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hybrid_model_builder.cc 66 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/new_model_manager/model_utils.h"
  23. #include "graph/manager/graph_var_manager.h"
  24. #include "graph/manager/host_mem_manager.h"
  25. #include "graph/manager/trans_var_data_utils.h"
  26. #if (ENABLE_OPEN_SRC != True)
  27. #include "graph/manager/graph_mem_allocator.h"
  28. #include "graph/manager/host_mem_allocator.h"
  29. #endif
  30. #include "graph/utils/graph_utils.h"
  31. #include "hybrid/common/npu_memory_allocator.h"
  32. #include "hybrid/node_executor/node_executor.h"
  33. namespace ge {
  34. namespace hybrid {
  35. namespace {
  36. const uint32_t kSubgraphIndex = 0U;
  37. const uint32_t kVarOutputIndex = 0U;
  38. const int kBytes = 8;
  39. const char *const kOwnerGraphIsUnknown = "OwnerGraphIsUnknown";
  40. Status SetOutputNameAttr(ComputeGraph &graph) {
  41. vector<string> output_names;
  42. for (const auto &node : graph.GetDirectNode()) {
  43. auto op_desc = node->GetOpDesc();
  44. if (op_desc == nullptr) {
  45. continue;
  46. }
  47. auto op_type = op_desc->GetType();
  48. if (op_type == NETOUTPUT) {
  49. for (InDataAnchorPtr &in_data_anchor : node->GetAllInDataAnchors()) {
  50. const OutDataAnchorPtr &peer_out_anchor = in_data_anchor->GetPeerOutAnchor();
  51. GE_IF_BOOL_EXEC(peer_out_anchor == nullptr, continue);
  52. NodePtr in_node = peer_out_anchor->GetOwnerNode();
  53. GE_CHECK_NOTNULL(in_node);
  54. output_names.push_back(in_node->GetName());
  55. }
  56. }
  57. }
  58. GE_CHK_BOOL_EXEC(ge::AttrUtils::SetListStr(&graph, ATTR_MODEL_OUT_NODES_NAME, output_names),
  59. GELOGE(FAILED, "SetListStr of ATTR_MODEL_OUT_NODES_NAME failed.");
  60. return FAILED);
  61. return SUCCESS;
  62. }
  63. int64_t CalcVarSizeInBytes(const GeTensorDesc &desc) {
  64. int64_t var_size = 0;
  65. auto data_type = desc.GetDataType();
  66. if (data_type == DT_STRING) {
  67. (void) TensorUtils::GetSize(desc, var_size);
  68. return var_size;
  69. }
  70. if (TensorUtils::GetTensorMemorySizeInBytes(desc, var_size) != GRAPH_SUCCESS) {
  71. GELOGW("Failed to calc var data size");
  72. return -1;
  73. }
  74. return var_size;
  75. }
  76. Status CollectDependenciesForFusedGraph(NodeItem &node_item, std::set<OpDesc *> &data_ops) {
  77. for (const auto &node : node_item.fused_subgraph->nodes) {
  78. auto op_desc = node->GetOpDesc();
  79. GE_CHECK_NOTNULL(op_desc);
  80. const auto &depends = op_desc->GetOpInferDepends();
  81. if (depends.empty()) {
  82. continue;
  83. }
  84. for (auto &input_name : depends) {
  85. auto input_index = op_desc->GetInputIndexByName(input_name);
  86. auto src_node = NodeUtils::GetInDataNodeByIndex(*node, input_index);
  87. GE_CHECK_NOTNULL(src_node);
  88. auto src_op_desc = src_node->GetOpDesc();
  89. GE_CHECK_NOTNULL(src_op_desc);
  90. if (src_node->GetType() != DATA_TYPE) {
  91. GELOGE(UNSUPPORTED,
  92. "[%s::%s] Node in fused subgraph can only depend on Data nodes, but depend on %s",
  93. node_item.NodeName().c_str(),
  94. node->GetName().c_str(),
  95. src_node->GetType().c_str());
  96. return UNSUPPORTED;
  97. }
  98. data_ops.emplace(src_op_desc.get());
