace) == std::string::npos) {
  130. return ge::SUCCESS;
  131. }
  132. const std::string training_trace = prof_options[kTrainingTrace];
  133. if (training_trace.empty()) {
  134. GELOGI("Training trace will not take effect.");
  135. return ge::SUCCESS;
  136. }
  137. GELOGI("GE profiling training trace:%s", training_trace.c_str());
  138. if (training_trace != "on") {
  139. GELOGE(ge::PARAM_INVALID, "Training trace param:%s is invalid.", training_trace.c_str());
  140. return ge::PARAM_INVALID;
  141. }
  142. fp_point_ = prof_options[kFpPoint];
  143. bp_point_ = prof_options[kBpPoint];
  144. if (!fp_point_.empty() && !bp_point_.empty()) {
  145. GELOGI("Training trace bp fp is set, bp_point:%s, fp_point:%s.", bp_point_.c_str(), fp_point_.c_str());
  146. }
  147. is_training_trace_ = true;
  148. } catch (...) {
  149. GELOGE(FAILED, "Json prof_conf options is invalid.");
  150. return ge::PARAM_INVALID;
  151. }
  152. return ge::SUCCESS;
  153. }
  154. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::StopProfiling() {
  155. #ifdef DAVINCI_SUPPORT_PROFILING
  156. uint64_t module = GetProfilingModule();
  157. // The following if case will not be executed in normal case, inc case of ProfStopProfiling is abnormal
  158. int32_t device_num = static_cast<int32_t>(device_id_.size());
  159. if (device_num != 0) {
  160. auto device_id_ptr = std::unique_ptr<uint32_t[]>(new (std::nothrow) uint32_t[device_num]);
  161. if (device_id_ptr == nullptr) {
  162. GELOGE(FAILED, "Stop profiling: device id ptr is null.");
  163. return;
  164. }
  165. for (int32_t i = 0; i < device_num; i++) {
  166. device_id_ptr[i] = static_cast<uint32_t>(device_id_[i]);
  167. }
  168. rtError_t rt_ret = rtProfilerStop(module, device_num, device_id_ptr.get());
  169. if (rt_ret != RT_ERROR_NONE) {
  170. GELOGW("Call rtProfilerStop failed, ret:%d", rt_ret);
  171. }
  172. }
  173. // stop profiling
  174. if (prof_cb_.msprofCtrlCallback == nullptr) {
  175. GELOGE(ge::PARAM_INVALID, "MsprofCtrlCallback callback is nullptr.");
  176. return;
  177. }
  178. int32_t cb_ret = prof_cb_.msprofCtrlCallback(static_cast<uint32_t>(MsprofCtrlCallbackType::MSPROF_CTRL_FINALIZE),
  179. nullptr, 0);
  180. if (cb_ret != 0) {
  181. GELOGW("call msprofCtrlCallback failed, type:%u, return:%d",
  182. static_cast<uint32_t>(MsprofCtrlCallbackType::MSPROF_CTRL_FINALIZE), cb_ret);
  183. return;
  184. }
  185. GELOGI("Stop Profiling success.");
  186. #endif
  187. }
  188. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::ProfilingTaskDescInfo(
  189. uint32_t model_id, const std::vector<TaskDescInfo> &task_desc_info, const int32_t &device_id) {
  190. #ifdef DAVINCI_SUPPORT_PROFILING
  191. std::string data;
  192. for (const auto &task : task_desc_info) {
  193. std::string model_name = task.model_name;
  194. std::string op_name = task.op_name;
  195. uint32_t block_dim = task.block_dim;
  196. uint32_t task_id = task.task_id;
  197. uint32_t stream_id = task.stream_id;
  198. std::string shape_type = task.shape_type;
  199. int64_t cur_iter_num = task.cur_iter_num;
  200. data = model_name.append(" ")
  201. .append(op_name).append(" ")
  202. .append(std::to_string(block_dim)).append(" ")
  203. .append(std::to_string(task_id)).append(" ")
  204. .append(std::to_string(stream_id)).append(" ")
  205. .append(std::to_string(model_id)).append(" ")
  206. .append(shape_type).append(" ")
  207. .append(std::to_string(cur_iter_num)).append("\n");
  208. ReporterData reporter_data{};
  209. reporter_data.deviceId = device_id;
  210. reporter_data.data = (unsigned char *)data.c_str();
