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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. #include "framework/omg/omg_inner_types.h"
  63. // create std::thread, catch exceptions using try/catch
  64. #define CREATE_STD_THREAD(thread_id, func, args) \
  65. do { \
  66. try { \
  67. thread_id = std::thread(func, args); \
  68. } catch (const std::system_error &e) { \
  69. REPORT_CALL_ERROR("E19999", "Create thread fail, ecode:%d, emsg:%s", \
  70. e.code().value(), e.what()); \
  71. GELOGE(FAILED, "[Create][Thread] Caught system_error with code:%d, meaning:%s", \
  72. e.code().value(), e.what()); \
  73. GELOGE(FAILED, "[Create][Thread] FAIL, Please check the left resource!"); \
  74. return FAILED; \
  75. } \
  76. } while (0)
  77. namespace ge {
  78. namespace {
  79. const uint32_t kDataIndex = 0;
  80. const uint32_t kTrueBranchStreamNum = 1;
  81. const uint32_t kGetDynamicDimsCount = 1;
  82. const uint32_t kThreadNum = 16;
  83. const uint32_t kAddrLen = sizeof(void *);
  84. const int kDecimal = 10;
  85. const int kBytes = 8;
  86. const uint32_t kDataMemAlignSizeCompare = 64;
  87. const uint32_t kDumpL1FusionOpMByteSize = 2097152; // 2 * 1024 * 1024
  88. const uint32_t kDumpFlagOfL1Fusion = 0;
  89. const char *const kDefaultBatchLable = "Batch_default";
  90. const char *const kGetDynamicDimsName = "ascend_mbatch_get_dynamic_dims_node";
  91. const char *const kMultiBatchNodePostfix = "_ascend_mbatch_batch_";
  92. const int32_t kInvalidStream = -1;
  93. const uint32_t kEndOfSequence = 0x0704000a;
  94. const uint32_t kEndOfSequenceNew = 507005;
  95. const int32_t kModelAbortNormal = 0x0704000e;
  96. const int32_t kModelAbortNormalNew = 507024;
  97. const uint32_t kInteval = 2;
  98. const uint32_t kFftsTbeHandleElementSize = 2;
  99. const uint32_t kNonTailBlock = 0;
  100. const uint32_t kTailBlock = 1;
  101. const char *const kModelName = "model_name";
  102. const char *const kModeleId = "model_id";
  103. const char *const kLoadStartTime = "load_start_time";
  104. const char *const kLoadEndTime = "load_end_time";
  105. const char *const kFusionOpInfo = "fusion_op_info";
  106. const char *const kFusionOpName = "fusion_op_name";
  107. const char *const kOriginalOpNum = "origin_op_num";
  108. const char *const kOriginalOpName = "origin_op_name";
  109. const char *const kStreamId = "stream_id";
  110. const char *const kFusionOpMemoryInfo = "memory_info";
  111. const char *const kInputSize = "input_size";
  112. const char *const kOutputSize = "output_size";
  113. const char *const kWeightSize = "weight_size";
  114. const char *const kWorkSpaceSize = "workspace_size";
  115. const char *const kTotalSize = "total_size";
  116. const char *const kTaskCount = "task_count";
  117. const char *const kTaskId = "task_id";
  118. const char *const kRequestId = "request_id";
  119. const char *const kThreadId = "thread_id";
  120. const char *const kInputBeginTime = "input_begin_time";
  121. const char *const kInputEndTime = "input_end_time";
  122. const char *const kInferBeginTime = "infer_begin_time";
  123. const char *const kInferEndTime = "infer_end_time";
  124. const char *const kOutputBeginTime = "output_start_time";
  125. const char *const kOutputEndTime = "output_end_time";
  126. const char *const kStubFuncName = "_register_stub_func";
  127. const uint32_t kStringHeadElems = 2;
  128. const uint32_t kPlacementHostData = 0;
  129. const size_t kAlignment = 64;
  130. inline bool IsDataOp(const std::string &node_type) {
  131. return (node_type == DATA_TYPE) || (node_type == AIPP_DATA_TYPE) || (node_type == ANN_DATA_TYPE);
  132. }
  133. bool IsTbeTask(const OpDescPtr &op_desc) {
  134. uint32_t run_mode = static_cast<uint32_t>(domi::ImplyType::INVALID);
  135. if (!AttrUtils::GetInt(op_desc, ATTR_NAME_IMPLY_TYPE, run_mode)) {
  136. return false;
  137. }
  138. if (run_mode != static_cast<uint32_t>(domi::ImplyType::TVM)) {
  139. return false;
  140. }
  141. // Skip no_task operator, such as concat and split.
  142. bool attr_no_task = false;
  143. bool get_attr_no_task_flag = AttrUtils::GetBool(op_desc, ATTR_NAME_NOTASK, attr_no_task);
  144. if (get_attr_no_task_flag && attr_no_task) {
  145. GELOGI("Node[name:%s, type:%s] does not generate task, skip initialization.",
  146. op_desc->GetName().c_str(), op_desc->GetType().c_str());
  147. return false;
  148. }
  149. return true;
  150. }
  151. inline bool IsNoTaskAndDumpNeeded(const OpDescPtr &op_desc) {
  152. bool save_dump_info = false;
  153. (void)ge::AttrUtils::GetBool(op_desc, ATTR_NO_TASK_AND_DUMP_NEEDED, save_dump_info);
  154. return save_dump_info;
  155. }
  156. } // namespace
  157. std::mutex DavinciModel::tvm_bin_mutex_;
  158. DavinciModel::DavinciModel(int32_t priority, const std::shared_ptr<ModelListener> &listener)
  159. : weights_mem_base_(nullptr),
  160. var_mem_base_(nullptr),
  161. fixed_mem_base_(0),
  162. mem_base_(nullptr),
  163. is_inner_mem_base_(false),
  164. is_inner_weight_base_(false),
  165. data_inputer_(nullptr),
  166. load_begin_time_(0),
  167. load_end_time_(0),
  168. time_info_(),
  169. dataInputTid(0),
  170. is_weight_mem_has_inited_(false),
  171. is_feature_map_mem_has_inited_(false),
  172. model_id_(0),
  173. runtime_model_id_(0),
  174. version_(0),
  175. ge_model_(nullptr),
  176. listener_(listener),
  177. run_flg_(false),
  178. priority_(priority),
  179. rt_model_handle_(nullptr),
  180. rt_model_stream_(nullptr),
  181. is_inner_model_stream_(false),
  182. is_async_mode_(false),
  183. last_execute_mode_(INITIALIZATION),
  184. session_id_(0),
  185. device_id_(0),
  186. maxDumpOpNum_(0), data_dumper_(&runtime_param_),
  187. iterator_count_(0),
  188. is_l1_fusion_enable_(false),
  189. is_first_execute_(true) {
  190. op_list_.clear();
  191. skt_info_ = {0, 0, 0, 0, nullptr, nullptr, {}, {}, {}, {}, {}, RT_KERNEL_DEFAULT, -1, 0, nullptr};
  192. }
  193. DavinciModel::~DavinciModel() {
  194. try {
  195. GE_CHK_STATUS(ModelRunStop());
  196. Status ret = data_dumper_.UnloadDumpInfo();
  197. if (ret != SUCCESS) {
  198. GELOGW("UnloadDumpInfo failed, ret: %u.", ret);
  199. }
  200. ClearTaskAddrs();
  201. op_list_.clear();
  202. tensor_name_to_fixed_addr_size_.clear();
  203. tensor_name_to_peer_output_index_.clear();
  204. GE_DELETE_NEW_SINGLE(data_inputer_);
  205. // check rt ctx is exist. rt api call will cause error log when ctx not exist
  206. rtContext_t ctx = nullptr;
  207. rtError_t rt_ret = rtCtxGetCurrent(&ctx);
  208. if (rt_ret == RT_ERROR_NONE) {
  209. UnbindTaskSinkStream();
  210. for (size_t i = 0; i < label_list_.size(); ++i) {
  211. if (label_list_[i] != nullptr) {
  212. GE_LOGW_IF(rtLabelDestroy(label_list_[i]) != RT_ERROR_NONE, "Destroy label failed, index:%zu.", i);
  213. }
  214. }
  215. for (size_t i = 0; i < stream_list_.size(); ++i) {
  216. GE_LOGW_IF(rtStreamDestroy(stream_list_[i]) != RT_ERROR_NONE, "Destroy stream failed, index:%zu.", i);
  217. }
  218. for (size_t i = 0; i < event_list_.size(); ++i) {
  219. GE_LOGW_IF(rtEventDestroy(event_list_[i]) != RT_ERROR_NONE, "Destroy event failed, index: %zu", i);
  220. }
  221. FreeWeightsMem();
  222. FreeFeatureMapMem();
  223. FreeExMem();
  224. OpDebugUnRegister();
  225. if (l1_fusion_addr_ != nullptr) {
  226. GE_CHK_RT(rtFree(l1_fusion_addr_));
  227. }
  228. if (rt_model_handle_ != nullptr) {
  229. GE_CHK_RT(rtModelDestroy(rt_model_handle_));
  230. rt_model_handle_ = nullptr;
  231. }
  232. }
  233. ReleaseTask();
  234. CleanTbeHandle();
  235. var_mem_base_ = nullptr;
  236. if (known_node_) {
  237. if (args_ != nullptr) {
  238. GE_CHK_RT(rtFree(args_));
  239. }
  240. total_io_addrs_.clear();
  241. if (fixed_addrs_ != nullptr) {
  242. GE_CHK_RT(rtFree(fixed_addrs_));
  243. }
  244. }
  245. } catch (...) {
  246. GELOGW("DavinciModel::~DavinciModel: clear op_list catch exception.");
  247. }
  248. }
  249. void DavinciModel::ClearTaskAddrs() {
  250. for (const auto &op_and_addr : saved_task_addrs_) {
  251. auto addr = op_and_addr.second;
  252. if (addr != nullptr) {
  253. GE_CHK_RT(rtFree(addr));
  254. }
  255. addr = nullptr;
  256. }
  257. saved_task_addrs_.clear();
  258. }
  259. void DavinciModel::UnbindHcomStream() {
  260. if (!all_hccl_stream_list_.empty()) {
  261. for (size_t i = 0; i < all_hccl_stream_list_.size(); i++) {
  262. GE_LOGW_IF(rtModelUnbindStream(rt_model_handle_, all_hccl_stream_list_[i]) != RT_ERROR_NONE,
  263. "Unbind hccl stream from model failed, Index: %zu", i);
  264. GE_LOGW_IF(rtStreamDestroy(all_hccl_stream_list_[i]) != RT_ERROR_NONE, "Destroy hccl stream for rt_model failed")
  265. }
  266. }
  267. return;
  268. }
  269. void DavinciModel::ReleaseTask() {
  270. for (const auto &task : cpu_task_list_) {
  271. if (task != nullptr) {
  272. GE_CHK_STATUS(task->Release(), "[Release][Task] failed, model id:%u.", model_id_);
  273. }
  274. }
  275. cpu_task_list_.clear();
  276. for (const auto &task : task_list_) {
  277. if (task != nullptr) {
  278. GE_CHK_STATUS(task->Release(), "[Release][Task] failed, model id:%u.", model_id_);
  279. }
  280. }
  281. for (auto &item : label_goto_args_) {
  282. GE_FREE_RT_LOG(item.second.first);
  283. }
  284. label_goto_args_.clear();
  285. }
  286. Status DavinciModel::Assign(const GeModelPtr &ge_model) {
  287. if (ge_model == nullptr) {
  288. GELOGI("can't assign null ge_model");
  289. return FAILED;
  290. }
  291. ge_model_ = ge_model;
  292. return SUCCESS;
  293. }
  294. ///
  295. /// @ingroup ge
  296. /// @brief Reduce memory usage after task sink.
  297. /// @return: void
  298. ///
  299. void DavinciModel::Shrink() {
  300. skt_info_ = {0, 0, 0, 0, nullptr, nullptr, {}, {}, {}, {}, {}, RT_KERNEL_DEFAULT, -1, 0, nullptr};
  301. DumperShrink();
  302. ge_model_.reset(); // delete object.
  303. op_list_.clear();
  304. ClearTaskAddrs();
  305. }
  306. Status DavinciModel::InitWeightMem(void *dev_ptr, void *weight_ptr, size_t weight_size) {
  307. if (is_weight_mem_has_inited_) {
  308. REPORT_INNER_ERROR("E19999", "Call InitWeightMem more than once, model_id:%u, check invalid", model_id_);
  309. GELOGE(FAILED, "[Check][Param] call InitWeightMem more than once, model id:%u.", model_id_);
  310. return FAILED;
  311. }
  312. is_weight_mem_has_inited_ = true;
  313. const Buffer &weights = ge_model_->GetWeight();
  314. std::size_t weights_size = weights.GetSize();
  315. GE_CHECK_LE(weights_size, ALLOC_MEMORY_MAX_SIZE);
  316. if ((weight_ptr != nullptr) && (weight_size < weights_size)) {
  317. REPORT_INNER_ERROR("E19999", "Param weight_ptr is nullptr or ge_model.weight.size:%zu < param weights_size:%zu, "
  318. "model_id:%u, check invalid", weight_size, weights_size, model_id_);
  319. GELOGE(FAILED, "[Check][Param] Invalid mem param: weight_size=%zu totalsize=%zu, model_id:%u.",
  320. weight_size, weights_size, model_id_);
  321. return FAILED;
  322. }
  323. weights_mem_base_ = static_cast<uint8_t *>(dev_ptr);
  324. is_inner_weight_base_ = false;
  325. if (weights_size != 0) {
  326. weights_mem_base_ = static_cast<uint8_t *>(weight_ptr);
  327. is_inner_weight_base_ = false;
  328. if (weight_ptr == nullptr) {
  329. weights_mem_base_ = MallocWeightsMem(weights_size);
  330. if (weights_mem_base_ == nullptr) {
  331. REPORT_CALL_ERROR("E19999", "MallocWeightsMem fail, weights_size:%zu, model_id:%u, check invalid",
  332. weights_size, model_id_);
  333. GELOGE(ACL_ERROR_GE_MEMORY_ALLOCATION, "[Alloc][Memory] for weight failed. size:%zu, model_id:%u",
  334. weights_size, model_id_);
  335. return ACL_ERROR_GE_MEMORY_ALLOCATION;
  336. }
  337. is_inner_weight_base_ = true;
  338. }
  339. GELOGI("[IMAS]InitWeightMem graph_%u MallocMemory type[W] memaddr[%p] mem_size[%zu]", runtime_param_.graph_id,
  340. weights_mem_base_, weights_size);
  341. GE_CHK_RT_RET(rtMemcpy(weights_mem_base_, weights_size, weights.GetData(), weights_size, RT_MEMCPY_HOST_TO_DEVICE));
  342. GELOGI("copy weights data to device");
  343. }
  344. runtime_param_.weight_base = weights_mem_base_;
  345. return SUCCESS;
  346. }
  347. Status DavinciModel::InitFeatureMapAndP2PMem(void *dev_ptr, size_t mem_size) {
  348. if (is_feature_map_mem_has_inited_) {
  349. REPORT_INNER_ERROR("E19999", "Call InitFeatureMapMem more than once, model_id:%u, check invalid", model_id_);
  350. GELOGE(PARAM_INVALID, "[Check][Param] call InitFeatureMapMem more than once, model_id:%u", model_id_);
  351. return PARAM_INVALID;
  352. }
  353. is_feature_map_mem_has_inited_ = true;
  354. std::size_t data_size = TotalMemSize();
  355. if ((dev_ptr != nullptr) && (mem_size < TotalMemSize())) {
  356. REPORT_INNER_ERROR("E19999", "Param dev_ptr is nullptr or mem_size:%zu < ge_model.mem_size:%zu, "
  357. "model_id:%u, check invalid", mem_size, TotalMemSize(), model_id_);
  358. GELOGE(PARAM_INVALID, "[Check][Param] Invalid mem param: mem_size=%zu totalsize=%zu, model_id:%u.",
  359. mem_size, TotalMemSize(), model_id_);
  360. return PARAM_INVALID;
  361. }
  362. mem_base_ = static_cast<uint8_t *>(dev_ptr);
  363. is_inner_mem_base_ = false;
  364. if (TotalMemSize() && mem_base_ == nullptr) {
  365. mem_base_ = MallocFeatureMapMem(data_size);
  366. if (mem_base_ == nullptr) {
  367. REPORT_CALL_ERROR("E19999", "MallocFeatureMapMem fail, data_size:%zu, model_id:%u, check invalid",
  368. data_size, model_id_);
  369. GELOGE(ACL_ERROR_GE_MEMORY_ALLOCATION, "[Alloc][Memory] for feature map failed. size:%zu, model_id:%u",
  370. data_size, model_id_);
  371. return ACL_ERROR_GE_MEMORY_ALLOCATION;
  372. }
  373. GEEVENT("[IMAS]InitFeatureMapAndP2PMem graph_%u MallocMemory type[F] memaddr[%p] mem_size[%zu]",
  374. runtime_param_.graph_id, mem_base_, data_size);
  375. if (!is_inner_weight_base_) {
  376. weights_mem_base_ = mem_base_;
  377. is_inner_weight_base_ = true;
  378. }
  379. is_inner_mem_base_ = true;
  380. }
  381. if (!runtime_param_.memory_infos.empty()) {
  382. GE_CHK_STATUS_RET(MallocExMem(), "MallocExMem failed.");
  383. }
  384. GE_CHK_STATUS_RET(InitVariableMem(), "[Init][VariableMemory] failed, model_id:%u", model_id_);
  385. runtime_param_.mem_base = mem_base_;
  386. runtime_param_.weight_base = weights_mem_base_;
  387. return SUCCESS;
  388. }
  389. Status DavinciModel::InitVariableMem() {
  390. // malloc variable memory base
  391. var_mem_base_ = VarManager::Instance(session_id_)->GetVarMemoryBase(RT_MEMORY_HBM);
  392. if (TotalVarMemSize() && (var_mem_base_ == nullptr)) {
  393. Status ret = VarManager::Instance(session_id_)->MallocVarMemory(TotalVarMemSize());
  394. if (ret != SUCCESS) {
  395. REPORT_CALL_ERROR("E19999", "MallocVarMemory fail, var_size:%zu, model_id:%u, check invalid",
  396. TotalVarMemSize(), model_id_);
  397. GELOGE(ret, "[Malloc][VarMemory] failed, var_size:%zu, model_id:%u", TotalVarMemSize(), model_id_);
  398. return ret;
  399. }
  400. var_mem_base_ = VarManager::Instance(session_id_)->GetVarMemoryBase(RT_MEMORY_HBM);
  401. GEEVENT("[IMAS]InitVariableMem graph_%u MallocMemory type[V] memaddr[%p] mem_size[%zu]", runtime_param_.graph_id,
  402. var_mem_base_, TotalVarMemSize());
  403. }
  404. runtime_param_.var_base = var_mem_base_;
  405. return SUCCESS;
  406. }
  407. void DavinciModel::InitRuntimeParams() {
  408. int64_t value = 0;
  409. bool ret;
  410. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_MEMORY_SIZE, value);
  411. runtime_param_.mem_size = ret ? (uint64_t)value : 0;
  412. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_WEIGHT_SIZE, value);
  413. runtime_param_.weight_size = ret ? (uint64_t)value : 0;
  414. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_STREAM_NUM, value);
  415. runtime_param_.stream_num = ret ? (uint32_t)value : 0;
  416. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_EVENT_NUM, value);
  417. runtime_param_.event_num = ret ? (uint32_t)value : 0;
  418. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_LABEL_NUM, value);
  419. runtime_param_.label_num = ret ? (uint32_t)value : 0;
  420. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_BATCH_NUM, value);
  421. runtime_param_.batch_num = ret ? (uint32_t)value : 0;
  422. ret = ge::AttrUtils::GetInt(ge_model_, MODEL_ATTR_TASK_GEN_BASE_ADDR, value);
  423. runtime_param_.logic_mem_base = ret ? (uint64_t)value : 0;
  424. ret = ge::AttrUtils::GetInt(ge_model_, MODEL_ATTR_TASK_GEN_WEIGHT_ADDR, value);
  425. runtime_param_.logic_weight_base = ret ? (uint64_t)value : 0;
  426. ret = ge::AttrUtils::GetInt(ge_model_, ge::MODEL_ATTR_SESSION_ID, value);
  427. runtime_param_.session_id = ret ? (uint64_t)value : 0;
  428. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_TASK_GEN_VAR_ADDR, value);
  429. runtime_param_.logic_var_base = ret ? (uint64_t)value : 0;
  430. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_VAR_SIZE, value);
  431. runtime_param_.var_size = ret ? (uint64_t)value : 0;
  432. session_id_ = runtime_param_.session_id;
  433. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_P2P_MEMORY_SIZE, value);
  434. MemInfo p2p_mem_info;
  435. p2p_mem_info.memory_size = static_cast<size_t>(ret ? value : 0);
  436. p2p_mem_info.memory_type = RT_MEMORY_P2P_DDR;
  437. p2p_mem_info.memory_key = "_p";
  438. runtime_param_.memory_infos[RT_MEMORY_P2P_DDR] = std::move(p2p_mem_info);
  439. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_SESSION_SCOPE_MEMORY_SIZE, value);
  440. MemInfo session_scope_mem_info;
  441. session_scope_mem_info.memory_size = static_cast<size_t>(ret ? value : 0);
  442. runtime_param_.memory_infos[kSessionScopeMemory | RT_MEMORY_HBM] = std::move(session_scope_mem_info);
  443. ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_ZERO_COPY_MEMORY_SIZE, value);
  444. runtime_param_.zero_copy_size = ret ? value : 0;
  445. GELOGI("InitRuntimeParams(), %s.", runtime_param_.ToString().c_str());
  446. }
  447. void DavinciModel::CheckHasHcomOp(const ComputeGraphPtr &compute_graph) {
  448. const set<string> hcom_opp_types({
  449. HCOMBROADCAST, HCOMALLGATHER, HCOMALLREDUCE, HCOMSEND, HCOMRECEIVE, HCOMREDUCESCATTER,
  450. HVDCALLBACKALLREDUCE, HVDCALLBACKALLGATHER, HVDCALLBACKBROADCAST, HVDWAIT, HCOMREDUCE
  451. });
  452. for (const auto &node : compute_graph->GetAllNodes()) {
  453. OpDescPtr op_desc = node->GetOpDesc();
  454. GE_IF_BOOL_EXEC(op_desc == nullptr, GELOGW("Node OpDesc is nullptr."); continue);
  455. if (hcom_opp_types.count(op_desc->GetType()) > 0) {
  456. uint32_t stream_id = static_cast<uint32_t>(op_desc->GetStreamId());
  457. hcom_streams_.emplace(stream_id);
  458. GELOGD("hcom stream: %u.", stream_id);
  459. }
  460. }
  461. }
  462. ///
  463. /// @ingroup ge
  464. /// @brief Make active stream list and bind to model.
  465. /// @return: 0 for success / others for fail
  466. ///
  467. Status DavinciModel::BindModelStream() {
  468. // Stream not in active_stream_indication_ is active stream.
  469. is_stream_list_bind_ = false;
  470. if ((!input_queue_ids_.empty() || !output_queue_ids_.empty()) || (deploy_type_ == AICPU_DEPLOY_CROSS_THREAD)) {
  471. for (size_t i = 0; i < stream_list_.size(); ++i) {
  472. if (active_stream_indication_.count(i) == 0) {
  473. active_stream_list_.push_back(stream_list_[i]);
  474. active_stream_indication_.insert(i); // deactive all model stream.
  475. }
  476. }
  477. }
  478. for (size_t i = 0; i < stream_list_.size(); ++i) {
  479. if (active_stream_indication_.count(i) > 0) {
  480. GELOGI("rtModelBindStream[%zu]", i);
  481. GE_CHK_RT_RET(rtModelBindStream(rt_model_handle_, stream_list_[i], RT_INVALID_FLAG));
  482. } else {
  483. // bind rt_model_handel to all streams that relates to op
  484. GE_CHK_RT_RET(rtModelBindStream(rt_model_handle_, stream_list_[i], RT_HEAD_STREAM));
  485. }
  486. }
  487. is_stream_list_bind_ = true;
  488. return SUCCESS;
  489. }
  490. Status DavinciModel::DoTaskSink() {
  491. // task sink is supported as model_task_def is set
  492. const auto &model_task_def = ge_model_->GetModelTaskDefPtr();
  493. if (model_task_def == nullptr) {
  494. return SUCCESS;
  495. }
  496. GE_CHK_RT_RET(rtGetAicpuDeploy(&deploy_type_));
  497. GELOGI("Do task sink. AiCpu deploy type is: %x.", deploy_type_);
  498. GE_CHK_STATUS_RET(BindModelStream(), "[Bind][ModelStream] failed, model_id:%u.", model_id_);
  499. if (known_node_) {
  500. GE_CHK_STATUS_RET(MallocKnownArgs(), "[Malloc][KnownArgs] failed, model_id:%u.", model_id_);
  501. }
  502. GE_CHK_STATUS_RET(InitTaskInfo(*model_task_def.get()), "[Init][TaskInfo] failed, model_id:%u.", model_id_);
  503. GE_CHK_STATUS_RET(ModelManager::GetInstance()->LaunchCustAicpuSo(),
  504. "[Launch][CustAicpuSo] failed, model_id:%u.", model_id_);
  505. GE_CHK_STATUS_RET(ModelManager::GetInstance()->CheckAicpuOpList(ge_model_),
  506. "[Check][AicpuOpList] failed, model_id:%u.", model_id_);
  507. GE_CHK_STATUS_RET(InitEntryTask(), "[Init][EntryTask] failed, model_id:%u.", model_id_);
  508. GE_CHK_STATUS_RET(InitL1DataDumperArgs(), "[Init][L1DataDumperArgs] failed, model_id:%u.", model_id_);
  509. GE_CHK_STATUS_RET(DistributeTask(), "[Distribute][Task] failed, model_id:%u.", model_id_);
  510. GE_CHK_RT_RET(rtModelLoadComplete(rt_model_handle_));
  511. SetCopyOnlyOutput();
  512. return SUCCESS;
  513. }
  514. // set device use aicore(0) or vectorcore(1)
  515. Status DavinciModel::SetTSDevice() {
  516. int64_t value = 0;
  517. bool ret = ge::AttrUtils::GetInt(ge_model_, ATTR_MODEL_CORE_TYPE, value);
  518. uint32_t core_type = ret ? static_cast<uint32_t>(value) : 0;
  519. GELOGD("Set TSDevice: %u.", core_type);
  520. rtError_t rt_ret = rtSetTSDevice(core_type);
  521. if (rt_ret != RT_ERROR_NONE) {
  522. REPORT_CALL_ERROR("E19999", "Call rtSetTSDevice failed, core_type:%u, model_id:%u", core_type, model_id_);
  523. GELOGE(RT_FAILED, "[Set][TSDevice] failed, core_type:%u, model_id:%u, ret: 0x%X", core_type, model_id_, rt_ret);
  524. return RT_ERROR_TO_GE_STATUS(rt_ret);
  525. }
  526. return SUCCESS;
  527. }
  528. Status DavinciModel::OpDebugRegister() {
  529. if (GetDumpProperties().IsOpDebugOpen()) {
  530. uint32_t op_debug_mode = GetDumpProperties().GetOpDebugMode();
  531. auto ret = opdebug_register_.RegisterDebugForModel(rt_model_handle_, op_debug_mode, data_dumper_);
  532. if (ret != SUCCESS) {
  533. GELOGE(ret,"[Call][RegisterDebugForModel] Register known shape op debug failed, ret: 0x%X", ret);
  534. return ret;
  535. }
  536. is_op_debug_reg_ = true;
  537. }
  538. return SUCCESS;
  539. }
  540. void DavinciModel::OpDebugUnRegister() {
  541. if (is_op_debug_reg_) {
  542. opdebug_register_.UnregisterDebugForModel(rt_model_handle_);
  543. is_op_debug_reg_ = false;
  544. }
  545. return;
  546. }
  547. // initialize op sequence and call initialization function of each op respectively
  548. Status DavinciModel::Init(void *dev_ptr, size_t mem_size, void *weight_ptr, size_t weight_size) {
  549. // validating params
  550. GELOGI("Priority is %d.", priority_);
  551. GE_CHK_BOOL_TRUE_EXEC_WITH_LOG(priority_ < 0 || priority_ > 7, return PARAM_INVALID,
  552. "[Check][Param] Priority must between 0-7, now is %d.", priority_);
  553. GE_CHK_BOOL_RET_STATUS(ge_model_ != nullptr, PARAM_INVALID, "[Check][Param] GeModel is null.");
  554. Graph graph = ge_model_->GetGraph();
  555. ComputeGraphPtr compute_graph = GraphUtils::GetComputeGraph(graph);
  556. GE_CHK_BOOL_RET_STATUS(compute_graph != nullptr, INTERNAL_ERROR, "[Get][ComputeGraph] failed, ret is nullptr.");
  557. // Initializing runtime_param_
  558. InitRuntimeParams();
  559. // RTS set aicore or vectorcore
  560. GE_CHK_STATUS_RET(SetTSDevice(), "[Set][TSDevice] failed, graph:%s.", compute_graph->GetName().c_str());
  561. version_ = ge_model_->GetVersion();
  562. name_ = ge_model_->GetName();
  563. (void)ge::AttrUtils::GetBool(ge_model_, ATTR_NAME_SWITCH_FOR_L1_FUSION, is_l1_fusion_enable_);
  564. GELOGD("The value of ge.l1Fusion in ge_model is %d.", is_l1_fusion_enable_);
  565. CheckHasHcomOp(compute_graph);
  566. vector<int64_t> huge_stream_list;
  567. (void)ge::AttrUtils::GetListInt(ge_model_, ATTR_MODEL_HUGE_STREAM_LIST, huge_stream_list);
  568. std::set<int64_t> huge_streams(huge_stream_list.begin(), huge_stream_list.end());
  569. for (uint32_t i = 0; i < StreamNum(); i++) {
  570. rtStream_t stream = nullptr;
  571. GE_MAKE_GUARD_RTSTREAM(stream);
  572. uint32_t stream_flags = RT_STREAM_PERSISTENT;
  573. if (huge_streams.find(i) != huge_streams.end()) {
  574. GELOGI("Stream %u is huge stream.", i);
  575. stream_flags |= RT_STREAM_HUGE;
  576. }
  577. if (hcom_streams_.find(i) != hcom_streams_.end()) {
  578. GE_CHK_RT_RET(rtStreamCreateWithFlags(&stream, priority_, stream_flags | RT_STREAM_FORCE_COPY));
  579. } else {
  580. GE_CHK_RT_RET(rtStreamCreateWithFlags(&stream, priority_, stream_flags));
  581. }
  582. GE_DISMISS_GUARD(stream);
  583. stream_list_.push_back(stream);
  584. int32_t rt_stream_id = kInvalidStream;
  585. (void)rtGetStreamId(stream, &rt_stream_id);
  586. GELOGI("Logical stream index:%u, stream:%p, rtstream: %d.", i, stream, rt_stream_id);
  587. }
  588. uint32_t event_num = EventNum();
  589. uint32_t create_flag = static_cast<uint32_t>((event_num > kEventReuseThreshold) ? RT_EVENT_WITH_FLAG :
  590. RT_EVENT_DEFAULT);
  591. for (uint32_t i = 0; i < event_num; ++i) {
  592. rtEvent_t rt_event = nullptr;
  593. GE_CHK_RT_RET(rtEventCreateWithFlag(&rt_event, create_flag));
  594. event_list_.push_back(rt_event);
  595. }
  596. label_list_.resize(LabelNum(), nullptr);
  597. // create model_handle to load model
  598. GE_CHK_RT_RET(rtModelCreate(&rt_model_handle_, 0));
  599. GE_CHK_RT_RET(rtModelGetId(rt_model_handle_, &runtime_model_id_));
  600. // inference will use default graph_id 0;
  601. runtime_param_.graph_id = compute_graph->GetGraphID();
  602. // op debug register
  603. GE_CHK_STATUS_RET(OpDebugRegister(), "[Call][OpDebugRegister] failed, model_id:%u.", model_id_);
  604. GE_TIMESTAMP_START(TransAllVarData);
  605. GE_CHK_STATUS_RET(TransAllVarData(compute_graph, runtime_param_.graph_id),
  606. "[Call][TransAllVarData] failed, graph:%s, graph_id:%u.",
  607. compute_graph->GetName().c_str(), runtime_param_.graph_id);
  608. GE_TIMESTAMP_END(TransAllVarData, "GraphLoader::TransAllVarData");
  609. GE_CHK_STATUS_RET(TransVarDataUtils::CopyVarData(compute_graph, session_id_, device_id_),
  610. "[Copy][VarData] failed, graph:%s, session_id:%lu, device_id:%u",
  611. compute_graph->GetName().c_str(), session_id_, device_id_);
  612. GE_TIMESTAMP_START(InitModelMem);
  613. GELOGD("Known node is %d.", known_node_);
  614. GE_CHK_STATUS_RET_NOLOG(InitWeightMem(dev_ptr, weight_ptr, weight_size));
  615. if (!known_node_) {
  616. GE_CHK_STATUS_RET_NOLOG(InitFeatureMapAndP2PMem(dev_ptr, mem_size));
  617. data_inputer_ = new (std::nothrow) DataInputer();
  618. GE_CHK_BOOL_RET_STATUS(data_inputer_ != nullptr, MEMALLOC_FAILED,
  619. "[Create][DataInputer] data_inputer_ is nullptr");
  620. }
  621. fixed_mem_base_ = reinterpret_cast<uintptr_t>(mem_base_);
  622. GE_TIMESTAMP_END(InitModelMem, "GraphLoader::InitModelMem");
  623. for (const ge::NodePtr &node : compute_graph->GetDirectNode()) {
  624. auto op_desc = node->GetOpDesc();
  625. GE_IF_BOOL_EXEC(op_desc == nullptr, continue);
  626. GE_IF_BOOL_EXEC(op_desc->GetType() != VARIABLE, continue);
  627. GE_IF_BOOL_EXEC(IsBroadCastOpData(node),
  628. (void)ge::AttrUtils::SetStr(op_desc, VAR_ATTR_VAR_IS_BROADCAST, "var_is_restore"););
  629. }
  630. GE_CHK_STATUS_RET(InitNodes(compute_graph), "[Init][Nodes] failed, graph:%s.", compute_graph->GetName().c_str());
  631. GE_TIMESTAMP_START(DoTaskSink);
  632. GE_CHK_STATUS_RET(DoTaskSink(), "[Call][DoTaskSink] failed, model_id:%u.", model_id_);
  633. GE_TIMESTAMP_END(DoTaskSink, "GraphLoader::DoTaskSink");
  634. /// In zero copy model, if a aicpu operator is connected to the first or last layer, before model execution,
  635. /// the aicpu opertor needs to destroy history record, and update operator memory address.