  99. }
  100. }
  101. return SUCCESS;
  102. }
  103. } // namespace
  104. HybridModelBuilder::HybridModelBuilder(HybridModel &hybrid_model)
  105. : hybrid_model_(hybrid_model), runtime_param_(hybrid_model.root_runtime_param_) {
  106. ge_root_model_ = hybrid_model_.ge_root_model_;
  107. }
  108. Status HybridModelBuilder::Build() {
  109. GE_CHK_STATUS_RET(ValidateParams(), "Failed to validate GeRootModel");
  110. hybrid_model_.model_name_ = ge_root_model_->GetRootGraph()->GetName();
  111. GELOGI("[%s] Start to build hybrid model.", GetGraphName());
  112. GE_CHK_STATUS_RET(InitRuntimeParams(), "[%s] Failed to InitRuntimeParams", GetGraphName());
  113. GE_CHK_STATUS_RET(RecoverGraphUnknownFlag(), "[%s] Failed to RecoverGraphUnknownFlag", GetGraphName());
  114. GE_CHK_STATUS_RET(IndexSpecialNodes(), "[%s] Failed to index nodes", GetGraphName());
  115. GE_CHK_STATUS_RET(IndexTaskDefs(), "[%s] Failed to index task defs", GetGraphName());
  116. GE_CHK_STATUS_RET(LoadGraph(), "[%s] Failed to load graph", GetGraphName());
  117. GE_CHK_STATUS_RET(AssignUninitializedConstantOps(), "[%s] Failed to assign uninitialized constants", GetGraphName());
  118. GE_CHK_STATUS_RET(TransAllVarData(), "[%s] Failed to trans all var data", GetGraphName());
  119. GE_CHK_STATUS_RET(CopyVarData(), "[%s] Failed to copy var data", GetGraphName());
  120. GE_CHK_STATUS_RET(InitModelMem(), "[%s] Failed to init memory", GetGraphName());
  121. GE_CHK_STATUS_RET(InitWeights(), "[%s] Failed to init weights", GetGraphName());
  122. GE_CHK_STATUS_RET(InitConstantOps(), "[%s] Failed to init constant op", GetGraphName());
  123. GE_CHK_STATUS_RET(InitVariableTensors(), "[%s] Failed to init variables", GetGraphName());
  124. GE_CHK_STATUS_RET(LoadTasks(), "[%s] Failed to load tasks", GetGraphName());
  125. GELOGI("[%s] Done building hybrid model successfully.", GetGraphName());
  126. return SUCCESS;
  127. }
  128. Status HybridModelBuilder::ValidateParams() {
  129. GE_CHECK_NOTNULL(ge_root_model_);
  130. GE_CHECK_NOTNULL(ge_root_model_->GetRootGraph());
  131. return SUCCESS;
  132. }
  133. Status HybridModelBuilder::BuildNodeItem(const NodePtr &node, NodeItem &node_item) {
  134. auto op_desc = node->GetOpDesc();
  135. vector<string> dependencies = node->GetOpDesc()->GetOpInferDepends();
  136. GE_CHK_STATUS_RET(ParseDependentInputNodes(node_item, dependencies),
  137. "[%s] Failed to parse node dependencies.",
  138. node_item.NodeName().c_str());
  139. node_item.outputs.resize(node_item.num_outputs);
  140. for (int i = 0; i < node_item.num_outputs; ++i) {
  141. auto out_data_anchor = node->GetOutDataAnchor(i);
  142. if (out_data_anchor == nullptr) {
  143. GELOGE(INTERNAL_ERROR, "out anchor[%d] of node %s is nullptr", i, node->GetName().c_str());
  144. return INTERNAL_ERROR;
  145. }
  146. for (auto &dst_in_anchor: out_data_anchor->GetPeerInDataAnchors()) {
  147. auto dst_node = dst_in_anchor->GetOwnerNode();
  148. if (dst_node == nullptr) {
  149. GELOGW("dst node is nullptr. out anchor = %d", out_data_anchor->GetIdx());
  150. continue;
  151. }
  152. NodeItem *dst_node_item = nullptr;
  153. GE_CHK_STATUS_RET(GetOrCreateNodeItem(dst_node, &dst_node_item),
