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hybrid_model_builder.cc 85 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 "hybrid/model/hybrid_model_builder.h"
  17. #include <algorithm>
  18. #include "common/math/math_util.h"
  19. #include "graph/ge_context.h"
  20. #include "graph/build/memory/var_mem_assign_util.h"
  21. #include "graph/debug/ge_attr_define.h"
  22. #include "graph/load/model_manager/model_utils.h"
  23. #include "graph/load/model_manager/model_manager.h"
  24. #include "graph/manager/graph_var_manager.h"
  25. #include "graph/manager/host_mem_manager.h"
  26. #include "graph/manager/trans_var_data_utils.h"
  27. #include "graph/manager/graph_mem_allocator.h"
  28. #include "graph/manager/host_mem_allocator.h"
  29. #include "graph/utils/graph_utils.h"
  30. #include "hybrid/common/npu_memory_allocator.h"
  31. #include "hybrid/node_executor/node_executor.h"
  32. namespace ge {
  33. namespace hybrid {
  34. using domi::LogTimeStampDef;
  35. using domi::TaskDef;
  36. namespace {
  37. const uint32_t kSubgraphIndex = 0U;
  38. const uint32_t kVarOutputIndex = 0U;
  39. const uint64_t kProfilingFpStartLogid = 1U;
  40. const uint64_t kProfilingBpEndLogid = 2U;
  41. const uint64_t kProfilingIterEndLogid = 65535U;
  42. const int kBytes = 8;
  43. const uint32_t kStringHeadElems = 2;
  44. const char *const kOwnerGraphIsUnknown = "OwnerGraphIsUnknown";
  45. const char *const kProfilingGraph = "ProfilingGraph";
  46. const char *const kProfilingFpNode = "ProfilingFpNode";
  47. const char *const kProfilingBpNode = "ProfilingBpNode";
  48. const char *const kProfilingEndNode = "ProfilingEndNode";
  49. const char *const kProfilingArNode = "ProfilingAllReduceNode";
  50. const char *const kEngineNameRts = "DNN_VM_RTS_OP_STORE";
  51. const char *const kForceInfershape = "_force_infershape_when_running";
  52. Status SetOutputNameAttr(ComputeGraph &graph) {
  53. vector<string> output_names;
  54. for (const auto &node : graph.GetDirectNode()) {
  55. auto op_desc = node->GetOpDesc();
  56. if (op_desc == nullptr) {
  57. continue;
  58. }
  59. auto op_type = op_desc->GetType();
  60. if (op_type == NETOUTPUT) {
  61. for (InDataAnchorPtr &in_data_anchor : node->GetAllInDataAnchors()) {
  62. const OutDataAnchorPtr &peer_out_anchor = in_data_anchor->GetPeerOutAnchor();
  63. GE_IF_BOOL_EXEC(peer_out_anchor == nullptr, continue);
  64. NodePtr in_node = peer_out_anchor->GetOwnerNode();
  65. GE_CHECK_NOTNULL(in_node);
  66. output_names.push_back(in_node->GetName());
  67. }
  68. }
  69. }
  70. GE_CHK_BOOL_EXEC(ge::AttrUtils::SetListStr(&graph, ATTR_MODEL_OUT_NODES_NAME, output_names),
  71. GELOGE(FAILED, "SetListStr of ATTR_MODEL_OUT_NODES_NAME failed.");
  72. return FAILED);
  73. return SUCCESS;
  74. }
  75. int64_t CalcVarSizeInBytes(const GeTensorDesc &desc) {
  76. int64_t var_size = 0;
  77. auto data_type = desc.GetDataType();
  78. if (data_type == DT_STRING) {
  79. (void) TensorUtils::GetSize(desc, var_size);
  80. return var_size;
  81. }
  82. if (TensorUtils::GetTensorMemorySizeInBytes(desc, var_size) != GRAPH_SUCCESS) {
  83. GELOGW("Failed to calc var data size");
  84. return -1;
  85. }
  86. return var_size;
  87. }
  88. Status CollectDependenciesForFusedGraph(NodeItem &node_item, std::set<OpDesc *> &data_ops) {
  89. for (const auto &node : node_item.fused_subgraph->nodes) {
  90. auto op_desc = node->GetOpDesc();
  91. GE_CHECK_NOTNULL(op_desc);
  92. const auto &depends = op_desc->GetOpInferDepends();
  93. if (depends.empty()) {
  94. continue;
  95. }
  96. for (auto &input_name : depends) {
  97. auto input_index = op_desc->GetInputIndexByName(input_name);
  98. auto src_node = NodeUtils::GetInDataNodeByIndex(*node, input_index);
  99. GE_CHECK_NOTNULL(src_node);
  100. auto src_op_desc = src_node->GetOpDesc();
  101. GE_CHECK_NOTNULL(src_op_desc);
  102. if (src_node->GetType() != DATA_TYPE) {
  103. GELOGE(UNSUPPORTED,
  104. "[%s::%s] Node in fused subgraph can only depend on Data nodes, but depend on %s",
  105. node_item.NodeName().c_str(),
  106. node->GetName().c_str(),
  107. src_node->GetType().c_str());
  108. return UNSUPPORTED;
  109. }
  110. data_ops.emplace(src_op_desc.get());
  111. }
  112. }
  113. return SUCCESS;
  114. }
  115. } // namespace
  116. HybridModelBuilder::HybridModelBuilder(HybridModel &hybrid_model)
  117. : hybrid_model_(hybrid_model), runtime_param_(hybrid_model.root_runtime_param_) {
  118. ge_root_model_ = hybrid_model_.ge_root_model_;
  119. }
  120. Status HybridModelBuilder::Build() {
  121. GE_CHK_STATUS_RET(ValidateParams(), "Failed to validate GeRootModel");
  122. hybrid_model_.model_name_ = ge_root_model_->GetRootGraph()->GetName();
  123. GELOGI("[%s] Start to build hybrid model.", GetGraphName());
  124. GE_CHK_STATUS_RET(InitRuntimeParams(), "[%s] Failed to InitRuntimeParams", GetGraphName());
  125. GE_CHK_STATUS_RET(RecoverGraphUnknownFlag(), "[%s] Failed to RecoverGraphUnknownFlag", GetGraphName());
  126. GE_CHK_STATUS_RET(IndexSpecialNodes(), "[%s] Failed to index nodes", GetGraphName());
  127. GE_CHK_STATUS_RET(IndexTaskDefs(), "[%s] Failed to index task defs", GetGraphName());
  128. GE_CHK_STATUS_RET(LoadGraph(), "[%s] Failed to load graph", GetGraphName());
  129. GE_CHK_STATUS_RET(AssignUninitializedConstantOps(), "[%s] Failed to assign uninitialized constants", GetGraphName());
  130. GE_CHK_STATUS_RET(TransAllVarData(), "[%s] Failed to trans all var data", GetGraphName());
  131. GE_CHK_STATUS_RET(CopyVarData(), "[%s] Failed to copy var data", GetGraphName());
  132. GE_CHK_STATUS_RET(InitModelMem(), "[%s] Failed to init memory", GetGraphName());
  133. GE_CHK_STATUS_RET(InitWeights(), "[%s] Failed to init weights", GetGraphName());
  134. GE_CHK_STATUS_RET(InitConstantOps(), "[%s] Failed to init constant op", GetGraphName());
  135. GE_CHK_STATUS_RET(InitVariableTensors(), "[%s] Failed to init variables", GetGraphName());
  136. GE_CHK_STATUS_RET(LoadTasks(), "[%s] Failed to load tasks", GetGraphName());
  137. GELOGI("[%s] Done building hybrid model successfully.", GetGraphName());
  138. return SUCCESS;
  139. }
  140. Status HybridModelBuilder::BuildForSingleOp() {
  141. GE_CHK_STATUS_RET(ValidateParams(), "Failed to validate GeRootModel");
  142. hybrid_model_.model_name_ = ge_root_model_->GetRootGraph()->GetName();
  143. GELOGI("[%s] Start to build hybrid model.", GetGraphName());
  144. auto ret = ge_root_model_->GetSubgraphInstanceNameToModel();
  145. const GeModelPtr ge_model = ret[ge_root_model_->GetRootGraph()->GetName()];
  146. GE_CHK_STATUS_RET(IndexTaskDefs(ge_root_model_->GetRootGraph(), ge_model),
  147. "[%s] Failed to index task defs", GetGraphName());
  148. GE_CHK_STATUS_RET(LoadGraph(), "[%s] Failed to load graph", GetGraphName());
  149. GE_CHK_STATUS_RET(InitWeights(), "[%s] Failed to init weights", GetGraphName());
  150. GE_CHK_STATUS_RET(LoadTasks(), "[%s] Failed to load tasks", GetGraphName());
  151. GELOGI("[%s] Done building hybrid model for single op successfully.", GetGraphName());
  152. return SUCCESS;
  153. }
  154. Status HybridModelBuilder::ValidateParams() {
  155. GE_CHECK_NOTNULL(ge_root_model_);
  156. GE_CHECK_NOTNULL(ge_root_model_->GetRootGraph());
  157. return SUCCESS;
  158. }
  159. Status HybridModelBuilder::BuildNodeItem(const NodePtr &node, NodeItem &node_item) {
  160. auto op_desc = node->GetOpDesc();
  161. GE_CHK_STATUS_RET(ParseForceInfershapeNodes(node, node_item),
  162. "[%s] Failed to parse force_infershape node.",
  163. node_item.NodeName().c_str());
  164. vector<string> dependencies = node->GetOpDesc()->GetOpInferDepends();
  165. GE_CHK_STATUS_RET(ParseDependentInputNodes(node_item, dependencies),
  166. "[%s] Failed to parse node dependencies.",
  167. node_item.NodeName().c_str());
  168. node_item.outputs.resize(node_item.num_outputs);
  169. for (int i = 0; i < node_item.num_outputs; ++i) {
  170. auto out_data_anchor = node->GetOutDataAnchor(i);
  171. if (out_data_anchor == nullptr) {
  172. GELOGE(INTERNAL_ERROR, "out anchor[%d] of node %s is nullptr", i, node->GetName().c_str());
  173. return INTERNAL_ERROR;
  174. }
  175. for (auto &dst_in_anchor: out_data_anchor->GetPeerInDataAnchors()) {
  176. auto dst_node = dst_in_anchor->GetOwnerNode();
  177. if (dst_node == nullptr) {
  178. GELOGW("dst node is nullptr. out anchor = %d", out_data_anchor->GetIdx());
  179. continue;
  180. }
  181. NodeItem *dst_node_item = nullptr;
  182. GE_CHK_STATUS_RET(GetOrCreateNodeItem(dst_node, &dst_node_item),
  183. "[%s] Failed to get or create node item.",
  184. dst_node->GetName().c_str());
  185. int canonical_index;
  186. GE_CHK_STATUS_RET(dst_node_item->GetCanonicalInputIndex(dst_in_anchor->GetIdx(), canonical_index),
  187. "[%s] Failed to canonical input index",
  188. dst_node->GetName().c_str());
  189. node_item.outputs[i].emplace_back(canonical_index, dst_node_item);
  190. }
  191. }
  192. GE_CHK_STATUS_RET_NOLOG(ResolveRefIo(node_item));
  193. return SUCCESS;
  194. }
  195. Status HybridModelBuilder::ResolveRefIo(NodeItem &node_item) {
  196. bool is_ref = false;
  197. auto &op_desc = *node_item.op_desc;
  198. (void) AttrUtils::GetBool(op_desc, ATTR_NAME_REFERENCE, is_ref);
  199. if (!is_ref) {
  200. return SUCCESS;
  201. }
  202. auto inputs = op_desc.GetAllInputName();
  203. auto outputs = op_desc.GetAllOutputName();
  204. for (auto &output : outputs) {
  205. for (auto &input : inputs) {
  206. if (input.first == output.first) {
  207. int input_idx;
  208. GE_CHK_STATUS_RET_NOLOG(node_item.GetCanonicalInputIndex(input.second, input_idx));
  209. auto output_idx = static_cast<int>(output.second);
  210. node_item.reuse_inputs[output_idx] = input_idx;
  211. GELOGD("[%s] Output[%d] reuse input[%d]", node_item.NodeName().c_str(), output_idx, input_idx);
  212. }
  213. }
  214. }
  215. return SUCCESS;
  216. }
  217. Status HybridModelBuilder::GetOrCreateNodeItem(const NodePtr &node, NodeItem **node_item) {
  218. auto &node_items = hybrid_model_.node_items_;
  219. auto it = node_items.find(node);
  220. if (it != node_items.end()) {
  221. *node_item = it->second.get();
  222. return SUCCESS;
  223. }
  224. std::unique_ptr<NodeItem> new_node;
  225. GE_CHK_STATUS_RET(NodeItem::Create(node, new_node), "Failed to create node item");
  226. GE_CHK_STATUS_RET_NOLOG(NodeExecutorManager::GetInstance().GetExecutor(*node, &new_node->node_executor));
  227. // we do not need L2 Buffer
  228. const char *const kIsFirstNode = "is_first_node";
  229. const char *const kIsLastNode = "is_last_node";
  230. (void) AttrUtils::SetBool(new_node->op_desc, kIsFirstNode, false);
  231. (void) AttrUtils::SetBool(new_node->op_desc, kIsLastNode, false);
  232. new_node->node_id = node_index;
  233. new_node->op_desc->SetId(node_index);
  234. node_index += 1;
  235. NodeExecutorManager::ExecutorType executor_type = NodeExecutorManager::GetInstance().ResolveExecutorType(*node);
  236. new_node->is_profiling_report = (executor_type == NodeExecutorManager::ExecutorType::AICORE) ||
  237. (executor_type == NodeExecutorManager::ExecutorType::AICPU_TF) ||
  238. (executor_type == NodeExecutorManager::ExecutorType::AICPU_CUSTOM);
  239. *node_item = new_node.get();
  240. node_items[node] = std::move(new_node);
  241. return SUCCESS;
  242. }
  243. Status HybridModelBuilder::ParseForceInfershapeNodes(const NodePtr &node, NodeItem &node_item) {
  244. auto op_desc = node->GetOpDesc();
  245. GE_CHECK_NOTNULL(op_desc);
  246. // not care result, if no this attr, stand for the op does not need force infershape
  247. (void)AttrUtils::GetBool(op_desc, kForceInfershape, node_item.is_need_force_infershape);
  248. GELOGD("node [%s] is need do infershape , flag is %d",
  249. op_desc->GetName().c_str(),
  250. node_item.is_need_force_infershape);
  251. return SUCCESS;
  252. }
  253. Status HybridModelBuilder::ParseDependentInputNodes(NodeItem &node_item, const std::vector<string> &dependencies) {
  254. std::set<NodePtr> dependent_input_nodes;
  255. auto &ge_node = node_item.node;
  256. bool is_hccl_op =
  257. NodeExecutorManager::GetInstance().ResolveExecutorType(*ge_node) == NodeExecutorManager::ExecutorType::HCCL;
  258. // The input tensors become valid after computation is done for parent nodes of type DEPEND_COMPUTE.
