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davinci_model.cc 204 kB

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  1. /**
  2. * Copyright 2019-2020 Huawei Technologies Co., Ltd
  3. *
  4. * Licensed under the Apache License, Version 2.0 (the "License");
  5. * you may not use this file except in compliance with the License.
  6. * You may obtain a copy of the License at
  7. *
  8. * http://www.apache.org/licenses/LICENSE-2.0
  9. *
  10. * Unless required by applicable law or agreed to in writing, software
  11. * distributed under the License is distributed on an "AS IS" BASIS,
  12. * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  13. * See the License for the specific language governing permissions and
  14. * limitations under the License.
  15. */
  16. #include "graph/load/model_manager/davinci_model.h"
  17. #include <graph/utils/node_utils.h>
  18. #include <algorithm>
  19. #include <map>
  20. #include <utility>
  21. #include "common/debug/log.h"
  22. #include "common/formats/formats.h"
  23. #include "common/formats/utils/formats_trans_utils.h"
  24. #include "common/math/math_util.h"
  25. #include "common/op/ge_op_utils.h"
  26. #include "common/profiling/profiling_manager.h"
  27. #include "common/properties_manager.h"
  28. #include "common/scope_guard.h"
  29. #include "common/thread_pool.h"
  30. #include "framework/common/debug/ge_log.h"
  31. #include "framework/common/util.h"
  32. #include "graph/common/ge_call_wrapper.h"
  33. #include "graph/compute_graph.h"
  34. #include "graph/debug/ge_attr_define.h"
  35. #include "graph/ge_context.h"
  36. #include "graph/graph.h"
  37. #include "graph/load/model_manager/cpu_queue_schedule.h"
  38. #include "graph/load/model_manager/model_manager.h"
  39. #include "graph/load/model_manager/tbe_handle_store.h"
  40. #include "graph/manager/graph_mem_manager.h"
  41. #include "graph/manager/graph_var_manager.h"
  42. #include "graph/manager/trans_var_data_utils.h"
  43. #include "graph/manager/util/debug.h"
  44. #include "graph/model_serialize.h"
  45. #include "graph/node.h"
  46. #include "graph/utils/graph_utils.h"
  47. #include "graph/utils/type_utils.h"
  48. #include "init/gelib.h"
  49. #include "mmpa/mmpa_api.h"
  50. #include "runtime/base.h"
  51. #include "runtime/dev.h"
  52. #include "runtime/event.h"
  53. #include "runtime/mem.h"
  54. #include "runtime/rt_model.h"
  55. #include "runtime/stream.h"
  56. #include "securec.h"
  57. #include "graph/common/local_context.h"
  58. #include "common/formats/utils/formats_trans_utils.h"
  59. #include "graph/common/omg_util.h"
  60. #include "graph/build/memory/block_mem_assigner.h"
  61. #include "graph/manager/session_scope_mem_allocator.h"
  62. // create std::thread, catch exceptions using try/catch
  63. #define CREATE_STD_THREAD(thread_id, func, args) \
  64. do { \
  65. try { \
  66. thread_id = std::thread(func, args); \
  67. } catch (const std::system_error &e) { \
  68. REPORT_CALL_ERROR("E19999", "Create thread fail, ecode:%d, emsg:%s", \
  69. e.code().value(), e.what()); \
  70. GELOGE(FAILED, "[Create][Thread] Caught system_error with code:%d, meaning:%s", \
  71. e.code().value(), e.what()); \
  72. GELOGE(FAILED, "[Create][Thread] FAIL, Please check the left resource!"); \
  73. return FAILED; \
  74. } \
  75. } while (0)
  76. namespace ge {
  77. namespace {
  78. const uint32_t kDataIndex = 0;
  79. const uint32_t kTrueBranchStreamNum = 1;
  80. const uint32_t kGetDynamicDimsCount = 1;
  81. const uint32_t kThreadNum = 16;
  82. const uint32_t kAddrLen = sizeof(void *);
  83. const int kDecimal = 10;
  84. const int kBytes = 8;
  85. const uint32_t kDataMemAlignSizeCompare = 64;
  86. const uint32_t kDumpL1FusionOpMByteSize = 2097152; // 2 * 1024 * 1024
  87. const uint32_t kDumpFlagOfL1Fusion = 0;
  88. const char *const kDefaultBatchLable = "Batch_default";
  89. const char *const kGetDynamicDimsName = "ascend_mbatch_get_dynamic_dims_node";
  90. const char *const kMultiBatchNodePostfix = "_ascend_mbatch_batch_";
  91. const int32_t kInvalidStream = -1;
  92. const uint32_t kEndOfSequence = 0x0704000a;
  93. const uint32_t kEndOfSequenceNew = 507005;
  94. const int32_t kModelAbortNormal = 0x0704000e;
  95. const int32_t kModelAbortNormalNew = 507024;
  96. const uint32_t kInteval = 2;
  97. const uint32_t kFftsTbeHandleElementSize = 2;
  98. const uint32_t kNonTailBlock = 0;
  99. const uint32_t kTailBlock = 1;
  100. const char *const kModelName = "model_name";
  101. const char *const kModeleId = "model_id";
  102. const char *const kLoadStartTime = "load_start_time";
  103. const char *const kLoadEndTime = "load_end_time";
  104. const char *const kFusionOpInfo = "fusion_op_info";
  105. const char *const kFusionOpName = "fusion_op_name";
  106. const char *const kOriginalOpNum = "origin_op_num";
  107. const char *const kOriginalOpName = "origin_op_name";
  108. const char *const kStreamId = "stream_id";
  109. const char *const kFusionOpMemoryInfo = "memory_info";
  110. const char *const kInputSize = "input_size";
  111. const char *const kOutputSize = "output_size";
  112. const char *const kWeightSize = "weight_size";
  113. const char *const kWorkSpaceSize = "workspace_size";
  114. const char *const kTotalSize = "total_size";
  115. const char *const kTaskCount = "task_count";
  116. const char *const kTaskId = "task_id";
  117. const char *const kRequestId = "request_id";
  118. const char *const kThreadId = "thread_id";
  119. const char *const kInputBeginTime = "input_begin_time";
  120. const char *const kInputEndTime = "input_end_time";
  121. const char *const kInferBeginTime = "infer_begin_time";
  122. const char *const kInferEndTime = "infer_end_time";
  123. const char *const kOutputBeginTime = "output_start_time";
  124. const char *const kOutputEndTime = "output_end_time";
  125. const char *const kStubFuncName = "_register_stub_func";
  126. const uint32_t kStringHeadElems = 2;
  127. const uint32_t kPlacementHostData = 0;
  128. const size_t kAlignment = 64;
  129. inline bool IsDataOp(const std::string &node_type) {
  130. return (node_type == DATA_TYPE) || (node_type == AIPP_DATA_TYPE) || (node_type == ANN_DATA_TYPE);
  131. }
  132. bool IsTbeTask(const OpDescPtr &op_desc) {
  133. uint32_t run_mode = static_cast<uint32_t>(domi::ImplyType::INVALID);
  134. if (!AttrUtils::GetInt(op_desc, ATTR_NAME_IMPLY_TYPE, run_mode)) {
  135. return false;
  136. }
  137. if (run_mode != static_cast<uint32_t>(domi::ImplyType::TVM)) {
  138. return false;
  139. }
  140. // Skip no_task operator, such as concat and split.
  141. bool attr_no_task = false;
  142. bool get_attr_no_task_flag = AttrUtils::GetBool(op_desc, ATTR_NAME_NOTASK, attr_no_task);
  143. if (get_attr_no_task_flag && attr_no_task) {
  144. GELOGI("Node[name:%s, type:%s] does not generate task, skip initialization.",
  145. op_desc->GetName().c_str(), op_desc->GetType().c_str());
  146. return false;
  147. }
  148. return true;
  149. }
  150. inline bool IsNoTaskAndDumpNeeded(const OpDescPtr &op_desc) {
  151. bool save_dump_info = false;
  152. (void)ge::AttrUtils::GetBool(op_desc, ATTR_NO_TASK_AND_DUMP_NEEDED, save_dump_info);
  153. return save_dump_info;
  154. }
  155. } // namespace
  156. std::mutex DavinciModel::tvm_bin_mutex_;
  157. DavinciModel::DavinciModel(int32_t priority, const std::shared_ptr<ModelListener> &listener)
  158. : weights_mem_base_(nullptr),
  159. var_mem_base_(nullptr),
  160. fixed_mem_base_(0),
  161. mem_base_(nullptr),
  162. is_inner_mem_base_(false),
  163. is_inner_weight_base_(false),
  164. data_inputer_(nullptr),
  165. load_begin_time_(0),
  166. load_end_time_(0),
  167. time_info_(),
  168. dataInputTid(0),
  169. is_weight_mem_has_inited_(false),
  170. is_feature_map_mem_has_inited_(false),
  171. model_id_(0),
  172. runtime_model_id_(0),
  173. version_(0),
  174. ge_model_(nullptr),
  175. listener_(listener),
  176. run_flg_(false),
  177. priority_(priority),
  178. rt_model_handle_(nullptr),
  179. rt_model_stream_(nullptr),
  180. is_inner_model_stream_(false),
  181. is_async_mode_(false),
  182. last_execute_mode_(INITIALIZATION),
  183. session_id_(0),
  184. device_id_(0),
  185. maxDumpOpNum_(0), data_dumper_(&runtime_param_),
  186. iterator_count_(0),
  187. is_l1_fusion_enable_(false),
  188. is_first_execute_(true) {
  189. op_list_.clear();
  190. skt_info_ = {0, 0, 0, 0, nullptr, nullptr, {}, {}, {}, {}, {}, RT_KERNEL_DEFAULT, -1, 0, nullptr};
  191. }
  192. DavinciModel::~DavinciModel() {
  193. try {
  194. GE_CHK_STATUS(ModelRunStop());
  195. Status ret = data_dumper_.UnloadDumpInfo();
  196. if (ret != SUCCESS) {
  197. GELOGW("UnloadDumpInfo failed, ret: %u.", ret);
  198. }
  199. ClearTaskAddrs();
  200. op_list_.clear();
  201. tensor_name_to_fixed_addr_size_.clear();
  202. tensor_name_to_peer_output_index_.clear();
  203. GE_DELETE_NEW_SINGLE(data_inputer_);
  204. // check rt ctx is exist. rt api call will cause error log when ctx not exist
  205. rtContext_t ctx = nullptr;
  206. rtError_t rt_ret = rtCtxGetCurrent(&ctx);
  207. if (rt_ret == RT_ERROR_NONE) {
  208. UnbindTaskSinkStream();
  209. for (size_t i = 0; i < label_list_.size(); ++i) {
  210. if (label_list_[i] != nullptr) {
  211. GE_LOGW_IF(rtLabelDestroy(label_list_[i]) != RT_ERROR_NONE, "Destroy label failed, index:%zu.", i);
  212. }
  213. }
  214. for (size_t i = 0; i < stream_list_.size(); ++i) {
  215. GE_LOGW_IF(rtStreamDestroy(stream_list_[i]) != RT_ERROR_NONE, "Destroy stream failed, index:%zu.", i);
  216. }
  217. for (size_t i = 0; i < event_list_.size(); ++i) {
  218. GE_LOGW_IF(rtEventDestroy(event_list_[i]) != RT_ERROR_NONE, "Destroy event failed, index: %zu", i);
  219. }
  220. FreeWeightsMem();
  221. FreeFeatureMapMem();
  222. FreeExMem();
  223. OpDebugUnRegister();
  224. if (l1_fusion_addr_ != nullptr) {
  225. GE_CHK_RT(rtFree(l1_fusion_addr_));
  226. }
  227. if (rt_model_handle_ != nullptr) {
  228. GE_CHK_RT(rtModelDestroy(rt_model_handle_));
  229. rt_model_handle_ = nullptr;
  230. }
  231. }
  232. ReleaseTask();
  233. CleanTbeHandle();
  234. var_mem_base_ = nullptr;
  235. if (known_node_) {
  236. if (args_ != nullptr) {
  237. GE_CHK_RT(rtFree(args_));
  238. }
  239. total_io_addrs_.clear();
  240. if (fixed_addrs_ != nullptr) {
  241. GE_CHK_RT(rtFree(fixed_addrs_));
  242. }
  243. }
  244. } catch (...) {
  245. GELOGW("DavinciModel::~DavinciModel: clear op_list catch exception.");
  246. }
  247. }
  248. void DavinciModel::ClearTaskAddrs() {
  249. for (const auto &op_and_addr : saved_task_addrs_) {
  250. auto addr = op_and_addr.second;
  251. if (addr != nullptr) {
  252. GE_CHK_RT(rtFree(addr));
  253. }
  254. addr = nullptr;
  255. }
  256. saved_task_addrs_.clear();
  257. }
  258. void DavinciModel::UnbindHcomStream() {
  259. if (!all_hccl_stream_list_.empty()) {
  260. for (size_t i = 0; i < all_hccl_stream_list_.size(); i++) {
  261. GE_LOGW_IF(rtModelUnbindStream(rt_model_handle_, all_hccl_stream_list_[i]) != RT_ERROR_NONE,
  262. "Unbind hccl stream from model failed, Index: %zu", i);
  263. GE_LOGW_IF(rtStreamDestroy(all_hccl_stream_list_[i]) != RT_ERROR_NONE, "Destroy hccl stream for rt_model failed")
  264. }
  265. }
  266. return;
  267. }
  268. void DavinciModel::ReleaseTask() {
  269. for (const auto &task : cpu_task_list_) {
  270. if (task != nullptr) {
  271. GE_CHK_STATUS(task->Release(), "[Release][Task] failed, model id:%u.", model_id_);
  272. }
  273. }
  274. cpu_task_list_.clear();
  275. for (const auto &task : task_list_) {
  276. if (task != nullptr) {
  277. GE_CHK_STATUS(task->Release(), "[Release][Task] failed, model id:%u.", model_id_);
  278. }
  279. }
  280. for (auto &item : label_goto_args_) {
  281. GE_FREE_RT_LOG(item.second.first);
  282. }
  283. label_goto_args_.clear();
  284. }
  285. Status DavinciModel::Assign(const GeModelPtr &ge_model) {
  286. if (ge_model == nullptr) {
  287. GELOGI("can't assign null ge_model");
  288. return FAILED;
  289. }
  290. ge_model_ = ge_model;
  291. return SUCCESS;
  292. }
  293. ///
  294. /// @ingroup ge
  295. /// @brief Reduce memory usage after task sink.
  296. /// @return: void
  297. ///
  298. void DavinciModel::Shrink() {
  299. skt_info_ = {0, 0, 0, 0, nullptr, nullptr, {}, {}, {}, {}, {}, RT_KERNEL_DEFAULT, -1, 0, nullptr};
  300. DumperShrink();
  301. ge_model_.reset(); // delete object.
  302. op_list_.clear();
  303. ClearTaskAddrs();
  304. }
  305. Status DavinciModel::InitWeightMem(void *dev_ptr, void *weight_ptr, size_t weight_size) {
  306. if (is_weight_mem_has_inited_) {
  307. REPORT_INNER_ERROR("E19999", "Call InitWeightMem more than once, model_id:%u, check invalid", model_id_);
  308. GELOGE(FAILED, "[Check][Param] call InitWeightMem more than once, model id:%u.", model_id_);
  309. return FAILED;
  310. }
  311. is_weight_mem_has_inited_ = true;
  312. const Buffer &weights = ge_model_->GetWeight();
  313. std::size_t weights_size = weights.GetSize();
  314. GE_CHECK_LE(weights_size, ALLOC_MEMORY_MAX_SIZE);
  315. if ((weight_ptr != nullptr) && (weight_size < weights_size)) {
  316. REPORT_INNER_ERROR("E19999", "Param weight_ptr is nullptr or ge_model.weight.size:%zu < param weights_size:%zu, "
  317. "model_id:%u, check invalid", weight_size, weights_size, model_id_);
  318. GELOGE(FAILED, "[Check][Param] Invalid mem param: weight_size=%zu totalsize=%zu, model_id:%u.",
  319. weight_size, weights_size, model_id_);
  320. return FAILED;
  321. }
  322. weights_mem_base_ = static_cast<uint8_t *>(dev_ptr);
  323. is_inner_weight_base_ = false;
  324. if (weights_size != 0) {
  325. weights_mem_base_ = static_cast<uint8_t *>(weight_ptr);
  326. is_inner_weight_base_ = false;
  327. if (weight_ptr == nullptr) {
  328. weights_mem_base_ = MallocWeightsMem(weights_size);
  329. if (weights_mem_base_ == nullptr) {
  330. REPORT_CALL_ERROR("E19999", "MallocWeightsMem fail, weights_size:%zu, model_id:%u, check invalid",
  331. weights_size, model_id_);
  332. GELOGE(ACL_ERROR_GE_MEMORY_ALLOCATION, "[Alloc][Memory] for weight failed. size:%zu, model_id:%u",
  333. weights_size, model_id_);
  334. return ACL_ERROR_GE_MEMORY_ALLOCATION;
  335. }
  336. is_inner_weight_base_ = true;
  337. }
  338. GELOGI("[IMAS]InitWeightMem graph_%u MallocMemory type[W] memaddr[%p] mem_size[%zu]", runtime_param_.graph_id,
  339. weights_mem_base_, weights_size);
  340. GE_CHK_RT_RET(rtMemcpy(weights_mem_base_, weights_size, weights.GetData(), weights_size, RT_MEMCPY_HOST_TO_DEVICE));
  341. GELOGI("copy weights data to device");
  342. }
  343. runtime_param_.weight_base = weights_mem_base_;
  344. return SUCCESS;
  345. }
  346. Status DavinciModel::InitFeatureMapAndP2PMem(void *dev_ptr, size_t mem_size) {
  347. if (is_feature_map_mem_has_inited_) {
  348. REPORT_INNER_ERROR("E19999", "Call InitFeatureMapMem more than once, model_id:%u, check invalid", model_id_);
  349. GELOGE(PARAM_INVALID, "[Check][Param] call InitFeatureMapMem more than once, model_id:%u", model_id_);
  350. return PARAM_INVALID;
  351. }
  352. is_feature_map_mem_has_inited_ = true;
  353. std::size_t data_size = TotalMemSize();
  354. if ((dev_ptr != nullptr) && (mem_size < TotalMemSize())) {
  355. REPORT_INNER_ERROR("E19999", "Param dev_ptr is nullptr or mem_size:%zu < ge_model.mem_size:%zu, "
  356. "model_id:%u, check invalid", mem_size, TotalMemSize(), model_id_);
  357. GELOGE(PARAM_INVALID, "[Check][Param] Invalid mem param: mem_size=%zu totalsize=%zu, model_id:%u.",
  358. mem_size, TotalMemSize(), model_id_);
  359. return PARAM_INVALID;
  360. }
  361. mem_base_ = static_cast<uint8_t *>(dev_ptr);
  362. is_inner_mem_base_ = false;
  363. if (TotalMemSize() && mem_base_ == nullptr) {
  364. mem_base_ = MallocFeatureMapMem(data_size);
  365. if (mem_base_ == nullptr) {
  366. REPORT_CALL_ERROR("E19999", "MallocFeatureMapMem fail, data_size:%zu, model_id:%u, check invalid",
  367. data_size, model_id_);
  368. GELOGE(ACL_ERROR_GE_MEMORY_ALLOCATION, "[Alloc][Memory] for feature map failed. size:%zu, model_id:%u",
  369. data_size, model_id_);
  370. return ACL_ERROR_GE_MEMORY_ALLOCATION;
  371. }
  372. GEEVENT("[IMAS]InitFeatureMapAndP2PMem graph_%u MallocMemory type[F] memaddr[%p] mem_size[%zu]",
  373. runtime_param_.graph_id, mem_base_, data_size);
  374. if (!is_inner_weight_base_) {
  375. weights_mem_base_ = mem_base_;
  376. is_inner_weight_base_ = true;
  377. }
  378. is_inner_mem_base_ = true;
  379. }
  380. if (!runtime_param_.memory_infos.empty()) {
  381. GE_CHK_STATUS_RET(MallocExMem(), "MallocExMem failed.");
  382. }
  383. GE_CHK_STATUS_RET(InitVariableMem(), "[Init][VariableMemory] failed, model_id:%u", model_id_);
  384. runtime_param_.mem_base = mem_base_;
  385. runtime_param_.weight_base = weights_mem_base_;
  386. return SUCCESS;
  387. }
  388. Status DavinciModel::InitVariableMem() {
  389. // malloc variable memory base
  390. var_mem_base_ = VarManager::Instance(session_id_)->GetVarMemoryBase(RT_MEMORY_HBM);
  391. if (TotalVarMemSize() && (var_mem_base_ == nullptr)) {
  392. Status ret = VarManager::Instance(session_id_)->MallocVarMemory(TotalVarMemSize());
  393. if (ret != SUCCESS) {
  394. REPORT_CALL_ERROR("E19999", "MallocVarMemory fail, var_size:%zu, model_id:%u, check invalid",
  395. TotalVarMemSize(), model_id_);
  396. GELOGE(ret, "[Malloc][VarMemory] failed, var_size:%zu, model_id:%u", TotalVarMemSize(), model_id_);
  397. return ret;
  398. }
  399. var_mem_base_ = VarManager::Instance(session_id_)->GetVarMemoryBase(RT_MEMORY_HBM);
  400. GEEVENT("[IMAS]InitVariableMem graph_%u MallocMemory type[V] memaddr[%p] mem_size[%zu]", runtime_param_.graph_id,
  401. var_mem_base_, TotalVarMemSize());
  402. }
  403. runtime_param_.var_base = var_mem_base_;
  404. return SUCCESS;
  405. }
  406. void DavinciModel::InitRuntimeParams() {
  407. int64_t value = 0;
  408. bool ret;
  409. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_MEMORY_SIZE, value);
  410. runtime_param_.mem_size = ret ? (uint64_t)value : 0;
  411. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_WEIGHT_SIZE, value);
  412. runtime_param_.weight_size = ret ? (uint64_t)value : 0;
  413. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_STREAM_NUM, value);
  414. runtime_param_.stream_num = ret ? (uint32_t)value : 0;
  415. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_EVENT_NUM, value);
  416. runtime_param_.event_num = ret ? (uint32_t)value : 0;
  417. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_LABEL_NUM, value);
  418. runtime_param_.label_num = ret ? (uint32_t)value : 0;
  419. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_BATCH_NUM, value);
  420. runtime_param_.batch_num = ret ? (uint32_t)value : 0;
  421. ret = ge::AttrUtils::GetInt(ge_model_, MODEL_ATTR_TASK_GEN_BASE_ADDR, value);
  422. runtime_param_.logic_mem_base = ret ? (uint64_t)value : 0;
  423. ret = ge::AttrUtils::GetInt(ge_model_, MODEL_ATTR_TASK_GEN_WEIGHT_ADDR, value);
  424. runtime_param_.logic_weight_base = ret ? (uint64_t)value : 0;
  425. ret = ge::AttrUtils::GetInt(ge_model_, ge::MODEL_ATTR_SESSION_ID, value);
  426. runtime_param_.session_id = ret ? (uint64_t)value : 0;
  427. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_TASK_GEN_VAR_ADDR, value);
  428. runtime_param_.logic_var_base = ret ? (uint64_t)value : 0;
  429. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_VAR_SIZE, value);
  430. runtime_param_.var_size = ret ? (uint64_t)value : 0;
  431. session_id_ = runtime_param_.session_id;
  432. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_P2P_MEMORY_SIZE, value);
  433. MemInfo p2p_mem_info;
  434. p2p_mem_info.memory_size = static_cast<size_t>(ret ? value : 0);
  435. p2p_mem_info.memory_type = RT_MEMORY_P2P_DDR;
  436. p2p_mem_info.memory_key = "_p";
  437. runtime_param_.memory_infos[RT_MEMORY_P2P_DDR] = std::move(p2p_mem_info);
  438. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_SESSION_SCOPE_MEMORY_SIZE, value);
  439. MemInfo session_scope_mem_info;
  440. session_scope_mem_info.memory_size = static_cast<size_t>(ret ? value : 0);
  441. runtime_param_.memory_infos[kSessionScopeMemory | RT_MEMORY_HBM] = std::move(session_scope_mem_info);
  442. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_ZERO_COPY_MEMORY_SIZE, value);
  443. runtime_param_.zero_copy_size = ret ? value : 0;
  444. GELOGI("InitRuntimeParams(), %s.", runtime_param_.ToString().c_str());
  445. }
  446. void DavinciModel::CheckHasHcomOp(const ComputeGraphPtr &compute_graph) {
  447. const set<string> hcom_opp_types({
  448. HCOMBROADCAST, HCOMALLGATHER, HCOMALLREDUCE, HCOMSEND, HCOMRECEIVE, HCOMREDUCESCATTER,
  449. HVDCALLBACKALLREDUCE, HVDCALLBACKALLGATHER, HVDCALLBACKBROADCAST, HVDWAIT, HCOMREDUCE
  450. });
  451. for (const auto &node : compute_graph->GetAllNodes()) {
  452. OpDescPtr op_desc = node->GetOpDesc();
  453. GE_IF_BOOL_EXEC(op_desc == nullptr, GELOGW("Node OpDesc is nullptr."); continue);
  454. if (hcom_opp_types.count(op_desc->GetType()) > 0) {
  455. uint32_t stream_id = static_cast<uint32_t>(op_desc->GetStreamId());
  456. hcom_streams_.emplace(stream_id);
  457. GELOGD("hcom stream: %u.", stream_id);
  458. }
  459. }
  460. }
  461. ///
  462. /// @ingroup ge
  463. /// @brief Make active stream list and bind to model.
  464. /// @return: 0 for success / others for fail
  465. ///
  466. Status DavinciModel::BindModelStream() {
  467. // Stream not in active_stream_indication_ is active stream.
  468. is_stream_list_bind_ = false;
  469. if ((!input_queue_ids_.empty() || !output_queue_ids_.empty()) || (deploy_type_ == AICPU_DEPLOY_CROSS_THREAD)) {
  470. for (size_t i = 0; i < stream_list_.size(); ++i) {
  471. if (active_stream_indication_.count(i) == 0) {
  472. active_stream_list_.push_back(stream_list_[i]);
  473. active_stream_indication_.insert(i); // deactive all model stream.
  474. }
  475. }
  476. }
  477. for (size_t i = 0; i < stream_list_.size(); ++i) {
  478. if (active_stream_indication_.count(i) > 0) {
  479. GELOGI("rtModelBindStream[%zu]", i);
  480. GE_CHK_RT_RET(rtModelBindStream(rt_model_handle_, stream_list_[i], RT_INVALID_FLAG));
  481. } else {
  482. // bind rt_model_handel to all streams that relates to op
  483. GE_CHK_RT_RET(rtModelBindStream(rt_model_handle_, stream_list_[i], RT_HEAD_STREAM));
  484. }
  485. }
  486. is_stream_list_bind_ = true;
  487. return SUCCESS;
  488. }
  489. Status DavinciModel::DoTaskSink() {
  490. // task sink is supported as model_task_def is set
  491. const auto &model_task_def = ge_model_->GetModelTaskDefPtr();
  492. if (model_task_def == nullptr) {
  493. return SUCCESS;
  494. }
  495. GE_CHK_RT_RET(rtGetAicpuDeploy(&deploy_type_));
  496. GELOGI("Do task sink. AiCpu deploy type is: %x.", deploy_type_);
  497. GE_CHK_STATUS_RET(BindModelStream(), "[Bind][ModelStream] failed, model_id:%u.", model_id_);
  498. if (known_node_) {
  499. GE_CHK_STATUS_RET(MallocKnownArgs(), "[Malloc][KnownArgs] failed, model_id:%u.", model_id_);
  500. }
  501. GE_CHK_STATUS_RET(InitTaskInfo(*model_task_def.get()), "[Init][TaskInfo] failed, model_id:%u.", model_id_);
  502. GE_CHK_STATUS_RET(ModelManager::GetInstance()->LaunchCustAicpuSo(),
  503. "[Launch][CustAicpuSo] failed, model_id:%u.", model_id_);
  504. GE_CHK_STATUS_RET(ModelManager::GetInstance()->CheckAicpuOpList(ge_model_),
  505. "[Check][AicpuOpList] failed, model_id:%u.", model_id_);
  506. GE_CHK_STATUS_RET(InitEntryTask(), "[Init][EntryTask] failed, model_id:%u.", model_id_);
  507. GE_CHK_STATUS_RET(InitL1DataDumperArgs(), "[Init][L1DataDumperArgs] failed, model_id:%u.", model_id_);
  508. GE_CHK_STATUS_RET(DistributeTask(), "[Distribute][Task] failed, model_id:%u.", model_id_);
  509. GE_CHK_RT_RET(rtModelLoadComplete(rt_model_handle_));
  510. SetCopyOnlyOutput();
  511. return SUCCESS;
  512. }
  513. // set device use aicore(0) or vectorcore(1)
  514. Status DavinciModel::SetTSDevice() {
  515. int64_t value = 0;
  516. bool ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_CORE_TYPE, value);
  517. uint32_t core_type = ret ? static_cast<uint32_t>(value) : 0;
  518. GELOGD("Set TSDevice: %u.", core_type);
  519. rtError_t rt_ret = rtSetTSDevice(core_type);
  520. if (rt_ret != RT_ERROR_NONE) {
  521. REPORT_CALL_ERROR("E19999", "Call rtSetTSDevice failed, core_type:%u, model_id:%u", core_type, model_id_);
  522. GELOGE(RT_FAILED, "[Set][TSDevice] failed, core_type:%u, model_id:%u, ret: 0x%X", core_type, model_id_, rt_ret);
  523. return RT_ERROR_TO_GE_STATUS(rt_ret);
  524. }
  525. return SUCCESS;
  526. }
  527. Status DavinciModel::OpDebugRegister() {
  528. if (GetDumpProperties().IsOpDebugOpen()) {
  529. uint32_t op_debug_mode = GetDumpProperties().GetOpDebugMode();
  530. auto ret = opdebug_register_.RegisterDebugForModel(rt_model_handle_, op_debug_mode, data_dumper_);
  531. if (ret != SUCCESS) {
  532. GELOGE(ret,"[Call][RegisterDebugForModel] Register known shape op debug failed, ret: 0x%X", ret);
  533. return ret;
  534. }
  535. is_op_debug_reg_ = true;
  536. }
  537. return SUCCESS;
  538. }
  539. void DavinciModel::OpDebugUnRegister() {
  540. if (is_op_debug_reg_) {
  541. opdebug_register_.UnregisterDebugForModel(rt_model_handle_);
  542. is_op_debug_reg_ = false;
  543. }
  544. return;
  545. }
  546. // initialize op sequence and call initialization function of each op respectively
  547. Status DavinciModel::Init(void *dev_ptr, size_t mem_size, void *weight_ptr, size_t weight_size) {
  548. // validating params
  549. GELOGI("Priority is %d.", priority_);
  550. GE_CHK_BOOL_TRUE_EXEC_WITH_LOG(priority_ < 0 || priority_ > 7, return PARAM_INVALID,
  551. "[Check][Param] Priority must between 0-7, now is %d.", priority_);
  552. GE_CHK_BOOL_RET_STATUS(ge_model_ != nullptr, PARAM_INVALID, "[Check][Param] GeModel is null.");
  553. Graph graph = ge_model_->GetGraph();
  554. ComputeGraphPtr compute_graph = GraphUtils::GetComputeGraph(graph);
  555. GE_CHK_BOOL_RET_STATUS(compute_graph != nullptr, INTERNAL_ERROR, "[Get][ComputeGraph] failed, ret is nullptr.");
  556. // Initializing runtime_param_
  557. InitRuntimeParams();
  558. // RTS set aicore or vectorcore
  559. GE_CHK_STATUS_RET(SetTSDevice(), "[Set][TSDevice] failed, graph:%s.", compute_graph->GetName().c_str());
  560. version_ = ge_model_->GetVersion();
  561. name_ = ge_model_->GetName();
  562. (void)ge::AttrUtils::GetBool(ge_model_, ATTR_NAME_SWITCH_FOR_L1_FUSION, is_l1_fusion_enable_);
  563. GELOGD("The value of ge.l1Fusion in ge_model is %d.", is_l1_fusion_enable_);
  564. CheckHasHcomOp(compute_graph);
  565. vector<int64_t> huge_stream_list;
  566. (void)ge::AttrUtils::GetListInt(ge_model_, ATTR_MODEL_HUGE_STREAM_LIST, huge_stream_list);
  567. std::set<int64_t> huge_streams(huge_stream_list.begin(), huge_stream_list.end());
  568. for (uint32_t i = 0; i < StreamNum(); i++) {
  569. rtStream_t stream = nullptr;
  570. GE_MAKE_GUARD_RTSTREAM(stream);
  571. uint32_t stream_flags = RT_STREAM_PERSISTENT;
  572. if (huge_streams.find(i) != huge_streams.end()) {
  573. GELOGI("Stream %u is huge stream.", i);
  574. stream_flags |= RT_STREAM_HUGE;
  575. }
  576. if (hcom_streams_.find(i) != hcom_streams_.end()) {
  577. GE_CHK_RT_RET(rtStreamCreateWithFlags(&stream, priority_, stream_flags | RT_STREAM_FORCE_COPY));
  578. } else {
  579. GE_CHK_RT_RET(rtStreamCreateWithFlags(&stream, priority_, stream_flags));
  580. }
  581. GE_DISMISS_GUARD(stream);
  582. stream_list_.push_back(stream);
  583. int32_t rt_stream_id = kInvalidStream;
  584. (void)rtGetStreamId(stream, &rt_stream_id);
  585. GELOGI("Logical stream index:%u, stream:%p, rtstream: %d.", i, stream, rt_stream_id);
  586. }
  587. uint32_t event_num = EventNum();
  588. uint32_t create_flag = static_cast<uint32_t>((event_num > kEventReuseThreshold) ? RT_EVENT_WITH_FLAG :
  589. RT_EVENT_DEFAULT);
  590. for (uint32_t i = 0; i < event_num; ++i) {
  591. rtEvent_t rt_event = nullptr;
  592. GE_CHK_RT_RET(rtEventCreateWithFlag(&rt_event, create_flag));
  593. event_list_.push_back(rt_event);
  594. }
  595. label_list_.resize(LabelNum(), nullptr);
  596. // create model_handle to load model
  597. GE_CHK_RT_RET(rtModelCreate(&rt_model_handle_, 0));
  598. GE_CHK_RT_RET(rtModelGetId(rt_model_handle_, &runtime_model_id_));
  599. // inference will use default graph_id 0;
  600. runtime_param_.graph_id = compute_graph->GetGraphID();
  601. // op debug register
  602. GE_CHK_STATUS_RET(OpDebugRegister(), "[Call][OpDebugRegister] failed, model_id:%u.", model_id_);
  603. GE_TIMESTAMP_START(TransAllVarData);
  604. GE_CHK_STATUS_RET(TransAllVarData(compute_graph, runtime_param_.graph_id),
  605. "[Call][TransAllVarData] failed, graph:%s, graph_id:%u.",
  606. compute_graph->GetName().c_str(), runtime_param_.graph_id);
  607. GE_TIMESTAMP_END(TransAllVarData, "GraphLoader::TransAllVarData");
  608. GE_CHK_STATUS_RET(TransVarDataUtils::CopyVarData(compute_graph, session_id_, device_id_),
  609. "[Copy][VarData] failed, graph:%s, session_id:%lu, device_id:%u",
  610. compute_graph->GetName().c_str(), session_id_, device_id_);
  611. GE_TIMESTAMP_START(InitModelMem);
  612. GELOGD("Known node is %d.", known_node_);
  613. GE_CHK_STATUS_RET_NOLOG(InitWeightMem(dev_ptr, weight_ptr, weight_size));
  614. if (!known_node_) {
  615. GE_CHK_STATUS_RET_NOLOG(InitFeatureMapAndP2PMem(dev_ptr, mem_size));
  616. data_inputer_ = new (std::nothrow) DataInputer();
  617. GE_CHK_BOOL_RET_STATUS(data_inputer_ != nullptr, MEMALLOC_FAILED,
  618. "[Create][DataInputer] data_inputer_ is nullptr");
  619. }
  620. fixed_mem_base_ = reinterpret_cast<uintptr_t>(mem_base_);
  621. GE_TIMESTAMP_END(InitModelMem, "GraphLoader::InitModelMem");
  622. for (const ge::NodePtr &node : compute_graph->GetDirectNode()) {
  623. auto op_desc = node->GetOpDesc();
  624. GE_IF_BOOL_EXEC(op_desc == nullptr, continue);
  625. GE_IF_BOOL_EXEC(op_desc->GetType() != VARIABLE, continue);
  626. GE_IF_BOOL_EXEC(IsBroadCastOpData(node),
  627. (void)ge::AttrUtils::SetStr(op_desc, VAR_ATTR_VAR_IS_BROADCAST, "var_is_restore"););
  628. }
  629. GE_CHK_STATUS_RET(InitNodes(compute_graph), "[Init][Nodes] failed, graph:%s.", compute_graph->GetName().c_str());
  630. GE_TIMESTAMP_START(DoTaskSink);
  631. GE_CHK_STATUS_RET(DoTaskSink(), "[Call][DoTaskSink] failed, model_id:%u.", model_id_);
  632. GE_TIMESTAMP_END(DoTaskSink, "GraphLoader::DoTaskSink");
  633. /// In zero copy model, if a aicpu operator is connected to the first or last layer, before model execution,
  634. /// the aicpu opertor needs to destroy history record, and update operator memory address.