  636. /// The model with specified aicpu operators is only marked here, and destruction is in ModelManager::ExecuteModel().
  637. need_destroy_aicpu_kernel_ = IsAicpuKernelConnectSpecifiedLayer();
  638. string fp_ceiling_mode;
  639. if (ge::AttrUtils::GetStr(ge_model_, ATTR_FP_CEILING_MODE, fp_ceiling_mode)) {
  640. GELOGI("Get attr ATTR_FP_CEILING_MODE from model, value is %s.", fp_ceiling_mode.c_str());
  641. // mode 0: Do not perform saturation processing. By default, IEEE754 is used.
  642. GE_CHK_RT_RET(rtSetCtxINFMode((fp_ceiling_mode != "0")));
  643. }
  644. SetProfileTime(MODEL_LOAD_END);
  645. // collect profiling for ge
  646. auto &profiling_manager = ProfilingManager::Instance();
  647. if (profiling_manager.ProfilingModelLoadOn()) {
  648. GE_CHK_STATUS_RET(InitModelProfile(), "[Init][ModelProfile] failed, model_id:%u.", model_id_);
  649. Status p_ret = ReportProfilingData();
  650. if (p_ret != SUCCESS) {
  651. GELOGE(p_ret, "[Report][ProfilingData] failed, ret:%d, model_id:%u.", p_ret, model_id_);
  652. return p_ret;
  653. }
  654. }
  655. Shrink();
  656. return SUCCESS;
  657. }
  658. // save specify attr values of op, such as ATTR_NAME_DATA_DUMP_ORIGIN_OP_NAMES
  659. // it will save more attr values in the future
  660. void DavinciModel::SaveSpecifyAttrValues(const OpDescPtr &op_desc) {
  661. std::vector<std::string> value;
  662. if (AttrUtils::GetListStr(op_desc, ATTR_NAME_DATA_DUMP_ORIGIN_OP_NAMES, value)) {
  663. std::map<std::string, std::vector<std::string>> attr_name_to_value;
  664. attr_name_to_value[ATTR_NAME_DATA_DUMP_ORIGIN_OP_NAMES]= value;
  665. op_name_to_attrs_[op_desc->GetName()] = attr_name_to_value;
  666. GELOGD("Get op:%s attr:%s success.", op_desc->GetName().c_str(), ATTR_NAME_DATA_DUMP_ORIGIN_OP_NAMES.c_str());
  667. }
  668. return;
  669. }
  670. Status DavinciModel::ReportProfilingData() {
  671. bool is_train = domi::GetContext().train_flag;
  672. auto model_id = model_id_;
  673. auto &profiling_manager = ProfilingManager::Instance();
  674. auto graph_id = runtime_param_.graph_id;
  675. if (is_train) {
  676. GELOGD("Replace model_id:%u with graph_id:%u, when training.", model_id, graph_id);
  677. model_id = graph_id;
  678. }
  679. profiling_manager.ReportProfilingData(model_id, GetTaskDescInfo());
  680. GE_CHK_STATUS(SinkModelProfile(), "[Sink][ModelProfile] failed, model_id:%u.", model_id);
  681. return SUCCESS;
  682. }
  683. ///
  684. /// @ingroup ge
  685. /// @brief Travel all nodes and determine if destruction is required.
  686. /// @return bool
  687. ///
  688. bool DavinciModel::IsAicpuKernelConnectSpecifiedLayer() {
  689. Graph graph = ge_model_->GetGraph();
  690. ComputeGraphPtr compute_graph = GraphUtils::GetComputeGraph(graph);
  691. auto all_nodes = compute_graph->GetAllNodes();
  692. for (auto &node : all_nodes) {
  693. GE_IF_BOOL_EXEC(node == nullptr, continue);
  694. OpDescPtr op_desc = node->GetOpDesc();
  695. GE_IF_BOOL_EXEC(op_desc == nullptr, continue);
  696. int64_t imply_type = -1;
  697. (void)ge::AttrUtils::GetInt(op_desc, ATTR_NAME_IMPLY_TYPE, imply_type);
  698. if (imply_type != static_cast<int64_t>(domi::ImplyType::AI_CPU)) {
  699. continue;
  700. }
  701. GELOGD("Current operator imply type is %ld, name is %s.", imply_type, op_desc->GetName().c_str());
  702. for (auto &in_data_anchor : node->GetAllInDataAnchors()) {
  703. GE_IF_BOOL_EXEC(in_data_anchor == nullptr, continue);
  704. auto peer_out_data_anchor = in_data_anchor->GetPeerOutAnchor();
  705. GE_IF_BOOL_EXEC(peer_out_data_anchor == nullptr, continue);
  706. auto peer_node = peer_out_data_anchor->GetOwnerNode();
  707. GE_IF_BOOL_EXEC(peer_node == nullptr, continue);
  708. auto peer_op_desc = peer_node->GetOpDesc();
  709. GE_IF_BOOL_EXEC(peer_op_desc == nullptr, continue);
  710. if (IsDataOp(peer_op_desc->GetType())) {
  711. GELOGI("Mark specified aicpu operator connected to data.");
  712. return true;
  713. }
  714. }
  715. for (auto &out_data_anchor : node->GetAllOutDataAnchors()) {
  716. GE_IF_BOOL_EXEC(out_data_anchor == nullptr, continue);
  717. auto peer_in_data_anchors = out_data_anchor->GetPeerInDataAnchors();
  718. for (auto &peer_in_data_anchor : peer_in_data_anchors) {
  719. GE_IF_BOOL_EXEC(peer_in_data_anchor == nullptr, continue);
  720. auto peer_node = peer_in_data_anchor->GetOwnerNode();
  721. GE_IF_BOOL_EXEC(peer_node == nullptr, continue);
  722. auto peer_op_desc = peer_node->GetOpDesc();
  723. GE_IF_BOOL_EXEC(peer_op_desc == nullptr, continue);
  724. if (peer_op_desc->GetType() == NETOUTPUT) {
  725. GELOGI("Mark specified aicpu operator connected to netoutput.");
  726. return true;
  727. }
  728. }
  729. }
  730. }
  731. return false;
  732. }
  733. Status DavinciModel::UpdateSessionId(uint64_t session_id) {
  734. GE_CHECK_NOTNULL(ge_model_);
  735. if (!AttrUtils::SetInt(ge_model_, MODEL_ATTR_SESSION_ID, static_cast<int64_t>(session_id))) {
  736. GELOGW("Set attr[%s] failed in updating session_id.", MODEL_ATTR_SESSION_ID.c_str());
  737. }
  738. GELOGD("Update session id: %lu.", session_id);
  739. return SUCCESS;
  740. }
  741. ///
  742. /// @ingroup ge
  743. /// @brief Travel all nodes and do some init.
  744. /// @param [in] compute_graph: ComputeGraph to load.
  745. /// @return Status
  746. ///
  747. Status DavinciModel::InitNodes(const ComputeGraphPtr &compute_graph) {
  748. uint32_t data_op_index = 0;
  749. GE_TIMESTAMP_CALLNUM_START(LoadTBEKernelBinToOpDesc);
  750. GE_TIMESTAMP_CALLNUM_START(InitTbeHandle);
  751. typedef Status (DavinciModel::*OpDescCall)(const OpDescPtr &);
  752. static std::map<std::string, OpDescCall> op_desc_handle = {
  753. {CONSTANTOP, &DavinciModel::InitConstant},
  754. {STREAMACTIVE, &DavinciModel::InitStreamActive},
  755. {STREAMSWITCH, &DavinciModel::InitStreamSwitch},
  756. {STREAMSWITCHN, &DavinciModel::InitStreamSwitchN},
  757. {LABELSET, &DavinciModel::InitLabelSet},
  758. {CASE, &DavinciModel::InitCase},
  759. };
  760. vector<OpDescPtr> output_op_list;
  761. set<const void *> input_outside_addrs;
  762. set<const void *> output_outside_addrs;
  763. map<uint32_t, OpDescPtr> data_by_index;
  764. map<string, OpDescPtr> variable_by_name;
  765. auto nodes = compute_graph->GetAllNodes();
  766. const CustAICPUKernelStore &aicpu_kernel_store = ge_model_->GetCustAICPUKernelStore();
  767. for (size_t i = 0; i < nodes.size(); ++i) {
  768. const auto &node = nodes.at(i);
  769. const auto &op_desc = node->GetOpDesc();
  770. GE_CHECK_NOTNULL(op_desc);
  771. SaveSpecifyAttrValues(op_desc);
  772. op_list_[op_desc->GetId()] = op_desc;
  773. GE_TIMESTAMP_RESTART(LoadTBEKernelBinToOpDesc);
  774. aicpu_kernel_store.LoadCustAICPUKernelBinToOpDesc(op_desc);
  775. GE_TIMESTAMP_ADD(LoadTBEKernelBinToOpDesc);
  776. if (IsDataOp(op_desc->GetType())) {
  777. if (InitDataOp(compute_graph, node, data_op_index, data_by_index, input_outside_addrs) != SUCCESS) {
  778. GELOGE(PARAM_INVALID, "[Init][DataOp] failed, Name:%s", op_desc->GetName().c_str());
  779. return PARAM_INVALID;
  780. }
  781. data_dumper_.SaveDumpInput(node);
  782. continue;
  783. }
  784. if (op_desc->GetType() == NETOUTPUT) {
  785. if (InitNetOutput(compute_graph, node, output_op_list, output_outside_addrs) != SUCCESS) {
  786. GELOGE(PARAM_INVALID, "[Init][NetOutput] failed, Name:%s", op_desc->GetName().c_str());
  787. return PARAM_INVALID;
  788. }
  789. if (InitRealSizeAndShapeInfo(compute_graph, node) != SUCCESS) {
  790. GELOGE(PARAM_INVALID, "[Init][RealSizeAndShapeInfo] failed, Name:%s", op_desc->GetName().c_str());
  791. return PARAM_INVALID;
  792. }
  793. continue;
  794. }
  795. if (op_desc->GetType() == VARIABLE) {
  796. if (InitVariable(op_desc, variable_by_name) != SUCCESS) {
  797. GELOGE(PARAM_INVALID, "[Init][Variable] failed, Name:%s", op_desc->GetName().c_str());
  798. return PARAM_INVALID;
  799. }
  800. continue;
  801. }
  802. // for dynamic shape with control flow
  803. SetLabelForDynamic(node);
  804. auto it = op_desc_handle.find(op_desc->GetType());
  805. if (it != op_desc_handle.end()) {
  806. GE_CHK_BOOL_TRUE_EXEC_WITH_LOG((this->*it->second)(op_desc) != SUCCESS, return PARAM_INVALID,
  807. "[Init][Node] failed, Name:%s", op_desc->GetName().c_str());
  808. continue;
  809. }
  810. if (IsNoTaskAndDumpNeeded(op_desc)) {
  811. GELOGD("node[%s] without task, and save op_desc and addr for dump", op_desc->GetName().c_str());
  812. const RuntimeParam &rts_param = GetRuntimeParam();
  813. const vector<void *> input_data_addrs = ModelUtils::GetInputDataAddrs(rts_param, op_desc);
  814. const vector<void *> output_data_addrs = ModelUtils::GetOutputDataAddrs(rts_param, op_desc);
  815. const vector<void *> workspace_data_addrs = ModelUtils::GetWorkspaceDataAddrs(rts_param, op_desc);
  816. vector<void *> tensor_device_addrs;
  817. tensor_device_addrs.insert(tensor_device_addrs.end(), input_data_addrs.begin(), input_data_addrs.end());
  818. tensor_device_addrs.insert(tensor_device_addrs.end(), output_data_addrs.begin(), output_data_addrs.end());
  819. tensor_device_addrs.insert(tensor_device_addrs.end(), workspace_data_addrs.begin(), workspace_data_addrs.end());
  820. void *addr = nullptr;
  821. auto size = kAddrLen * tensor_device_addrs.size();
  822. GE_CHK_RT_RET(rtMalloc(&addr, size, RT_MEMORY_HBM));
  823. rtError_t rt_ret = rtMemcpy(addr, size, tensor_device_addrs.data(), size, RT_MEMCPY_HOST_TO_DEVICE);
  824. if (rt_ret != RT_ERROR_NONE) {
  825. REPORT_CALL_ERROR("E19999", "Call rtMemcpy failed, size:%zu, ret:0x%X", size, rt_ret);
  826. GELOGE(RT_FAILED, "[Call][RtMemcpy] failed, size:%zu, ret:0x%X", size, rt_ret);
  827. GE_CHK_RT(rtFree(addr));
  828. return RT_ERROR_TO_GE_STATUS(rt_ret);
  829. }
  830. saved_task_addrs_.emplace(op_desc, addr);
  831. }
  832. GE_TIMESTAMP_RESTART(InitTbeHandle);
  833. if (IsTbeTask(op_desc)) {
  834. Status status =
  835. op_desc->HasAttr(ATTR_NAME_THREAD_SCOPE_ID) ? InitTbeHandleWithFfts(op_desc) : InitTbeHandle(op_desc);
  836. if (status != SUCCESS) {
  837. GELOGE(status, "[Init][TbeHandle] failed. op:%s", op_desc->GetName().c_str());
  838. return status;
  839. }
  840. }
  841. GE_TIMESTAMP_ADD(InitTbeHandle);
  842. }
  843. SetDataDumperArgs(compute_graph, variable_by_name);
  844. GE_TIMESTAMP_CALLNUM_END(LoadTBEKernelBinToOpDesc, "GraphLoader::LoadTBEKernelBinToOpDesc.");
  845. GE_TIMESTAMP_CALLNUM_END(InitTbeHandle, "GraphLoader::InitTbeHandle.");
  846. return GenInputOutputInfo(data_by_index, output_op_list);
  847. }
  848. void DavinciModel::SetLabelForDynamic(const NodePtr &node) {
  849. if (known_node_ && (node->GetType() == LABELSWITCHBYINDEX || node->GetType() == STREAMSWITCH)) {
  850. for (auto &in_data_anchor : node->GetAllInDataAnchors()) {
  851. auto peer_out_data_anchor = in_data_anchor->GetPeerOutAnchor();
  852. if (peer_out_data_anchor != nullptr) {
  853. // name+index as the label of switch input
  854. string tensor_name = node->GetName() + std::to_string(in_data_anchor->GetIdx());
  855. auto peer_node = peer_out_data_anchor->GetOwnerNode();
  856. (void)AttrUtils::SetStr(peer_node->GetOpDesc(), ATTR_DYNAMIC_SHAPE_FIXED_ADDR, tensor_name);
  857. (void)AttrUtils::SetInt(peer_node->GetOpDesc(), ATTR_DYNAMIC_SHAPE_FIXED_ADDR_INDEX, 0);
  858. tensor_name_to_peer_output_index_[tensor_name] = 0;
  859. }
  860. }
  861. }
  862. }
  863. ///
  864. /// @ingroup ge
  865. /// @brief Data Op Initialize.
  866. /// @param [in] ComputeGraphPtr: root graph of the model.
  867. /// @param [in] NodePtr: Data Op.
  868. /// @param [in/out] data_op_index: index of courrent count.
  869. /// @param [in/out] data_by_index: Data ordered by index.
  870. /// @return Status
  871. ///
  872. Status DavinciModel::InitDataOp(const ComputeGraphPtr &graph, const NodePtr &node, uint32_t &data_op_index,
  873. map<uint32_t, OpDescPtr> &data_by_index, set<const void *> &input_outside_addrs) {
  874. // op_desc Checked by Init: Data, valid.
  875. auto op_desc = node->GetOpDesc();
  876. if (node->GetOwnerComputeGraph() != graph) {
  877. GELOGI("Skip subgraph Data node: %s.", op_desc->GetName().c_str());
  878. return SUCCESS;
  879. }
  880. auto data_index = data_op_index++;
  881. const auto &index_attr = GraphUtils::FindRootGraph(graph) == graph ? ATTR_NAME_INDEX : ATTR_NAME_PARENT_NODE_INDEX;
  882. if (AttrUtils::GetInt(op_desc, index_attr, data_index)) {
  883. GELOGD("Get new index %u, old %u", data_index, data_op_index - 1);
  884. }
  885. GELOGI("Init data node: %s, index: %u.", op_desc->GetName().c_str(), data_index);
  886. data_by_index[data_index] = op_desc;
  887. if (known_node_) {
  888. return SUCCESS;
  889. }
  890. // Make information for copy input data.
  891. const vector<int64_t> output_size_list = ModelUtils::GetOutputSize(op_desc);
  892. const vector<void *> virtual_addr_list = ModelUtils::GetOutputDataAddrs(runtime_param_, op_desc);
  893. const vector<int64_t> output_offset_list = op_desc->GetOutputOffset();
  894. if (output_size_list.empty() || virtual_addr_list.empty() || (output_size_list.size() != virtual_addr_list.size()) ||
  895. (output_offset_list.size() != virtual_addr_list.size())) {
  896. REPORT_INNER_ERROR(
  897. "E19999", "Check data fail in op:%s(%s), output_desc size:%zu output addr size:%zu output offset size:%zu "
  898. "not equal or has empty, model_id:%u",
  899. op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  900. output_size_list.size(), virtual_addr_list.size(), output_offset_list.size(), model_id_);
  901. GELOGE(PARAM_INVALID, "[Check][Param] Data[%s] init failed: output size is %zu, "
  902. "virtual_addr size is %zu, offset size is %zu.", op_desc->GetName().c_str(), output_size_list.size(),
  903. virtual_addr_list.size(), output_offset_list.size());
  904. return PARAM_INVALID;
  905. }
  906. bool fusion_flag = false;
  907. ZeroCopyOffset zero_copy_offset;
  908. int64_t data_size = output_size_list[kDataIndex];
  909. void *virtual_addr = virtual_addr_list[kDataIndex];
  910. Status ret = zero_copy_offset.InitInputDataInfo(data_size, virtual_addr, op_desc, fusion_flag);
  911. if (ret != SUCCESS) {
  912. GELOGE(PARAM_INVALID, "[Init][DataInfo] of input_info %s failed.", op_desc->GetName().c_str());
  913. return PARAM_INVALID;
  914. }
  915. if (input_outside_addrs.count(virtual_addr) == 0) {
  916. int64_t output_offset = output_offset_list.at(kDataIndex);
  917. zero_copy_offset.SetInputOutsideAddrs(output_offset, virtual_addr, fusion_flag, real_virtual_addrs_);
  918. input_outside_addrs.insert(virtual_addr);
  919. }
  920. input_data_info_[data_index] = zero_copy_offset;
  921. return SUCCESS;
  922. }
  923. ///
  924. /// @ingroup ge
  925. /// @brief Sort Data op list by index.
  926. /// @param [in] data_by_index: map of Data Op.
  927. /// @param [in] output_op_list: list of NetOutput op.
  928. /// @return Status
  929. ///
  930. Status DavinciModel::GenInputOutputInfo(const map<uint32_t, OpDescPtr> &data_by_index,
  931. const vector<OpDescPtr> &output_op_list) {
  932. GELOGD("Data node size: %zu, NetOutput node size: %zu", data_by_index.size(), output_op_list.size());
  933. for (auto &item : data_by_index) {
  934. const auto output_addrs = ModelUtils::GetOutputDataAddrs(runtime_param_, item.second);
  935. GELOGD("Data node is: %s, output addr size: %zu", item.second->GetName().c_str(), output_addrs.size());
  936. input_addrs_list_.emplace_back(output_addrs);
  937. GE_CHK_STATUS_RET(InitAippInfo(item.first, item.second),
  938. "[Init][AippInfo] failed, node:%s", item.second->GetName().c_str());
  939. GE_CHK_STATUS_RET(InitAippType(item.first, item.second, data_by_index),
  940. "[Init][AippType] failed, node:%s", item.second->GetName().c_str());
  941. GE_CHK_STATUS_RET(InitOrigInputInfo(item.first, item.second),
  942. "[Init][OrigInputInfo] failed, node:%s", item.second->GetName().c_str());
  943. GE_CHK_STATUS_RET(InitAippInputOutputDims(item.first, item.second),
  944. "[Init][AippInputOutputDims] failed, node:%s", item.second->GetName().c_str());
  945. GE_CHK_STATUS_RET(InitInputDescInfo(item.second),
  946. "[Init][InputDescInfo] failed, node:%s", item.second->GetName().c_str());
  947. if (item.second->GetType() == AIPP_DATA_TYPE) {
  948. GELOGI("This is dynamic aipp model, Node: %s", item.second->GetName().c_str());
  949. is_dynamic_aipp_ = true;
  950. }
  951. }
  952. vector<string> out_node_name;
  953. (void)AttrUtils::GetListStr(ge_model_, ATTR_MODEL_OUT_NODES_NAME, out_node_name);
  954. GELOGD("Output node size: %zu, out nodes name is: %zu", output_op_list.size(), out_node_name.size());
  955. for (const auto &op_desc : output_op_list) {
  956. const auto input_addrs = ModelUtils::GetInputDataAddrs(runtime_param_, op_desc);
  957. GELOGD("NetOutput node is: %s, input addr size: %zu", op_desc->GetName().c_str(), input_addrs.size());
  958. output_addrs_list_.emplace_back(input_addrs);
  959. bool getnext_sink_dynamic = false;
  960. if (AttrUtils::GetBool(op_desc, ATTR_GETNEXT_SINK_DYNMAIC, getnext_sink_dynamic) && getnext_sink_dynamic) {
  961. GELOGI("ATTR_GETNEXT_SINK_DYNMAIC has been set and is true, node: %s", op_desc->GetName().c_str());
  962. is_getnext_sink_dynamic_ = true;
  963. }
  964. vector<string> shape_info;
  965. if (AttrUtils::GetListStr(op_desc, ATTR_NAME_DYNAMIC_OUTPUT_DIMS, shape_info)) {
  966. dynamic_output_shape_info_.insert(dynamic_output_shape_info_.end(), shape_info.begin(), shape_info.end());
  967. }
  968. if (InitOutputTensorInfo(op_desc) != SUCCESS) {
  969. return INTERNAL_ERROR;
  970. }
  971. GE_CHK_STATUS_RET(InitOutputDescInfo(op_desc, out_node_name),
  972. "[Init][OutputDescInfo] failed, node:%s", op_desc->GetName().c_str());
  973. }
  974. return SUCCESS;
  975. }
  976. bool DavinciModel::IsGetNextSinkDynamic(const OpDescPtr &op_desc) {
  977. bool getnext_sink_dynamic = false;
  978. if (ge::AttrUtils::GetBool(op_desc, ATTR_GETNEXT_SINK_DYNMAIC, getnext_sink_dynamic) && getnext_sink_dynamic) {
  979. GELOGI("ATTR_GETNEXT_SINK_DYNMAIC has been set and is true.");
  980. return true;
  981. }
  982. return false;
  983. }
  984. /// @ingroup ge
  985. /// @brief NetOutput Op Initialize.
  986. /// @param [in] ComputeGraphPtr: root graph of the model.
  987. /// @param [in] NodePtr: NetOutput Op.
  988. /// @param [in/out] vector<OpDescPtr>: All NetOutput node in model.
  989. /// @return Status
  990. Status DavinciModel::InitNetOutput(const ComputeGraphPtr &graph, const NodePtr &node,
  991. vector<OpDescPtr> &output_op_list, set<const void *> &output_outside_addrs) {
  992. // node->GetOpDesc Checked by Init: NetOutput, valid.
  993. auto op_desc = node->GetOpDesc();
  994. // excludes the function op sub graph, e.g. case,if
  995. if (node->GetOwnerComputeGraph() != graph) {
  996. GELOGI("Skip subgraph NetOutput node: %s.", op_desc->GetName().c_str());
  997. op_list_.erase(op_desc->GetId());
  998. return SUCCESS;
  999. }
  1000. GELOGI("Init NetOutput node: %s.", op_desc->GetName().c_str());
  1001. output_op_list.push_back(op_desc);
  1002. has_output_node_ = true;
  1003. if (known_node_) {
  1004. return SUCCESS;
  1005. }
  1006. // Make information for copy output data.