  259. // Wait for these parent nodes before execution.
  260. for (const auto &in_anchor : ge_node->GetAllInDataAnchors()) {
  261. const auto &peer_anchor = in_anchor->GetPeerOutAnchor();
  262. if (peer_anchor == nullptr) {
  263. GELOGD("[%s] Input[%d] do not have peer anchor", node_item.NodeName().c_str(), in_anchor->GetIdx());
  264. continue;
  265. }
  266. auto src_node = peer_anchor->GetOwnerNode();
  267. GE_CHECK_NOTNULL(src_node);
  268. auto src_node_item = MutableNodeItem(src_node);
  269. GE_CHECK_NOTNULL(src_node_item);
  270. if (is_hccl_op) {
  271. GELOGD("[%s] Add input data dependent node [%s] due to engine type is HCCL",
  272. node_item.NodeName().c_str(),
  273. src_node_item->NodeName().c_str());
  274. src_node_item->has_observer = true;
  275. node_item.dependents_for_execution.emplace_back(src_node);
  276. node_item.has_observer = true;
  277. for (auto &dst_node : ge_node->GetOutNodes()) {
  278. if (dst_node == nullptr) {
  279. continue;
  280. }
  281. NodeItem *dst_node_item = nullptr;
  282. GE_CHK_STATUS_RET_NOLOG(GetOrCreateNodeItem(dst_node, &dst_node_item));
  283. dst_node_item->dependents_for_execution.emplace_back(ge_node);
  284. }
  285. } else if (src_node_item->shape_inference_type == DEPEND_COMPUTE) {
  286. GELOGD("[%s] Add input data dependent node [%s] due to inference type = DEPEND_COMPUTE",
  287. node_item.NodeName().c_str(),
  288. src_node_item->NodeName().c_str());
  289. src_node_item->has_observer = true;
  290. node_item.dependents_for_execution.emplace_back(src_node);
  291. }
  292. if (src_node_item->shape_inference_type == DEPEND_SHAPE_RANGE) {
  293. GELOGD("[%s] Add input shape dependent node [%s] due to inference type = DEPEND_SHAPE_RANGE",
  294. node_item.NodeName().c_str(),
  295. src_node_item->NodeName().c_str());
  296. src_node_item->has_observer = true;
  297. dependent_input_nodes.emplace(src_node);
  298. }
  299. }
  300. // cond or branch need to be prepared before the execution of IF or CASE
  301. if (node_item.node_type == IF || node_item.node_type == STATELESSIF || node_item.node_type == CASE) {
  302. const auto &in_anchor = ge_node->GetInDataAnchor(0);
  303. GE_CHECK_NOTNULL(in_anchor);
  304. const auto &peer_anchor = in_anchor->GetPeerOutAnchor();
  305. GE_CHECK_NOTNULL(peer_anchor);
  306. auto src_node = peer_anchor->GetOwnerNode();
  307. GE_CHECK_NOTNULL(src_node);
  308. auto src_node_item = MutableNodeItem(src_node);
  309. GE_CHECK_NOTNULL(src_node_item);
  310. src_node_item->has_observer = true;
  311. node_item.dependents_for_execution.emplace_back(src_node);
  312. GELOGD("[%s] Dependent added from %s for control op's cond/branch",
  313. node_item.NodeName().c_str(),
  314. src_node_item->NodeName().c_str());
  315. }
  316. for (const auto &input_name : dependencies) {
  317. int input_index = node_item.op_desc->GetInputIndexByName(input_name);
  318. if (input_index < 0) {
  319. GELOGE(INTERNAL_ERROR,
  320. "[%s] Failed to get input index by name: %s",
  321. node_item.NodeName().c_str(),
  322. input_name.c_str());
  323. return INTERNAL_ERROR;
  324. }
  325. const auto &in_anchor = ge_node->GetInDataAnchor(input_index);
  326. GE_CHECK_NOTNULL(in_anchor);
  327. const auto &peer_out_anchor = in_anchor->GetPeerOutAnchor();
  328. GE_CHECK_NOTNULL(peer_out_anchor);
  329. const auto &src_node = peer_out_anchor->GetOwnerNode();
  330. GE_CHECK_NOTNULL(src_node);
  331. auto src_node_item = MutableNodeItem(src_node);
  332. src_node_item->to_const_output_id_list.emplace(peer_out_anchor->GetIdx());
  333. src_node_item->has_observer = true;
  334. dependent_input_nodes.emplace(src_node);
  335. GELOGD("[%s] Dependent added from output of [%s:%d]",
  336. node_item.NodeName().c_str(),
  337. src_node_item->NodeName().c_str(),
  338. peer_out_anchor->GetIdx());
  339. }
  340. for (const auto &dep_node : dependent_input_nodes) {
  341. node_item.dependents_for_shape_inference.emplace_back(dep_node);
  342. }
  343. GE_CHK_STATUS_RET(ParseDependentForFusedSubgraph(node_item));
  344. return SUCCESS;
  345. }
  346. Status HybridModelBuilder::ParseDependentForFusedSubgraph(NodeItem &node_item) {
  347. if (node_item.fused_subgraph == nullptr) {
  348. return SUCCESS;
  349. }
  350. std::set<OpDesc *> data_ops;
  351. GE_CHK_STATUS_RET_NOLOG(CollectDependenciesForFusedGraph(node_item, data_ops));
  352. for (auto &op_desc : data_ops) {
  353. uint32_t parent_index = 0;
  354. if (!AttrUtils::GetInt(*op_desc, ATTR_NAME_PARENT_NODE_INDEX, parent_index)) {
  355. GELOGE(INTERNAL_ERROR,
  356. "[%s] Failed to get attr [%s]",
  357. op_desc->GetName().c_str(),
  358. ATTR_NAME_PARENT_NODE_INDEX.c_str());
  359. return INTERNAL_ERROR;
  360. }
  361. const auto &in_anchor = node_item.node->GetInDataAnchor(parent_index);
  362. GE_CHECK_NOTNULL(in_anchor);
  363. const auto &peer_out_anchor = in_anchor->GetPeerOutAnchor();
  364. GE_CHECK_NOTNULL(peer_out_anchor);
  365. const auto &src_node = peer_out_anchor->GetOwnerNode();
  366. GE_CHECK_NOTNULL(src_node);
  367. NodeItem *src_node_item = nullptr;
  368. GE_CHK_STATUS_RET_NOLOG(GetOrCreateNodeItem(src_node, &src_node_item));
  369. op_desc->SetId(src_node_item->op_desc->GetId());
  370. GELOGD("[%s::%s] Node id was set to that of outer src node's, src_node = %s",
  371. node_item.NodeName().c_str(),
  372. op_desc->GetName().c_str(),
  373. src_node_item->NodeName().c_str());
  374. src_node_item->has_observer = true;
  375. src_node_item->to_const_output_id_list.emplace(peer_out_anchor->GetIdx());
  376. auto &depends = node_item.dependents_for_shape_inference;
  377. if (std::find(depends.begin(), depends.end(), src_node) == depends.end()) {
  378. depends.emplace_back(src_node);
  379. GELOGD("[%s] Dependent added from output of [%s:%d]",
  380. node_item.NodeName().c_str(),
  381. src_node_item->NodeName().c_str(),
  382. peer_out_anchor->GetIdx());
  383. }
  384. }
  385. return SUCCESS;
  386. }
  387. Status HybridModelBuilder::UpdateAnchorStatus(const NodePtr &node) {
  388. if (NodeUtils::SetAllAnchorStatus(node) != GRAPH_SUCCESS) {
  389. GELOGE(INTERNAL_ERROR, "[%s] NodeUtils::SetAllAnchorStatus failed.", node->GetName().c_str());
  390. return INTERNAL_ERROR;
  391. }
  392. for (auto &anchor : node->GetAllInDataAnchors()) {
  393. auto peer_anchor = anchor->GetPeerOutAnchor();
  394. if (peer_anchor == nullptr) {
  395. if (AnchorUtils::SetStatus(anchor, ANCHOR_SUSPEND) != GRAPH_SUCCESS) {
  396. GELOGE(INTERNAL_ERROR, "[%s] AnchorUtils::SetStatus failed.", node->GetName().c_str());
  397. return INTERNAL_ERROR;
  398. }
  399. } else if (peer_anchor->GetOwnerNode()->GetType() == CONSTANT) {
  400. if (AnchorUtils::SetStatus(anchor, ANCHOR_CONST) != GRAPH_SUCCESS) {
  401. GELOGE(INTERNAL_ERROR, "[%s] AnchorUtils::SetStatus failed.", node->GetName().c_str());
  402. return INTERNAL_ERROR;
  403. }
  404. } else {
  405. if (AnchorUtils::SetStatus(anchor, ANCHOR_DATA) != GRAPH_SUCCESS) {
  406. GELOGE(INTERNAL_ERROR, "[%s] AnchorUtils::SetStatus failed.", node->GetName().c_str());
  407. return INTERNAL_ERROR;
  408. }
  409. }
  410. }
  411. return SUCCESS;
  412. }
  413. Status HybridModelBuilder::DoUnlinkDataAnchors(const OutDataAnchorPtr &out_data_anchor,
  414. const InDataAnchorPtr &in_data_anchor) {
  415. GE_CHK_GRAPH_STATUS_RET(out_data_anchor->Unlink(in_data_anchor), "Failed to unlink %s:%d from %s:%d",
  416. out_data_anchor->GetOwnerNode()->GetName().c_str(),
  417. out_data_anchor->GetIdx(),
  418. in_data_anchor->GetOwnerNode()->GetName().c_str(),
  419. in_data_anchor->GetIdx());
  420. GELOGD("Succeeded in unlinking %s:%d from %s:%d",
  421. out_data_anchor->GetOwnerNode()->GetName().c_str(),
  422. out_data_anchor->GetIdx(),
  423. in_data_anchor->GetOwnerNode()->GetName().c_str(),
  424. in_data_anchor->GetIdx());
  425. return SUCCESS;
  426. }
  427. Status HybridModelBuilder::DoLinkDataAnchors(OutDataAnchorPtr &out_data_anchor, InDataAnchorPtr &in_data_anchor) {
  428. GE_CHK_GRAPH_STATUS_RET(out_data_anchor->LinkTo(in_data_anchor), "Failed to link %s:%d to %s:%d",
  429. out_data_anchor->GetOwnerNode()->GetName().c_str(),
  430. out_data_anchor->GetIdx(),
  431. in_data_anchor->GetOwnerNode()->GetName().c_str(),
  432. in_data_anchor->GetIdx());
  433. GELOGD("Succeeded in linking %s:%d to %s:%d",
  434. out_data_anchor->GetOwnerNode()->GetName().c_str(),
  435. out_data_anchor->GetIdx(),
  436. in_data_anchor->GetOwnerNode()->GetName().c_str(),
  437. in_data_anchor->GetIdx());
  438. return SUCCESS;
  439. }
  440. Status HybridModelBuilder::MergeInputNodes(ComputeGraph &graph) {
  441. const auto &wrapped_node = graph.GetParentNode();
  442. std::set<NodePtr> root_nodes;
  443. for (const auto &node : graph.GetDirectNode()) {
  444. GE_CHECK_NOTNULL(node);
  445. if (node->GetType() != DATA_TYPE) {
  446. if (node->GetInDataNodes().empty()) {
  447. root_nodes.emplace(node);
  448. }
  449. continue;
  450. }
  451. auto data_op_desc = node->GetOpDesc();
  452. GE_CHECK_NOTNULL(data_op_desc);
  453. uint32_t parent_index = 0;
  454. if (!AttrUtils::GetInt(data_op_desc, ATTR_NAME_PARENT_NODE_INDEX, parent_index)) {
  455. GELOGE(FAILED,
  456. "[%s] Failed to get attr [%s]",
  457. data_op_desc->GetName().c_str(),
  458. ATTR_NAME_PARENT_NODE_INDEX.c_str());
  459. return FAILED;
  460. }
  461. auto wrapped_node_in_anchor = wrapped_node->GetInDataAnchor(parent_index);
  462. GE_CHECK_NOTNULL(wrapped_node_in_anchor);
  463. auto src_out_anchor = wrapped_node_in_anchor->GetPeerOutAnchor();
  464. if (src_out_anchor == nullptr || src_out_anchor->GetOwnerNode() == nullptr) {
  465. continue;
  466. }
  467. wrapped_node_in_anchor->UnlinkAll();
  468. // link src to outputs of DataNode
  469. for (auto &out_data_anchor : node->GetAllOutDataAnchors()) {
  470. GE_CHECK_NOTNULL(out_data_anchor);
  471. for (auto &peer_in_data_anchor : out_data_anchor->GetPeerInDataAnchors()) {
  472. auto dst_node = peer_in_data_anchor->GetOwnerNode();
  473. GE_CHECK_NOTNULL(dst_node);
  474. root_nodes.emplace(dst_node);
  475. GE_CHK_STATUS_RET_NOLOG(DoUnlinkDataAnchors(out_data_anchor, peer_in_data_anchor));
  476. GE_CHK_STATUS_RET_NOLOG(DoLinkDataAnchors(src_out_anchor, peer_in_data_anchor));
  477. }
  478. }
  479. }
  480. // transfer in control edges to all root nodes
  481. for (auto &root_node : root_nodes) {
  482. auto in_nodes = root_node->GetInAllNodes();
  483. std::set<NodePtr> in_node_set(in_nodes.begin(), in_nodes.end());
  484. for (auto &in_control_node : wrapped_node->GetInControlNodes()) {
  485. if (in_node_set.count(in_control_node) == 0) {
  486. GELOGD("[%s] Restore control edge to [%s]", in_control_node->GetName().c_str(), root_node->GetName().c_str());
  487. GE_CHECK_NOTNULL(in_control_node->GetOutControlAnchor());