  635. /// The model with specified aicpu operators is only marked here, and destruction is in ModelManager::ExecuteModel().
  636. need_destroy_aicpu_kernel_ = IsAicpuKernelConnectSpecifiedLayer();
  637. string fp_ceiling_mode;
  638. if (ge::AttrUtils::GetStr(ge_model_, ATTR_FP_CEILING_MODE, fp_ceiling_mode)) {
  639. GELOGI("Get attr ATTR_FP_CEILING_MODE from model, value is %s.", fp_ceiling_mode.c_str());
  640. // mode 0: Do not perform saturation processing. By default, IEEE754 is used.
  641. GE_CHK_RT_RET(rtSetCtxINFMode((fp_ceiling_mode != "0")));
  642. }
  643. SetProfileTime(MODEL_LOAD_END);
  644. // collect profiling for ge
  645. auto &profiling_manager = ProfilingManager::Instance();
  646. if (profiling_manager.ProfilingModelLoadOn()) {
  647. GE_CHK_STATUS_RET(InitModelProfile(), "[Init][ModelProfile] failed, model_id:%u.", model_id_);
  648. Status p_ret = ReportProfilingData();
  649. if (p_ret != SUCCESS) {
  650. GELOGE(p_ret, "[Report][ProfilingData] failed, ret:%d, model_id:%u.", p_ret, model_id_);
  651. return p_ret;
  652. }
  653. }
  654. Shrink();
  655. return SUCCESS;
  656. }
  657. // save specify attr values of op, such as ATTR_NAME_DATA_DUMP_ORIGIN_OP_NAMES
  658. // it will save more attr values in the future
  659. void DavinciModel::SaveSpecifyAttrValues(const OpDescPtr &op_desc) {
  660. std::vector<std::string> value;
  661. if (AttrUtils::GetListStr(op_desc, ATTR_NAME_DATA_DUMP_ORIGIN_OP_NAMES, value)) {
  662. std::map<std::string, std::vector<std::string>> attr_name_to_value;
  663. attr_name_to_value[ATTR_NAME_DATA_DUMP_ORIGIN_OP_NAMES]= value;
  664. op_name_to_attrs_[op_desc->GetName()] = attr_name_to_value;
  665. GELOGD("Get op:%s attr:%s success.", op_desc->GetName().c_str(), ATTR_NAME_DATA_DUMP_ORIGIN_OP_NAMES.c_str());
  666. }
  667. return;
  668. }
  669. Status DavinciModel::ReportProfilingData() {
  670. ProfilingManager::Instance().ReportProfilingData(model_id_, GetTaskDescInfo());
  671. GE_CHK_STATUS(SinkModelProfile(), "[Sink][ModelProfile] failed, model_id:%u.", model_id_);
  672. return SUCCESS;
  673. }
  674. ///
  675. /// @ingroup ge
  676. /// @brief Travel all nodes and determine if destruction is required.
  677. /// @return bool
  678. ///
  679. bool DavinciModel::IsAicpuKernelConnectSpecifiedLayer() {
  680. Graph graph = ge_model_->GetGraph();
  681. ComputeGraphPtr compute_graph = GraphUtils::GetComputeGraph(graph);
  682. auto all_nodes = compute_graph->GetAllNodes();
  683. for (auto &node : all_nodes) {
  684. GE_IF_BOOL_EXEC(node == nullptr, continue);
  685. OpDescPtr op_desc = node->GetOpDesc();
  686. GE_IF_BOOL_EXEC(op_desc == nullptr, continue);
  687. int64_t imply_type = -1;
  688. (void)ge::AttrUtils::GetInt(op_desc, ATTR_NAME_IMPLY_TYPE, imply_type);
  689. if (imply_type != static_cast<int64_t>(domi::ImplyType::AI_CPU)) {
  690. continue;
  691. }
  692. GELOGD("Current operator imply type is %ld, name is %s.", imply_type, op_desc->GetName().c_str());
  693. for (auto &in_data_anchor : node->GetAllInDataAnchors()) {
  694. GE_IF_BOOL_EXEC(in_data_anchor == nullptr, continue);
  695. auto peer_out_data_anchor = in_data_anchor->GetPeerOutAnchor();
  696. GE_IF_BOOL_EXEC(peer_out_data_anchor == nullptr, continue);
  697. auto peer_node = peer_out_data_anchor->GetOwnerNode();
  698. GE_IF_BOOL_EXEC(peer_node == nullptr, continue);
  699. auto peer_op_desc = peer_node->GetOpDesc();
  700. GE_IF_BOOL_EXEC(peer_op_desc == nullptr, continue);
  701. if (IsDataOp(peer_op_desc->GetType())) {
  702. GELOGI("Mark specified aicpu operator connected to data.");
  703. return true;
  704. }
  705. }
  706. for (auto &out_data_anchor : node->GetAllOutDataAnchors()) {
  707. GE_IF_BOOL_EXEC(out_data_anchor == nullptr, continue);
  708. auto peer_in_data_anchors = out_data_anchor->GetPeerInDataAnchors();
  709. for (auto &peer_in_data_anchor : peer_in_data_anchors) {
  710. GE_IF_BOOL_EXEC(peer_in_data_anchor == nullptr, continue);
  711. auto peer_node = peer_in_data_anchor->GetOwnerNode();
  712. GE_IF_BOOL_EXEC(peer_node == nullptr, continue);
  713. auto peer_op_desc = peer_node->GetOpDesc();
  714. GE_IF_BOOL_EXEC(peer_op_desc == nullptr, continue);
  715. if (peer_op_desc->GetType() == NETOUTPUT) {
  716. GELOGI("Mark specified aicpu operator connected to netoutput.");
  717. return true;
  718. }
  719. }
  720. }
  721. }
  722. return false;
  723. }
  724. Status DavinciModel::UpdateSessionId(uint64_t session_id) {
  725. GE_CHECK_NOTNULL(ge_model_);
  726. if (!AttrUtils::SetInt(ge_model_, MODEL_ATTR_SESSION_ID, static_cast<int64_t>(session_id))) {
  727. GELOGW("Set attr[%s] failed in updating session_id.", MODEL_ATTR_SESSION_ID.c_str());
  728. }
  729. GELOGD("Update session id: %lu.", session_id);
  730. return SUCCESS;
  731. }
  732. ///
  733. /// @ingroup ge
  734. /// @brief Travel all nodes and do some init.
  735. /// @param [in] compute_graph: ComputeGraph to load.
  736. /// @return Status
  737. ///
  738. Status DavinciModel::InitNodes(const ComputeGraphPtr &compute_graph) {
  739. uint32_t data_op_index = 0;
  740. GE_TIMESTAMP_CALLNUM_START(LoadTBEKernelBinToOpDesc);
  741. GE_TIMESTAMP_CALLNUM_START(InitTbeHandle);
  742. typedef Status (DavinciModel::*OpDescCall)(const OpDescPtr &);
  743. static std::map<std::string, OpDescCall> op_desc_handle = {
  744. {CONSTANTOP, &DavinciModel::InitConstant},
  745. {STREAMACTIVE, &DavinciModel::InitStreamActive},
  746. {STREAMSWITCH, &DavinciModel::InitStreamSwitch},
  747. {STREAMSWITCHN, &DavinciModel::InitStreamSwitchN},
  748. {LABELSET, &DavinciModel::InitLabelSet},
  749. {CASE, &DavinciModel::InitCase},
  750. };
  751. vector<OpDescPtr> output_op_list;
  752. set<const void *> input_outside_addrs;
  753. set<const void *> output_outside_addrs;
  754. map<uint32_t, OpDescPtr> data_by_index;
  755. map<string, OpDescPtr> variable_by_name;
  756. auto nodes = compute_graph->GetAllNodes();
  757. const CustAICPUKernelStore &aicpu_kernel_store = ge_model_->GetCustAICPUKernelStore();
  758. for (size_t i = 0; i < nodes.size(); ++i) {
  759. const auto &node = nodes.at(i);
  760. const auto &op_desc = node->GetOpDesc();
  761. GE_CHECK_NOTNULL(op_desc);
  762. SaveSpecifyAttrValues(op_desc);
  763. op_list_[op_desc->GetId()] = op_desc;
  764. GE_TIMESTAMP_RESTART(LoadTBEKernelBinToOpDesc);
  765. aicpu_kernel_store.LoadCustAICPUKernelBinToOpDesc(op_desc);
  766. GE_TIMESTAMP_ADD(LoadTBEKernelBinToOpDesc);
  767. if (IsDataOp(op_desc->GetType())) {
  768. if (InitDataOp(compute_graph, node, data_op_index, data_by_index, input_outside_addrs) != SUCCESS) {
  769. GELOGE(PARAM_INVALID, "[Init][DataOp] failed, Name:%s", op_desc->GetName().c_str());
  770. return PARAM_INVALID;
  771. }
  772. data_dumper_.SaveDumpInput(node);
  773. continue;
  774. }
  775. if (op_desc->GetType() == NETOUTPUT) {
  776. if (InitNetOutput(compute_graph, node, output_op_list, output_outside_addrs) != SUCCESS) {
  777. GELOGE(PARAM_INVALID, "[Init][NetOutput] failed, Name:%s", op_desc->GetName().c_str());
  778. return PARAM_INVALID;
  779. }
  780. if (InitRealSizeAndShapeInfo(compute_graph, node) != SUCCESS) {
  781. GELOGE(PARAM_INVALID, "[Init][RealSizeAndShapeInfo] failed, Name:%s", op_desc->GetName().c_str());
  782. return PARAM_INVALID;
  783. }
  784. continue;
  785. }
  786. if (op_desc->GetType() == VARIABLE) {
  787. if (InitVariable(op_desc, variable_by_name) != SUCCESS) {
  788. GELOGE(PARAM_INVALID, "[Init][Variable] failed, Name:%s", op_desc->GetName().c_str());
  789. return PARAM_INVALID;
  790. }
  791. continue;
  792. }
  793. // for dynamic shape with control flow
  794. SetLabelForDynamic(node);
  795. auto it = op_desc_handle.find(op_desc->GetType());
  796. if (it != op_desc_handle.end()) {
  797. GE_CHK_BOOL_TRUE_EXEC_WITH_LOG((this->*it->second)(op_desc) != SUCCESS, return PARAM_INVALID,
  798. "[Init][Node] failed, Name:%s", op_desc->GetName().c_str());
  799. continue;
  800. }
  801. if (IsNoTaskAndDumpNeeded(op_desc)) {
  802. GELOGD("node[%s] without task, and save op_desc and addr for dump", op_desc->GetName().c_str());
  803. const RuntimeParam &rts_param = GetRuntimeParam();
  804. const vector<void *> input_data_addrs = ModelUtils::GetInputDataAddrs(rts_param, op_desc);
  805. const vector<void *> output_data_addrs = ModelUtils::GetOutputDataAddrs(rts_param, op_desc);
  806. const vector<void *> workspace_data_addrs = ModelUtils::GetWorkspaceDataAddrs(rts_param, op_desc);
  807. vector<void *> tensor_device_addrs;
  808. tensor_device_addrs.insert(tensor_device_addrs.end(), input_data_addrs.begin(), input_data_addrs.end());
  809. tensor_device_addrs.insert(tensor_device_addrs.end(), output_data_addrs.begin(), output_data_addrs.end());
  810. tensor_device_addrs.insert(tensor_device_addrs.end(), workspace_data_addrs.begin(), workspace_data_addrs.end());
  811. void *addr = nullptr;
  812. auto size = kAddrLen * tensor_device_addrs.size();
  813. GE_CHK_RT_RET(rtMalloc(&addr, size, RT_MEMORY_HBM));
  814. rtError_t rt_ret = rtMemcpy(addr, size, tensor_device_addrs.data(), size, RT_MEMCPY_HOST_TO_DEVICE);
  815. if (rt_ret != RT_ERROR_NONE) {
  816. REPORT_CALL_ERROR("E19999", "Call rtMemcpy failed, size:%zu, ret:0x%X", size, rt_ret);
  817. GELOGE(RT_FAILED, "[Call][RtMemcpy] failed, size:%zu, ret:0x%X", size, rt_ret);
  818. GE_CHK_RT(rtFree(addr));
  819. return RT_ERROR_TO_GE_STATUS(rt_ret);
  820. }
  821. saved_task_addrs_.emplace(op_desc, addr);
  822. }
  823. GE_TIMESTAMP_RESTART(InitTbeHandle);
  824. if (IsTbeTask(op_desc)) {
  825. Status status =
  826. op_desc->HasAttr(ATTR_NAME_THREAD_SCOPE_ID) ? InitTbeHandleWithFfts(op_desc) : InitTbeHandle(op_desc);
  827. if (status != SUCCESS) {
  828. GELOGE(status, "[Init][TbeHandle] failed. op:%s", op_desc->GetName().c_str());
  829. return status;
  830. }
  831. }
  832. GE_TIMESTAMP_ADD(InitTbeHandle);
  833. }
  834. SetDataDumperArgs(compute_graph, variable_by_name);
  835. GE_TIMESTAMP_CALLNUM_END(LoadTBEKernelBinToOpDesc, "GraphLoader::LoadTBEKernelBinToOpDesc.");
  836. GE_TIMESTAMP_CALLNUM_END(InitTbeHandle, "GraphLoader::InitTbeHandle.");
  837. return GenInputOutputInfo(data_by_index, output_op_list);
  838. }
  839. void DavinciModel::SetLabelForDynamic(const NodePtr &node) {
  840. if (known_node_ && (node->GetType() == LABELSWITCHBYINDEX || node->GetType() == STREAMSWITCH)) {
  841. for (auto &in_data_anchor : node->GetAllInDataAnchors()) {
  842. auto peer_out_data_anchor = in_data_anchor->GetPeerOutAnchor();
  843. if (peer_out_data_anchor != nullptr) {
  844. // name+index as the label of switch input
  845. string tensor_name = node->GetName() + std::to_string(in_data_anchor->GetIdx());
  846. auto peer_node = peer_out_data_anchor->GetOwnerNode();
  847. (void)AttrUtils::SetStr(peer_node->GetOpDesc(), ATTR_DYNAMIC_SHAPE_FIXED_ADDR, tensor_name);
  848. (void)AttrUtils::SetInt(peer_node->GetOpDesc(), ATTR_DYNAMIC_SHAPE_FIXED_ADDR_INDEX, 0);
  849. tensor_name_to_peer_output_index_[tensor_name] = 0;
  850. }
  851. }
  852. }
  853. }
  854. ///
  855. /// @ingroup ge
  856. /// @brief Data Op Initialize.
  857. /// @param [in] ComputeGraphPtr: root graph of the model.
  858. /// @param [in] NodePtr: Data Op.
  859. /// @param [in/out] data_op_index: index of courrent count.
  860. /// @param [in/out] data_by_index: Data ordered by index.
  861. /// @return Status
  862. ///
  863. Status DavinciModel::InitDataOp(const ComputeGraphPtr &graph, const NodePtr &node, uint32_t &data_op_index,
  864. map<uint32_t, OpDescPtr> &data_by_index, set<const void *> &input_outside_addrs) {
  865. // op_desc Checked by Init: Data, valid.
  866. auto op_desc = node->GetOpDesc();
  867. if (node->GetOwnerComputeGraph() != graph) {
  868. GELOGI("Skip subgraph Data node: %s.", op_desc->GetName().c_str());
  869. return SUCCESS;
  870. }
  871. auto data_index = data_op_index++;
  872. const auto &index_attr = GraphUtils::FindRootGraph(graph) == graph ? ATTR_NAME_INDEX : ATTR_NAME_PARENT_NODE_INDEX;
  873. if (AttrUtils::GetInt(op_desc, index_attr, data_index)) {
  874. GELOGD("Get new index %u, old %u", data_index, data_op_index - 1);
  875. }
  876. GELOGI("Init data node: %s, index: %u.", op_desc->GetName().c_str(), data_index);
  877. data_by_index[data_index] = op_desc;
  878. if (known_node_) {
  879. return SUCCESS;
  880. }
  881. // Make information for copy input data.
  882. const vector<int64_t> output_size_list = ModelUtils::GetOutputSize(op_desc);
  883. const vector<void *> virtual_addr_list = ModelUtils::GetOutputDataAddrs(runtime_param_, op_desc);
  884. const vector<int64_t> output_offset_list = op_desc->GetOutputOffset();
  885. if (output_size_list.empty() || virtual_addr_list.empty() || (output_size_list.size() != virtual_addr_list.size()) ||
  886. (output_offset_list.size() != virtual_addr_list.size())) {
  887. REPORT_INNER_ERROR(
  888. "E19999", "Check data fail in op:%s(%s), output_desc size:%zu output addr size:%zu output offset size:%zu "
  889. "not equal or has empty, model_id:%u",
  890. op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  891. output_size_list.size(), virtual_addr_list.size(), output_offset_list.size(), model_id_);
  892. GELOGE(PARAM_INVALID, "[Check][Param] Data[%s] init failed: output size is %zu, "
  893. "virtual_addr size is %zu, offset size is %zu.", op_desc->GetName().c_str(), output_size_list.size(),
  894. virtual_addr_list.size(), output_offset_list.size());
  895. return PARAM_INVALID;
  896. }
  897. bool fusion_flag = false;
  898. ZeroCopyOffset zero_copy_offset;
  899. int64_t data_size = output_size_list[kDataIndex];
  900. void *virtual_addr = virtual_addr_list[kDataIndex];
  901. Status ret = zero_copy_offset.InitInputDataInfo(data_size, virtual_addr, op_desc, fusion_flag);
  902. if (ret != SUCCESS) {
  903. GELOGE(PARAM_INVALID, "[Init][DataInfo] of input_info %s failed.", op_desc->GetName().c_str());
  904. return PARAM_INVALID;
  905. }
  906. if (input_outside_addrs.count(virtual_addr) == 0) {
  907. int64_t output_offset = output_offset_list.at(kDataIndex);
  908. zero_copy_offset.SetInputOutsideAddrs(output_offset, virtual_addr, fusion_flag, real_virtual_addrs_);
  909. input_outside_addrs.insert(virtual_addr);
  910. }
  911. input_data_info_[data_index] = zero_copy_offset;
  912. return SUCCESS;
  913. }
  914. ///
  915. /// @ingroup ge
  916. /// @brief Sort Data op list by index.
  917. /// @param [in] data_by_index: map of Data Op.
  918. /// @param [in] output_op_list: list of NetOutput op.
  919. /// @return Status
  920. ///
  921. Status DavinciModel::GenInputOutputInfo(const map<uint32_t, OpDescPtr> &data_by_index,
  922. const vector<OpDescPtr> &output_op_list) {
  923. GELOGD("Data node size: %zu, NetOutput node size: %zu", data_by_index.size(), output_op_list.size());
  924. for (auto &item : data_by_index) {
  925. const auto output_addrs = ModelUtils::GetOutputDataAddrs(runtime_param_, item.second);
  926. GELOGD("Data node is: %s, output addr size: %zu", item.second->GetName().c_str(), output_addrs.size());
  927. input_addrs_list_.emplace_back(output_addrs);
  928. GE_CHK_STATUS_RET(InitAippInfo(item.first, item.second),
  929. "[Init][AippInfo] failed, node:%s", item.second->GetName().c_str());
  930. GE_CHK_STATUS_RET(InitAippType(item.first, item.second, data_by_index),
  931. "[Init][AippType] failed, node:%s", item.second->GetName().c_str());
  932. GE_CHK_STATUS_RET(InitOrigInputInfo(item.first, item.second),
  933. "[Init][OrigInputInfo] failed, node:%s", item.second->GetName().c_str());
  934. GE_CHK_STATUS_RET(InitAippInputOutputDims(item.first, item.second),
  935. "[Init][AippInputOutputDims] failed, node:%s", item.second->GetName().c_str());
  936. GE_CHK_STATUS_RET(InitInputDescInfo(item.second),
  937. "[Init][InputDescInfo] failed, node:%s", item.second->GetName().c_str());
  938. if (item.second->GetType() == AIPP_DATA_TYPE) {
  939. GELOGI("This is dynamic aipp model, Node: %s", item.second->GetName().c_str());
  940. is_dynamic_aipp_ = true;
  941. }
  942. }
  943. vector<string> out_node_name;
  944. (void)AttrUtils::GetListStr(ge_model_, ATTR_MODEL_OUT_NODES_NAME, out_node_name);
  945. GELOGD("Output node size: %zu, out nodes name is: %zu", output_op_list.size(), out_node_name.size());
  946. for (const auto &op_desc : output_op_list) {
  947. const auto input_addrs = ModelUtils::GetInputDataAddrs(runtime_param_, op_desc);
  948. GELOGD("NetOutput node is: %s, input addr size: %zu", op_desc->GetName().c_str(), input_addrs.size());
  949. output_addrs_list_.emplace_back(input_addrs);
  950. bool getnext_sink_dynamic = false;
  951. if (AttrUtils::GetBool(op_desc, ATTR_GETNEXT_SINK_DYNMAIC, getnext_sink_dynamic) && getnext_sink_dynamic) {
  952. GELOGI("ATTR_GETNEXT_SINK_DYNMAIC has been set and is true, node: %s", op_desc->GetName().c_str());
  953. is_getnext_sink_dynamic_ = true;
  954. }
  955. vector<string> shape_info;
  956. if (AttrUtils::GetListStr(op_desc, ATTR_NAME_DYNAMIC_OUTPUT_DIMS, shape_info)) {
  957. dynamic_output_shape_info_.insert(dynamic_output_shape_info_.end(), shape_info.begin(), shape_info.end());
  958. }
  959. if (InitOutputTensorInfo(op_desc) != SUCCESS) {
  960. return INTERNAL_ERROR;
  961. }
  962. GE_CHK_STATUS_RET(InitOutputDescInfo(op_desc, out_node_name),
  963. "[Init][OutputDescInfo] failed, node:%s", op_desc->GetName().c_str());
  964. }
  965. return SUCCESS;
  966. }
  967. bool DavinciModel::IsGetNextSinkDynamic(const OpDescPtr &op_desc) {
  968. bool getnext_sink_dynamic = false;
  969. if (ge::AttrUtils::GetBool(op_desc, ATTR_GETNEXT_SINK_DYNMAIC, getnext_sink_dynamic) && getnext_sink_dynamic) {
  970. GELOGI("ATTR_GETNEXT_SINK_DYNMAIC has been set and is true.");
  971. return true;
  972. }
  973. return false;
  974. }
  975. /// @ingroup ge
  976. /// @brief NetOutput Op Initialize.
  977. /// @param [in] ComputeGraphPtr: root graph of the model.
  978. /// @param [in] NodePtr: NetOutput Op.
  979. /// @param [in/out] vector<OpDescPtr>: All NetOutput node in model.
  980. /// @return Status
  981. Status DavinciModel::InitNetOutput(const ComputeGraphPtr &graph, const NodePtr &node,
  982. vector<OpDescPtr> &output_op_list, set<const void *> &output_outside_addrs) {
  983. // node->GetOpDesc Checked by Init: NetOutput, valid.
  984. auto op_desc = node->GetOpDesc();
  985. // excludes the function op sub graph, e.g. case,if
  986. if (node->GetOwnerComputeGraph() != graph) {
  987. GELOGI("Skip subgraph NetOutput node: %s.", op_desc->GetName().c_str());
  988. op_list_.erase(op_desc->GetId());
  989. return SUCCESS;
  990. }
  991. GELOGI("Init NetOutput node: %s.", op_desc->GetName().c_str());
  992. output_op_list.push_back(op_desc);
  993. has_output_node_ = true;
  994. if (known_node_) {
  995. return SUCCESS;
  996. }
  997. // Make information for copy output data.