  1007. const vector<int64_t> input_size_list = ModelUtils::GetInputSize(op_desc);
  1008. const vector<void *> virtual_addr_list = ModelUtils::GetInputDataAddrs(runtime_param_, op_desc);
  1009. const vector<int64_t> input_offset_list = op_desc->GetInputOffset();
  1010. GE_IF_BOOL_EXEC(input_offset_list.size() != virtual_addr_list.size(),
  1011. REPORT_INNER_ERROR("E19999", "Check data fail in op:%s(%s), input addr size:%zu "
  1012. "input offset size:%zu not equal, model_id:%u", op_desc->GetName().c_str(),
  1013. op_desc->GetType().c_str(), virtual_addr_list.size(), input_offset_list.size(),
  1014. model_id_);
  1015. GELOGE(PARAM_INVALID, "[Check][Param] virtual_addr size:%zu should be equal to offset size:%zu, "
  1016. "op:%s(%s), model id:%u", virtual_addr_list.size(), input_offset_list.size(),
  1017. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  1018. return PARAM_INVALID;);
  1019. if (input_size_list.empty() && virtual_addr_list.empty()) {
  1020. GELOGI("NetOutput[%s] is empty.", op_desc->GetName().c_str());
  1021. return SUCCESS;
  1022. }
  1023. if (input_size_list.empty() || input_size_list.size() != virtual_addr_list.size()) {
  1024. REPORT_INNER_ERROR("E19999", "Check data fail in op:%s(%s), input_desc size:%zu input addr size:%zu "
  1025. "not equal or has empty, model_id:%u", op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1026. input_size_list.size(), virtual_addr_list.size(), model_id_);
  1027. GELOGE(PARAM_INVALID, "[Check][Param] NetOutput[%s] init failed: Input size is %zu, Input addr is %zu",
  1028. op_desc->GetName().c_str(), input_size_list.size(), virtual_addr_list.size());
  1029. return PARAM_INVALID;
  1030. }
  1031. size_t num = output_data_info_.size();
  1032. bool fusion_flag = false;
  1033. size_t input_count = input_size_list.size();
  1034. is_getnext_sink_dynamic_ = false;
  1035. if (IsGetNextSinkDynamic(op_desc)) {
  1036. input_count = input_size_list.size() - kGetDynamicDimsCount;
  1037. is_getnext_sink_dynamic_ = true;
  1038. }
  1039. for (size_t idx = 0; idx < input_count; ++idx) {
  1040. ZeroCopyOffset zero_copy_offset;
  1041. Status ret = zero_copy_offset.InitOutputDataInfo(input_size_list, virtual_addr_list, op_desc, idx, fusion_flag);
  1042. GE_IF_BOOL_EXEC(ret != SUCCESS,
  1043. GELOGE(PARAM_INVALID, "[Init][DataInfo] of input_info %s failed.", op_desc->GetName().c_str());
  1044. return PARAM_INVALID;);
  1045. void *addr = virtual_addr_list.at(idx);
  1046. int64_t input_offset = input_offset_list.at(idx);
  1047. if (output_outside_addrs.count(addr) == 0) {
  1048. vector<void *> tensor_addrs;
  1049. zero_copy_offset.SetOutputOutsideAddrs(input_offset, fusion_flag, addr, tensor_addrs);
  1050. output_outside_addrs.insert(addr);
  1051. for (size_t i = 0; i < tensor_addrs.size(); ++i) {
  1052. void *real_addr = tensor_addrs.at(i);
  1053. DisableZeroCopy(real_addr);
  1054. real_virtual_addrs_.insert(real_addr);
  1055. }
  1056. } else {
  1057. GELOGI("same output_tensor_addr %p to different input_tensor of %s", addr, op_desc->GetName().c_str());
  1058. DisableZeroCopy(addr);
  1059. }
  1060. output_data_info_[num + idx] = zero_copy_offset;
  1061. }
  1062. return SUCCESS;
  1063. }
  1064. Status DavinciModel::InitRealSizeAndShapeInfo(const ComputeGraphPtr &compute_graph, const NodePtr &node) {
  1065. if (node->GetName().find(kMultiBatchNodePostfix) != string::npos) {
  1066. GELOGD("No need to get size and shape of netoutput in subgraph.");
  1067. return SUCCESS;
  1068. }
  1069. GELOGD("Start init real size and shape info of %s.", node->GetName().c_str());
  1070. GetAllGearsInfo(node);
  1071. if (is_getnext_sink_dynamic_) {
  1072. GE_IF_BOOL_EXEC(GetGetDynamicDimsNodeInfo(node) != SUCCESS,
  1073. GELOGE(PARAM_INVALID, "[Get][Info] of getdynamicdims node:%s failed.", node->GetName().c_str());
  1074. return PARAM_INVALID;);
  1075. }
  1076. if (is_online_infer_dynamic_) {
  1077. GE_IF_BOOL_EXEC(GetGearAndRealOutSizeInfo(compute_graph, node) != SUCCESS,
  1078. GELOGE(PARAM_INVALID, "[Call][GetGearAndRealOutSizeInfo] failed, node:%s.",
  1079. node->GetName().c_str());
  1080. return PARAM_INVALID;);
  1081. GE_IF_BOOL_EXEC(GetGearAndRealOutShapeInfo(compute_graph, node) != SUCCESS,
  1082. GELOGE(PARAM_INVALID, "[Call][GetGearAndRealOutShapeInfo] failed, node:%s.",
  1083. node->GetName().c_str());
  1084. return PARAM_INVALID;);
  1085. }
  1086. return SUCCESS;
  1087. }
  1088. void DavinciModel::GetAllGearsInfo(const NodePtr &node) {
  1089. is_online_infer_dynamic_ = false;
  1090. all_gears_info_.clear();
  1091. std::string shapes;
  1092. (void) AttrUtils::GetStr(node->GetOpDesc(), ATTR_ALL_GEARS_INFO, shapes);
  1093. if (!shapes.empty()) {
  1094. is_online_infer_dynamic_ = true;
  1095. std::vector<std::string> shape_strs = ge::StringUtils::Split(shapes, ';');
  1096. for (const auto &shape_str : shape_strs) {
  1097. if (shape_str.empty()) {
  1098. continue;
  1099. }
  1100. std::vector<int32_t> gear_info;
  1101. std::vector<std::string> dims = ge::StringUtils::Split(shape_str, ',');
  1102. for (const auto &dim : dims) {
  1103. if (dim.empty()) {
  1104. continue;
  1105. }
  1106. gear_info.emplace_back(std::strtol(dim.c_str(), nullptr, kDecimal));
  1107. }
  1108. if (!gear_info.empty()) {
  1109. all_gears_info_.emplace_back(gear_info);
  1110. GELOGD("Init all gears info from %s, gaer info is %s", node->GetName().c_str(),
  1111. formats::JoinToString(gear_info).c_str());
  1112. }
  1113. }
  1114. }
  1115. }
  1116. Status DavinciModel::GetGetDynamicDimsNodeInfo(const NodePtr &node) {
  1117. GE_CHECK_NOTNULL(node->GetOpDesc());
  1118. size_t input_count = node->GetAllInDataAnchors().size();
  1119. GELOGI("input_anchor count of %s is %zu.", node->GetName().c_str(), input_count);
  1120. size_t get_dynamic_dims_index = input_count - kGetDynamicDimsCount;
  1121. auto in_anchor = node->GetAllInDataAnchors().at(get_dynamic_dims_index);
  1122. auto peer_out_anchor = in_anchor->GetPeerOutAnchor();
  1123. if (peer_out_anchor == nullptr) {
  1124. REPORT_INNER_ERROR("E19999", "In anchor index:%zu in op:%s(%s) peer anchor is nullptr, model_id:%u, check invalid",
  1125. get_dynamic_dims_index, node->GetName().c_str(), node->GetType().c_str(), model_id_);
  1126. GELOGE(PARAM_INVALID, "[Check][Param] In anchor index:%zu in op:%s(%s) peer anchor is nullptr, model_id:%u.",
  1127. get_dynamic_dims_index, node->GetName().c_str(), node->GetType().c_str(), model_id_);
  1128. return PARAM_INVALID;
  1129. }
  1130. auto peer_node = peer_out_anchor->GetOwnerNode();
  1131. auto op_desc = peer_node->GetOpDesc();
  1132. GE_CHECK_NOTNULL(op_desc);
  1133. if (op_desc->GetName() == kGetDynamicDimsName && op_desc->GetType() == GETDYNAMICDIMS) {
  1134. GELOGD("Start get info of %s.", op_desc->GetName().c_str());
  1135. auto input_addr = ModelUtils::GetInputDataAddrs(runtime_param_, node->GetOpDesc());
  1136. auto input_size = ModelUtils::GetInputSize(node->GetOpDesc());
  1137. if (input_addr.empty() || input_size.empty()) {
  1138. REPORT_INNER_ERROR("E19999", "input_addr size:%zu or input_length size:%zu in op:%s(%s) has empty, model_id:%u "
  1139. "check invalid", input_addr.size(), input_size.size(),
  1140. node->GetName().c_str(), node->GetType().c_str(), model_id_);
  1141. GELOGE(PARAM_INVALID, "[Check][Param] input_addr size:%zu or input_length size:%zu in op:%s(%s) is empty, "
  1142. "model_id:%u", input_addr.size(), input_size.size(),
  1143. node->GetName().c_str(), node->GetType().c_str(), model_id_);
  1144. return PARAM_INVALID;
  1145. }
  1146. auto input_desc = node->GetOpDesc()->GetInputDescPtr(get_dynamic_dims_index);
  1147. GE_CHECK_NOTNULL(input_desc);
  1148. if (input_desc->GetShape().GetDims().empty()) {
  1149. REPORT_INNER_ERROR("E19999", "input_desc_index:%zu in op:%s(%s) shape dim is empty, model_id:%u, check invalid",
  1150. get_dynamic_dims_index, node->GetName().c_str(), node->GetType().c_str(), model_id_);
  1151. GELOGE(PARAM_INVALID, "[Check][Param] input_desc_index:%zu in op:%s(%s) shape dim is empty, model_id:%u",
  1152. get_dynamic_dims_index, node->GetName().c_str(), node->GetType().c_str(), model_id_);
  1153. return PARAM_INVALID;
  1154. }
  1155. netoutput_last_input_addr_ = input_addr[get_dynamic_dims_index];
  1156. netoutput_last_input_size_ = input_size[get_dynamic_dims_index];
  1157. shape_of_cur_dynamic_dims_ = input_desc->GetShape().GetDims().at(0);
  1158. GELOGD("Shape of cur dynamic dims is %zu, size is %ld, addr is %p.", shape_of_cur_dynamic_dims_,
  1159. netoutput_last_input_size_, netoutput_last_input_addr_);
  1160. }
  1161. return SUCCESS;
  1162. }
  1163. Status DavinciModel::GetGearAndRealOutSizeInfo(const ComputeGraphPtr &graph, const NodePtr &node) {
  1164. GELOGD("Start get gear and real output size info of %s.", node->GetName().c_str());
  1165. merge_nodes_gear_and_real_out_size_info_.clear();
  1166. size_t idx = 0;
  1167. for (const auto &in_anchor : node->GetAllInDataAnchors()) {
  1168. auto peer_out_anchor = in_anchor->GetPeerOutAnchor();
  1169. if (peer_out_anchor == nullptr) {
  1170. continue;
  1171. }
  1172. auto peer_node = peer_out_anchor->GetOwnerNode();
  1173. auto op_desc = peer_node->GetOpDesc();
  1174. GE_CHECK_NOTNULL(op_desc);
  1175. if ((peer_node->GetType() == CASE) && (op_desc->HasAttr(ATTR_INSERT_BY_MBATCH))) {
  1176. if (GetRealOutputSizeOfCase(graph, idx, peer_node) != SUCCESS) {
  1177. GELOGE(PARAM_INVALID, "[Get][RealOutputSizeOfCase] %s failed.", peer_node->GetName().c_str());
  1178. return PARAM_INVALID;
  1179. }
  1180. }
  1181. idx++;
  1182. }
  1183. return SUCCESS;
  1184. }
  1185. Status DavinciModel::GetRealOutputSizeOfCase(const ComputeGraphPtr &graph, size_t input_index,
  1186. const NodePtr &case_node) {
  1187. GELOGD("Start get output size of %s, which is %zu input to netoutput", case_node->GetName().c_str(), input_index);
  1188. const auto &func_desc = case_node->GetOpDesc();
  1189. GE_CHECK_NOTNULL(func_desc);
  1190. std::map<vector<int32_t>, int64_t> gear_and_real_out_size_info;
  1191. for (const auto &name : func_desc->GetSubgraphInstanceNames()) {
  1192. const auto &subgraph = graph->GetSubgraph(name);
  1193. if (subgraph == nullptr) {
  1194. REPORT_INNER_ERROR("E19999", "Get name:%s subgraph in graph:%s fail, model_id:%u, check invalid",
  1195. name.c_str(), graph->GetName().c_str(), model_id_);
  1196. GELOGE(GE_GRAPH_EMPTY_SUBGRAPH, "[Get][Subgraph] %s in graph:%s failed, model_id:%u.",
  1197. name.c_str(), graph->GetName().c_str(), model_id_);
  1198. return GE_GRAPH_EMPTY_SUBGRAPH;
  1199. }
  1200. for (auto &node : subgraph->GetDirectNode()) {
  1201. if (node->GetType() == NETOUTPUT) {
  1202. auto op_desc = node->GetOpDesc();
  1203. GE_CHECK_NOTNULL(op_desc);
  1204. string batch_label;
  1205. if (AttrUtils::GetStr(op_desc, ATTR_NAME_BATCH_LABEL, batch_label)) {
  1206. size_t batch_index = static_cast<size_t>(stoi(batch_label.substr(batch_label.rfind('_') + 1)));
  1207. GELOGD("Batch index of %s is %zu.", op_desc->GetName().c_str(), batch_index);
  1208. if (batch_index > all_gears_info_.size()) {
  1209. REPORT_INNER_ERROR("E19999", "Batch_index:%zu in op:%s(%s) > all_gears_info.size:%zu, model_id:%u, "
  1210. "check invalid", batch_index,
  1211. op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1212. all_gears_info_.size(), model_id_);
  1213. GELOGE(PARAM_INVALID, "[Check][Param] Batch_index:%zu in op:%s(%s) > all_gears_info.size:%zu, "
  1214. "model_id:%u.", batch_index, op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1215. all_gears_info_.size(), model_id_);
  1216. return PARAM_INVALID;
  1217. }
  1218. const vector<int64_t> input_size_list = ModelUtils::GetInputSize(op_desc);
  1219. auto tensor_desc = op_desc->GetInputDescPtr(input_index);
  1220. GE_CHECK_NOTNULL(tensor_desc);
  1221. int64_t data_size = 0;
  1222. if (TensorUtils::GetTensorSizeInBytes(*tensor_desc, data_size) != GRAPH_SUCCESS) {
  1223. REPORT_INNER_ERROR("E19999", "Get input TensorSize in op:%s(%s) failed, input_index:%zu, model_id:%u",
  1224. op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1225. input_index, model_id_);
  1226. GELOGE(FAILED, "[Get][TensorSize] in op:%s(%s) failed, input_index:%zu, model_id:%u",
  1227. op_desc->GetName().c_str(), op_desc->GetType().c_str(), input_index, model_id_);
  1228. return FAILED;
  1229. }
  1230. gear_and_real_out_size_info[all_gears_info_[batch_index]] = data_size;
  1231. GELOGD("Get real gear index is: %zu, gear info is %s, size is %ld, tensor size is %ld",
  1232. batch_index, formats::JoinToString(all_gears_info_[batch_index]).c_str(),
  1233. input_size_list[input_index], data_size);
  1234. }
  1235. break;
  1236. }
  1237. }
  1238. }
  1239. merge_nodes_gear_and_real_out_size_info_[input_index] = gear_and_real_out_size_info;
  1240. return SUCCESS;
  1241. }
  1242. Status DavinciModel::GetGearAndRealOutShapeInfo(const ComputeGraphPtr &graph, const NodePtr &node) {
  1243. GELOGD("Start to get dynamic output dims of %s", node->GetName().c_str());
  1244. merge_nodes_gear_and_real_out_shape_info_.clear();
  1245. size_t idx = 0;
  1246. for (const auto &in_anchor : node->GetAllInDataAnchors()) {
  1247. auto peer_out_anchor = in_anchor->GetPeerOutAnchor();
  1248. if (peer_out_anchor == nullptr) {
  1249. continue;
  1250. }
  1251. auto peer_node = peer_out_anchor->GetOwnerNode();
  1252. auto op_desc = peer_node->GetOpDesc();
  1253. GE_CHECK_NOTNULL(op_desc);
  1254. if ((peer_node->GetType() == CASE) && (op_desc->HasAttr(ATTR_INSERT_BY_MBATCH))) {
  1255. std::vector<std::string> dynamic_output_shape_info;
  1256. if (!AttrUtils::GetListStr(node->GetOpDesc(), ATTR_NAME_DYNAMIC_OUTPUT_DIMS, dynamic_output_shape_info)) {
  1257. GELOGD("Can not get dynamic output dims attr from %s", node->GetName().c_str());
  1258. return SUCCESS;
  1259. }
  1260. GELOGI("Dynamic output shape info is %s", formats::JoinToString(dynamic_output_shape_info).c_str());
  1261. std::vector<vector<int64_t>> dynamic_output_shape;
  1262. ParseDynamicOutShape(dynamic_output_shape_info, dynamic_output_shape);
  1263. std::map<vector<int32_t>, vector<int64_t>> gear_and_real_out_shape_info;
  1264. for (auto &it : dynamic_output_shape) {
  1265. auto gear_index = static_cast<size_t>(it[0]);
  1266. if (gear_index > all_gears_info_.size()) {
  1267. REPORT_INNER_ERROR("E19999", "gear index:%zu in op:%s(%s) > all_gears_info.size:%zu in model:%u "
  1268. "check invalid", gear_index, op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1269. all_gears_info_.size(), model_id_);
  1270. GELOGE(PARAM_INVALID, "[Check][Param] gear index:%zu in op:%s(%s) > all_gears_info.size:%zu in model:%u.",
  1271. gear_index, op_desc->GetName().c_str(), op_desc->GetType().c_str(), all_gears_info_.size(), model_id_);
  1272. return PARAM_INVALID;
  1273. }
  1274. if (static_cast<size_t>(it[1]) == idx) {
  1275. vector<int64_t> output_shape;
  1276. for (size_t i = 2; i < it.size(); ++i) {
  1277. output_shape.emplace_back(it[i]);
  1278. }
  1279. gear_and_real_out_shape_info[all_gears_info_[gear_index]] = output_shape;
  1280. GELOGD("Get real gear index is: %zu, gear info is %s, output shape is %s",
  1281. gear_index, formats::JoinToString(all_gears_info_[gear_index]).c_str(),
  1282. formats::JoinToString(output_shape).c_str());
  1283. }
  1284. }
  1285. merge_nodes_gear_and_real_out_shape_info_[idx] = gear_and_real_out_shape_info;
  1286. }
  1287. idx++;
  1288. }
  1289. return SUCCESS;
  1290. }
  1291. void DavinciModel::ParseDynamicOutShape(const std::vector<std::string> &str_info,
  1292. std::vector<vector<int64_t>> &vec_info) {
  1293. for (size_t i = 0; i < str_info.size(); ++i) {
  1294. std::vector<int64_t> shape;
  1295. std::vector<std::string> dims = ge::StringUtils::Split(str_info[i], ',');
  1296. for (const auto &dim : dims) {
  1297. if (dim.empty()) {
  1298. continue;
  1299. }
  1300. shape.emplace_back(std::strtol(dim.c_str(), nullptr, kDecimal));
  1301. }
  1302. GELOGI("Shape from attr is %s", formats::JoinToString(shape).c_str());
  1303. vec_info.emplace_back(shape);
  1304. }
  1305. }
  1306. Status DavinciModel::GetLabelGotoAddr(uint32_t label_index, rtMemType_t mem_type, void *&arg_addr, uint32_t &arg_size) {
  1307. std::lock_guard<std::mutex> lock(label_args_mutex_);
  1308. auto it = label_goto_args_.find(label_index);
  1309. if (it != label_goto_args_.end()) {
  1310. arg_addr = it->second.first;
  1311. arg_size = it->second.second;
  1312. return SUCCESS;
  1313. }
  1314. if (label_index >= label_list_.size()) {
  1315. REPORT_INNER_ERROR("E19999", "Param label index:%u >= label_list_.size:%zu in model:%u, check invalid",
  1316. label_index, label_list_.size(), model_id_);
  1317. GELOGE(INTERNAL_ERROR, "[Check][Param] Param label index:%u >= label_list_.size:%zu in model:%u",
  1318. label_index, label_list_.size(), model_id_);
  1319. return INTERNAL_ERROR;
  1320. }
  1321. GE_CHECK_NOTNULL(label_list_[label_index]);
  1322. vector<rtLabel_t> label_used = { label_list_[label_index] };
  1323. arg_size = label_used.size() * sizeof(rtLabelDevInfo);
  1324. rtError_t rt_ret = rtMalloc(&arg_addr, arg_size, mem_type);
  1325. if (rt_ret != RT_ERROR_NONE) {
  1326. REPORT_CALL_ERROR("E19999", "Call rtMalloc failed, size:%u, ret:0x%X", arg_size, rt_ret);
  1327. GELOGE(RT_FAILED, "[Call][RtMalloc] failed, size:%u, ret:0x%X", arg_size, rt_ret);
  1328. return RT_ERROR_TO_GE_STATUS(rt_ret);
  1329. }
  1330. label_goto_args_[label_index] = { arg_addr, arg_size };
  1331. rt_ret = rtLabelListCpy(label_used.data(), label_used.size(), arg_addr, arg_size);
  1332. if (rt_ret != RT_ERROR_NONE) {
  1333. REPORT_CALL_ERROR("E19999", "Call rtLabelListCpy failed, ret:0x%X", rt_ret);
  1334. GELOGE(RT_FAILED, "[Call][RtLabelListCpy] failed, ret:0x%X", rt_ret);
  1335. return RT_ERROR_TO_GE_STATUS(rt_ret);
  1336. }
  1337. return SUCCESS;
  1338. }
  1339. void DavinciModel::SetGlobalStep(void *global_step, uint64_t global_step_size) {
  1340. global_step_addr_ = global_step;
  1341. global_step_size_ = global_step_size;
  1342. }
  1343. /// @ingroup ge
  1344. /// @brief LabelSet Op Initialize.
  1345. /// @param [in] op_desc: LabelSet Op descriptor.
  1346. /// @return Status
  1347. Status DavinciModel::InitLabelSet(const OpDescPtr &op_desc) {
  1348. uint32_t label_index = 0;
  1349. if (!AttrUtils::GetInt(op_desc, ATTR_NAME_LABEL_SWITCH_INDEX, label_index)) {
  1350. REPORT_INNER_ERROR("E19999", "Get Attr:%s in op:%s(%s) fail, model_id:%u, check invalid",
  1351. ATTR_NAME_LABEL_SWITCH_INDEX.c_str(),
  1352. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  1353. GELOGE(INTERNAL_ERROR, "[Get][Attr] %s in op:%s(%s) fail, model_id:%u",
  1354. ATTR_NAME_LABEL_SWITCH_INDEX.c_str(), op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  1355. return INTERNAL_ERROR;
  1356. }
  1357. if (label_index >= LabelNum()) {
  1358. REPORT_INNER_ERROR("E19999", "label_switch_index:%u in op:%s(%s) >= label_num:%u in model:%u, check invalid",
  1359. label_index, op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1360. LabelNum(), model_id_);
  1361. GELOGE(INTERNAL_ERROR, "[Check][Param] label_switch_index:%u in op:%s(%s) >= label_num:%u in model:%u",
  1362. label_index, op_desc->GetName().c_str(), op_desc->GetType().c_str(), LabelNum(), model_id_);
  1363. return INTERNAL_ERROR;
  1364. }
  1365. if (label_id_indication_.count(label_index) > 0) {
  1366. REPORT_INNER_ERROR("E19999", "label_switch_index:%u in op:%s(%s) is already used in model:%u, check invalid",
  1367. label_index, op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1368. model_id_);
  1369. GELOGE(INTERNAL_ERROR, "[Check][Param] label_switch_index:%u in op:%s(%s) is already used in model:%u",
  1370. label_index, op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  1371. return INTERNAL_ERROR;
  1372. }
  1373. rtStream_t stream = nullptr;
  1374. uint32_t stream_id = static_cast<uint32_t>(op_desc->GetStreamId());
  1375. if (stream_list_.size() == 1) {
  1376. stream = stream_list_[0];
  1377. } else if (stream_list_.size() > stream_id) {
  1378. stream = stream_list_[stream_id];
  1379. } else {
  1380. REPORT_INNER_ERROR("E19999", "stream_id:%u in op:%s(%s) >= stream size:%zu in model:%u, check invalid",
  1381. stream_id, op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1382. stream_list_.size(), model_id_);
  1383. GELOGE(INTERNAL_ERROR, "[Check][Param] stream_id:%u in op:%s(%s) >= stream size:%zu in model:%u",
  1384. stream_id, op_desc->GetName().c_str(), op_desc->GetType().c_str(), stream_list_.size(), model_id_);
  1385. return INTERNAL_ERROR;
  1386. }
  1387. rtLabel_t rt_label = nullptr;
  1388. rtError_t rt_error = rtLabelCreateExV2(&rt_label, rt_model_handle_, stream);
  1389. if (rt_error != RT_ERROR_NONE || rt_label == nullptr) {
  1390. REPORT_CALL_ERROR("E19999", "Call rtLabelCreateExV2 failed, ret:0x%X", rt_error);
  1391. GELOGE(INTERNAL_ERROR, "[Call][RtLabelCreateExV2] InitLabelSet: %s create label failed, ret:0x%x.",
  1392. op_desc->GetName().c_str(), rt_error);
  1393. return INTERNAL_ERROR;
  1394. }
  1395. GELOGI("InitLabelSet: label[%u]=%p stream[%u]=%p", label_index, rt_label, stream_id, stream);
  1396. label_id_indication_.insert(label_index);
  1397. label_list_[label_index] = rt_label;
  1398. return SUCCESS;
  1399. }
  1400. Status DavinciModel::InitVariable(const OpDescPtr &op_desc, map<string, OpDescPtr> &variable_by_name) {
  1401. if (!known_node_) {
  1402. if (op_desc->GetName() == NODE_NAME_GLOBAL_STEP) {
  1403. const auto output_sizes = ModelUtils::GetOutputSize(op_desc);
  1404. if (!output_sizes.empty()) {
  1405. global_step_size_ = output_sizes[0];
  1406. }
  1407. const auto output_addrs = ModelUtils::GetOutputDataAddrs(runtime_param_, op_desc);
  1408. if (!output_addrs.empty()) {
  1409. global_step_addr_ = output_addrs[0];
  1410. }
  1411. }
  1412. }
  1413. if (op_desc->HasAttr(VAR_ATTR_VAR_IS_BROADCAST)) {
  1414. broadcast_variable_[op_desc->GetName()] = op_desc->GetOutputDesc(0);
  1415. }
  1416. variable_by_name[op_desc->GetName()] = op_desc;
  1417. return SUCCESS;
  1418. }
  1419. /// @ingroup ge
  1420. /// @brief ACL case, Load task list with queue.
  1421. /// @param [in] input_queue_ids: input queue ids from user, nums equal Data Op.
  1422. /// @param [in] output_queue_ids: input queue ids from user, nums equal NetOutput Op.
  1423. /// @return: 0 for success / others for failed
  1424. Status DavinciModel::SetQueIds(const std::vector<uint32_t> &input_queue_ids,
  1425. const std::vector<uint32_t> &output_queue_ids) {
  1426. if (input_queue_ids.empty() && output_queue_ids.empty()) {
  1427. REPORT_INNER_ERROR("E19999", "Param input_queue_ids.size:%zu and output_queue_ids.size:%zu is empty, model_id:%u,"
  1428. "check invalid", input_queue_ids.size(), output_queue_ids.size(),
  1429. model_id_);
  1430. GELOGE(ACL_ERROR_GE_EXEC_MODEL_QUEUE_ID_INVALID, "[Check][Param] Param is empty, model_id:%u", model_id_);
  1431. return ACL_ERROR_GE_EXEC_MODEL_QUEUE_ID_INVALID;
  1432. }
  1433. input_queue_ids_ = input_queue_ids;
  1434. output_queue_ids_ = output_queue_ids;
  1435. return SUCCESS;
  1436. }
  1437. ///
  1438. /// @ingroup ge
  1439. /// @brief ACL case, Load task list with queue.
  1440. /// @param [in] input_que_ids: input queue ids from user, nums equal Data Op.
  1441. /// @param [in] output_que_ids: input queue ids from user, nums equal NetOutput Op.
  1442. /// @return: 0 for success / others for failed
  1443. ///
  1444. Status DavinciModel::LoadWithQueue() {
  1445. if (input_queue_ids_.empty() && output_queue_ids_.empty()) {
  1446. return SUCCESS;
  1447. }
  1448. if (input_queue_ids_.size() != input_data_info_.size()) {
  1449. REPORT_INNER_ERROR("E19999", "Param input_queue_ids_.size:%zu != input_data_info_.size:%zu, model_id:%u,"
  1450. "check invalid", input_queue_ids_.size(), input_data_info_.size(),
  1451. model_id_);
  1452. GELOGE(ACL_ERROR_GE_EXEC_MODEL_QUEUE_ID_INVALID, "[Check][Param] Input queue ids not match model: "
  1453. "input_queue=%zu input_data=%zu, model_id:%u", input_queue_ids_.size(), input_data_info_.size(), model_id_);
  1454. return ACL_ERROR_GE_EXEC_MODEL_QUEUE_ID_INVALID;
  1455. }
  1456. if (output_queue_ids_.size() != output_data_info_.size()) {
  1457. REPORT_INNER_ERROR("E19999", "Param output_queue_ids_.size:%zu != output_data_info_.size:%zu, model_id:%u,"
  1458. "check invalid", output_queue_ids_.size(), output_data_info_.size(), model_id_);
  1459. GELOGE(ACL_ERROR_GE_EXEC_MODEL_QUEUE_ID_INVALID,
  1460. "[Check][Param] Output queue ids not match model: output_queue=%zu output_data=%zu, model_id:%u",
  1461. output_queue_ids_.size(), output_data_info_.size(), model_id_);
  1462. return ACL_ERROR_GE_EXEC_MODEL_QUEUE_ID_INVALID;
  1463. }
  1464. GE_CHK_STATUS_RET(AddHeadStream(), "[Add][HeadStream] failed, model_id:%u", model_id_);
  1465. // Binding input_queue and Data Op.
  1466. GE_CHK_STATUS_RET(BindInputQueue(), "[Bind][InputQueue] failed, model_id:%u", model_id_);
  1467. GE_CHK_STATUS_RET(CpuTaskModelZeroCopy(input_mbuf_list_, input_data_info_),
  1468. "[Call][CpuTaskModelZeroCopy] failed, model_id:%u", model_id_);
  1469. // Binding output_queue and NetOutput Op.
  1470. GE_CHK_STATUS_RET(BindOutputQueue(), "[Bind][OutputQueue] failed, model_id:%u", model_id_);
  1471. GE_CHK_STATUS_RET(CpuTaskModelZeroCopy(output_mbuf_list_, output_data_info_),
  1472. "[Call][CpuTaskModelZeroCopy] failed, model_id:%u", model_id_);
  1473. GE_CHK_STATUS_RET(CpuActiveStream(), "[Call][CpuActiveStream] failed, model_id:%u", model_id_);
  1474. GE_CHK_STATUS_RET(CpuWaitEndGraph(), "[Call][CpuWaitEndGraph] failed, model_id:%u", model_id_);
  1475. GE_CHK_STATUS_RET(BindEnqueue(), "[Call][BindEnqueue] failed, model_id:%u", model_id_);
  1476. GE_CHK_STATUS_RET(CpuModelRepeat(), "[Call][CpuModelRepeat] failed, model_id:%u", model_id_);
  1477. return SUCCESS;
  1478. }
  1479. /// @ingroup ge
  1480. /// @brief queue schedule, Bind input queue to Data output address.
  1481. /// @return: 0 for success / others for failed
  1482. Status DavinciModel::BindInputQueue() {
  1483. // Caller checked: input_queue_ids_.size() == input_size_list_.size() != input_addr_list_.size()
  1484. for (size_t i = 0; i < input_queue_ids_.size(); ++i) {
  1485. auto it = input_data_info_.find(i);
  1486. if (it == input_data_info_.end()) {
  1487. GELOGE(FAILED, "[Check][Param] Input not match: tensor num=%zu, Queue id index=%zu", input_data_info_.size(), i);
  1488. return FAILED;
  1489. }
  1490. uint32_t queue_id = input_queue_ids_[i];
  1491. if (it->second.GetDataInfo().empty()) {
  1492. GELOGE(INTERNAL_ERROR, "[Check][Param] the %zu input_queue not set data_info.", i);
  1493. return INTERNAL_ERROR;
  1494. }
  1495. uint32_t data_size = static_cast<uint32_t>(it->second.GetDataInfo().at(0).first);
  1496. uintptr_t data_addr = reinterpret_cast<uintptr_t>(it->second.GetDataInfo().at(0).second);
  1497. GELOGI("BindInputToQueue: graph_%u index[%zu] queue id[%u] output addr[0x%lx] output size[%u]",
  1498. runtime_param_.graph_id, i, queue_id, data_addr, data_size);
  1499. rtError_t rt_ret = rtModelBindQueue(rt_model_handle_, queue_id, RT_MODEL_INPUT_QUEUE);
  1500. if (rt_ret != RT_ERROR_NONE) {
  1501. REPORT_CALL_ERROR("E19999", "Call rtModelBindQueue failed, ret: 0x%X", rt_ret);
  1502. GELOGE(RT_FAILED, "[Call][RtModelBindQueue] failed, ret: 0x%X", rt_ret);
  1503. return RT_ERROR_TO_GE_STATUS(rt_ret);
  1504. }
  1505. if (CpuModelDequeue(queue_id) != SUCCESS) {
  1506. return INTERNAL_ERROR;
  1507. }
  1508. }
  1509. return SUCCESS;
  1510. }
  1511. /// @ingroup ge
  1512. /// @brief definiteness queue schedule, bind input queue to task.
  1513. /// @param [in] queue_id: input queue id from user.
  1514. /// @return: 0 for success / others for failed
  1515. Status DavinciModel::CpuModelDequeue(uint32_t queue_id) {
  1516. GELOGI("Set CpuKernel model dequeue task enter.");
  1517. std::shared_ptr<CpuTaskModelDequeue> dequeue_task = MakeShared<CpuTaskModelDequeue>(rt_entry_stream_);
  1518. if (dequeue_task == nullptr) {
  1519. REPORT_CALL_ERROR("E19999", "New CpuTaskModelDequeue failed, model_id:%u", model_id_);
  1520. GELOGE(MEMALLOC_FAILED, "[New][CpuTaskModelDequeue] task failed, model_id:%u", model_id_);
  1521. return MEMALLOC_FAILED;
  1522. }
  1523. // Get DataOp Output address and bind to queue.
  1524. uintptr_t in_mbuf = 0;
  1525. Status status = dequeue_task->Init(queue_id, in_mbuf);
  1526. if (status != SUCCESS) {
  1527. return status;
  1528. }
  1529. cpu_task_list_.push_back(dequeue_task);
  1530. input_mbuf_list_.push_back(in_mbuf);
  1531. GELOGI("Set CpuKernel model dequeue task success.");
  1532. return SUCCESS;
  1533. }
  1534. Status DavinciModel::CpuTaskModelZeroCopy(std::vector<uintptr_t> &mbuf_list,
  1535. const map<uint32_t, ZeroCopyOffset> &outside_addrs) {
  1536. GELOGI("Set CpuKernel model zero_copy task enter.");
  1537. std::shared_ptr<CpuTaskZeroCopy> zero_copy = MakeShared<CpuTaskZeroCopy>(rt_entry_stream_);
  1538. if (zero_copy == nullptr) {
  1539. REPORT_CALL_ERROR("E19999", "New CpuTaskZeroCopy failed, model_id:%u", model_id_);
  1540. GELOGE(MEMALLOC_FAILED, "[New][CpuTaskZeroCopy] failed, model_id:%u", model_id_);
  1541. return MEMALLOC_FAILED;
  1542. }
  1543. // mdc zero_copy not support l2 fusion
  1544. Status status = zero_copy->Init(mbuf_list, outside_addrs);
  1545. if (status != SUCCESS) {
  1546. return status;
  1547. }
  1548. cpu_task_list_.push_back(zero_copy);
  1549. GELOGI("Set CpuKernel model zero_copy task success.");
  1550. return SUCCESS;
  1551. }
  1552. /// @ingroup ge
  1553. /// @brief queue schedule, bind output queue to NetOutput input address.
  1554. /// @return: 0 for success / others for failed
  1555. Status DavinciModel::BindOutputQueue() {
  1556. // Caller checked: input_queue_ids_.size() == input_size_list_.size() != input_addr_list_.size()
  1557. for (size_t i = 0; i < output_queue_ids_.size(); ++i) {
  1558. auto it = output_data_info_.find(i);
  1559. if (it == output_data_info_.end()) {
  1560. REPORT_INNER_ERROR("E19999", "Index:%zu can't find in output_data_info_ size:%zu in model_id:%u, check invalid",
  1561. i, output_data_info_.size(), model_id_);
  1562. GELOGE(FAILED, "[Check][Param] Index:%zu can't find in output_data_info_ size:%zu in model_id:%u",
  1563. i, output_data_info_.size(), model_id_);
  1564. return FAILED;
  1565. }
  1566. uint32_t queue_id = output_queue_ids_[i];
  1567. if (it->second.GetDataInfo().empty()) {
  1568. REPORT_INNER_ERROR("E19999", "Index:%zu out_data_info in model:%u is empty, check invalid", i, model_id_);
  1569. GELOGE(INTERNAL_ERROR, "[Check][Param] Index:%zu out_data_info in model:%u is empty, check invalid",
  1570. i, model_id_);
  1571. return INTERNAL_ERROR;
  1572. }
  1573. uint32_t data_size = static_cast<uint32_t>(it->second.GetDataInfo().at(0).first);
  1574. uintptr_t data_addr = reinterpret_cast<uintptr_t>(it->second.GetDataInfo().at(0).second);
  1575. GELOGI("BindOutputToQueue: graph_%u index[%zu] queue id[%u] input addr[0x%lx] input size[%u]",
  1576. runtime_param_.graph_id, i, queue_id, data_addr, data_size);
  1577. rtError_t rt_ret = rtModelBindQueue(rt_model_handle_, queue_id, RT_MODEL_OUTPUT_QUEUE);
  1578. if (rt_ret != RT_ERROR_NONE) {
  1579. REPORT_CALL_ERROR("E19999", "Call rtModelBindQueue failed, queue_id:%u, ret:0x%X", queue_id, rt_ret);
  1580. GELOGE(RT_FAILED, "[Call][RtModelBindQueue] failed, queue_id:%u, ret:0x%X", queue_id, rt_ret);
  1581. return RT_ERROR_TO_GE_STATUS(rt_ret);
  1582. }
  1583. Status status = CpuModelPrepareOutput(data_addr, data_size);
  1584. if (status != SUCCESS) {
  1585. return status;
  1586. }
  1587. }
  1588. return SUCCESS;
  1589. }
  1590. /// @ingroup ge
  1591. /// @brief definiteness queue schedule, bind output queue to task.
  1592. /// @param [in] addr: NetOutput Op input tensor address.
  1593. /// @param [in] size: NetOutput Op input tensor size.