  488. (void) in_control_node->GetOutControlAnchor()->LinkTo(root_node->GetInControlAnchor());
  489. }
  490. }
  491. }
  492. wrapped_node->GetInControlAnchor()->UnlinkAll();
  493. return SUCCESS;
  494. }
  495. Status HybridModelBuilder::MergeNetOutputNode(ComputeGraph &graph) {
  496. const auto &parent_node = graph.GetParentNode();
  497. const NodePtr &net_output_node = graph.FindFirstNodeMatchType(NETOUTPUT);
  498. if (net_output_node == nullptr) {
  499. GELOGD("Graph has no netoutput no need to merge.");
  500. return SUCCESS;
  501. }
  502. const auto &net_output_desc = net_output_node->GetOpDesc();
  503. GE_CHECK_NOTNULL(net_output_desc);
  504. auto all_in_nodes = net_output_node->GetInAllNodes();
  505. auto all_out_nodes = parent_node->GetOutAllNodes();
  506. net_output_node->GetInControlAnchor()->UnlinkAll();
  507. parent_node->GetOutControlAnchor()->UnlinkAll();
  508. for (const auto &in_data_anchor : net_output_node->GetAllInDataAnchors()) {
  509. auto src_out_anchor = in_data_anchor->GetPeerOutAnchor();
  510. GE_CHECK_NOTNULL(src_out_anchor);
  511. GE_CHECK_NOTNULL(src_out_anchor->GetOwnerNode());
  512. GE_CHK_STATUS_RET_NOLOG(DoUnlinkDataAnchors(src_out_anchor, in_data_anchor));
  513. auto index = in_data_anchor->GetIdx();
  514. auto input_desc = net_output_desc->MutableInputDesc(index);
  515. if (input_desc == nullptr) {
  516. GELOGE(INTERNAL_ERROR, "[%s] Failed to get input desc[%d]", net_output_desc->GetName().c_str(), index);
  517. return INTERNAL_ERROR;
  518. }
  519. uint32_t parent_index = 0;
  520. if (!AttrUtils::GetInt(input_desc, ATTR_NAME_PARENT_NODE_INDEX, parent_index)) {
  521. GELOGW("SubGraph: %s NetOutput input tensor %d, attr %s not found.",
  522. graph.GetName().c_str(), index, ATTR_NAME_PARENT_NODE_INDEX.c_str());
  523. continue;
  524. }
  525. const OutDataAnchorPtr &parent_out_anchor = parent_node->GetOutDataAnchor(parent_index);
  526. GE_CHECK_NOTNULL(parent_out_anchor);
  527. for (InDataAnchorPtr &dst_in_anchor : parent_out_anchor->GetPeerInDataAnchors()) {
  528. if (dst_in_anchor == nullptr) {
  529. continue;
  530. }
  531. GE_CHECK_NOTNULL(dst_in_anchor->GetOwnerNode());
  532. GE_CHK_STATUS_RET_NOLOG(DoUnlinkDataAnchors(parent_out_anchor, dst_in_anchor));
  533. GE_CHK_STATUS_RET_NOLOG(DoLinkDataAnchors(src_out_anchor, dst_in_anchor));
  534. }
  535. }
  536. // transfer out control edges
  537. std::set<NodePtr> in_node_set(all_in_nodes.begin(), all_in_nodes.end());
  538. std::set<NodePtr> out_node_set(all_out_nodes.begin(), all_out_nodes.end());
  539. for (auto &src_node : in_node_set) {
  540. GELOGD("[%s] process in node.", src_node->GetName().c_str());
  541. auto out_nodes = src_node->GetOutAllNodes();
  542. std::set<NodePtr> node_set(out_nodes.begin(), out_nodes.end());
  543. for (auto &dst_node : out_node_set) {
  544. if (node_set.count(dst_node) == 0) {
  545. src_node->GetOutControlAnchor()->LinkTo(dst_node->GetInControlAnchor());
  546. GELOGD("[%s] Restore control edge to [%s]", src_node->GetName().c_str(), dst_node->GetName().c_str());
  547. }
  548. }
  549. }
  550. return SUCCESS;
  551. }
  552. Status HybridModelBuilder::UnfoldSubgraphs(ComputeGraph &root_graph, ComputeGraphPtr &merged_graph) {
  553. merged_graph = MakeShared<ComputeGraph>("MergedGraph");
  554. for (const auto &node : root_graph.GetDirectNode()) {
  555. GE_CHECK_NOTNULL(node);
  556. auto op_desc = node->GetOpDesc();
  557. GE_CHECK_NOTNULL(op_desc);
  558. const auto &op_type = node->GetType();
  559. if (op_type != PARTITIONEDCALL) {
  560. merged_graph->AddNode(node);
  561. GELOGD("[%s] Node added to merged graph.", op_desc->GetName().c_str());
  562. continue;
  563. }
  564. auto subgraph = NodeUtils::GetSubgraph(*node, kSubgraphIndex);
  565. GE_CHECK_NOTNULL(subgraph);
  566. bool is_unknown_shape = subgraph->GetGraphUnknownFlag();
  567. if (!is_unknown_shape) {
  568. merged_graph->AddNode(node);
  569. GELOGD("[%s] Known shape partitioned call added to merged graph.", op_desc->GetName().c_str());
  570. continue;
  571. }
  572. if (op_desc->HasAttr(ATTR_STAGE_LEVEL)) {
  573. uint32_t stage_level = UINT32_MAX;
  574. if (AttrUtils::GetInt(node->GetOpDesc(), ATTR_STAGE_LEVEL, stage_level)) {
  575. for (const auto &stage_node : subgraph->GetAllNodes()) {
  576. GELOGD("Set ATTR_STAGE_LEVEL on node %s, stage_level=%u", stage_node->GetName().c_str(), stage_level);
  577. (void)AttrUtils::SetInt(stage_node->GetOpDesc(), ATTR_STAGE_LEVEL, stage_level);
  578. }
  579. }
  580. }
  581. GE_CHK_GRAPH_STATUS_RET(UnfoldSubgraph(root_graph, *merged_graph, *subgraph),
  582. "[%s] Failed to merge subgraph.",
  583. subgraph->GetName().c_str());
  584. }
  585. // invoke before adding subgraphs. in case modify node id in known-shaped subgraphs.
  586. GE_CHK_GRAPH_STATUS_RET(merged_graph->TopologicalSorting(), "Failed to invoke TopologicalSorting on merged graph.");
  587. GE_DUMP(merged_graph, "hybrid_merged_graph_BeforeStageSort");
  588. merged_graph->TopologicalSorting([](const NodePtr &a, const NodePtr &b) -> bool {
  589. uint32_t a_level = UINT32_MAX;
  590. (void)AttrUtils::GetInt(a->GetOpDesc(), ATTR_STAGE_LEVEL, a_level);
  591. uint32_t b_level = UINT32_MAX;
  592. (void)AttrUtils::GetInt(b->GetOpDesc(), ATTR_STAGE_LEVEL, b_level);
  593. return a_level < b_level;
  594. });
  595. for (auto &remained_subgraph : root_graph.GetAllSubgraphs()) {
  596. GELOGD("Adding subgraph [%s] to merged-graph.", remained_subgraph->GetName().c_str());
  597. GE_CHK_GRAPH_STATUS_RET(merged_graph->AddSubgraph(remained_subgraph),
  598. "Failed to add subgraph [%s]",
  599. remained_subgraph->GetName().c_str());
  600. }
  601. return SUCCESS;
  602. }
  603. Status HybridModelBuilder::UnfoldSubgraph(ComputeGraph &root_graph,
  604. ComputeGraph &parent_graph,
  605. ComputeGraph &sub_graph) {
  606. auto parent_node = sub_graph.GetParentNode();
  607. GE_CHECK_NOTNULL(parent_node);
  608. GE_CHK_STATUS_RET(MergeInputNodes(sub_graph),
  609. "[%s] Failed to merge data nodes for subgraph",
  610. sub_graph.GetName().c_str());
  611. GE_CHK_STATUS_RET(MergeNetOutputNode(sub_graph),
  612. "[%s] Failed to merge net output nodes for subgraph",
  613. sub_graph.GetName().c_str());
  614. GELOGD("[%s] Done merging subgraph inputs and outputs successfully.", sub_graph.GetName().c_str());
  615. for (auto &sub_node : sub_graph.GetDirectNode()) {
  616. auto sub_op_type = sub_node->GetType();
  617. if (sub_op_type == DATA_TYPE || sub_op_type == NETOUTPUT) {
  618. continue;
  619. }
  620. if (sub_op_type == PARTITIONEDCALL) {
  621. auto sub_sub_graph = NodeUtils::GetSubgraph(*sub_node, kSubgraphIndex);
  622. GE_CHECK_NOTNULL(sub_sub_graph);
  623. if (sub_sub_graph->GetGraphUnknownFlag()) {
  624. GE_CHK_STATUS_RET(UnfoldSubgraph(root_graph, parent_graph, *sub_sub_graph),
  625. "[%s] Failed to merge subgraph",
  626. sub_sub_graph->GetName().c_str());
  627. continue;
  628. }
  629. }
  630. parent_graph.AddNode(sub_node);
  631. GELOGD("[%s::%s] added to parent graph: [%s].",
  632. sub_graph.GetName().c_str(),
  633. sub_node->GetName().c_str(),
  634. parent_graph.GetName().c_str());
  635. }
  636. GELOGD("[%s] Done merging subgraph. remove it from root graph.", sub_graph.GetName().c_str());
  637. root_graph.RemoveSubgraph(sub_graph.GetName());
  638. return SUCCESS;
  639. }
  640. Status HybridModelBuilder::BuildOutputMapping(GraphItem &graph_item,
  641. const NodeItem &node_item,
  642. bool is_root_graph) {
  643. auto output_size = node_item.num_inputs;
  644. graph_item.output_edges_.resize(output_size);
  645. for (auto &in_data_anchor : node_item.node->GetAllInDataAnchors()) {
  646. auto peer_out_anchor = in_data_anchor->GetPeerOutAnchor();
  647. GE_CHECK_NOTNULL(peer_out_anchor);
  648. auto src_node = peer_out_anchor->GetOwnerNode();
  649. GE_CHECK_NOTNULL(src_node);
  650. auto src_node_item = GetNodeItem(src_node);
  651. GE_CHECK_NOTNULL(src_node_item);
  652. auto output_idx = in_data_anchor->GetIdx();
  653. auto output_offset = src_node_item->output_start + peer_out_anchor->GetIdx();
  654. GELOGI("Output[%d], node = %s, output_index = %d, output_offset = %d ",
  655. output_idx,
  656. src_node_item->NodeName().c_str(),
  657. peer_out_anchor->GetIdx(),
  658. output_offset);
  659. GE_CHECK_LE(output_idx, output_size - 1);
  660. graph_item.output_edges_[output_idx] = {src_node_item, peer_out_anchor->GetIdx()};
  661. }
  662. if (!is_root_graph) {
  663. for (uint32_t i = 0; i < static_cast<uint32_t>(output_size); ++i) {
  664. uint32_t p_index = i;
  665. // Net output of Subgraph of while do not have parent index
  666. if (AttrUtils::GetInt(node_item.op_desc->GetInputDesc(i), ATTR_NAME_PARENT_NODE_INDEX, p_index)) {
  667. GELOGD("[%s] Parent index not set for input[%u].", node_item.NodeName().c_str(), i);
  668. }
  669. graph_item.output_index_mapping_.emplace_back(p_index);
  670. }
  671. }
  672. return SUCCESS;
  673. }
  674. Status HybridModelBuilder::LoadGraph() {
  675. auto root_graph = ge_root_model_->GetRootGraph();
  676. if (!GetContext().GetHostExecFlag()) {
  677. std::shared_ptr<ComputeGraph> merged_graph;
  678. GELOGI("Before merging subgraphs DirectNodesSize = %zu, GetAllNodesSize = %zu",
  679. root_graph->GetDirectNodesSize(),
  680. root_graph->GetAllNodesSize());
  681. GE_CHK_GRAPH_STATUS_RET(UnfoldSubgraphs(*root_graph, merged_graph), "Failed to unfold subgraphs.");
  682. root_graph = std::move(merged_graph);
  683. GELOGI("After merging subgraphs DirectNodesSize = %zu, GetAllNodesSize = %zu",
  684. root_graph->GetDirectNodesSize(),
  685. root_graph->GetAllNodesSize());
  686. GE_DUMP(root_graph, "hybrid_merged_graph");
  687. }
  688. GE_CHK_STATUS_RET(LoadDynamicSubgraph(*root_graph, true), "Failed to load root graph.");
  689. GELOGD("Done loading root graph successfully.");
  690. GE_CHK_STATUS_RET(hybrid_model_.root_graph_item_->GroupNodes(), "Failed to group nodes for root graph");
  691. for (auto &sub_graph : root_graph->GetAllSubgraphs()) {
  692. GE_CHECK_NOTNULL(sub_graph);
  693. GELOGD("Start to load subgraph [%s]", sub_graph->GetName().c_str());
  694. auto parent_node = sub_graph->GetParentNode();
  695. GE_CHECK_NOTNULL(parent_node);
  696. auto parent_node_item = MutableNodeItem(parent_node);
  697. // parent node is in another known subgraph
  698. if (parent_node_item == nullptr) {
  699. GELOGD("[%s] Subgraph is in another known shaped subgraph, skip it.", sub_graph->GetName().c_str());
  700. continue;
  701. }
  702. if (sub_graph->GetGraphUnknownFlag()) {
  703. GE_CHK_STATUS_RET(LoadDynamicSubgraph(*sub_graph, false),
  704. "Failed to load subgraph: [%s]",
  705. sub_graph->GetName().c_str());
  706. } else {