  211. reporter_data.dataLen = data.size();
  212. int ret = memcpy_s(reporter_data.tag, MSPROF_ENGINE_MAX_TAG_LEN + 1, "task_desc_info", sizeof("task_desc_info"));
  213. if (ret != EOK) {
  214. GELOGE(ret, "Report data tag of task_desc_info memcpy error!");
  215. return;
  216. }
  217. int32_t cb_ret = CallMsprofReport(reporter_data);
  218. if (cb_ret != 0) {
  219. GELOGE(cb_ret, "Reporter data of task_desc_info failed, ret:%d", cb_ret);
  220. return;
  221. }
  222. }
  223. data.clear();
  224. #endif
  225. }
  226. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::ProfilingGraphDescInfo(
  227. uint32_t model_id, const std::vector<ComputeGraphDescInfo> &compute_graph_desc_info, const int32_t &device_id) {
  228. #ifdef DAVINCI_SUPPORT_PROFILING
  229. std::string data;
  230. for (const auto &graph : compute_graph_desc_info) {
  231. data.append("model_name:")
  232. .append(graph.model_name)
  233. .append(" op_name:")
  234. .append(graph.op_name)
  235. .append(" op_type:")
  236. .append(graph.op_type);
  237. for (size_t i = 0; i < graph.input_format.size(); ++i) {
  238. data.append(" input_id:")
  239. .append(std::to_string(i))
  240. .append(" input_format:")
  241. .append(std::to_string(graph.input_format.at(i)))
  242. .append(" input_data_type:")
  243. .append(std::to_string(graph.input_data_type.at(i)))
  244. .append(" input_shape:\"");
  245. size_t input_shape_len = graph.input_shape.at(i).size();
  246. if (input_shape_len == 0) {
  247. data.append("");
  248. } else if (input_shape_len == 1) {
  249. data.append(std::to_string(graph.input_shape.at(i).at(0)));
  250. } else {
  251. for (size_t j = 0; j < input_shape_len - 1; ++j) {
  252. data.append(std::to_string(graph.input_shape.at(i).at(j))).append(",");
  253. }
  254. data.append(std::to_string(graph.input_shape.at(i).at(input_shape_len - 1)));
  255. }
  256. data.append("\"");
  257. }
  258. for (size_t i = 0; i < graph.output_format.size(); ++i) {
  259. data.append(" output_id:")
  260. .append(std::to_string(i))
  261. .append(" output_format:")
  262. .append(std::to_string(graph.output_format.at(i)))
  263. .append(" output_data_type:")
  264. .append(std::to_string(graph.output_data_type.at(i)))
  265. .append(" output_shape:\"");
  266. size_t output_shape_len = graph.output_shape.at(i).size();
  267. if (output_shape_len == 0) {
  268. data.append("");
  269. } else if (output_shape_len == 1) {
  270. data.append(std::to_string(graph.output_shape.at(i).at(0)));
  271. } else {
  272. for (size_t j = 0; j < output_shape_len - 1; ++j) {
  273. data.append(std::to_string(graph.output_shape.at(i).at(j))).append(",");
  274. }
  275. data.append(std::to_string(graph.output_shape.at(i).at(output_shape_len - 1)));
  276. }
  277. data.append("\"");
  278. }
  279. data.append(" model_id:").append(std::to_string(model_id));
  280. data.append(" task_id:").append(std::to_string(graph.task_id));
  281. data.append(" stream_id:").append(std::to_string(graph.stream_id));
  282. data.append("\n");
  283. GraphDescReport(device_id, data);
  284. data.clear();
  285. }
  286. #endif
  287. }
  288. void ProfilingManager::GraphDescReport(const int32_t &device_id, const string &data) {
  289. #ifdef DAVINCI_SUPPORT_PROFILING
  290. ReporterData reporter_data{};
  291. int ret = -1;
  292. int32_t cb_ret = -1;
  293. size_t index = data.size() / kReportMaxLen;
  294. if (index >= 1) {
  295. reporter_data.deviceId = device_id;
  296. ret = memcpy_s(reporter_data.tag, MSPROF_ENGINE_MAX_TAG_LEN + 1, "graph_desc_info", sizeof("graph_desc_info"));