  998. const vector<int64_t> input_size_list = ModelUtils::GetInputSize(op_desc);
  999. const vector<void *> virtual_addr_list = ModelUtils::GetInputDataAddrs(runtime_param_, op_desc);
  1000. const vector<int64_t> input_offset_list = op_desc->GetInputOffset();
  1001. GE_IF_BOOL_EXEC(input_offset_list.size() != virtual_addr_list.size(),
  1002. REPORT_INNER_ERROR("E19999", "Check data fail in op:%s(%s), input addr size:%zu "
  1003. "input offset size:%zu not equal, model_id:%u", op_desc->GetName().c_str(),
  1004. op_desc->GetType().c_str(), virtual_addr_list.size(), input_offset_list.size(),
  1005. model_id_);
  1006. GELOGE(PARAM_INVALID, "[Check][Param] virtual_addr size:%zu should be equal to offset size:%zu, "
  1007. "op:%s(%s), model id:%u", virtual_addr_list.size(), input_offset_list.size(),
  1008. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  1009. return PARAM_INVALID;);
  1010. if (input_size_list.empty() && virtual_addr_list.empty()) {
  1011. GELOGI("NetOutput[%s] is empty.", op_desc->GetName().c_str());
  1012. return SUCCESS;
  1013. }
  1014. if (input_size_list.empty() || input_size_list.size() != virtual_addr_list.size()) {
  1015. REPORT_INNER_ERROR("E19999", "Check data fail in op:%s(%s), input_desc size:%zu input addr size:%zu "
  1016. "not equal or has empty, model_id:%u", op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1017. input_size_list.size(), virtual_addr_list.size(), model_id_);
  1018. GELOGE(PARAM_INVALID, "[Check][Param] NetOutput[%s] init failed: Input size is %zu, Input addr is %zu",
  1019. op_desc->GetName().c_str(), input_size_list.size(), virtual_addr_list.size());
  1020. return PARAM_INVALID;
  1021. }
  1022. size_t num = output_data_info_.size();
  1023. bool fusion_flag = false;
  1024. size_t input_count = input_size_list.size();
  1025. is_getnext_sink_dynamic_ = false;
  1026. if (IsGetNextSinkDynamic(op_desc)) {
  1027. input_count = input_size_list.size() - kGetDynamicDimsCount;
  1028. is_getnext_sink_dynamic_ = true;
  1029. }
  1030. for (size_t idx = 0; idx < input_count; ++idx) {
  1031. ZeroCopyOffset zero_copy_offset;
  1032. Status ret = zero_copy_offset.InitOutputDataInfo(input_size_list, virtual_addr_list, op_desc, idx, fusion_flag);
  1033. GE_IF_BOOL_EXEC(ret != SUCCESS,
  1034. GELOGE(PARAM_INVALID, "[Init][DataInfo] of input_info %s failed.", op_desc->GetName().c_str());
  1035. return PARAM_INVALID;);
  1036. void *addr = virtual_addr_list.at(idx);
  1037. int64_t input_offset = input_offset_list.at(idx);
  1038. if (output_outside_addrs.count(addr) == 0) {
  1039. vector<void *> tensor_addrs;
  1040. zero_copy_offset.SetOutputOutsideAddrs(input_offset, fusion_flag, addr, tensor_addrs);
  1041. output_outside_addrs.insert(addr);
  1042. for (size_t i = 0; i < tensor_addrs.size(); ++i) {
  1043. void *real_addr = tensor_addrs.at(i);
  1044. DisableZeroCopy(real_addr);
  1045. real_virtual_addrs_.insert(real_addr);
  1046. }
  1047. } else {
  1048. GELOGI("same output_tensor_addr %p to different input_tensor of %s", addr, op_desc->GetName().c_str());
  1049. DisableZeroCopy(addr);
  1050. }
  1051. output_data_info_[num + idx] = zero_copy_offset;
  1052. }
  1053. return SUCCESS;
  1054. }
  1055. Status DavinciModel::InitRealSizeAndShapeInfo(const ComputeGraphPtr &compute_graph, const NodePtr &node) {
  1056. if (node->GetName().find(kMultiBatchNodePostfix) != string::npos) {
  1057. GELOGD("No need to get size and shape of netoutput in subgraph.");
  1058. return SUCCESS;
  1059. }
  1060. GELOGD("Start init real size and shape info of %s.", node->GetName().c_str());
  1061. GetAllGearsInfo(node);
  1062. if (is_getnext_sink_dynamic_) {
  1063. GE_IF_BOOL_EXEC(GetGetDynamicDimsNodeInfo(node) != SUCCESS,
  1064. GELOGE(PARAM_INVALID, "[Get][Info] of getdynamicdims node:%s failed.", node->GetName().c_str());
  1065. return PARAM_INVALID;);
  1066. }
  1067. if (is_online_infer_dynamic_) {
  1068. GE_IF_BOOL_EXEC(GetGearAndRealOutSizeInfo(compute_graph, node) != SUCCESS,
  1069. GELOGE(PARAM_INVALID, "[Call][GetGearAndRealOutSizeInfo] failed, node:%s.",
  1070. node->GetName().c_str());
  1071. return PARAM_INVALID;);
  1072. GE_IF_BOOL_EXEC(GetGearAndRealOutShapeInfo(compute_graph, node) != SUCCESS,
  1073. GELOGE(PARAM_INVALID, "[Call][GetGearAndRealOutShapeInfo] failed, node:%s.",
  1074. node->GetName().c_str());
  1075. return PARAM_INVALID;);
  1076. }
  1077. return SUCCESS;
  1078. }
  1079. void DavinciModel::GetAllGearsInfo(const NodePtr &node) {
  1080. is_online_infer_dynamic_ = false;
  1081. all_gears_info_.clear();
  1082. std::string shapes;
  1083. (void) AttrUtils::GetStr(node->GetOpDesc(), ATTR_ALL_GEARS_INFO, shapes);
  1084. if (!shapes.empty()) {
  1085. is_online_infer_dynamic_ = true;
  1086. std::vector<std::string> shape_strs = ge::StringUtils::Split(shapes, ';');
  1087. for (const auto &shape_str : shape_strs) {
  1088. if (shape_str.empty()) {
  1089. continue;
  1090. }
  1091. std::vector<int32_t> gear_info;
  1092. std::vector<std::string> dims = ge::StringUtils::Split(shape_str, ',');
  1093. for (const auto &dim : dims) {
  1094. if (dim.empty()) {
  1095. continue;
  1096. }
  1097. gear_info.emplace_back(std::strtol(dim.c_str(), nullptr, kDecimal));
  1098. }
  1099. if (!gear_info.empty()) {
  1100. all_gears_info_.emplace_back(gear_info);
  1101. GELOGD("Init all gears info from %s, gaer info is %s", node->GetName().c_str(),
  1102. formats::JoinToString(gear_info).c_str());
  1103. }
  1104. }
  1105. }
  1106. }
  1107. Status DavinciModel::GetGetDynamicDimsNodeInfo(const NodePtr &node) {
  1108. GE_CHECK_NOTNULL(node->GetOpDesc());
  1109. size_t input_count = node->GetAllInDataAnchors().size();
  1110. GELOGI("input_anchor count of %s is %zu.", node->GetName().c_str(), input_count);
  1111. size_t get_dynamic_dims_index = input_count - kGetDynamicDimsCount;
  1112. auto in_anchor = node->GetAllInDataAnchors().at(get_dynamic_dims_index);
  1113. auto peer_out_anchor = in_anchor->GetPeerOutAnchor();
  1114. if (peer_out_anchor == nullptr) {
  1115. REPORT_INNER_ERROR("E19999", "In anchor index:%zu in op:%s(%s) peer anchor is nullptr, model_id:%u, check invalid",
  1116. get_dynamic_dims_index, node->GetName().c_str(), node->GetType().c_str(), model_id_);
  1117. GELOGE(PARAM_INVALID, "[Check][Param] In anchor index:%zu in op:%s(%s) peer anchor is nullptr, model_id:%u.",
  1118. get_dynamic_dims_index, node->GetName().c_str(), node->GetType().c_str(), model_id_);
  1119. return PARAM_INVALID;
  1120. }
  1121. auto peer_node = peer_out_anchor->GetOwnerNode();
  1122. auto op_desc = peer_node->GetOpDesc();
  1123. GE_CHECK_NOTNULL(op_desc);
  1124. if (op_desc->GetName() == kGetDynamicDimsName && op_desc->GetType() == GETDYNAMICDIMS) {
  1125. GELOGD("Start get info of %s.", op_desc->GetName().c_str());
  1126. auto input_addr = ModelUtils::GetInputDataAddrs(runtime_param_, node->GetOpDesc());
  1127. auto input_size = ModelUtils::GetInputSize(node->GetOpDesc());
  1128. if (input_addr.empty() || input_size.empty()) {
  1129. REPORT_INNER_ERROR("E19999", "input_addr size:%zu or input_length size:%zu in op:%s(%s) has empty, model_id:%u "
  1130. "check invalid", input_addr.size(), input_size.size(),
  1131. node->GetName().c_str(), node->GetType().c_str(), model_id_);
  1132. GELOGE(PARAM_INVALID, "[Check][Param] input_addr size:%zu or input_length size:%zu in op:%s(%s) is empty, "
  1133. "model_id:%u", input_addr.size(), input_size.size(),
  1134. node->GetName().c_str(), node->GetType().c_str(), model_id_);
  1135. return PARAM_INVALID;
  1136. }
  1137. auto input_desc = node->GetOpDesc()->GetInputDescPtr(get_dynamic_dims_index);
  1138. GE_CHECK_NOTNULL(input_desc);
  1139. if (input_desc->GetShape().GetDims().empty()) {
  1140. REPORT_INNER_ERROR("E19999", "input_desc_index:%zu in op:%s(%s) shape dim is empty, model_id:%u, check invalid",
  1141. get_dynamic_dims_index, node->GetName().c_str(), node->GetType().c_str(), model_id_);
  1142. GELOGE(PARAM_INVALID, "[Check][Param] input_desc_index:%zu in op:%s(%s) shape dim is empty, model_id:%u",
  1143. get_dynamic_dims_index, node->GetName().c_str(), node->GetType().c_str(), model_id_);
  1144. return PARAM_INVALID;
  1145. }
  1146. netoutput_last_input_addr_ = input_addr[get_dynamic_dims_index];
  1147. netoutput_last_input_size_ = input_size[get_dynamic_dims_index];
  1148. shape_of_cur_dynamic_dims_ = input_desc->GetShape().GetDims().at(0);
  1149. GELOGD("Shape of cur dynamic dims is %zu, size is %ld, addr is %p.", shape_of_cur_dynamic_dims_,
  1150. netoutput_last_input_size_, netoutput_last_input_addr_);
  1151. }
  1152. return SUCCESS;
  1153. }
  1154. Status DavinciModel::GetGearAndRealOutSizeInfo(const ComputeGraphPtr &graph, const NodePtr &node) {
  1155. GELOGD("Start get gear and real output size info of %s.", node->GetName().c_str());
  1156. merge_nodes_gear_and_real_out_size_info_.clear();
  1157. size_t idx = 0;
  1158. for (const auto &in_anchor : node->GetAllInDataAnchors()) {
  1159. auto peer_out_anchor = in_anchor->GetPeerOutAnchor();
  1160. if (peer_out_anchor == nullptr) {
  1161. continue;
  1162. }
  1163. auto peer_node = peer_out_anchor->GetOwnerNode();
  1164. auto op_desc = peer_node->GetOpDesc();
  1165. GE_CHECK_NOTNULL(op_desc);
  1166. if ((peer_node->GetType() == CASE) && (op_desc->HasAttr(ATTR_INSERT_BY_MBATCH))) {
  1167. if (GetRealOutputSizeOfCase(graph, idx, peer_node) != SUCCESS) {
  1168. GELOGE(PARAM_INVALID, "[Get][RealOutputSizeOfCase] %s failed.", peer_node->GetName().c_str());
  1169. return PARAM_INVALID;
  1170. }
  1171. }
  1172. idx++;
  1173. }
  1174. return SUCCESS;
  1175. }
  1176. Status DavinciModel::GetRealOutputSizeOfCase(const ComputeGraphPtr &graph, size_t input_index,
  1177. const NodePtr &case_node) {
  1178. GELOGD("Start get output size of %s, which is %zu input to netoutput", case_node->GetName().c_str(), input_index);
  1179. const auto &func_desc = case_node->GetOpDesc();
  1180. GE_CHECK_NOTNULL(func_desc);
  1181. std::map<vector<int32_t>, int64_t> gear_and_real_out_size_info;
  1182. for (const auto &name : func_desc->GetSubgraphInstanceNames()) {
  1183. const auto &subgraph = graph->GetSubgraph(name);
  1184. if (subgraph == nullptr) {
  1185. REPORT_INNER_ERROR("E19999", "Get name:%s subgraph in graph:%s fail, model_id:%u, check invalid",
  1186. name.c_str(), graph->GetName().c_str(), model_id_);
  1187. GELOGE(GE_GRAPH_EMPTY_SUBGRAPH, "[Get][Subgraph] %s in graph:%s failed, model_id:%u.",
  1188. name.c_str(), graph->GetName().c_str(), model_id_);
  1189. return GE_GRAPH_EMPTY_SUBGRAPH;
  1190. }
  1191. for (auto &node : subgraph->GetDirectNode()) {
  1192. if (node->GetType() == NETOUTPUT) {
  1193. auto op_desc = node->GetOpDesc();
  1194. GE_CHECK_NOTNULL(op_desc);
  1195. string batch_label;
  1196. if (AttrUtils::GetStr(op_desc, ATTR_NAME_BATCH_LABEL, batch_label)) {
  1197. size_t batch_index = static_cast<size_t>(stoi(batch_label.substr(batch_label.rfind('_') + 1)));
  1198. GELOGD("Batch index of %s is %zu.", op_desc->GetName().c_str(), batch_index);
  1199. if (batch_index > all_gears_info_.size()) {
  1200. REPORT_INNER_ERROR("E19999", "Batch_index:%zu in op:%s(%s) > all_gears_info.size:%zu, model_id:%u, "
  1201. "check invalid", batch_index,
  1202. op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1203. all_gears_info_.size(), model_id_);
  1204. GELOGE(PARAM_INVALID, "[Check][Param] Batch_index:%zu in op:%s(%s) > all_gears_info.size:%zu, "
  1205. "model_id:%u.", batch_index, op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1206. all_gears_info_.size(), model_id_);
  1207. return PARAM_INVALID;
  1208. }
  1209. const vector<int64_t> input_size_list = ModelUtils::GetInputSize(op_desc);
  1210. auto tensor_desc = op_desc->GetInputDescPtr(input_index);
  1211. GE_CHECK_NOTNULL(tensor_desc);
  1212. int64_t data_size = 0;
  1213. if (TensorUtils::GetTensorSizeInBytes(*tensor_desc, data_size) != GRAPH_SUCCESS) {
  1214. REPORT_INNER_ERROR("E19999", "Get input TensorSize in op:%s(%s) failed, input_index:%zu, model_id:%u",
  1215. op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1216. input_index, model_id_);
  1217. GELOGE(FAILED, "[Get][TensorSize] in op:%s(%s) failed, input_index:%zu, model_id:%u",
  1218. op_desc->GetName().c_str(), op_desc->GetType().c_str(), input_index, model_id_);
  1219. return FAILED;
  1220. }
  1221. gear_and_real_out_size_info[all_gears_info_[batch_index]] = data_size;
  1222. GELOGD("Get real gear index is: %zu, gear info is %s, size is %ld, tensor size is %ld",
  1223. batch_index, formats::JoinToString(all_gears_info_[batch_index]).c_str(),
  1224. input_size_list[input_index], data_size);
  1225. }
  1226. break;
  1227. }
  1228. }
  1229. }
  1230. merge_nodes_gear_and_real_out_size_info_[input_index] = gear_and_real_out_size_info;
  1231. return SUCCESS;
  1232. }
  1233. Status DavinciModel::GetGearAndRealOutShapeInfo(const ComputeGraphPtr &graph, const NodePtr &node) {
  1234. GELOGD("Start to get dynamic output dims of %s", node->GetName().c_str());
  1235. merge_nodes_gear_and_real_out_shape_info_.clear();
  1236. size_t idx = 0;
  1237. for (const auto &in_anchor : node->GetAllInDataAnchors()) {
  1238. auto peer_out_anchor = in_anchor->GetPeerOutAnchor();
  1239. if (peer_out_anchor == nullptr) {
  1240. continue;
  1241. }
  1242. auto peer_node = peer_out_anchor->GetOwnerNode();
  1243. auto op_desc = peer_node->GetOpDesc();
  1244. GE_CHECK_NOTNULL(op_desc);
  1245. if ((peer_node->GetType() == CASE) && (op_desc->HasAttr(ATTR_INSERT_BY_MBATCH))) {
  1246. std::vector<std::string> dynamic_output_shape_info;
  1247. if (!AttrUtils::GetListStr(node->GetOpDesc(), ATTR_NAME_DYNAMIC_OUTPUT_DIMS, dynamic_output_shape_info)) {
  1248. GELOGD("Can not get dynamic output dims attr from %s", node->GetName().c_str());
  1249. return SUCCESS;
  1250. }
  1251. GELOGI("Dynamic output shape info is %s", formats::JoinToString(dynamic_output_shape_info).c_str());
  1252. std::vector<vector<int64_t>> dynamic_output_shape;
  1253. ParseDynamicOutShape(dynamic_output_shape_info, dynamic_output_shape);
  1254. std::map<vector<int32_t>, vector<int64_t>> gear_and_real_out_shape_info;
  1255. for (auto &it : dynamic_output_shape) {
  1256. auto gear_index = static_cast<size_t>(it[0]);
  1257. if (gear_index > all_gears_info_.size()) {
  1258. REPORT_INNER_ERROR("E19999", "gear index:%zu in op:%s(%s) > all_gears_info.size:%zu in model:%u "
  1259. "check invalid", gear_index, op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1260. all_gears_info_.size(), model_id_);
  1261. GELOGE(PARAM_INVALID, "[Check][Param] gear index:%zu in op:%s(%s) > all_gears_info.size:%zu in model:%u.",
  1262. gear_index, op_desc->GetName().c_str(), op_desc->GetType().c_str(), all_gears_info_.size(), model_id_);
  1263. return PARAM_INVALID;
  1264. }
  1265. if (static_cast<size_t>(it[1]) == idx) {
  1266. vector<int64_t> output_shape;
  1267. for (size_t i = 2; i < it.size(); ++i) {
  1268. output_shape.emplace_back(it[i]);
  1269. }
  1270. gear_and_real_out_shape_info[all_gears_info_[gear_index]] = output_shape;
  1271. GELOGD("Get real gear index is: %zu, gear info is %s, output shape is %s",
  1272. gear_index, formats::JoinToString(all_gears_info_[gear_index]).c_str(),
  1273. formats::JoinToString(output_shape).c_str());
  1274. }
  1275. }
  1276. merge_nodes_gear_and_real_out_shape_info_[idx] = gear_and_real_out_shape_info;
  1277. }
  1278. idx++;
  1279. }
  1280. return SUCCESS;
  1281. }
  1282. void DavinciModel::ParseDynamicOutShape(const std::vector<std::string> &str_info,
  1283. std::vector<vector<int64_t>> &vec_info) {
  1284. for (size_t i = 0; i < str_info.size(); ++i) {
  1285. std::vector<int64_t> shape;
  1286. std::vector<std::string> dims = ge::StringUtils::Split(str_info[i], ',');
  1287. for (const auto &dim : dims) {
  1288. if (dim.empty()) {
  1289. continue;
  1290. }
  1291. shape.emplace_back(std::strtol(dim.c_str(), nullptr, kDecimal));
  1292. }
  1293. GELOGI("Shape from attr is %s", formats::JoinToString(shape).c_str());
  1294. vec_info.emplace_back(shape);
  1295. }
  1296. }
  1297. Status DavinciModel::GetLabelGotoAddr(uint32_t label_index, rtMemType_t mem_type, void *&arg_addr, uint32_t &arg_size) {
  1298. std::lock_guard<std::mutex> lock(label_args_mutex_);
  1299. auto it = label_goto_args_.find(label_index);
  1300. if (it != label_goto_args_.end()) {
  1301. arg_addr = it->second.first;
  1302. arg_size = it->second.second;
  1303. return SUCCESS;
  1304. }
  1305. if (label_index >= label_list_.size()) {
  1306. REPORT_INNER_ERROR("E19999", "Param label index:%u >= label_list_.size:%zu in model:%u, check invalid",
  1307. label_index, label_list_.size(), model_id_);
  1308. GELOGE(INTERNAL_ERROR, "[Check][Param] Param label index:%u >= label_list_.size:%zu in model:%u",
  1309. label_index, label_list_.size(), model_id_);
  1310. return INTERNAL_ERROR;
  1311. }
  1312. GE_CHECK_NOTNULL(label_list_[label_index]);
  1313. vector<rtLabel_t> label_used = { label_list_[label_index] };
  1314. arg_size = label_used.size() * sizeof(rtLabelDevInfo);
  1315. rtError_t rt_ret = rtMalloc(&arg_addr, arg_size, mem_type);
  1316. if (rt_ret != RT_ERROR_NONE) {
  1317. REPORT_CALL_ERROR("E19999", "Call rtMalloc failed, size:%u, ret:0x%X", arg_size, rt_ret);
  1318. GELOGE(RT_FAILED, "[Call][RtMalloc] failed, size:%u, ret:0x%X", arg_size, rt_ret);
  1319. return RT_ERROR_TO_GE_STATUS(rt_ret);
  1320. }
  1321. label_goto_args_[label_index] = { arg_addr, arg_size };
  1322. rt_ret = rtLabelListCpy(label_used.data(), label_used.size(), arg_addr, arg_size);
  1323. if (rt_ret != RT_ERROR_NONE) {
  1324. REPORT_CALL_ERROR("E19999", "Call rtLabelListCpy failed, ret:0x%X", rt_ret);
  1325. GELOGE(RT_FAILED, "[Call][RtLabelListCpy] failed, ret:0x%X", rt_ret);
  1326. return RT_ERROR_TO_GE_STATUS(rt_ret);
  1327. }
  1328. return SUCCESS;
  1329. }
  1330. void DavinciModel::SetGlobalStep(void *global_step, uint64_t global_step_size) {
  1331. global_step_addr_ = global_step;
  1332. global_step_size_ = global_step_size;
  1333. }
  1334. /// @ingroup ge
  1335. /// @brief LabelSet Op Initialize.
  1336. /// @param [in] op_desc: LabelSet Op descriptor.
  1337. /// @return Status
  1338. Status DavinciModel::InitLabelSet(const OpDescPtr &op_desc) {
  1339. uint32_t label_index = 0;
  1340. if (!AttrUtils::GetInt(op_desc, ATTR_NAME_LABEL_SWITCH_INDEX, label_index)) {
  1341. REPORT_INNER_ERROR("E19999", "Get Attr:%s in op:%s(%s) fail, model_id:%u, check invalid",
  1342. ATTR_NAME_LABEL_SWITCH_INDEX.c_str(),
  1343. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  1344. GELOGE(INTERNAL_ERROR, "[Get][Attr] %s in op:%s(%s) fail, model_id:%u",
  1345. ATTR_NAME_LABEL_SWITCH_INDEX.c_str(), op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  1346. return INTERNAL_ERROR;
  1347. }
  1348. if (label_index >= LabelNum()) {
  1349. REPORT_INNER_ERROR("E19999", "label_switch_index:%u in op:%s(%s) >= label_num:%u in model:%u, check invalid",
  1350. label_index, op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1351. LabelNum(), model_id_);
  1352. GELOGE(INTERNAL_ERROR, "[Check][Param] label_switch_index:%u in op:%s(%s) >= label_num:%u in model:%u",
  1353. label_index, op_desc->GetName().c_str(), op_desc->GetType().c_str(), LabelNum(), model_id_);
  1354. return INTERNAL_ERROR;
  1355. }
  1356. if (label_id_indication_.count(label_index) > 0) {
  1357. REPORT_INNER_ERROR("E19999", "label_switch_index:%u in op:%s(%s) is already used in model:%u, check invalid",
  1358. label_index, op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1359. model_id_);
  1360. GELOGE(INTERNAL_ERROR, "[Check][Param] label_switch_index:%u in op:%s(%s) is already used in model:%u",
  1361. label_index, op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  1362. return INTERNAL_ERROR;
  1363. }
  1364. rtStream_t stream = nullptr;
  1365. uint32_t stream_id = static_cast<uint32_t>(op_desc->GetStreamId());
  1366. if (stream_list_.size() == 1) {
  1367. stream = stream_list_[0];
  1368. } else if (stream_list_.size() > stream_id) {
  1369. stream = stream_list_[stream_id];
  1370. } else {
  1371. REPORT_INNER_ERROR("E19999", "stream_id:%u in op:%s(%s) >= stream size:%zu in model:%u, check invalid",
  1372. stream_id, op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1373. stream_list_.size(), model_id_);
  1374. GELOGE(INTERNAL_ERROR, "[Check][Param] stream_id:%u in op:%s(%s) >= stream size:%zu in model:%u",
  1375. stream_id, op_desc->GetName().c_str(), op_desc->GetType().c_str(), stream_list_.size(), model_id_);
  1376. return INTERNAL_ERROR;
  1377. }
  1378. rtLabel_t rt_label = nullptr;
  1379. rtError_t rt_error = rtLabelCreateExV2(&rt_label, rt_model_handle_, stream);
  1380. if (rt_error != RT_ERROR_NONE || rt_label == nullptr) {
  1381. REPORT_CALL_ERROR("E19999", "Call rtLabelCreateExV2 failed, ret:0x%X", rt_error);
  1382. GELOGE(INTERNAL_ERROR, "[Call][RtLabelCreateExV2] InitLabelSet: %s create label failed, ret:0x%x.",
  1383. op_desc->GetName().c_str(), rt_error);
  1384. return INTERNAL_ERROR;
  1385. }
  1386. GELOGI("InitLabelSet: label[%u]=%p stream[%u]=%p", label_index, rt_label, stream_id, stream);
  1387. label_id_indication_.insert(label_index);
  1388. label_list_[label_index] = rt_label;
  1389. return SUCCESS;
  1390. }
  1391. Status DavinciModel::InitVariable(const OpDescPtr &op_desc, map<string, OpDescPtr> &variable_by_name) {
  1392. if (!known_node_) {
  1393. if (op_desc->GetName() == NODE_NAME_GLOBAL_STEP) {
  1394. const auto output_sizes = ModelUtils::GetOutputSize(op_desc);
  1395. if (!output_sizes.empty()) {
  1396. global_step_size_ = output_sizes[0];
  1397. }
  1398. const auto output_addrs = ModelUtils::GetOutputDataAddrs(runtime_param_, op_desc);
  1399. if (!output_addrs.empty()) {
  1400. global_step_addr_ = output_addrs[0];
  1401. }
  1402. }
  1403. }
  1404. if (op_desc->HasAttr(VAR_ATTR_VAR_IS_BROADCAST)) {
  1405. broadcast_variable_[op_desc->GetName()] = op_desc->GetOutputDesc(0);
  1406. }
  1407. variable_by_name[op_desc->GetName()] = op_desc;
  1408. return SUCCESS;
  1409. }
  1410. /// @ingroup ge
  1411. /// @brief ACL case, Load task list with queue.
  1412. /// @param [in] input_queue_ids: input queue ids from user, nums equal Data Op.
  1413. /// @param [in] output_queue_ids: input queue ids from user, nums equal NetOutput Op.
  1414. /// @return: 0 for success / others for failed
  1415. Status DavinciModel::SetQueIds(const std::vector<uint32_t> &input_queue_ids,
  1416. const std::vector<uint32_t> &output_queue_ids) {
  1417. if (input_queue_ids.empty() && output_queue_ids.empty()) {
  1418. REPORT_INNER_ERROR("E19999", "Param input_queue_ids.size:%zu and output_queue_ids.size:%zu is empty, model_id:%u,"
  1419. "check invalid", input_queue_ids.size(), output_queue_ids.size(),
  1420. model_id_);
  1421. GELOGE(ACL_ERROR_GE_EXEC_MODEL_QUEUE_ID_INVALID, "[Check][Param] Param is empty, model_id:%u", model_id_);
  1422. return ACL_ERROR_GE_EXEC_MODEL_QUEUE_ID_INVALID;
  1423. }
  1424. input_queue_ids_ = input_queue_ids;
  1425. output_queue_ids_ = output_queue_ids;
  1426. return SUCCESS;
  1427. }
  1428. ///
  1429. /// @ingroup ge
  1430. /// @brief ACL case, Load task list with queue.
  1431. /// @param [in] input_que_ids: input queue ids from user, nums equal Data Op.
  1432. /// @param [in] output_que_ids: input queue ids from user, nums equal NetOutput Op.
  1433. /// @return: 0 for success / others for failed
  1434. ///
  1435. Status DavinciModel::LoadWithQueue() {
  1436. if (input_queue_ids_.empty() && output_queue_ids_.empty()) {
  1437. return SUCCESS;
  1438. }
  1439. if (input_queue_ids_.size() != input_data_info_.size()) {
  1440. REPORT_INNER_ERROR("E19999", "Param input_queue_ids_.size:%zu != input_data_info_.size:%zu, model_id:%u,"
  1441. "check invalid", input_queue_ids_.size(), input_data_info_.size(),
  1442. model_id_);
  1443. GELOGE(ACL_ERROR_GE_EXEC_MODEL_QUEUE_ID_INVALID, "[Check][Param] Input queue ids not match model: "
  1444. "input_queue=%zu input_data=%zu, model_id:%u", input_queue_ids_.size(), input_data_info_.size(), model_id_);
  1445. return ACL_ERROR_GE_EXEC_MODEL_QUEUE_ID_INVALID;
  1446. }
  1447. if (output_queue_ids_.size() != output_data_info_.size()) {
  1448. REPORT_INNER_ERROR("E19999", "Param output_queue_ids_.size:%zu != output_data_info_.size:%zu, model_id:%u,"
  1449. "check invalid", output_queue_ids_.size(), output_data_info_.size(), model_id_);
  1450. GELOGE(ACL_ERROR_GE_EXEC_MODEL_QUEUE_ID_INVALID,
  1451. "[Check][Param] Output queue ids not match model: output_queue=%zu output_data=%zu, model_id:%u",
  1452. output_queue_ids_.size(), output_data_info_.size(), model_id_);
  1453. return ACL_ERROR_GE_EXEC_MODEL_QUEUE_ID_INVALID;
  1454. }
  1455. GE_CHK_STATUS_RET(AddHeadStream(), "[Add][HeadStream] failed, model_id:%u", model_id_);
  1456. // Binding input_queue and Data Op.
  1457. GE_CHK_STATUS_RET(BindInputQueue(), "[Bind][InputQueue] failed, model_id:%u", model_id_);
  1458. GE_CHK_STATUS_RET(CpuTaskModelZeroCopy(input_mbuf_list_, input_data_info_),
  1459. "[Call][CpuTaskModelZeroCopy] failed, model_id:%u", model_id_);
  1460. // Binding output_queue and NetOutput Op.
  1461. GE_CHK_STATUS_RET(BindOutputQueue(), "[Bind][OutputQueue] failed, model_id:%u", model_id_);
  1462. GE_CHK_STATUS_RET(CpuTaskModelZeroCopy(output_mbuf_list_, output_data_info_),
  1463. "[Call][CpuTaskModelZeroCopy] failed, model_id:%u", model_id_);
  1464. GE_CHK_STATUS_RET(CpuActiveStream(), "[Call][CpuActiveStream] failed, model_id:%u", model_id_);
  1465. GE_CHK_STATUS_RET(CpuWaitEndGraph(), "[Call][CpuWaitEndGraph] failed, model_id:%u", model_id_);
  1466. GE_CHK_STATUS_RET(BindEnqueue(), "[Call][BindEnqueue] failed, model_id:%u", model_id_);
  1467. GE_CHK_STATUS_RET(CpuModelRepeat(), "[Call][CpuModelRepeat] failed, model_id:%u", model_id_);
  1468. return SUCCESS;
  1469. }
  1470. /// @ingroup ge
  1471. /// @brief queue schedule, Bind input queue to Data output address.
  1472. /// @return: 0 for success / others for failed
  1473. Status DavinciModel::BindInputQueue() {
  1474. // Caller checked: input_queue_ids_.size() == input_size_list_.size() != input_addr_list_.size()
  1475. for (size_t i = 0; i < input_queue_ids_.size(); ++i) {
  1476. auto it = input_data_info_.find(i);
  1477. if (it == input_data_info_.end()) {
  1478. GELOGE(FAILED, "[Check][Param] Input not match: tensor num=%zu, Queue id index=%zu", input_data_info_.size(), i);
  1479. return FAILED;
  1480. }
  1481. uint32_t queue_id = input_queue_ids_[i];
  1482. if (it->second.GetDataInfo().empty()) {
  1483. GELOGE(INTERNAL_ERROR, "[Check][Param] the %zu input_queue not set data_info.", i);
  1484. return INTERNAL_ERROR;
  1485. }
  1486. uint32_t data_size = static_cast<uint32_t>(it->second.GetDataInfo().at(0).first);
  1487. uintptr_t data_addr = reinterpret_cast<uintptr_t>(it->second.GetDataInfo().at(0).second);
  1488. GELOGI("BindInputToQueue: graph_%u index[%zu] queue id[%u] output addr[0x%lx] output size[%u]",
  1489. runtime_param_.graph_id, i, queue_id, data_addr, data_size);
  1490. rtError_t rt_ret = rtModelBindQueue(rt_model_handle_, queue_id, RT_MODEL_INPUT_QUEUE);
  1491. if (rt_ret != RT_ERROR_NONE) {
  1492. REPORT_CALL_ERROR("E19999", "Call rtModelBindQueue failed, ret: 0x%X", rt_ret);
  1493. GELOGE(RT_FAILED, "[Call][RtModelBindQueue] failed, ret: 0x%X", rt_ret);
  1494. return RT_ERROR_TO_GE_STATUS(rt_ret);
  1495. }
  1496. if (CpuModelDequeue(queue_id) != SUCCESS) {
  1497. return INTERNAL_ERROR;
  1498. }
  1499. }
  1500. return SUCCESS;
  1501. }
  1502. /// @ingroup ge
  1503. /// @brief definiteness queue schedule, bind input queue to task.
  1504. /// @param [in] queue_id: input queue id from user.
  1505. /// @return: 0 for success / others for failed
  1506. Status DavinciModel::CpuModelDequeue(uint32_t queue_id) {
  1507. GELOGI("Set CpuKernel model dequeue task enter.");
  1508. std::shared_ptr<CpuTaskModelDequeue> dequeue_task = MakeShared<CpuTaskModelDequeue>(rt_entry_stream_);
  1509. if (dequeue_task == nullptr) {
  1510. REPORT_CALL_ERROR("E19999", "New CpuTaskModelDequeue failed, model_id:%u", model_id_);
  1511. GELOGE(MEMALLOC_FAILED, "[New][CpuTaskModelDequeue] task failed, model_id:%u", model_id_);
  1512. return MEMALLOC_FAILED;
  1513. }
  1514. // Get DataOp Output address and bind to queue.
  1515. uintptr_t in_mbuf = 0;
  1516. Status status = dequeue_task->Init(queue_id, in_mbuf);
  1517. if (status != SUCCESS) {
  1518. return status;
  1519. }
  1520. cpu_task_list_.push_back(dequeue_task);
  1521. input_mbuf_list_.push_back(in_mbuf);
  1522. GELOGI("Set CpuKernel model dequeue task success.");
  1523. return SUCCESS;
  1524. }
  1525. Status DavinciModel::CpuTaskModelZeroCopy(std::vector<uintptr_t> &mbuf_list,
  1526. const map<uint32_t, ZeroCopyOffset> &outside_addrs) {
  1527. GELOGI("Set CpuKernel model zero_copy task enter.");
  1528. std::shared_ptr<CpuTaskZeroCopy> zero_copy = MakeShared<CpuTaskZeroCopy>(rt_entry_stream_);
  1529. if (zero_copy == nullptr) {
  1530. REPORT_CALL_ERROR("E19999", "New CpuTaskZeroCopy failed, model_id:%u", model_id_);
  1531. GELOGE(MEMALLOC_FAILED, "[New][CpuTaskZeroCopy] failed, model_id:%u", model_id_);
  1532. return MEMALLOC_FAILED;
  1533. }
  1534. // mdc zero_copy not support l2 fusion
  1535. Status status = zero_copy->Init(mbuf_list, outside_addrs);
  1536. if (status != SUCCESS) {
  1537. return status;
  1538. }
  1539. cpu_task_list_.push_back(zero_copy);
  1540. GELOGI("Set CpuKernel model zero_copy task success.");
  1541. return SUCCESS;
  1542. }
  1543. /// @ingroup ge
  1544. /// @brief queue schedule, bind output queue to NetOutput input address.
  1545. /// @return: 0 for success / others for failed
  1546. Status DavinciModel::BindOutputQueue() {
  1547. // Caller checked: input_queue_ids_.size() == input_size_list_.size() != input_addr_list_.size()
  1548. for (size_t i = 0; i < output_queue_ids_.size(); ++i) {
  1549. auto it = output_data_info_.find(i);
  1550. if (it == output_data_info_.end()) {
  1551. REPORT_INNER_ERROR("E19999", "Index:%zu can't find in output_data_info_ size:%zu in model_id:%u, check invalid",
  1552. i, output_data_info_.size(), model_id_);
  1553. GELOGE(FAILED, "[Check][Param] Index:%zu can't find in output_data_info_ size:%zu in model_id:%u",
  1554. i, output_data_info_.size(), model_id_);
  1555. return FAILED;
  1556. }
  1557. uint32_t queue_id = output_queue_ids_[i];
  1558. if (it->second.GetDataInfo().empty()) {
  1559. REPORT_INNER_ERROR("E19999", "Index:%zu out_data_info in model:%u is empty, check invalid", i, model_id_);
  1560. GELOGE(INTERNAL_ERROR, "[Check][Param] Index:%zu out_data_info in model:%u is empty, check invalid",
  1561. i, model_id_);
  1562. return INTERNAL_ERROR;
  1563. }
  1564. uint32_t data_size = static_cast<uint32_t>(it->second.GetDataInfo().at(0).first);
  1565. uintptr_t data_addr = reinterpret_cast<uintptr_t>(it->second.GetDataInfo().at(0).second);
  1566. GELOGI("BindOutputToQueue: graph_%u index[%zu] queue id[%u] input addr[0x%lx] input size[%u]",
  1567. runtime_param_.graph_id, i, queue_id, data_addr, data_size);
  1568. rtError_t rt_ret = rtModelBindQueue(rt_model_handle_, queue_id, RT_MODEL_OUTPUT_QUEUE);
  1569. if (rt_ret != RT_ERROR_NONE) {
  1570. REPORT_CALL_ERROR("E19999", "Call rtModelBindQueue failed, queue_id:%u, ret:0x%X", queue_id, rt_ret);
  1571. GELOGE(RT_FAILED, "[Call][RtModelBindQueue] failed, queue_id:%u, ret:0x%X", queue_id, rt_ret);
  1572. return RT_ERROR_TO_GE_STATUS(rt_ret);
  1573. }
  1574. Status status = CpuModelPrepareOutput(data_addr, data_size);
  1575. if (status != SUCCESS) {
  1576. return status;
  1577. }
  1578. }
  1579. return SUCCESS;
  1580. }
  1581. /// @ingroup ge
  1582. /// @brief definiteness queue schedule, bind output queue to task.