  707. GE_CHK_STATUS_RET(IdentifyVariableOutputs(*parent_node_item),
  708. "[%s] Failed to identify ref outputs.",
  709. parent_node_item->NodeName().c_str());
  710. GE_CHK_STATUS_RET(IdentifySameInputs(*parent_node_item),
  711. "[%s] Failed to identify same outputs.",
  712. parent_node_item->NodeName().c_str());
  713. // if parent is function control op. need add a virtual partitioned call
  714. if (parent_node_item->IsControlOp()) {
  715. GE_CHK_STATUS_RET(LoadKnownShapedSubgraph(*sub_graph, parent_node_item),
  716. "Failed to load function control op subgraph [%s]",
  717. sub_graph->GetName().c_str());
  718. }
  719. }
  720. }
  721. GELOGI("Done loading all subgraphs successfully.");
  722. return SUCCESS;
  723. }
  724. const NodeItem *HybridModelBuilder::GetNodeItem(const NodePtr &node) const {
  725. return hybrid_model_.GetNodeItem(node);
  726. }
  727. NodeItem *HybridModelBuilder::MutableNodeItem(const NodePtr &node) {
  728. return hybrid_model_.MutableNodeItem(node);
  729. }
  730. Status HybridModelBuilder::VarNodeToTensor(const NodePtr &var_node, std::unique_ptr<TensorValue> &tensor) {
  731. string var_name = var_node->GetName();
  732. auto tensor_desc = var_node->GetOpDesc()->MutableOutputDesc(0);
  733. uint8_t *var_logic = nullptr;
  734. GE_CHK_STATUS_RET(var_manager_->GetVarAddr(var_name, *tensor_desc, &var_logic),
  735. "Failed to get var addr. var_name = %s, session_id = %ld",
  736. var_name.c_str(),
  737. hybrid_model_.GetSessionId());
  738. rtMemType_t memory_type = RT_MEMORY_HBM;
  739. uint32_t mem_type = 0;
  740. if (AttrUtils::GetInt(var_node->GetOpDesc(), ATTR_OUTPUT_MEMORY_TYPE, mem_type) && (mem_type == 1)) {
  741. memory_type = RT_MEMORY_RDMA_HBM;
  742. }
  743. uint8_t *dev_mem = var_manager_->GetVarMemoryAddr(var_logic, memory_type);
  744. if (dev_mem == nullptr) {
  745. GELOGE(INTERNAL_ERROR,
  746. "Failed to copy var %s from device, cant not get "
  747. "var addr from logic addr %p",
  748. var_node->GetName().c_str(), var_logic);
  749. return INTERNAL_ERROR;
  750. }
  751. int64_t var_size = CalcVarSizeInBytes(*tensor_desc);
  752. // var size is only for checking, will not allocate any memory by it
  753. tensor.reset(new(std::nothrow)TensorValue(dev_mem, static_cast<size_t>(var_size)));
  754. GE_CHECK_NOTNULL(tensor);
  755. GELOGI("Get var memory addr %p for node %s, size = %ld, mem_type=%u", dev_mem, var_name.c_str(), var_size, mem_type);
  756. return SUCCESS;
  757. }
  758. Status HybridModelBuilder::HandleDtString(const GeTensor &tensor, void *var_addr) {
  759. auto desc = tensor.GetTensorDesc();
  760. if (desc.GetDataType() == DT_STRING) {
  761. GeShape tensor_shape = desc.GetShape();
  762. /// if tensor is a scaler, it's shape size if zero, according ge_tensor.cc.
  763. /// the logic of GetShapeSize is wrong, the scaler tensor's GetShapeSize is zero
  764. /// and that of unknown shape is zero too.
  765. /// unknown shape will not appear here, so we can use zero judge a tensor is scalar or not
  766. int64_t elem_num = tensor_shape.GetShapeSize();
  767. if (elem_num == 0 && tensor_shape.GetDims().empty()) {
  768. elem_num = 1;
  769. }
  770. auto &mutable_tensor = const_cast<GeTensor &>(tensor);
  771. uint64_t *buff = reinterpret_cast<uint64_t *>(mutable_tensor.MutableData().data());
  772. GE_CHK_BOOL_RET_STATUS(ge::CheckInt64Uint32MulOverflow(elem_num, kBytes * kStringHeadElems) == SUCCESS, FAILED,
  773. "Shape size is invalid");
  774. auto offset = static_cast<uint64_t>(elem_num * kBytes * kStringHeadElems);
  775. auto hbm_raw_data_base_addr =
  776. static_cast<uint64_t>(reinterpret_cast<uintptr_t>(var_addr) + offset);
  777. for (int64_t i = elem_num - 1; i >= 0; --i) {
  778. buff[i * kStringHeadElems] = hbm_raw_data_base_addr + (buff[i * kStringHeadElems] - buff[0]);
  779. }
  780. }
  781. return SUCCESS;
  782. }
  783. Status HybridModelBuilder::AssignUninitializedConstantOps() {
  784. if (GetContext().GetHostExecFlag()) {
  785. GELOGI("no need to assign when exec on host.");
  786. return SUCCESS;
  787. }
  788. for (auto &it : constant_op_nodes_) {
  789. const string &var_name = it.first;
  790. const NodePtr &var_node = it.second;
  791. auto tensor_desc = var_node->GetOpDesc()->MutableOutputDesc(0);
  792. if (!var_manager_->IsVarExist(var_name, *tensor_desc)) {
  793. // allocate constant
  794. GELOGD("[%s] Constant not allocated during graph building. now allocate it.", var_name.c_str());
  795. GE_CHK_STATUS_RET(var_manager_->AssignVarMem(var_name, *tensor_desc, RT_MEMORY_HBM));
  796. GE_CHK_STATUS_RET(var_manager_->SetAllocatedGraphId(var_name, runtime_param_.graph_id));
  797. }
  798. }
  799. for (auto &it : hybrid_model_.device_variable_nodes_) {
  800. const string &var_name = it.first;
  801. const NodePtr &var_node = it.second;
  802. auto tensor_desc = var_node->GetOpDesc()->MutableOutputDesc(0);
  803. if (!var_manager_->IsVarExist(var_name, *tensor_desc)) {
  804. // allocate constant
  805. GELOGD("[%s] Constant not allocated during graph building. now allocate it.", var_name.c_str());
  806. GE_CHK_STATUS_RET(var_manager_->AssignVarMem(var_name, *tensor_desc, RT_MEMORY_HBM));
  807. GE_CHK_STATUS_RET(VarMemAssignUtil::AssignData2Fp32Var(var_node, runtime_param_.session_id))
  808. GE_CHK_STATUS_RET(var_manager_->SetAllocatedGraphId(var_name, runtime_param_.graph_id));
  809. }
  810. }
  811. return SUCCESS;
  812. }
  813. Status HybridModelBuilder::InitConstantOps() {
  814. for (auto &it : constant_op_nodes_) {
  815. const string &var_name = it.first;
  816. const NodePtr &var_node = it.second;
  817. auto op_desc = var_node->GetOpDesc();
  818. auto v_weights = ModelUtils::GetWeights(op_desc);
  819. if (v_weights.empty()) {
  820. GELOGE(INTERNAL_ERROR, "[%s] Constant no not have value", var_node->GetName().c_str());
  821. return INTERNAL_ERROR;
  822. }
  823. auto *ge_tensor = const_cast<GeTensor *>(v_weights[0].get());
  824. std::unique_ptr<TensorValue> var_tensor;
  825. if (GetContext().GetHostExecFlag()) {
  826. GE_CHECK_NOTNULL(ge_tensor);
  827. // Address for eigen kernel should be aligned with 16 bytes
  828. // Tensors return by api GetWeights share data with proto, whose addr is not confirmed to be aligned
  829. GeTensor aligned_tensor = ge_tensor->Clone();
  830. GELOGD("Init tensor with host constant %s size = %zu", var_name.c_str(), aligned_tensor.MutableData().GetSize());
  831. if (MemManager::Instance().HostMemInstance(RT_MEMORY_HBM).Malloc(aligned_tensor.GetAlignedPtr(),
  832. aligned_tensor.GetData().size()) == nullptr) {
  833. GELOGE(MEMALLOC_FAILED, "Malloc host memory for an existed GeTensor failed.");
  834. return MEMALLOC_FAILED;
  835. }
  836. var_tensor.reset(new(std::nothrow)TensorValue(aligned_tensor.MutableData().data(),
  837. aligned_tensor.GetData().size()));
  838. } else {
  839. GE_CHK_STATUS_RET_NOLOG(VarNodeToTensor(var_node, var_tensor));
  840. GELOGD("Init const op tensor. name = %s, size = %ld", var_name.c_str(), var_tensor->GetSize());
  841. var_tensor->SetName("ConstOp_" + var_name);
  842. auto v_output_size = var_tensor->GetSize();
  843. auto v_output_addr = var_tensor->MutableData();
  844. if (ge_tensor->GetData().size() > 0) {
  845. GE_CHK_STATUS_RET_NOLOG(HandleDtString(*ge_tensor, v_output_addr));
  846. GELOGI("[IMAS]InitConstant memcpy graph_%u type[V] name[%s] output[%d] memaddr[%p] mem_size[%zu] datasize[%zu]",
  847. runtime_param_.graph_id, op_desc->GetName().c_str(), 0, v_output_addr, v_output_size,
  848. ge_tensor->GetData().size());
  849. GE_CHK_RT_RET(rtMemcpy(v_output_addr, v_output_size, ge_tensor->GetData().data(), ge_tensor->GetData().size(),
  850. RT_MEMCPY_HOST_TO_DEVICE));
  851. } else {
  852. GELOGI("[%s] Const op has no weight data.", op_desc->GetName().c_str());
  853. }
  854. }
  855. hybrid_model_.variable_tensors_.emplace(var_name, std::move(var_tensor));
  856. }
  857. return SUCCESS;
  858. }
  859. Status HybridModelBuilder::InitVariableTensors() {
  860. for (auto &it : hybrid_model_.device_variable_nodes_) {
  861. string var_name = it.first;
  862. NodePtr &var_node = it.second;
  863. std::unique_ptr<TensorValue> tensor;
  864. GE_CHK_STATUS_RET_NOLOG(VarNodeToTensor(var_node, tensor));
  865. GELOGD("Init variable tensor. name = %s, size = %ld, addr = %p",
  866. var_name.c_str(),
  867. tensor->GetSize(),
  868. tensor->GetData());
  869. tensor->SetName("Var_" + var_name);
  870. hybrid_model_.variable_tensors_.emplace(var_name, std::move(tensor));
  871. }
  872. for (const auto &it : hybrid_model_.host_variable_nodes_) {
  873. auto op_desc = it.second->GetOpDesc();
  874. GE_CHECK_NOTNULL(op_desc);
  875. GeTensorDesc output_tensor = op_desc->GetOutputDesc(0);
  876. int64_t tensor_size = 0;
  877. if (TensorUtils::CalcTensorMemSize(output_tensor.GetShape(), output_tensor.GetFormat(), output_tensor.GetDataType(),
  878. tensor_size) != SUCCESS) {
  879. GELOGE(INTERNAL_ERROR, "Calculate variable size failed, node name:%s", it.first.c_str());
  880. return INTERNAL_ERROR;
  881. }
  882. SharedMemInfo mem_info(it.first, tensor_size);
  883. if (HostMemManager::Instance().MallocSharedMemory(mem_info) != SUCCESS) {
  884. GELOGE(GE_GRAPH_MALLOC_FAILED, "Host variable [%s] malloc failed.", it.first.c_str());
  885. return GE_GRAPH_MALLOC_FAILED;
  886. }
  887. if (MemManager::Instance().HostMemInstance(RT_MEMORY_HBM).Malloc(mem_info.host_aligned_ptr,
  888. tensor_size) == nullptr) {
  889. GELOGE(MEMALLOC_FAILED, "Malloc host memory for an existed GeTensor failed.");
  890. return MEMALLOC_FAILED;
  891. }
  892. GELOGD("Host variable [%s] malloc success, size=%ld.", it.first.c_str(), tensor_size);
  893. std::unique_ptr<TensorValue> tensor(new (std::nothrow) TensorValue(mem_info.host_aligned_ptr->MutableGet(),
  894. tensor_size));
  895. GE_CHECK_NOTNULL(tensor);
  896. hybrid_model_.variable_tensors_.emplace(it.first, std::move(tensor));
  897. }
  898. return SUCCESS;
  899. }
  900. Status HybridModelBuilder::InitWeights() {
  901. // For constant in root graph
  902. for (const auto &subgraph_model : ge_root_model_->GetSubgraphInstanceNameToModel()) {
  903. const auto &weight_buffer = subgraph_model.second->GetWeight();
  904. if (weight_buffer.GetSize() == 0) {
  905. GELOGD("weight is empty");
  906. return SUCCESS;
  907. }
  908. auto allocator = NpuMemoryAllocator::GetAllocator();
  909. GE_CHECK_NOTNULL(allocator);
  910. auto sub_weight_buffer = TensorBuffer::Create(allocator, weight_buffer.size());
  911. GE_CHECK_NOTNULL(sub_weight_buffer);
  912. auto weight_base = reinterpret_cast<uint8_t *>(sub_weight_buffer->GetData());
  913. GE_CHK_RT_RET(rtMemcpy(weight_base,
  914. sub_weight_buffer->GetSize(),
  915. weight_buffer.GetData(),