  297. GE_IF_BOOL_EXEC(ret != EOK, GELOGE(ret, "Report data tag of graph_desc_info memcpy error!"); return;);
  298. for (size_t i = 0; i < index; ++i) {
  299. reporter_data.data = (unsigned char *)data.c_str() + kReportMaxLen * i;
  300. reporter_data.dataLen = kReportMaxLen;
  301. cb_ret = CallMsprofReport(reporter_data);
  302. GE_IF_BOOL_EXEC(cb_ret != 0, GELOGE(cb_ret, "Reporter data of graph_desc_info failed, ret:%d", cb_ret); return;);
  303. }
  304. reporter_data.dataLen = data.size() - kReportMaxLen * index;
  305. if (reporter_data.dataLen != 0) {
  306. reporter_data.data = (unsigned char *)data.c_str() + kReportMaxLen * index;
  307. cb_ret = CallMsprofReport(reporter_data);
  308. GE_IF_BOOL_EXEC(cb_ret != 0, GELOGE(cb_ret, "Reporter data of graph_desc_info failed, ret:%d", cb_ret); return;);
  309. }
  310. } else {
  311. reporter_data.deviceId = device_id;
  312. reporter_data.data = (unsigned char *)data.c_str();
  313. reporter_data.dataLen = data.size();
  314. ret = memcpy_s(reporter_data.tag, MSPROF_ENGINE_MAX_TAG_LEN + 1, "graph_desc_info", sizeof("graph_desc_info"));
  315. GE_IF_BOOL_EXEC(ret != EOK, GELOGE(ret, "Report data tag of graph_desc_info memcpy error!"); return;);
  316. cb_ret = CallMsprofReport(reporter_data);
  317. GE_IF_BOOL_EXEC(cb_ret != 0, GELOGE(cb_ret, "Reporter data of graph_desc_info failed, ret:%d", cb_ret); return;);
  318. }
  319. #endif
  320. }
  321. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::ReportProfilingData(
  322. uint32_t model_id, const std::vector<TaskDescInfo> &task_desc_info,
  323. const std::vector<ComputeGraphDescInfo> &compute_graph_desc_info) {
  324. #ifdef DAVINCI_SUPPORT_PROFILING
  325. int32_t logic_device_id = 0;
  326. rtError_t rt_ret = rtGetDevice(&logic_device_id);
  327. if (rt_ret != RT_ERROR_NONE) {
  328. GELOGE(rt_ret, "runtime get logic_device_id failed, current logic_device_id:%d", logic_device_id);
  329. return;
  330. }
  331. GELOGD("current logic_device_id:%d", logic_device_id);
  332. GELOGD("start ProfilingTaskDescInfo.");
  333. ProfilingTaskDescInfo(model_id, task_desc_info, logic_device_id);
  334. GELOGD("start ProfilingGraphDescInfo.");
  335. ProfilingGraphDescInfo(model_id, compute_graph_desc_info, logic_device_id);
  336. GELOGD("Report profiling data for GE end.");
  337. #endif
  338. }
  339. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY uint64_t ProfilingManager::GetProfilingModule() {
  340. uint64_t module = PROF_MODEL_EXECUTE_MASK |
  341. PROF_RUNTIME_API_MASK |
  342. PROF_RUNTIME_TRACE_MASK |
  343. PROF_SCHEDULE_TIMELINE_MASK |
  344. PROF_SCHEDULE_TRACE_MASK |
  345. PROF_TASK_TIME_MASK |
  346. PROF_SUBTASK_TIME_MASK |
  347. PROF_AICPU_TRACE_MASK |
  348. PROF_AICORE_METRICS_MASK |
  349. PROF_AIVECTORCORE_METRICS_MASK |
  350. PROF_MODEL_LOAD_MASK;
  351. return module;
  352. }
  353. void ProfilingManager::UpdateSubscribeDeviceModuleMap(std::string prof_type, uint32_t device_id, uint64_t module) {
  354. #ifdef DAVINCI_SUPPORT_PROFILING
  355. if (prof_type == kProfModelSubscribe) {
  356. if (subs_dev_module_.find(device_id) != subs_dev_module_.end()) {
  357. subs_dev_module_[device_id].subscribe_count++;
  358. } else {
  359. DeviceSubsInfo dev_info;
  360. dev_info.module = module;
  361. dev_info.subscribe_count = 1;
  362. subs_dev_module_[device_id] = dev_info;
  363. }
  364. } else if (prof_type == kProfModelUnsubscribe) {
  365. auto iter = subs_dev_module_.find(device_id);
  366. if (iter != subs_dev_module_.end()) {
  367. if (iter->second.subscribe_count > 0) {
  368. iter->second.subscribe_count--;
  369. }
