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