  154. "[%s] Failed to get or create node item.",
  155. dst_node->GetName().c_str());
  156. int canonical_index;
  157. GE_CHK_STATUS_RET(dst_node_item->GetCanonicalInputIndex(dst_in_anchor->GetIdx(), canonical_index),
  158. "[%s] Failed to canonical input index",
  159. dst_node->GetName().c_str());
  160. node_item.outputs[i].emplace_back(canonical_index, dst_node_item);
  161. }
  162. }
  163. GE_CHK_STATUS_RET_NOLOG(ResolveRefIo(node_item));
  164. return SUCCESS;
  165. }
  166. Status HybridModelBuilder::ResolveRefIo(NodeItem &node_item) {
  167. bool is_ref = false;
  168. auto &op_desc = *node_item.op_desc;
  169. (void) AttrUtils::GetBool(op_desc, ATTR_NAME_REFERENCE, is_ref);
  170. if (!is_ref) {
  171. return SUCCESS;
  172. }
  173. auto inputs = op_desc.GetAllInputName();
  174. auto outputs = op_desc.GetAllOutputName();
  175. for (auto &output : outputs) {
  176. for (auto &input : inputs) {
  177. if (input.first == output.first) {
  178. int input_idx;
  179. GE_CHK_STATUS_RET_NOLOG(node_item.GetCanonicalInputIndex(input.second, input_idx));
  180. auto output_idx = static_cast<int>(output.second);
  181. node_item.reuse_inputs[output_idx] = input_idx;
  182. GELOGD("[%s] Output[%d] reuse input[%d]", node_item.NodeName().c_str(), output_idx, input_idx);
  183. }
  184. }
  185. }
  186. return SUCCESS;
  187. }
  188. Status HybridModelBuilder::GetOrCreateNodeItem(const NodePtr &node, NodeItem **node_item) {
  189. auto &node_items = hybrid_model_.node_items_;
  190. auto it = node_items.find(node);
  191. if (it != node_items.end()) {
  192. *node_item = it->second.get();
  193. return SUCCESS;
  194. }
  195. std::unique_ptr<NodeItem> new_node;
  196. GE_CHK_STATUS_RET(NodeItem::Create(node, new_node), "Failed to create node item");
  197. GE_CHK_STATUS_RET_NOLOG(NodeExecutorManager::GetInstance().GetExecutor(*node, &new_node->node_executor));
  198. // we do not need L2 Buffer
  199. const char *const kIsFirstNode = "is_first_node";
  200. const char *const kIsLastNode = "is_last_node";
  201. (void) AttrUtils::SetBool(new_node->op_desc, kIsFirstNode, false);
  202. (void) AttrUtils::SetBool(new_node->op_desc, kIsLastNode, false);
  203. new_node->node_id = node_index;
  204. new_node->op_desc->SetId(node_index);
  205. node_index += 1;
  206. NodeExecutorManager::ExecutorType executor_type = NodeExecutorManager::GetInstance().ResolveExecutorType(*node);
  207. new_node->is_profiling_report = (executor_type == NodeExecutorManager::ExecutorType::AICORE) ||
  208. (executor_type == NodeExecutorManager::ExecutorType::AICPU_TF) ||
  209. (executor_type == NodeExecutorManager::ExecutorType::AICPU_CUSTOM);
  210. *node_item = new_node.get();
  211. node_items[node] = std::move(new_node);
  212. return SUCCESS;
  213. }
  214. Status HybridModelBuilder::ParseDependentInputNodes(NodeItem &node_item, const std::vector<string> &dependencies) {
  215. std::set<NodePtr> dependent_input_nodes;
  216. auto &ge_node = node_item.node;
  217. bool is_hccl_op =
  218. NodeExecutorManager::GetInstance().ResolveExecutorType(*ge_node) == NodeExecutorManager::ExecutorType::HCCL;
  219. // The input tensors become valid after computation is done for parent nodes of type DEPEND_COMPUTE.