  370. if (iter->second.subscribe_count == 0) {
  371. subs_dev_module_.erase(iter);
  372. }
  373. }
  374. } else {
  375. GELOGI("No need to update device_id module map.");
  376. }
  377. #endif
  378. }
  379. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY Status ProfilingManager::ProfModelSubscribe(
  380. uint64_t module, void *model) {
  381. #ifdef DAVINCI_SUPPORT_PROFILING
  382. std::lock_guard<std::mutex> lock(mutex_);
  383. uint64_t model_load_mask = module & PROF_MODEL_LOAD_MASK;
  384. if ((subscribe_count_ == 0) && (model_load_mask == PROF_MODEL_LOAD_MASK)) {
  385. // register framework to profiling
  386. // register Framework to profiling
  387. int32_t cb_ret = PluginInit();
  388. if (cb_ret != 0) {
  389. GELOGE(cb_ret, "profiling plugin init failed, ret:%d", cb_ret);
  390. return cb_ret;
  391. }
  392. GELOGI("Prof subscribe: model load profiling on.");
  393. }
  394. subscribe_count_++;
  395. auto davinci_model = static_cast<DavinciModel *>(model);
  396. int32_t device_num = 1;
  397. uint32_t device[1];
  398. device[0] = davinci_model->GetDeviceId();
  399. rtError_t rt_ret = rtProfilerStart(module, device_num, device);
  400. if (rt_ret != RT_ERROR_NONE) {
  401. GELOGE(FAILED, "Runtime profiler start failed.");
  402. return FAILED;
  403. }
  404. UpdateSubscribeDeviceModuleMap(kProfModelSubscribe, device[0], module);
  405. // Report profiling data
  406. Status p_ret = davinci_model->ReportProfilingData();
  407. if (p_ret != SUCCESS) {
  408. GELOGE(p_ret, "Report profiling data failed.");
  409. return p_ret;
  410. }
  411. #endif
  412. return SUCCESS;
  413. }
  414. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY Status ProfilingManager::ProfModelUnsubscribe(
  415. void *model) {
  416. #ifdef DAVINCI_SUPPORT_PROFILING
  417. std::lock_guard<std::mutex> lock(mutex_);
  418. if (subscribe_count_ == 0) {
  419. GELOGW("The profiler has not been subscribed, you do not need to cannel the subscription.");
  420. return SUCCESS;
  421. }
  422. auto davinci_model = static_cast<DavinciModel *>(model);
  423. int32_t dev_num = 1;
  424. uint32_t device[1];
  425. device[0] = davinci_model->GetDeviceId();
  426. auto iter = subs_dev_module_.find(device[0]);
  427. if (iter != subs_dev_module_.end()) {
  428. if (subs_dev_module_[device[0]].subscribe_count == 1) {
  429. // The same device_id, only stop at last time
  430. rtError_t rt_ret = rtProfilerStop(subs_dev_module_[device[0]].module, dev_num, device);
  431. if (rt_ret != RT_ERROR_NONE) {
  432. GELOGE(FAILED, "Runtime profiler stop failed.");
  433. return FAILED;
  434. }
  435. }
  436. UpdateSubscribeDeviceModuleMap(kProfModelUnsubscribe, device[0], subs_dev_module_[device[0]].module);
  437. } else {
  438. GELOGE(FAILED, "The device_id:%u has not been subscribed, do not need to cancel.", device[0]);
  439. return FAILED;
  440. }
  441. subscribe_count_--;
  442. if (subscribe_count_ == 0) {
  443. // profiling plugin uninit at last subscription
  444. PluginUnInit();
  445. }
  446. #endif
  447. return SUCCESS;
  448. }
  449. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY Status ProfilingManager::ProfInit(uint64_t module) {
  450. #ifdef DAVINCI_SUPPORT_PROFILING
  451. std::lock_guard<std::mutex> lock(mutex_);
  452. uint64_t model_load_mask = module & PROF_MODEL_LOAD_MASK;
  453. if (model_load_mask == PROF_MODEL_LOAD_MASK) {
  454. // register Framework to profiling
  455. int32_t cb_ret = PluginInit();
  456. if (cb_ret != 0) {
  457. GELOGE(cb_ret, "profiling plugin init failed, ret:%d", cb_ret);
  458. return cb_ret;
  459. }