  916. weight_buffer.GetSize(),
  917. RT_MEMCPY_HOST_TO_DEVICE));
  918. GELOGI("Init weight mem successfully, weight base %p, weight size = %zu",
  919. weight_base,
  920. sub_weight_buffer->GetSize());
  921. auto root_graph = GraphUtils::GetComputeGraph(subgraph_model.second->GetGraph());
  922. hybrid_model_.weight_buffer_map_.emplace(root_graph->GetName(),std::move(sub_weight_buffer));
  923. for (auto &node : root_graph->GetDirectNode()) {
  924. if (node->GetType() != CONSTANT) {
  925. continue;
  926. }
  927. auto op_desc = node->GetOpDesc();
  928. auto v_weights = ModelUtils::GetWeights(op_desc);
  929. if (v_weights.empty()) {
  930. GELOGE(INTERNAL_ERROR, "[%s] Constant has no value", node->GetName().c_str());
  931. return INTERNAL_ERROR;
  932. }
  933. auto *ge_tensor = const_cast<GeTensor *>(v_weights[0].get());
  934. GE_CHECK_NOTNULL(ge_tensor);
  935. const GeTensorDesc &tensor_desc = ge_tensor->GetTensorDesc();
  936. int64_t tensor_size = 0;
  937. GE_CHK_GRAPH_STATUS_RET(TensorUtils::GetSize(*op_desc->MutableOutputDesc(0), tensor_size),
  938. "[%s] Failed to get tensor size",
  939. node->GetName().c_str());
  940. int64_t data_offset = 0;
  941. GE_CHK_GRAPH_STATUS_RET(TensorUtils::GetDataOffset(tensor_desc, data_offset),
  942. "[%s] Failed to get data offset",
  943. node->GetName().c_str());
  944. GELOGD("[%s] Start to init Constant node [%s], size = %ld, offset = %ld",
  945. GetGraphName(),
  946. node->GetName().c_str(),
  947. tensor_size,
  948. data_offset);
  949. auto tensor_buffer = TensorBuffer::Create(weight_base + data_offset, tensor_size);
  950. GE_CHECK_NOTNULL(tensor_buffer);
  951. std::unique_ptr<TensorValue> constant_tensor(new (std::nothrow)TensorValue(std::move(tensor_buffer)));
  952. GE_CHECK_NOTNULL(constant_tensor);
  953. constant_tensor->SetName("Constant_" + op_desc->GetName());
  954. hybrid_model_.constant_tensors_.emplace(node, std::move(constant_tensor));
  955. GELOGD("[%s] Constant node [%s] added, size = %ld", GetGraphName(), node->GetName().c_str(), tensor_size);
  956. }
  957. }
  958. return SUCCESS;
  959. }
  960. Status HybridModelBuilder::LoadTasks() {
  961. GE_CHK_STATUS_RET(CheckAicpuOpList(), "Check Aicpu op failed.");
  962. for (auto &it : hybrid_model_.node_items_) {
  963. auto &node_item = it.second;
  964. auto &node_ptr = node_item->node;
  965. if (node_item->node_type == NETOUTPUT) {
  966. continue;
  967. }
  968. GELOGD("[%s] Start to build kernel task", node_ptr->GetName().c_str());
  969. auto load_ret = node_item->node_executor->LoadTask(hybrid_model_,
  970. node_ptr,
  971. node_item->kernel_task);
  972. if (load_ret != UNSUPPORTED && load_ret != SUCCESS) {
  973. GELOGE(load_ret, "[%s] Failed to load task", node_ptr->GetName().c_str());
  974. return load_ret;
  975. }
  976. GELOGD("[%s] Done loading task successfully.", node_ptr->GetName().c_str());
  977. }
  978. return SUCCESS;
  979. }
  980. Status HybridModelBuilder::LoadGeModel(ComputeGraph &sub_graph, const GeModelPtr &ge_model) {
  981. auto parent_node = sub_graph.GetParentNode();
  982. GE_CHECK_NOTNULL(parent_node);
  983. auto op_type = parent_node->GetType();
  984. if (IsControlOp(op_type)) {
  985. GELOGD("Set ge_model for control op subgraph: [%s], task_size = %d",
  986. sub_graph.GetName().c_str(),
  987. ge_model->GetModelTaskDefPtr()->task_size());
  988. subgraph_models_.emplace(sub_graph.GetName(), ge_model);
  989. } else {
  990. GELOGD("Set ge_model for subgraph: [%s], task_size = %d",
  991. sub_graph.GetName().c_str(),
  992. ge_model->GetModelTaskDefPtr()->task_size());
  993. hybrid_model_.known_shape_sub_models_.emplace(parent_node, ge_model);
  994. }
  995. return SUCCESS;
  996. }
  997. Status HybridModelBuilder::IndexTaskDefs(const ComputeGraphPtr &sub_graph, const GeModelPtr &ge_model) {
  998. // index task defs
  999. GELOGD("To index tasks for subgraph: %s", sub_graph->GetName().c_str());
  1000. std::unordered_map<int64_t, NodePtr> node_map;
  1001. for (const auto &node : sub_graph->GetDirectNode()) {
  1002. GE_CHECK_NOTNULL(node);
  1003. GE_CHECK_NOTNULL(node->GetOpDesc());
  1004. auto node_id = node->GetOpDesc()->GetId();
  1005. GELOGD("op_index = %ld, node_name = %s", node_id, node->GetName().c_str());
  1006. node_map.emplace(node_id, node);
  1007. }
  1008. auto tasks = ge_model->GetModelTaskDefPtr()->task();
  1009. for (int i = 0; i < tasks.size(); ++i) {
  1010. const domi::TaskDef &task_def = tasks[i];
  1011. GELOGI("Task id = %d, task type = %d", i, task_def.type());
  1012. auto task_type = static_cast<rtModelTaskType_t>(task_def.type());
  1013. uint32_t op_index = -1;
  1014. if (task_type == RT_MODEL_TASK_KERNEL) {
  1015. op_index = task_def.kernel().context().op_index();
  1016. } else if (task_type == RT_MODEL_TASK_KERNEL_EX) {
  1017. op_index = task_def.kernel_ex().op_index();
  1018. } else if (task_type == RT_MODEL_TASK_HCCL) {
  1019. op_index = task_def.kernel_hccl().op_index();
  1020. } else if (task_type == RT_MODEL_TASK_ALL_KERNEL) {
  1021. op_index = task_def.kernel_with_handle().context().op_index();
  1022. } else {
  1023. GELOGD("Skip task type: %d", static_cast<int>(task_type));
  1024. continue;
  1025. }
  1026. GELOGD("op_index = %u, task_type = %d.", op_index, task_type);
  1027. auto iter = node_map.find(op_index);
  1028. if (iter == node_map.end()) {
  1029. GELOGE(INTERNAL_ERROR, "Failed to get node by op_index = %u.", op_index);
  1030. return INTERNAL_ERROR;
  1031. }
  1032. auto &node = iter->second;
  1033. if (task_type == RT_MODEL_TASK_KERNEL || task_type == RT_MODEL_TASK_ALL_KERNEL) {
  1034. ge_model->GetTBEKernelStore().LoadTBEKernelBinToOpDesc(node->GetOpDesc());
  1035. }
  1036. GELOGD("Task loaded for node: %s, task type = %d, op_index = %u.", node->GetName().c_str(), task_type, op_index);
  1037. hybrid_model_.task_defs_[node].emplace_back(task_def);
  1038. }
  1039. return SUCCESS;
  1040. }
  1041. Status HybridModelBuilder::IndexTaskDefs() {
  1042. const auto &root_graph = ge_root_model_->GetRootGraph();
  1043. if (SetOutputNameAttr(*root_graph) != SUCCESS) {
  1044. GELOGW("Set output name attr failed.");
  1045. }
  1046. for (auto &it : ge_root_model_->GetSubgraphInstanceNameToModel()) {
  1047. auto &name = it.first;
  1048. auto &ge_model = it.second;
  1049. GE_CHECK_NOTNULL(ge_model);
  1050. const auto &sub_graph = root_graph->GetSubgraph(name);
  1051. if (sub_graph == nullptr) {
  1052. continue;
  1053. }
  1054. bool is_unknown_shape = sub_graph->GetGraphUnknownFlag();
  1055. if (!is_unknown_shape) {
  1056. GE_CHK_STATUS_RET_NOLOG(LoadGeModel(*sub_graph, ge_model));
  1057. continue;
  1058. }
  1059. // index task defs
  1060. GELOGD("To index tasks for subgraph: %s", name.c_str());
  1061. std::unordered_map<int64_t, NodePtr> node_map;
  1062. for (const auto &node : sub_graph->GetDirectNode()) {
  1063. GE_CHECK_NOTNULL(node);
  1064. GE_CHECK_NOTNULL(node->GetOpDesc());
  1065. auto node_id = node->GetOpDesc()->GetId();
  1066. GELOGD("op_index = %ld, node_name = %s", node_id, node->GetName().c_str());
  1067. node_map.emplace(node_id, node);
  1068. }
  1069. auto tasks = ge_model->GetModelTaskDefPtr()->task();
  1070. for (int i = 0; i < tasks.size(); ++i) {
  1071. const domi::TaskDef &task_def = tasks[i];
  1072. GELOGI("Task id = %d, task type = %d", i, task_def.type());
  1073. auto task_type = static_cast<rtModelTaskType_t>(task_def.type());
  1074. uint32_t op_index = -1;
  1075. if (task_type == RT_MODEL_TASK_KERNEL) {
  1076. op_index = task_def.kernel().context().op_index();
  1077. } else if (task_type == RT_MODEL_TASK_KERNEL_EX) {
  1078. op_index = task_def.kernel_ex().op_index();
  1079. } else if (task_type == RT_MODEL_TASK_HCCL) {
  1080. op_index = task_def.kernel_hccl().op_index();
  1081. } else if (task_type == RT_MODEL_TASK_ALL_KERNEL) {
  1082. op_index = task_def.kernel_with_handle().context().op_index();
  1083. } else {
  1084. GELOGD("Skip task type: %d", static_cast<int>(task_type));
  1085. continue;
  1086. }
  1087. auto iter = node_map.find(op_index);
  1088. if (iter == node_map.end()) {
  1089. GELOGE(INTERNAL_ERROR, "Failed to get node by index = %u", op_index);
  1090. return INTERNAL_ERROR;
  1091. }
  1092. auto &node = iter->second;
  1093. if (task_type == RT_MODEL_TASK_KERNEL || task_type == RT_MODEL_TASK_ALL_KERNEL) {
  1094. ge_model->GetTBEKernelStore().LoadTBEKernelBinToOpDesc(node->GetOpDesc());
  1095. }
  1096. GELOGD("Task loaded for node: %s, task type = %d, op_index = %u", node->GetName().c_str(), task_type, op_index);
  1097. hybrid_model_.task_defs_[node].emplace_back(task_def);
  1098. }
  1099. }
  1100. return SUCCESS;
  1101. }
  1102. Status HybridModelBuilder::IndexSpecialNodes() {
  1103. GELOGD("Start to index special nodes");
  1104. const auto &root_graph = ge_root_model_->GetRootGraph();
  1105. for (auto &node : root_graph->GetAllNodes()) {
  1106. GE_CHECK_NOTNULL(node);
  1107. GE_CHECK_NOTNULL(node->GetOpDesc());
  1108. auto op_type = node->GetType();
  1109. GELOGD("node name = %s, node type = %s", node->GetName().c_str(), node->GetType().c_str());
  1110. if (op_type == VARIABLE) {
  1111. string placement;
  1112. (void) AttrUtils::GetStr(node->GetOpDesc(), ATTR_VARIABLE_PLACEMENT, placement);
  1113. if (placement == "host") {
  1114. hybrid_model_.host_variable_nodes_.emplace(node->GetName(), node);
  1115. } else {
  1116. hybrid_model_.device_variable_nodes_.emplace(node->GetName(), node);
  1117. }
  1118. } else if (op_type == CONSTANTOP) {
  1119. constant_op_nodes_.emplace(node->GetName(), node);
  1120. } else if (op_type == DATA && node->GetOwnerComputeGraph() != root_graph) {
  1121. NodePtr src_node;
  1122. int peer_out_index = -1;
  1123. GE_CHK_STATUS_RET_NOLOG(GetPeerNodeAcrossSubGraphs(node, src_node, peer_out_index));
  1124. GELOGD("Got peer node for data node %s, peer node = %s(%s)",
  1125. node->GetName().c_str(),
  1126. src_node->GetName().c_str(),
  1127. src_node->GetType().c_str());
  1128. auto src_op_type = src_node->GetType();
  1129. if (src_op_type == CONSTANTOP || src_op_type == VARIABLE) {
  1130. for (auto &dst_node_and_in_anchor : node->GetOutDataNodesAndAnchors()) {
  1131. auto &dst_node = dst_node_and_in_anchor.first;
  1132. auto &in_anchor = dst_node_and_in_anchor.second;
  1133. node_ref_inputs_[dst_node].emplace_back(std::make_pair(in_anchor->GetIdx(), src_node));
  1134. }
  1135. }
  1136. }
  1137. }
  1138. return SUCCESS;
  1139. }
  1140. Status HybridModelBuilder::GetPeerNodeAcrossSubGraphs(const NodePtr &data_node,
  1141. NodePtr &peer_node,
  1142. int &peer_out_index) {
  1143. auto sub_graph = data_node->GetOwnerComputeGraph();
  1144. GE_CHECK_NOTNULL(sub_graph);