  220. // Wait for these parent nodes before execution.
  221. for (const auto &in_anchor : ge_node->GetAllInDataAnchors()) {
  222. const auto &peer_anchor = in_anchor->GetPeerOutAnchor();
  223. if (peer_anchor == nullptr) {
  224. GELOGD("[%s] Input[%d] do not have peer anchor", node_item.NodeName().c_str(), in_anchor->GetIdx());
  225. continue;
  226. }
  227. auto src_node = peer_anchor->GetOwnerNode();
  228. GE_CHECK_NOTNULL(src_node);
  229. auto src_node_item = MutableNodeItem(src_node);
  230. GE_CHECK_NOTNULL(src_node_item);
  231. if (is_hccl_op) {
  232. GELOGD("[%s] Add input data dependent node [%s] due to engine type is HCCL",
  233. node_item.NodeName().c_str(),
  234. src_node_item->NodeName().c_str());
  235. src_node_item->has_observer = true;
  236. node_item.dependents_for_execution.emplace_back(src_node);
  237. } else if (src_node_item->shape_inference_type == DEPEND_COMPUTE) {
  238. GELOGD("[%s] Add input data dependent node [%s] due to inference type = DEPEND_COMPUTE",
  239. node_item.NodeName().c_str(),
  240. src_node_item->NodeName().c_str());
  241. src_node_item->has_observer = true;
  242. node_item.dependents_for_execution.emplace_back(src_node);
  243. }
  244. if (src_node_item->shape_inference_type == DEPEND_SHAPE_RANGE) {
  245. GELOGD("[%s] Add input shape dependent node [%s] due to inference type = DEPEND_SHAPE_RANGE",
  246. node_item.NodeName().c_str(),
  247. src_node_item->NodeName().c_str());
  248. src_node_item->has_observer = true;
  249. dependent_input_nodes.emplace(src_node);
  250. }
  251. }
  252. // cond or branch need to be prepared before the execution of IF or CASE
  253. if (node_item.node_type == IF || node_item.node_type == STATELESSIF || node_item.node_type == CASE) {
  254. const auto &in_anchor = ge_node->GetInDataAnchor(0);
  255. GE_CHECK_NOTNULL(in_anchor);
  256. const auto &peer_anchor = in_anchor->GetPeerOutAnchor();
  257. GE_CHECK_NOTNULL(peer_anchor);
  258. auto src_node = peer_anchor->GetOwnerNode();
  259. GE_CHECK_NOTNULL(src_node);
  260. auto src_node_item = MutableNodeItem(src_node);
  261. GE_CHECK_NOTNULL(src_node_item);
  262. src_node_item->has_observer = true;
  263. node_item.dependents_for_execution.emplace_back(src_node);
  264. GELOGD("[%s] Dependent added from %s for control op's cond/branch",
  265. node_item.NodeName().c_str(),
  266. src_node_item->NodeName().c_str());
  267. }
  268. for (const auto &input_name : dependencies) {
  269. int input_index = node_item.op_desc->GetInputIndexByName(input_name);
  270. if (input_index < 0) {
  271. GELOGE(INTERNAL_ERROR,
  272. "[%s] Failed to get input index by name: %s",
  273. node_item.NodeName().c_str(),
  274. input_name.c_str());
  275. return INTERNAL_ERROR;
  276. }
  277. const auto &in_anchor = ge_node->GetInDataAnchor(input_index);
  278. GE_CHECK_NOTNULL(in_anchor);
  279. const auto &peer_out_anchor = in_anchor->GetPeerOutAnchor();
  280. GE_CHECK_NOTNULL(peer_out_anchor);
  281. const auto &src_node = peer_out_anchor->GetOwnerNode();