  1583. /// @param [in] addr: NetOutput Op input tensor address.
  1584. /// @param [in] size: NetOutput Op input tensor size.
  1585. /// @return: 0 for success / others for failed
  1586. Status DavinciModel::CpuModelPrepareOutput(uintptr_t addr, uint32_t size) {
  1587. GELOGI("Set CpuKernel model enqueue task enter.");
  1588. if (input_mbuf_list_.empty()) {
  1589. REPORT_INNER_ERROR("E19999", "input_mbuf_list_ is empty, model_id:%u, check invalid", model_id_);
  1590. GELOGE(FAILED, "[Check][Param] input_mbuf_list_ is empty, model_id:%u", model_id_);
  1591. return FAILED;
  1592. }
  1593. std::shared_ptr<CpuTaskPrepareOutput> prepare_output = MakeShared<CpuTaskPrepareOutput>(rt_entry_stream_);
  1594. if (prepare_output == nullptr) {
  1595. REPORT_CALL_ERROR("E19999", "New CpuTaskPrepareOutput failed, model_id:%u", model_id_);
  1596. GELOGE(MEMALLOC_FAILED, "[New][CpuTaskPrepareOutput] failed, model_id:%u", model_id_);
  1597. return MEMALLOC_FAILED;
  1598. }
  1599. uintptr_t out_mbuf = 0;
  1600. if (prepare_output->Init(addr, size, input_mbuf_list_.back(), out_mbuf) != SUCCESS) {
  1601. return FAILED;
  1602. }
  1603. cpu_task_list_.push_back(prepare_output);
  1604. output_mbuf_list_.push_back(out_mbuf);
  1605. GELOGI("Set CpuKernel model enqueue task success.");
  1606. return SUCCESS;
  1607. }
  1608. ///
  1609. /// @ingroup ge
  1610. /// @brief definiteness queue schedule, active original model stream.
  1611. /// @return: 0 for success / others for failed
  1612. ///
  1613. Status DavinciModel::CpuActiveStream() {
  1614. GELOGI("Set CpuKernel active stream task enter.");
  1615. std::shared_ptr<CpuTaskActiveEntry> active_entry = MakeShared<CpuTaskActiveEntry>(rt_entry_stream_);
  1616. if (active_entry == nullptr) {
  1617. REPORT_CALL_ERROR("E19999", "New CpuTaskActiveEntry failed, model_id:%u", model_id_);
  1618. GELOGE(MEMALLOC_FAILED, "[New][CpuTaskActiveEntry] failed, model_id:%u", model_id_);
  1619. return MEMALLOC_FAILED;
  1620. }
  1621. Status status = active_entry->Init(rt_head_stream_);
  1622. if (status != SUCCESS) {
  1623. return status;
  1624. }
  1625. cpu_task_list_.push_back(active_entry);
  1626. GELOGI("Set CpuKernel active stream task success.");
  1627. return SUCCESS;
  1628. }
  1629. /// @ingroup ge
  1630. /// @brief definiteness queue schedule, wait for end graph.
  1631. /// @return: 0 for success / others for failed
  1632. Status DavinciModel::CpuWaitEndGraph() {
  1633. GELOGI("Set CpuKernel wait end graph task enter.");
  1634. std::shared_ptr<CpuTaskWaitEndGraph> wait_endgraph = MakeShared<CpuTaskWaitEndGraph>(rt_entry_stream_);
  1635. if (wait_endgraph == nullptr) {
  1636. REPORT_CALL_ERROR("E19999", "New CpuTaskWaitEndGraph failed, model_id:%u", model_id_);
  1637. GELOGE(MEMALLOC_FAILED, "[New][CpuTaskWaitEndGraph] failed, model_id:%u", model_id_);
  1638. return MEMALLOC_FAILED;
  1639. }
  1640. Status status = wait_endgraph->Init(runtime_model_id_);
  1641. if (status != SUCCESS) {
  1642. return status;
  1643. }
  1644. cpu_task_list_.push_back(wait_endgraph);
  1645. GELOGI("Set CpuKernel wait end graph task success.");
  1646. return SUCCESS;
  1647. }
  1648. Status DavinciModel::BindEnqueue() {
  1649. for (size_t i = 0; i < output_queue_ids_.size(); ++i) {
  1650. auto it = output_data_info_.find(i);
  1651. if (it == output_data_info_.end()) {
  1652. REPORT_INNER_ERROR("E19999", "Index:%zu can't find in output_data_info_ size:%zu in model_id:%u, check invalid",
  1653. i, output_data_info_.size(), model_id_);
  1654. GELOGE(FAILED, "Index:%zu can't find in output_data_info_ size:%zu in model_id:%u",
  1655. i, output_data_info_.size(), model_id_);
  1656. return FAILED;
  1657. }
  1658. uint32_t queue_id = output_queue_ids_[i];
  1659. if (CpuModelEnqueue(queue_id, output_mbuf_list_[i]) != SUCCESS) {
  1660. return INTERNAL_ERROR;
  1661. }
  1662. }
  1663. return SUCCESS;
  1664. }
  1665. Status DavinciModel::CpuModelEnqueue(uint32_t queue_id, uintptr_t out_mbuf) {
  1666. GELOGI("Set CpuKernel model enqueue task enter.");
  1667. std::shared_ptr<CpuTaskModelEnqueue> model_enqueue = MakeShared<CpuTaskModelEnqueue>(rt_entry_stream_);
  1668. if (model_enqueue == nullptr) {
  1669. REPORT_CALL_ERROR("E19999", "New CpuTaskModelEnqueue failed, model_id:%u", model_id_);
  1670. GELOGE(MEMALLOC_FAILED, "[New][CpuTaskModelEnqueue] failed, model_id:%u", model_id_);
  1671. return MEMALLOC_FAILED;
  1672. }
  1673. Status status = model_enqueue->Init(queue_id, out_mbuf);
  1674. if (status != SUCCESS) {
  1675. return status;
  1676. }
  1677. cpu_task_list_.push_back(model_enqueue);
  1678. GELOGI("Set CpuKernel model enqueue task enter.");
  1679. return SUCCESS;
  1680. }
  1681. /// @ingroup ge
  1682. /// @brief definiteness queue schedule, repeat run model.
  1683. /// @return: 0 for success / others for failed
  1684. Status DavinciModel::CpuModelRepeat() {
  1685. GELOGI("Set CpuKernel repeat task enter.");
  1686. std::shared_ptr<CpuTaskModelRepeat> model_repeat = MakeShared<CpuTaskModelRepeat>(rt_entry_stream_);
  1687. if (model_repeat == nullptr) {
  1688. REPORT_CALL_ERROR("E19999", "New CpuTaskModelRepeat failed, model_id:%u", model_id_);
  1689. GELOGE(MEMALLOC_FAILED, "[New][CpuTaskModelRepeat] failed, model_id:%u", model_id_);
  1690. return MEMALLOC_FAILED;
  1691. }
  1692. Status status = model_repeat->Init(runtime_model_id_);
  1693. if (status != SUCCESS) {
  1694. return status;
  1695. }
  1696. cpu_task_list_.push_back(model_repeat);
  1697. GELOGI("Set CpuKernel repeat task success.");
  1698. return SUCCESS;
  1699. }
  1700. Status DavinciModel::GetInputOutputDescInfo(vector<InputOutputDescInfo> &input_desc,
  1701. vector<InputOutputDescInfo> &output_desc) {
  1702. if (input_addrs_list_.empty() || input_addrs_list_[0].size() != 1) {
  1703. GELOGI("data_op_list_ is empty or input_desc size is not 1.");
  1704. } else {
  1705. vector<uint32_t> input_formats;
  1706. GE_CHK_STATUS_RET(GetInputDescInfo(input_desc, input_formats, false),
  1707. "[Get][InputDescInfo] failed, model_id:%u", model_id_);
  1708. }
  1709. vector<uint32_t> output_formats;
  1710. GE_CHK_STATUS_RET(GetOutputDescInfo(output_desc, output_formats),
  1711. "[Get][OutputDescInfo] failed, model_id:%u", model_id_);
  1712. return SUCCESS;
  1713. }
  1714. Status DavinciModel::GetInputOutputDescInfo(vector<InputOutputDescInfo> &input_desc,
  1715. vector<InputOutputDescInfo> &output_desc,
  1716. vector<uint32_t> &input_formats,
  1717. vector<uint32_t> &output_formats, bool by_dims) {
  1718. if (input_addrs_list_.empty() || input_addrs_list_[0].size() != 1) {
  1719. REPORT_INNER_ERROR("E19999", "input_addrs_list_ is empty or first member size != 1, model_id:%u, "
  1720. "check invalid", model_id_);
  1721. GELOGE(FAILED, "[Check][Param] input_addrs_list_ is empty or first member size != 1, model_id:%u", model_id_);
  1722. return FAILED;
  1723. }
  1724. GE_CHK_STATUS_RET(GetInputDescInfo(input_desc, input_formats, by_dims),
  1725. "[Get][InputDescInfo] failed, model_id:%u", model_id_);
  1726. GE_CHK_STATUS_RET(GetOutputDescInfo(output_desc, output_formats),
  1727. "[Get][OutputDescInfo] failed, model_id:%u", model_id_);
  1728. return SUCCESS;
  1729. }
  1730. ///
  1731. /// @ingroup ge
  1732. /// @brief Get dynamic batch_info
  1733. /// @param [out] batch_info
  1734. /// @param [out] dynamic_type
  1735. /// @return execute result
  1736. ///
  1737. Status DavinciModel::GetDynamicBatchInfo(std::vector<std::vector<int64_t>> &batch_info, int32_t &dynamic_type) const {
  1738. dynamic_type = dynamic_type_;
  1739. batch_info = batch_info_;
  1740. return SUCCESS;
  1741. }
  1742. ///
  1743. /// @ingroup ge
  1744. /// @brief Get combined dynamic dims info
  1745. /// @param [out] batch_info
  1746. /// @return None
  1747. ///
  1748. void DavinciModel::GetCombinedDynamicDims(std::vector<std::vector<int64_t>> &batch_info) const {
  1749. batch_info.clear();
  1750. batch_info = combined_batch_info_;
  1751. }
  1752. ///
  1753. /// @ingroup ge
  1754. /// @brief Get user designate shape order
  1755. /// @param [out] user_input_shape_order
  1756. /// @return None
  1757. ///
  1758. void DavinciModel::GetUserDesignateShapeOrder(std::vector<std::string> &user_input_shape_order) const {
  1759. user_input_shape_order.clear();
  1760. user_input_shape_order = user_designate_shape_order_;
  1761. }
  1762. ///
  1763. /// @ingroup ge
  1764. /// @brief Get AIPP input info
  1765. /// @param [in] index
  1766. /// @param [int] OpDescPtr
  1767. /// @return execute result
  1768. ///
  1769. Status DavinciModel::InitAippInfo(uint32_t index, const OpDescPtr &op_desc) {
  1770. if (!op_desc->HasAttr(ATTR_NAME_AIPP)) {
  1771. GELOGW("There is not AIPP related with index %u", index);
  1772. return SUCCESS;
  1773. }
  1774. domi::AippOpParams aipp_params;
  1775. GeAttrValue::NAMED_ATTRS aipp_attr;
  1776. GE_CHK_BOOL_RET_STATUS(AttrUtils::GetNamedAttrs(op_desc, ATTR_NAME_AIPP, aipp_attr), ACL_ERROR_GE_AIPP_NOT_EXIST,
  1777. "[Get][NamedAttrs] Data node:%s do not contain param aipp!", op_desc->GetName().c_str());
  1778. GE_CHK_STATUS_RET(OpUtils::ConvertAippParams(aipp_attr, &aipp_params),
  1779. "[Convert][AippParams] get aipp params failed, op:%s", op_desc->GetName().c_str());
  1780. GELOGI("Node data: %s, type: %s, current index: %u, current node related input rank: %u",
  1781. op_desc->GetName().c_str(), op_desc->GetType().c_str(), index, aipp_params.related_input_rank());
  1782. AippConfigInfo aipp_info;
  1783. GE_CHK_STATUS_RET(AippUtils::ConvertAippParams2AippInfo(&aipp_params, aipp_info),
  1784. "[Call][ConvertAippParams2AippInfo] failed, op:%s", op_desc->GetName().c_str());
  1785. aipp_info_list_[index] = aipp_info;
  1786. return SUCCESS;
  1787. }
  1788. ///
  1789. /// @ingroup ge
  1790. /// @brief Get AIPP input info
  1791. /// @param [in] index
  1792. /// @param [out] aipp_info
  1793. /// @return execute result
  1794. ///
  1795. Status DavinciModel::GetAippInfo(uint32_t index, AippConfigInfo &aipp_info) const {
  1796. const auto it = aipp_info_list_.find(index);
  1797. if (it == aipp_info_list_.end()) {
  1798. GELOGW("there is not AIPP related with index %u", index);
  1799. return ACL_ERROR_GE_AIPP_NOT_EXIST;
  1800. }
  1801. aipp_info = it->second;
  1802. return SUCCESS;
  1803. }
  1804. Status DavinciModel::InitAippType(uint32_t index, const OpDescPtr &op_desc, const map<uint32_t, OpDescPtr> &data_list) {
  1805. if (!op_desc->HasAttr(ATTR_DATA_RELATED_AIPP_MODE)) {
  1806. GELOGW("There is no aipp releated info with index %u", index);
  1807. return SUCCESS;
  1808. }
  1809. // Set default value
  1810. InputAippType aipp_type = DATA_WITHOUT_AIPP;
  1811. string data_mode;
  1812. (void)AttrUtils::GetStr(op_desc, ATTR_DATA_RELATED_AIPP_MODE, data_mode);
  1813. if (data_mode == "static_aipp") {
  1814. aipp_type = DATA_WITH_STATIC_AIPP;
  1815. } else if (data_mode == "dynamic_aipp") {
  1816. aipp_type = DATA_WITH_DYNAMIC_AIPP;
  1817. } else if (data_mode == "dynamic_aipp_conf") {
  1818. aipp_type = DYNAMIC_AIPP_NODE;
  1819. } else {
  1820. REPORT_INNER_ERROR("E19999", "Attr:%s data_mode:%s in op:%s(%s), model_id:%u, check invalid",
  1821. ATTR_DATA_RELATED_AIPP_MODE.c_str(), data_mode.c_str(),
  1822. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  1823. GELOGE(ACL_ERROR_GE_AIPP_MODE_INVALID, "[Get][Attr] %s data_mode:%s in op:%s(%s), model_id:%u, check invalid",
  1824. ATTR_DATA_RELATED_AIPP_MODE.c_str(), data_mode.c_str(),
  1825. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  1826. return ACL_ERROR_GE_AIPP_MODE_INVALID;
  1827. }
  1828. size_t aipp_index = 0xFFFFFFFF; // default invalid value
  1829. if (aipp_type == DATA_WITH_DYNAMIC_AIPP) {
  1830. string releated_name;
  1831. (void)AttrUtils::GetStr(op_desc, ATTR_DATA_AIPP_DATA_NAME_MAP, releated_name);
  1832. for (const auto item : data_list) {
  1833. if (item.second->GetName() == releated_name) {
  1834. GELOGI("Find aipp_data [%s] index %u from index %u", releated_name.c_str(), item.first, index);
  1835. aipp_index = item.first;
  1836. }
  1837. }
  1838. if (aipp_index == 0xFFFFFFFF) {
  1839. GELOGW("Can not find aipp data node from index %u", index);
  1840. return SUCCESS;
  1841. }
  1842. }
  1843. aipp_type_list_[index] = { aipp_type, aipp_index };
  1844. return SUCCESS;
  1845. }
  1846. Status DavinciModel::GetAippType(uint32_t index, InputAippType &aipp_type, size_t &aipp_index) const {
  1847. GE_CHK_BOOL_RET_STATUS(index < input_addrs_list_.size(), PARAM_INVALID,
  1848. "[Check][Param] Index %u is invalid", index);
  1849. const auto it = aipp_type_list_.find(index);
  1850. if (it == aipp_type_list_.end()) {
  1851. GELOGW("There is no aipp releated info with index %u", index);
  1852. aipp_type = DATA_WITHOUT_AIPP;
  1853. aipp_index = 0xFFFFFFFF;
  1854. return SUCCESS;
  1855. }
  1856. aipp_type = it->second.first;
  1857. aipp_index = it->second.second;
  1858. return SUCCESS;
  1859. }
  1860. void DavinciModel::SetDynamicSize(const std::vector<uint64_t> &batch_num, int32_t dynamic_type) {
  1861. batch_size_.clear();
  1862. if (batch_num.empty()) {
  1863. GELOGD("User has not set dynammic data");
  1864. }
  1865. for (size_t i = 0; i < batch_num.size(); i++) {
  1866. batch_size_.emplace_back(batch_num[i]);
  1867. }
  1868. dynamic_type_ = dynamic_type;
  1869. }
  1870. void DavinciModel::GetCurShape(std::vector<int64_t> &batch_info, int32_t &dynamic_type) const {
  1871. if (batch_size_.empty()) {
  1872. GELOGD("User does not set dynamic size");
  1873. }
  1874. for (size_t i = 0; i < batch_size_.size(); i++) {
  1875. GELOGI("Start to get current shape");
  1876. batch_info.emplace_back(batch_size_[i]);
  1877. }
  1878. dynamic_type = dynamic_type_;
  1879. }
  1880. Status DavinciModel::GetOpAttr(const std::string &op_name, const std::string &attr_name,
  1881. std::string &attr_value) const {
  1882. auto itr = op_name_to_attrs_.find(op_name);
  1883. if (itr == op_name_to_attrs_.end()) {
  1884. GELOGW("Did not save op:%s attr", op_name.c_str());
  1885. return SUCCESS;
  1886. }
  1887. auto attr_itr = itr->second.find(attr_name);
  1888. if (attr_itr == itr->second.end()) {
  1889. GELOGW("Did not save attr:%s of op:%s", attr_name.c_str(), op_name.c_str());
  1890. return SUCCESS;
  1891. }
  1892. for (const auto &name : attr_itr->second) {
  1893. attr_value += "[" + std::to_string(name.size()) + "]" + name;
  1894. }
  1895. GELOGD("Get attr:%s of op:%s success, attr value:%s", attr_name.c_str(), op_name.c_str(), attr_value.c_str());
  1896. return SUCCESS;
  1897. }
  1898. void DavinciModel::GetModelAttr(vector<string> &out_shape_info) const {
  1899. out_shape_info.insert(out_shape_info.end(), dynamic_output_shape_info_.begin(), dynamic_output_shape_info_.end());
  1900. }
  1901. void DavinciModel::SetInputDimsInfo(const vector<int64_t> &input_dims, Format &format, ShapeDescription &shape_info) {
  1902. uint32_t n, c, h, w;
  1903. n = format == FORMAT_NHWC ? NHWC_DIM_N : NCHW_DIM_N;
  1904. c = format == FORMAT_NHWC ? NHWC_DIM_C : NCHW_DIM_C;
  1905. h = format == FORMAT_NHWC ? NHWC_DIM_H : NCHW_DIM_H;
  1906. w = format == FORMAT_NHWC ? NHWC_DIM_W : NCHW_DIM_W;
  1907. if (input_dims.size() == static_cast<size_t>(NORMAL_TENSOR_SIZE)) {
  1908. shape_info.num = input_dims[n];
  1909. shape_info.height = input_dims[h];
  1910. shape_info.width = input_dims[w];
  1911. shape_info.channel = input_dims[c];
  1912. }
  1913. for (size_t k = 0; k < input_dims.size(); ++k) {
  1914. shape_info.dims.push_back(input_dims[k]);
  1915. }
  1916. }
  1917. void DavinciModel::CreateInputDimsInfo(const OpDescPtr &op_desc, Format format,
  1918. ShapeDescription &shape_info, ShapeDescription &dims_info) {
  1919. // judge if this data is linked dynamic aipp first, multiply batch has been considered
  1920. if (op_desc->HasAttr(ATTR_DYNAMIC_AIPP_INPUT_DIMS)) {
  1921. vector<int64_t> dynamic_aipp_input_dims;
  1922. (void)AttrUtils::GetListInt(op_desc, ATTR_DYNAMIC_AIPP_INPUT_DIMS, dynamic_aipp_input_dims);
  1923. SetInputDimsInfo(dynamic_aipp_input_dims, format, shape_info);
  1924. } else {
  1925. // judge if this data is multiply batch
  1926. if (!op_desc->HasAttr(ATTR_MBATCH_ORIGIN_INPUT_DIMS)) {
  1927. vector<int64_t> input_dims = op_desc->GetInputDescPtr(0)->GetShape().GetDims();
  1928. SetInputDimsInfo(input_dims, format, shape_info);
  1929. } else {
  1930. vector<int64_t> origin_input_dims;
  1931. (void)AttrUtils::GetListInt(op_desc, ATTR_MBATCH_ORIGIN_INPUT_DIMS, origin_input_dims);
  1932. SetInputDimsInfo(origin_input_dims, format, shape_info);
  1933. }
  1934. }
  1935. if (op_desc->HasAttr(ATTR_NAME_INPUT_DIMS)) {
  1936. // When static aipp is set, need to get the model input dims which processed by aipp
  1937. vector<int64_t> model_input_dims;
  1938. (void)AttrUtils::GetListInt(op_desc, ATTR_NAME_INPUT_DIMS, model_input_dims);
  1939. SetInputDimsInfo(model_input_dims, format, dims_info);
  1940. } else {
  1941. dims_info = shape_info;
  1942. }
  1943. }
  1944. Status DavinciModel::InitInputDescInfo(const OpDescPtr &op_desc) {
  1945. GE_CHECK_NOTNULL(op_desc->GetInputDescPtr(0));
  1946. InputOutputDescInfo input;
  1947. ShapeDescription dims_info;
  1948. Format format = op_desc->GetInputDescPtr(0)->GetFormat();
  1949. CreateInputDimsInfo(op_desc, format, input.shape_info, dims_info);
  1950. input.data_type = op_desc->GetInputDescPtr(0)->GetDataType();
  1951. input.name = op_desc->GetName();
  1952. int64_t input_size = 0;
  1953. GE_CHK_STATUS_RET(TensorUtils::GetSize(*op_desc->GetInputDescPtr(0), input_size),
  1954. "[Get][InputSize] failed in op:%s.", op_desc->GetName().c_str());
  1955. input.size = input_size;
  1956. input_formats_.push_back(format);
  1957. input_descs_.push_back(input);
  1958. input.shape_info = dims_info;
  1959. input_descs_dims_.push_back(input);
  1960. return SUCCESS;
  1961. }
  1962. Status DavinciModel::GetInputDescInfo(vector<InputOutputDescInfo> &input_descs,
  1963. vector<uint32_t> &input_formats, bool by_dims) const {
  1964. const vector<InputOutputDescInfo> &input_desc_info = by_dims ? input_descs_dims_ : input_descs_;
  1965. input_descs.insert(input_descs.end(), input_desc_info.begin(), input_desc_info.end());
  1966. input_formats.insert(input_formats.end(), input_formats_.begin(), input_formats_.end());
  1967. return SUCCESS;
  1968. }
  1969. void DavinciModel::CreateOutput(uint32_t index, const OpDescPtr &op_desc, InputOutputDescInfo &output,
  1970. uint32_t &format_result) {
  1971. /// netoutput input tensor desc
  1972. GE_IF_BOOL_EXEC(op_desc->GetInputDescPtr(index) == nullptr,
  1973. REPORT_INNER_ERROR("E19999", "input_desc index:%u in op:%s(%s) not exist, model_id:%u, "
  1974. "check invalid", index, op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1975. model_id_);
  1976. GELOGE(FAILED, "[Get][InputDescPtr] input_desc index:%u in op:%s(%s) not exist, model_id:%u",
  1977. index, op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  1978. return);
  1979. Format format = op_desc->GetInputDescPtr(index)->GetFormat();
  1980. GeShape shape = op_desc->GetInputDescPtr(index)->GetShape();
  1981. DataType data_type = op_desc->GetInputDescPtr(index)->GetDataType();
  1982. int64_t dims[] = {1, 1, 1, 1};
  1983. format_result = format;
  1984. if (format == FORMAT_ND) { // for ND tensor
  1985. for (size_t i = 0; i < shape.GetDimNum() && i < (sizeof(dims) / sizeof(dims[0])); i++) {
  1986. dims[i] = shape.GetDim(i);
  1987. }
  1988. } else { // FOR FORMAT_NHWC or FORMAT_NCHW
  1989. dims[0] = shape.GetDim(format == FORMAT_NHWC ? NHWC_DIM_N : NCHW_DIM_N); // 0: first dim
  1990. dims[1] = shape.GetDim(format == FORMAT_NHWC ? NHWC_DIM_C : NCHW_DIM_C); // 1: second dim
  1991. dims[2] = shape.GetDim(format == FORMAT_NHWC ? NHWC_DIM_H : NCHW_DIM_H); // 2: third dim
  1992. dims[3] = shape.GetDim(format == FORMAT_NHWC ? NHWC_DIM_W : NCHW_DIM_W); // 3: forth dim
  1993. }
  1994. output.shape_info.num = dims[0]; // 0: first dim
  1995. output.shape_info.channel = dims[1]; // 1: second dim
  1996. output.shape_info.height = dims[2]; // 2: third dim
  1997. output.shape_info.width = dims[3]; // 3: forth dim
  1998. if (op_desc->GetInputDescPtr(index)->GetFormat() == FORMAT_FRACTAL_Z) { // FraczToHWCK
  1999. int64_t k = shape.GetDim(0); // 0: first dim
  2000. int64_t c = shape.GetDim(1); // 1: second dim
  2001. int64_t h = shape.GetDim(2); // 2: third dim
  2002. int64_t w = shape.GetDim(3); // 3: forth dim
  2003. output.shape_info.dims.push_back(h);
  2004. output.shape_info.dims.push_back(w);
  2005. output.shape_info.dims.push_back(c);
  2006. output.shape_info.dims.push_back(k);
  2007. format_result = FORMAT_HWCN;
  2008. } else {
  2009. for (size_t j = 0; j < shape.GetDimNum(); j++) {
  2010. output.shape_info.dims.push_back(shape.GetDim(j));
  2011. }
  2012. }
  2013. int64_t tensor_size = 0;
  2014. if (AttrUtils::GetInt(op_desc->GetInputDescPtr(index), ATTR_NAME_SPECIAL_OUTPUT_SIZE, tensor_size)
  2015. && (tensor_size > 0)) {
  2016. GELOGI("netoutput[%s] [%d]th input has special size [%ld]", op_desc->GetName().c_str(), index, tensor_size);
  2017. } else {
  2018. (void)TensorUtils::CalcTensorMemSize(shape, format, data_type, tensor_size); // no need to check value
  2019. }
  2020. output.size = static_cast<uint64_t>(tensor_size);
  2021. output.data_type = op_desc->GetInputDescPtr(index)->GetDataType();
  2022. }
  2023. Status DavinciModel::InitOutputDescInfo(const OpDescPtr &op_desc, const vector<string> &out_node_name) {
  2024. uint32_t out_size = static_cast<uint32_t>(op_desc->GetInputsSize());
  2025. for (uint32_t i = 0; i < out_size; ++i) {
  2026. string output_name;
  2027. InputOutputDescInfo output;
  2028. uint32_t format_result;
  2029. CreateOutput(i, op_desc, output, format_result);
  2030. std::vector<std::string> src_name = op_desc->GetSrcName();
  2031. std::vector<int64_t> src_index = op_desc->GetSrcIndex();
  2032. GE_CHK_BOOL_RET_STATUS(src_name.size() > i && src_index.size() > i, INTERNAL_ERROR,
  2033. "[Check][Param] construct output failed, as index:%u >= src name size:%zu, "
  2034. "or index >= src index size:%zu, op:%s.",
  2035. i, src_name.size(), src_index.size(), op_desc->GetName().c_str());
  2036. // forward compatbility, if old om has no out_node_name, need to return output follow origin way
  2037. if (out_size == out_node_name.size()) {
  2038. // neweast plan, the index will add to name during generate model.