  460. int32_t device_num = -1;
  461. rtError_t rt_ret = rtProfilerStart(model_load_mask, device_num, nullptr);
  462. if (rt_ret != RT_ERROR_NONE) {
  463. GELOGE(FAILED, "Runtime profiler start failed.");
  464. return FAILED;
  465. }
  466. is_load_profiling_ = true;
  467. GELOGI("Prof init: model load profiling on.");
  468. }
  469. uint64_t training_trace_mask = module & PROF_TRAINING_TRACE_MASK;
  470. if (training_trace_mask == PROF_TRAINING_TRACE_MASK) {
  471. is_training_trace_ = true;
  472. }
  473. GELOGI("Prof init success.");
  474. #endif
  475. return SUCCESS;
  476. }
  477. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY Status ProfilingManager::ProfFinalize() {
  478. #ifdef DAVINCI_SUPPORT_PROFILING
  479. std::lock_guard<std::mutex> lock(mutex_);
  480. is_load_profiling_ = false;
  481. is_training_trace_ = false;
  482. is_execute_profiling_ = false;
  483. // profiling plugin uninit
  484. PluginUnInit();
  485. int32_t dev_num = -1;
  486. rtError_t rt_ret = rtProfilerStop(PROF_MODEL_LOAD_MASK, dev_num, nullptr);
  487. if (rt_ret != RT_ERROR_NONE) {
  488. GELOGE(FAILED, "Runtime profiler stop failed.");
  489. return FAILED;
  490. }
  491. for (auto device_id_module : device_id_module_map_) {
  492. if (device_id_module.second != 0) {
  493. uint32_t device_id = static_cast<uint32_t>(device_id_module.first);
  494. GELOGI("Prof finalize: device_id: %u, module: 0x%llx.", device_id, device_id_module.second);
  495. rt_ret = rtProfilerStop(device_id_module.second, 1, &device_id);
  496. if (rt_ret != RT_ERROR_NONE) {
  497. GELOGE(FAILED, "Runtime profiler stop failed.");
  498. return FAILED;
  499. }
  500. }
  501. }
  502. device_id_module_map_.clear();
  503. device_id_.clear();
  504. GELOGI("Prof finalize success.");
  505. #endif
  506. return SUCCESS;
  507. }
  508. Status ProfilingManager::ProfParseDeviceId(const std::map<std::string, std::string> &config_para,
  509. vector<int32_t> &device_list) {
  510. #ifdef DAVINCI_SUPPORT_PROFILING
  511. auto iter = config_para.find(kConfigDevIdList);
  512. if (iter != config_para.end()) {
  513. std::string device_id_list = iter->second;
  514. std::string temp;
  515. vector<std::string> decvice_id;
  516. for (uint32_t i = 0; i < device_id_list.size(); i++) {
  517. if (isdigit(device_id_list[i])) {
  518. temp.append(1, device_id_list[i]);
  519. } else {
  520. if (!temp.empty()) {
  521. decvice_id.emplace_back(temp);
  522. }
  523. temp.clear();
  524. }
  525. }
  526. if (!temp.empty()) {
  527. decvice_id.emplace_back(temp);
  528. }
  529. for (uint32_t i = 0; i < decvice_id.size(); i++) {
  530. try {
  531. int32_t dev_id = std::stoi(decvice_id[i]);
  532. device_list.push_back(dev_id);
  533. } catch (std::invalid_argument &) {
  534. GELOGE(FAILED, "Device id: %s is invalid.", decvice_id[i].c_str());
  535. return FAILED;
  536. } catch (std::out_of_range &) {
  537. GELOGE(FAILED, "Device id: %s is out of range.", decvice_id[i].c_str());
  538. return FAILED;
  539. } catch (...) {
  540. GELOGE(FAILED, "Device id: %s cannot change to int.", decvice_id[i].c_str());
  541. return FAILED;
  542. }
  543. }
  544. } else {
  545. GELOGE(FAILED, "Config para not contain device id list.");
  546. return FAILED;
  547. }
  548. #endif
  549. return SUCCESS;
  550. }
  551. Status ProfilingManager::ProfParseParam(const std::map<std::string, std::string> &config_para,
  552. int32_t &device_num, vector<int32_t> &device_list) {
  553. #ifdef DAVINCI_SUPPORT_PROFILING
  554. // device num
  555. auto iter = config_para.find(kConfigNumsdev);
  556. if (iter != config_para.end()) {