  1594. /// @return: 0 for success / others for failed
  1595. Status DavinciModel::CpuModelPrepareOutput(uintptr_t addr, uint32_t size) {
  1596. GELOGI("Set CpuKernel model enqueue task enter.");
  1597. if (input_mbuf_list_.empty()) {
  1598. REPORT_INNER_ERROR("E19999", "input_mbuf_list_ is empty, model_id:%u, check invalid", model_id_);
  1599. GELOGE(FAILED, "[Check][Param] input_mbuf_list_ is empty, model_id:%u", model_id_);
  1600. return FAILED;
  1601. }
  1602. std::shared_ptr<CpuTaskPrepareOutput> prepare_output = MakeShared<CpuTaskPrepareOutput>(rt_entry_stream_);
  1603. if (prepare_output == nullptr) {
  1604. REPORT_CALL_ERROR("E19999", "New CpuTaskPrepareOutput failed, model_id:%u", model_id_);
  1605. GELOGE(MEMALLOC_FAILED, "[New][CpuTaskPrepareOutput] failed, model_id:%u", model_id_);
  1606. return MEMALLOC_FAILED;
  1607. }
  1608. uintptr_t out_mbuf = 0;
  1609. if (prepare_output->Init(addr, size, input_mbuf_list_.back(), out_mbuf) != SUCCESS) {
  1610. return FAILED;
  1611. }
  1612. cpu_task_list_.push_back(prepare_output);
  1613. output_mbuf_list_.push_back(out_mbuf);
  1614. GELOGI("Set CpuKernel model enqueue task success.");
  1615. return SUCCESS;
  1616. }
  1617. ///
  1618. /// @ingroup ge
  1619. /// @brief definiteness queue schedule, active original model stream.
  1620. /// @return: 0 for success / others for failed
  1621. ///
  1622. Status DavinciModel::CpuActiveStream() {
  1623. GELOGI("Set CpuKernel active stream task enter.");
  1624. std::shared_ptr<CpuTaskActiveEntry> active_entry = MakeShared<CpuTaskActiveEntry>(rt_entry_stream_);
  1625. if (active_entry == nullptr) {
  1626. REPORT_CALL_ERROR("E19999", "New CpuTaskActiveEntry failed, model_id:%u", model_id_);
  1627. GELOGE(MEMALLOC_FAILED, "[New][CpuTaskActiveEntry] failed, model_id:%u", model_id_);
  1628. return MEMALLOC_FAILED;
  1629. }
  1630. Status status = active_entry->Init(rt_head_stream_);
  1631. if (status != SUCCESS) {
  1632. return status;
  1633. }
  1634. cpu_task_list_.push_back(active_entry);
  1635. GELOGI("Set CpuKernel active stream task success.");
  1636. return SUCCESS;
  1637. }
  1638. /// @ingroup ge
  1639. /// @brief definiteness queue schedule, wait for end graph.
  1640. /// @return: 0 for success / others for failed
  1641. Status DavinciModel::CpuWaitEndGraph() {
  1642. GELOGI("Set CpuKernel wait end graph task enter.");
  1643. std::shared_ptr<CpuTaskWaitEndGraph> wait_endgraph = MakeShared<CpuTaskWaitEndGraph>(rt_entry_stream_);
  1644. if (wait_endgraph == nullptr) {
  1645. REPORT_CALL_ERROR("E19999", "New CpuTaskWaitEndGraph failed, model_id:%u", model_id_);
  1646. GELOGE(MEMALLOC_FAILED, "[New][CpuTaskWaitEndGraph] failed, model_id:%u", model_id_);
  1647. return MEMALLOC_FAILED;
  1648. }
  1649. Status status = wait_endgraph->Init(runtime_model_id_);
  1650. if (status != SUCCESS) {
  1651. return status;
  1652. }
  1653. cpu_task_list_.push_back(wait_endgraph);
  1654. GELOGI("Set CpuKernel wait end graph task success.");
  1655. return SUCCESS;
  1656. }
  1657. Status DavinciModel::BindEnqueue() {
  1658. for (size_t i = 0; i < output_queue_ids_.size(); ++i) {
  1659. auto it = output_data_info_.find(i);
  1660. if (it == output_data_info_.end()) {
  1661. REPORT_INNER_ERROR("E19999", "Index:%zu can't find in output_data_info_ size:%zu in model_id:%u, check invalid",
  1662. i, output_data_info_.size(), model_id_);
  1663. GELOGE(FAILED, "Index:%zu can't find in output_data_info_ size:%zu in model_id:%u",
  1664. i, output_data_info_.size(), model_id_);
  1665. return FAILED;
  1666. }
  1667. uint32_t queue_id = output_queue_ids_[i];
  1668. if (CpuModelEnqueue(queue_id, output_mbuf_list_[i]) != SUCCESS) {
  1669. return INTERNAL_ERROR;
  1670. }
  1671. }
  1672. return SUCCESS;
  1673. }
  1674. Status DavinciModel::CpuModelEnqueue(uint32_t queue_id, uintptr_t out_mbuf) {
  1675. GELOGI("Set CpuKernel model enqueue task enter.");
  1676. std::shared_ptr<CpuTaskModelEnqueue> model_enqueue = MakeShared<CpuTaskModelEnqueue>(rt_entry_stream_);
  1677. if (model_enqueue == nullptr) {
  1678. REPORT_CALL_ERROR("E19999", "New CpuTaskModelEnqueue failed, model_id:%u", model_id_);
  1679. GELOGE(MEMALLOC_FAILED, "[New][CpuTaskModelEnqueue] failed, model_id:%u", model_id_);
  1680. return MEMALLOC_FAILED;
  1681. }
  1682. Status status = model_enqueue->Init(queue_id, out_mbuf);
  1683. if (status != SUCCESS) {
  1684. return status;
  1685. }
  1686. cpu_task_list_.push_back(model_enqueue);
  1687. GELOGI("Set CpuKernel model enqueue task enter.");
  1688. return SUCCESS;
  1689. }
  1690. /// @ingroup ge
  1691. /// @brief definiteness queue schedule, repeat run model.
  1692. /// @return: 0 for success / others for failed
  1693. Status DavinciModel::CpuModelRepeat() {
  1694. GELOGI("Set CpuKernel repeat task enter.");
  1695. std::shared_ptr<CpuTaskModelRepeat> model_repeat = MakeShared<CpuTaskModelRepeat>(rt_entry_stream_);
  1696. if (model_repeat == nullptr) {
  1697. REPORT_CALL_ERROR("E19999", "New CpuTaskModelRepeat failed, model_id:%u", model_id_);
  1698. GELOGE(MEMALLOC_FAILED, "[New][CpuTaskModelRepeat] failed, model_id:%u", model_id_);
  1699. return MEMALLOC_FAILED;
  1700. }
  1701. Status status = model_repeat->Init(runtime_model_id_);
  1702. if (status != SUCCESS) {
  1703. return status;
  1704. }
  1705. cpu_task_list_.push_back(model_repeat);
  1706. GELOGI("Set CpuKernel repeat task success.");
  1707. return SUCCESS;
  1708. }
  1709. Status DavinciModel::GetInputOutputDescInfo(vector<InputOutputDescInfo> &input_desc,
  1710. vector<InputOutputDescInfo> &output_desc) {
  1711. if (input_addrs_list_.empty() || input_addrs_list_[0].size() != 1) {
  1712. GELOGI("data_op_list_ is empty or input_desc size is not 1.");
  1713. } else {
  1714. vector<uint32_t> input_formats;
  1715. GE_CHK_STATUS_RET(GetInputDescInfo(input_desc, input_formats, false),
  1716. "[Get][InputDescInfo] failed, model_id:%u", model_id_);
  1717. }
  1718. vector<uint32_t> output_formats;
  1719. GE_CHK_STATUS_RET(GetOutputDescInfo(output_desc, output_formats),
  1720. "[Get][OutputDescInfo] failed, model_id:%u", model_id_);
  1721. return SUCCESS;
  1722. }
  1723. Status DavinciModel::GetInputOutputDescInfo(vector<InputOutputDescInfo> &input_desc,
  1724. vector<InputOutputDescInfo> &output_desc,
  1725. vector<uint32_t> &input_formats,
  1726. vector<uint32_t> &output_formats, bool by_dims) {
  1727. if (input_addrs_list_.empty() || input_addrs_list_[0].size() != 1) {
  1728. REPORT_INNER_ERROR("E19999", "input_addrs_list_ is empty or first member size != 1, model_id:%u, "
  1729. "check invalid", model_id_);
  1730. GELOGE(FAILED, "[Check][Param] input_addrs_list_ is empty or first member size != 1, model_id:%u", model_id_);
  1731. return FAILED;
  1732. }
  1733. GE_CHK_STATUS_RET(GetInputDescInfo(input_desc, input_formats, by_dims),
  1734. "[Get][InputDescInfo] failed, model_id:%u", model_id_);
  1735. GE_CHK_STATUS_RET(GetOutputDescInfo(output_desc, output_formats),
  1736. "[Get][OutputDescInfo] failed, model_id:%u", model_id_);
  1737. return SUCCESS;
  1738. }
  1739. ///
  1740. /// @ingroup ge
  1741. /// @brief Get dynamic batch_info
  1742. /// @param [out] batch_info
  1743. /// @param [out] dynamic_type
  1744. /// @return execute result
  1745. ///
  1746. Status DavinciModel::GetDynamicBatchInfo(std::vector<std::vector<int64_t>> &batch_info, int32_t &dynamic_type) const {
  1747. dynamic_type = dynamic_type_;
  1748. batch_info = batch_info_;
  1749. return SUCCESS;
  1750. }
  1751. ///
  1752. /// @ingroup ge
  1753. /// @brief Get combined dynamic dims info
  1754. /// @param [out] batch_info
  1755. /// @return None
  1756. ///
  1757. void DavinciModel::GetCombinedDynamicDims(std::vector<std::vector<int64_t>> &batch_info) const {
  1758. batch_info.clear();
  1759. batch_info = combined_batch_info_;
  1760. }
  1761. ///
  1762. /// @ingroup ge
  1763. /// @brief Get user designate shape order
  1764. /// @param [out] user_input_shape_order
  1765. /// @return None
  1766. ///
  1767. void DavinciModel::GetUserDesignateShapeOrder(std::vector<std::string> &user_input_shape_order) const {
  1768. user_input_shape_order.clear();
  1769. user_input_shape_order = user_designate_shape_order_;
  1770. }
  1771. ///
  1772. /// @ingroup ge
  1773. /// @brief Get AIPP input info
  1774. /// @param [in] index
  1775. /// @param [int] OpDescPtr
  1776. /// @return execute result
  1777. ///
  1778. Status DavinciModel::InitAippInfo(uint32_t index, const OpDescPtr &op_desc) {
  1779. if (!op_desc->HasAttr(ATTR_NAME_AIPP)) {
  1780. GELOGW("There is not AIPP related with index %u", index);
  1781. return SUCCESS;
  1782. }
  1783. domi::AippOpParams aipp_params;
  1784. GeAttrValue::NAMED_ATTRS aipp_attr;
  1785. GE_CHK_BOOL_RET_STATUS(AttrUtils::GetNamedAttrs(op_desc, ATTR_NAME_AIPP, aipp_attr), ACL_ERROR_GE_AIPP_NOT_EXIST,
  1786. "[Get][NamedAttrs] Data node:%s do not contain param aipp!", op_desc->GetName().c_str());
  1787. GE_CHK_STATUS_RET(OpUtils::ConvertAippParams(aipp_attr, &aipp_params),
  1788. "[Convert][AippParams] get aipp params failed, op:%s", op_desc->GetName().c_str());
  1789. GELOGI("Node data: %s, type: %s, current index: %u, current node related input rank: %u",
  1790. op_desc->GetName().c_str(), op_desc->GetType().c_str(), index, aipp_params.related_input_rank());
  1791. AippConfigInfo aipp_info;
  1792. GE_CHK_STATUS_RET(AippUtils::ConvertAippParams2AippInfo(&aipp_params, aipp_info),
  1793. "[Call][ConvertAippParams2AippInfo] failed, op:%s", op_desc->GetName().c_str());
  1794. aipp_info_list_[index] = aipp_info;
  1795. return SUCCESS;
  1796. }
  1797. ///
  1798. /// @ingroup ge
  1799. /// @brief Get AIPP input info
  1800. /// @param [in] index
  1801. /// @param [out] aipp_info
  1802. /// @return execute result
  1803. ///
  1804. Status DavinciModel::GetAippInfo(uint32_t index, AippConfigInfo &aipp_info) const {
  1805. const auto it = aipp_info_list_.find(index);
  1806. if (it == aipp_info_list_.end()) {
  1807. GELOGW("there is not AIPP related with index %u", index);
  1808. return ACL_ERROR_GE_AIPP_NOT_EXIST;
  1809. }
  1810. aipp_info = it->second;
  1811. return SUCCESS;
  1812. }
  1813. Status DavinciModel::InitAippType(uint32_t index, const OpDescPtr &op_desc, const map<uint32_t, OpDescPtr> &data_list) {
  1814. if (!op_desc->HasAttr(ATTR_DATA_RELATED_AIPP_MODE)) {
  1815. GELOGW("There is no aipp releated info with index %u", index);
  1816. return SUCCESS;
  1817. }
  1818. // Set default value
  1819. InputAippType aipp_type = DATA_WITHOUT_AIPP;
  1820. string data_mode;
  1821. (void)AttrUtils::GetStr(op_desc, ATTR_DATA_RELATED_AIPP_MODE, data_mode);
  1822. if (data_mode == "static_aipp") {
  1823. aipp_type = DATA_WITH_STATIC_AIPP;
  1824. } else if (data_mode == "dynamic_aipp") {
  1825. aipp_type = DATA_WITH_DYNAMIC_AIPP;
  1826. } else if (data_mode == "dynamic_aipp_conf") {
  1827. aipp_type = DYNAMIC_AIPP_NODE;
  1828. } else {
  1829. REPORT_INNER_ERROR("E19999", "Attr:%s data_mode:%s in op:%s(%s), model_id:%u, check invalid",
  1830. ATTR_DATA_RELATED_AIPP_MODE.c_str(), data_mode.c_str(),
  1831. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  1832. GELOGE(ACL_ERROR_GE_AIPP_MODE_INVALID, "[Get][Attr] %s data_mode:%s in op:%s(%s), model_id:%u, check invalid",
  1833. ATTR_DATA_RELATED_AIPP_MODE.c_str(), data_mode.c_str(),
  1834. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  1835. return ACL_ERROR_GE_AIPP_MODE_INVALID;
  1836. }
  1837. size_t aipp_index = 0xFFFFFFFF; // default invalid value
  1838. if (aipp_type == DATA_WITH_DYNAMIC_AIPP) {
  1839. string releated_name;
  1840. (void)AttrUtils::GetStr(op_desc, ATTR_DATA_AIPP_DATA_NAME_MAP, releated_name);
  1841. for (const auto item : data_list) {
  1842. if (item.second->GetName() == releated_name) {
  1843. GELOGI("Find aipp_data [%s] index %u from index %u", releated_name.c_str(), item.first, index);
  1844. aipp_index = item.first;
  1845. }
  1846. }
  1847. if (aipp_index == 0xFFFFFFFF) {
  1848. GELOGW("Can not find aipp data node from index %u", index);
  1849. return SUCCESS;
  1850. }
  1851. }
  1852. aipp_type_list_[index] = { aipp_type, aipp_index };
  1853. return SUCCESS;
  1854. }
  1855. Status DavinciModel::GetAippType(uint32_t index, InputAippType &aipp_type, size_t &aipp_index) const {
  1856. GE_CHK_BOOL_RET_STATUS(index < input_addrs_list_.size(), PARAM_INVALID,
  1857. "[Check][Param] Index %u is invalid", index);
  1858. const auto it = aipp_type_list_.find(index);
  1859. if (it == aipp_type_list_.end()) {
  1860. GELOGW("There is no aipp releated info with index %u", index);
  1861. aipp_type = DATA_WITHOUT_AIPP;
  1862. aipp_index = 0xFFFFFFFF;
  1863. return SUCCESS;
  1864. }
  1865. aipp_type = it->second.first;
  1866. aipp_index = it->second.second;
  1867. return SUCCESS;
  1868. }
  1869. void DavinciModel::SetDynamicSize(const std::vector<uint64_t> &batch_num, int32_t dynamic_type) {
  1870. batch_size_.clear();
  1871. if (batch_num.empty()) {
  1872. GELOGD("User has not set dynammic data");
  1873. }
  1874. for (size_t i = 0; i < batch_num.size(); i++) {
  1875. batch_size_.emplace_back(batch_num[i]);
  1876. }
  1877. dynamic_type_ = dynamic_type;
  1878. }
  1879. void DavinciModel::GetCurShape(std::vector<int64_t> &batch_info, int32_t &dynamic_type) const {
  1880. if (batch_size_.empty()) {
  1881. GELOGD("User does not set dynamic size");
  1882. }
  1883. for (size_t i = 0; i < batch_size_.size(); i++) {
  1884. GELOGI("Start to get current shape");
  1885. batch_info.emplace_back(batch_size_[i]);
  1886. }
  1887. dynamic_type = dynamic_type_;
  1888. }
  1889. Status DavinciModel::GetOpAttr(const std::string &op_name, const std::string &attr_name,
  1890. std::string &attr_value) const {
  1891. auto itr = op_name_to_attrs_.find(op_name);
  1892. if (itr == op_name_to_attrs_.end()) {
  1893. GELOGW("Did not save op:%s attr", op_name.c_str());
  1894. return SUCCESS;
  1895. }
  1896. auto attr_itr = itr->second.find(attr_name);
  1897. if (attr_itr == itr->second.end()) {
  1898. GELOGW("Did not save attr:%s of op:%s", attr_name.c_str(), op_name.c_str());
  1899. return SUCCESS;
  1900. }
  1901. for (const auto &name : attr_itr->second) {
  1902. attr_value += "[" + std::to_string(name.size()) + "]" + name;
  1903. }
  1904. GELOGD("Get attr:%s of op:%s success, attr value:%s", attr_name.c_str(), op_name.c_str(), attr_value.c_str());
  1905. return SUCCESS;
  1906. }
  1907. void DavinciModel::GetModelAttr(vector<string> &out_shape_info) const {
  1908. out_shape_info.insert(out_shape_info.end(), dynamic_output_shape_info_.begin(), dynamic_output_shape_info_.end());
  1909. }
  1910. void DavinciModel::SetInputDimsInfo(const vector<int64_t> &input_dims, Format &format, ShapeDescription &shape_info) {
  1911. uint32_t n, c, h, w;
  1912. n = format == FORMAT_NHWC ? NHWC_DIM_N : NCHW_DIM_N;
  1913. c = format == FORMAT_NHWC ? NHWC_DIM_C : NCHW_DIM_C;
  1914. h = format == FORMAT_NHWC ? NHWC_DIM_H : NCHW_DIM_H;
  1915. w = format == FORMAT_NHWC ? NHWC_DIM_W : NCHW_DIM_W;
  1916. if (input_dims.size() == static_cast<size_t>(NORMAL_TENSOR_SIZE)) {
  1917. shape_info.num = input_dims[n];
  1918. shape_info.height = input_dims[h];
  1919. shape_info.width = input_dims[w];
  1920. shape_info.channel = input_dims[c];
  1921. }
  1922. for (size_t k = 0; k < input_dims.size(); ++k) {
  1923. shape_info.dims.push_back(input_dims[k]);
  1924. }
  1925. }
  1926. void DavinciModel::CreateInputDimsInfo(const OpDescPtr &op_desc, Format format,
  1927. ShapeDescription &shape_info, ShapeDescription &dims_info) {
  1928. // judge if this data is linked dynamic aipp first, multiply batch has been considered
  1929. if (op_desc->HasAttr(ATTR_DYNAMIC_AIPP_INPUT_DIMS)) {
  1930. vector<int64_t> dynamic_aipp_input_dims;
  1931. (void)AttrUtils::GetListInt(op_desc, ATTR_DYNAMIC_AIPP_INPUT_DIMS, dynamic_aipp_input_dims);
  1932. SetInputDimsInfo(dynamic_aipp_input_dims, format, shape_info);
  1933. } else {
  1934. // judge if this data is multiply batch
  1935. if (!op_desc->HasAttr(ATTR_MBATCH_ORIGIN_INPUT_DIMS)) {
  1936. vector<int64_t> input_dims = op_desc->GetInputDescPtr(0)->GetShape().GetDims();
  1937. SetInputDimsInfo(input_dims, format, shape_info);
  1938. } else {
  1939. vector<int64_t> origin_input_dims;
  1940. (void)AttrUtils::GetListInt(op_desc, ATTR_MBATCH_ORIGIN_INPUT_DIMS, origin_input_dims);
  1941. SetInputDimsInfo(origin_input_dims, format, shape_info);
  1942. }
  1943. }
  1944. if (op_desc->HasAttr(ATTR_NAME_INPUT_DIMS)) {
  1945. // When static aipp is set, need to get the model input dims which processed by aipp
  1946. vector<int64_t> model_input_dims;
  1947. (void)AttrUtils::GetListInt(op_desc, ATTR_NAME_INPUT_DIMS, model_input_dims);
  1948. SetInputDimsInfo(model_input_dims, format, dims_info);
  1949. } else {
  1950. dims_info = shape_info;
  1951. }
  1952. }
  1953. Status DavinciModel::InitInputDescInfo(const OpDescPtr &op_desc) {
  1954. GE_CHECK_NOTNULL(op_desc->GetInputDescPtr(0));
  1955. InputOutputDescInfo input;
  1956. ShapeDescription dims_info;
  1957. Format format = op_desc->GetInputDescPtr(0)->GetFormat();
  1958. CreateInputDimsInfo(op_desc, format, input.shape_info, dims_info);
  1959. input.data_type = op_desc->GetInputDescPtr(0)->GetDataType();
  1960. input.name = op_desc->GetName();
  1961. int64_t input_size = 0;
  1962. GE_CHK_STATUS_RET(TensorUtils::GetSize(*op_desc->GetInputDescPtr(0), input_size),
  1963. "[Get][InputSize] failed in op:%s.", op_desc->GetName().c_str());
  1964. input.size = input_size;
  1965. input_formats_.push_back(format);
  1966. input_descs_.push_back(input);
  1967. input.shape_info = dims_info;
  1968. input_descs_dims_.push_back(input);
  1969. return SUCCESS;
  1970. }
  1971. Status DavinciModel::GetInputDescInfo(vector<InputOutputDescInfo> &input_descs,
  1972. vector<uint32_t> &input_formats, bool by_dims) const {
  1973. const vector<InputOutputDescInfo> &input_desc_info = by_dims ? input_descs_dims_ : input_descs_;
  1974. input_descs.insert(input_descs.end(), input_desc_info.begin(), input_desc_info.end());
  1975. input_formats.insert(input_formats.end(), input_formats_.begin(), input_formats_.end());
  1976. return SUCCESS;
  1977. }
  1978. void DavinciModel::CreateOutput(uint32_t index, const OpDescPtr &op_desc, InputOutputDescInfo &output,
  1979. uint32_t &format_result) {
  1980. /// netoutput input tensor desc
  1981. GE_IF_BOOL_EXEC(op_desc->GetInputDescPtr(index) == nullptr,
  1982. REPORT_INNER_ERROR("E19999", "input_desc index:%u in op:%s(%s) not exist, model_id:%u, "
  1983. "check invalid", index, op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  1984. model_id_);
  1985. GELOGE(FAILED, "[Get][InputDescPtr] input_desc index:%u in op:%s(%s) not exist, model_id:%u",
  1986. index, op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  1987. return);
  1988. Format format = op_desc->GetInputDescPtr(index)->GetFormat();
  1989. GeShape shape = op_desc->GetInputDescPtr(index)->GetShape();
  1990. DataType data_type = op_desc->GetInputDescPtr(index)->GetDataType();
  1991. int64_t dims[] = {1, 1, 1, 1};
  1992. format_result = format;
  1993. if (format == FORMAT_ND) { // for ND tensor
  1994. for (size_t i = 0; i < shape.GetDimNum() && i < (sizeof(dims) / sizeof(dims[0])); i++) {
  1995. dims[i] = shape.GetDim(i);
  1996. }
  1997. } else { // FOR FORMAT_NHWC or FORMAT_NCHW
  1998. dims[0] = shape.GetDim(format == FORMAT_NHWC ? NHWC_DIM_N : NCHW_DIM_N); // 0: first dim
  1999. dims[1] = shape.GetDim(format == FORMAT_NHWC ? NHWC_DIM_C : NCHW_DIM_C); // 1: second dim
  2000. dims[2] = shape.GetDim(format == FORMAT_NHWC ? NHWC_DIM_H : NCHW_DIM_H); // 2: third dim
  2001. dims[3] = shape.GetDim(format == FORMAT_NHWC ? NHWC_DIM_W : NCHW_DIM_W); // 3: forth dim
  2002. }
  2003. output.shape_info.num = dims[0]; // 0: first dim
  2004. output.shape_info.channel = dims[1]; // 1: second dim
  2005. output.shape_info.height = dims[2]; // 2: third dim
  2006. output.shape_info.width = dims[3]; // 3: forth dim
  2007. if (op_desc->GetInputDescPtr(index)->GetFormat() == FORMAT_FRACTAL_Z) { // FraczToHWCK
  2008. int64_t k = shape.GetDim(0); // 0: first dim
  2009. int64_t c = shape.GetDim(1); // 1: second dim
  2010. int64_t h = shape.GetDim(2); // 2: third dim
  2011. int64_t w = shape.GetDim(3); // 3: forth dim
  2012. output.shape_info.dims.push_back(h);
  2013. output.shape_info.dims.push_back(w);
  2014. output.shape_info.dims.push_back(c);
  2015. output.shape_info.dims.push_back(k);
  2016. format_result = FORMAT_HWCN;
  2017. } else {
  2018. for (size_t j = 0; j < shape.GetDimNum(); j++) {
  2019. output.shape_info.dims.push_back(shape.GetDim(j));
  2020. }
  2021. }
  2022. int64_t tensor_size = 0;
  2023. if (AttrUtils::GetInt(op_desc->GetInputDescPtr(index), ATTR_NAME_SPECIAL_OUTPUT_SIZE, tensor_size)
  2024. && (tensor_size > 0)) {
  2025. GELOGI("netoutput[%s] [%d]th input has special size [%ld]", op_desc->GetName().c_str(), index, tensor_size);
  2026. } else {
  2027. (void)TensorUtils::CalcTensorMemSize(shape, format, data_type, tensor_size); // no need to check value
  2028. }
  2029. output.size = static_cast<uint64_t>(tensor_size);
  2030. output.data_type = op_desc->GetInputDescPtr(index)->GetDataType();
  2031. }
  2032. Status DavinciModel::InitOutputDescInfo(const OpDescPtr &op_desc, const vector<string> &out_node_name) {
  2033. uint32_t out_size = static_cast<uint32_t>(op_desc->GetInputsSize());
  2034. for (uint32_t i = 0; i < out_size; ++i) {
  2035. string output_name;
  2036. InputOutputDescInfo output;
  2037. uint32_t format_result;
  2038. CreateOutput(i, op_desc, output, format_result);
  2039. std::vector<std::string> src_name = op_desc->GetSrcName();
  2040. std::vector<int64_t> src_index = op_desc->GetSrcIndex();
  2041. GE_CHK_BOOL_RET_STATUS(src_name.size() > i && src_index.size() > i, INTERNAL_ERROR,
  2042. "[Check][Param] construct output failed, as index:%u >= src name size:%zu, "
  2043. "or index >= src index size:%zu, op:%s.",
  2044. i, src_name.size(), src_index.size(), op_desc->GetName().c_str());
  2045. // forward compatbility, if old om has no out_node_name, need to return output follow origin way
  2046. if (out_size == out_node_name.size()) {
  2047. // neweast plan, the index will add to name during generate model.