  2039. bool contains_colon = out_node_name[i].find(":") != std::string::npos;
  2040. output_name = contains_colon ? out_node_name[i] : out_node_name[i] + ":" + std::to_string(src_index[i]);
  2041. } else {
  2042. output_name = string("output_") + std::to_string(i) + "_" + src_name[i] + "_" + std::to_string(src_index[i]);
  2043. }
  2044. output.name = output_name;
  2045. output_descs_.push_back(output);
  2046. output_formats_.push_back(format_result);
  2047. }
  2048. return SUCCESS;
  2049. }
  2050. Status DavinciModel::GetOutputDescInfo(vector<InputOutputDescInfo> &output_descs,
  2051. vector<uint32_t> &output_formats) const {
  2052. output_descs.insert(output_descs.end(), output_descs_.begin(), output_descs_.end());
  2053. output_formats.insert(output_formats.end(), output_formats_.begin(), output_formats_.end());
  2054. return SUCCESS;
  2055. }
  2056. Status DavinciModel::CopyInputData(const InputData &input_data) {
  2057. const std::vector<DataBuffer> &blobs = input_data.blobs;
  2058. for (const auto &data : input_data_info_) {
  2059. if (data.first >= blobs.size()) {
  2060. REPORT_INNER_ERROR("E19999", "index:%u in input_data_info_ >= input_data.blobs.size:%zu, model_id:%u, "
  2061. "check invalid", data.first, blobs.size(), model_id_);
  2062. GELOGE(FAILED, "[Check][Param] Blobs not match: blobs=%zu, tensor=%zu, index=%u, size=%ld, op_name(%s)",
  2063. blobs.size(), input_data_info_.size(), data.first, data.second.GetDataInfo().at(0).first,
  2064. data.second.GetOpName().c_str());
  2065. return FAILED;
  2066. }
  2067. const DataBuffer &data_buf = blobs[data.first];
  2068. rtMemcpyKind_t kind =
  2069. data_buf.placement == kPlacementHostData ? RT_MEMCPY_HOST_TO_DEVICE : RT_MEMCPY_DEVICE_TO_DEVICE;
  2070. if (data_buf.length == 0) {
  2071. GELOGW("No data need to memcpy!");
  2072. return SUCCESS;
  2073. }
  2074. uint64_t data_size = data.second.GetDataSize();
  2075. GE_CHK_BOOL_RET_STATUS(data_size >= data_buf.length, PARAM_INVALID,
  2076. "[Check][Param] input data size(%lu) does not match model required size(%lu), "
  2077. "op_name(%s), ret failed.", data_buf.length, data_size, data.second.GetOpName().c_str());
  2078. void *mem_addr = data.second.GetBasicAddr();
  2079. void *data_buf_addr = reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(data_buf.data));
  2080. uint64_t data_buf_length = data_buf.length;
  2081. GELOGI("CopyPlainData memcpy graph_%u type[F] input[%s] rank[%u] dst[%p] src[%p] mem_size[%lu] datasize[%lu]",
  2082. runtime_param_.graph_id, data.second.GetOpName().c_str(), data.first, mem_addr, data_buf_addr, data_size,
  2083. data_buf_length);
  2084. GE_CHK_RT_RET(rtMemcpy(mem_addr, data_size, data_buf_addr, data_buf_length, kind));
  2085. }
  2086. return SUCCESS;
  2087. }
  2088. Status DavinciModel::SyncVarData() {
  2089. GELOGI("Sync var data, model id:%u", model_id_);
  2090. if (global_step_addr_ != nullptr && global_step_size_ != 0) {
  2091. const vector<uint64_t> v_step = { iterator_count_ };
  2092. GE_CHK_RT_RET(rtMemcpy(global_step_addr_, global_step_size_, v_step.data(), v_step.size() * sizeof(uint64_t),
  2093. RT_MEMCPY_HOST_TO_DEVICE));
  2094. }
  2095. return SUCCESS;
  2096. }
  2097. Status DavinciModel::InitModelProfile() {
  2098. for (const auto &task : task_list_) {
  2099. GE_CHECK_NOTNULL(task);
  2100. const FusionOpInfo *fusion_op_info = task->GetFusionOpInfo();
  2101. // when type is RT_MODEL_TASK_KERNEL, ctx is not null
  2102. if ((fusion_op_info == nullptr) || fusion_op_info->original_op_names.empty()) {
  2103. continue;
  2104. }
  2105. GELOGI("task.id = %u, opNum = %zu", task->GetTaskID(), fusion_op_info->original_op_names.size());
  2106. op_id_map_.insert(std::make_pair(fusion_op_info->op_index, task->GetTaskID()));
  2107. }
  2108. std::set<uint32_t> task_id_set;
  2109. using CIT = std::multimap<uint32_t, uint32_t>::const_iterator;
  2110. using Range = std::pair<CIT, CIT>;
  2111. for (const auto &task : task_list_) {
  2112. GE_CHECK_NOTNULL(task);
  2113. const FusionOpInfo *fusion_op_info = task->GetFusionOpInfo();
  2114. if ((fusion_op_info == nullptr) || fusion_op_info->original_op_names.empty()) {
  2115. continue;
  2116. }
  2117. if (task_id_set.count(task->GetTaskID()) > 0) {
  2118. continue;
  2119. }
  2120. const auto &op_desc = GetOpByIndex(fusion_op_info->op_index);
  2121. GE_CHK_BOOL_EXEC(op_desc != nullptr,
  2122. REPORT_INNER_ERROR("E19999", "Get op by index failed, as index:%u out of range",
  2123. fusion_op_info->op_index);
  2124. return FAILED,
  2125. "[Get][Op] failed, as index:%u out of range", fusion_op_info->op_index);
  2126. ProfileInfo profile;
  2127. profile.fusion_info = *fusion_op_info;
  2128. Range range = op_id_map_.equal_range(fusion_op_info->op_index);
  2129. for (CIT range_idx = range.first; range_idx != range.second; ++range_idx) {
  2130. profile.task_count++;
  2131. task_id_set.insert(range_idx->second);
  2132. }
  2133. // memory info
  2134. TaskMemInfo &mem_info = profile.memory_info;
  2135. const auto input_size = ModelUtils::GetInputSize(op_desc);
  2136. const auto output_size = ModelUtils::GetOutputSize(op_desc);
  2137. const auto workspace_size = ModelUtils::GetWorkspaceSize(op_desc);
  2138. const auto weight_size = ModelUtils::GetWeightSize(op_desc);
  2139. mem_info.input_size = std::accumulate(input_size.begin(), input_size.end(), 0);
  2140. mem_info.output_size = std::accumulate(output_size.begin(), output_size.end(), 0);
  2141. mem_info.workspace_size = std::accumulate(workspace_size.begin(), workspace_size.end(), 0);
  2142. mem_info.weight_size = std::accumulate(weight_size.begin(), weight_size.end(), 0);
  2143. mem_info.total_size = mem_info.weight_size + mem_info.input_size + mem_info.output_size + mem_info.workspace_size;
  2144. profile_list_.emplace_back(profile);
  2145. }
  2146. GELOGI("fusion task size: %zu, profile info size: %zu", op_id_map_.size(), profile_list_.size());
  2147. return SUCCESS;
  2148. }
  2149. Status DavinciModel::SinkModelProfile() {
  2150. auto &prof_mgr = ProfilingManager::Instance();
  2151. // Model Header
  2152. std::string name = om_name_.empty() ? name_ : om_name_;
  2153. uint32_t model_id = this->Id();
  2154. int64_t start_time = this->GetLoadBeginTime();
  2155. int64_t end_time = this->GetLoadEndTime();
  2156. Json model_load_info;
  2157. model_load_info[kModelName] = name;
  2158. model_load_info[kModeleId] = model_id;
  2159. model_load_info[kLoadStartTime] = start_time;
  2160. model_load_info[kLoadEndTime] = end_time;
  2161. // fusion op info
  2162. using CIT = std::multimap<uint32_t, uint32_t>::const_iterator;
  2163. using Range = std::pair<CIT, CIT>;
  2164. for (const ProfileInfo &profile : profile_list_) {
  2165. Json fusion_op_info;
  2166. string fusion_op_name = profile.fusion_info.op_name;
  2167. uint32_t op_num = profile.fusion_info.original_op_names.size();
  2168. vector<string> original_name;
  2169. for (uint32_t k = 0; k < op_num; k++) {
  2170. original_name.emplace_back(profile.fusion_info.original_op_names[k]);
  2171. }
  2172. uint32_t stream_id = 0;
  2173. auto iter = profiler_report_op_info_.find(fusion_op_name);
  2174. if (iter != profiler_report_op_info_.end()) {
  2175. stream_id = iter->second.second;
  2176. }
  2177. fusion_op_info[kFusionOpName] = fusion_op_name;
  2178. fusion_op_info[kOriginalOpNum] = op_num;
  2179. fusion_op_info[kOriginalOpName] = original_name;
  2180. fusion_op_info[kStreamId] = stream_id;
  2181. fusion_op_info[kFusionOpMemoryInfo][kInputSize] = profile.memory_info.input_size;
  2182. fusion_op_info[kFusionOpMemoryInfo][kOutputSize] = profile.memory_info.output_size;
  2183. fusion_op_info[kFusionOpMemoryInfo][kWeightSize] = profile.memory_info.weight_size;
  2184. fusion_op_info[kFusionOpMemoryInfo][kWorkSpaceSize] = profile.memory_info.workspace_size;
  2185. fusion_op_info[kFusionOpMemoryInfo][kTotalSize] = profile.memory_info.total_size;
  2186. fusion_op_info[kTaskCount] = profile.task_count;
  2187. vector<uint32_t> task_id;
  2188. Range task_range = op_id_map_.equal_range(profile.fusion_info.op_index);
  2189. for (CIT idx = task_range.first; idx != task_range.second; ++idx) {
  2190. task_id.push_back(idx->second);
  2191. }
  2192. fusion_op_info[kTaskId] = task_id;
  2193. model_load_info[kFusionOpInfo] += fusion_op_info;
  2194. }
  2195. std::string tag_name("model_load_info_" + std::to_string(this->Id()));
  2196. std::string reported_data;
  2197. try {
  2198. reported_data = model_load_info.dump(kInteval, ' ', false, Json::error_handler_t::ignore);
  2199. } catch (std::exception &e) {
  2200. REPORT_INNER_ERROR("E19999", "Convert model_load_info JSON to string failed, model_id:%u, reason:%s",
  2201. model_id_, e.what());
  2202. GELOGE(FAILED, "[Convert][JSON] to string failed, model_id:%u, reason:%s.", model_id_, e.what());
  2203. } catch (...) {
  2204. REPORT_INNER_ERROR("E19999", "Convert model_load_info JSON to string failed, model_id:%u", model_id_);
  2205. GELOGE(FAILED, "[Convert][JSON] to string failed, model_id:%u.", model_id_);
  2206. }
  2207. reported_data.append(",")
  2208. .append("\n");
  2209. prof_mgr.ReportData(device_id_, reported_data, tag_name);
  2210. return SUCCESS;
  2211. }
  2212. Status DavinciModel::SinkTimeProfile(const InputData &current_data) {
  2213. auto &prof_mgr = ProfilingManager::Instance();
  2214. string name = om_name_.empty() ? name_ : om_name_;
  2215. Json model_time_info;
  2216. model_time_info[kModelName] = name;
  2217. model_time_info[kModeleId] = this->Id();
  2218. model_time_info[kRequestId] = current_data.request_id;
  2219. model_time_info[kThreadId] = mmGetTid();
  2220. model_time_info[kInputBeginTime] = time_info_.processBeginTime;
  2221. model_time_info[kInputEndTime] = time_info_.processEndTime;
  2222. model_time_info[kInferBeginTime] = time_info_.inferenceBeginTime;
  2223. model_time_info[kInferEndTime] = time_info_.inferenceEndTime;
  2224. model_time_info[kOutputBeginTime] = time_info_.dumpBeginTime;
  2225. model_time_info[kOutputEndTime] = time_info_.dumpEndTime;
  2226. // report model data tag name
  2227. std::string tag_name;
  2228. tag_name.append("model_time_info_")
  2229. .append(std::to_string(this->Id()))
  2230. .append("_")
  2231. .append(std::to_string(current_data.index));
  2232. std::string reported_data;
  2233. try {
  2234. reported_data = model_time_info.dump(kInteval, ' ', false, Json::error_handler_t::ignore);
  2235. } catch (std::exception &e) {
  2236. REPORT_INNER_ERROR("E19999", "Convert model_time_info JSON to string failed, model_id:%u, reason:%s",
  2237. model_id_, e.what());
  2238. GELOGE(FAILED, "[Convert][JSON] to string failed, model_id:%u, reason:%s.", model_id_, e.what());
  2239. } catch (...) {
  2240. REPORT_INNER_ERROR("E19999", "Convert model_time_info JSON to string failed, model_id:%u", model_id_);
  2241. GELOGE(FAILED, "[Convert][JSON] to string failed, model_id:%u.", model_id_);
  2242. }
  2243. reported_data.append(",")
  2244. .append("\n");
  2245. prof_mgr.ReportData(device_id_, reported_data, tag_name);
  2246. return SUCCESS;
  2247. }
  2248. void DavinciModel::SetProfileTime(ModelProcStage stage, int64_t endTime) {
  2249. int64_t time = endTime;
  2250. if (time == 0) {
  2251. mmTimespec timespec = mmGetTickCount();
  2252. time = timespec.tv_sec * 1000 * 1000 * 1000 + timespec.tv_nsec; // 1000 ^ 3 converts second to nanosecond
  2253. }
  2254. switch (stage) {
  2255. case MODEL_LOAD_START:
  2256. load_begin_time_ = time;
  2257. break;
  2258. case MODEL_LOAD_END:
  2259. load_end_time_ = time;
  2260. break;
  2261. case MODEL_PRE_PROC_START:
  2262. time_info_.processBeginTime = time;
  2263. break;
  2264. case MODEL_PRE_PROC_END:
  2265. time_info_.processEndTime = time;
  2266. break;
  2267. case MODEL_INFER_START:
  2268. time_info_.inferenceBeginTime = time;
  2269. break;
  2270. case MODEL_INFER_END:
  2271. time_info_.inferenceEndTime = time;
  2272. break;
  2273. case MODEL_AFTER_PROC_START:
  2274. time_info_.dumpBeginTime = time;
  2275. break;
  2276. case MODEL_AFTER_PROC_END:
  2277. time_info_.dumpEndTime = time;
  2278. break;
  2279. default:
  2280. break;
  2281. }
  2282. return;
  2283. }
  2284. ///
  2285. /// @ingroup ge
  2286. /// @brief send Output Op result to upper layer
  2287. /// @already malloced in ModelLoad, no need to malloc again
  2288. /// @param [in] data_id: the index of output_data
  2289. /// @param [in/out] output_data: real user output_data
  2290. /// @param [in] kind: the kind of rtMemcpy
  2291. /// @return Status result
  2292. /// @author
  2293. ///
  2294. Status DavinciModel::CopyOutputData(uint32_t data_id, OutputData &output_data, rtMemcpyKind_t kind) {
  2295. if (!has_output_node_) {
  2296. return SyncVarData();
  2297. }
  2298. output_data.index = data_id;
  2299. output_data.model_id = model_id_;
  2300. if (output_data.blobs.size() != output_data_info_.size()) {
  2301. REPORT_INNER_ERROR("E19999", "output_data.blobs.size:%zu != output_data_info.size:%zu, model_id:%u, "
  2302. "check invalid", output_data.blobs.size(), output_data_info_.size(), model_id_);
  2303. GELOGE(FAILED, "[Check][Param] output_data.blobs.size:%zu != output_data_info.size:%zu, model_id:%u",
  2304. output_data.blobs.size(), output_data_info_.size(), model_id_);
  2305. return FAILED;
  2306. }
  2307. std::vector<DataBuffer> &blobs = output_data.blobs;
  2308. size_t idx = 0;
  2309. for (const auto &output : output_data_info_) {
  2310. if (output.first >= blobs.size()) {
  2311. REPORT_INNER_ERROR("E19999", "index:%u in output_data_info_ >= output_data.blobs.size:%zu, model_id:%u, "
  2312. "check invalid", output.first, blobs.size(), model_id_);
  2313. GELOGE(FAILED, "[Check][Param] index:%u in output_data_info_ >= output_data.blobs.size:%zu, model_id:%u",
  2314. output.first, blobs.size(), model_id_);
  2315. return FAILED;
  2316. }
  2317. if ((kind == RT_MEMCPY_DEVICE_TO_DEVICE) && (copy_only_addrs_.count(output.second.GetBasicAddr()) == 0)) {
  2318. continue; // Skip: Feed by zero copy.
  2319. }
  2320. DataBuffer &buffer = blobs[output.first];
  2321. uint64_t mem_size = static_cast<uint64_t>(output.second.GetDataSize());
  2322. if ((buffer.length == 0) || (mem_size == 0)) {
  2323. GELOGI("Length of data is zero, No need copy. output tensor index=%u", output.first);
  2324. continue;
  2325. }
  2326. if (is_dynamic_) {
  2327. GELOGI("No need to check output data size.");
  2328. } else if (buffer.length < mem_size) {
  2329. REPORT_INNER_ERROR("E19999", "Buffer.length:%lu in output blob < mem_size:%lu in output_data_info, index:%u, "
  2330. "model_id:%u, check invalid", buffer.length, mem_size, output.first, model_id_);
  2331. GELOGE(FAILED, "[Check][Param] Buffer.length:%lu in output blob < mem_size:%lu in output_data_info, index:%u, "
  2332. "model_id:%u", buffer.length, mem_size, output.first, model_id_);
  2333. return FAILED;
  2334. } else if (buffer.length > mem_size) {
  2335. GELOGW("Tensor data size=%lu, buffer size=%lu", mem_size, buffer.length);
  2336. }
  2337. int64_t data_size = output.second.GetDataSize();
  2338. if (is_online_infer_dynamic_) {
  2339. if (merge_nodes_gear_and_real_out_size_info_.find(idx) != merge_nodes_gear_and_real_out_size_info_.end()) {
  2340. auto gear_and_real_out_size_info = merge_nodes_gear_and_real_out_size_info_[idx];
  2341. data_size = gear_and_real_out_size_info[cur_dynamic_dims_];
  2342. }
  2343. }
  2344. uint64_t buffer_length = buffer.length;
  2345. void *buffer_addr = reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(buffer.data));
  2346. GELOGI("CopyPlainData memcpy graph_%u type[F] output[%u] memaddr[%p] mem_size[%lu] datasize[%lu]",
  2347. runtime_param_.graph_id, output.first, output.second.GetBasicAddr(), data_size, buffer_length);
  2348. GE_CHK_RT_RET(rtMemcpy(buffer_addr, buffer_length, output.second.GetBasicAddr(), data_size, kind));
  2349. idx++;
  2350. }
  2351. return SUCCESS;
  2352. }
  2353. Status DavinciModel::InitOutputTensorInfo(const OpDescPtr &op_desc) {
  2354. size_t input_num = op_desc->GetInputsSize();
  2355. if (is_getnext_sink_dynamic_) {
  2356. input_num = input_num - kGetDynamicDimsCount;
  2357. }
  2358. for (size_t i = 0; i < input_num; ++i) {
  2359. int64_t size = 0;
  2360. auto input_desc = op_desc->GetInputDescPtr(i);
  2361. GE_CHECK_NOTNULL(input_desc);
  2362. auto ret = TensorUtils::GetTensorSizeInBytes(*input_desc, size);
  2363. GE_IF_BOOL_EXEC(ret != GRAPH_SUCCESS,
  2364. REPORT_INNER_ERROR("E19999", "Get input TensorSize in op:%s(%s) failed, input_index:%zu, "
  2365. "model_id:%u", op_desc->GetName().c_str(), op_desc->GetType().c_str(), i,
  2366. model_id_);
  2367. GELOGE(ret, "[Get][InputTensorSize] in op:%s(%s) failed, input_index:%zu, model_id:%u",
  2368. op_desc->GetName().c_str(), op_desc->GetType().c_str(), i, model_id_);
  2369. return ret);
  2370. const GeShape &shape = input_desc->GetShape();
  2371. GELOGI("Output size is %ld, output shape is %s.", size, formats::JoinToString(shape.GetDims()).c_str());
  2372. output_buffer_size_.emplace_back(size);
  2373. output_shape_info_.emplace_back(shape);
  2374. }
  2375. return SUCCESS;
  2376. }
  2377. Status DavinciModel::GenOutputTensorInfo(OutputData *output_data, vector<ge::Tensor> &outputs) {
  2378. GE_CHECK_NOTNULL(output_data);
  2379. if (!output_data->blobs.empty()) {
  2380. GELOGI("No need to generate output tensor info, model id:%u", model_id_);
  2381. return SUCCESS;
  2382. }
  2383. vector<int64_t> output_buffer_size;
  2384. vector<vector<int64_t>> output_shape_info;
  2385. size_t output_num = output_buffer_size_.size();
  2386. for (size_t i = 0; i < output_num; ++i) {
  2387. int64_t output_size = output_buffer_size_[i];
  2388. vector<int64_t> output_shape = output_shape_info_[i].GetDims();
  2389. if (is_online_infer_dynamic_) {
  2390. if (merge_nodes_gear_and_real_out_size_info_.find(i) != merge_nodes_gear_and_real_out_size_info_.end()) {
  2391. auto gear_and_real_out_size_info = merge_nodes_gear_and_real_out_size_info_[i];
  2392. output_size = gear_and_real_out_size_info[cur_dynamic_dims_];
  2393. auto gear_and_real_out_shape_info = merge_nodes_gear_and_real_out_shape_info_[i];
  2394. output_shape = gear_and_real_out_shape_info[cur_dynamic_dims_];
  2395. is_dynamic_ = true;
  2396. }
  2397. }
  2398. GELOGI("Output size is %ld, output shape is %s.", output_size, formats::JoinToString(output_shape).c_str());
  2399. output_buffer_size.push_back(output_size);
  2400. output_shape_info.push_back(output_shape);
  2401. }
  2402. GELOGI("Output blobs size:%zu, model id:%u", output_buffer_size_.size(), model_id_);
  2403. for (size_t i = 0; i < output_buffer_size.size(); ++i) {
  2404. auto aligned_ptr = MakeShared<AlignedPtr>(output_buffer_size[i], kAlignment);
  2405. GE_CHECK_NOTNULL(aligned_ptr);
  2406. GeShape ge_shape(output_shape_info[i]);
  2407. GeTensorDesc tensor_desc;
  2408. tensor_desc.SetShape(ge_shape);
  2409. GeTensor ge_tensor(tensor_desc);
  2410. ge_tensor.SetData(aligned_ptr, output_buffer_size[i]);
  2411. ge::Tensor output_tensor = TensorAdapter::AsTensor(ge_tensor);
  2412. auto data_ptr = aligned_ptr->MutableGet();
  2413. output_data->blobs.push_back(
  2414. {reinterpret_cast<void *>(data_ptr), static_cast<uint64_t>(output_buffer_size[i]), false});
  2415. outputs.emplace_back(std::move(output_tensor));
  2416. GELOGD("Output index:%zu, output dims is %s, data length:%lu.", i,
  2417. formats::JoinToString(output_shape_info[i]).c_str(), output_buffer_size[i]);
  2418. }
  2419. return SUCCESS;
  2420. }
  2421. ///
  2422. /// @ingroup ge
  2423. /// @brief send Output Op result to upper layer
  2424. /// @already malloced in ModelLoad, no need to malloc again
  2425. /// @param [in] data_id: the index of output_data
  2426. /// @param [in] rslt_flg: result flag
  2427. /// @param [in] seq_end_flag: sequence end flag
  2428. /// @param [out] output_data: real user output_data
  2429. /// @return Status result
  2430. /// @author
  2431. ///
  2432. Status DavinciModel::ReturnResult(uint32_t data_id, const bool rslt_flg, const bool seq_end_flag,
  2433. OutputData *output_data) {
  2434. GE_CHK_BOOL_EXEC(listener_ != nullptr,
  2435. REPORT_INNER_ERROR("E19999", "listener_ is nullptr, check invalid.");
  2436. return PARAM_INVALID, "[Check][Param] listener_ is null.");
  2437. std::vector<ge::Tensor> outputs;
  2438. // return result is not required
  2439. if (!rslt_flg && !seq_end_flag) {
  2440. GELOGW("Compute failed, model id: %u", model_id_);
  2441. auto model_manager = ModelManager::GetInstance();
  2442. GE_CHECK_NOTNULL(model_manager);
  2443. auto exception_infos = model_manager->GetExceptionInfos();
  2444. if (exception_infos.size() > 0) {
  2445. GE_CHK_STATUS_RET(DumpExceptionInfo(exception_infos),
  2446. "[Dump][Exception] Dump exception info failed, model_id:%u.", model_id_);
  2447. } else {
  2448. GELOGI("[Dump][Exception] Exception info is null.");
  2449. }
  2450. GE_CHK_STATUS(listener_->OnComputeDone(model_id_, data_id, INTERNAL_ERROR, outputs),
  2451. "[Call][OnComputeDone] failed, model_id:%u, data_id:%u.", model_id_, data_id);
  2452. return INTERNAL_ERROR;
  2453. }
  2454. if (!has_output_node_) {
  2455. GELOGW("Output tensor list is empty, model id: %u", model_id_);
  2456. GE_CHK_STATUS(listener_->OnComputeDone(model_id_, data_id, INTERNAL_ERROR, outputs),
  2457. "[Call][OnComputeDone] failed, model_id:%u, data_id:%u.", model_id_, data_id);
  2458. return INTERNAL_ERROR;
  2459. }
  2460. GE_CHECK_NOTNULL(output_data);
  2461. output_data->index = data_id;
  2462. output_data->model_id = model_id_;
  2463. if (is_getnext_sink_dynamic_) {
  2464. GELOGD("Reinit cur dynamic dims when getnext sink dynamic.");
  2465. cur_dynamic_dims_.clear();
  2466. cur_dynamic_dims_.resize(shape_of_cur_dynamic_dims_);
  2467. auto ret = rtMemcpy(cur_dynamic_dims_.data(), shape_of_cur_dynamic_dims_ * sizeof(int32_t),
  2468. netoutput_last_input_addr_, netoutput_last_input_size_, RT_MEMCPY_DEVICE_TO_HOST);
  2469. GE_CHK_RT_RET(ret);
  2470. }
  2471. GELOGD("Cur dynamic dims is %s.", formats::JoinToString(cur_dynamic_dims_).c_str());
  2472. if (GenOutputTensorInfo(output_data, outputs) != SUCCESS) {
  2473. return INTERNAL_ERROR;
  2474. }
  2475. if (CopyOutputData(data_id, *output_data, RT_MEMCPY_DEVICE_TO_HOST) != SUCCESS) {
  2476. GE_CHK_STATUS(listener_->OnComputeDone(model_id_, data_id, INTERNAL_ERROR, outputs),
  2477. "[Call][OnComputeDone] failed, model_id:%u, data_id:%u.", model_id_, data_id);
  2478. return INTERNAL_ERROR;
  2479. }
  2480. if (seq_end_flag) {
  2481. GELOGW("End of sequence, model id: %u", model_id_);
  2482. GE_CHK_STATUS(listener_->OnComputeDone(model_id_, data_id, END_OF_SEQUENCE, outputs),
  2483. "[Call][OnComputeDone] failed, model_id:%u, data_id:%u.", model_id_, data_id);
  2484. return END_OF_SEQUENCE;
  2485. }
  2486. GE_CHK_STATUS(listener_->OnComputeDone(model_id_, data_id, SUCCESS, outputs),
  2487. "[Call][OnComputeDone] failed, model_id:%u, data_id:%u.", model_id_, data_id);
  2488. return SUCCESS;
  2489. }
  2490. ///
  2491. /// @ingroup ge
  2492. /// @brief return not output to upper layer for cloud case
  2493. /// @param [in] data_id
  2494. /// @return Status result
  2495. ///
  2496. Status DavinciModel::ReturnNoOutput(uint32_t data_id) {
  2497. GELOGI("ReturnNoOutput model id:%u.", model_id_);
  2498. GE_CHK_BOOL_EXEC(listener_ != nullptr,
  2499. REPORT_INNER_ERROR("E19999", "listener_ is nullptr, check invalid.");
  2500. return PARAM_INVALID, "[Check][Param] listener_ is null!");
  2501. std::vector<ge::Tensor> outputs;
  2502. GE_CHK_STATUS(listener_->OnComputeDone(model_id_, data_id, SUCCESS, outputs),
  2503. "[Call][OnComputeDone] failed, model_id:%u, data_id:%u.", model_id_, data_id);
  2504. return SUCCESS;
  2505. }
  2506. void *DavinciModel::Run(DavinciModel *model) {
  2507. GE_CHK_BOOL_EXEC(model != nullptr,
  2508. return nullptr, "[Check][Param] model_pointer is null!")
  2509. bool seq_end_flag = false;
  2510. uint32_t model_id = model->Id();
  2511. uint32_t device_id = model->GetDeviceId();
  2512. ErrorManager::GetInstance().SetErrorContext(model->GetErrorContext());
  2513. GELOGI("Model Run thread start, model_id:%u.", model_id);
  2514. rtError_t rt_ret = rtSetDevice(static_cast<int32_t>(device_id));
  2515. if (rt_ret != RT_ERROR_NONE) {
  2516. GELOGE(FAILED, "[Run][Rtsetdevice] failed, model_id:%u, device_id:%u.", model_id, device_id);
  2517. return nullptr;
  2518. }
  2519. // DeviceReset before thread run finished!
  2520. GE_MAKE_GUARD(not_used_var, [&] { GE_CHK_RT(rtDeviceReset(device_id)); });
  2521. ErrorManager::GetInstance().SetStage(error_message::kModelExecute, error_message::kModelExecute);
  2522. while (model->RunFlag()) {
  2523. // Model hasn't truly started runing before received data
  2524. model->SetRunningFlag(false);
  2525. bool rslt_flg = true;
  2526. if (model->GetDataInputer() == nullptr) {
  2527. GELOGW("Data inputer is nullptr.");
  2528. break;
  2529. }
  2530. std::shared_ptr<InputDataWrapper> data_wrapper;
  2531. Status ret = model->GetDataInputer()->Pop(data_wrapper);
  2532. // Model run indeedly start after received data.
  2533. model->SetRunningFlag(true);
  2534. if (data_wrapper == nullptr || ret != SUCCESS) {
  2535. GELOGI("data_wrapper is null!");
  2536. continue;
  2537. }
  2538. GELOGI("Getting the input data, model_id:%u", model_id);
  2539. GE_IF_BOOL_EXEC(!model->RunFlag(), break);
  2540. InputData current_data = data_wrapper->GetInput();
  2541. GELOGI("Model thread Run begin, model id:%u, data index:%u.", model_id, current_data.index);
  2542. GE_TIMESTAMP_START(Model_SyncVarData);
  2543. ret = model->SyncVarData();
  2544. GE_CHK_BOOL_TRUE_EXEC_WITH_LOG(
  2545. ret != SUCCESS, (void)model->ReturnResult(current_data.index, false, false, data_wrapper->GetOutput());
  2546. continue,
  2547. "[Call][SyncVarData] Copy input data to model failed, model_id:%u.", model_id); // [No need to check value]
  2548. GE_IF_BOOL_EXEC(model->is_first_execute_, GE_TIMESTAMP_EVENT_END(Model_SyncVarData, "Model Run SyncVarData"));
  2549. GELOGI("Copy input data, model id:%u", model_id);
  2550. GE_IF_BOOL_EXEC(ProfilingManager::Instance().ProfilingModelExecuteOn(),
  2551. model->SetProfileTime(MODEL_PRE_PROC_START));
  2552. ret = model->CopyInputData(current_data);
  2553. GE_CHK_BOOL_TRUE_EXEC_WITH_LOG(
  2554. ret != SUCCESS, (void)model->ReturnResult(current_data.index, false, false, data_wrapper->GetOutput());
  2555. continue,
  2556. "[Call][CopyInputData] Copy input data to model failed, model_id:%u.", model_id); // [No need to check value]
  2557. if (model->is_online_infer_dynamic_ && !model->is_getnext_sink_dynamic_) {
  2558. model->cur_dynamic_dims_.clear();
  2559. GE_IF_BOOL_EXEC(current_data.blobs.empty(), break);
  2560. auto shape_data_buffer_data = current_data.blobs.back().data;
  2561. auto shape_data_buffer_length = current_data.blobs.back().length;
  2562. model->cur_dynamic_dims_.assign(reinterpret_cast<int32_t *>(shape_data_buffer_data),
  2563. reinterpret_cast<int32_t *>(shape_data_buffer_data) +
  2564. shape_data_buffer_length / sizeof(int32_t));
  2565. GELOGD("Data: cur dynamic dims is %s", formats::JoinToString(model->cur_dynamic_dims_).c_str());
  2566. delete[] reinterpret_cast<int32_t *>(current_data.blobs.back().data);
  2567. current_data.blobs.pop_back();
  2568. }
  2569. GE_IF_BOOL_EXEC(ProfilingManager::Instance().ProfilingModelExecuteOn(), model->SetProfileTime(MODEL_PRE_PROC_END));
  2570. GE_IF_BOOL_EXEC(ProfilingManager::Instance().ProfilingModelExecuteOn(), model->SetProfileTime(MODEL_INFER_START));
  2571. GE_TIMESTAMP_START(rtModelExecute);
  2572. GELOGI("rtModelExecute start.");
  2573. rt_ret = rtModelExecute(model->rt_model_handle_, model->rt_model_stream_, 0);
  2574. GE_IF_BOOL_EXEC(rt_ret != RT_ERROR_NONE, rslt_flg = false;
  2575. (void)model->ReturnResult(current_data.index, false, false, data_wrapper->GetOutput());
  2576. continue);
  2577. GELOGI("rtModelExecute end");
  2578. GE_IF_BOOL_EXEC(model->is_first_execute_, GE_TIMESTAMP_EVENT_END(rtModelExecute, "GraphExcute::rtModelExecute"));
  2579. GE_TIMESTAMP_START(rtStreamSynchronize);
  2580. GELOGI("rtStreamSynchronize start.");
  2581. rt_ret = rtStreamSynchronize(model->rt_model_stream_);
  2582. if (rt_ret == kEndOfSequence || rt_ret == kEndOfSequenceNew) {
  2583. seq_end_flag = true;
  2584. }
  2585. if (rt_ret == kModelAbortNormal || rt_ret == kModelAbortNormalNew) {
  2586. GELOGI("The model with multiple datasets aborts normally.");
  2587. } else {
  2588. GE_IF_BOOL_EXEC(
  2589. rt_ret != RT_ERROR_NONE, rslt_flg = false; GELOGI("seq_end_flg: %d", seq_end_flag);
  2590. (void)model->ReturnResult(current_data.index, false, seq_end_flag,
  2591. data_wrapper->GetOutput()); // [No need to check value]
  2592. continue);
  2593. }
  2594. GELOGI("rtStreamSynchronize end.");
  2595. GE_IF_BOOL_EXEC(model->is_first_execute_,
  2596. GE_TIMESTAMP_EVENT_END(rtStreamSynchronize, "GraphExcute::Wait for rtStreamSynchronize"));
  2597. GE_IF_BOOL_EXEC(ProfilingManager::Instance().ProfilingModelExecuteOn(), model->SetProfileTime(MODEL_INFER_END));
  2598. GE_IF_BOOL_EXEC(ProfilingManager::Instance().ProfilingModelExecuteOn(),
  2599. model->SetProfileTime(MODEL_AFTER_PROC_START));
  2600. GE_TIMESTAMP_START(ReturnResult3);
  2601. // copy output data from device to host
  2602. GE_IF_BOOL_EXEC(model->has_output_node_,
  2603. (void)model->ReturnResult(current_data.index, rslt_flg, false, data_wrapper->GetOutput()));
  2604. // copy output data from device to host for variable graph
  2605. GE_IF_BOOL_EXEC(!model->has_output_node_, (void)model->ReturnNoOutput(current_data.index));
  2606. GE_IF_BOOL_EXEC(model->is_first_execute_,
  2607. GE_TIMESTAMP_EVENT_END(ReturnResult3, "GraphExcute::CopyDataFromDeviceToHost"));
  2608. GE_IF_BOOL_EXEC(ProfilingManager::Instance().ProfilingModelExecuteOn(),
  2609. model->SetProfileTime(MODEL_AFTER_PROC_END));
  2610. GE_IF_BOOL_EXEC(ProfilingManager::Instance().ProfilingModelExecuteOn(), (void)model->SinkTimeProfile(current_data));
  2611. model->iterator_count_++;
  2612. model->is_first_execute_ = false;
  2613. // model run finished
  2614. model->SetRunningFlag(false);
  2615. GELOGI("run iterator count is %lu, model_id:%u", model->iterator_count_, model->model_id_);
  2616. }
  2617. GELOGI("Model run end, model id:%u", model->model_id_);
  2618. return nullptr;
  2619. }
  2620. ///
  2621. /// @ingroup ge
  2622. /// @brief call API provided by data inputer to destroy thread
  2623. /// @param [in] no
  2624. /// @return Status Destroy result
  2625. /// @author
  2626. ///
  2627. Status DavinciModel::DestroyThread() {
  2628. run_flg_ = false;
  2629. if (data_inputer_ != nullptr) {
  2630. data_inputer_->Stop();
  2631. }
  2632. if (thread_id_.joinable()) {
  2633. thread_id_.join();
  2634. }
  2635. return SUCCESS;
  2636. }
  2637. ///
  2638. /// @ingroup ge
  2639. /// @brief create model std::thread,
  2640. /// @brief start to execute Model
  2641. /// @param [in] no
  2642. /// @return Status create model thread and execute result
  2643. /// @author
  2644. ///
  2645. Status DavinciModel::ModelRunStart() {
  2646. GE_CHK_BOOL_RET_STATUS(data_inputer_ != nullptr, INTERNAL_ERROR,
  2647. "[Check][Param] data_inputer_ is nullptr, model id:%u.", model_id_);
  2648. LockRunFlg();
  2649. GE_MAKE_GUARD(tmp_lock, [&] { UnlockRunFlg(); });
  2650. GE_CHK_BOOL_RET_STATUS(!run_flg_, INTERNAL_ERROR, "[Check][Param] Model already started, model id:%u.", model_id_);
  2651. run_flg_ = true;
  2652. // create stream instance which rt_model_handel is running on
  2653. GE_CHK_RT_RET(rtStreamCreate(&rt_model_stream_, priority_));
  2654. is_inner_model_stream_ = true;
  2655. string opt = "0";
  2656. (void)ge::GetContext().GetOption(OPTION_GE_MAX_DUMP_OP_NUM, opt); // option may not be set up, no need to check value
  2657. int64_t maxDumpOpNum = std::strtol(opt.c_str(), nullptr, kDecimal);
  2658. maxDumpOpNum_ = maxDumpOpNum;
  2659. error_context_ = ErrorManager::GetInstance().GetErrorManagerContext();
  2660. CREATE_STD_THREAD(thread_id_, DavinciModel::Run, this);
  2661. GELOGI("model thread create success, model id:%u.", model_id_);
  2662. return SUCCESS;
  2663. }
  2664. ///
  2665. /// @ingroup ge
  2666. /// @brief call API provided by data inputer and destroy model Thread
  2667. /// @param [in] no
  2668. /// @return Status Destroy result
  2669. /// @author
  2670. ///
  2671. Status DavinciModel::ModelRunStop() {
  2672. LockRunFlg();
  2673. GE_MAKE_GUARD(tmp_lock, [&] { UnlockRunFlg(); });
  2674. GE_CHK_STATUS_RET(DestroyThread(), "[Destoy][Thead] failed, model id:%u.", model_id_);
  2675. return SUCCESS;
  2676. }
  2677. void DavinciModel::UnbindTaskSinkStream() {
  2678. // unbinding hcom stream
  2679. UnbindHcomStream();
  2680. if (is_stream_list_bind_) {
  2681. for (size_t i = 0; i < stream_list_.size(); i++) {
  2682. // unbind rt_model_handle and streams
  2683. GE_LOGW_IF(rtModelUnbindStream(rt_model_handle_, stream_list_[i]) != RT_ERROR_NONE,
  2684. "Unbind stream from model failed! Index: %zu", i);