  557. try {
  558. device_num = std::stoi(iter->second);
  559. } catch (std::invalid_argument &) {
  560. GELOGE(FAILED, "Device nun: %s is invalid.", iter->second.c_str());
  561. return FAILED;
  562. } catch (std::out_of_range &) {
  563. GELOGE(FAILED, "Device num: %s is out of range.", iter->second.c_str());
  564. return FAILED;
  565. } catch (...) {
  566. GELOGE(FAILED, "Device num: %s cannot change to int.", iter->second.c_str());
  567. return FAILED;
  568. }
  569. } else {
  570. GELOGE(FAILED, "Config para not contain device num.");
  571. return FAILED;
  572. }
  573. // device id
  574. if (ProfParseDeviceId(config_para, device_list) != SUCCESS) {
  575. GELOGE(FAILED, "Parse config para device id failed.");
  576. return FAILED;
  577. }
  578. if (device_num == 0 || device_num > kMaxDeviceNum || device_num != static_cast<int32_t>(device_list.size())) {
  579. GELOGE(FAILED, "Config para device num: %d not equal to device list size: %d.", device_num, device_list.size());
  580. return FAILED;
  581. }
  582. #endif
  583. return SUCCESS;
  584. }
  585. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY Status ProfilingManager::ProfStartProfiling(
  586. uint64_t module, const std::map<std::string, std::string> &config_para) {
  587. #ifdef DAVINCI_SUPPORT_PROFILING
  588. std::lock_guard<std::mutex> lock(mutex_);
  589. uint64_t training_trace_mask = module & PROF_TRAINING_TRACE_MASK;
  590. if (training_trace_mask == PROF_TRAINING_TRACE_MASK) {
  591. is_training_trace_ = true;
  592. }
  593. int32_t device_num = 0;
  594. vector<int32_t> device_list;
  595. if (ProfParseParam(config_para, device_num, device_list) != SUCCESS) {
  596. GELOGE(FAILED, "Prof start parse param failed.");
  597. return FAILED;
  598. }
  599. auto device_id_ptr = std::unique_ptr<uint32_t[]>(new (std::nothrow) uint32_t[device_num]);
  600. if (device_id_ptr == nullptr) {
  601. GELOGE(FAILED, "Prof start: device id ptr is null.");
  602. return FAILED;
  603. }
  604. for (int32_t i = 0; i < device_num; i++) {
  605. device_id_ptr[i] = static_cast<uint32_t>(device_list[i]);
  606. }
  607. GELOGI("Runtime config param: 0x%llx, device num: %d.", module, device_num);
  608. rtError_t rt_ret = rtProfilerStart(module, device_num, device_id_ptr.get());
  609. if (rt_ret != RT_ERROR_NONE) {
  610. GELOGE(FAILED, "Runtime profiler config proc failed.");
  611. return FAILED;
  612. }
  613. if ((module & PROF_MODEL_EXECUTE_MASK) == PROF_MODEL_EXECUTE_MASK) {
  614. for (int32_t i = 0; i < device_num; i++) {
  615. if (std::find(device_id_.begin(), device_id_.end(), device_list[i]) == device_id_.end()) {
  616. device_id_.push_back(device_list[i]);
  617. }
  618. }
  619. GELOGI("Prof start: ge execute model start profiling.");
  620. }
  621. if ((module & PROF_MODEL_LOAD_MASK) == PROF_MODEL_LOAD_MASK) {
  622. GELOGW("Prof start: load model module is invalid.");
  623. }
  624. UpdateDeviceIdModuleMap(kProfStart, module, device_list);
  625. GELOGI("Prof start profiling success.");
  626. #endif
  627. return SUCCESS;
  628. }
  629. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY Status ProfilingManager::ProfStopProfiling(uint64_t module,
  630. const std::map<std::string, std::string> &config_para) {
  631. #ifdef DAVINCI_SUPPORT_PROFILING
  632. std::lock_guard<std::mutex> lock(mutex_);
  633. int32_t device_num = 0;
  634. vector<int32_t> device_list;
  635. if (ProfParseParam(config_para, device_num, device_list) != SUCCESS) {
  636. GELOGE(FAILED, "Prof stop parse param failed.");
  637. return FAILED;
  638. }