  2048. bool contains_colon = out_node_name[i].find(":") != std::string::npos;
  2049. output_name = contains_colon ? out_node_name[i] : out_node_name[i] + ":" + std::to_string(src_index[i]);
  2050. } else {
  2051. output_name = string("output_") + std::to_string(i) + "_" + src_name[i] + "_" + std::to_string(src_index[i]);
  2052. }
  2053. output.name = output_name;
  2054. output_descs_.push_back(output);
  2055. output_formats_.push_back(format_result);
  2056. }
  2057. return SUCCESS;
  2058. }
  2059. Status DavinciModel::GetOutputDescInfo(vector<InputOutputDescInfo> &output_descs,
  2060. vector<uint32_t> &output_formats) const {
  2061. output_descs.insert(output_descs.end(), output_descs_.begin(), output_descs_.end());
  2062. output_formats.insert(output_formats.end(), output_formats_.begin(), output_formats_.end());
  2063. return SUCCESS;
  2064. }
  2065. Status DavinciModel::CopyInputData(const InputData &input_data) {
  2066. const std::vector<DataBuffer> &blobs = input_data.blobs;
  2067. for (const auto &data : input_data_info_) {
  2068. if (data.first >= blobs.size()) {
  2069. REPORT_INNER_ERROR("E19999", "index:%u in input_data_info_ >= input_data.blobs.size:%zu, model_id:%u, "
  2070. "check invalid", data.first, blobs.size(), model_id_);
  2071. GELOGE(FAILED, "[Check][Param] Blobs not match: blobs=%zu, tensor=%zu, index=%u, size=%ld, op_name(%s)",
  2072. blobs.size(), input_data_info_.size(), data.first, data.second.GetDataInfo().at(0).first,
  2073. data.second.GetOpName().c_str());
  2074. return FAILED;
  2075. }
  2076. const DataBuffer &data_buf = blobs[data.first];
  2077. rtMemcpyKind_t kind =
  2078. data_buf.placement == kPlacementHostData ? RT_MEMCPY_HOST_TO_DEVICE : RT_MEMCPY_DEVICE_TO_DEVICE;
  2079. if (data_buf.length == 0) {
  2080. GELOGW("No data need to memcpy!");
  2081. return SUCCESS;
  2082. }
  2083. uint64_t data_size = data.second.GetDataSize();
  2084. GE_CHK_BOOL_RET_STATUS(data_size >= data_buf.length, PARAM_INVALID,
  2085. "[Check][Param] input data size(%lu) does not match model required size(%lu), "
  2086. "op_name(%s), ret failed.", data_buf.length, data_size, data.second.GetOpName().c_str());
  2087. void *mem_addr = data.second.GetBasicAddr();
  2088. void *data_buf_addr = reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(data_buf.data));
  2089. uint64_t data_buf_length = data_buf.length;
  2090. GELOGI("CopyPlainData memcpy graph_%u type[F] input[%s] rank[%u] dst[%p] src[%p] mem_size[%lu] datasize[%lu]",
  2091. runtime_param_.graph_id, data.second.GetOpName().c_str(), data.first, mem_addr, data_buf_addr, data_size,
  2092. data_buf_length);
  2093. GE_CHK_RT_RET(rtMemcpy(mem_addr, data_size, data_buf_addr, data_buf_length, kind));
  2094. }
  2095. return SUCCESS;
  2096. }
  2097. Status DavinciModel::SyncVarData() {
  2098. GELOGI("Sync var data, model id:%u", model_id_);
  2099. if (global_step_addr_ != nullptr && global_step_size_ != 0) {
  2100. const vector<uint64_t> v_step = { iterator_count_ };
  2101. GE_CHK_RT_RET(rtMemcpy(global_step_addr_, global_step_size_, v_step.data(), v_step.size() * sizeof(uint64_t),
  2102. RT_MEMCPY_HOST_TO_DEVICE));
  2103. }
  2104. return SUCCESS;
  2105. }
  2106. Status DavinciModel::InitModelProfile() {
  2107. for (const auto &task : task_list_) {
  2108. GE_CHECK_NOTNULL(task);
  2109. const FusionOpInfo *fusion_op_info = task->GetFusionOpInfo();
  2110. // when type is RT_MODEL_TASK_KERNEL, ctx is not null
  2111. if ((fusion_op_info == nullptr) || fusion_op_info->original_op_names.empty()) {
  2112. continue;
  2113. }
  2114. GELOGI("task.id = %u, opNum = %zu", task->GetTaskID(), fusion_op_info->original_op_names.size());
  2115. op_id_map_.insert(std::make_pair(fusion_op_info->op_index, task->GetTaskID()));
  2116. }
  2117. std::set<uint32_t> task_id_set;
  2118. using CIT = std::multimap<uint32_t, uint32_t>::const_iterator;
  2119. using Range = std::pair<CIT, CIT>;
  2120. for (const auto &task : task_list_) {
  2121. GE_CHECK_NOTNULL(task);
  2122. const FusionOpInfo *fusion_op_info = task->GetFusionOpInfo();
  2123. if ((fusion_op_info == nullptr) || fusion_op_info->original_op_names.empty()) {
  2124. continue;
  2125. }
  2126. if (task_id_set.count(task->GetTaskID()) > 0) {
  2127. continue;
  2128. }
  2129. const auto &op_desc = GetOpByIndex(fusion_op_info->op_index);
  2130. GE_CHK_BOOL_EXEC(op_desc != nullptr,
  2131. REPORT_INNER_ERROR("E19999", "Get op by index failed, as index:%u out of range",
  2132. fusion_op_info->op_index);
  2133. return FAILED,
  2134. "[Get][Op] failed, as index:%u out of range", fusion_op_info->op_index);
  2135. ProfileInfo profile;
  2136. profile.fusion_info = *fusion_op_info;
  2137. Range range = op_id_map_.equal_range(fusion_op_info->op_index);
  2138. for (CIT range_idx = range.first; range_idx != range.second; ++range_idx) {
  2139. profile.task_count++;
  2140. task_id_set.insert(range_idx->second);
  2141. }
  2142. // memory info
  2143. TaskMemInfo &mem_info = profile.memory_info;
  2144. const auto input_size = ModelUtils::GetInputSize(op_desc);
  2145. const auto output_size = ModelUtils::GetOutputSize(op_desc);
  2146. const auto workspace_size = ModelUtils::GetWorkspaceSize(op_desc);
  2147. const auto weight_size = ModelUtils::GetWeightSize(op_desc);
  2148. mem_info.input_size = std::accumulate(input_size.begin(), input_size.end(), 0);
  2149. mem_info.output_size = std::accumulate(output_size.begin(), output_size.end(), 0);
  2150. mem_info.workspace_size = std::accumulate(workspace_size.begin(), workspace_size.end(), 0);
  2151. mem_info.weight_size = std::accumulate(weight_size.begin(), weight_size.end(), 0);
  2152. mem_info.total_size = mem_info.weight_size + mem_info.input_size + mem_info.output_size + mem_info.workspace_size;
  2153. profile_list_.emplace_back(profile);
  2154. }
  2155. GELOGI("fusion task size: %zu, profile info size: %zu", op_id_map_.size(), profile_list_.size());
  2156. return SUCCESS;
  2157. }
  2158. Status DavinciModel::SinkModelProfile() {
  2159. auto &prof_mgr = ProfilingManager::Instance();
  2160. // Model Header
  2161. std::string name = om_name_.empty() ? name_ : om_name_;
  2162. uint32_t model_id = this->Id();
  2163. int64_t start_time = this->GetLoadBeginTime();
  2164. int64_t end_time = this->GetLoadEndTime();
  2165. Json model_load_info;
  2166. model_load_info[kModelName] = name;
  2167. model_load_info[kModeleId] = model_id;
  2168. model_load_info[kLoadStartTime] = start_time;
  2169. model_load_info[kLoadEndTime] = end_time;
  2170. // fusion op info
  2171. using CIT = std::multimap<uint32_t, uint32_t>::const_iterator;
  2172. using Range = std::pair<CIT, CIT>;
  2173. for (const ProfileInfo &profile : profile_list_) {
  2174. Json fusion_op_info;
  2175. string fusion_op_name = profile.fusion_info.op_name;
  2176. uint32_t op_num = profile.fusion_info.original_op_names.size();
  2177. vector<string> original_name;
  2178. for (uint32_t k = 0; k < op_num; k++) {
  2179. original_name.emplace_back(profile.fusion_info.original_op_names[k]);
  2180. }
  2181. uint32_t stream_id = 0;
  2182. auto iter = profiler_report_op_info_.find(fusion_op_name);
  2183. if (iter != profiler_report_op_info_.end()) {
  2184. stream_id = iter->second.second;
  2185. }
  2186. fusion_op_info[kFusionOpName] = fusion_op_name;
  2187. fusion_op_info[kOriginalOpNum] = op_num;
  2188. fusion_op_info[kOriginalOpName] = original_name;
  2189. fusion_op_info[kStreamId] = stream_id;
  2190. fusion_op_info[kFusionOpMemoryInfo][kInputSize] = profile.memory_info.input_size;
  2191. fusion_op_info[kFusionOpMemoryInfo][kOutputSize] = profile.memory_info.output_size;
  2192. fusion_op_info[kFusionOpMemoryInfo][kWeightSize] = profile.memory_info.weight_size;
  2193. fusion_op_info[kFusionOpMemoryInfo][kWorkSpaceSize] = profile.memory_info.workspace_size;
  2194. fusion_op_info[kFusionOpMemoryInfo][kTotalSize] = profile.memory_info.total_size;
  2195. fusion_op_info[kTaskCount] = profile.task_count;
  2196. vector<uint32_t> task_id;
  2197. Range task_range = op_id_map_.equal_range(profile.fusion_info.op_index);
  2198. for (CIT idx = task_range.first; idx != task_range.second; ++idx) {
  2199. task_id.push_back(idx->second);
  2200. }
  2201. fusion_op_info[kTaskId] = task_id;
  2202. model_load_info[kFusionOpInfo] += fusion_op_info;
  2203. }
  2204. std::string tag_name("model_load_info_" + std::to_string(this->Id()));
  2205. std::string reported_data;
  2206. try {
  2207. reported_data = model_load_info.dump(kInteval, ' ', false, Json::error_handler_t::ignore);
  2208. } catch (std::exception &e) {
  2209. REPORT_INNER_ERROR("E19999", "Convert model_load_info JSON to string failed, model_id:%u, reason:%s",
  2210. model_id_, e.what());
  2211. GELOGE(FAILED, "[Convert][JSON] to string failed, model_id:%u, reason:%s.", model_id_, e.what());
  2212. } catch (...) {
  2213. REPORT_INNER_ERROR("E19999", "Convert model_load_info JSON to string failed, model_id:%u", model_id_);
  2214. GELOGE(FAILED, "[Convert][JSON] to string failed, model_id:%u.", model_id_);
  2215. }
  2216. reported_data.append(",")
  2217. .append("\n");
  2218. prof_mgr.ReportData(device_id_, reported_data, tag_name);
  2219. return SUCCESS;
  2220. }
  2221. Status DavinciModel::SinkTimeProfile(const InputData &current_data) {
  2222. auto &prof_mgr = ProfilingManager::Instance();
  2223. string name = om_name_.empty() ? name_ : om_name_;
  2224. Json model_time_info;
  2225. model_time_info[kModelName] = name;
  2226. model_time_info[kModeleId] = this->Id();
  2227. model_time_info[kRequestId] = current_data.request_id;
  2228. model_time_info[kThreadId] = mmGetTid();
  2229. model_time_info[kInputBeginTime] = time_info_.processBeginTime;
  2230. model_time_info[kInputEndTime] = time_info_.processEndTime;
  2231. model_time_info[kInferBeginTime] = time_info_.inferenceBeginTime;
  2232. model_time_info[kInferEndTime] = time_info_.inferenceEndTime;
  2233. model_time_info[kOutputBeginTime] = time_info_.dumpBeginTime;
  2234. model_time_info[kOutputEndTime] = time_info_.dumpEndTime;
  2235. // report model data tag name
  2236. std::string tag_name;
  2237. tag_name.append("model_time_info_")
  2238. .append(std::to_string(this->Id()))
  2239. .append("_")
  2240. .append(std::to_string(current_data.index));
  2241. std::string reported_data;
  2242. try {
  2243. reported_data = model_time_info.dump(kInteval, ' ', false, Json::error_handler_t::ignore);
  2244. } catch (std::exception &e) {
  2245. REPORT_INNER_ERROR("E19999", "Convert model_time_info JSON to string failed, model_id:%u, reason:%s",
  2246. model_id_, e.what());
  2247. GELOGE(FAILED, "[Convert][JSON] to string failed, model_id:%u, reason:%s.", model_id_, e.what());
  2248. } catch (...) {
  2249. REPORT_INNER_ERROR("E19999", "Convert model_time_info JSON to string failed, model_id:%u", model_id_);
  2250. GELOGE(FAILED, "[Convert][JSON] to string failed, model_id:%u.", model_id_);
  2251. }
  2252. reported_data.append(",")
  2253. .append("\n");
  2254. prof_mgr.ReportData(device_id_, reported_data, tag_name);
  2255. return SUCCESS;
  2256. }
  2257. void DavinciModel::SetProfileTime(ModelProcStage stage, int64_t endTime) {
  2258. int64_t time = endTime;
  2259. if (time == 0) {
  2260. mmTimespec timespec = mmGetTickCount();
  2261. time = timespec.tv_sec * 1000 * 1000 * 1000 + timespec.tv_nsec; // 1000 ^ 3 converts second to nanosecond
  2262. }
  2263. switch (stage) {
  2264. case MODEL_LOAD_START:
  2265. load_begin_time_ = time;
  2266. break;
  2267. case MODEL_LOAD_END:
  2268. load_end_time_ = time;
  2269. break;
  2270. case MODEL_PRE_PROC_START:
  2271. time_info_.processBeginTime = time;
  2272. break;
  2273. case MODEL_PRE_PROC_END:
  2274. time_info_.processEndTime = time;
  2275. break;
  2276. case MODEL_INFER_START:
  2277. time_info_.inferenceBeginTime = time;
  2278. break;
  2279. case MODEL_INFER_END:
  2280. time_info_.inferenceEndTime = time;
  2281. break;
  2282. case MODEL_AFTER_PROC_START:
  2283. time_info_.dumpBeginTime = time;
  2284. break;
  2285. case MODEL_AFTER_PROC_END:
  2286. time_info_.dumpEndTime = time;
  2287. break;
  2288. default:
  2289. break;
  2290. }
  2291. return;
  2292. }
  2293. ///
  2294. /// @ingroup ge
  2295. /// @brief send Output Op result to upper layer
  2296. /// @already malloced in ModelLoad, no need to malloc again
  2297. /// @param [in] data_id: the index of output_data
  2298. /// @param [in/out] output_data: real user output_data
  2299. /// @param [in] kind: the kind of rtMemcpy
  2300. /// @return Status result
  2301. /// @author
  2302. ///
  2303. Status DavinciModel::CopyOutputData(uint32_t data_id, OutputData &output_data, rtMemcpyKind_t kind) {
  2304. if (!has_output_node_) {
  2305. return SyncVarData();
  2306. }
  2307. output_data.index = data_id;
  2308. output_data.model_id = model_id_;
  2309. if (output_data.blobs.size() != output_data_info_.size()) {
  2310. REPORT_INNER_ERROR("E19999", "output_data.blobs.size:%zu != output_data_info.size:%zu, model_id:%u, "
  2311. "check invalid", output_data.blobs.size(), output_data_info_.size(), model_id_);
  2312. GELOGE(FAILED, "[Check][Param] output_data.blobs.size:%zu != output_data_info.size:%zu, model_id:%u",
  2313. output_data.blobs.size(), output_data_info_.size(), model_id_);
  2314. return FAILED;
  2315. }
  2316. std::vector<DataBuffer> &blobs = output_data.blobs;
  2317. size_t idx = 0;
  2318. for (const auto &output : output_data_info_) {
  2319. if (output.first >= blobs.size()) {
  2320. REPORT_INNER_ERROR("E19999", "index:%u in output_data_info_ >= output_data.blobs.size:%zu, model_id:%u, "
  2321. "check invalid", output.first, blobs.size(), model_id_);
  2322. GELOGE(FAILED, "[Check][Param] index:%u in output_data_info_ >= output_data.blobs.size:%zu, model_id:%u",
  2323. output.first, blobs.size(), model_id_);
  2324. return FAILED;
  2325. }
  2326. if ((kind == RT_MEMCPY_DEVICE_TO_DEVICE) && (copy_only_addrs_.count(output.second.GetBasicAddr()) == 0)) {
  2327. continue; // Skip: Feed by zero copy.
  2328. }
  2329. DataBuffer &buffer = blobs[output.first];
  2330. uint64_t mem_size = static_cast<uint64_t>(output.second.GetDataSize());
  2331. if ((buffer.length == 0) || (mem_size == 0)) {
  2332. GELOGI("Length of data is zero, No need copy. output tensor index=%u", output.first);
  2333. continue;
  2334. }
  2335. if (is_dynamic_) {
  2336. GELOGI("No need to check output data size.");
  2337. } else if (buffer.length < mem_size) {
  2338. REPORT_INNER_ERROR("E19999", "Buffer.length:%lu in output blob < mem_size:%lu in output_data_info, index:%u, "
  2339. "model_id:%u, check invalid", buffer.length, mem_size, output.first, model_id_);
  2340. GELOGE(FAILED, "[Check][Param] Buffer.length:%lu in output blob < mem_size:%lu in output_data_info, index:%u, "
  2341. "model_id:%u", buffer.length, mem_size, output.first, model_id_);
  2342. return FAILED;
  2343. } else if (buffer.length > mem_size) {
  2344. GELOGW("Tensor data size=%lu, buffer size=%lu", mem_size, buffer.length);
  2345. }
  2346. int64_t data_size = output.second.GetDataSize();
  2347. if (is_online_infer_dynamic_) {
  2348. if (merge_nodes_gear_and_real_out_size_info_.find(idx) != merge_nodes_gear_and_real_out_size_info_.end()) {
  2349. auto gear_and_real_out_size_info = merge_nodes_gear_and_real_out_size_info_[idx];
  2350. data_size = gear_and_real_out_size_info[cur_dynamic_dims_];
  2351. }
  2352. }
  2353. uint64_t buffer_length = buffer.length;
  2354. void *buffer_addr = reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(buffer.data));
  2355. GELOGI("CopyPlainData memcpy graph_%u type[F] output[%u] memaddr[%p] mem_size[%lu] datasize[%lu]",
  2356. runtime_param_.graph_id, output.first, output.second.GetBasicAddr(), data_size, buffer_length);
  2357. GE_CHK_RT_RET(rtMemcpy(buffer_addr, buffer_length, output.second.GetBasicAddr(), data_size, kind));
  2358. idx++;
  2359. }
  2360. return SUCCESS;
  2361. }
  2362. Status DavinciModel::InitOutputTensorInfo(const OpDescPtr &op_desc) {
  2363. size_t input_num = op_desc->GetInputsSize();
  2364. if (is_getnext_sink_dynamic_) {
  2365. input_num = input_num - kGetDynamicDimsCount;
  2366. }
  2367. for (size_t i = 0; i < input_num; ++i) {
  2368. int64_t size = 0;
  2369. auto input_desc = op_desc->GetInputDescPtr(i);
  2370. GE_CHECK_NOTNULL(input_desc);
  2371. auto ret = TensorUtils::GetTensorSizeInBytes(*input_desc, size);
  2372. GE_IF_BOOL_EXEC(ret != GRAPH_SUCCESS,
  2373. REPORT_INNER_ERROR("E19999", "Get input TensorSize in op:%s(%s) failed, input_index:%zu, "
  2374. "model_id:%u", op_desc->GetName().c_str(), op_desc->GetType().c_str(), i,
  2375. model_id_);
  2376. GELOGE(ret, "[Get][InputTensorSize] in op:%s(%s) failed, input_index:%zu, model_id:%u",
  2377. op_desc->GetName().c_str(), op_desc->GetType().c_str(), i, model_id_);
  2378. return ret);
  2379. const GeShape &shape = input_desc->GetShape();
  2380. GELOGI("Output size is %ld, output shape is %s.", size, formats::JoinToString(shape.GetDims()).c_str());
  2381. output_buffer_size_.emplace_back(size);
  2382. output_shape_info_.emplace_back(shape);
  2383. }
  2384. return SUCCESS;
  2385. }
  2386. Status DavinciModel::GenOutputTensorInfo(OutputData *output_data, vector<ge::Tensor> &outputs) {
  2387. GE_CHECK_NOTNULL(output_data);
  2388. if (!output_data->blobs.empty()) {
  2389. GELOGI("No need to generate output tensor info, model id:%u", model_id_);
  2390. return SUCCESS;
  2391. }
  2392. vector<int64_t> output_buffer_size;
  2393. vector<vector<int64_t>> output_shape_info;
  2394. size_t output_num = output_buffer_size_.size();
  2395. for (size_t i = 0; i < output_num; ++i) {
  2396. int64_t output_size = output_buffer_size_[i];
  2397. vector<int64_t> output_shape = output_shape_info_[i].GetDims();
  2398. if (is_online_infer_dynamic_) {
  2399. if (merge_nodes_gear_and_real_out_size_info_.find(i) != merge_nodes_gear_and_real_out_size_info_.end()) {
  2400. auto gear_and_real_out_size_info = merge_nodes_gear_and_real_out_size_info_[i];
  2401. output_size = gear_and_real_out_size_info[cur_dynamic_dims_];
  2402. auto gear_and_real_out_shape_info = merge_nodes_gear_and_real_out_shape_info_[i];
  2403. output_shape = gear_and_real_out_shape_info[cur_dynamic_dims_];
  2404. is_dynamic_ = true;
  2405. }
  2406. }
  2407. GELOGI("Output size is %ld, output shape is %s.", output_size, formats::JoinToString(output_shape).c_str());
  2408. output_buffer_size.push_back(output_size);
  2409. output_shape_info.push_back(output_shape);
  2410. }
  2411. GELOGI("Output blobs size:%zu, model id:%u", output_buffer_size_.size(), model_id_);
  2412. for (size_t i = 0; i < output_buffer_size.size(); ++i) {
  2413. auto aligned_ptr = MakeShared<AlignedPtr>(output_buffer_size[i], kAlignment);
  2414. GE_CHECK_NOTNULL(aligned_ptr);
  2415. GeShape ge_shape(output_shape_info[i]);
  2416. GeTensorDesc tensor_desc;
  2417. tensor_desc.SetShape(ge_shape);
  2418. GeTensor ge_tensor(tensor_desc);
  2419. ge_tensor.SetData(aligned_ptr, output_buffer_size[i]);
  2420. ge::Tensor output_tensor = TensorAdapter::AsTensor(ge_tensor);
  2421. auto data_ptr = aligned_ptr->MutableGet();
  2422. output_data->blobs.push_back(
  2423. {reinterpret_cast<void *>(data_ptr), static_cast<uint64_t>(output_buffer_size[i]), false});
  2424. outputs.emplace_back(std::move(output_tensor));
  2425. GELOGD("Output index:%zu, output dims is %s, data length:%lu.", i,
  2426. formats::JoinToString(output_shape_info[i]).c_str(), output_buffer_size[i]);
  2427. }
  2428. return SUCCESS;
  2429. }
  2430. ///
  2431. /// @ingroup ge
  2432. /// @brief send Output Op result to upper layer
  2433. /// @already malloced in ModelLoad, no need to malloc again
  2434. /// @param [in] data_id: the index of output_data
  2435. /// @param [in] rslt_flg: result flag
  2436. /// @param [in] seq_end_flag: sequence end flag
  2437. /// @param [out] output_data: real user output_data
  2438. /// @return Status result
  2439. /// @author
  2440. ///
  2441. Status DavinciModel::ReturnResult(uint32_t data_id, const bool rslt_flg, const bool seq_end_flag,
  2442. OutputData *output_data) {
  2443. GE_CHK_BOOL_EXEC(listener_ != nullptr,
  2444. REPORT_INNER_ERROR("E19999", "listener_ is nullptr, check invalid.");
  2445. return PARAM_INVALID, "[Check][Param] listener_ is null.");
  2446. std::vector<ge::Tensor> outputs;
  2447. // return result is not required
  2448. if (!rslt_flg && !seq_end_flag) {
  2449. GELOGW("Compute failed, model id: %u", model_id_);
  2450. auto model_manager = ModelManager::GetInstance();
  2451. GE_CHECK_NOTNULL(model_manager);
  2452. auto exception_infos = model_manager->GetExceptionInfos();
  2453. if (exception_infos.size() > 0) {
  2454. GE_CHK_STATUS_RET(DumpExceptionInfo(exception_infos),
  2455. "[Dump][Exception] Dump exception info failed, model_id:%u.", model_id_);
  2456. } else {
  2457. GELOGI("[Dump][Exception] Exception info is null.");
  2458. }
  2459. GE_CHK_STATUS(listener_->OnComputeDone(model_id_, data_id, INTERNAL_ERROR, outputs),
  2460. "[Call][OnComputeDone] failed, model_id:%u, data_id:%u.", model_id_, data_id);
  2461. return INTERNAL_ERROR;
  2462. }
  2463. if (!has_output_node_) {
  2464. GELOGW("Output tensor list is empty, model id: %u", model_id_);
  2465. GE_CHK_STATUS(listener_->OnComputeDone(model_id_, data_id, INTERNAL_ERROR, outputs),
  2466. "[Call][OnComputeDone] failed, model_id:%u, data_id:%u.", model_id_, data_id);
  2467. return INTERNAL_ERROR;
  2468. }
  2469. GE_CHECK_NOTNULL(output_data);
  2470. output_data->index = data_id;
  2471. output_data->model_id = model_id_;
  2472. if (is_getnext_sink_dynamic_) {
  2473. GELOGD("Reinit cur dynamic dims when getnext sink dynamic.");
  2474. cur_dynamic_dims_.clear();
  2475. cur_dynamic_dims_.resize(shape_of_cur_dynamic_dims_);
  2476. auto ret = rtMemcpy(cur_dynamic_dims_.data(), shape_of_cur_dynamic_dims_ * sizeof(int32_t),
  2477. netoutput_last_input_addr_, netoutput_last_input_size_, RT_MEMCPY_DEVICE_TO_HOST);
  2478. GE_CHK_RT_RET(ret);
  2479. }
  2480. GELOGD("Cur dynamic dims is %s.", formats::JoinToString(cur_dynamic_dims_).c_str());
  2481. if (GenOutputTensorInfo(output_data, outputs) != SUCCESS) {
  2482. return INTERNAL_ERROR;
  2483. }
  2484. if (CopyOutputData(data_id, *output_data, RT_MEMCPY_DEVICE_TO_HOST) != SUCCESS) {
  2485. GE_CHK_STATUS(listener_->OnComputeDone(model_id_, data_id, INTERNAL_ERROR, outputs),
  2486. "[Call][OnComputeDone] failed, model_id:%u, data_id:%u.", model_id_, data_id);
  2487. return INTERNAL_ERROR;
  2488. }
  2489. if (seq_end_flag) {
  2490. GELOGW("End of sequence, model id: %u", model_id_);
  2491. GE_CHK_STATUS(listener_->OnComputeDone(model_id_, data_id, END_OF_SEQUENCE, outputs),
  2492. "[Call][OnComputeDone] failed, model_id:%u, data_id:%u.", model_id_, data_id);
  2493. return END_OF_SEQUENCE;
  2494. }
  2495. GE_CHK_STATUS(listener_->OnComputeDone(model_id_, data_id, SUCCESS, outputs),
  2496. "[Call][OnComputeDone] failed, model_id:%u, data_id:%u.", model_id_, data_id);
  2497. return SUCCESS;
  2498. }
  2499. ///
  2500. /// @ingroup ge
  2501. /// @brief return not output to upper layer for cloud case
  2502. /// @param [in] data_id
  2503. /// @return Status result
  2504. ///
  2505. Status DavinciModel::ReturnNoOutput(uint32_t data_id) {
  2506. GELOGI("ReturnNoOutput model id:%u.", model_id_);
  2507. GE_CHK_BOOL_EXEC(listener_ != nullptr,
  2508. REPORT_INNER_ERROR("E19999", "listener_ is nullptr, check invalid.");
  2509. return PARAM_INVALID, "[Check][Param] listener_ is null!");
  2510. std::vector<ge::Tensor> outputs;
  2511. GE_CHK_STATUS(listener_->OnComputeDone(model_id_, data_id, SUCCESS, outputs),
  2512. "[Call][OnComputeDone] failed, model_id:%u, data_id:%u.", model_id_, data_id);
  2513. return SUCCESS;
  2514. }
  2515. void *DavinciModel::Run(DavinciModel *model) {
  2516. GE_CHK_BOOL_EXEC(model != nullptr,
  2517. return nullptr, "[Check][Param] model_pointer is null!")
  2518. bool seq_end_flag = false;
  2519. uint32_t model_id = model->Id();
  2520. uint32_t device_id = model->GetDeviceId();
  2521. ErrorManager::GetInstance().SetErrorContext(model->GetErrorContext());
  2522. GELOGI("Model Run thread start, model_id:%u.", model_id);
  2523. rtError_t rt_ret = rtSetDevice(static_cast<int32_t>(device_id));
  2524. if (rt_ret != RT_ERROR_NONE) {
  2525. GELOGE(FAILED, "[Run][Rtsetdevice] failed, model_id:%u, device_id:%u.", model_id, device_id);
  2526. return nullptr;
  2527. }
  2528. // DeviceReset before thread run finished!
  2529. GE_MAKE_GUARD(not_used_var, [&] { GE_CHK_RT(rtDeviceReset(device_id)); });
  2530. ErrorManager::GetInstance().SetStage(error_message::kModelExecute, error_message::kModelExecute);
  2531. while (model->RunFlag()) {
  2532. // Model hasn't truly started runing before received data
  2533. model->SetRunningFlag(false);
  2534. bool rslt_flg = true;
  2535. if (model->GetDataInputer() == nullptr) {
  2536. GELOGW("Data inputer is nullptr.");
  2537. break;
  2538. }
  2539. std::shared_ptr<InputDataWrapper> data_wrapper;
  2540. Status ret = model->GetDataInputer()->Pop(data_wrapper);
  2541. // Model run indeedly start after received data.
  2542. model->SetRunningFlag(true);
  2543. if (data_wrapper == nullptr || ret != SUCCESS) {
  2544. GELOGI("data_wrapper is null!");
  2545. continue;
  2546. }
  2547. GELOGI("Getting the input data, model_id:%u", model_id);
  2548. GE_IF_BOOL_EXEC(!model->RunFlag(), break);
  2549. InputData current_data = data_wrapper->GetInput();
  2550. GELOGI("Model thread Run begin, model id:%u, data index:%u.", model_id, current_data.index);
  2551. GE_TIMESTAMP_START(Model_SyncVarData);
  2552. ret = model->SyncVarData();
  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][SyncVarData] Copy input data to model failed, model_id:%u.", model_id); // [No need to check value]
  2557. GE_IF_BOOL_EXEC(model->is_first_execute_, GE_TIMESTAMP_EVENT_END(Model_SyncVarData, "Model Run SyncVarData"));
  2558. GELOGI("Copy input data, model id:%u", model_id);
  2559. GE_IF_BOOL_EXEC(ProfilingManager::Instance().ProfilingModelExecuteOn(),
  2560. model->SetProfileTime(MODEL_PRE_PROC_START));
  2561. ret = model->CopyInputData(current_data);
  2562. GE_CHK_BOOL_TRUE_EXEC_WITH_LOG(
  2563. ret != SUCCESS, (void)model->ReturnResult(current_data.index, false, false, data_wrapper->GetOutput());
  2564. continue,
  2565. "[Call][CopyInputData] Copy input data to model failed, model_id:%u.", model_id); // [No need to check value]
  2566. if (model->is_online_infer_dynamic_ && !model->is_getnext_sink_dynamic_) {
  2567. model->cur_dynamic_dims_.clear();
  2568. GE_IF_BOOL_EXEC(current_data.blobs.empty(), break);
  2569. auto shape_data_buffer_data = current_data.blobs.back().data;
  2570. auto shape_data_buffer_length = current_data.blobs.back().length;
  2571. model->cur_dynamic_dims_.assign(reinterpret_cast<int32_t *>(shape_data_buffer_data),
  2572. reinterpret_cast<int32_t *>(shape_data_buffer_data) +
  2573. shape_data_buffer_length / sizeof(int32_t));
  2574. GELOGD("Data: cur dynamic dims is %s", formats::JoinToString(model->cur_dynamic_dims_).c_str());
  2575. delete[] reinterpret_cast<int32_t *>(current_data.blobs.back().data);
  2576. current_data.blobs.pop_back();
  2577. }
  2578. GE_IF_BOOL_EXEC(ProfilingManager::Instance().ProfilingModelExecuteOn(), model->SetProfileTime(MODEL_PRE_PROC_END));
  2579. GE_IF_BOOL_EXEC(ProfilingManager::Instance().ProfilingModelExecuteOn(), model->SetProfileTime(MODEL_INFER_START));
  2580. GE_TIMESTAMP_START(rtModelExecute);
  2581. GELOGI("rtModelExecute start.");
  2582. rt_ret = rtModelExecute(model->rt_model_handle_, model->rt_model_stream_, 0);
  2583. GE_IF_BOOL_EXEC(rt_ret != RT_ERROR_NONE, rslt_flg = false;
  2584. (void)model->ReturnResult(current_data.index, false, false, data_wrapper->GetOutput());
  2585. continue);
  2586. GELOGI("rtModelExecute end");
  2587. GE_IF_BOOL_EXEC(model->is_first_execute_, GE_TIMESTAMP_EVENT_END(rtModelExecute, "GraphExcute::rtModelExecute"));
  2588. GE_TIMESTAMP_START(rtStreamSynchronize);
  2589. GELOGI("rtStreamSynchronize start.");
  2590. rt_ret = rtStreamSynchronize(model->rt_model_stream_);
  2591. if (rt_ret == kEndOfSequence || rt_ret == kEndOfSequenceNew) {
  2592. seq_end_flag = true;
  2593. }
  2594. if (rt_ret == kModelAbortNormal || rt_ret == kModelAbortNormalNew) {
  2595. GELOGI("The model with multiple datasets aborts normally.");
  2596. } else {
  2597. GE_IF_BOOL_EXEC(
  2598. rt_ret != RT_ERROR_NONE, rslt_flg = false; GELOGI("seq_end_flg: %d", seq_end_flag);
  2599. (void)model->ReturnResult(current_data.index, false, seq_end_flag,
  2600. data_wrapper->GetOutput()); // [No need to check value]
  2601. continue);
  2602. }
  2603. GELOGI("rtStreamSynchronize end.");
  2604. GE_IF_BOOL_EXEC(model->is_first_execute_,
  2605. GE_TIMESTAMP_EVENT_END(rtStreamSynchronize, "GraphExcute::Wait for rtStreamSynchronize"));
  2606. GE_IF_BOOL_EXEC(ProfilingManager::Instance().ProfilingModelExecuteOn(), model->SetProfileTime(MODEL_INFER_END));
  2607. GE_IF_BOOL_EXEC(ProfilingManager::Instance().ProfilingModelExecuteOn(),
  2608. model->SetProfileTime(MODEL_AFTER_PROC_START));
  2609. GE_TIMESTAMP_START(ReturnResult3);
  2610. // copy output data from device to host
  2611. GE_IF_BOOL_EXEC(model->has_output_node_,
  2612. (void)model->ReturnResult(current_data.index, rslt_flg, false, data_wrapper->GetOutput()));
  2613. // copy output data from device to host for variable graph
  2614. GE_IF_BOOL_EXEC(!model->has_output_node_, (void)model->ReturnNoOutput(current_data.index));
  2615. GE_IF_BOOL_EXEC(model->is_first_execute_,
  2616. GE_TIMESTAMP_EVENT_END(ReturnResult3, "GraphExcute::CopyDataFromDeviceToHost"));
  2617. GE_IF_BOOL_EXEC(ProfilingManager::Instance().ProfilingModelExecuteOn(),
  2618. model->SetProfileTime(MODEL_AFTER_PROC_END));
  2619. GE_IF_BOOL_EXEC(ProfilingManager::Instance().ProfilingModelExecuteOn(), (void)model->SinkTimeProfile(current_data));
  2620. model->iterator_count_++;
  2621. model->is_first_execute_ = false;
  2622. // model run finished
  2623. model->SetRunningFlag(false);
  2624. GELOGI("run iterator count is %lu, model_id:%u", model->iterator_count_, model->model_id_);
  2625. }
  2626. GELOGI("Model run end, model id:%u", model->model_id_);
  2627. return nullptr;
  2628. }
  2629. ///
  2630. /// @ingroup ge
  2631. /// @brief call API provided by data inputer to destroy thread
  2632. /// @param [in] no
  2633. /// @return Status Destroy result
  2634. /// @author
  2635. ///
  2636. Status DavinciModel::DestroyThread() {
  2637. run_flg_ = false;
  2638. if (data_inputer_ != nullptr) {
  2639. data_inputer_->Stop();
  2640. }
  2641. if (thread_id_.joinable()) {
  2642. thread_id_.join();
  2643. }
  2644. return SUCCESS;
  2645. }
  2646. ///
  2647. /// @ingroup ge
  2648. /// @brief create model std::thread,
  2649. /// @brief start to execute Model
  2650. /// @param [in] no
  2651. /// @return Status create model thread and execute result
  2652. /// @author
  2653. ///
  2654. Status DavinciModel::ModelRunStart() {
  2655. GE_CHK_BOOL_RET_STATUS(data_inputer_ != nullptr, INTERNAL_ERROR,
  2656. "[Check][Param] data_inputer_ is nullptr, model id:%u.", model_id_);
  2657. LockRunFlg();
  2658. GE_MAKE_GUARD(tmp_lock, [&] { UnlockRunFlg(); });
  2659. GE_CHK_BOOL_RET_STATUS(!run_flg_, INTERNAL_ERROR, "[Check][Param] Model already started, model id:%u.", model_id_);
  2660. run_flg_ = true;
  2661. // create stream instance which rt_model_handel is running on
  2662. GE_CHK_RT_RET(rtStreamCreate(&rt_model_stream_, priority_));
  2663. is_inner_model_stream_ = true;
  2664. string opt = "0";
  2665. (void)ge::GetContext().GetOption(OPTION_GE_MAX_DUMP_OP_NUM, opt); // option may not be set up, no need to check value
  2666. int64_t maxDumpOpNum = std::strtol(opt.c_str(), nullptr, kDecimal);
  2667. maxDumpOpNum_ = maxDumpOpNum;
  2668. error_context_ = ErrorManager::GetInstance().GetErrorManagerContext();
  2669. CREATE_STD_THREAD(thread_id_, DavinciModel::Run, this);
  2670. GELOGI("model thread create success, model id:%u.", model_id_);
  2671. return SUCCESS;
  2672. }
  2673. ///
  2674. /// @ingroup ge
  2675. /// @brief call API provided by data inputer and destroy model Thread
  2676. /// @param [in] no
  2677. /// @return Status Destroy result
  2678. /// @author
  2679. ///
  2680. Status DavinciModel::ModelRunStop() {
  2681. LockRunFlg();
  2682. GE_MAKE_GUARD(tmp_lock, [&] { UnlockRunFlg(); });
  2683. GE_CHK_STATUS_RET(DestroyThread(), "[Destoy][Thead] failed, model id:%u.", model_id_);
  2684. return SUCCESS;
  2685. }
  2686. void DavinciModel::UnbindTaskSinkStream() {
  2687. // unbinding hcom stream
  2688. UnbindHcomStream();
  2689. if (is_stream_list_bind_) {
  2690. for (size_t i = 0; i < stream_list_.size(); i++) {
  2691. // unbind rt_model_handle and streams
  2692. GE_LOGW_IF(rtModelUnbindStream(rt_model_handle_, stream_list_[i]) != RT_ERROR_NONE,
  2693. "Unbind stream from model failed! Index: %zu", i);