  2685. }
  2686. }
  2687. if (is_inner_model_stream_) {
  2688. if (!input_queue_ids_.empty() || !output_queue_ids_.empty()) {
  2689. GE_LOGW_IF(rtModelUnbindStream(rt_model_handle_, rt_model_stream_) != RT_ERROR_NONE, "Unbind stream failed!");
  2690. }
  2691. // destroy stream that is bound with rt_model
  2692. GE_LOGW_IF(rtStreamDestroy(rt_model_stream_) != RT_ERROR_NONE, "Destroy stream for rt_model failed.")
  2693. }
  2694. if (is_pure_head_stream_ && rt_head_stream_ != nullptr) {
  2695. GE_LOGW_IF(rtModelUnbindStream(rt_model_handle_, rt_head_stream_) != RT_ERROR_NONE, "Unbind stream failed!");
  2696. GE_LOGW_IF(rtStreamDestroy(rt_head_stream_) != RT_ERROR_NONE, "Destroy stream for rt_model failed.");
  2697. rt_head_stream_ = nullptr;
  2698. }
  2699. if (rt_entry_stream_ != nullptr) {
  2700. GE_LOGW_IF(rtModelUnbindStream(rt_model_handle_, rt_entry_stream_) != RT_ERROR_NONE, "Unbind stream failed!");
  2701. GE_LOGW_IF(rtStreamDestroy(rt_entry_stream_) != RT_ERROR_NONE, "Destroy stream for rt_model failed.");
  2702. rt_entry_stream_ = nullptr;
  2703. }
  2704. }
  2705. void *DavinciModel::GetRunAddress(void *addr) const {
  2706. if (fixed_mem_base_ == reinterpret_cast<uintptr_t>(mem_base_)) {
  2707. return addr;
  2708. }
  2709. uintptr_t ptr = reinterpret_cast<uintptr_t>(addr);
  2710. if ((fixed_mem_base_ <= ptr) && (ptr < fixed_mem_base_ + runtime_param_.mem_size)) {
  2711. return mem_base_ + (ptr - fixed_mem_base_);
  2712. } else {
  2713. return addr;
  2714. }
  2715. }
  2716. Status DavinciModel::CreateKnownZeroCopyMap(const vector<void *> &inputs, const vector<void *> &outputs) {
  2717. GELOGI("in, inputs size: %zu, input addr size: %zu, outputs size: %zu, output addr size: %zu",
  2718. inputs.size(), input_addrs_list_.size(), outputs.size(), output_addrs_list_.size());
  2719. if (inputs.size() > input_addrs_list_.size()) {
  2720. REPORT_INNER_ERROR("E19999", "input data addr %zu should less than input op num %zu.",
  2721. inputs.size(), input_addrs_list_.size());
  2722. GELOGE(FAILED, "[Check][Param] input data addr %zu should less than input op num %zu.",
  2723. inputs.size(), input_addrs_list_.size());
  2724. return FAILED;
  2725. }
  2726. // remove zero copy addr in last iteration
  2727. known_input_data_info_.clear();
  2728. known_output_data_info_.clear();
  2729. for (size_t i = 0; i < inputs.size(); ++i) {
  2730. const vector<void *> &addr_list = input_addrs_list_[i];
  2731. void *addr = GetRunAddress(addr_list[kDataIndex]);
  2732. known_input_data_info_[addr] = inputs[i];
  2733. GELOGI("input %zu, v addr %p, r addr %p, p addr %p", i, addr_list[kDataIndex], addr, inputs[i]);
  2734. }
  2735. if (!has_output_node_) {
  2736. GELOGW("output op num in graph is %zu", output_addrs_list_.size());
  2737. return SUCCESS;
  2738. }
  2739. const vector<void *> &addr_list = output_addrs_list_.front();
  2740. for (size_t i = 0; i < addr_list.size() && i < outputs.size(); ++i) {
  2741. void *addr = GetRunAddress(addr_list[i]);
  2742. known_output_data_info_[addr] = outputs[i];
  2743. GELOGI("output %zu, v addr %p, r addr %p, p addr %p", i, addr_list[i], addr, outputs[i]);
  2744. }
  2745. GELOGI("success, known input data info size: %zu, known output data info size: %zu",
  2746. known_input_data_info_.size(), known_output_data_info_.size());
  2747. return SUCCESS;
  2748. }
  2749. void DavinciModel::SetTotalIOAddrs(const vector<void *> &io_addrs) {
  2750. if (fixed_mem_base_ == reinterpret_cast<uintptr_t>(mem_base_)) {
  2751. total_io_addrs_.insert(total_io_addrs_.end(), io_addrs.begin(), io_addrs.end());
  2752. return;
  2753. }
  2754. for (size_t i = 0; i < io_addrs.size(); ++i) {
  2755. total_io_addrs_.emplace_back(GetRunAddress(io_addrs[i]));
  2756. }
  2757. }
  2758. Status DavinciModel::UpdateKnownZeroCopyAddr(vector<void *> &total_io_addrs, bool update_args) {
  2759. if (fixed_mem_base_ != reinterpret_cast<uintptr_t>(mem_base_) && update_args) {
  2760. for (size_t i = 0; i < total_io_addrs.size(); ++i) {
  2761. total_io_addrs[i] = GetRunAddress(total_io_addrs[i]);
  2762. }
  2763. }
  2764. for (size_t i = 0; i < total_io_addrs.size(); ++i) {
  2765. auto it_in = known_input_data_info_.find(total_io_addrs[i]);
  2766. if (it_in != known_input_data_info_.end()) {
  2767. GELOGI("input %zu, v addr %p, p addr %p", i, total_io_addrs[i], known_input_data_info_.at(total_io_addrs[i]));
  2768. total_io_addrs[i] = known_input_data_info_.at(total_io_addrs[i]);
  2769. }
  2770. auto it_out = known_output_data_info_.find(total_io_addrs[i]);
  2771. if (it_out != known_output_data_info_.end()) {
  2772. GELOGI("output %zu, v addr %p, p addr %p", i, total_io_addrs[i], known_output_data_info_.at(total_io_addrs[i]));
  2773. total_io_addrs[i] = known_output_data_info_.at(total_io_addrs[i]);
  2774. }
  2775. }
  2776. GELOGI("success, total io addrs size: %zu", total_io_addrs.size());
  2777. return SUCCESS;
  2778. }
  2779. Status DavinciModel::UpdateKnownNodeArgs(const vector<void *> &inputs, const vector<void *> &outputs) {
  2780. GELOGI("DavinciModel::UpdateKnownNodeArgs in");
  2781. GE_CHK_STATUS_RET(CreateKnownZeroCopyMap(inputs, outputs),
  2782. "[Call][CreateKnownZeroCopyMap] failed, model_id:%u.", model_id_);
  2783. total_io_addrs_.clear();
  2784. for (size_t task_index = 0; task_index < task_list_.size(); ++task_index) {
  2785. auto &task = task_list_[task_index];
  2786. if (task != nullptr) {
  2787. Status ret = task->UpdateArgs();
  2788. if (ret != SUCCESS) {
  2789. REPORT_CALL_ERROR("E19999", "task %zu update args failed, model_id:%u", task_index, model_id_);
  2790. GELOGE(FAILED, "[Update][Args] to task %zu failed, model_id:%u.", task_index, model_id_);
  2791. return FAILED;
  2792. }
  2793. }
  2794. }
  2795. GE_CHK_STATUS_RET(UpdateKnownZeroCopyAddr(total_io_addrs_, false),
  2796. "[Call][UpdateKnownZeroCopyAddr] failed, model_id:%u.", model_id_);
  2797. if (total_args_size_ == 0) {
  2798. GELOGW("DavinciModel::UpdateKnownNodeArgs device args %p, dst size %u, pass rtMemcpy.", args_, total_args_size_);
  2799. } else {
  2800. uint32_t total_addr_size = total_io_addrs_.size() * sizeof(uint64_t);
  2801. GELOGI("DavinciModel::UpdateKnownNodeArgs device args %p, dst size %u, src size %u", args_, total_args_size_,
  2802. total_addr_size);
  2803. Status rt_ret =
  2804. rtMemcpy(args_, total_args_size_, total_io_addrs_.data(), total_addr_size, RT_MEMCPY_HOST_TO_DEVICE);
  2805. GE_IF_BOOL_EXEC(rt_ret != RT_ERROR_NONE,
  2806. REPORT_CALL_ERROR("E19999", "Call rtMemcpy failed, size:%u, ret:0x%X", total_args_size_ , rt_ret);
  2807. GELOGE(rt_ret, "[Call][RtMemcpy] failed, size:%u, ret:0x%X", total_args_size_ , rt_ret);
  2808. return FAILED;)
  2809. }
  2810. GELOGI("DavinciModel::UpdateKnownNodeArgs success");
  2811. return SUCCESS;
  2812. }
  2813. Status DavinciModel::InitTaskInfo(domi::ModelTaskDef &model_task_def) {
  2814. GELOGI("InitTaskInfo in, task size %d", model_task_def.task().size());
  2815. task_list_.resize(model_task_def.task_size());
  2816. for (int i = 0; i < model_task_def.task_size(); ++i) {
  2817. // dynamic shape will create task_list_ before
  2818. const domi::TaskDef &task = model_task_def.task(i);
  2819. if (this->task_list_[i] == nullptr) {
  2820. task_list_[i] = TaskInfoFactory::Instance().Create(static_cast<rtModelTaskType_t>(task.type()));
  2821. }
  2822. GE_CHECK_NOTNULL(task_list_[i]);
  2823. Status ret = task_list_[i]->Init(task, this);
  2824. if (ret != SUCCESS) {
  2825. REPORT_CALL_ERROR("E19999", "Task index:%d init failed, ret:%d.", i, ret);
  2826. GELOGE(ret, "[Init][Task] index:%d failed, ret:%d.", i, ret);
  2827. return ret;
  2828. }
  2829. }
  2830. GELOGI("InitTaskInfo out");
  2831. return SUCCESS;
  2832. }
  2833. Status DavinciModel::CheckCapability(rtFeatureType_t featureType, int32_t featureInfo, bool &is_support) const {
  2834. int64_t value = RT_CAPABILITY_SUPPORT;
  2835. auto rt_ret = rtGetRtCapability(featureType, featureInfo, &value);
  2836. GE_CHK_BOOL_RET_STATUS(rt_ret == RT_ERROR_NONE, FAILED, "[Call][RtGetRtCapability] failed, ret:0x%X", rt_ret);
  2837. is_support = (value == RT_CAPABILITY_SUPPORT) ? true : false;
  2838. return SUCCESS;
  2839. }
  2840. Status DavinciModel::MallocKnownArgs() {
  2841. GELOGI("DavinciModel::MallocKnownArgs in");
  2842. const auto &model_task_def = ge_model_->GetModelTaskDefPtr();
  2843. if (model_task_def->task_size() == 0) {
  2844. GELOGW("DavinciModel::MallocKnownArgs davincimodel has no task info.");
  2845. return SUCCESS;
  2846. }
  2847. task_list_.resize(model_task_def->task_size());
  2848. for (int32_t i = 0; i < model_task_def->task_size(); ++i) {
  2849. const domi::TaskDef &taskdef = model_task_def->task(i);
  2850. task_list_[i] = TaskInfoFactory::Instance().Create(static_cast<rtModelTaskType_t>(taskdef.type()));
  2851. GE_CHECK_NOTNULL(task_list_[i]);
  2852. Status ret = task_list_[i]->CalculateArgs(taskdef, this);
  2853. if (ret != SUCCESS) {
  2854. REPORT_CALL_ERROR("E19999", "task index:%d CalculateArgs failed, ret:%d", i, ret);
  2855. GELOGE(ret, "[Calculate][Args] for taskdef index:%d failed, ret:%d", i, ret);
  2856. return ret;
  2857. }
  2858. }
  2859. rtError_t rt_ret;
  2860. bool is_support = false;
  2861. GE_CHK_STATUS_RET_NOLOG(CheckCapability(FEATURE_TYPE_MEMORY, MEMORY_INFO_TS_4G_LIMITED, is_support));
  2862. auto mem_type = is_support ? RT_MEMORY_TS_4G : RT_MEMORY_HBM;
  2863. // malloc args memory
  2864. if (total_args_size_ != 0) {
  2865. rt_ret = rtMalloc(&args_, total_args_size_, mem_type);
  2866. if (rt_ret != RT_ERROR_NONE) {
  2867. REPORT_CALL_ERROR("E19999", "Call rtMalloc failed, size:%u, ret: 0x%X", total_args_size_, rt_ret);
  2868. GELOGE(RT_FAILED, "[Call][RtMalloc] failed, size:%u, ret: 0x%X", total_args_size_, rt_ret);
  2869. return RT_ERROR_TO_GE_STATUS(rt_ret);
  2870. }
  2871. }
  2872. // malloc dynamic and static hybrid memory
  2873. if (total_hybrid_args_size_ != 0) {
  2874. rt_ret = rtMalloc(&hybrid_addrs_, total_hybrid_args_size_, mem_type);
  2875. if (rt_ret != RT_ERROR_NONE) {
  2876. REPORT_CALL_ERROR("E19999", "Call rtMalloc failed, size:%u, ret: 0x%X", total_hybrid_args_size_, rt_ret);
  2877. GELOGE(RT_FAILED, "[Call][RtMalloc] failed, size:%u, ret: 0x%X", total_hybrid_args_size_, rt_ret);
  2878. return RT_ERROR_TO_GE_STATUS(rt_ret);
  2879. }
  2880. }
  2881. // malloc fixed addr memory, eg: rts op
  2882. if (total_fixed_addr_size_ != 0) {
  2883. GELOGI("Begin to allocate fixed addr.");
  2884. rt_ret = rtMalloc(&fixed_addrs_, total_fixed_addr_size_, mem_type);
  2885. if (rt_ret != RT_ERROR_NONE) {
  2886. REPORT_CALL_ERROR("E19999", "Call rtMalloc failed, size:%u, ret: 0x%X", total_hybrid_args_size_, rt_ret);
  2887. GELOGE(RT_FAILED, "[Call][RtMalloc] failed, size:%u, ret: 0x%X", total_hybrid_args_size_, rt_ret);
  2888. return RT_ERROR_TO_GE_STATUS(rt_ret);
  2889. }
  2890. }
  2891. GELOGI("DavinciModel::MallocKnownArgs success, total args size %u. total fixed addr size %ld", total_args_size_,
  2892. total_fixed_addr_size_);
  2893. return SUCCESS;
  2894. }
  2895. void DavinciModel::SaveProfilingTaskDescInfo(const OpDescPtr &op, const TaskInfoPtr &task,
  2896. const domi::TaskDef &task_def, size_t task_index) {
  2897. bool flag = GetL1FusionEnableOption();
  2898. char skt_enable_env[MMPA_MAX_PATH] = { 0x00 };
  2899. INT32 res = mmGetEnv("SKT_ENABLE", skt_enable_env, MMPA_MAX_PATH);
  2900. int64_t env_flag = (res == EN_OK) ? std::strtol(skt_enable_env, nullptr, kDecimal) : 0;
  2901. if (env_flag != 0) {
  2902. flag = true;
  2903. }
  2904. TaskDescInfo task_desc_info;
  2905. if (!om_name_.empty()) {
  2906. task_desc_info.model_name = om_name_;
  2907. } else {
  2908. task_desc_info.model_name = name_;
  2909. }
  2910. task_desc_info.op_name = op->GetName();
  2911. task_desc_info.op_type = op->GetType();
  2912. task_desc_info.block_dim = task_def.kernel().block_dim();
  2913. task_desc_info.task_id = task->GetTaskID();
  2914. task_desc_info.stream_id = task->GetStreamId();
  2915. task_desc_info.shape_type = "static";
  2916. task_desc_info.cur_iter_num = 0;
  2917. task_desc_info.task_type = kTaskTypeInvalid;
  2918. auto &prof_mgr = ProfilingManager::Instance();
  2919. prof_mgr.GetOpInputOutputInfo(op, task_desc_info);
  2920. auto model_task_type = static_cast<rtModelTaskType_t>(task_def.type());
  2921. if (model_task_type == RT_MODEL_TASK_KERNEL) {
  2922. const domi::KernelDef &kernel_def = task_def.kernel();
  2923. const auto &context = kernel_def.context();
  2924. auto kernel_type = static_cast<ccKernelType>(context.kernel_type());
  2925. if (kernel_type == ccKernelType::TE) {
  2926. task_desc_info.task_type = kTaskTypeAicore;
  2927. } else if (kernel_type == ccKernelType::AI_CPU || kernel_type == ccKernelType::CUST_AI_CPU) {
  2928. task_desc_info.task_type = kTaskTypeAicpu;
  2929. } else {
  2930. GELOGD("Other kernel type: %u", context.kernel_type());
  2931. }
  2932. } else if (model_task_type == RT_MODEL_TASK_KERNEL_EX) {
  2933. task_desc_info.task_type = kTaskTypeAicpu;
  2934. } else {
  2935. GELOGD("Skip task type: %d", static_cast<int>(model_task_type));
  2936. }
  2937. profiler_report_op_info_[task_desc_info.op_name] =
  2938. std::pair<uint32_t, uint32_t>(task_desc_info.task_id, task_desc_info.stream_id);
  2939. task_desc_info_.emplace_back(task_desc_info);
  2940. if (flag) {
  2941. if (task->GetSktTaskID() != 0xFFFFFFFF) {
  2942. TaskDescInfo task_desc_info;
  2943. string op_name = "super_kernel_" + to_string(task_index);
  2944. task_desc_info.op_name = op_name;
  2945. task_desc_info.task_id = task->GetSktTaskID();
  2946. profiler_report_op_info_[task_desc_info.op_name] =
  2947. std::pair<uint32_t, uint32_t>(task_desc_info.task_id, task_desc_info.stream_id);
  2948. task_desc_info_.emplace_back(task_desc_info);
  2949. }
  2950. }
  2951. }
  2952. Status DavinciModel::DistributeTask() {
  2953. GELOGI("do Distribute.");
  2954. for (auto &task : cpu_task_list_) {
  2955. if (task == nullptr) {
  2956. GELOGW("task is null");
  2957. continue;
  2958. }
  2959. GE_CHK_STATUS_RET(task->Distribute());
  2960. }
  2961. task_desc_info_.clear();
  2962. const auto &model_task_def = ge_model_->GetModelTaskDefPtr();
  2963. for (size_t task_index = 0; task_index < task_list_.size(); ++task_index) {
  2964. auto &task_def = model_task_def->task(task_index);
  2965. auto &task = task_list_.at(task_index);
  2966. GE_CHECK_NOTNULL(task);
  2967. GE_CHK_STATUS_RET(task->Distribute(), "[Call][Distribute] for Task[%zu] fail", task_index);
  2968. // for data dump
  2969. auto op_index = std::max(task_def.kernel().context().op_index(),
  2970. task_def.kernel_ex().op_index());
  2971. OpDescPtr op = GetOpByIndex(op_index);
  2972. GE_CHECK_NOTNULL(op);
  2973. if (reinterpret_cast<void *>(task->GetDumpArgs()) != nullptr) {
  2974. bool call_dump = OpNeedDump(op->GetName()) && task->CallSaveDumpInfo();
  2975. if (call_dump || is_op_debug_reg_) {
  2976. SaveDumpTask(task->GetTaskID(), task->GetStreamId(), op, task->GetDumpArgs());
  2977. }
  2978. }
  2979. auto task_type = static_cast<rtModelTaskType_t>(task_def.type());
  2980. bool no_need_profiling = (task_type != RT_MODEL_TASK_KERNEL) && (task_type != RT_MODEL_TASK_KERNEL_EX);
  2981. GE_IF_BOOL_EXEC(no_need_profiling, continue);
  2982. SaveDumpOpInfo(runtime_param_, op, task->GetTaskID(), task->GetStreamId());
  2983. // save task info for profiling
  2984. SaveProfilingTaskDescInfo(op, task, task_def, task_index);
  2985. }
  2986. // launch dump kernel to aicpu
  2987. GE_CHK_STATUS_RET(data_dumper_.LoadDumpInfo(), "[Load][DumpInfo] failed, model_id:%u.", model_id_);
  2988. return SUCCESS;
  2989. }
  2990. bool DavinciModel::ModelNeedDump() {
  2991. auto all_dump_model = GetDumpProperties().GetAllDumpModel();
  2992. bool ret = all_dump_model.find(ge::DUMP_ALL_MODEL) != all_dump_model.end() ||
  2993. all_dump_model.find(dump_model_name_) != all_dump_model.end() ||
  2994. all_dump_model.find(om_name_) != all_dump_model.end();
  2995. return ret;
  2996. }
  2997. void DavinciModel::SetEndGraphId(uint32_t task_id, uint32_t stream_id) {
  2998. if (ModelNeedDump()) {
  2999. GELOGI("start save end_graph_info to dumper, task_id is %u, stream_id is %u", task_id, stream_id);
  3000. data_dumper_.SaveEndGraphId(task_id, stream_id);
  3001. }
  3002. }
  3003. ///
  3004. /// @ingroup ge
  3005. /// @brief Set copy only for No task feed NetOutput address.
  3006. /// @return None.
  3007. ///
  3008. void DavinciModel::SetCopyOnlyOutput() {
  3009. for (const auto &output_outside_addrs : output_data_info_) {
  3010. ZeroCopyOffset output_outside = output_outside_addrs.second;
  3011. if (!output_outside.IsRelativeOffsetValid()) {
  3012. return;
  3013. }
  3014. for (uint32_t out_count = 0; out_count < output_outside.GetAddrCount(); ++out_count) {
  3015. auto &addrs_mapping_list = output_outside.GetOutsideAddrs();
  3016. std::map<const void *, std::vector<void *>> virtual_args_addrs = addrs_mapping_list[out_count];
  3017. for (const auto &virtual_args_addr : virtual_args_addrs) {
  3018. const auto &args_addrs = virtual_args_addr.second;
  3019. if (args_addrs.empty()) { // No task feed Output addr, Need copy directly.
  3020. GELOGI("[ZCPY] just copy %p to netoutput.", virtual_args_addr.first);
  3021. copy_only_addrs_.insert(virtual_args_addr.first);
  3022. }
  3023. }
  3024. }
  3025. }
  3026. }
  3027. ///
  3028. /// @ingroup ge
  3029. /// @brief Set disabled input zero copy addr.
  3030. /// @param [in] const void *addr: address of task
  3031. /// @return None.
  3032. ///
  3033. void DavinciModel::DisableZeroCopy(const void *addr) {
  3034. if (real_virtual_addrs_.find(addr) == real_virtual_addrs_.end()) {
  3035. return;
  3036. }
  3037. // Data link to RTS Op directly.
  3038. std::lock_guard<std::mutex> lock(outside_addrs_mutex_);
  3039. GELOGI("[ZCPY] disable zero copy of %p.", addr);
  3040. copy_only_addrs_.insert(addr);
  3041. }
  3042. ///
  3043. /// @ingroup ge
  3044. /// @brief Save outside address used info for ZeroCopy.
  3045. /// @param [in] const OpDescPtr &op_desc: current op desc
  3046. /// @param [in] const std::vector<void *> &outside_addrs: address of task
  3047. /// @param [in] const void *info: task args
  3048. /// @param [in] const char *args: task args
  3049. /// @param [in] size_t size: size of task args
  3050. /// @param [in] size_t offset: offset of task args
  3051. /// @return None.
  3052. ///
  3053. void DavinciModel::SetZeroCopyAddr(const OpDescPtr &op_desc, const std::vector<void *> &outside_addrs, const void *info,
  3054. void *args, size_t size, size_t offset) {
  3055. // Internal call has ensured that op_desc is not nullptr
  3056. GELOGD("[ZCPY] SetZeroCopyAddr for %s.", op_desc->GetName().c_str());
  3057. size_t nums = outside_addrs.size();
  3058. ZeroCopyTask zero_copy_task(op_desc->GetName(), static_cast<uint8_t *>(args), size);
  3059. for (size_t i = 0; i < nums; ++i) {
  3060. std::lock_guard<std::mutex> lock(outside_addrs_mutex_);
  3061. for (auto &input_outside_addrs : input_data_info_) {
  3062. ZeroCopyOffset &input_outside = input_outside_addrs.second;
  3063. input_outside.SetOutsideAddrsValue(zero_copy_task, outside_addrs[i], args, offset + i * kAddrLen);
  3064. }
  3065. for (auto &output_outside_addrs : output_data_info_) {
  3066. ZeroCopyOffset &output_outside = output_outside_addrs.second;
  3067. output_outside.SetOutsideAddrsValue(zero_copy_task, outside_addrs[i], args, offset + i * kAddrLen);
  3068. }
  3069. }
  3070. string batch_label;
  3071. if (!AttrUtils::GetStr(op_desc, ATTR_NAME_BATCH_LABEL, batch_label) || batch_label.empty()) {
  3072. zero_copy_task.SetBatchLabel(kDefaultBatchLable);
  3073. } else {
  3074. zero_copy_task.SetBatchLabel(batch_label);
  3075. }
  3076. std::lock_guard<std::mutex> lock(outside_addrs_mutex_);
  3077. if (zero_copy_task.IsTaskArgsSet()) {
  3078. zero_copy_task.SetOriginalArgs(info, offset + nums * kAddrLen);
  3079. zero_copy_tasks_.emplace_back(zero_copy_task);
  3080. }
  3081. }
  3082. ///
  3083. /// @ingroup ge
  3084. /// @brief Copy Check input size and model op size.
  3085. /// @param [in] const int64_t &input_size: input size.
  3086. /// @param [in] const int64_t &op_size: model op size.
  3087. /// @param [in] is_dynamic: dynamic batch input flag.
  3088. /// @return true if success
  3089. ///
  3090. bool DavinciModel::CheckUserAndModelSize(const int64_t &size, const int64_t &op_size,
  3091. bool is_input, bool is_dynamic) {
  3092. const std::string input_or_output = is_input ? "input" : "output";
  3093. if (is_dynamic) { // dynamic is max size.
  3094. GELOGI("No need to check user %s and model size.", input_or_output.c_str());
  3095. return true;
  3096. }
  3097. if (size > op_size) {
  3098. GELOGW(
  3099. "User %s size [%ld] is bigger than om size need [%ld], "
  3100. "MAY cause inference result ERROR, please check model input",
  3101. input_or_output.c_str(), size, op_size);
  3102. }
  3103. if (is_dynamic_aipp_) {
  3104. GELOGI("This is dynamic aipp model, no need to judge smaller user size");
  3105. return true;
  3106. }
  3107. // Judge overflow first
  3108. if (size > (INT64_MAX - kDataMemAlignSizeCompare)) {
  3109. GELOGI("The user %s size [%ld] is smaller than model size [%ld] and is in the range of 64 bytes",
  3110. input_or_output.c_str(), size, op_size);
  3111. return true;
  3112. }
  3113. // The input and model input size can not be exactly equal because user input is not definite.
  3114. if ((size + kDataMemAlignSizeCompare) < op_size) {
  3115. REPORT_INNER_ERROR("E19999", "%s size:%ld from user add align:%u < op_size:%ld in model, model_id:%u, "
  3116. "check invalid",
  3117. input_or_output.c_str(), size, kDataMemAlignSizeCompare, op_size, model_id_);
  3118. GELOGE(ACL_ERROR_GE_PARAM_INVALID,
  3119. "[Check][Param] %s size:%ld from user add align:%u < op_size:%ld in model, model_id:%u",
  3120. input_or_output.c_str(), size, kDataMemAlignSizeCompare, op_size, model_id_);
  3121. return false;
  3122. }
  3123. return true;
  3124. }
  3125. ///
  3126. /// @ingroup ge
  3127. /// @brief Copy Inputs and Outputs addr to model for direct use.
  3128. /// @param [in] const InputData &input_data: model input data.
  3129. /// @param [in] OutputData &output_data: model output data.
  3130. /// @param [in] bool is_dynamic_input: whether is dynamic input, true: is dynamic input; false: not is dynamic input
  3131. /// @return SUCCESS handle successfully / PARAM_INVALID for failed
  3132. ///
  3133. Status DavinciModel::CopyModelData(const InputData &input_data, OutputData &output_data, bool is_dynamic) {
  3134. if (UpdateIoTaskArgs(input_data_info_, true, input_data.blobs, is_dynamic, input_data.batch_label) != SUCCESS) {
  3135. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "[Call][UpdateIoTaskArgs] [ZCPY] Update input data to model:%u failed.",
  3136. model_id_);
  3137. return ACL_ERROR_GE_PARAM_INVALID;
  3138. }
  3139. if (UpdateIoTaskArgs(output_data_info_, false, output_data.blobs, is_dynamic, input_data.batch_label) !=
  3140. SUCCESS) {
  3141. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "[Call][UpdateIoTaskArgs] [ZCPY] Update output data to model:%u failed.",
  3142. model_id_);
  3143. return ACL_ERROR_GE_PARAM_INVALID;
  3144. }
  3145. for (ZeroCopyTask &task : zero_copy_tasks_) {
  3146. GE_CHK_STATUS_RET(task.DistributeParam(is_async_mode_, rt_model_stream_),
  3147. "[Call][DistributeParam] [ZCPY] Update args failed, model_id:%u.", model_id_);
  3148. }
  3149. output_data.index = input_data.index;
  3150. output_data.model_id = model_id_;
  3151. return SUCCESS;
  3152. }
  3153. ///
  3154. /// @ingroup ge
  3155. /// @brief Copy Data addr to model for direct use.
  3156. /// @param [in] data_info: model memory addr/size map { data_index, { tensor_size, tensor_addr } }.
  3157. /// @param [in] is_input: input data or output data
  3158. /// @param [in] blobs: user input/output data list.
  3159. /// @param [in] is_dynamic: whether is dynamic input, true: is dynamic input; false: not is dynamic input
  3160. /// @param [in] batch_label: batch label for multi-batch scenes
  3161. /// @return SUCCESS handle successfully / others handle failed
  3162. ///
  3163. Status DavinciModel::UpdateIoTaskArgs(const std::map<uint32_t, ZeroCopyOffset> &data_info, bool is_input,
  3164. const vector<DataBuffer> &blobs, bool is_dynamic, const string &batch_label) {
  3165. if (blobs.size() != data_info.size()) {
  3166. REPORT_INNER_ERROR("E19999", "is_input:%d blob size:%ld from user != op_size:%ld in model, mode_id:%u"
  3167. "check invalid", is_input, blobs.size(), data_info.size(), model_id_);
  3168. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "[Check][Param] is_input:%d blob size:%ld "
  3169. "from user != op_size:%ld in model, mode_id:%u",
  3170. is_input, blobs.size(), data_info.size(), model_id_);
  3171. return ACL_ERROR_GE_PARAM_INVALID;
  3172. }
  3173. for (const auto &data : data_info) {
  3174. if (data.first >= blobs.size()) { // check data index.