  1145. GELOGD("To get peer node of %s::%s", sub_graph->GetName().c_str(), data_node->GetName().c_str());
  1146. auto wrapped_node = data_node->GetOwnerComputeGraph()->GetParentNode();
  1147. if (wrapped_node == nullptr) {
  1148. GELOGE(INTERNAL_ERROR, "[%s] Node is in root graph.", data_node->GetName().c_str());
  1149. return INTERNAL_ERROR;
  1150. }
  1151. auto data_op_desc = data_node->GetOpDesc();
  1152. uint32_t parent_index = 0;
  1153. if (!AttrUtils::GetInt(data_op_desc, ATTR_NAME_PARENT_NODE_INDEX, parent_index)) {
  1154. GELOGE(INTERNAL_ERROR,
  1155. "[%s] Failed to get attr [%s]",
  1156. data_op_desc->GetName().c_str(),
  1157. ATTR_NAME_PARENT_NODE_INDEX.c_str());
  1158. return INTERNAL_ERROR;
  1159. }
  1160. auto wrapped_node_in_anchor = wrapped_node->GetInDataAnchor(parent_index);
  1161. GE_CHECK_NOTNULL(wrapped_node_in_anchor);
  1162. auto src_out_anchor = wrapped_node_in_anchor->GetPeerOutAnchor();
  1163. if (src_out_anchor == nullptr || src_out_anchor->GetOwnerNode() == nullptr) {
  1164. GELOGE(INTERNAL_ERROR, "[%s] Parent node do not have peer anchor.", data_node->GetName().c_str());
  1165. return INTERNAL_ERROR;
  1166. }
  1167. auto src_wrapped_node_out_anchor = wrapped_node_in_anchor->GetPeerOutAnchor();
  1168. GE_CHECK_NOTNULL(src_wrapped_node_out_anchor);
  1169. auto src_wrapped_node = src_wrapped_node_out_anchor->GetOwnerNode();
  1170. GE_CHECK_NOTNULL(src_wrapped_node);
  1171. // connected to root-graph's DATA
  1172. auto src_node_type = src_wrapped_node->GetType();
  1173. if (src_node_type != PARTITIONEDCALL) {
  1174. peer_node = src_wrapped_node;
  1175. peer_out_index = kVarOutputIndex;
  1176. GELOGD("[%s] Node is connected to root graph's node: %s",
  1177. data_node->GetName().c_str(),
  1178. peer_node->GetName().c_str());
  1179. return SUCCESS;
  1180. }
  1181. auto src_graph = NodeUtils::GetSubgraph(*src_wrapped_node, kSubgraphIndex);
  1182. GE_CHECK_NOTNULL(src_graph);
  1183. auto src_net_output_node = src_graph->FindFirstNodeMatchType(NETOUTPUT);
  1184. GE_CHK_BOOL_TRUE_EXEC_WITH_LOG(src_net_output_node == nullptr,
  1185. return INTERNAL_ERROR,
  1186. "Failed to find NetOutput in subgraph: %s",
  1187. src_graph->GetName().c_str());
  1188. auto net_output_desc = src_net_output_node->GetOpDesc();
  1189. GE_CHECK_NOTNULL(net_output_desc);
  1190. auto out_index = static_cast<uint32_t>(src_wrapped_node_out_anchor->GetIdx());
  1191. GELOGD("src graph = %s, src parent output index = %u", src_graph->GetName().c_str(), out_index);
  1192. // link src to outputs of DataNode
  1193. auto input_size = net_output_desc->GetAllInputsSize();
  1194. GE_CHECK_LE(input_size, UINT32_MAX);
  1195. for (uint32_t i = 0; i < static_cast<uint32_t>(input_size); ++i) {
  1196. uint32_t p_index = 0;
  1197. if (!AttrUtils::GetInt(net_output_desc->GetInputDesc(i), ATTR_NAME_PARENT_NODE_INDEX, p_index)) {
  1198. GELOGW("SubGraph: %s input tensor %u attr %s not found.",
  1199. src_graph->GetName().c_str(), i, ATTR_NAME_PARENT_NODE_INDEX.c_str());
  1200. continue;
  1201. }
  1202. GELOGD("NetOutput's input[%u], parent_node_index = %u", i, p_index);
  1203. if (p_index == out_index) {
  1204. auto in_anchor = src_net_output_node->GetInDataAnchor(i);
  1205. GE_CHECK_NOTNULL(in_anchor);
  1206. auto peer_out_anchor = in_anchor->GetPeerOutAnchor();
  1207. GE_CHECK_NOTNULL(peer_out_anchor);
  1208. peer_node = peer_out_anchor->GetOwnerNode();
  1209. GE_CHECK_NOTNULL(peer_node);
  1210. peer_out_index = peer_out_anchor->GetIdx();
  1211. GELOGD("Found peer node of Data node: %s::%s is %s::%s",
  1212. sub_graph->GetName().c_str(),
  1213. data_node->GetName().c_str(),
  1214. src_graph->GetName().c_str(),
  1215. peer_node->GetName().c_str());
  1216. return SUCCESS;
  1217. }
  1218. }
  1219. GELOGE(FAILED,
  1220. "Failed to find peer node for %s::%s",
  1221. sub_graph->GetName().c_str(),
  1222. data_node->GetName().c_str());
  1223. return FAILED;
  1224. }
  1225. Status HybridModelBuilder::InitRuntimeParams() {
  1226. int64_t value = 0;
  1227. bool ret = false;
  1228. if (ge_root_model_->GetSubgraphInstanceNameToModel().empty()) {
  1229. GELOGE(INTERNAL_ERROR, "Root model has no sub model");
  1230. return INTERNAL_ERROR;
  1231. }
  1232. // session id and var size is same for every model
  1233. auto first_model = ge_root_model_->GetSubgraphInstanceNameToModel().begin()->second;
  1234. ret = ge::AttrUtils::GetInt(first_model, ge::MODEL_ATTR_SESSION_ID, value);
  1235. runtime_param_.session_id = ret ? static_cast<uint64_t>(value) : 0;
  1236. ret = ge::AttrUtils::GetInt(first_model, ATTR_MODEL_TASK_GEN_VAR_ADDR, value);
  1237. runtime_param_.logic_var_base = ret ? static_cast<uint64_t>(value) : 0;
  1238. runtime_param_.graph_id = ge_root_model_->GetRootGraph()->GetGraphID();
  1239. value = 0;
  1240. for (auto &it : ge_root_model_->GetSubgraphInstanceNameToModel()) {
  1241. (void) ge::AttrUtils::GetInt(it.second, ATTR_MODEL_VAR_SIZE, value);
  1242. if (value > 0) {
  1243. runtime_param_.var_size = static_cast<uint64_t>(value);
  1244. break;
  1245. }
  1246. }
  1247. GELOGI("InitRuntimeParams(), session_id:%lu, var_size:%lu. graph_id = %u",
  1248. runtime_param_.session_id, runtime_param_.var_size, runtime_param_.graph_id);
  1249. var_manager_ = VarManager::Instance(runtime_param_.session_id);
  1250. GE_CHECK_NOTNULL(var_manager_);
  1251. return SUCCESS;
  1252. }
  1253. Status HybridModelBuilder::IdentifySameInputs(NodeItem &node_item) {
  1254. GELOGD("Start to parse same inputs on net output: %s", node_item.NodeName().c_str());
  1255. auto subgraph = NodeUtils::GetSubgraph(*node_item.node, kSubgraphIndex);
  1256. GE_CHECK_NOTNULL(subgraph);
  1257. auto net_output_node = subgraph->FindFirstNodeMatchType(NETOUTPUT);
  1258. if (net_output_node == nullptr) {
  1259. GELOGD("Subgraph [%s] does not have net output", subgraph->GetName().c_str());
  1260. return SUCCESS;
  1261. }
  1262. auto net_output_desc = net_output_node->GetOpDesc();
  1263. GE_CHECK_NOTNULL(net_output_desc);
  1264. std::map<std::string, int> connected_inputs;
  1265. for (const auto &in_data_anchor : net_output_node->GetAllInDataAnchors()) {
  1266. auto out_data_anchor = in_data_anchor->GetPeerOutAnchor();
  1267. if (out_data_anchor == nullptr) {
  1268. continue;
  1269. }
  1270. auto src_node = out_data_anchor->GetOwnerNode();
  1271. GE_CHECK_NOTNULL(src_node);
  1272. auto op_desc = src_node->GetOpDesc();
  1273. GE_CHECK_NOTNULL(op_desc);
  1274. std::string input_key = std::to_string(op_desc->GetId()) + "_" + std::to_string(out_data_anchor->GetIdx());
  1275. auto it = connected_inputs.find(input_key);
  1276. if (it == connected_inputs.end()) {
  1277. connected_inputs.emplace(input_key, in_data_anchor->GetIdx());
  1278. } else {
  1279. GELOGD("[%s] output [%d] reuse output [%d] input node = %s, idx = %d.", node_item.NodeName().c_str(),
  1280. in_data_anchor->GetIdx(),
  1281. it->second,
  1282. src_node->GetName().c_str(),
  1283. out_data_anchor->GetIdx());
  1284. node_item.reuse_outputs.emplace(in_data_anchor->GetIdx(), it->second);
  1285. }
  1286. }
  1287. return SUCCESS;
  1288. }
  1289. Status HybridModelBuilder::IdentifyVariableOutputs(NodeItem &node_item) {
  1290. GELOGD("Start to parse outputs of node: %s", node_item.NodeName().c_str());
  1291. auto subgraph = NodeUtils::GetSubgraph(*node_item.node, kSubgraphIndex);
  1292. GE_CHECK_NOTNULL(subgraph);
  1293. auto net_output_node = subgraph->FindFirstNodeMatchType(NETOUTPUT);
  1294. if (net_output_node == nullptr) {
  1295. GELOGD("[%s] Subgraph do not got net output", subgraph->GetName().c_str());
  1296. return SUCCESS;
  1297. }
  1298. auto net_output_desc = net_output_node->GetOpDesc();
  1299. GE_CHECK_NOTNULL(net_output_desc);
  1300. // constant/variable connected to net output
  1301. for (const auto &in_data_anchor : net_output_node->GetAllInDataAnchors()) {
  1302. auto src_node = GetPeerNode(in_data_anchor);
  1303. GE_CHECK_NOTNULL(src_node);
  1304. auto src_op_type = src_node->GetType();
  1305. GELOGD("Node %s, output %d, src node = %s, src node type = %s",
  1306. node_item.NodeName().c_str(),
  1307. in_data_anchor->GetIdx(),
  1308. src_node->GetName().c_str(),
  1309. src_op_type.c_str());
  1310. if (src_op_type != CONSTANTOP && src_op_type != VARIABLE) {
  1311. continue;
  1312. }
  1313. uint32_t parent_index = 0;
  1314. GE_CHK_STATUS_RET_NOLOG(GetParentNodeOutputIndex(*net_output_desc, in_data_anchor->GetIdx(), parent_index));
  1315. GELOGD("Got parent output index = %u", parent_index);
  1316. GE_CHECK_LE(parent_index, INT32_MAX);
  1317. node_item.ref_outputs.emplace(static_cast<int>(parent_index), src_node);
  1318. }
  1319. // Data nodes marked with REF_VAR_SRC_VAR_NAME
  1320. // Using variable tensor as data's output
  1321. for (auto &node : subgraph->GetDirectNode()) {
  1322. if (node->GetType() != DATA) {
  1323. continue;
  1324. }
  1325. string ref_var_name;
  1326. (void) AttrUtils::GetStr(node->GetOpDesc(), REF_VAR_SRC_VAR_NAME, ref_var_name);
  1327. if (ref_var_name.empty()) {
  1328. continue;
  1329. }
  1330. GELOGD("Data node ref to variable: %s", ref_var_name.c_str());
  1331. NodePtr src_node;
  1332. auto var_node = hybrid_model_.GetVariableNode(ref_var_name);
  1333. GE_CHECK_NOTNULL(var_node);
  1334. GELOGD("Found var node [%s] by ref_var_name [%s]", var_node->GetName().c_str(), ref_var_name.c_str());
  1335. int peer_output_index = -1;
  1336. GE_CHK_STATUS_RET_NOLOG(GetPeerNodeAcrossSubGraphs(node, src_node, peer_output_index));
  1337. auto src_node_item = MutableNodeItem(src_node);
  1338. GE_CHECK_NOTNULL(src_node_item);
  1339. src_node_item->ref_outputs.emplace(peer_output_index, var_node);
  1340. }
  1341. return SUCCESS;
  1342. }
  1343. NodePtr HybridModelBuilder::GetPeerNode(const InDataAnchorPtr &in_data_anchor) {
  1344. auto peer_out_anchor = in_data_anchor->GetPeerOutAnchor();
  1345. if (peer_out_anchor != nullptr) {
  1346. return peer_out_anchor->GetOwnerNode();
  1347. }
  1348. return nullptr;
  1349. }
  1350. Status HybridModelBuilder::GetParentNodeOutputIndex(const OpDesc &op_desc, int index, uint32_t &out_index) {
  1351. auto input_desc = op_desc.MutableInputDesc(index);
  1352. GE_CHECK_NOTNULL(input_desc);
  1353. if (!AttrUtils::GetInt(input_desc, ATTR_NAME_PARENT_NODE_INDEX, out_index)) {
  1354. GELOGE(INTERNAL_ERROR, "NetOutput input tensor %d, attr %s not found.",
  1355. index, ATTR_NAME_PARENT_NODE_INDEX.c_str());
  1356. return INTERNAL_ERROR;
  1357. }
  1358. return SUCCESS;
  1359. }
  1360. Status HybridModelBuilder::InitModelMem() {
  1361. hybrid_model_.var_mem_base_ = var_manager_->GetVarMemoryBase(RT_MEMORY_HBM);
  1362. auto total_var_size = hybrid_model_.TotalVarMemSize();