  2694. }
  2695. }
  2696. if (is_inner_model_stream_) {
  2697. if (!input_queue_ids_.empty() || !output_queue_ids_.empty()) {
  2698. GE_LOGW_IF(rtModelUnbindStream(rt_model_handle_, rt_model_stream_) != RT_ERROR_NONE, "Unbind stream failed!");
  2699. }
  2700. // destroy stream that is bound with rt_model
  2701. GE_LOGW_IF(rtStreamDestroy(rt_model_stream_) != RT_ERROR_NONE, "Destroy stream for rt_model failed.")
  2702. }
  2703. if (is_pure_head_stream_ && rt_head_stream_ != nullptr) {
  2704. GE_LOGW_IF(rtModelUnbindStream(rt_model_handle_, rt_head_stream_) != RT_ERROR_NONE, "Unbind stream failed!");
  2705. GE_LOGW_IF(rtStreamDestroy(rt_head_stream_) != RT_ERROR_NONE, "Destroy stream for rt_model failed.");
  2706. rt_head_stream_ = nullptr;
  2707. }
  2708. if (rt_entry_stream_ != nullptr) {
  2709. GE_LOGW_IF(rtModelUnbindStream(rt_model_handle_, rt_entry_stream_) != RT_ERROR_NONE, "Unbind stream failed!");
  2710. GE_LOGW_IF(rtStreamDestroy(rt_entry_stream_) != RT_ERROR_NONE, "Destroy stream for rt_model failed.");
  2711. rt_entry_stream_ = nullptr;
  2712. }
  2713. }
  2714. void *DavinciModel::GetRunAddress(void *addr) const {
  2715. if (fixed_mem_base_ == reinterpret_cast<uintptr_t>(mem_base_)) {
  2716. return addr;
  2717. }
  2718. uintptr_t ptr = reinterpret_cast<uintptr_t>(addr);
  2719. if ((fixed_mem_base_ <= ptr) && (ptr < fixed_mem_base_ + runtime_param_.mem_size)) {
  2720. return mem_base_ + (ptr - fixed_mem_base_);
  2721. } else {
  2722. return addr;
  2723. }
  2724. }
  2725. Status DavinciModel::CreateKnownZeroCopyMap(const vector<void *> &inputs, const vector<void *> &outputs) {
  2726. GELOGI("in, inputs size: %zu, input addr size: %zu, outputs size: %zu, output addr size: %zu",
  2727. inputs.size(), input_addrs_list_.size(), outputs.size(), output_addrs_list_.size());
  2728. if (inputs.size() > input_addrs_list_.size()) {
  2729. REPORT_INNER_ERROR("E19999", "input data addr %zu should less than input op num %zu.",
  2730. inputs.size(), input_addrs_list_.size());
  2731. GELOGE(FAILED, "[Check][Param] input data addr %zu should less than input op num %zu.",
  2732. inputs.size(), input_addrs_list_.size());
  2733. return FAILED;
  2734. }
  2735. // remove zero copy addr in last iteration
  2736. known_input_data_info_.clear();
  2737. known_output_data_info_.clear();
  2738. for (size_t i = 0; i < inputs.size(); ++i) {
  2739. const vector<void *> &addr_list = input_addrs_list_[i];
  2740. void *addr = GetRunAddress(addr_list[kDataIndex]);
  2741. known_input_data_info_[addr] = inputs[i];
  2742. GELOGI("input %zu, v addr %p, r addr %p, p addr %p", i, addr_list[kDataIndex], addr, inputs[i]);
  2743. }
  2744. if (!has_output_node_) {
  2745. GELOGW("output op num in graph is %zu", output_addrs_list_.size());
  2746. return SUCCESS;
  2747. }
  2748. const vector<void *> &addr_list = output_addrs_list_.front();
  2749. for (size_t i = 0; i < addr_list.size() && i < outputs.size(); ++i) {
  2750. void *addr = GetRunAddress(addr_list[i]);
  2751. known_output_data_info_[addr] = outputs[i];
  2752. GELOGI("output %zu, v addr %p, r addr %p, p addr %p", i, addr_list[i], addr, outputs[i]);
  2753. }
  2754. GELOGI("success, known input data info size: %zu, known output data info size: %zu",
  2755. known_input_data_info_.size(), known_output_data_info_.size());
  2756. return SUCCESS;
  2757. }
  2758. void DavinciModel::SetTotalIOAddrs(const vector<void *> &io_addrs) {
  2759. if (fixed_mem_base_ == reinterpret_cast<uintptr_t>(mem_base_)) {
  2760. total_io_addrs_.insert(total_io_addrs_.end(), io_addrs.begin(), io_addrs.end());
  2761. return;
  2762. }
  2763. for (size_t i = 0; i < io_addrs.size(); ++i) {
  2764. total_io_addrs_.emplace_back(GetRunAddress(io_addrs[i]));
  2765. }
  2766. }
  2767. Status DavinciModel::UpdateKnownZeroCopyAddr(vector<void *> &total_io_addrs, bool update_args) {
  2768. if (fixed_mem_base_ != reinterpret_cast<uintptr_t>(mem_base_) && update_args) {
  2769. for (size_t i = 0; i < total_io_addrs.size(); ++i) {
  2770. total_io_addrs[i] = GetRunAddress(total_io_addrs[i]);
  2771. }
  2772. }
  2773. for (size_t i = 0; i < total_io_addrs.size(); ++i) {
  2774. auto it_in = known_input_data_info_.find(total_io_addrs[i]);
  2775. if (it_in != known_input_data_info_.end()) {
  2776. GELOGI("input %zu, v addr %p, p addr %p", i, total_io_addrs[i], known_input_data_info_.at(total_io_addrs[i]));
  2777. total_io_addrs[i] = known_input_data_info_.at(total_io_addrs[i]);
  2778. }
  2779. auto it_out = known_output_data_info_.find(total_io_addrs[i]);
  2780. if (it_out != known_output_data_info_.end()) {
  2781. GELOGI("output %zu, v addr %p, p addr %p", i, total_io_addrs[i], known_output_data_info_.at(total_io_addrs[i]));
  2782. total_io_addrs[i] = known_output_data_info_.at(total_io_addrs[i]);
  2783. }
  2784. }
  2785. GELOGI("success, total io addrs size: %zu", total_io_addrs.size());
  2786. return SUCCESS;
  2787. }
  2788. Status DavinciModel::UpdateKnownNodeArgs(const vector<void *> &inputs, const vector<void *> &outputs) {
  2789. GELOGI("DavinciModel::UpdateKnownNodeArgs in");
  2790. GE_CHK_STATUS_RET(CreateKnownZeroCopyMap(inputs, outputs),
  2791. "[Call][CreateKnownZeroCopyMap] failed, model_id:%u.", model_id_);
  2792. total_io_addrs_.clear();
  2793. for (size_t task_index = 0; task_index < task_list_.size(); ++task_index) {
  2794. auto &task = task_list_[task_index];
  2795. if (task != nullptr) {
  2796. Status ret = task->UpdateArgs();
  2797. if (ret != SUCCESS) {
  2798. REPORT_CALL_ERROR("E19999", "task %zu update args failed, model_id:%u", task_index, model_id_);
  2799. GELOGE(FAILED, "[Update][Args] to task %zu failed, model_id:%u.", task_index, model_id_);
  2800. return FAILED;
  2801. }
  2802. }
  2803. }
  2804. GE_CHK_STATUS_RET(UpdateKnownZeroCopyAddr(total_io_addrs_, false),
  2805. "[Call][UpdateKnownZeroCopyAddr] failed, model_id:%u.", model_id_);
  2806. if (total_args_size_ == 0) {
  2807. GELOGW("DavinciModel::UpdateKnownNodeArgs device args %p, dst size %u, pass rtMemcpy.", args_, total_args_size_);
  2808. } else {
  2809. uint32_t total_addr_size = total_io_addrs_.size() * sizeof(uint64_t);
  2810. GELOGI("DavinciModel::UpdateKnownNodeArgs device args %p, dst size %u, src size %u", args_, total_args_size_,
  2811. total_addr_size);
  2812. Status rt_ret =
  2813. rtMemcpy(args_, total_args_size_, total_io_addrs_.data(), total_addr_size, RT_MEMCPY_HOST_TO_DEVICE);
  2814. GE_IF_BOOL_EXEC(rt_ret != RT_ERROR_NONE,
  2815. REPORT_CALL_ERROR("E19999", "Call rtMemcpy failed, size:%u, ret:0x%X", total_args_size_ , rt_ret);
  2816. GELOGE(rt_ret, "[Call][RtMemcpy] failed, size:%u, ret:0x%X", total_args_size_ , rt_ret);
  2817. return FAILED;)
  2818. }
  2819. GELOGI("DavinciModel::UpdateKnownNodeArgs success");
  2820. return SUCCESS;
  2821. }
  2822. Status DavinciModel::InitTaskInfo(domi::ModelTaskDef &model_task_def) {
  2823. GELOGI("InitTaskInfo in, task size %d", model_task_def.task().size());
  2824. task_list_.resize(model_task_def.task_size());
  2825. for (int i = 0; i < model_task_def.task_size(); ++i) {
  2826. // dynamic shape will create task_list_ before
  2827. const domi::TaskDef &task = model_task_def.task(i);
  2828. if (this->task_list_[i] == nullptr) {
  2829. task_list_[i] = TaskInfoFactory::Instance().Create(static_cast<rtModelTaskType_t>(task.type()));
  2830. }
  2831. GE_CHECK_NOTNULL(task_list_[i]);
  2832. Status ret = task_list_[i]->Init(task, this);
  2833. if (ret != SUCCESS) {
  2834. REPORT_CALL_ERROR("E19999", "Task index:%d init failed, ret:%d.", i, ret);
  2835. GELOGE(ret, "[Init][Task] index:%d failed, ret:%d.", i, ret);
  2836. return ret;
  2837. }
  2838. }
  2839. GELOGI("InitTaskInfo out");
  2840. return SUCCESS;
  2841. }
  2842. Status DavinciModel::CheckCapability(rtFeatureType_t featureType, int32_t featureInfo, bool &is_support) const {
  2843. int64_t value = RT_CAPABILITY_SUPPORT;
  2844. auto rt_ret = rtGetRtCapability(featureType, featureInfo, &value);
  2845. GE_CHK_BOOL_RET_STATUS(rt_ret == RT_ERROR_NONE, FAILED, "[Call][RtGetRtCapability] failed, ret:0x%X", rt_ret);
  2846. is_support = (value == RT_CAPABILITY_SUPPORT) ? true : false;
  2847. return SUCCESS;
  2848. }
  2849. Status DavinciModel::MallocKnownArgs() {
  2850. GELOGI("DavinciModel::MallocKnownArgs in");
  2851. const auto &model_task_def = ge_model_->GetModelTaskDefPtr();
  2852. if (model_task_def->task_size() == 0) {
  2853. GELOGW("DavinciModel::MallocKnownArgs davincimodel has no task info.");
  2854. return SUCCESS;
  2855. }
  2856. task_list_.resize(model_task_def->task_size());
  2857. for (int32_t i = 0; i < model_task_def->task_size(); ++i) {
  2858. const domi::TaskDef &taskdef = model_task_def->task(i);
  2859. task_list_[i] = TaskInfoFactory::Instance().Create(static_cast<rtModelTaskType_t>(taskdef.type()));
  2860. GE_CHECK_NOTNULL(task_list_[i]);
  2861. Status ret = task_list_[i]->CalculateArgs(taskdef, this);
  2862. if (ret != SUCCESS) {
  2863. REPORT_CALL_ERROR("E19999", "task index:%d CalculateArgs failed, ret:%d", i, ret);
  2864. GELOGE(ret, "[Calculate][Args] for taskdef index:%d failed, ret:%d", i, ret);
  2865. return ret;
  2866. }
  2867. }
  2868. rtError_t rt_ret;
  2869. bool is_support = false;
  2870. GE_CHK_STATUS_RET_NOLOG(CheckCapability(FEATURE_TYPE_MEMORY, MEMORY_INFO_TS_4G_LIMITED, is_support));
  2871. auto mem_type = is_support ? RT_MEMORY_TS_4G : RT_MEMORY_HBM;
  2872. // malloc args memory
  2873. if (total_args_size_ != 0) {
  2874. rt_ret = rtMalloc(&args_, total_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_args_size_, rt_ret);
  2877. GELOGE(RT_FAILED, "[Call][RtMalloc] failed, size:%u, ret: 0x%X", total_args_size_, rt_ret);
  2878. return RT_ERROR_TO_GE_STATUS(rt_ret);
  2879. }
  2880. }
  2881. // malloc dynamic and static hybrid memory
  2882. if (total_hybrid_args_size_ != 0) {
  2883. rt_ret = rtMalloc(&hybrid_addrs_, total_hybrid_args_size_, mem_type);
  2884. if (rt_ret != RT_ERROR_NONE) {
  2885. REPORT_CALL_ERROR("E19999", "Call rtMalloc failed, size:%u, ret: 0x%X", total_hybrid_args_size_, rt_ret);
  2886. GELOGE(RT_FAILED, "[Call][RtMalloc] failed, size:%u, ret: 0x%X", total_hybrid_args_size_, rt_ret);
  2887. return RT_ERROR_TO_GE_STATUS(rt_ret);
  2888. }
  2889. }
  2890. // malloc fixed addr memory, eg: rts op
  2891. if (total_fixed_addr_size_ != 0) {
  2892. GELOGI("Begin to allocate fixed addr.");
  2893. rt_ret = rtMalloc(&fixed_addrs_, total_fixed_addr_size_, mem_type);
  2894. if (rt_ret != RT_ERROR_NONE) {
  2895. REPORT_CALL_ERROR("E19999", "Call rtMalloc failed, size:%u, ret: 0x%X", total_hybrid_args_size_, rt_ret);
  2896. GELOGE(RT_FAILED, "[Call][RtMalloc] failed, size:%u, ret: 0x%X", total_hybrid_args_size_, rt_ret);
  2897. return RT_ERROR_TO_GE_STATUS(rt_ret);
  2898. }
  2899. }
  2900. GELOGI("DavinciModel::MallocKnownArgs success, total args size %u. total fixed addr size %ld", total_args_size_,
  2901. total_fixed_addr_size_);
  2902. return SUCCESS;
  2903. }
  2904. void DavinciModel::SaveProfilingTaskDescInfo(const OpDescPtr &op, const TaskInfoPtr &task,
  2905. const domi::TaskDef &task_def, size_t task_index) {
  2906. bool flag = GetL1FusionEnableOption();
  2907. char skt_enable_env[MMPA_MAX_PATH] = { 0x00 };
  2908. INT32 res = mmGetEnv("SKT_ENABLE", skt_enable_env, MMPA_MAX_PATH);
  2909. int64_t env_flag = (res == EN_OK) ? std::strtol(skt_enable_env, nullptr, kDecimal) : 0;
  2910. if (env_flag != 0) {
  2911. flag = true;
  2912. }
  2913. TaskDescInfo task_desc_info;
  2914. if (!om_name_.empty()) {
  2915. task_desc_info.model_name = om_name_;
  2916. } else {
  2917. task_desc_info.model_name = name_;
  2918. }
  2919. task_desc_info.op_name = op->GetName();
  2920. task_desc_info.op_type = op->GetType();
  2921. task_desc_info.block_dim = task_def.kernel().block_dim();
  2922. task_desc_info.task_id = task->GetTaskID();
  2923. task_desc_info.stream_id = task->GetStreamId();
  2924. task_desc_info.shape_type = "static";
  2925. task_desc_info.cur_iter_num = 0;
  2926. task_desc_info.task_type = kTaskTypeInvalid;
  2927. auto &prof_mgr = ProfilingManager::Instance();
  2928. prof_mgr.GetOpInputOutputInfo(op, task_desc_info);
  2929. auto model_task_type = static_cast<rtModelTaskType_t>(task_def.type());
  2930. if (model_task_type == RT_MODEL_TASK_KERNEL) {
  2931. const domi::KernelDef &kernel_def = task_def.kernel();
  2932. const auto &context = kernel_def.context();
  2933. auto kernel_type = static_cast<ccKernelType>(context.kernel_type());
  2934. if (kernel_type == ccKernelType::TE) {
  2935. task_desc_info.task_type = kTaskTypeAicore;
  2936. } else if (kernel_type == ccKernelType::AI_CPU || kernel_type == ccKernelType::CUST_AI_CPU) {
  2937. task_desc_info.task_type = kTaskTypeAicpu;
  2938. } else {
  2939. GELOGD("Other kernel type: %u", context.kernel_type());
  2940. }
  2941. } else if (model_task_type == RT_MODEL_TASK_KERNEL_EX) {
  2942. task_desc_info.task_type = kTaskTypeAicpu;
  2943. } else {
  2944. GELOGD("Skip task type: %d", static_cast<int>(model_task_type));
  2945. }
  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. if (flag) {
  2950. if (task->GetSktTaskID() != 0xFFFFFFFF) {
  2951. TaskDescInfo task_desc_info;
  2952. string op_name = "super_kernel_" + to_string(task_index);
  2953. task_desc_info.op_name = op_name;
  2954. task_desc_info.task_id = task->GetSktTaskID();
  2955. profiler_report_op_info_[task_desc_info.op_name] =
  2956. std::pair<uint32_t, uint32_t>(task_desc_info.task_id, task_desc_info.stream_id);
  2957. task_desc_info_.emplace_back(task_desc_info);
  2958. }
  2959. }
  2960. }
  2961. Status DavinciModel::DistributeTask() {
  2962. GELOGI("do Distribute.");
  2963. for (auto &task : cpu_task_list_) {
  2964. if (task == nullptr) {
  2965. GELOGW("task is null");
  2966. continue;
  2967. }
  2968. GE_CHK_STATUS_RET(task->Distribute());
  2969. }
  2970. task_desc_info_.clear();
  2971. const auto &model_task_def = ge_model_->GetModelTaskDefPtr();
  2972. for (size_t task_index = 0; task_index < task_list_.size(); ++task_index) {
  2973. auto &task_def = model_task_def->task(task_index);
  2974. auto &task = task_list_.at(task_index);
  2975. GE_CHECK_NOTNULL(task);
  2976. GE_CHK_STATUS_RET(task->Distribute(), "[Call][Distribute] for Task[%zu] fail", task_index);
  2977. // for data dump
  2978. auto op_index = std::max(task_def.kernel().context().op_index(),
  2979. task_def.kernel_ex().op_index());
  2980. OpDescPtr op = GetOpByIndex(op_index);
  2981. GE_CHECK_NOTNULL(op);
  2982. if (reinterpret_cast<void *>(task->GetDumpArgs()) != nullptr) {
  2983. bool call_dump = OpNeedDump(op->GetName()) && task->CallSaveDumpInfo();
  2984. if (call_dump || is_op_debug_reg_) {
  2985. SaveDumpTask(task->GetTaskID(), task->GetStreamId(), op, task->GetDumpArgs());
  2986. }
  2987. }
  2988. auto task_type = static_cast<rtModelTaskType_t>(task_def.type());
  2989. bool no_need_profiling = (task_type != RT_MODEL_TASK_KERNEL) && (task_type != RT_MODEL_TASK_KERNEL_EX);
  2990. GE_IF_BOOL_EXEC(no_need_profiling, continue);
  2991. SaveDumpOpInfo(runtime_param_, op, task->GetTaskID(), task->GetStreamId());
  2992. // save task info for profiling
  2993. SaveProfilingTaskDescInfo(op, task, task_def, task_index);
  2994. }
  2995. // launch dump kernel to aicpu
  2996. GE_CHK_STATUS_RET(data_dumper_.LoadDumpInfo(), "[Load][DumpInfo] failed, model_id:%u.", model_id_);
  2997. return SUCCESS;
  2998. }
  2999. bool DavinciModel::ModelNeedDump() {
  3000. auto all_dump_model = GetDumpProperties().GetAllDumpModel();
  3001. bool ret = all_dump_model.find(ge::DUMP_ALL_MODEL) != all_dump_model.end() ||
  3002. all_dump_model.find(dump_model_name_) != all_dump_model.end() ||
  3003. all_dump_model.find(om_name_) != all_dump_model.end();
  3004. return ret;
  3005. }
  3006. void DavinciModel::SetEndGraphId(uint32_t task_id, uint32_t stream_id) {
  3007. if (ModelNeedDump()) {
  3008. GELOGI("start save end_graph_info to dumper, task_id is %u, stream_id is %u", task_id, stream_id);
  3009. data_dumper_.SaveEndGraphId(task_id, stream_id);
  3010. }
  3011. }
  3012. ///
  3013. /// @ingroup ge
  3014. /// @brief Set copy only for No task feed NetOutput address.
  3015. /// @return None.
  3016. ///
  3017. void DavinciModel::SetCopyOnlyOutput() {
  3018. for (const auto &output_outside_addrs : output_data_info_) {
  3019. ZeroCopyOffset output_outside = output_outside_addrs.second;
  3020. if (!output_outside.IsRelativeOffsetValid()) {
  3021. return;
  3022. }
  3023. for (uint32_t out_count = 0; out_count < output_outside.GetAddrCount(); ++out_count) {
  3024. auto &addrs_mapping_list = output_outside.GetOutsideAddrs();
  3025. std::map<const void *, std::vector<void *>> virtual_args_addrs = addrs_mapping_list[out_count];
  3026. for (const auto &virtual_args_addr : virtual_args_addrs) {
  3027. const auto &args_addrs = virtual_args_addr.second;
  3028. if (args_addrs.empty()) { // No task feed Output addr, Need copy directly.
  3029. GELOGI("[ZCPY] just copy %p to netoutput.", virtual_args_addr.first);
  3030. copy_only_addrs_.insert(virtual_args_addr.first);
  3031. }
  3032. }
  3033. }
  3034. }
  3035. }
  3036. ///
  3037. /// @ingroup ge
  3038. /// @brief Set disabled input zero copy addr.
  3039. /// @param [in] const void *addr: address of task
  3040. /// @return None.
  3041. ///
  3042. void DavinciModel::DisableZeroCopy(const void *addr) {
  3043. if (real_virtual_addrs_.find(addr) == real_virtual_addrs_.end()) {
  3044. return;
  3045. }
  3046. // Data link to RTS Op directly.
  3047. std::lock_guard<std::mutex> lock(outside_addrs_mutex_);
  3048. GELOGI("[ZCPY] disable zero copy of %p.", addr);
  3049. copy_only_addrs_.insert(addr);
  3050. }
  3051. ///
  3052. /// @ingroup ge
  3053. /// @brief Save outside address used info for ZeroCopy.
  3054. /// @param [in] const OpDescPtr &op_desc: current op desc
  3055. /// @param [in] const std::vector<void *> &outside_addrs: address of task
  3056. /// @param [in] const void *info: task args
  3057. /// @param [in] const char *args: task args
  3058. /// @param [in] size_t size: size of task args
  3059. /// @param [in] size_t offset: offset of task args
  3060. /// @return None.
  3061. ///
  3062. void DavinciModel::SetZeroCopyAddr(const OpDescPtr &op_desc, const std::vector<void *> &outside_addrs, const void *info,
  3063. void *args, size_t size, size_t offset) {
  3064. // Internal call has ensured that op_desc is not nullptr
  3065. GELOGD("[ZCPY] SetZeroCopyAddr for %s.", op_desc->GetName().c_str());
  3066. size_t nums = outside_addrs.size();
  3067. ZeroCopyTask zero_copy_task(op_desc->GetName(), static_cast<uint8_t *>(args), size);
  3068. for (size_t i = 0; i < nums; ++i) {
  3069. std::lock_guard<std::mutex> lock(outside_addrs_mutex_);
  3070. for (auto &input_outside_addrs : input_data_info_) {
  3071. ZeroCopyOffset &input_outside = input_outside_addrs.second;
  3072. input_outside.SetOutsideAddrsValue(zero_copy_task, outside_addrs[i], args, offset + i * kAddrLen);
  3073. }
  3074. for (auto &output_outside_addrs : output_data_info_) {
  3075. ZeroCopyOffset &output_outside = output_outside_addrs.second;
  3076. output_outside.SetOutsideAddrsValue(zero_copy_task, outside_addrs[i], args, offset + i * kAddrLen);
  3077. }
  3078. }
  3079. string batch_label;
  3080. if (!AttrUtils::GetStr(op_desc, ATTR_NAME_BATCH_LABEL, batch_label) || batch_label.empty()) {
  3081. zero_copy_task.SetBatchLabel(kDefaultBatchLable);
  3082. } else {
  3083. zero_copy_task.SetBatchLabel(batch_label);
  3084. }
  3085. std::lock_guard<std::mutex> lock(outside_addrs_mutex_);
  3086. if (zero_copy_task.IsTaskArgsSet()) {
  3087. zero_copy_task.SetOriginalArgs(info, offset + nums * kAddrLen);
  3088. zero_copy_tasks_.emplace_back(zero_copy_task);
  3089. }
  3090. }
  3091. ///
  3092. /// @ingroup ge
  3093. /// @brief Copy Check input size and model op size.
  3094. /// @param [in] const int64_t &input_size: input size.
  3095. /// @param [in] const int64_t &op_size: model op size.
  3096. /// @param [in] is_dynamic: dynamic batch input flag.
  3097. /// @return true if success
  3098. ///
  3099. bool DavinciModel::CheckUserAndModelSize(const int64_t &size, const int64_t &op_size,
  3100. bool is_input, bool is_dynamic) {
  3101. const std::string input_or_output = is_input ? "input" : "output";
  3102. if (is_dynamic) { // dynamic is max size.
  3103. GELOGI("No need to check user %s and model size.", input_or_output.c_str());
  3104. return true;
  3105. }
  3106. if (size > op_size) {
  3107. GELOGW(
  3108. "User %s size [%ld] is bigger than om size need [%ld], "
  3109. "MAY cause inference result ERROR, please check model input",
  3110. input_or_output.c_str(), size, op_size);
  3111. }
  3112. if (is_dynamic_aipp_) {
  3113. GELOGI("This is dynamic aipp model, no need to judge smaller user size");
  3114. return true;
  3115. }
  3116. // Judge overflow first
  3117. if (size > (INT64_MAX - kDataMemAlignSizeCompare)) {
  3118. GELOGI("The user %s size [%ld] is smaller than model size [%ld] and is in the range of 64 bytes",
  3119. input_or_output.c_str(), size, op_size);
  3120. return true;
  3121. }
  3122. // The input and model input size can not be exactly equal because user input is not definite.
  3123. if ((size + kDataMemAlignSizeCompare) < op_size) {
  3124. REPORT_INNER_ERROR("E19999", "%s size:%ld from user add align:%u < op_size:%ld in model, model_id:%u, "
  3125. "check invalid",
  3126. input_or_output.c_str(), size, kDataMemAlignSizeCompare, op_size, model_id_);
  3127. GELOGE(ACL_ERROR_GE_PARAM_INVALID,
  3128. "[Check][Param] %s size:%ld from user add align:%u < op_size:%ld in model, model_id:%u",
  3129. input_or_output.c_str(), size, kDataMemAlignSizeCompare, op_size, model_id_);
  3130. return false;
  3131. }
  3132. return true;
  3133. }
  3134. ///
  3135. /// @ingroup ge
  3136. /// @brief Copy Inputs and Outputs addr to model for direct use.
  3137. /// @param [in] const InputData &input_data: model input data.
  3138. /// @param [in] OutputData &output_data: model output data.
  3139. /// @param [in] bool is_dynamic_input: whether is dynamic input, true: is dynamic input; false: not is dynamic input
  3140. /// @return SUCCESS handle successfully / PARAM_INVALID for failed
  3141. ///
  3142. Status DavinciModel::CopyModelData(const InputData &input_data, OutputData &output_data, bool is_dynamic) {
  3143. if (UpdateIoTaskArgs(input_data_info_, true, input_data.blobs, is_dynamic, input_data.batch_label) != SUCCESS) {
  3144. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "[Call][UpdateIoTaskArgs] [ZCPY] Update input data to model:%u failed.",
  3145. model_id_);
  3146. return ACL_ERROR_GE_PARAM_INVALID;
  3147. }
  3148. if (UpdateIoTaskArgs(output_data_info_, false, output_data.blobs, is_dynamic, input_data.batch_label) !=
  3149. SUCCESS) {
  3150. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "[Call][UpdateIoTaskArgs] [ZCPY] Update output data to model:%u failed.",
  3151. model_id_);
  3152. return ACL_ERROR_GE_PARAM_INVALID;
  3153. }
  3154. for (ZeroCopyTask &task : zero_copy_tasks_) {
  3155. GE_CHK_STATUS_RET(task.DistributeParam(is_async_mode_, rt_model_stream_),
  3156. "[Call][DistributeParam] [ZCPY] Update args failed, model_id:%u.", model_id_);
  3157. }
  3158. output_data.index = input_data.index;
  3159. output_data.model_id = model_id_;
  3160. return SUCCESS;
  3161. }
  3162. ///
  3163. /// @ingroup ge
  3164. /// @brief Copy Data addr to model for direct use.
  3165. /// @param [in] data_info: model memory addr/size map { data_index, { tensor_size, tensor_addr } }.
  3166. /// @param [in] is_input: input data or output data
  3167. /// @param [in] blobs: user input/output data list.
  3168. /// @param [in] is_dynamic: whether is dynamic input, true: is dynamic input; false: not is dynamic input
  3169. /// @param [in] batch_label: batch label for multi-batch scenes
  3170. /// @return SUCCESS handle successfully / others handle failed
  3171. ///
  3172. Status DavinciModel::UpdateIoTaskArgs(const std::map<uint32_t, ZeroCopyOffset> &data_info, bool is_input,
  3173. const vector<DataBuffer> &blobs, bool is_dynamic, const string &batch_label) {
  3174. if (blobs.size() != data_info.size()) {
  3175. REPORT_INNER_ERROR("E19999", "is_input:%d blob size:%ld from user != op_size:%ld in model, mode_id:%u"
  3176. "check invalid", is_input, blobs.size(), data_info.size(), model_id_);
  3177. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "[Check][Param] is_input:%d blob size:%ld "
  3178. "from user != op_size:%ld in model, mode_id:%u",
  3179. is_input, blobs.size(), data_info.size(), model_id_);
  3180. return ACL_ERROR_GE_PARAM_INVALID;
  3181. }
  3182. for (const auto &data : data_info) {
  3183. if (data.first >= blobs.size()) { // check data index.
  3184. REPORT_INNER_ERROR("E19999", "is_input:%d, data index:%u from model >= blobs.size:%zu from user, mode_id:%u"
  3185. "check invalid", is_input, data.first, blobs.size(), model_id_);
  3186. GELOGE(ACL_ERROR_GE_PARAM_INVALID,
  3187. "[Check][Param] is_input:%d, data index:%u from model >= blobs.size:%zu from user, mode_id:%u",
  3188. is_input, data.first, blobs.size(), model_id_);
  3189. return ACL_ERROR_GE_PARAM_INVALID;
  3190. }
  3191. const DataBuffer &buffer = blobs[data.first]; // index of data.