  3175. REPORT_INNER_ERROR("E19999", "is_input:%d, data index:%u from model >= blobs.size:%zu from user, mode_id:%u"
  3176. "check invalid", is_input, data.first, blobs.size(), model_id_);
  3177. GELOGE(ACL_ERROR_GE_PARAM_INVALID,
  3178. "[Check][Param] is_input:%d, data index:%u from model >= blobs.size:%zu from user, mode_id:%u",
  3179. is_input, data.first, blobs.size(), model_id_);
  3180. return ACL_ERROR_GE_PARAM_INVALID;
  3181. }
  3182. const DataBuffer &buffer = blobs[data.first]; // index of data.
  3183. if (buffer.data == nullptr) {
  3184. REPORT_INNER_ERROR("E19999", "is_input:%d buffer from user is nullptr, index:%u, mode_id:%u"
  3185. "check invalid", is_input, data.first, model_id_);
  3186. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "[Check][Param] data_buf.data is nullptr, "
  3187. "index=%u, mode_id:%u", data.first, model_id_);
  3188. return ACL_ERROR_GE_PARAM_INVALID;
  3189. }
  3190. if (!CheckUserAndModelSize(buffer.length, data.second.GetDataSize(), is_input, is_dynamic)) {
  3191. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "[Call][CheckInputAndModelSize] failed, op[%s]",
  3192. data.second.GetOpName().c_str());
  3193. return ACL_ERROR_GE_PARAM_INVALID;
  3194. }
  3195. void *basic_addr = data.second.GetBasicAddr();
  3196. uint64_t data_size = data.second.GetDataSize();
  3197. if (copy_only_addrs_.count(basic_addr) > 0) {
  3198. if (is_input && buffer.length > 0) {
  3199. GELOGI("[IMAS] Find addr %p need direct copy from user malloc input %p", basic_addr, buffer.data);
  3200. rtError_t rt_ret = rtMemcpy(basic_addr, data_size, buffer.data, buffer.length, RT_MEMCPY_DEVICE_TO_DEVICE);
  3201. if (rt_ret != RT_ERROR_NONE) {
  3202. REPORT_CALL_ERROR("E19999", "Call rtMemcpy failed, size:%lu, model_id:%u", data_size, model_id_);
  3203. GELOGE(rt_ret, "[Call][RtMemcpy] failed, size:%lu, model_id:%u", data_size, model_id_);
  3204. return RT_ERROR_TO_GE_STATUS(rt_ret);
  3205. }
  3206. }
  3207. GELOGI("No need to exeucte zero copy task because this addr %p need direct copy.", basic_addr);
  3208. continue;
  3209. }
  3210. for (size_t count = 0; count < data.second.GetDataCount(); ++count) {
  3211. void *addr = data.second.GetDataInfo().at(count).second;
  3212. void *buffer_addr = reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(buffer.data) +
  3213. data.second.GetRelativeOffset().at(count));
  3214. GELOGI("[ZCPY] Copy %s blobs_index %u, virtual_addr: %p, size: %ld, user_data_addr: %p, batch_label: %s",
  3215. is_input ? "input" : "output", data.first, addr, data.second.GetDataInfo().at(count).first,
  3216. buffer_addr, batch_label.c_str());
  3217. // For input data, just copy for rts task.
  3218. for (auto &task : zero_copy_tasks_) {
  3219. bool not_same_batch = (task.GetBatchLabel() != kDefaultBatchLable && task.GetBatchLabel() != batch_label);
  3220. if (not_same_batch) {
  3221. continue;
  3222. }
  3223. uintptr_t addr_val = reinterpret_cast<uintptr_t>(addr);
  3224. (void)task.UpdateTaskParam(addr_val, buffer_addr);
  3225. }
  3226. }
  3227. }
  3228. return SUCCESS;
  3229. }
  3230. ///
  3231. /// @ingroup ge
  3232. /// @brief get unique identification for op when load two or more models
  3233. /// @param [in] const OpDescPtr: current op.
  3234. /// @param [in] string identification: unique identification for current op.
  3235. /// @return SUCCESS handle successfully / others handle failed
  3236. ///
  3237. void DavinciModel::GetUniqueId(const OpDescPtr &op_desc, std::string &unique_identification) {
  3238. std::string session_graph_id;
  3239. GE_IF_BOOL_EXEC(AttrUtils::GetStr(*op_desc, ATTR_NAME_SESSION_GRAPH_ID, session_graph_id),
  3240. GELOGD("Get original type of session_graph_id."));
  3241. if (session_graph_id.empty()) {
  3242. return;
  3243. } else if (session_graph_id.find("-1") != string::npos) {
  3244. unique_identification = session_graph_id + "_" + to_string(model_id_);
  3245. } else {
  3246. unique_identification = session_graph_id;
  3247. }
  3248. }
  3249. ///
  3250. /// @ingroup ge
  3251. /// @brief For TVM Op, avoid Addr Reuse.
  3252. /// @return void*
  3253. ///
  3254. const char *DavinciModel::GetRegisterStub(const string &binfile, const string &session_graph_id) {
  3255. string binfile_key;
  3256. if (session_graph_id.empty()) {
  3257. binfile_key = binfile;
  3258. } else {
  3259. binfile_key = session_graph_id + "_" + binfile;
  3260. }
  3261. auto it = tvm_bin_kernel_.find(binfile_key);
  3262. if (it != tvm_bin_kernel_.end()) {
  3263. return it->c_str();
  3264. } else {
  3265. it = tvm_bin_kernel_.insert(tvm_bin_kernel_.end(), binfile_key);
  3266. return it->c_str();
  3267. }
  3268. }
  3269. ///
  3270. /// @ingroup ge
  3271. /// @brief Constant Op Init.
  3272. /// @return Status
  3273. ///
  3274. Status DavinciModel::InitConstant(const OpDescPtr &op_desc) {
  3275. auto v_weights = ModelUtils::GetWeights(op_desc);
  3276. auto v_output_size = ModelUtils::GetOutputSize(op_desc);
  3277. auto v_output_addr = ModelUtils::GetOutputDataAddrs(runtime_param_, op_desc);
  3278. GE_IF_BOOL_EXEC(v_weights.empty() || v_output_size.empty() || v_output_addr.empty(),
  3279. REPORT_INNER_ERROR("E19999", "weight.size:%zu output_length.size:%zu output_addr.size:%zu in "
  3280. "op:%s(%s) has empty, model_id:%u, check invalid",
  3281. v_weights.size(),v_output_size.size(), v_output_addr.size(),
  3282. op_desc->GetName().c_str(), op_desc->GetType().c_str() ,model_id_);
  3283. GELOGE(PARAM_INVALID, "const op:%s not set output", op_desc->GetName().c_str());
  3284. return PARAM_INVALID;);
  3285. GeTensor *tensor = const_cast<GeTensor *>(v_weights[0].get());
  3286. GE_IF_BOOL_EXEC(static_cast<size_t>(v_output_size[0]) < tensor->GetData().size(),
  3287. REPORT_INNER_ERROR("E19999", "Output size:%zu < weight size:%zu in op:%s(%s) model_id:%u, "
  3288. "check invalid", v_output_size[0], tensor->GetData().size(),
  3289. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3290. GELOGE(PARAM_INVALID, "[Check][Param] Output size:%zu < weight size:%zu in op:%s(%s), model_id:%u",
  3291. v_output_size[0], tensor->GetData().size(),
  3292. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3293. return PARAM_INVALID;);
  3294. GE_IF_BOOL_EXEC(tensor->GetData().size() == 0, GELOGW("const op:%s has no weight data.", op_desc->GetName().c_str());
  3295. return SUCCESS;);
  3296. auto desc = tensor->GetTensorDesc();
  3297. if (desc.GetDataType() == DT_STRING) {
  3298. GeShape tensor_shape = desc.GetShape();
  3299. /// if tensor is a scaler, it's shape size if zero, according ge_tensor.cc.
  3300. /// the logic of GetShapeSize is wrong, the scaler tensor's GetShapeSize is zero
  3301. /// and that of unknown shape is zero too.
  3302. /// unknown shape will not appear here, so we can use zero judge a tensor is scaler or not
  3303. int64_t elem_num = tensor_shape.GetShapeSize();
  3304. if (elem_num == 0 && tensor_shape.GetDims().size() == 0) {
  3305. elem_num = 1;
  3306. }
  3307. uint64_t *buff = reinterpret_cast<uint64_t *>(tensor->MutableData().data());
  3308. GE_CHECK_NOTNULL(buff);
  3309. if (ge::CheckInt64Uint32MulOverflow(elem_num, kBytes * kStringHeadElems) != SUCCESS) {
  3310. GELOGE(FAILED, "[Call][CheckInt64Uint32MulOverflow] Shape size:%ld is invalid", elem_num);
  3311. return FAILED;
  3312. }
  3313. uint64_t offset = elem_num * kBytes * kStringHeadElems;
  3314. uint64_t hbm_raw_data_base_addr =
  3315. static_cast<uint64_t>(reinterpret_cast<uintptr_t>(v_output_addr[0])) + offset;
  3316. for (int64_t i = elem_num - 1; i >= 0; --i) {
  3317. buff[i * kStringHeadElems] = hbm_raw_data_base_addr + (buff[i * kStringHeadElems] - buff[0]);
  3318. }
  3319. }
  3320. GELOGI("[IMAS]InitConstant memcpy graph_%u type[V] name[%s] output[%d] memaddr[%p] mem_size[%lu] datasize[%zu]",
  3321. runtime_param_.graph_id, op_desc->GetName().c_str(), 0, v_output_addr[0], v_output_size[0],
  3322. tensor->GetData().size());
  3323. GE_CHK_RT_RET(rtMemcpy(v_output_addr[0], v_output_size[0], tensor->GetData().data(), tensor->GetData().size(),
  3324. RT_MEMCPY_HOST_TO_DEVICE));
  3325. return SUCCESS;
  3326. }
  3327. ///
  3328. /// @ingroup ge
  3329. /// @brief TVM Op Init.
  3330. /// @return Status
  3331. ///
  3332. Status DavinciModel::InitTbeHandle(const OpDescPtr &op_desc) {
  3333. string bin_file = op_desc->GetName();
  3334. auto kernel = ge_model_->GetTBEKernelStore().FindKernel(op_desc->GetName());
  3335. auto tbe_kernel = (kernel != nullptr) ? kernel : op_desc->TryGetExtAttr(OP_EXTATTR_NAME_TBE_KERNEL, TBEKernelPtr());
  3336. if (tbe_kernel == nullptr) {
  3337. REPORT_INNER_ERROR("E19999", "Get tbe_kernel for op:%s(%s) fail, model_id:%u",
  3338. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3339. GELOGE(INTERNAL_ERROR, "[Check][Param] TBE: %s can't find tvm bin file!", op_desc->GetName().c_str());
  3340. return INTERNAL_ERROR;
  3341. }
  3342. GE_CHK_STATUS_RET(FunctionRegister(op_desc, bin_file, tbe_kernel, false), "Function register of bin file: %s failed",
  3343. bin_file.c_str());
  3344. return SUCCESS;
  3345. }
  3346. Status DavinciModel::InitTbeHandleWithFfts(const OpDescPtr &op_desc) {
  3347. std::vector<OpKernelBinPtr> tbe_kernel;
  3348. tbe_kernel = op_desc->TryGetExtAttr(OP_EXTATTR_NAME_THREAD_TBE_KERNEL, tbe_kernel);
  3349. GELOGD("Kernel bin ptr vec size is %zu.", tbe_kernel.size());
  3350. if (tbe_kernel.size() != kFftsTbeHandleElementSize) {
  3351. REPORT_INNER_ERROR("E19999", "Get tbe_kernel for op:%s(%s) fail, model_id:%u",
  3352. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3353. GELOGE(INTERNAL_ERROR, "[Check][Param] TBE: %s can't find tvm bin file, size is %zu when ffts",
  3354. op_desc->GetName().c_str(), tbe_kernel.size());
  3355. return INTERNAL_ERROR;
  3356. }
  3357. if (tbe_kernel[0] == nullptr || tbe_kernel[1] == nullptr) {
  3358. REPORT_INNER_ERROR("E19999", "Tbe kernel for op:%s is nullptr.", op_desc->GetName().c_str());
  3359. GELOGE(INTERNAL_ERROR, "[Check][Param] TBE: tvm bin file of %s is nullptr when ffts.", op_desc->GetName().c_str());
  3360. return INTERNAL_ERROR;
  3361. }
  3362. vector<string> bin_file_keys;
  3363. (void)AttrUtils::GetListStr(op_desc, kStubFuncName, bin_file_keys);
  3364. if (bin_file_keys.size() != kFftsTbeHandleElementSize) {
  3365. REPORT_INNER_ERROR("E19999", "Get bin_file for op:%s(%s) fail.", op_desc->GetName().c_str(),
  3366. op_desc->GetType().c_str());
  3367. GELOGE(INTERNAL_ERROR, "[Check][Param] TBE: %s can't find bin file keys, size is %zu when ffts",
  3368. op_desc->GetName().c_str(), bin_file_keys.size());
  3369. return INTERNAL_ERROR;
  3370. }
  3371. GE_CHK_STATUS_RET(FunctionRegister(op_desc, bin_file_keys[kNonTailBlock], tbe_kernel[kNonTailBlock], true,
  3372. kNonTailBlock),
  3373. "Function register of first bin file %s failed.", bin_file_keys[kNonTailBlock].c_str());
  3374. GE_CHK_STATUS_RET(FunctionRegister(op_desc, bin_file_keys[kTailBlock], tbe_kernel[kTailBlock], true, kTailBlock),
  3375. "Function register of second bin file %s failed.", bin_file_keys[kTailBlock].c_str());
  3376. return SUCCESS;
  3377. }
  3378. Status DavinciModel::FunctionRegister(const OpDescPtr &op_desc, string &bin_file, OpKernelBinPtr &tbe_kernel,
  3379. bool is_ffts, size_t thread_index) {
  3380. if (thread_index > 1) {
  3381. GELOGE(INTERNAL_ERROR, "[Check][Param] failed. Thread index: %zu should less than 1.", thread_index);
  3382. return INTERNAL_ERROR;
  3383. }
  3384. const char *bin_file_key;
  3385. if (is_ffts) {
  3386. bin_file_key = GetRegisterStub(bin_file, "");
  3387. GELOGI("Node:%s inherit func name:%s directly.", op_desc->GetName().c_str(), bin_file_key);
  3388. } else {
  3389. std::string session_graph_model_id;
  3390. GetUniqueId(op_desc, session_graph_model_id);
  3391. bin_file_key = GetRegisterStub(bin_file, session_graph_model_id); // from set, always valid.
  3392. }
  3393. TBEHandleStore &kernel_store = TBEHandleStore::GetInstance();
  3394. std::lock_guard<std::mutex> lock(tvm_bin_mutex_);
  3395. if (rtQueryFunctionRegistered(bin_file_key) != RT_ERROR_NONE) {
  3396. void *bin_handle = nullptr;
  3397. if (!kernel_store.FindTBEHandle(bin_file_key, bin_handle)) {
  3398. GELOGD("TBE: can't find the kernel_name[%s] in HandleMap", bin_file_key);
  3399. rtDevBinary_t binary;
  3400. GE_CHK_STATUS_RET(InitBinaryMagic(op_desc, is_ffts, thread_index, binary), "Init binary magic of %s failed.",
  3401. op_desc->GetName().c_str());
  3402. binary.version = 0;
  3403. binary.data = tbe_kernel->GetBinData();
  3404. binary.length = tbe_kernel->GetBinDataSize();
  3405. GELOGD("TBE: binary.length: %lu", binary.length);
  3406. GE_CHK_RT_RET(rtDevBinaryRegister(&binary, &bin_handle));
  3407. GE_CHK_STATUS_RET(InitMetaData(op_desc, is_ffts, thread_index, bin_handle), "Init tvm meta data of %s failed.",
  3408. op_desc->GetName().c_str());
  3409. kernel_store.StoreTBEHandle(bin_file_key, bin_handle, tbe_kernel);
  3410. } else {
  3411. GELOGI("TBE: find the kernel_name[%s] in HandleMap", bin_file_key);
  3412. kernel_store.ReferTBEHandle(bin_file_key);
  3413. }
  3414. std::string kernel_name;
  3415. GE_CHK_STATUS_RET(InitKernelName(op_desc, is_ffts, thread_index, kernel_name), "Init kernel name of %s failed.",
  3416. op_desc->GetName().c_str());
  3417. GE_CHK_RT_RET(rtFunctionRegister(bin_handle, bin_file_key, bin_file_key, kernel_name.c_str(), 0));
  3418. used_tbe_handle_map_[bin_file_key] = 1; // Init used num to 1.
  3419. return SUCCESS;
  3420. }
  3421. // Kernel registed, Increase used num in store.
  3422. StoreTbeHandle(bin_file_key);
  3423. return SUCCESS;
  3424. }
  3425. Status DavinciModel::InitBinaryMagic(const OpDescPtr &op_desc, bool is_ffts, size_t thread_index,
  3426. rtDevBinary_t &binary) {
  3427. string json_string;
  3428. const string &tvm_magic = is_ffts ? TVM_ATTR_NAME_THREAD_MAGIC : TVM_ATTR_NAME_MAGIC;
  3429. const static std::map<std::string, uint32_t> binary_magics = {
  3430. {"RT_DEV_BINARY_MAGIC_ELF_AICPU", RT_DEV_BINARY_MAGIC_ELF_AICPU},
  3431. {"RT_DEV_BINARY_MAGIC_ELF", RT_DEV_BINARY_MAGIC_ELF},
  3432. {"RT_DEV_BINARY_MAGIC_ELF_AIVEC", RT_DEV_BINARY_MAGIC_ELF_AIVEC},
  3433. {"RT_DEV_BINARY_MAGIC_ELF_AICUBE", RT_DEV_BINARY_MAGIC_ELF_AICUBE}
  3434. };
  3435. if (is_ffts) {
  3436. vector<string> json_list;
  3437. (void)AttrUtils::GetListStr(op_desc, tvm_magic, json_list);
  3438. if (json_list.size() != kFftsTbeHandleElementSize) {
  3439. GELOGE(INTERNAL_ERROR, "[Check][Param] failed. Attr is %s, thread index is %zu, json list size is %zu.",
  3440. tvm_magic.c_str(), thread_index, json_list.size());
  3441. return INTERNAL_ERROR;
  3442. }
  3443. json_string = json_list[thread_index];
  3444. } else {
  3445. (void)AttrUtils::GetStr(op_desc, tvm_magic, json_string);
  3446. }
  3447. auto iter = binary_magics.find(json_string);
  3448. if (iter == binary_magics.end()) {
  3449. REPORT_INNER_ERROR("E19999", "Attr:%s value:%s in op:%s(%s), model_id:%u, check invalid",
  3450. tvm_magic.c_str(), json_string.c_str(), op_desc->GetName().c_str(),
  3451. op_desc->GetType().c_str(), model_id_);
  3452. GELOGE(PARAM_INVALID, "[Check][Param] Attr:%s value:%s in op:%s(%s), model_id:%u, check invalid",
  3453. TVM_ATTR_NAME_MAGIC.c_str(), json_string.c_str(),
  3454. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3455. return PARAM_INVALID;
  3456. }
  3457. binary.magic = iter->second;
  3458. return SUCCESS;
  3459. }
  3460. Status DavinciModel::InitMetaData(const OpDescPtr &op_desc, bool is_ffts, size_t thread_index, void *bin_handle) {
  3461. string meta_data;
  3462. const string &tvm_metadata = is_ffts ? TVM_ATTR_NAME_THREAD_METADATA : TVM_ATTR_NAME_METADATA;
  3463. if (is_ffts) {
  3464. vector<string> meta_data_list;
  3465. (void)AttrUtils::GetListStr(op_desc, tvm_metadata, meta_data_list);
  3466. if (meta_data_list.size() != kFftsTbeHandleElementSize) {
  3467. GELOGE(INTERNAL_ERROR, "[Check][Param] failed, attr is %s, thread index is %zu, meta data list size is %zu.",
  3468. tvm_metadata.c_str(), thread_index, meta_data_list.size());
  3469. return INTERNAL_ERROR;
  3470. }
  3471. meta_data = meta_data_list[thread_index];
  3472. } else {
  3473. (void)AttrUtils::GetStr(op_desc, tvm_metadata, meta_data);
  3474. }
  3475. GELOGD("TBE: meta data: %s", meta_data.empty() ? "null" : meta_data.c_str());
  3476. if (!meta_data.empty()) {
  3477. GE_CHK_RT_RET(rtMetadataRegister(bin_handle, meta_data.c_str()));
  3478. }
  3479. return SUCCESS;
  3480. }
  3481. Status DavinciModel::InitKernelName(const OpDescPtr &op_desc, bool is_ffts, size_t thread_index, string &kernel_name) {
  3482. if (is_ffts) {
  3483. // delete prefix, eg: *sgt_graph_nodes*/loss_scale/gradient/fp32_vals/Mean_grad/Tile
  3484. vector<string> kernel_name_list;
  3485. auto pos = op_desc->GetName().find("/");
  3486. if (pos == std::string::npos) {
  3487. GELOGE(INTERNAL_ERROR, "[Check][Param] failed, subgraph node name: %s.", op_desc->GetName().c_str());
  3488. return INTERNAL_ERROR;
  3489. }
  3490. string attr_kernel_name = op_desc->GetName().substr(pos + 1) + "_thread_kernelname";
  3491. (void)AttrUtils::GetListStr(op_desc, attr_kernel_name, kernel_name_list);
  3492. if (kernel_name_list.size() != kFftsTbeHandleElementSize) {
  3493. GELOGE(INTERNAL_ERROR, "[Check][Param] failed, attr is %s, thread index is %zu, kernel name list size is %zu.",
  3494. attr_kernel_name.c_str(), thread_index, kernel_name_list.size());
  3495. return INTERNAL_ERROR;
  3496. }
  3497. kernel_name = kernel_name_list[thread_index];
  3498. } else {
  3499. string attr_kernel_name = op_desc->GetName() + "_kernelname";
  3500. (void)AttrUtils::GetStr(op_desc, attr_kernel_name, kernel_name);
  3501. }
  3502. return SUCCESS;
  3503. }
  3504. void DavinciModel::StoreTbeHandle(const std::string &handle_key) {
  3505. // Online mode FE may call rtFunctionRegister.
  3506. TBEHandleStore &kernel_store = TBEHandleStore::GetInstance();
  3507. auto it = used_tbe_handle_map_.find(handle_key);
  3508. if (it != used_tbe_handle_map_.end()) {
  3509. // GE registered, increase reference.
  3510. kernel_store.ReferTBEHandle(handle_key);
  3511. it->second++;
  3512. return;
  3513. }
  3514. void *bin_handle = nullptr;
  3515. if (kernel_store.FindTBEHandle(handle_key, bin_handle)) {
  3516. // GE registered, increase reference.
  3517. used_tbe_handle_map_[handle_key] = 1; // Init used num to 1.
  3518. kernel_store.ReferTBEHandle(handle_key);
  3519. }
  3520. }
  3521. void DavinciModel::CleanTbeHandle() {
  3522. TBEHandleStore &kernel_store = TBEHandleStore::GetInstance();
  3523. kernel_store.EraseTBEHandle(used_tbe_handle_map_);
  3524. used_tbe_handle_map_.clear();
  3525. tvm_bin_kernel_.clear();
  3526. }
  3527. ///
  3528. /// @ingroup ge
  3529. /// @brief insert active_stream_indication_
  3530. /// @return Status
  3531. ///
  3532. Status DavinciModel::InitStreamActive(const OpDescPtr &op_desc) {
  3533. if (op_desc->HasAttr(ATTR_NAME_SWITCH_BRANCH_NODE_LABEL)) {
  3534. std::vector<uint32_t> active_stream_list;
  3535. GE_CHK_BOOL_EXEC(AttrUtils::GetListInt(op_desc, ATTR_NAME_ACTIVE_STREAM_LIST, active_stream_list),
  3536. REPORT_INNER_ERROR("E19999", "[Get][Attr] %s in op:%s(%s) failed, model_id:%u.",
  3537. ATTR_NAME_ACTIVE_STREAM_LIST.c_str(),
  3538. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3539. return INTERNAL_ERROR,
  3540. "[Get][Attr] %s in op:%s(%s) failed, model_id:%u.", ATTR_NAME_ACTIVE_STREAM_LIST.c_str(),
  3541. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3542. for (size_t j = 0; j < active_stream_list.size(); ++j) {
  3543. active_stream_indication_.insert(active_stream_list[j]);
  3544. GELOGI("flowctrl_op_index_map node:%s, active_stream_id=%u.", op_desc->GetName().c_str(), active_stream_list[j]);
  3545. }
  3546. }
  3547. return SUCCESS;
  3548. }
  3549. Status DavinciModel::InitStreamSwitch(const OpDescPtr &op_desc) {
  3550. std::vector<uint32_t> active_stream_list;
  3551. GE_LOGI_IF(!ge::AttrUtils::GetListInt(op_desc, ATTR_NAME_ACTIVE_STREAM_LIST, active_stream_list),
  3552. "GetInt ACTIVE_STREAM_LIST failed.");
  3553. if (active_stream_list.size() != kTrueBranchStreamNum) {
  3554. REPORT_INNER_ERROR("E19999", "Attr:%s active_stream_list.size:%zu in op:%s(%s) != kTrueBranchStreamNum:%u, "
  3555. "model_id:%u, check invalid",
  3556. ATTR_NAME_ACTIVE_STREAM_LIST.c_str(), active_stream_list.size(),
  3557. op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  3558. kTrueBranchStreamNum, model_id_);
  3559. GELOGE(INTERNAL_ERROR, "[Check][Param] Attr:%s active_stream_list.size:%zu in op:%s(%s) != %u, model_id:%u",
  3560. ATTR_NAME_ACTIVE_STREAM_LIST.c_str(), active_stream_list.size(),
  3561. op_desc->GetName().c_str(), op_desc->GetType().c_str(), kTrueBranchStreamNum, model_id_);
  3562. return INTERNAL_ERROR;
  3563. }
  3564. uint32_t true_stream_id = active_stream_list.front();
  3565. active_stream_indication_.insert(true_stream_id);
  3566. GELOGI("flowctrl_op_index_map node:%s, true_stream_id=%u.", op_desc->GetName().c_str(), true_stream_id);
  3567. return SUCCESS;
  3568. }
  3569. Status DavinciModel::InitStreamSwitchN(const OpDescPtr &op_desc) {
  3570. std::vector<uint32_t> active_stream_list;
  3571. if (!AttrUtils::GetListInt(op_desc, ATTR_NAME_ACTIVE_STREAM_LIST, active_stream_list)) {
  3572. REPORT_INNER_ERROR("E19999", "Get Attr:%s from op:%s(%s) fail, model_id:%u", ATTR_NAME_ACTIVE_STREAM_LIST.c_str(),
  3573. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3574. GELOGE(INTERNAL_ERROR, "[Get][Attr] %s from op:%s(%s) fail, model_id:%u", ATTR_NAME_ACTIVE_STREAM_LIST.c_str(),
  3575. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3576. return INTERNAL_ERROR;
  3577. }
  3578. for (size_t j = 0; j < active_stream_list.size(); ++j) {
  3579. active_stream_indication_.insert(active_stream_list[j]);
  3580. GELOGI("StreamSwitchNOp node:%s, active_stream_id=%u.", op_desc->GetName().c_str(), active_stream_list[j]);
  3581. }
  3582. uint32_t batch_num = 0;
  3583. if (!AttrUtils::GetInt(op_desc, ATTR_NAME_BATCH_NUM, batch_num)) {
  3584. REPORT_INNER_ERROR("E19999", "Get Attr:%s from op:%s(%s) fail, model_id:%u", ATTR_NAME_BATCH_NUM.c_str(),
  3585. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3586. GELOGE(FAILED, "[Get][Attr] %s from op:%s(%s) fail, model_id:%u", ATTR_NAME_BATCH_NUM.c_str(),
  3587. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3588. return FAILED;
  3589. }
  3590. return SetDynamicBatchInfo(op_desc, batch_num);
  3591. }
  3592. Status DavinciModel::SetDynamicBatchInfo(const OpDescPtr &op_desc, uint32_t batch_num) {
  3593. batch_info_.clear();
  3594. combined_batch_info_.clear();
  3595. (void)AttrUtils::GetInt(op_desc, ATTR_DYNAMIC_TYPE, dynamic_type_);
  3596. (void)AttrUtils::GetListStr(op_desc, ATTR_USER_DESIGNEATE_SHAPE_ORDER, user_designate_shape_order_);
  3597. for (uint32_t i = 0; i < batch_num; ++i) {
  3598. std::vector<int64_t> batch_shape;
  3599. const std::string attr_name = ATTR_NAME_PRED_VALUE + "_" + std::to_string(i);
  3600. if (!AttrUtils::GetListInt(op_desc, attr_name, batch_shape)) {
  3601. REPORT_INNER_ERROR("E19999", "Get Attr:%s from op:%s(%s) fail, model_id:%u", attr_name.c_str(),
  3602. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3603. GELOGE(FAILED, "[Get][Attr] %s from op:%s(%s) fail, model_id:%u", attr_name.c_str(),
  3604. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3605. batch_info_.clear();
  3606. return FAILED;
  3607. }
  3608. batch_info_.emplace_back(batch_shape);
  3609. batch_shape.clear();
  3610. const string attr_combined_batch = ATTR_NAME_COMBINED_BATCH + "_" + std::to_string(i);
  3611. if (AttrUtils::GetListInt(op_desc, attr_combined_batch, batch_shape)) {
  3612. combined_batch_info_.emplace_back(batch_shape);
  3613. }
  3614. }
  3615. return SUCCESS;
  3616. }
  3617. Status DavinciModel::InitCase(const OpDescPtr &op_desc) {
  3618. uint32_t batch_num = 0;
  3619. if (!AttrUtils::GetInt(op_desc, ATTR_NAME_BATCH_NUM, batch_num)) {
  3620. GELOGI("Not multi-batch Node: %s", op_desc->GetName().c_str());
  3621. return SUCCESS;
  3622. }
  3623. return SetDynamicBatchInfo(op_desc, batch_num);
  3624. }
  3625. bool DavinciModel::IsBroadCastOpData(const ge::NodePtr &var_node) {
  3626. for (auto out_anchor : var_node->GetAllOutDataAnchors()) {
  3627. GE_RT_FALSE_CHECK_NOTNULL(out_anchor);
  3628. for (auto in_anchor : out_anchor->GetPeerInDataAnchors()) {
  3629. GE_RT_FALSE_CHECK_NOTNULL(in_anchor);
  3630. ge::NodePtr dst_node = in_anchor->GetOwnerNode();
  3631. GE_RT_FALSE_CHECK_NOTNULL(dst_node);
  3632. if (dst_node->GetType() == HCOMBROADCAST || dst_node->GetType() == HVDCALLBACKBROADCAST) {
  3633. return true;
  3634. }
  3635. }
  3636. }
  3637. return false;
  3638. }
  3639. ///
  3640. /// @ingroup ge
  3641. /// @brief Init model stream for NN model.
  3642. /// @param [in] stream user input model stream.
  3643. /// @return Status
  3644. ///
  3645. Status DavinciModel::InitModelStream(rtStream_t stream) {
  3646. ExecuteMode curr_mode = is_async_mode_ ? ASYNCHRONIZATION : SYNCHRONIZATION;
  3647. GE_CHK_BOOL_RET_STATUS((curr_mode == last_execute_mode_) || (last_execute_mode_ == INITIALIZATION), INTERNAL_ERROR,
  3648. "[Check][Param] NnExecute not support mix execute.");
  3649. last_execute_mode_ = curr_mode;
  3650. // asynchronize mode, use user input stream.
  3651. if (is_async_mode_) {
  3652. rt_model_stream_ = stream;
  3653. is_inner_model_stream_ = false;
  3654. return SUCCESS;
  3655. }
  3656. // synchronize mode, use forbidden stream.
  3657. if (stream != nullptr) {
  3658. if ((rt_model_stream_ != nullptr) && is_inner_model_stream_) {
  3659. GE_LOGW_IF(rtStreamDestroy(rt_model_stream_) != RT_ERROR_NONE, "Destroy rt_stream failed!");
  3660. }
  3661. rt_model_stream_ = stream;
  3662. is_inner_model_stream_ = false;
  3663. return SUCCESS;
  3664. }
  3665. if (rt_model_stream_ == nullptr) {
  3666. GE_CHK_RT_RET(rtStreamCreateWithFlags(&rt_model_stream_, priority_, RT_STREAM_FORBIDDEN_DEFAULT));
  3667. is_inner_model_stream_ = true;
  3668. }
  3669. return SUCCESS;
  3670. }
  3671. ///
  3672. /// @ingroup ge
  3673. /// @brief ACL case, do not start new thread, return execute result.