  1363. if (total_var_size == 0 && !constant_op_nodes_.empty()) {
  1364. total_var_size = var_manager_->GetVarMemSize(RT_MEMORY_HBM) > 0 ? var_manager_->GetVarMemMaxSize() : 0;
  1365. GELOGD("Model var size = 0. but got uninitialized constant. set var size to %zu.", total_var_size);
  1366. }
  1367. if (total_var_size > 0 && hybrid_model_.var_mem_base_ == nullptr) {
  1368. GE_CHK_STATUS_RET(var_manager_->MallocVarMemory(total_var_size),
  1369. "Malloc Var Memory Fail.");
  1370. hybrid_model_.var_mem_base_ = var_manager_->GetVarMemoryBase(RT_MEMORY_HBM);
  1371. }
  1372. runtime_param_.var_base = hybrid_model_.var_mem_base_;
  1373. return SUCCESS;
  1374. }
  1375. Status HybridModelBuilder::TransAllVarData() {
  1376. GELOGI("TransAllVarData start: session_id:%lu, graph_id: %u.", runtime_param_.session_id, runtime_param_.graph_id);
  1377. rtContext_t ctx = nullptr;
  1378. rtError_t rt_ret = rtCtxGetCurrent(&ctx);
  1379. if (rt_ret != RT_ERROR_NONE) {
  1380. GELOGE(RT_FAILED, "Failed to get current context, error_code is: 0x%X.", rt_ret);
  1381. return RT_FAILED;
  1382. }
  1383. std::vector<NodePtr> variable_node_list;
  1384. for (auto &it : hybrid_model_.device_variable_nodes_) {
  1385. variable_node_list.emplace_back(it.second);
  1386. GELOGD("[%s] added for trans var data", it.first.c_str());
  1387. }
  1388. GE_CHK_STATUS_RET(TransVarDataUtils::TransAllVarData(variable_node_list,
  1389. runtime_param_.session_id,
  1390. ctx,
  1391. runtime_param_.graph_id),
  1392. "TransAllVarData failed.");
  1393. GELOGI("TransAllVarData success.");
  1394. return SUCCESS;
  1395. }
  1396. Status HybridModelBuilder::CopyVarData() {
  1397. GE_CHK_STATUS_RET(TransVarDataUtils::CopyVarData(ge_root_model_->GetRootGraph(),
  1398. runtime_param_.session_id,
  1399. hybrid_model_.device_id_),
  1400. "CopyVarData failed.");
  1401. GELOGI("CopyVarData success.");
  1402. return SUCCESS;
  1403. }
  1404. Status HybridModelBuilder::LoadKnownShapedSubgraph(ComputeGraph &graph, NodeItem *parent_node_item) {
  1405. GELOGD("Start to load known shaped subgraph [%s]", graph.GetName().c_str());
  1406. auto graph_item = std::unique_ptr<GraphItem>(new(std::nothrow)GraphItem());
  1407. GE_CHECK_NOTNULL(graph_item);
  1408. graph_item->is_dynamic_ = false;
  1409. auto subgraph_name = graph.GetName();
  1410. auto wrapper_op_desc = MakeShared<OpDesc>(subgraph_name + "_partitioned_call", PARTITIONEDCALL);
  1411. GE_CHECK_NOTNULL(wrapper_op_desc);
  1412. for (auto &node : graph.GetDirectNode()) {
  1413. GE_CHECK_NOTNULL(node);
  1414. auto op_desc = node->GetOpDesc();
  1415. GE_CHECK_NOTNULL(op_desc);
  1416. const auto &op_type = node->GetType();
  1417. if (op_type == DATA) {
  1418. int32_t data_index = 0;
  1419. if (!AttrUtils::GetInt(node->GetOpDesc(), ATTR_NAME_PARENT_NODE_INDEX, data_index)) {
  1420. GELOGE(FAILED,
  1421. "[%s] Failed to get attr [%s]",
  1422. node->GetName().c_str(),
  1423. ATTR_NAME_PARENT_NODE_INDEX.c_str());
  1424. return FAILED;
  1425. }
  1426. (void) wrapper_op_desc->AddInputDesc(op_desc->GetInputDesc(0));
  1427. graph_item->input_index_mapping_.emplace_back(data_index);
  1428. } else if (op_type == NETOUTPUT) {
  1429. int output_index = 0;
  1430. for (const auto &output_desc : op_desc->GetAllInputsDescPtr()) {
  1431. int32_t data_index = output_index++;
  1432. if (!AttrUtils::GetInt(output_desc, ATTR_NAME_PARENT_NODE_INDEX, data_index)) {
  1433. GELOGI("[%s] Failed to get attr [%s]", node->GetName().c_str(), ATTR_NAME_PARENT_NODE_INDEX.c_str());
  1434. }
  1435. GE_CHK_GRAPH_STATUS_RET(wrapper_op_desc->AddOutputDesc(*output_desc),
  1436. "[%s] Failed to add output desc. output index = %d",
  1437. graph.GetName().c_str(),
  1438. output_index);
  1439. graph_item->output_index_mapping_.emplace_back(data_index);
  1440. }
  1441. }
  1442. }
  1443. auto temp_graph = MakeShared<ComputeGraph>("temp");
  1444. GE_CHECK_NOTNULL(temp_graph);
  1445. auto wrapper_node = temp_graph->AddNode(wrapper_op_desc);
  1446. GeModelPtr ge_model = subgraph_models_[subgraph_name];
  1447. GE_CHECK_NOTNULL(ge_model);
  1448. hybrid_model_.known_shape_sub_models_.emplace(wrapper_node, ge_model);
  1449. NodeItem *node_item = nullptr;
  1450. GE_CHK_STATUS_RET_NOLOG(GetOrCreateNodeItem(wrapper_node, &node_item));
  1451. node_item->input_start = 0;
  1452. node_item->output_start = 0;
  1453. node_item->outputs.resize(node_item->num_outputs);
  1454. graph_item->node_items_.emplace_back(node_item);
  1455. graph_item->output_node_ = node_item;
  1456. graph_item->total_inputs_ = node_item->num_inputs;
  1457. graph_item->total_outputs_ = node_item->num_outputs;
  1458. GELOGD("NodeItem create for known shape subgraph [%s], NodeItem = %s",
  1459. graph.GetName().c_str(),
  1460. node_item->DebugString().c_str());
  1461. GELOGD("Done parse known shape subgraph successfully. graph = [%s]", graph.GetName().c_str());
  1462. graph_item->SetName(graph.GetName());
  1463. GELOGD("Done loading known shape subgraph: [%s]", graph_item->GetName().c_str());
  1464. hybrid_model_.subgraph_items_.emplace(graph.GetName(), std::move(graph_item));
  1465. return SUCCESS;
  1466. }
  1467. Status HybridModelBuilder::RecoverGraphUnknownFlag() {
  1468. const auto &root_graph = ge_root_model_->GetRootGraph();
  1469. for (auto &sub_graph : root_graph->GetAllSubgraphs()) {
  1470. GE_CHECK_NOTNULL(sub_graph);
  1471. for (const auto &node : sub_graph->GetDirectNode()) {
  1472. bool is_unknown_shape = false;
  1473. (void)AttrUtils::GetBool(node->GetOpDesc(), kOwnerGraphIsUnknown, is_unknown_shape);
  1474. sub_graph->SetGraphUnknownFlag(is_unknown_shape);
  1475. break;
  1476. }
  1477. }
  1478. return SUCCESS;
  1479. }
  1480. Status HybridModelBuilder::GenerateFpProfilingTask(const OpDescPtr &op_desc, vector<domi::TaskDef> &task_def_list) {
  1481. uint64_t jobid_log_id = ge::GetContext().TraceId();
  1482. GELOGD("The first FP operator is %s,, job_id %lu", op_desc->GetName().c_str(), jobid_log_id);
  1483. TaskDef job_task_def;
  1484. job_task_def.set_type(RT_MODEL_TASK_PROFILER_TRACE);
  1485. job_task_def.set_stream_id(op_desc->GetStreamId());
  1486. LogTimeStampDef *job_log_def = job_task_def.mutable_log_timestamp();
  1487. if (job_log_def != nullptr) {
  1488. job_log_def->set_logid(jobid_log_id);
  1489. job_log_def->set_notify(false);
  1490. }
  1491. task_def_list.emplace_back(job_task_def);
  1492. TaskDef fp_task_def;
  1493. fp_task_def.set_type(RT_MODEL_TASK_PROFILER_TRACE);
  1494. fp_task_def.set_stream_id(op_desc->GetStreamId());
  1495. LogTimeStampDef *fp_log_def = fp_task_def.mutable_log_timestamp();
  1496. if (fp_log_def != nullptr) {
  1497. fp_log_def->set_logid(kProfilingFpStartLogid);
  1498. fp_log_def->set_notify(false);
  1499. }
  1500. task_def_list.emplace_back(fp_task_def);
  1501. return SUCCESS;
  1502. }
  1503. Status HybridModelBuilder::GenerateArProfilingTask(const OpDescPtr &op_desc, int64_t log_id,
  1504. vector<domi::TaskDef> &task_def_list) {
  1505. TaskDef ar_task_def;
  1506. ar_task_def.set_type(RT_MODEL_TASK_PROFILER_TRACE);
  1507. ar_task_def.set_stream_id(op_desc->GetStreamId());
  1508. LogTimeStampDef *ar_log_def = ar_task_def.mutable_log_timestamp();
  1509. if (ar_log_def != nullptr) {
  1510. ar_log_def->set_logid(log_id);
  1511. ar_log_def->set_notify(false);
  1512. }
  1513. task_def_list.emplace_back(ar_task_def);
  1514. return SUCCESS;
  1515. }
  1516. Status HybridModelBuilder::GenerateBpProfilingTask(const OpDescPtr &op_desc, vector<domi::TaskDef> &task_def_list) {
  1517. TaskDef bp_task_def;
  1518. bp_task_def.set_type(RT_MODEL_TASK_PROFILER_TRACE);
  1519. bp_task_def.set_stream_id(op_desc->GetStreamId());
  1520. LogTimeStampDef *bp_log_def = bp_task_def.mutable_log_timestamp();
  1521. GE_CHECK_NOTNULL(bp_log_def);
  1522. bp_log_def->set_logid(kProfilingBpEndLogid);
  1523. bp_log_def->set_notify(false);
  1524. task_def_list.emplace_back(bp_task_def);
  1525. return SUCCESS;
  1526. }
  1527. Status HybridModelBuilder::GenerateEndProfilingTask(const OpDescPtr &op_desc, vector<domi::TaskDef> &task_def_list) {
  1528. TaskDef end_task_def;
  1529. end_task_def.set_type(RT_MODEL_TASK_PROFILER_TRACE);
  1530. end_task_def.set_stream_id(op_desc->GetStreamId());
  1531. LogTimeStampDef *end_log_def = end_task_def.mutable_log_timestamp();
  1532. GE_CHECK_NOTNULL(end_log_def);
  1533. end_log_def->set_logid(kProfilingIterEndLogid);
  1534. end_log_def->set_notify(true);
  1535. task_def_list.emplace_back(end_task_def);
  1536. return SUCCESS;
  1537. }
  1538. Status HybridModelBuilder::CreateProfilingNodeBefore(GraphItem &graph_item, const NodePtr &node) {
  1539. GE_CHECK_NOTNULL(node);
  1540. const OpDescPtr &op_desc = node->GetOpDesc();
  1541. GE_CHECK_NOTNULL(op_desc);
  1542. const auto &compute_graph = MakeShared<ComputeGraph>(kProfilingGraph);
  1543. GE_CHECK_NOTNULL(compute_graph);
  1544. NodePtr node_ptr = nullptr;
  1545. map<NodePtr, vector<domi::TaskDef>> node_task_map;
  1546. // create fp node
  1547. bool is_insert_fp_profiling_task = false;
  1548. (void)ge::AttrUtils::GetBool(op_desc, ATTR_NAME_INSERT_FP_PROFILILNG_TASK, is_insert_fp_profiling_task);
  1549. if (is_insert_fp_profiling_task) {
  1550. vector<domi::TaskDef> task_def_list;
  1551. (void)GenerateFpProfilingTask(op_desc, task_def_list);
  1552. auto fp_desc = MakeShared<OpDesc>(kProfilingFpNode, PROFILINGTRAININGTRACE);
  1553. GE_CHECK_NOTNULL(fp_desc);
  1554. fp_desc->SetOpKernelLibName(kEngineNameRts);
  1555. node_ptr = compute_graph->AddNode(fp_desc);
  1556. GE_CHECK_NOTNULL(node_ptr);
  1557. node_task_map[node_ptr] = task_def_list;
  1558. GELOGD("Create fp profiling node success before.");
  1559. }
  1560. // creat all reduce start node
  1561. bool is_insert_bp_profiling_task = false;
  1562. (void)ge::AttrUtils::GetBool(op_desc, ATTR_NAME_INSERT_BP_PROFILILNG_TASK, is_insert_bp_profiling_task);
  1563. bool is_all_reduce = (op_desc->GetType() == HCOMALLREDUCE || op_desc->GetType() == HVDCALLBACKALLREDUCE);
  1564. if (is_all_reduce && is_insert_bp_profiling_task) {
  1565. vector<domi::TaskDef> task_def_list;
  1566. int64_t log_id = 0;
  1567. (void)ge::AttrUtils::GetInt(op_desc, ATTR_NAME_INSERT_PROFILILNG_TASK_LOG_ID, log_id);
  1568. GELOGD("All reduce node profiling task log id: %ld before", log_id);
  1569. (void) GenerateArProfilingTask(op_desc, log_id, task_def_list);
  1570. string op_name = string(kProfilingArNode) + std::to_string(log_id);
  1571. auto ar_desc_start = MakeShared<OpDesc>(op_name, PROFILINGTRAININGTRACE);
  1572. GE_CHECK_NOTNULL(ar_desc_start);
  1573. ar_desc_start->SetOpKernelLibName(kEngineNameRts);
  1574. node_ptr = compute_graph->AddNode(ar_desc_start);