  639. auto device_id_ptr = std::unique_ptr<uint32_t[]>(new (std::nothrow) uint32_t[device_num]);
  640. if (device_id_ptr == nullptr) {
  641. GELOGE(FAILED, "Prof stop: device id ptr is null.");
  642. return FAILED;
  643. }
  644. for (int32_t i = 0; i < device_num; i++) {
  645. device_id_ptr[i] = static_cast<uint32_t>(device_list[i]);
  646. }
  647. GELOGI("Prof stop: runtime config param: 0x%llx, device num: %d", module, device_num);
  648. rtError_t rt_ret = rtProfilerStop(module, device_num, device_id_ptr.get());
  649. if (rt_ret != RT_ERROR_NONE) {
  650. GELOGE(FAILED, "Prof stop: runtime profiler config proc failed.");
  651. return FAILED;
  652. }
  653. uint64_t execute_model_mask = module & PROF_MODEL_EXECUTE_MASK;
  654. if (execute_model_mask == PROF_MODEL_EXECUTE_MASK) {
  655. for (int32_t i = 0; i < device_num; i++) {
  656. auto iter = std::find(device_id_.begin(), device_id_.end(), device_list[i]);
  657. if (iter != device_id_.end()) {
  658. device_id_.erase(iter);
  659. }
  660. }
  661. GELOGI("Prof stop: ge execute model stop profiling.");
  662. }
  663. if ((module & PROF_MODEL_LOAD_MASK) == PROF_MODEL_LOAD_MASK) {
  664. GELOGW("Prof stop: load model module is invalid.");
  665. }
  666. UpdateDeviceIdModuleMap(kProfStop, module, device_list);
  667. GELOGI("Prof stop profiling success.");
  668. #endif
  669. return SUCCESS;
  670. }
  671. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::UpdateDeviceIdModuleMap(string prof_type,
  672. uint64_t module, const vector<int32_t> &device_list) {
  673. #ifdef DAVINCI_SUPPORT_PROFILING
  674. if (prof_type == kProfStart) {
  675. for (uint32_t i = 0; i < device_list.size(); i++) {
  676. auto iter = device_id_module_map_.find(device_list[i]);
  677. if (iter != device_id_module_map_.end()) {
  678. uint64_t prof_on_module = device_id_module_map_[device_list[i]];
  679. // save all profiling on module of device
  680. device_id_module_map_[device_list[i]] = prof_on_module | module;
  681. } else {
  682. device_id_module_map_[device_list[i]] = module;
  683. }
  684. }
  685. } else if (prof_type == kProfStop) {
  686. for (uint32_t i = 0; i < device_list.size(); i++) {
  687. auto iter = device_id_module_map_.find(device_list[i]);
  688. if (iter != device_id_module_map_.end()) {
  689. uint64_t prof_on_module = device_id_module_map_[device_list[i]];
  690. uint64_t prof_off_module = prof_on_module & module;
  691. uint64_t prof_on_left_module = prof_on_module & (~prof_off_module);
  692. // stop profiling on module of device
  693. device_id_module_map_[device_list[i]] = prof_on_left_module;
  694. }
  695. }
  696. } else {
  697. GELOGI("No need to update device_id module map.");
  698. }
  699. #endif
  700. }
  701. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY bool ProfilingManager::ProfilingModelExecuteOn() const {
  702. int32_t logic_device_id = 0;
  703. rtError_t rt_ret = rtGetDevice(&logic_device_id);
  704. if (rt_ret != RT_ERROR_NONE) {
  705. GELOGE(rt_ret, "Runtime get logic_device_id failed, current logic_device_id:%d", logic_device_id);
  706. }
  707. GELOGI("Current logic_device_id:%d", logic_device_id);
  708. bool execute_model_prof_on = false;
  709. auto iter = std::find(device_id_.begin(), device_id_.end(), logic_device_id);
  710. if (iter != device_id_.end()) {
  711. execute_model_prof_on = true;
  712. }
  713. GELOGI("Flag is_execute_profiling: %d, execute_model_prof_on: %d", is_execute_profiling_, execute_model_prof_on);
  714. return execute_model_prof_on;
  715. }
  716. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY Status ProfilingManager::PluginInit() const {