  3674. /// @param [in] stream execute model stream.
  3675. /// @param [in] async_mode is asynchronize mode.
  3676. /// @param [in] input_data model input data.
  3677. /// @param [out] output_data model output data.
  3678. ///
  3679. Status DavinciModel::NnExecute(rtStream_t stream, bool async_mode, const InputData &input_data,
  3680. OutputData &output_data) {
  3681. is_async_mode_ = async_mode;
  3682. GELOGD("Model Run begin, model id:%u, data index:%u, flag:%d.", model_id_, input_data.index, is_async_mode_);
  3683. GE_CHK_STATUS_RET(InitModelStream(stream), "[Init][ModelStream] failed, model_id:%u.", model_id_);
  3684. is_dynamic_ = input_data.is_dynamic_batch;
  3685. bool profiling_model_execute_on = ProfilingManager::Instance().ProfilingModelExecuteOn();
  3686. GE_IF_BOOL_EXEC(profiling_model_execute_on, SetProfileTime(MODEL_PRE_PROC_START));
  3687. Status ret = CopyModelData(input_data, output_data, is_dynamic_);
  3688. GE_CHK_BOOL_TRUE_EXEC_WITH_LOG(ret != SUCCESS, return ret,
  3689. "[Copy][ModelData] failed. model id: %u", model_id_);
  3690. GELOGD("current_data.index=%u", input_data.index);
  3691. GE_IF_BOOL_EXEC(profiling_model_execute_on, SetProfileTime(MODEL_PRE_PROC_END));
  3692. if (!task_list_.empty()) {
  3693. uint64_t index_id = iterator_count_ + 1;
  3694. uint64_t model_id = static_cast<uint64_t>(model_id_);
  3695. int32_t device_id = static_cast<int32_t>(device_id_);
  3696. // tag_id 0 means step begin, 1 meas step end.
  3697. GE_CHK_STATUS_RET_NOLOG(
  3698. ProfilingManager::Instance().ProfileStepInfo(index_id, model_id, 0, rt_model_stream_, device_id));
  3699. GELOGD("rtModelExecute do");
  3700. GE_IF_BOOL_EXEC(profiling_model_execute_on, SetProfileTime(MODEL_INFER_START));
  3701. rtError_t rt_ret = rtModelExecute(rt_model_handle_, rt_model_stream_, 0);
  3702. GE_CHK_RT_EXEC(rt_ret, return RT_ERROR_TO_GE_STATUS(rt_ret));
  3703. GE_IF_BOOL_EXEC(profiling_model_execute_on, SetProfileTime(MODEL_INFER_END));
  3704. GELOGD("rtModelExecute end");
  3705. GE_CHK_STATUS_RET_NOLOG(
  3706. ProfilingManager::Instance().ProfileStepInfo(index_id, model_id, 1, rt_model_stream_, device_id));
  3707. iterator_count_++;
  3708. }
  3709. GE_IF_BOOL_EXEC(profiling_model_execute_on, SetProfileTime(MODEL_AFTER_PROC_START));
  3710. ret = CopyOutputData(input_data.index, output_data, RT_MEMCPY_DEVICE_TO_DEVICE);
  3711. GE_CHK_BOOL_TRUE_EXEC_WITH_LOG(ret != SUCCESS, return ACL_ERROR_GE_INTERNAL_ERROR,
  3712. "[Copy][OutputData] to user failed, ret:%d, model_id:%u.", ret, model_id_);
  3713. GE_IF_BOOL_EXEC(profiling_model_execute_on, SetProfileTime(MODEL_AFTER_PROC_END));
  3714. // report model time data
  3715. GE_IF_BOOL_EXEC(profiling_model_execute_on, (void)SinkTimeProfile(input_data));
  3716. GELOGD("Model run end, model id:%u", model_id_);
  3717. return SUCCESS;
  3718. }
  3719. // Add active entry stream for special env.
  3720. Status DavinciModel::AddHeadStream() {
  3721. if (active_stream_list_.empty()) {
  3722. REPORT_INNER_ERROR("E19999", "active_stream_list is empty in model:%u, check invalid", model_id_);
  3723. GELOGE(INTERNAL_ERROR, "[Check][Param] active_stream_list is empty in model:%u, check invalid", model_id_);
  3724. return INTERNAL_ERROR;
  3725. }
  3726. if (active_stream_list_.size() == 1) {
  3727. GELOGI("Just one active stream, take as head stream.");
  3728. rt_head_stream_ = active_stream_list_[0];
  3729. is_pure_head_stream_ = false;
  3730. } else {
  3731. // Create stream which rt_model_handel running on, this is S0, TS stream.
  3732. GELOGI("Multiple active stream: %zu, create head stream.", active_stream_list_.size());
  3733. GE_CHK_RT_RET(rtStreamCreateWithFlags(&rt_head_stream_, priority_, RT_STREAM_PERSISTENT));
  3734. GE_CHK_RT_RET(rtModelBindStream(rt_model_handle_, rt_head_stream_, RT_INVALID_FLAG)); // Not active.
  3735. is_pure_head_stream_ = true;
  3736. for (auto s : active_stream_list_) {
  3737. std::shared_ptr<CpuTaskActiveEntry> active_entry = MakeShared<CpuTaskActiveEntry>(rt_head_stream_);
  3738. if (active_entry == nullptr) {
  3739. REPORT_CALL_ERROR("E19999", "New CpuTaskActiveEntry failed, model_id:%u", model_id_);
  3740. GELOGE(MEMALLOC_FAILED, "[New][CpuTaskActiveEntry] task failed, model_id:%u", model_id_);
  3741. return MEMALLOC_FAILED;
  3742. }
  3743. Status status = active_entry->Init(s);
  3744. if (status != SUCCESS) {
  3745. return status;
  3746. }
  3747. cpu_task_list_.emplace_back(active_entry);
  3748. }
  3749. }
  3750. // Create entry stream active head stream. AICPU stream.
  3751. GE_CHK_RT_RET(rtStreamCreateWithFlags(&rt_entry_stream_, priority_, RT_STREAM_AICPU));
  3752. GE_CHK_RT_RET(rtModelBindStream(rt_model_handle_, rt_entry_stream_, RT_HEAD_STREAM));
  3753. return SUCCESS;
  3754. }
  3755. Status DavinciModel::InitEntryTask() {
  3756. if (deploy_type_ == AICPU_DEPLOY_CROSS_THREAD) {
  3757. GE_CHK_STATUS_RET(AddHeadStream(), "[Add][HeadStream] failed.");
  3758. return CpuActiveStream();
  3759. } else {
  3760. return LoadWithQueue();
  3761. }
  3762. }
  3763. uint8_t *DavinciModel::MallocFeatureMapMem(size_t data_size) {
  3764. uint8_t *mem_base = nullptr;
  3765. const string purpose("feature map,used for op input and output.");
  3766. char ge_static_mem_env[MMPA_MAX_PATH] = {0x00};
  3767. INT32 res = mmGetEnv(kEnvGeuseStaticMemory, ge_static_mem_env, MMPA_MAX_PATH);
  3768. if (res == EN_OK) {
  3769. data_size = static_cast<size_t>(VarManager::Instance(session_id_)->GetGraphMemoryMaxSize());
  3770. string memory_key = std::to_string(0) + "_f";
  3771. mem_base =
  3772. MemManager::Instance().MemInstance(RT_MEMORY_HBM).MallocMemory(purpose, memory_key, data_size, GetDeviceId());
  3773. } else {
  3774. mem_base = MemManager::Instance().MemInstance(RT_MEMORY_HBM).MallocMemory(purpose, data_size, GetDeviceId());
  3775. }
  3776. if (mem_base != nullptr) {
  3777. GE_CHK_RT(rtMemset(mem_base, data_size, 0U, data_size));
  3778. }
  3779. return mem_base;
  3780. }
  3781. Status DavinciModel::MallocExMem() {
  3782. char ge_static_mem_env[MMPA_MAX_PATH] = {0x00};
  3783. INT32 res_static_memory = mmGetEnv(kEnvGeuseStaticMemory, ge_static_mem_env, MMPA_MAX_PATH);
  3784. for (auto &it : runtime_param_.memory_infos) {
  3785. auto mem_size = it.second.memory_size;
  3786. if (mem_size == 0) {
  3787. continue;
  3788. }
  3789. bool sessoion_scope = ((kSessionScopeMemory & it.first) == kSessionScopeMemory);
  3790. auto mem_type = it.first & kMemoryTypeMask;
  3791. uint8_t *mem_base = nullptr;
  3792. const string purpose("p2p memory, used for some op related to hcom or session scope memory");
  3793. if (sessoion_scope) {
  3794. mem_base = MemManager::Instance().SessionScopeMemInstance(mem_type).Malloc(mem_size, runtime_param_.session_id);
  3795. } else if (res_static_memory == EN_OK) {
  3796. string memory_key = std::to_string(0) + it.second.memory_key;
  3797. mem_base =
  3798. MemManager::Instance().MemInstance(mem_type).MallocMemory(purpose, memory_key, mem_size, GetDeviceId());
  3799. } else {
  3800. mem_base = MemManager::Instance().MemInstance(mem_type).MallocMemory(purpose, mem_size, GetDeviceId());
  3801. }
  3802. if (mem_base == nullptr) {
  3803. REPORT_CALL_ERROR("E19999", "MallocExMem fail, type:%ld size:%zu, model_id:%u, check invalid",
  3804. mem_type, mem_size, model_id_);
  3805. GELOGE(ACL_ERROR_GE_MEMORY_ALLOCATION, "Alloc ex memory failed, type:%ld size: %zu", mem_type, mem_size);
  3806. return ACL_ERROR_GE_MEMORY_ALLOCATION;
  3807. }
  3808. it.second.memory_base = mem_base;
  3809. GELOGI("InitFeatureMapAndP2PMem graph_%u MallocMemory type[F] mem_type[%ld] mem_addr[%p] mem_size[%zu]",
  3810. runtime_param_.graph_id, mem_type, mem_base, mem_size);
  3811. }
  3812. return SUCCESS;
  3813. }
  3814. uint8_t *DavinciModel::MallocWeightsMem(size_t weights_size) {
  3815. uint8_t *weights_mem_base = nullptr;
  3816. const string purpose("weights memory in inference network.");
  3817. char ge_static_mem_env[MMPA_MAX_PATH] = {0x00};
  3818. INT32 res = mmGetEnv(kEnvGeuseStaticMemory, ge_static_mem_env, MMPA_MAX_PATH);
  3819. if (res == EN_OK) {
  3820. string weight_memory_key = std::to_string(0) + "_w";
  3821. weights_mem_base = MemManager::Instance()
  3822. .MemInstance(RT_MEMORY_HBM)
  3823. .MallocMemory(purpose, weight_memory_key, weights_size, GetDeviceId());
  3824. } else {
  3825. weights_mem_base =
  3826. MemManager::Instance().MemInstance(RT_MEMORY_HBM).MallocMemory(purpose, weights_size, GetDeviceId());
  3827. }
  3828. return weights_mem_base;
  3829. }
  3830. void DavinciModel::FreeFeatureMapMem() {
  3831. char ge_static_mem_env[MMPA_MAX_PATH] = {0x00};
  3832. INT32 res = mmGetEnv(kEnvGeuseStaticMemory, ge_static_mem_env, MMPA_MAX_PATH);
  3833. if (res == EN_OK && is_inner_mem_base_) {
  3834. string weight_memory_key = std::to_string(0) + "_f";
  3835. if (MemManager::Instance().MemInstance(RT_MEMORY_HBM).GetMemoryAddr(weight_memory_key) != nullptr) {
  3836. GE_CHK_STATUS(MemManager::Instance().MemInstance(RT_MEMORY_HBM).FreeMemory(weight_memory_key, GetDeviceId()),
  3837. "failed to free weight memory");
  3838. }
  3839. mem_base_ = nullptr;
  3840. } else {
  3841. GE_IF_BOOL_EXEC(
  3842. mem_base_ != nullptr && is_inner_mem_base_,
  3843. GE_CHK_STATUS(MemManager::Instance().MemInstance(RT_MEMORY_HBM).FreeMemory(mem_base_, GetDeviceId()),
  3844. "failed to free feature_map memory");
  3845. mem_base_ = nullptr);
  3846. }
  3847. }
  3848. void DavinciModel::FreeExMem() {
  3849. char ge_static_mem_env[MMPA_MAX_PATH] = {0x00};
  3850. INT32 res_static_memory = mmGetEnv(kEnvGeuseStaticMemory, ge_static_mem_env, MMPA_MAX_PATH);
  3851. for (auto &it : runtime_param_.memory_infos) {
  3852. // free when session destory
  3853. if ((kSessionScopeMemory & it.first) == kSessionScopeMemory) {
  3854. continue;
  3855. }
  3856. auto mem_type = it.first & kMemoryTypeMask;
  3857. if (res_static_memory == EN_OK) {
  3858. std::string memory_key = std::to_string(0) + it.second.memory_key;
  3859. if (MemManager::Instance().MemInstance(mem_type).GetMemoryAddr(memory_key) != nullptr) {
  3860. GE_CHK_STATUS(MemManager::Instance().MemInstance(mem_type).FreeMemory(memory_key, GetDeviceId()),
  3861. "failed to free memory");
  3862. }
  3863. it.second.memory_base = nullptr;
  3864. } else {
  3865. GE_IF_BOOL_EXEC(
  3866. it.second.memory_base != nullptr,
  3867. GE_CHK_STATUS(MemManager::Instance().MemInstance(mem_type).FreeMemory(it.second.memory_base, GetDeviceId()),
  3868. "failed to free memory");
  3869. it.second.memory_base = nullptr);
  3870. }
  3871. }
  3872. }
  3873. void DavinciModel::FreeWeightsMem() {
  3874. char ge_static_mem_env[MMPA_MAX_PATH] = {0x00};
  3875. INT32 res = mmGetEnv(kEnvGeuseStaticMemory, ge_static_mem_env, MMPA_MAX_PATH);
  3876. if (res == EN_OK) {
  3877. string memory_key = std::to_string(0) + "_w";
  3878. if (MemManager::Instance().MemInstance(RT_MEMORY_HBM).GetMemoryAddr(memory_key) != nullptr) {
  3879. GE_CHK_STATUS(MemManager::Instance().MemInstance(RT_MEMORY_HBM).FreeMemory(memory_key, GetDeviceId()),
  3880. "failed to free feature_map memory");
  3881. }
  3882. weights_mem_base_ = nullptr;
  3883. } else {
  3884. GE_IF_BOOL_EXEC(
  3885. weights_mem_base_ != nullptr && weights_mem_base_ != mem_base_ && is_inner_weight_base_,
  3886. GE_CHK_STATUS(MemManager::Instance().MemInstance(RT_MEMORY_HBM).FreeMemory(weights_mem_base_, GetDeviceId()),
  3887. "failed to free weight memory");
  3888. weights_mem_base_ = nullptr);
  3889. }
  3890. }
  3891. Status DavinciModel::TransAllVarData(ComputeGraphPtr &graph, uint32_t graph_id) {
  3892. rtContext_t ctx = nullptr;
  3893. rtError_t rt_ret = rtCtxGetCurrent(&ctx);
  3894. if (rt_ret != RT_ERROR_NONE) {
  3895. REPORT_CALL_ERROR("E19999", "Call rtCtxGetCurrent failed, model_id:%u", model_id_);
  3896. GELOGE(RT_FAILED, "[Call][RtCtxGetCurrent] failed, ret:0x%X, model_id:%u.", rt_ret, model_id_);
  3897. return RT_ERROR_TO_GE_STATUS(rt_ret);
  3898. }
  3899. std::vector<NodePtr> variable_node_list;
  3900. for (ge::NodePtr &node : graph->GetAllNodes()) {
  3901. if (node == nullptr) {
  3902. continue;
  3903. }
  3904. if (node->GetType() != VARIABLE) {
  3905. continue;
  3906. }
  3907. variable_node_list.emplace_back(node);
  3908. }
  3909. GE_CHK_STATUS_RET_NOLOG(
  3910. TransVarDataUtils::TransAllVarData(variable_node_list, session_id_, ctx, graph_id, kThreadNum));
  3911. return SUCCESS;
  3912. }
  3913. void DavinciModel::SetDataDumperArgs(const ComputeGraphPtr &graph, const map<string, OpDescPtr> &variable_by_name) {
  3914. if(dump_model_name_.empty()) {
  3915. dump_model_name_ = name_;
  3916. }
  3917. data_dumper_.SetModelName(dump_model_name_);
  3918. data_dumper_.SetModelId(model_id_);
  3919. data_dumper_.SetOmName(om_name_);
  3920. data_dumper_.SetComputeGraph(graph);
  3921. data_dumper_.SetRefInfo(saved_task_addrs_);
  3922. int32_t device_id = 0;
  3923. rtError_t rt_ret = rtGetDevice(&device_id);
  3924. if (rt_ret != RT_ERROR_NONE || device_id < 0) {
  3925. REPORT_CALL_ERROR("E19999", "Call rtGetDevice failed, model_id:%u", model_id_);
  3926. GELOGE(RT_FAILED, "[Call][RtGetDevice] failed, ret = 0x%X, device_id = %d.", rt_ret, device_id);
  3927. return;
  3928. }
  3929. data_dumper_.SetDeviceId(device_id);
  3930. if (known_node_) {
  3931. data_dumper_.SetLoopAddr(global_step_addr_, nullptr, nullptr);
  3932. } else {
  3933. // set loop count addr
  3934. auto get_var_addr = [&](const string &name) -> void *{
  3935. const auto it = variable_by_name.find(name);
  3936. if (it != variable_by_name.end()) {
  3937. const auto output_sizes = ModelUtils::GetOutputSize(it->second);
  3938. const auto output_addrs = ModelUtils::GetOutputDataAddrs(runtime_param_, it->second);
  3939. if (output_sizes.empty() || output_addrs.empty()) {
  3940. return nullptr;
  3941. }
  3942. return output_addrs[0];
  3943. }
  3944. GELOGD("op: %s is null.", name.c_str());
  3945. return nullptr;
  3946. };
  3947. data_dumper_.SetLoopAddr(get_var_addr(NODE_NAME_GLOBAL_STEP),
  3948. get_var_addr(NODE_NAME_FLOWCTRL_LOOP_PER_ITER),
  3949. get_var_addr(NODE_NAME_FLOWCTRL_LOOP_COND));
  3950. }
  3951. }
  3952. uint32_t DavinciModel::GetFlowctrlIndex(uint32_t op_index) {
  3953. std::lock_guard<std::mutex> lock(flowctrl_op_index_internal_map_mutex_);
  3954. return (++flowctrl_op_index_internal_map_[op_index]) - 1;
  3955. }
  3956. void DavinciModel::PushHcclStream(rtStream_t value) {
  3957. std::lock_guard<std::mutex> lock(all_hccl_stream_list_mutex_);
  3958. all_hccl_stream_list_.push_back(value);
  3959. }
  3960. void DavinciModel::SaveHcclFollowStream(int64_t main_stream_id, rtStream_t stream) {
  3961. std::lock_guard<std::mutex> lock(capacity_of_stream_mutex_);
  3962. main_follow_stream_mapping_[main_stream_id].emplace_back(stream);
  3963. }
  3964. void DavinciModel::SetTotalFixedAddrsSize(string tensor_name, int64_t fix_addr_size) {
  3965. if (tensor_name_to_fixed_addr_size_.find(tensor_name) == tensor_name_to_fixed_addr_size_.end()) {
  3966. tensor_name_to_fixed_addr_size_[tensor_name] = total_fixed_addr_size_;
  3967. total_fixed_addr_size_ += fix_addr_size;
  3968. }
  3969. }
  3970. Status DavinciModel::InitOrigInputInfo(uint32_t index, const OpDescPtr &op_desc) {
  3971. if (!op_desc->HasAttr(ATTR_NAME_AIPP_INPUTS) || !op_desc->HasAttr(ATTR_NAME_AIPP_OUTPUTS)) {
  3972. GELOGI("there is not AIPP related with index %u, node: %s.", index, op_desc->GetName().c_str());
  3973. return SUCCESS;
  3974. }
  3975. vector<string> inputs;
  3976. if (AttrUtils::GetListStr(op_desc, ATTR_NAME_AIPP_INPUTS, inputs) && !inputs.empty()) {
  3977. std::string input = inputs[kAippOriginInputIndex];
  3978. GELOGI("origin input str: %s.", input.c_str());
  3979. std::vector<std::string> infos = ge::StringUtils::Split(input, ':');
  3980. if (infos.size() != kAippInfoNum) {
  3981. REPORT_INNER_ERROR("E19999", "Attr:%s in op:%s(%s), aipp input size:%zu != kAippInfoNum:%u, model_id:%u, "
  3982. "check invalid", ATTR_NAME_AIPP_INPUTS.c_str(),
  3983. op_desc->GetName().c_str(), op_desc->GetType().c_str(), infos.size(), kAippInfoNum,
  3984. model_id_);
  3985. GELOGE(ACL_ERROR_GE_AIPP_MODE_INVALID, "[Check][Param] Attr:%s in op:%s(%s), "
  3986. "aipp input size:%zu != kAippInfoNum:%u, model_id:%u", ATTR_NAME_AIPP_INPUTS.c_str(),
  3987. op_desc->GetName().c_str(), op_desc->GetType().c_str(), infos.size(), kAippInfoNum, model_id_);
  3988. return ACL_ERROR_GE_AIPP_MODE_INVALID;
  3989. }
  3990. OriginInputInfo input_info;
  3991. input_info.format = TypeUtils::SerialStringToFormat(infos[kAippInfoFormat]);
  3992. input_info.data_type = TypeUtils::SerialStringToDataType(infos[kAippInfoDataType]);
  3993. input_info.dim_num = std::strtol(infos[kAippInfoDimNum].c_str(), nullptr, kDecimal);
  3994. orig_input_info_[index] = input_info;
  3995. } else {
  3996. OriginInputInfo input_info = { FORMAT_RESERVED, DT_UNDEFINED, 0 };
  3997. orig_input_info_[index] = input_info;
  3998. }
  3999. return SUCCESS;
  4000. }
  4001. Status DavinciModel::GetOrigInputInfo(uint32_t index, OriginInputInfo &orig_input_info) const {
  4002. const auto it = orig_input_info_.find(index);
  4003. if (it == orig_input_info_.end()) {
  4004. REPORT_INNER_ERROR("E19999", "Get index:%u from orig_input_info_ fail, model_id:%u", index, model_id_);
  4005. GELOGE(ACL_ERROR_GE_AIPP_NOT_EXIST, "[Check][Param] Get index:%u from orig_input_info_ fail, model_id:%u",
  4006. index, model_id_);
  4007. return ACL_ERROR_GE_AIPP_NOT_EXIST;
  4008. }
  4009. const OriginInputInfo &input_info = it->second;
  4010. if (input_info.format != FORMAT_RESERVED || input_info.data_type != DT_UNDEFINED) {
  4011. orig_input_info = input_info;
  4012. }
  4013. return SUCCESS;
  4014. }
  4015. void DavinciModel::ParseAIPPInfo(std::string in_out_info, InputOutputDims &dims_info) {
  4016. GELOGI("ParseAIPPInfo: origin str: %s", in_out_info.c_str());
  4017. std::vector<std::string> infos = ge::StringUtils::Split(in_out_info, ':');
  4018. if (infos.size() != kAippInfoNum) {
  4019. REPORT_INNER_ERROR("E19999", "in_out_info:%s size:%zu != kAippInfoNum:%u, model_id:%u, "
  4020. "check invalid", in_out_info.c_str(), infos.size(), kAippInfoNum,
  4021. model_id_);
  4022. GELOGE(ACL_ERROR_GE_AIPP_MODE_INVALID, "[Check][Param] in_out_info:%s size:%zu != kAippInfoNum:%u, model_id:%u",
  4023. in_out_info.c_str(), infos.size(), kAippInfoNum, model_id_);
  4024. return;
  4025. }
  4026. dims_info.name = infos[kAippInfoTensorName];
  4027. dims_info.size = std::strtol(infos[kAippInfoTensorSize].c_str(), nullptr, kDecimal);
  4028. dims_info.dim_num = std::strtol(infos[kAippInfoDimNum].c_str(), nullptr, kDecimal);
  4029. std::vector<std::string> dims = ge::StringUtils::Split(infos[kAippInfoShape], ',');
  4030. for (const auto &dim : dims) {
  4031. if (dim.empty()) {
  4032. continue;
  4033. }
  4034. dims_info.dims.emplace_back(std::strtol(dim.c_str(), nullptr, kDecimal));
  4035. }
  4036. }
  4037. Status DavinciModel::InitAippInputOutputDims(uint32_t index, const OpDescPtr &op_desc) {
  4038. if (!op_desc->HasAttr(ATTR_NAME_AIPP_INPUTS) || !op_desc->HasAttr(ATTR_NAME_AIPP_OUTPUTS)) {
  4039. GELOGI("There is not AIPP related with index %u.", index);
  4040. return SUCCESS;
  4041. }
  4042. vector<string> inputs;
  4043. vector<InputOutputDims> input_dims;
  4044. if (AttrUtils::GetListStr(op_desc, ATTR_NAME_AIPP_INPUTS, inputs) && !inputs.empty()) {
  4045. GELOGI("Data: %s has %zu related aippInfo.", op_desc->GetName().c_str(), inputs.size());
  4046. for (auto it : inputs) {
  4047. InputOutputDims input_info;
  4048. ParseAIPPInfo(it, input_info);
  4049. input_dims.emplace_back(input_info);
  4050. GELOGD("Aipp origin input dims info: %s", it.c_str());
  4051. ConstGeTensorDescPtr data_input_desc = op_desc->GetInputDescPtr(kDataIndex);
  4052. int64_t data_input_size;
  4053. (void)TensorUtils::GetSize(*(op_desc->GetInputDescPtr(kDataIndex)), data_input_size);
  4054. GELOGD("Related Data[%d]: tensor_name: %s, dim_num: %zu, tensor_size: %zu, format: %s, data_type: %s, shape: %s.",
  4055. index, op_desc->GetName().c_str(), data_input_desc->GetShape().GetDimNum(), data_input_size,
  4056. TypeUtils::FormatToSerialString(data_input_desc->GetFormat()).c_str(),
  4057. TypeUtils::DataTypeToSerialString(data_input_desc->GetDataType()).c_str(),
  4058. formats::JoinToString(data_input_desc->GetShape().GetDims()).c_str());
  4059. }
  4060. }
  4061. vector<string> outputs;
  4062. vector<InputOutputDims> output_dims;
  4063. if (AttrUtils::GetListStr(op_desc, ATTR_NAME_AIPP_OUTPUTS, outputs) && !outputs.empty()) {
  4064. for (auto it : outputs) {
  4065. InputOutputDims output_info;
  4066. ParseAIPPInfo(it, output_info);
  4067. output_dims.emplace_back(output_info);
  4068. GELOGD("Aipp output dims info: %s", it.c_str());
  4069. }
  4070. }
  4071. aipp_dims_info_[index] = { input_dims, input_dims };
  4072. return SUCCESS;
  4073. }
  4074. Status DavinciModel::GetAllAippInputOutputDims(uint32_t index, vector<InputOutputDims> &input_dims,
  4075. vector<InputOutputDims> &output_dims) const {
  4076. const auto it = aipp_dims_info_.find(index);
  4077. if (it == aipp_dims_info_.end()) {
  4078. REPORT_INNER_ERROR("E19999", "Get index:%u from aipp_dims_info_ fail, model_id:%u", index, model_id_);
  4079. GELOGE(ACL_ERROR_GE_AIPP_NOT_EXIST, "[Check][Param] Get index:%u from aipp_dims_info_ fail, model_id:%u",
  4080. index, model_id_);
  4081. return ACL_ERROR_GE_AIPP_NOT_EXIST;
  4082. }
  4083. input_dims = it->second.first;
  4084. output_dims = it->second.second;
  4085. return SUCCESS;
  4086. }
  4087. int64_t DavinciModel::GetFixedAddrsSize(string tensor_name) {
  4088. if (tensor_name_to_fixed_addr_size_.find(tensor_name) != tensor_name_to_fixed_addr_size_.end()) {
  4089. return tensor_name_to_fixed_addr_size_[tensor_name];
  4090. } else {
  4091. return total_fixed_addr_size_;
  4092. }
  4093. }
  4094. Status DavinciModel::InitL1DataDumperArgs() {
  4095. auto all_dump_model = GetDumpProperties().GetAllDumpModel();
  4096. bool find_by_om_name = all_dump_model.find(om_name_) != all_dump_model.end();
  4097. bool find_by_model_name = all_dump_model.find(dump_model_name_) != all_dump_model.end();
  4098. bool dump_l1fusion_op =
  4099. (all_dump_model.find(ge::DUMP_ALL_MODEL) != all_dump_model.end()) || find_by_om_name || find_by_model_name;
  4100. if (dump_l1fusion_op) {
  4101. // malloc 2M for dump l1fusion op
  4102. GE_CHK_RT_RET(rtMalloc(&l1_fusion_addr_, kDumpL1FusionOpMByteSize, RT_MEMORY_DDR));
  4103. // send l1fusion dump addr to rts
  4104. if (rtDumpAddrSet(rt_model_handle_, l1_fusion_addr_, kDumpL1FusionOpMByteSize, kDumpFlagOfL1Fusion) !=
  4105. RT_ERROR_NONE) {
  4106. // l1_fusion_addr_ will be free when DavinciModel destruct
  4107. REPORT_CALL_ERROR("E19999", "Call rtDumpAddrSet failed, model_id:%u", model_id_);
  4108. GELOGE(FAILED, "[Call][RtDumpAddrSet] failed, model_id:%u", model_id_);
  4109. return FAILED;
  4110. }
  4111. // set addr for l1 data dump
  4112. data_dumper_.SetL1FusionAddr(l1_fusion_addr_);
  4113. }
  4114. return SUCCESS;
  4115. }
  4116. Status DavinciModel::SetRunAsyncListenerCallback(const RunAsyncCallback &callback) {
  4117. auto listener = dynamic_cast<RunAsyncListener *>(listener_.get());
  4118. GE_CHECK_NOTNULL(listener);
  4119. listener->SetCallback(callback);
  4120. return SUCCESS;
  4121. }
  4122. void DavinciModel::UpdateOpIOAddrs(uint32_t task_id, uint32_t stream_id, const std::vector<void *> &io_addrs) {
  4123. if (fixed_mem_base_ == reinterpret_cast<uintptr_t>(mem_base_)) {
  4124. GELOGD("[Update][OpIOAddrs] No need to update op input output addr.");
  4125. return;
  4126. }
  4127. OpDescInfo *op_desc_info = exception_dumper_.MutableOpDescInfo(task_id, stream_id);
  4128. if (op_desc_info == nullptr) {
  4129. GELOGW("[Update][OpIOAddrs] Find op desc failed, task_id: %u, stream_id: %u.", task_id, stream_id);
  4130. return;
  4131. }
  4132. size_t input_size = op_desc_info->input_addrs.size();
  4133. size_t output_size = op_desc_info->output_addrs.size();
  4134. if (input_size + output_size != io_addrs.size()) {
  4135. GELOGW("[Update][OpIOAddrs] Op[%s] input size[%zu] and output size[%zu] is not equal to io addr size[%zu]",
  4136. op_desc_info->op_name.c_str(), input_size, output_size, io_addrs.size());
  4137. return;
  4138. }
  4139. vector<void *> input_addrs;
  4140. vector<void *> output_addrs;
  4141. for (size_t i = 0; i < io_addrs.size(); i++) {
  4142. if (i < input_size) {
  4143. input_addrs.emplace_back(GetRunAddress(io_addrs[i]));
  4144. } else {
  4145. output_addrs.emplace_back(GetRunAddress(io_addrs[i]));
  4146. }
  4147. }
  4148. op_desc_info->input_addrs = input_addrs;
  4149. op_desc_info->output_addrs = output_addrs;
  4150. GELOGD("[Update][OpIOAddrs] Op [%s] update input output addr success.", op_desc_info->op_name.c_str());
  4151. }
  4152. ///
  4153. /// @ingroup ge
  4154. /// @brief Get total useful size, in known subgraph, no need to allocate zero copy memory during initialization.
  4155. /// @param [in] total_useful_size: total mem size - zero copy size.
  4156. /// @return Status
  4157. ///
  4158. Status DavinciModel::GetTotalMemSizeExcludeZeroCopy(int64_t &total_useful_size) {
  4159. if (runtime_param_.mem_size < static_cast<uint64_t>(runtime_param_.zero_copy_size)) {
  4160. REPORT_CALL_ERROR("E19999", "total mem size[%lu] is less than zero copy size[%ld] ", runtime_param_.mem_size,
  4161. runtime_param_.zero_copy_size);
  4162. GELOGE(FAILED, "[Check][TotalMemSizeExcludeZeroCopy] failed, total mem size[%lu] is less than zero copy size[%ld]",
  4163. runtime_param_.mem_size, runtime_param_.zero_copy_size);
  4164. return FAILED;
  4165. }
  4166. total_useful_size = runtime_param_.mem_size - runtime_param_.zero_copy_size;
  4167. return SUCCESS;
  4168. }
  4169. } // 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