  1575. GE_CHECK_NOTNULL(node_ptr);
  1576. node_task_map[node_ptr] = task_def_list;
  1577. GELOGD("Create all reduce start profiling node success before.");
  1578. }
  1579. if (!node_task_map.empty()) {
  1580. for (const auto &node_task : node_task_map) {
  1581. NodePtr profiling_node = node_task.first;
  1582. vector<domi::TaskDef> task_def_lists = node_task.second;
  1583. for (const auto &task_def : task_def_lists) {
  1584. hybrid_model_.task_defs_[profiling_node].emplace_back(task_def);
  1585. }
  1586. if (op_desc->HasAttr(ATTR_STAGE_LEVEL)) {
  1587. uint32_t stage_level = UINT32_MAX;
  1588. (void)ge::AttrUtils::GetInt(op_desc, ATTR_STAGE_LEVEL, stage_level);
  1589. (void)ge::AttrUtils::SetInt(node_ptr->GetOpDesc(), ATTR_STAGE_LEVEL, stage_level);
  1590. }
  1591. NodeItem *node_item = nullptr;
  1592. GE_CHK_STATUS_RET_NOLOG(GetOrCreateNodeItem(profiling_node, &node_item));
  1593. GE_CHECK_NOTNULL(node_item);
  1594. node_item->input_start = 0;
  1595. node_item->output_start = 0;
  1596. graph_item.node_items_.emplace_back(node_item);
  1597. }
  1598. } else {
  1599. GELOGD("No need to create profiling node before.");
  1600. }
  1601. return SUCCESS;
  1602. }
  1603. Status HybridModelBuilder::CreateProfilingNodeAfter(GraphItem &graph_item, const NodePtr &node) {
  1604. GE_CHECK_NOTNULL(node);
  1605. const OpDescPtr &op_desc = node->GetOpDesc();
  1606. GE_CHECK_NOTNULL(op_desc);
  1607. const auto &compute_graph = MakeShared<ComputeGraph>(kProfilingGraph);
  1608. GE_CHECK_NOTNULL(compute_graph);
  1609. NodePtr node_ptr = nullptr;
  1610. map<NodePtr, vector<domi::TaskDef>> node_task_map;
  1611. // Create all reduce end node
  1612. bool is_insert_bp_profiling_task = false;
  1613. (void)ge::AttrUtils::GetBool(op_desc, ATTR_NAME_INSERT_BP_PROFILILNG_TASK, is_insert_bp_profiling_task);
  1614. bool is_all_reduce = (op_desc->GetType() == HCOMALLREDUCE || op_desc->GetType() == HVDCALLBACKALLREDUCE);
  1615. if (is_all_reduce && is_insert_bp_profiling_task) {
  1616. vector<domi::TaskDef> task_def_list;
  1617. int64_t log_id = 0;
  1618. (void)ge::AttrUtils::GetInt(op_desc, ATTR_NAME_INSERT_PROFILILNG_TASK_LOG_ID, log_id);
  1619. GELOGD("All reduce node profiling task log id: %ld after", log_id);
  1620. (void) GenerateArProfilingTask(op_desc, log_id + 1, task_def_list);
  1621. string op_name = string(kProfilingArNode) + std::to_string(log_id + 1);
  1622. auto ar_desc_end = MakeShared<OpDesc>(op_name, PROFILINGTRAININGTRACE);
  1623. GE_CHECK_NOTNULL(ar_desc_end);
  1624. ar_desc_end->SetOpKernelLibName(kEngineNameRts);
  1625. node_ptr = compute_graph->AddNode(ar_desc_end);
  1626. GE_CHECK_NOTNULL(node_ptr);
  1627. node_task_map[node_ptr] = task_def_list;
  1628. GELOGD("Create all reduce end profiling node success after.");
  1629. }
  1630. // create bp node
  1631. if (!is_all_reduce && is_insert_bp_profiling_task) {
  1632. vector<domi::TaskDef> task_def_list;
  1633. (void) GenerateBpProfilingTask(op_desc, task_def_list);
  1634. auto bp_op_desc = MakeShared<OpDesc>(kProfilingBpNode, PROFILINGTRAININGTRACE);
  1635. GE_CHECK_NOTNULL(bp_op_desc);
  1636. bp_op_desc->SetOpKernelLibName(kEngineNameRts);
  1637. node_ptr = compute_graph->AddNode(bp_op_desc);
  1638. GE_CHECK_NOTNULL(node_ptr);
  1639. node_task_map[node_ptr] = task_def_list;
  1640. GELOGD("Create bp profiling node success after.");
  1641. }
  1642. // create end node
  1643. bool is_insert_end_profiling_task = false;
  1644. (void)ge::AttrUtils::GetBool(op_desc, ATTR_NAME_INSERT_END_PROFILILNG_TASK, is_insert_end_profiling_task);
  1645. if (is_insert_end_profiling_task) {
  1646. vector<domi::TaskDef> task_def_list;
  1647. (void)GenerateEndProfilingTask(op_desc, task_def_list);
  1648. auto end_desc = MakeShared<OpDesc>(kProfilingEndNode, PROFILINGTRAININGTRACE);
  1649. GE_CHECK_NOTNULL(end_desc);
  1650. end_desc->SetOpKernelLibName(kEngineNameRts);
  1651. node_ptr = compute_graph->AddNode(end_desc);
  1652. GE_CHECK_NOTNULL(node_ptr);
  1653. node_task_map[node_ptr] = task_def_list;
  1654. GELOGD("Create end profiling node success after.");
  1655. }
  1656. if (!node_task_map.empty()) {
  1657. for (const auto &node_task : node_task_map) {
  1658. NodePtr profiling_node = node_task.first;
  1659. vector<domi::TaskDef> task_def_lists = node_task.second;
  1660. for (const auto &task_def : task_def_lists) {
  1661. hybrid_model_.task_defs_[profiling_node].emplace_back(task_def);
  1662. }
  1663. if (op_desc->HasAttr(ATTR_STAGE_LEVEL)) {
  1664. uint32_t stage_level = UINT32_MAX;
  1665. (void)ge::AttrUtils::GetInt(op_desc, ATTR_STAGE_LEVEL, stage_level);
  1666. (void)ge::AttrUtils::SetInt(profiling_node->GetOpDesc(), ATTR_STAGE_LEVEL, stage_level);
  1667. }
  1668. NodeItem *node_item = nullptr;
  1669. GE_CHK_STATUS_RET_NOLOG(GetOrCreateNodeItem(profiling_node, &node_item));
  1670. GE_CHECK_NOTNULL(node_item);
  1671. node_item->input_start = 0;
  1672. node_item->output_start = 0;
  1673. graph_item.node_items_.emplace_back(node_item);
  1674. }
  1675. } else {
  1676. GELOGD("No need to create profiling node after.");
  1677. }
  1678. return SUCCESS;
  1679. }
  1680. Status HybridModelBuilder::LoadDynamicSubgraph(ComputeGraph &graph, bool is_root_graph) {
  1681. GELOGD("Start to load subgraph [%s]", graph.GetName().c_str());
  1682. // for known partitioned call, load all nodes
  1683. auto graph_item = std::unique_ptr<GraphItem>(new(std::nothrow)GraphItem());
  1684. GE_CHECK_NOTNULL(graph_item);
  1685. graph_item->is_dynamic_ = true;
  1686. graph_item->node_items_.reserve(graph.GetDirectNodesSize());
  1687. int input_start = 0;
  1688. int output_start = 0;
  1689. std::vector<NodeItem *> data_nodes;
  1690. for (auto &node : graph.GetDirectNode()) {
  1691. GE_CHECK_NOTNULL(node);
  1692. GE_CHECK_NOTNULL(node->GetOpDesc());
  1693. const auto &op_type = node->GetType();
  1694. if (op_type == NOOP) {
  1695. GELOGD("[%s] Skip NoOp", node->GetName().c_str());
  1696. continue;
  1697. }
  1698. NodeItem *node_item = nullptr;
  1699. GE_CHK_STATUS_RET_NOLOG(GetOrCreateNodeItem(node, &node_item));
  1700. GE_CHK_STATUS_RET_NOLOG(BuildNodeItem(node, *node_item));
  1701. GE_CHK_STATUS_RET_NOLOG(UpdateAnchorStatus(node)); // needed by FE generate task
  1702. node_item->input_start = input_start;
  1703. node_item->output_start = output_start;
  1704. input_start += node_item->num_inputs;
  1705. output_start += node_item->num_outputs;
  1706. if (op_type == DATA_TYPE || op_type == AIPP_DATA_TYPE) {
  1707. data_nodes.emplace_back(node_item);
  1708. } else if (op_type == NETOUTPUT) {
  1709. graph_item->output_node_ = node_item;
  1710. GE_CHK_STATUS_RET_NOLOG(BuildOutputMapping(*graph_item, *node_item, is_root_graph));
  1711. }
  1712. GE_CHK_STATUS_RET_NOLOG(CreateProfilingNodeBefore(*graph_item, node));
  1713. graph_item->node_items_.emplace_back(node_item);
  1714. GE_CHK_STATUS_RET_NOLOG(CreateProfilingNodeAfter(*graph_item, node));
  1715. // parse var outputs
  1716. GE_CHK_STATUS_RET_NOLOG(ParseVarOutputs(*node_item));
  1717. GELOGD("NodeItem created: %s", node_item->DebugString().c_str());
  1718. }
  1719. graph_item->total_inputs_ = input_start;
  1720. graph_item->total_outputs_ = output_start;
  1721. GE_CHK_STATUS_RET_NOLOG(BuildInputMapping(*graph_item, data_nodes, is_root_graph));
  1722. if (is_root_graph) {
  1723. graph_item->SetName("Root-Graph");
  1724. GELOGD("Done loading dynamic subgraph: [%s]", graph_item->GetName().c_str());
  1725. hybrid_model_.root_graph_item_ = std::move(graph_item);
  1726. } else {
  1727. graph_item->SetName(graph.GetName());
  1728. GELOGD("Done loading dynamic subgraph: [%s]", graph_item->GetName().c_str());
  1729. hybrid_model_.subgraph_items_.emplace(graph.GetName(), std::move(graph_item));
  1730. }
  1731. return SUCCESS;
  1732. }
  1733. Status HybridModelBuilder::ParseVarOutputs(NodeItem &node_item) {
  1734. for (int i = 0; i < node_item.num_outputs; ++i) {
  1735. auto output_tensor_desc = node_item.op_desc->GetOutputDesc(i);
  1736. std::string var_name;
  1737. (void) AttrUtils::GetStr(output_tensor_desc, ASSIGN_VAR_NAME, var_name);
  1738. if (!var_name.empty()) {
  1739. auto var_node = hybrid_model_.GetVariableNode(var_name);
  1740. GE_CHECK_NOTNULL(var_node);
  1741. node_item.ref_outputs.emplace(i, var_node);
  1742. }
  1743. }
  1744. return SUCCESS;
  1745. }
  1746. Status HybridModelBuilder::BuildInputMapping(GraphItem &graph_item,
  1747. vector<NodeItem *> &data_nodes,
  1748. bool is_root_graph) {
  1749. uint32_t data_op_index = 0;
  1750. for (auto &node_item : data_nodes) {
  1751. auto node = node_item->node;
  1752. int data_index = data_op_index;
  1753. if (is_root_graph) {
  1754. if (AttrUtils::GetInt(node->GetOpDesc(), ATTR_NAME_INDEX, data_index)) {
  1755. GELOGI("ge_train: get new index %u, old %u", data_index, data_op_index);
  1756. }
  1757. data_op_index++;
  1758. } else {
  1759. if (!AttrUtils::GetInt(node->GetOpDesc(), ATTR_NAME_PARENT_NODE_INDEX, data_index)) {
  1760. GELOGE(FAILED,
  1761. "[%s] Failed to get attr [%s]",
  1762. node->GetName().c_str(),
  1763. ATTR_NAME_PARENT_NODE_INDEX.c_str());
  1764. return FAILED;
  1765. }
  1766. }
  1767. if (graph_item.input_nodes_.size() <= static_cast<size_t>(data_index)) {
  1768. graph_item.input_nodes_.resize(data_index + 1);
  1769. }
  1770. graph_item.input_nodes_[data_index] = node_item;
  1771. }
  1772. return SUCCESS;
  1773. }
  1774. Status HybridModelBuilder::CheckAicpuOpList() {
  1775. std::vector<std::string> aicpu_optype_list;
  1776. std::vector<std::string> aicpu_tf_optype_list;
  1777. std::set<std::string> aicpu_optype_set;
  1778. std::set<std::string> aicpu_tf_optype_set;
  1779. for (auto &it : ge_root_model_->GetSubgraphInstanceNameToModel()) {
  1780. auto &ge_model = it.second;
  1781. GE_CHECK_NOTNULL(ge_model);
  1782. if (ge::AttrUtils::GetListStr(*ge_model, "needCheckCpu", aicpu_optype_list)) {
  1783. aicpu_optype_set.insert(aicpu_optype_list.begin(), aicpu_optype_list.end());
  1784. }
  1785. if (ge::AttrUtils::GetListStr(*ge_model, "needCheckTf", aicpu_tf_optype_list)) {
  1786. aicpu_tf_optype_set.insert(aicpu_tf_optype_list.begin(), aicpu_tf_optype_list.end());
  1787. }
  1788. }
  1789. // reset list with set
  1790. aicpu_optype_list.assign(aicpu_optype_set.begin(), aicpu_optype_set.end());
  1791. aicpu_tf_optype_list.assign(aicpu_tf_optype_set.begin(), aicpu_tf_optype_set.end());
  1792. GE_CHK_STATUS_RET(ModelManager::GetInstance()->LaunchKernelCheckAicpuOp(aicpu_optype_list, aicpu_tf_optype_list),
  1793. "Launch check aicpu op type failed.");
  1794. return SUCCESS;
  1795. }
  1796. } // namespace hybrid
  1797. } // 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