  3192. if (buffer.data == nullptr) {
  3193. REPORT_INNER_ERROR("E19999", "is_input:%d buffer from user is nullptr, index:%u, mode_id:%u"
  3194. "check invalid", is_input, data.first, model_id_);
  3195. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "[Check][Param] data_buf.data is nullptr, "
  3196. "index=%u, mode_id:%u", data.first, model_id_);
  3197. return ACL_ERROR_GE_PARAM_INVALID;
  3198. }
  3199. if (!CheckUserAndModelSize(buffer.length, data.second.GetDataSize(), is_input, is_dynamic)) {
  3200. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "[Call][CheckInputAndModelSize] failed, op[%s]",
  3201. data.second.GetOpName().c_str());
  3202. return ACL_ERROR_GE_PARAM_INVALID;
  3203. }
  3204. void *basic_addr = data.second.GetBasicAddr();
  3205. uint64_t data_size = data.second.GetDataSize();
  3206. if (copy_only_addrs_.count(basic_addr) > 0) {
  3207. if (is_input && buffer.length > 0) {
  3208. GELOGI("[IMAS] Find addr %p need direct copy from user malloc input %p", basic_addr, buffer.data);
  3209. rtError_t rt_ret = rtMemcpy(basic_addr, data_size, buffer.data, buffer.length, RT_MEMCPY_DEVICE_TO_DEVICE);
  3210. if (rt_ret != RT_ERROR_NONE) {
  3211. REPORT_CALL_ERROR("E19999", "Call rtMemcpy failed, size:%lu, model_id:%u", data_size, model_id_);
  3212. GELOGE(rt_ret, "[Call][RtMemcpy] failed, size:%lu, model_id:%u", data_size, model_id_);
  3213. return RT_ERROR_TO_GE_STATUS(rt_ret);
  3214. }
  3215. }
  3216. GELOGI("No need to exeucte zero copy task because this addr %p need direct copy.", basic_addr);
  3217. continue;
  3218. }
  3219. for (size_t count = 0; count < data.second.GetDataCount(); ++count) {
  3220. void *addr = data.second.GetDataInfo().at(count).second;
  3221. void *buffer_addr = reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(buffer.data) +
  3222. data.second.GetRelativeOffset().at(count));
  3223. GELOGI("[ZCPY] Copy %s blobs_index %u, virtual_addr: %p, size: %ld, user_data_addr: %p, batch_label: %s",
  3224. is_input ? "input" : "output", data.first, addr, data.second.GetDataInfo().at(count).first,
  3225. buffer_addr, batch_label.c_str());
  3226. // For input data, just copy for rts task.
  3227. for (auto &task : zero_copy_tasks_) {
  3228. bool not_same_batch = (task.GetBatchLabel() != kDefaultBatchLable && task.GetBatchLabel() != batch_label);
  3229. if (not_same_batch) {
  3230. continue;
  3231. }
  3232. uintptr_t addr_val = reinterpret_cast<uintptr_t>(addr);
  3233. (void)task.UpdateTaskParam(addr_val, buffer_addr);
  3234. }
  3235. }
  3236. }
  3237. return SUCCESS;
  3238. }
  3239. ///
  3240. /// @ingroup ge
  3241. /// @brief get unique identification for op when load two or more models
  3242. /// @param [in] const OpDescPtr: current op.
  3243. /// @param [in] string identification: unique identification for current op.
  3244. /// @return SUCCESS handle successfully / others handle failed
  3245. ///
  3246. void DavinciModel::GetUniqueId(const OpDescPtr &op_desc, std::string &unique_identification) {
  3247. std::string session_graph_id;
  3248. GE_IF_BOOL_EXEC(AttrUtils::GetStr(*op_desc, ATTR_NAME_SESSION_GRAPH_ID, session_graph_id),
  3249. GELOGD("Get original type of session_graph_id."));
  3250. if (session_graph_id.empty()) {
  3251. return;
  3252. } else if (session_graph_id.find("-1") != string::npos) {
  3253. unique_identification = session_graph_id + "_" + to_string(model_id_);
  3254. } else {
  3255. unique_identification = session_graph_id;
  3256. }
  3257. }
  3258. ///
  3259. /// @ingroup ge
  3260. /// @brief For TVM Op, avoid Addr Reuse.
  3261. /// @return void*
  3262. ///
  3263. const char *DavinciModel::GetRegisterStub(const string &binfile, const string &session_graph_id) {
  3264. string binfile_key;
  3265. if (session_graph_id.empty()) {
  3266. binfile_key = binfile;
  3267. } else {
  3268. binfile_key = session_graph_id + "_" + binfile;
  3269. }
  3270. auto it = tvm_bin_kernel_.find(binfile_key);
  3271. if (it != tvm_bin_kernel_.end()) {
  3272. return it->c_str();
  3273. } else {
  3274. it = tvm_bin_kernel_.insert(tvm_bin_kernel_.end(), binfile_key);
  3275. return it->c_str();
  3276. }
  3277. }
  3278. ///
  3279. /// @ingroup ge
  3280. /// @brief Constant Op Init.
  3281. /// @return Status
  3282. ///
  3283. Status DavinciModel::InitConstant(const OpDescPtr &op_desc) {
  3284. auto v_weights = ModelUtils::GetWeights(op_desc);
  3285. auto v_output_size = ModelUtils::GetOutputSize(op_desc);
  3286. auto v_output_addr = ModelUtils::GetOutputDataAddrs(runtime_param_, op_desc);
  3287. GE_IF_BOOL_EXEC(v_weights.empty() || v_output_size.empty() || v_output_addr.empty(),
  3288. REPORT_INNER_ERROR("E19999", "weight.size:%zu output_length.size:%zu output_addr.size:%zu in "
  3289. "op:%s(%s) has empty, model_id:%u, check invalid",
  3290. v_weights.size(),v_output_size.size(), v_output_addr.size(),
  3291. op_desc->GetName().c_str(), op_desc->GetType().c_str() ,model_id_);
  3292. GELOGE(PARAM_INVALID, "const op:%s not set output", op_desc->GetName().c_str());
  3293. return PARAM_INVALID;);
  3294. GeTensor *tensor = const_cast<GeTensor *>(v_weights[0].get());
  3295. GE_IF_BOOL_EXEC(static_cast<size_t>(v_output_size[0]) < tensor->GetData().size(),
  3296. REPORT_INNER_ERROR("E19999", "Output size:%zu < weight size:%zu in op:%s(%s) model_id:%u, "
  3297. "check invalid", v_output_size[0], tensor->GetData().size(),
  3298. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3299. GELOGE(PARAM_INVALID, "[Check][Param] Output size:%zu < weight size:%zu in op:%s(%s), model_id:%u",
  3300. v_output_size[0], tensor->GetData().size(),
  3301. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3302. return PARAM_INVALID;);
  3303. GE_IF_BOOL_EXEC(tensor->GetData().size() == 0, GELOGW("const op:%s has no weight data.", op_desc->GetName().c_str());
  3304. return SUCCESS;);
  3305. auto desc = tensor->GetTensorDesc();
  3306. if (desc.GetDataType() == DT_STRING) {
  3307. GeShape tensor_shape = desc.GetShape();
  3308. /// if tensor is a scaler, it's shape size if zero, according ge_tensor.cc.
  3309. /// the logic of GetShapeSize is wrong, the scaler tensor's GetShapeSize is zero
  3310. /// and that of unknown shape is zero too.
  3311. /// unknown shape will not appear here, so we can use zero judge a tensor is scaler or not
  3312. int64_t elem_num = tensor_shape.GetShapeSize();
  3313. if (elem_num == 0 && tensor_shape.GetDims().size() == 0) {
  3314. elem_num = 1;
  3315. }
  3316. uint64_t *buff = reinterpret_cast<uint64_t *>(tensor->MutableData().data());
  3317. GE_CHECK_NOTNULL(buff);
  3318. if (ge::CheckInt64Uint32MulOverflow(elem_num, kBytes * kStringHeadElems) != SUCCESS) {
  3319. GELOGE(FAILED, "[Call][CheckInt64Uint32MulOverflow] Shape size:%ld is invalid", elem_num);
  3320. return FAILED;
  3321. }
  3322. uint64_t offset = elem_num * kBytes * kStringHeadElems;
  3323. uint64_t hbm_raw_data_base_addr =
  3324. static_cast<uint64_t>(reinterpret_cast<uintptr_t>(v_output_addr[0])) + offset;
  3325. for (int64_t i = elem_num - 1; i >= 0; --i) {
  3326. buff[i * kStringHeadElems] = hbm_raw_data_base_addr + (buff[i * kStringHeadElems] - buff[0]);
  3327. }
  3328. }
  3329. GELOGI("[IMAS]InitConstant memcpy graph_%u type[V] name[%s] output[%d] memaddr[%p] mem_size[%lu] datasize[%zu]",
  3330. runtime_param_.graph_id, op_desc->GetName().c_str(), 0, v_output_addr[0], v_output_size[0],
  3331. tensor->GetData().size());
  3332. GE_CHK_RT_RET(rtMemcpy(v_output_addr[0], v_output_size[0], tensor->GetData().data(), tensor->GetData().size(),
  3333. RT_MEMCPY_HOST_TO_DEVICE));
  3334. return SUCCESS;
  3335. }
  3336. ///
  3337. /// @ingroup ge
  3338. /// @brief TVM Op Init.
  3339. /// @return Status
  3340. ///
  3341. Status DavinciModel::InitTbeHandle(const OpDescPtr &op_desc) {
  3342. string bin_file = op_desc->GetName();
  3343. auto kernel = ge_model_->GetTBEKernelStore().FindKernel(op_desc->GetName());
  3344. auto tbe_kernel = (kernel != nullptr) ? kernel : op_desc->TryGetExtAttr(OP_EXTATTR_NAME_TBE_KERNEL, TBEKernelPtr());
  3345. if (tbe_kernel == nullptr) {
  3346. REPORT_INNER_ERROR("E19999", "Get tbe_kernel for op:%s(%s) fail, model_id:%u",
  3347. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3348. GELOGE(INTERNAL_ERROR, "[Check][Param] TBE: %s can't find tvm bin file!", op_desc->GetName().c_str());
  3349. return INTERNAL_ERROR;
  3350. }
  3351. GE_CHK_STATUS_RET(FunctionRegister(op_desc, bin_file, tbe_kernel, false), "Function register of bin file: %s failed",
  3352. bin_file.c_str());
  3353. return SUCCESS;
  3354. }
  3355. Status DavinciModel::InitTbeHandleWithFfts(const OpDescPtr &op_desc) {
  3356. std::vector<OpKernelBinPtr> tbe_kernel;
  3357. tbe_kernel = op_desc->TryGetExtAttr(OP_EXTATTR_NAME_THREAD_TBE_KERNEL, tbe_kernel);
  3358. GELOGD("Kernel bin ptr vec size is %zu.", tbe_kernel.size());
  3359. if (tbe_kernel.size() != kFftsTbeHandleElementSize) {
  3360. REPORT_INNER_ERROR("E19999", "Get tbe_kernel for op:%s(%s) fail, model_id:%u",
  3361. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3362. GELOGE(INTERNAL_ERROR, "[Check][Param] TBE: %s can't find tvm bin file, size is %zu when ffts",
  3363. op_desc->GetName().c_str(), tbe_kernel.size());
  3364. return INTERNAL_ERROR;
  3365. }
  3366. if (tbe_kernel[0] == nullptr || tbe_kernel[1] == nullptr) {
  3367. REPORT_INNER_ERROR("E19999", "Tbe kernel for op:%s is nullptr.", op_desc->GetName().c_str());
  3368. GELOGE(INTERNAL_ERROR, "[Check][Param] TBE: tvm bin file of %s is nullptr when ffts.", op_desc->GetName().c_str());
  3369. return INTERNAL_ERROR;
  3370. }
  3371. vector<string> bin_file_keys;
  3372. (void)AttrUtils::GetListStr(op_desc, kStubFuncName, bin_file_keys);
  3373. if (bin_file_keys.size() != kFftsTbeHandleElementSize) {
  3374. REPORT_INNER_ERROR("E19999", "Get bin_file for op:%s(%s) fail.", op_desc->GetName().c_str(),
  3375. op_desc->GetType().c_str());
  3376. GELOGE(INTERNAL_ERROR, "[Check][Param] TBE: %s can't find bin file keys, size is %zu when ffts",
  3377. op_desc->GetName().c_str(), bin_file_keys.size());
  3378. return INTERNAL_ERROR;
  3379. }
  3380. GE_CHK_STATUS_RET(FunctionRegister(op_desc, bin_file_keys[kNonTailBlock], tbe_kernel[kNonTailBlock], true,
  3381. kNonTailBlock),
  3382. "Function register of first bin file %s failed.", bin_file_keys[kNonTailBlock].c_str());
  3383. GE_CHK_STATUS_RET(FunctionRegister(op_desc, bin_file_keys[kTailBlock], tbe_kernel[kTailBlock], true, kTailBlock),
  3384. "Function register of second bin file %s failed.", bin_file_keys[kTailBlock].c_str());
  3385. return SUCCESS;
  3386. }
  3387. Status DavinciModel::FunctionRegister(const OpDescPtr &op_desc, string &bin_file, OpKernelBinPtr &tbe_kernel,
  3388. bool is_ffts, size_t thread_index) {
  3389. if (thread_index > 1) {
  3390. GELOGE(INTERNAL_ERROR, "[Check][Param] failed. Thread index: %zu should less than 1.", thread_index);
  3391. return INTERNAL_ERROR;
  3392. }
  3393. const char *bin_file_key;
  3394. if (is_ffts) {
  3395. bin_file_key = GetRegisterStub(bin_file, "");
  3396. GELOGI("Node:%s inherit func name:%s directly.", op_desc->GetName().c_str(), bin_file_key);
  3397. } else {
  3398. std::string session_graph_model_id;
  3399. GetUniqueId(op_desc, session_graph_model_id);
  3400. bin_file_key = GetRegisterStub(bin_file, session_graph_model_id); // from set, always valid.
  3401. }
  3402. TBEHandleStore &kernel_store = TBEHandleStore::GetInstance();
  3403. std::lock_guard<std::mutex> lock(tvm_bin_mutex_);
  3404. if (rtQueryFunctionRegistered(bin_file_key) != RT_ERROR_NONE) {
  3405. void *bin_handle = nullptr;
  3406. if (!kernel_store.FindTBEHandle(bin_file_key, bin_handle)) {
  3407. GELOGD("TBE: can't find the kernel_name[%s] in HandleMap", bin_file_key);
  3408. rtDevBinary_t binary;
  3409. GE_CHK_STATUS_RET(InitBinaryMagic(op_desc, is_ffts, thread_index, binary), "Init binary magic of %s failed.",
  3410. op_desc->GetName().c_str());
  3411. binary.version = 0;
  3412. binary.data = tbe_kernel->GetBinData();
  3413. binary.length = tbe_kernel->GetBinDataSize();
  3414. GELOGD("TBE: binary.length: %lu", binary.length);
  3415. GE_CHK_RT_RET(rtDevBinaryRegister(&binary, &bin_handle));
  3416. GE_CHK_STATUS_RET(InitMetaData(op_desc, is_ffts, thread_index, bin_handle), "Init tvm meta data of %s failed.",
  3417. op_desc->GetName().c_str());
  3418. kernel_store.StoreTBEHandle(bin_file_key, bin_handle, tbe_kernel);
  3419. } else {
  3420. GELOGI("TBE: find the kernel_name[%s] in HandleMap", bin_file_key);
  3421. kernel_store.ReferTBEHandle(bin_file_key);
  3422. }
  3423. std::string kernel_name;
  3424. GE_CHK_STATUS_RET(InitKernelName(op_desc, is_ffts, thread_index, kernel_name), "Init kernel name of %s failed.",
  3425. op_desc->GetName().c_str());
  3426. GE_CHK_RT_RET(rtFunctionRegister(bin_handle, bin_file_key, bin_file_key, kernel_name.c_str(), 0));
  3427. used_tbe_handle_map_[bin_file_key] = 1; // Init used num to 1.
  3428. return SUCCESS;
  3429. }
  3430. // Kernel registed, Increase used num in store.
  3431. StoreTbeHandle(bin_file_key);
  3432. return SUCCESS;
  3433. }
  3434. Status DavinciModel::InitBinaryMagic(const OpDescPtr &op_desc, bool is_ffts, size_t thread_index,
  3435. rtDevBinary_t &binary) {
  3436. string json_string;
  3437. const string &tvm_magic = is_ffts ? TVM_ATTR_NAME_THREAD_MAGIC : TVM_ATTR_NAME_MAGIC;
  3438. const static std::map<std::string, uint32_t> binary_magics = {
  3439. {"RT_DEV_BINARY_MAGIC_ELF_AICPU", RT_DEV_BINARY_MAGIC_ELF_AICPU},
  3440. {"RT_DEV_BINARY_MAGIC_ELF", RT_DEV_BINARY_MAGIC_ELF},
  3441. {"RT_DEV_BINARY_MAGIC_ELF_AIVEC", RT_DEV_BINARY_MAGIC_ELF_AIVEC},
  3442. {"RT_DEV_BINARY_MAGIC_ELF_AICUBE", RT_DEV_BINARY_MAGIC_ELF_AICUBE}
  3443. };
  3444. if (is_ffts) {
  3445. vector<string> json_list;
  3446. (void)AttrUtils::GetListStr(op_desc, tvm_magic, json_list);
  3447. if (json_list.size() != kFftsTbeHandleElementSize) {
  3448. GELOGE(INTERNAL_ERROR, "[Check][Param] failed. Attr is %s, thread index is %zu, json list size is %zu.",
  3449. tvm_magic.c_str(), thread_index, json_list.size());
  3450. return INTERNAL_ERROR;
  3451. }
  3452. json_string = json_list[thread_index];
  3453. } else {
  3454. (void)AttrUtils::GetStr(op_desc, tvm_magic, json_string);
  3455. }
  3456. auto iter = binary_magics.find(json_string);
  3457. if (iter == binary_magics.end()) {
  3458. REPORT_INNER_ERROR("E19999", "Attr:%s value:%s in op:%s(%s), model_id:%u, check invalid",
  3459. tvm_magic.c_str(), json_string.c_str(), op_desc->GetName().c_str(),
  3460. op_desc->GetType().c_str(), model_id_);
  3461. GELOGE(PARAM_INVALID, "[Check][Param] Attr:%s value:%s in op:%s(%s), model_id:%u, check invalid",
  3462. TVM_ATTR_NAME_MAGIC.c_str(), json_string.c_str(),
  3463. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3464. return PARAM_INVALID;
  3465. }
  3466. binary.magic = iter->second;
  3467. return SUCCESS;
  3468. }
  3469. Status DavinciModel::InitMetaData(const OpDescPtr &op_desc, bool is_ffts, size_t thread_index, void *bin_handle) {
  3470. string meta_data;
  3471. const string &tvm_metadata = is_ffts ? TVM_ATTR_NAME_THREAD_METADATA : TVM_ATTR_NAME_METADATA;
  3472. if (is_ffts) {
  3473. vector<string> meta_data_list;
  3474. (void)AttrUtils::GetListStr(op_desc, tvm_metadata, meta_data_list);
  3475. if (meta_data_list.size() != kFftsTbeHandleElementSize) {
  3476. GELOGE(INTERNAL_ERROR, "[Check][Param] failed, attr is %s, thread index is %zu, meta data list size is %zu.",
  3477. tvm_metadata.c_str(), thread_index, meta_data_list.size());
  3478. return INTERNAL_ERROR;
  3479. }
  3480. meta_data = meta_data_list[thread_index];
  3481. } else {
  3482. (void)AttrUtils::GetStr(op_desc, tvm_metadata, meta_data);
  3483. }
  3484. GELOGD("TBE: meta data: %s", meta_data.empty() ? "null" : meta_data.c_str());
  3485. if (!meta_data.empty()) {
  3486. GE_CHK_RT_RET(rtMetadataRegister(bin_handle, meta_data.c_str()));
  3487. }
  3488. return SUCCESS;
  3489. }
  3490. Status DavinciModel::InitKernelName(const OpDescPtr &op_desc, bool is_ffts, size_t thread_index, string &kernel_name) {
  3491. if (is_ffts) {
  3492. // delete prefix, eg: *sgt_graph_nodes*/loss_scale/gradient/fp32_vals/Mean_grad/Tile
  3493. vector<string> kernel_name_list;
  3494. auto pos = op_desc->GetName().find("/");
  3495. if (pos == std::string::npos) {
  3496. GELOGE(INTERNAL_ERROR, "[Check][Param] failed, subgraph node name: %s.", op_desc->GetName().c_str());
  3497. return INTERNAL_ERROR;
  3498. }
  3499. string attr_kernel_name = op_desc->GetName().substr(pos + 1) + "_thread_kernelname";
  3500. (void)AttrUtils::GetListStr(op_desc, attr_kernel_name, kernel_name_list);
  3501. if (kernel_name_list.size() != kFftsTbeHandleElementSize) {
  3502. GELOGE(INTERNAL_ERROR, "[Check][Param] failed, attr is %s, thread index is %zu, kernel name list size is %zu.",
  3503. attr_kernel_name.c_str(), thread_index, kernel_name_list.size());
  3504. return INTERNAL_ERROR;
  3505. }
  3506. kernel_name = kernel_name_list[thread_index];
  3507. } else {
  3508. string attr_kernel_name = op_desc->GetName() + "_kernelname";
  3509. (void)AttrUtils::GetStr(op_desc, attr_kernel_name, kernel_name);
  3510. }
  3511. return SUCCESS;
  3512. }
  3513. void DavinciModel::StoreTbeHandle(const std::string &handle_key) {
  3514. // Online mode FE may call rtFunctionRegister.
  3515. TBEHandleStore &kernel_store = TBEHandleStore::GetInstance();
  3516. auto it = used_tbe_handle_map_.find(handle_key);
  3517. if (it != used_tbe_handle_map_.end()) {
  3518. // GE registered, increase reference.
  3519. kernel_store.ReferTBEHandle(handle_key);
  3520. it->second++;
  3521. return;
  3522. }
  3523. void *bin_handle = nullptr;
  3524. if (kernel_store.FindTBEHandle(handle_key, bin_handle)) {
  3525. // GE registered, increase reference.
  3526. used_tbe_handle_map_[handle_key] = 1; // Init used num to 1.
  3527. kernel_store.ReferTBEHandle(handle_key);
  3528. }
  3529. }
  3530. void DavinciModel::CleanTbeHandle() {
  3531. TBEHandleStore &kernel_store = TBEHandleStore::GetInstance();
  3532. kernel_store.EraseTBEHandle(used_tbe_handle_map_);
  3533. used_tbe_handle_map_.clear();
  3534. tvm_bin_kernel_.clear();
  3535. }
  3536. ///
  3537. /// @ingroup ge
  3538. /// @brief insert active_stream_indication_
  3539. /// @return Status
  3540. ///
  3541. Status DavinciModel::InitStreamActive(const OpDescPtr &op_desc) {
  3542. if (op_desc->HasAttr(ATTR_NAME_SWITCH_BRANCH_NODE_LABEL)) {
  3543. std::vector<uint32_t> active_stream_list;
  3544. GE_CHK_BOOL_EXEC(AttrUtils::GetListInt(op_desc, ATTR_NAME_ACTIVE_STREAM_LIST, active_stream_list),
  3545. REPORT_INNER_ERROR("E19999", "[Get][Attr] %s in op:%s(%s) failed, model_id:%u.",
  3546. ATTR_NAME_ACTIVE_STREAM_LIST.c_str(),
  3547. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3548. return INTERNAL_ERROR,
  3549. "[Get][Attr] %s in op:%s(%s) failed, model_id:%u.", ATTR_NAME_ACTIVE_STREAM_LIST.c_str(),
  3550. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3551. for (size_t j = 0; j < active_stream_list.size(); ++j) {
  3552. active_stream_indication_.insert(active_stream_list[j]);
  3553. GELOGI("flowctrl_op_index_map node:%s, active_stream_id=%u.", op_desc->GetName().c_str(), active_stream_list[j]);
  3554. }
  3555. }
  3556. return SUCCESS;
  3557. }
  3558. Status DavinciModel::InitStreamSwitch(const OpDescPtr &op_desc) {
  3559. std::vector<uint32_t> active_stream_list;
  3560. GE_LOGI_IF(!ge::AttrUtils::GetListInt(op_desc, ATTR_NAME_ACTIVE_STREAM_LIST, active_stream_list),
  3561. "GetInt ACTIVE_STREAM_LIST failed.");
  3562. if (active_stream_list.size() != kTrueBranchStreamNum) {
  3563. REPORT_INNER_ERROR("E19999", "Attr:%s active_stream_list.size:%zu in op:%s(%s) != kTrueBranchStreamNum:%u, "
  3564. "model_id:%u, check invalid",
  3565. ATTR_NAME_ACTIVE_STREAM_LIST.c_str(), active_stream_list.size(),
  3566. op_desc->GetName().c_str(), op_desc->GetType().c_str(),
  3567. kTrueBranchStreamNum, model_id_);
  3568. GELOGE(INTERNAL_ERROR, "[Check][Param] Attr:%s active_stream_list.size:%zu in op:%s(%s) != %u, model_id:%u",
  3569. ATTR_NAME_ACTIVE_STREAM_LIST.c_str(), active_stream_list.size(),
  3570. op_desc->GetName().c_str(), op_desc->GetType().c_str(), kTrueBranchStreamNum, model_id_);
  3571. return INTERNAL_ERROR;
  3572. }
  3573. uint32_t true_stream_id = active_stream_list.front();
  3574. active_stream_indication_.insert(true_stream_id);
  3575. GELOGI("flowctrl_op_index_map node:%s, true_stream_id=%u.", op_desc->GetName().c_str(), true_stream_id);
  3576. return SUCCESS;
  3577. }
  3578. Status DavinciModel::InitStreamSwitchN(const OpDescPtr &op_desc) {
  3579. std::vector<uint32_t> active_stream_list;
  3580. if (!AttrUtils::GetListInt(op_desc, ATTR_NAME_ACTIVE_STREAM_LIST, active_stream_list)) {
  3581. REPORT_INNER_ERROR("E19999", "Get Attr:%s from op:%s(%s) fail, model_id:%u", ATTR_NAME_ACTIVE_STREAM_LIST.c_str(),
  3582. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3583. GELOGE(INTERNAL_ERROR, "[Get][Attr] %s from op:%s(%s) fail, model_id:%u", ATTR_NAME_ACTIVE_STREAM_LIST.c_str(),
  3584. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3585. return INTERNAL_ERROR;
  3586. }
  3587. for (size_t j = 0; j < active_stream_list.size(); ++j) {
  3588. active_stream_indication_.insert(active_stream_list[j]);
  3589. GELOGI("StreamSwitchNOp node:%s, active_stream_id=%u.", op_desc->GetName().c_str(), active_stream_list[j]);
  3590. }
  3591. uint32_t batch_num = 0;
  3592. if (!AttrUtils::GetInt(op_desc, ATTR_NAME_BATCH_NUM, batch_num)) {
  3593. REPORT_INNER_ERROR("E19999", "Get Attr:%s from op:%s(%s) fail, model_id:%u", ATTR_NAME_BATCH_NUM.c_str(),
  3594. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3595. GELOGE(FAILED, "[Get][Attr] %s from op:%s(%s) fail, model_id:%u", ATTR_NAME_BATCH_NUM.c_str(),
  3596. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3597. return FAILED;
  3598. }
  3599. return SetDynamicBatchInfo(op_desc, batch_num);
  3600. }
  3601. Status DavinciModel::SetDynamicBatchInfo(const OpDescPtr &op_desc, uint32_t batch_num) {
  3602. batch_info_.clear();
  3603. combined_batch_info_.clear();
  3604. (void)AttrUtils::GetInt(op_desc, ATTR_DYNAMIC_TYPE, dynamic_type_);
  3605. (void)AttrUtils::GetListStr(op_desc, ATTR_USER_DESIGNEATE_SHAPE_ORDER, user_designate_shape_order_);
  3606. for (uint32_t i = 0; i < batch_num; ++i) {
  3607. std::vector<int64_t> batch_shape;
  3608. const std::string attr_name = ATTR_NAME_PRED_VALUE + "_" + std::to_string(i);
  3609. if (!AttrUtils::GetListInt(op_desc, attr_name, batch_shape)) {
  3610. REPORT_INNER_ERROR("E19999", "Get Attr:%s from op:%s(%s) fail, model_id:%u", attr_name.c_str(),
  3611. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3612. GELOGE(FAILED, "[Get][Attr] %s from op:%s(%s) fail, model_id:%u", attr_name.c_str(),
  3613. op_desc->GetName().c_str(), op_desc->GetType().c_str(), model_id_);
  3614. batch_info_.clear();
  3615. return FAILED;
  3616. }
  3617. batch_info_.emplace_back(batch_shape);
  3618. batch_shape.clear();
  3619. const string attr_combined_batch = ATTR_NAME_COMBINED_BATCH + "_" + std::to_string(i);
  3620. if (AttrUtils::GetListInt(op_desc, attr_combined_batch, batch_shape)) {
  3621. combined_batch_info_.emplace_back(batch_shape);
  3622. }
  3623. }
  3624. return SUCCESS;
  3625. }
  3626. Status DavinciModel::InitCase(const OpDescPtr &op_desc) {
  3627. uint32_t batch_num = 0;
  3628. if (!AttrUtils::GetInt(op_desc, ATTR_NAME_BATCH_NUM, batch_num)) {
  3629. GELOGI("Not multi-batch Node: %s", op_desc->GetName().c_str());
  3630. return SUCCESS;
  3631. }
  3632. return SetDynamicBatchInfo(op_desc, batch_num);
  3633. }
  3634. bool DavinciModel::IsBroadCastOpData(const ge::NodePtr &var_node) {
  3635. for (auto out_anchor : var_node->GetAllOutDataAnchors()) {
  3636. GE_RT_FALSE_CHECK_NOTNULL(out_anchor);
  3637. for (auto in_anchor : out_anchor->GetPeerInDataAnchors()) {
  3638. GE_RT_FALSE_CHECK_NOTNULL(in_anchor);
  3639. ge::NodePtr dst_node = in_anchor->GetOwnerNode();
  3640. GE_RT_FALSE_CHECK_NOTNULL(dst_node);
  3641. if (dst_node->GetType() == HCOMBROADCAST || dst_node->GetType() == HVDCALLBACKBROADCAST) {
  3642. return true;
  3643. }
  3644. }
  3645. }
  3646. return false;
  3647. }
  3648. ///
  3649. /// @ingroup ge
  3650. /// @brief Init model stream for NN model.
  3651. /// @param [in] stream user input model stream.
  3652. /// @return Status
  3653. ///
  3654. Status DavinciModel::InitModelStream(rtStream_t stream) {
  3655. ExecuteMode curr_mode = is_async_mode_ ? ASYNCHRONIZATION : SYNCHRONIZATION;
  3656. GE_CHK_BOOL_RET_STATUS((curr_mode == last_execute_mode_) || (last_execute_mode_ == INITIALIZATION), INTERNAL_ERROR,
  3657. "[Check][Param] NnExecute not support mix execute.");
  3658. last_execute_mode_ = curr_mode;
  3659. // asynchronize mode, use user input stream.
  3660. if (is_async_mode_) {
  3661. rt_model_stream_ = stream;
  3662. is_inner_model_stream_ = false;
  3663. return SUCCESS;
  3664. }
  3665. // synchronize mode, use forbidden stream.
  3666. if (stream != nullptr) {
  3667. if ((rt_model_stream_ != nullptr) && is_inner_model_stream_) {
  3668. GE_LOGW_IF(rtStreamDestroy(rt_model_stream_) != RT_ERROR_NONE, "Destroy rt_stream failed!");
  3669. }
  3670. rt_model_stream_ = stream;
  3671. is_inner_model_stream_ = false;
  3672. return SUCCESS;
  3673. }
  3674. if (rt_model_stream_ == nullptr) {
  3675. GE_CHK_RT_RET(rtStreamCreateWithFlags(&rt_model_stream_, priority_, RT_STREAM_FORBIDDEN_DEFAULT));
  3676. is_inner_model_stream_ = true;
  3677. }
  3678. return SUCCESS;
  3679. }
  3680. ///
  3681. /// @ingroup ge
  3682. /// @brief ACL case, do not start new thread, return execute result.
  3683. /// @param [in] stream execute model stream.
  3684. /// @param [in] async_mode is asynchronize mode.
  3685. /// @param [in] input_data model input data.
  3686. /// @param [out] output_data model output data.