  717. if (prof_cb_.msprofReporterCallback == nullptr) {
  718. GELOGE(ge::PARAM_INVALID, "MsprofReporterCallback callback is nullptr.");
  719. return ge::PARAM_INVALID;
  720. }
  721. return prof_cb_.msprofReporterCallback(
  722. static_cast<uint32_t>(MsprofReporterModuleId::MSPROF_MODULE_FRAMEWORK),
  723. static_cast<uint32_t>(MsprofReporterCallbackType::MSPROF_REPORTER_INIT),
  724. nullptr, 0);
  725. }
  726. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::PluginUnInit() const {
  727. #ifdef DAVINCI_SUPPORT_PROFILING
  728. if (prof_cb_.msprofReporterCallback == nullptr) {
  729. GELOGE(ge::PARAM_INVALID, "MsprofReporterCallback callback is nullptr.");
  730. return;
  731. }
  732. int32_t cb_ret = prof_cb_.msprofReporterCallback(
  733. static_cast<uint32_t>(MsprofReporterModuleId::MSPROF_MODULE_FRAMEWORK),
  734. static_cast<uint32_t>(MsprofReporterCallbackType::MSPROF_REPORTER_UNINIT),
  735. nullptr, 0);
  736. if (cb_ret != 0) {
  737. GELOGW("profiling plugin uninit failed, ret:%d", cb_ret);
  738. }
  739. #endif
  740. }
  741. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY Status ProfilingManager::CallMsprofReport(
  742. ReporterData &reporter_data) const {
  743. if (prof_cb_.msprofReporterCallback == nullptr) {
  744. GELOGE(ge::PARAM_INVALID, "MsprofReporterCallback callback is nullptr.");
  745. return ge::PARAM_INVALID;
  746. }
  747. return prof_cb_.msprofReporterCallback(
  748. static_cast<uint32_t>(MsprofReporterModuleId::MSPROF_MODULE_FRAMEWORK),
  749. static_cast<uint32_t>(MsprofReporterCallbackType::MSPROF_REPORTER_REPORT),
  750. static_cast<void *>(&reporter_data), sizeof(ReporterData));
  751. }
  752. FMK_FUNC_HOST_VISIBILITY FMK_FUNC_DEV_VISIBILITY void ProfilingManager::GetFpBpPoint(
  753. std::string &fp_point, std::string &bp_point) {
  754. // Env or options mode, fp_point_/bp_point_ have initiliazed on profiling init
  755. if (!fp_point_.empty() && !bp_point_.empty()) {
  756. fp_point = fp_point_;
  757. bp_point = bp_point_;
  758. GELOGI("Bp Fp have been initialized in env or options. bp_point: %s, fp_point: %s", bp_point.c_str(),
  759. fp_point.c_str());
  760. return;
  761. }
  762. // ProfApi mode and training trace is set
  763. // Parse options first
  764. char env_profiling_options[MSPROF_OPTIONS_DEF_LEN_MAX] = { 0x00 };
  765. bool is_profiling_valid = false;
  766. std::string profiling_options;
  767. if (ge::GetContext().GetOption(OPTION_EXEC_PROFILING_OPTIONS, profiling_options) == SUCCESS &&
  768. !profiling_options.empty()) {
  769. is_profiling_valid = true;
  770. } else {
  771. INT32 ret = mmGetEnv("PROFILING_OPTIONS", env_profiling_options, MSPROF_OPTIONS_DEF_LEN_MAX);
  772. if (ret != EN_OK) {
  773. GELOGI("PROFILING_OPTIONS env is not exist.");
  774. return;
  775. }
  776. GELOGI("Parse env PROFILING_OPTIONS:%s.", env_profiling_options);
  777. profiling_options = env_profiling_options;
  778. is_profiling_valid = true;
  779. }
  780. if (is_profiling_valid) {
  781. try {
  782. Json prof_options = Json::parse(profiling_options);
  783. fp_point_ = prof_options[kFpPoint];
  784. bp_point_ = prof_options[kBpPoint];
  785. fp_point = fp_point_;
  786. bp_point = bp_point_;
  787. if (!fp_point_.empty() && !bp_point_.empty()) {
  788. GELOGI("Training trace bp fp is set, bp_point:%s, fp_point:%s.", bp_point_.c_str(), fp_point_.c_str());
  789. }
  790. } catch (...) {
  791. GELOGW("Json prof options is invalid.");
  792. return;
  793. }
  794. }
  795. return;
  796. }
  797. } // 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