  3687. ///
  3688. Status DavinciModel::NnExecute(rtStream_t stream, bool async_mode, const InputData &input_data,
  3689. OutputData &output_data) {
  3690. is_async_mode_ = async_mode;
  3691. GELOGD("Model Run begin, model id:%u, data index:%u, flag:%d.", model_id_, input_data.index, is_async_mode_);
  3692. GE_CHK_STATUS_RET(InitModelStream(stream), "[Init][ModelStream] failed, model_id:%u.", model_id_);
  3693. is_dynamic_ = input_data.is_dynamic_batch;
  3694. bool profiling_model_execute_on = ProfilingManager::Instance().ProfilingModelExecuteOn();
  3695. GE_IF_BOOL_EXEC(profiling_model_execute_on, SetProfileTime(MODEL_PRE_PROC_START));
  3696. Status ret = CopyModelData(input_data, output_data, is_dynamic_);
  3697. GE_CHK_BOOL_TRUE_EXEC_WITH_LOG(ret != SUCCESS, return ret,
  3698. "[Copy][ModelData] failed. model id: %u", model_id_);
  3699. GELOGD("current_data.index=%u", input_data.index);
  3700. GE_IF_BOOL_EXEC(profiling_model_execute_on, SetProfileTime(MODEL_PRE_PROC_END));
  3701. if (!task_list_.empty()) {
  3702. uint64_t index_id = iterator_count_ + 1;
  3703. uint64_t model_id = static_cast<uint64_t>(model_id_);
  3704. int32_t device_id = static_cast<int32_t>(device_id_);
  3705. // tag_id 0 means step begin, 1 meas step end.
  3706. GE_CHK_STATUS_RET_NOLOG(
  3707. ProfilingManager::Instance().ProfileStepInfo(index_id, model_id, 0, rt_model_stream_, device_id));
  3708. GELOGD("rtModelExecute do");
  3709. GE_IF_BOOL_EXEC(profiling_model_execute_on, SetProfileTime(MODEL_INFER_START));
  3710. rtError_t rt_ret = rtModelExecute(rt_model_handle_, rt_model_stream_, 0);
  3711. GE_CHK_RT_EXEC(rt_ret, return RT_ERROR_TO_GE_STATUS(rt_ret));
  3712. GE_IF_BOOL_EXEC(profiling_model_execute_on, SetProfileTime(MODEL_INFER_END));
  3713. GELOGD("rtModelExecute end");
  3714. GE_CHK_STATUS_RET_NOLOG(
  3715. ProfilingManager::Instance().ProfileStepInfo(index_id, model_id, 1, rt_model_stream_, device_id));
  3716. iterator_count_++;
  3717. }
  3718. GE_IF_BOOL_EXEC(profiling_model_execute_on, SetProfileTime(MODEL_AFTER_PROC_START));
  3719. ret = CopyOutputData(input_data.index, output_data, RT_MEMCPY_DEVICE_TO_DEVICE);
  3720. GE_CHK_BOOL_TRUE_EXEC_WITH_LOG(ret != SUCCESS, return ACL_ERROR_GE_INTERNAL_ERROR,
  3721. "[Copy][OutputData] to user failed, ret:%d, model_id:%u.", ret, model_id_);
  3722. GE_IF_BOOL_EXEC(profiling_model_execute_on, SetProfileTime(MODEL_AFTER_PROC_END));
  3723. // report model time data
  3724. GE_IF_BOOL_EXEC(profiling_model_execute_on, (void)SinkTimeProfile(input_data));
  3725. GELOGD("Model run end, model id:%u", model_id_);
  3726. return SUCCESS;
  3727. }
  3728. // Add active entry stream for special env.
  3729. Status DavinciModel::AddHeadStream() {
  3730. if (active_stream_list_.empty()) {
  3731. REPORT_INNER_ERROR("E19999", "active_stream_list is empty in model:%u, check invalid", model_id_);
  3732. GELOGE(INTERNAL_ERROR, "[Check][Param] active_stream_list is empty in model:%u, check invalid", model_id_);
  3733. return INTERNAL_ERROR;
  3734. }
  3735. if (active_stream_list_.size() == 1) {
  3736. GELOGI("Just one active stream, take as head stream.");
  3737. rt_head_stream_ = active_stream_list_[0];
  3738. is_pure_head_stream_ = false;
  3739. } else {
  3740. // Create stream which rt_model_handel running on, this is S0, TS stream.
  3741. GELOGI("Multiple active stream: %zu, create head stream.", active_stream_list_.size());
  3742. GE_CHK_RT_RET(rtStreamCreateWithFlags(&rt_head_stream_, priority_, RT_STREAM_PERSISTENT));
  3743. GE_CHK_RT_RET(rtModelBindStream(rt_model_handle_, rt_head_stream_, RT_INVALID_FLAG)); // Not active.
  3744. is_pure_head_stream_ = true;
  3745. for (auto s : active_stream_list_) {
  3746. std::shared_ptr<CpuTaskActiveEntry> active_entry = MakeShared<CpuTaskActiveEntry>(rt_head_stream_);
  3747. if (active_entry == nullptr) {
  3748. REPORT_CALL_ERROR("E19999", "New CpuTaskActiveEntry failed, model_id:%u", model_id_);
  3749. GELOGE(MEMALLOC_FAILED, "[New][CpuTaskActiveEntry] task failed, model_id:%u", model_id_);
  3750. return MEMALLOC_FAILED;
  3751. }
  3752. Status status = active_entry->Init(s);
  3753. if (status != SUCCESS) {
  3754. return status;
  3755. }
  3756. cpu_task_list_.emplace_back(active_entry);
  3757. }
  3758. }
  3759. // Create entry stream active head stream. AICPU stream.
  3760. GE_CHK_RT_RET(rtStreamCreateWithFlags(&rt_entry_stream_, priority_, RT_STREAM_AICPU));
  3761. GE_CHK_RT_RET(rtModelBindStream(rt_model_handle_, rt_entry_stream_, RT_HEAD_STREAM));
  3762. return SUCCESS;
  3763. }
  3764. Status DavinciModel::InitEntryTask() {
  3765. if (deploy_type_ == AICPU_DEPLOY_CROSS_THREAD) {
  3766. GE_CHK_STATUS_RET(AddHeadStream(), "[Add][HeadStream] failed.");
  3767. return CpuActiveStream();
  3768. } else {
  3769. return LoadWithQueue();
  3770. }
  3771. }
  3772. uint8_t *DavinciModel::MallocFeatureMapMem(size_t data_size) {
  3773. uint8_t *mem_base = nullptr;
  3774. const string purpose("feature map,used for op input and output.");
  3775. char ge_static_mem_env[MMPA_MAX_PATH] = {0x00};
  3776. INT32 res = mmGetEnv(kEnvGeuseStaticMemory, ge_static_mem_env, MMPA_MAX_PATH);
  3777. if (res == EN_OK) {
  3778. data_size = static_cast<size_t>(VarManager::Instance(session_id_)->GetGraphMemoryMaxSize());
  3779. string memory_key = std::to_string(0) + "_f";
  3780. mem_base =
  3781. MemManager::Instance().MemInstance(RT_MEMORY_HBM).MallocMemory(purpose, memory_key, data_size, GetDeviceId());
  3782. } else {
  3783. mem_base = MemManager::Instance().MemInstance(RT_MEMORY_HBM).MallocMemory(purpose, data_size, GetDeviceId());
  3784. }
  3785. if (mem_base != nullptr) {
  3786. GE_CHK_RT(rtMemset(mem_base, data_size, 0U, data_size));
  3787. }
  3788. return mem_base;
  3789. }
  3790. Status DavinciModel::MallocExMem() {
  3791. char ge_static_mem_env[MMPA_MAX_PATH] = {0x00};
  3792. INT32 res_static_memory = mmGetEnv(kEnvGeuseStaticMemory, ge_static_mem_env, MMPA_MAX_PATH);
  3793. for (auto &it : runtime_param_.memory_infos) {
  3794. auto mem_size = it.second.memory_size;
  3795. if (mem_size == 0) {
  3796. continue;
  3797. }
  3798. bool sessoion_scope = ((kSessionScopeMemory & it.first) == kSessionScopeMemory);
  3799. auto mem_type = it.first & kMemoryTypeMask;
  3800. uint8_t *mem_base = nullptr;
  3801. const string purpose("p2p memory, used for some op related to hcom or session scope memory");
  3802. if (sessoion_scope) {
  3803. mem_base = MemManager::Instance().SessionScopeMemInstance(mem_type).Malloc(mem_size, runtime_param_.session_id);
  3804. } else if (res_static_memory == EN_OK) {
  3805. string memory_key = std::to_string(0) + it.second.memory_key;
  3806. mem_base =
  3807. MemManager::Instance().MemInstance(mem_type).MallocMemory(purpose, memory_key, mem_size, GetDeviceId());
  3808. } else {
  3809. mem_base = MemManager::Instance().MemInstance(mem_type).MallocMemory(purpose, mem_size, GetDeviceId());
  3810. }
  3811. if (mem_base == nullptr) {
  3812. REPORT_CALL_ERROR("E19999", "MallocExMem fail, type:%ld size:%zu, model_id:%u, check invalid",
  3813. mem_type, mem_size, model_id_);
  3814. GELOGE(ACL_ERROR_GE_MEMORY_ALLOCATION, "Alloc ex memory failed, type:%ld size: %zu", mem_type, mem_size);
  3815. return ACL_ERROR_GE_MEMORY_ALLOCATION;
  3816. }
  3817. it.second.memory_base = mem_base;
  3818. GELOGI("InitFeatureMapAndP2PMem graph_%u MallocMemory type[F] mem_type[%ld] mem_addr[%p] mem_size[%zu]",
  3819. runtime_param_.graph_id, mem_type, mem_base, mem_size);
  3820. }
  3821. return SUCCESS;
  3822. }
  3823. uint8_t *DavinciModel::MallocWeightsMem(size_t weights_size) {
  3824. uint8_t *weights_mem_base = nullptr;
  3825. const string purpose("weights memory in inference network.");
  3826. char ge_static_mem_env[MMPA_MAX_PATH] = {0x00};
  3827. INT32 res = mmGetEnv(kEnvGeuseStaticMemory, ge_static_mem_env, MMPA_MAX_PATH);
  3828. if (res == EN_OK) {
  3829. string weight_memory_key = std::to_string(0) + "_w";
  3830. weights_mem_base = MemManager::Instance()
  3831. .MemInstance(RT_MEMORY_HBM)
  3832. .MallocMemory(purpose, weight_memory_key, weights_size, GetDeviceId());
  3833. } else {
  3834. weights_mem_base =
  3835. MemManager::Instance().MemInstance(RT_MEMORY_HBM).MallocMemory(purpose, weights_size, GetDeviceId());
  3836. }
  3837. return weights_mem_base;
  3838. }
  3839. void DavinciModel::FreeFeatureMapMem() {
  3840. char ge_static_mem_env[MMPA_MAX_PATH] = {0x00};
  3841. INT32 res = mmGetEnv(kEnvGeuseStaticMemory, ge_static_mem_env, MMPA_MAX_PATH);
  3842. if (res == EN_OK && is_inner_mem_base_) {
  3843. string weight_memory_key = std::to_string(0) + "_f";
  3844. if (MemManager::Instance().MemInstance(RT_MEMORY_HBM).GetMemoryAddr(weight_memory_key) != nullptr) {
  3845. GE_CHK_STATUS(MemManager::Instance().MemInstance(RT_MEMORY_HBM).FreeMemory(weight_memory_key, GetDeviceId()),
  3846. "failed to free weight memory");
  3847. }
  3848. mem_base_ = nullptr;
  3849. } else {
  3850. GE_IF_BOOL_EXEC(
  3851. mem_base_ != nullptr && is_inner_mem_base_,
  3852. GE_CHK_STATUS(MemManager::Instance().MemInstance(RT_MEMORY_HBM).FreeMemory(mem_base_, GetDeviceId()),
  3853. "failed to free feature_map memory");
  3854. mem_base_ = nullptr);
  3855. }
  3856. }
  3857. void DavinciModel::FreeExMem() {
  3858. char ge_static_mem_env[MMPA_MAX_PATH] = {0x00};
  3859. INT32 res_static_memory = mmGetEnv(kEnvGeuseStaticMemory, ge_static_mem_env, MMPA_MAX_PATH);
  3860. for (auto &it : runtime_param_.memory_infos) {
  3861. // free when session destory
  3862. if ((kSessionScopeMemory & it.first) == kSessionScopeMemory) {
  3863. continue;
  3864. }
  3865. auto mem_type = it.first & kMemoryTypeMask;
  3866. if (res_static_memory == EN_OK) {
  3867. std::string memory_key = std::to_string(0) + it.second.memory_key;
  3868. if (MemManager::Instance().MemInstance(mem_type).GetMemoryAddr(memory_key) != nullptr) {
  3869. GE_CHK_STATUS(MemManager::Instance().MemInstance(mem_type).FreeMemory(memory_key, GetDeviceId()),
  3870. "failed to free memory");
  3871. }
  3872. it.second.memory_base = nullptr;
  3873. } else {
  3874. GE_IF_BOOL_EXEC(
  3875. it.second.memory_base != nullptr,
  3876. GE_CHK_STATUS(MemManager::Instance().MemInstance(mem_type).FreeMemory(it.second.memory_base, GetDeviceId()),
  3877. "failed to free memory");
  3878. it.second.memory_base = nullptr);
  3879. }
  3880. }
  3881. }
  3882. void DavinciModel::FreeWeightsMem() {
  3883. char ge_static_mem_env[MMPA_MAX_PATH] = {0x00};
  3884. INT32 res = mmGetEnv(kEnvGeuseStaticMemory, ge_static_mem_env, MMPA_MAX_PATH);
  3885. if (res == EN_OK) {
  3886. string memory_key = std::to_string(0) + "_w";
  3887. if (MemManager::Instance().MemInstance(RT_MEMORY_HBM).GetMemoryAddr(memory_key) != nullptr) {
  3888. GE_CHK_STATUS(MemManager::Instance().MemInstance(RT_MEMORY_HBM).FreeMemory(memory_key, GetDeviceId()),
  3889. "failed to free feature_map memory");
  3890. }
  3891. weights_mem_base_ = nullptr;
  3892. } else {
  3893. GE_IF_BOOL_EXEC(
  3894. weights_mem_base_ != nullptr && weights_mem_base_ != mem_base_ && is_inner_weight_base_,
  3895. GE_CHK_STATUS(MemManager::Instance().MemInstance(RT_MEMORY_HBM).FreeMemory(weights_mem_base_, GetDeviceId()),
  3896. "failed to free weight memory");
  3897. weights_mem_base_ = nullptr);
  3898. }
  3899. }
  3900. Status DavinciModel::TransAllVarData(ComputeGraphPtr &graph, uint32_t graph_id) {
  3901. rtContext_t ctx = nullptr;
  3902. rtError_t rt_ret = rtCtxGetCurrent(&ctx);
  3903. if (rt_ret != RT_ERROR_NONE) {
  3904. REPORT_CALL_ERROR("E19999", "Call rtCtxGetCurrent failed, model_id:%u", model_id_);
  3905. GELOGE(RT_FAILED, "[Call][RtCtxGetCurrent] failed, ret:0x%X, model_id:%u.", rt_ret, model_id_);
  3906. return RT_ERROR_TO_GE_STATUS(rt_ret);
  3907. }
  3908. std::vector<NodePtr> variable_node_list;
  3909. for (ge::NodePtr &node : graph->GetAllNodes()) {
  3910. if (node == nullptr) {
  3911. continue;
  3912. }
  3913. if (node->GetType() != VARIABLE) {
  3914. continue;
  3915. }
  3916. variable_node_list.emplace_back(node);
  3917. }
  3918. GE_CHK_STATUS_RET_NOLOG(
  3919. TransVarDataUtils::TransAllVarData(variable_node_list, session_id_, ctx, graph_id, kThreadNum));
  3920. return SUCCESS;
  3921. }
  3922. void DavinciModel::SetDataDumperArgs(const ComputeGraphPtr &graph, const map<string, OpDescPtr> &variable_by_name) {
  3923. if(dump_model_name_.empty()) {
  3924. dump_model_name_ = name_;
  3925. }
  3926. data_dumper_.SetModelName(dump_model_name_);
  3927. data_dumper_.SetModelId(model_id_);
  3928. data_dumper_.SetOmName(om_name_);
  3929. data_dumper_.SetComputeGraph(graph);
  3930. data_dumper_.SetRefInfo(saved_task_addrs_);
  3931. int32_t device_id = 0;
  3932. rtError_t rt_ret = rtGetDevice(&device_id);
  3933. if (rt_ret != RT_ERROR_NONE || device_id < 0) {
  3934. REPORT_CALL_ERROR("E19999", "Call rtGetDevice failed, model_id:%u", model_id_);
  3935. GELOGE(RT_FAILED, "[Call][RtGetDevice] failed, ret = 0x%X, device_id = %d.", rt_ret, device_id);
  3936. return;
  3937. }
  3938. data_dumper_.SetDeviceId(device_id);
  3939. if (known_node_) {
  3940. data_dumper_.SetLoopAddr(global_step_addr_, nullptr, nullptr);
  3941. } else {
  3942. // set loop count addr
  3943. auto get_var_addr = [&](const string &name) -> void *{
  3944. const auto it = variable_by_name.find(name);
  3945. if (it != variable_by_name.end()) {
  3946. const auto output_sizes = ModelUtils::GetOutputSize(it->second);
  3947. const auto output_addrs = ModelUtils::GetOutputDataAddrs(runtime_param_, it->second);
  3948. if (output_sizes.empty() || output_addrs.empty()) {
  3949. return nullptr;
  3950. }
  3951. return output_addrs[0];
  3952. }
  3953. GELOGD("op: %s is null.", name.c_str());
  3954. return nullptr;
  3955. };
  3956. data_dumper_.SetLoopAddr(get_var_addr(NODE_NAME_GLOBAL_STEP),
  3957. get_var_addr(NODE_NAME_FLOWCTRL_LOOP_PER_ITER),
  3958. get_var_addr(NODE_NAME_FLOWCTRL_LOOP_COND));
  3959. }
  3960. }
  3961. uint32_t DavinciModel::GetFlowctrlIndex(uint32_t op_index) {
  3962. std::lock_guard<std::mutex> lock(flowctrl_op_index_internal_map_mutex_);
  3963. return (++flowctrl_op_index_internal_map_[op_index]) - 1;
  3964. }
  3965. void DavinciModel::PushHcclStream(rtStream_t value) {
  3966. std::lock_guard<std::mutex> lock(all_hccl_stream_list_mutex_);
  3967. all_hccl_stream_list_.push_back(value);
  3968. }
  3969. void DavinciModel::SaveHcclFollowStream(int64_t main_stream_id, rtStream_t stream) {
  3970. std::lock_guard<std::mutex> lock(capacity_of_stream_mutex_);
  3971. main_follow_stream_mapping_[main_stream_id].emplace_back(stream);
  3972. }
  3973. void DavinciModel::SetTotalFixedAddrsSize(string tensor_name, int64_t fix_addr_size) {
  3974. if (tensor_name_to_fixed_addr_size_.find(tensor_name) == tensor_name_to_fixed_addr_size_.end()) {
  3975. tensor_name_to_fixed_addr_size_[tensor_name] = total_fixed_addr_size_;
  3976. total_fixed_addr_size_ += fix_addr_size;
  3977. }
  3978. }
  3979. Status DavinciModel::InitOrigInputInfo(uint32_t index, const OpDescPtr &op_desc) {
  3980. if (!op_desc->HasAttr(ATTR_NAME_AIPP_INPUTS) || !op_desc->HasAttr(ATTR_NAME_AIPP_OUTPUTS)) {
  3981. GELOGI("there is not AIPP related with index %u, node: %s.", index, op_desc->GetName().c_str());
  3982. return SUCCESS;
  3983. }
  3984. vector<string> inputs;
  3985. if (AttrUtils::GetListStr(op_desc, ATTR_NAME_AIPP_INPUTS, inputs) && !inputs.empty()) {
  3986. std::string input = inputs[kAippOriginInputIndex];
  3987. GELOGI("origin input str: %s.", input.c_str());
  3988. std::vector<std::string> infos = ge::StringUtils::Split(input, ':');
  3989. if (infos.size() != kAippInfoNum) {
  3990. REPORT_INNER_ERROR("E19999", "Attr:%s in op:%s(%s), aipp input size:%zu != kAippInfoNum:%u, model_id:%u, "
  3991. "check invalid", ATTR_NAME_AIPP_INPUTS.c_str(),
  3992. op_desc->GetName().c_str(), op_desc->GetType().c_str(), infos.size(), kAippInfoNum,
  3993. model_id_);
  3994. GELOGE(ACL_ERROR_GE_AIPP_MODE_INVALID, "[Check][Param] Attr:%s in op:%s(%s), "
  3995. "aipp input size:%zu != kAippInfoNum:%u, model_id:%u", ATTR_NAME_AIPP_INPUTS.c_str(),
  3996. op_desc->GetName().c_str(), op_desc->GetType().c_str(), infos.size(), kAippInfoNum, model_id_);
  3997. return ACL_ERROR_GE_AIPP_MODE_INVALID;
  3998. }
  3999. OriginInputInfo input_info;
  4000. input_info.format = TypeUtils::SerialStringToFormat(infos[kAippInfoFormat]);
  4001. input_info.data_type = TypeUtils::SerialStringToDataType(infos[kAippInfoDataType]);
  4002. input_info.dim_num = std::strtol(infos[kAippInfoDimNum].c_str(), nullptr, kDecimal);
  4003. orig_input_info_[index] = input_info;
  4004. } else {
  4005. OriginInputInfo input_info = { FORMAT_RESERVED, DT_UNDEFINED, 0 };
  4006. orig_input_info_[index] = input_info;
  4007. }
  4008. return SUCCESS;
  4009. }
  4010. Status DavinciModel::GetOrigInputInfo(uint32_t index, OriginInputInfo &orig_input_info) const {
  4011. const auto it = orig_input_info_.find(index);
  4012. if (it == orig_input_info_.end()) {
  4013. REPORT_INNER_ERROR("E19999", "Get index:%u from orig_input_info_ fail, model_id:%u", index, model_id_);
  4014. GELOGE(ACL_ERROR_GE_AIPP_NOT_EXIST, "[Check][Param] Get index:%u from orig_input_info_ fail, model_id:%u",
  4015. index, model_id_);
  4016. return ACL_ERROR_GE_AIPP_NOT_EXIST;
  4017. }
  4018. const OriginInputInfo &input_info = it->second;
  4019. if (input_info.format != FORMAT_RESERVED || input_info.data_type != DT_UNDEFINED) {
  4020. orig_input_info = input_info;
  4021. }
  4022. return SUCCESS;
  4023. }
  4024. void DavinciModel::ParseAIPPInfo(std::string in_out_info, InputOutputDims &dims_info) {
  4025. GELOGI("ParseAIPPInfo: origin str: %s", in_out_info.c_str());
  4026. std::vector<std::string> infos = ge::StringUtils::Split(in_out_info, ':');
  4027. if (infos.size() != kAippInfoNum) {
  4028. REPORT_INNER_ERROR("E19999", "in_out_info:%s size:%zu != kAippInfoNum:%u, model_id:%u, "
  4029. "check invalid", in_out_info.c_str(), infos.size(), kAippInfoNum,
  4030. model_id_);
  4031. GELOGE(ACL_ERROR_GE_AIPP_MODE_INVALID, "[Check][Param] in_out_info:%s size:%zu != kAippInfoNum:%u, model_id:%u",
  4032. in_out_info.c_str(), infos.size(), kAippInfoNum, model_id_);
  4033. return;
  4034. }
  4035. dims_info.name = infos[kAippInfoTensorName];
  4036. dims_info.size = std::strtol(infos[kAippInfoTensorSize].c_str(), nullptr, kDecimal);
  4037. dims_info.dim_num = std::strtol(infos[kAippInfoDimNum].c_str(), nullptr, kDecimal);
  4038. std::vector<std::string> dims = ge::StringUtils::Split(infos[kAippInfoShape], ',');
  4039. for (const auto &dim : dims) {
  4040. if (dim.empty()) {
  4041. continue;
  4042. }
  4043. dims_info.dims.emplace_back(std::strtol(dim.c_str(), nullptr, kDecimal));
  4044. }
  4045. }
  4046. Status DavinciModel::InitAippInputOutputDims(uint32_t index, const OpDescPtr &op_desc) {
  4047. if (!op_desc->HasAttr(ATTR_NAME_AIPP_INPUTS) || !op_desc->HasAttr(ATTR_NAME_AIPP_OUTPUTS)) {
  4048. GELOGI("There is not AIPP related with index %u.", index);
  4049. return SUCCESS;
  4050. }
  4051. vector<string> inputs;
  4052. vector<InputOutputDims> input_dims;
  4053. if (AttrUtils::GetListStr(op_desc, ATTR_NAME_AIPP_INPUTS, inputs) && !inputs.empty()) {
  4054. GELOGI("Data: %s has %zu related aippInfo.", op_desc->GetName().c_str(), inputs.size());
  4055. for (auto it : inputs) {
  4056. InputOutputDims input_info;
  4057. ParseAIPPInfo(it, input_info);
  4058. input_dims.emplace_back(input_info);
  4059. GELOGD("Aipp origin input dims info: %s", it.c_str());
  4060. ConstGeTensorDescPtr data_input_desc = op_desc->GetInputDescPtr(kDataIndex);
  4061. int64_t data_input_size;
  4062. (void)TensorUtils::GetSize(*(op_desc->GetInputDescPtr(kDataIndex)), data_input_size);
  4063. GELOGD("Related Data[%d]: tensor_name: %s, dim_num: %zu, tensor_size: %zu, format: %s, data_type: %s, shape: %s.",
  4064. index, op_desc->GetName().c_str(), data_input_desc->GetShape().GetDimNum(), data_input_size,
  4065. TypeUtils::FormatToSerialString(data_input_desc->GetFormat()).c_str(),
  4066. TypeUtils::DataTypeToSerialString(data_input_desc->GetDataType()).c_str(),
  4067. formats::JoinToString(data_input_desc->GetShape().GetDims()).c_str());
  4068. }
  4069. }
  4070. vector<string> outputs;
  4071. vector<InputOutputDims> output_dims;
  4072. if (AttrUtils::GetListStr(op_desc, ATTR_NAME_AIPP_OUTPUTS, outputs) && !outputs.empty()) {
  4073. for (auto it : outputs) {
  4074. InputOutputDims output_info;
  4075. ParseAIPPInfo(it, output_info);
  4076. output_dims.emplace_back(output_info);
  4077. GELOGD("Aipp output dims info: %s", it.c_str());
  4078. }
  4079. }
  4080. aipp_dims_info_[index] = { input_dims, input_dims };
  4081. return SUCCESS;
  4082. }
  4083. Status DavinciModel::GetAllAippInputOutputDims(uint32_t index, vector<InputOutputDims> &input_dims,
  4084. vector<InputOutputDims> &output_dims) const {
  4085. const auto it = aipp_dims_info_.find(index);
  4086. if (it == aipp_dims_info_.end()) {
  4087. REPORT_INNER_ERROR("E19999", "Get index:%u from aipp_dims_info_ fail, model_id:%u", index, model_id_);
  4088. GELOGE(ACL_ERROR_GE_AIPP_NOT_EXIST, "[Check][Param] Get index:%u from aipp_dims_info_ fail, model_id:%u",
  4089. index, model_id_);
  4090. return ACL_ERROR_GE_AIPP_NOT_EXIST;
  4091. }
  4092. input_dims = it->second.first;
  4093. output_dims = it->second.second;
  4094. return SUCCESS;
  4095. }
  4096. int64_t DavinciModel::GetFixedAddrsSize(string tensor_name) {
  4097. if (tensor_name_to_fixed_addr_size_.find(tensor_name) != tensor_name_to_fixed_addr_size_.end()) {
  4098. return tensor_name_to_fixed_addr_size_[tensor_name];
  4099. } else {
  4100. return total_fixed_addr_size_;
  4101. }
  4102. }
  4103. Status DavinciModel::InitL1DataDumperArgs() {
  4104. auto all_dump_model = GetDumpProperties().GetAllDumpModel();
  4105. bool find_by_om_name = all_dump_model.find(om_name_) != all_dump_model.end();
  4106. bool find_by_model_name = all_dump_model.find(dump_model_name_) != all_dump_model.end();
  4107. bool dump_l1fusion_op =
  4108. (all_dump_model.find(ge::DUMP_ALL_MODEL) != all_dump_model.end()) || find_by_om_name || find_by_model_name;
  4109. if (dump_l1fusion_op) {
  4110. // malloc 2M for dump l1fusion op
  4111. GE_CHK_RT_RET(rtMalloc(&l1_fusion_addr_, kDumpL1FusionOpMByteSize, RT_MEMORY_DDR));
  4112. // send l1fusion dump addr to rts
  4113. if (rtDumpAddrSet(rt_model_handle_, l1_fusion_addr_, kDumpL1FusionOpMByteSize, kDumpFlagOfL1Fusion) !=
  4114. RT_ERROR_NONE) {
  4115. // l1_fusion_addr_ will be free when DavinciModel destruct
  4116. REPORT_CALL_ERROR("E19999", "Call rtDumpAddrSet failed, model_id:%u", model_id_);
  4117. GELOGE(FAILED, "[Call][RtDumpAddrSet] failed, model_id:%u", model_id_);
  4118. return FAILED;
  4119. }
  4120. // set addr for l1 data dump
  4121. data_dumper_.SetL1FusionAddr(l1_fusion_addr_);
  4122. }
  4123. return SUCCESS;
  4124. }
  4125. Status DavinciModel::SetRunAsyncListenerCallback(const RunAsyncCallback &callback) {
  4126. auto listener = dynamic_cast<RunAsyncListener *>(listener_.get());
  4127. GE_CHECK_NOTNULL(listener);
  4128. listener->SetCallback(callback);
  4129. return SUCCESS;
  4130. }
  4131. void DavinciModel::UpdateOpIOAddrs(uint32_t task_id, uint32_t stream_id, const std::vector<void *> &io_addrs) {
  4132. if (fixed_mem_base_ == reinterpret_cast<uintptr_t>(mem_base_)) {
  4133. GELOGD("[Update][OpIOAddrs] No need to update op input output addr.");
  4134. return;
  4135. }
  4136. OpDescInfo *op_desc_info = exception_dumper_.MutableOpDescInfo(task_id, stream_id);
  4137. if (op_desc_info == nullptr) {
  4138. GELOGW("[Update][OpIOAddrs] Find op desc failed, task_id: %u, stream_id: %u.", task_id, stream_id);
  4139. return;
  4140. }
  4141. size_t input_size = op_desc_info->input_addrs.size();
  4142. size_t output_size = op_desc_info->output_addrs.size();
  4143. if (input_size + output_size != io_addrs.size()) {
  4144. GELOGW("[Update][OpIOAddrs] Op[%s] input size[%zu] and output size[%zu] is not equal to io addr size[%zu]",
  4145. op_desc_info->op_name.c_str(), input_size, output_size, io_addrs.size());
  4146. return;
  4147. }
  4148. vector<void *> input_addrs;
  4149. vector<void *> output_addrs;
  4150. for (size_t i = 0; i < io_addrs.size(); i++) {
  4151. if (i < input_size) {
  4152. input_addrs.emplace_back(GetRunAddress(io_addrs[i]));
  4153. } else {
  4154. output_addrs.emplace_back(GetRunAddress(io_addrs[i]));
  4155. }
  4156. }
  4157. op_desc_info->input_addrs = input_addrs;
  4158. op_desc_info->output_addrs = output_addrs;
  4159. GELOGD("[Update][OpIOAddrs] Op [%s] update input output addr success.", op_desc_info->op_name.c_str());
  4160. }
  4161. ///
  4162. /// @ingroup ge
  4163. /// @brief Get total useful size, in known subgraph, no need to allocate zero copy memory during initialization.
  4164. /// @param [in] total_useful_size: total mem size - zero copy size.
  4165. /// @return Status
  4166. ///
  4167. Status DavinciModel::GetTotalMemSizeExcludeZeroCopy(int64_t &total_useful_size) {
  4168. if (runtime_param_.mem_size < static_cast<uint64_t>(runtime_param_.zero_copy_size)) {
  4169. REPORT_CALL_ERROR("E19999", "total mem size[%lu] is less than zero copy size[%ld] ", runtime_param_.mem_size,
  4170. runtime_param_.zero_copy_size);
  4171. GELOGE(FAILED, "[Check][TotalMemSizeExcludeZeroCopy] failed, total mem size[%lu] is less than zero copy size[%ld]",
  4172. runtime_param_.mem_size, runtime_param_.zero_copy_size);
  4173. return FAILED;
  4174. }
  4175. total_useful_size = runtime_param_.mem_size - runtime_param_.zero_copy_size;
  4176. return SUCCESS;
  4177. }
  4178. } // 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