  282. GE_CHECK_NOTNULL(src_node);
  283. auto src_node_item = MutableNodeItem(src_node);
  284. src_node_item->to_const_output_id_list.emplace(peer_out_anchor->GetIdx());
  285. src_node_item->has_observer = true;
  286. dependent_input_nodes.emplace(src_node);
  287. GELOGD("[%s] Dependent added from output of [%s:%d]",
  288. node_item.NodeName().c_str(),
  289. src_node_item->NodeName().c_str(),
  290. peer_out_anchor->GetIdx());
  291. }
  292. for (const auto &dep_node : dependent_input_nodes) {
  293. node_item.dependents_for_shape_inference.emplace_back(dep_node);
  294. }
  295. GE_CHK_STATUS_RET(ParseDependentForFusedSubgraph(node_item));
  296. return SUCCESS;
  297. }
  298. Status HybridModelBuilder::ParseDependentForFusedSubgraph(NodeItem &node_item) {
  299. if (node_item.fused_subgraph == nullptr) {
  300. return SUCCESS;
  301. }
  302. std::set<OpDesc *> data_ops;
  303. GE_CHK_STATUS_RET_NOLOG(CollectDependenciesForFusedGraph(node_item, data_ops));
  304. for (auto &op_desc : data_ops) {
  305. uint32_t parent_index = 0;
  306. if (!AttrUtils::GetInt(*op_desc, ATTR_NAME_PARENT_NODE_INDEX, parent_index)) {
  307. GELOGE(INTERNAL_ERROR,
  308. "[%s] Failed to get attr [%s]",
  309. op_desc->GetName().c_str(),
  310. ATTR_NAME_PARENT_NODE_INDEX.c_str());
  311. return INTERNAL_ERROR;
  312. }
  313. const auto &in_anchor = node_item.node->GetInDataAnchor(parent_index);
  314. GE_CHECK_NOTNULL(in_anchor);
  315. const auto &peer_out_anchor = in_anchor->GetPeerOutAnchor();
  316. GE_CHECK_NOTNULL(peer_out_anchor);
  317. const auto &src_node = peer_out_anchor->GetOwnerNode();
  318. GE_CHECK_NOTNULL(src_node);
  319. NodeItem *src_node_item = nullptr;
  320. GE_CHK_STATUS_RET_NOLOG(GetOrCreateNodeItem(src_node, &src_node_item));
  321. op_desc->SetId(src_node_item->op_desc->GetId());
  322. GELOGD("[%s::%s] Node id was set to that of outer src node's, src_node = %s",
  323. node_item.NodeName().c_str(),
  324. op_desc->GetName().c_str(),
  325. src_node_item->NodeName().c_str());
  326. src_node_item->has_observer = true;
  327. src_node_item->to_const_output_id_list.emplace(peer_out_anchor->GetIdx());
  328. auto &depends = node_item.dependents_for_shape_inference;
  329. if (std::find(depends.begin(), depends.end(), src_node) == depends.end()) {
  330. depends.emplace_back(src_node);
  331. GELOGD("[%s] Dependent added from output of [%s:%d]",
  332. node_item.NodeName().c_str(),
  333. src_node_item->NodeName().c_str(),
  334. peer_out_anchor->GetIdx());
  335. }
  336. }
  337. return SUCCESS;
  338. }
  339. Status HybridModelBuilder::UpdateAnchorStatus(const NodePtr &node) {
  340. if (NodeUtils::SetAllAnchorStatus(node) != GRAPH_SUCCESS) {
  341. GELOGE(INTERNAL_ERROR, "[%s] NodeUtils::SetAllAnchorStatus failed.", node->GetName().c_str());
  342. return INTERNAL_ERROR;
  343. }
  344. for (auto &anchor : node->GetAllInDataAnchors()) {
  345. auto peer_anchor = anchor->GetPeerOutAnchor();
  346. if (peer_anchor == nullptr) {
  347. if (AnchorUtils::SetStatus(anchor, ANCHOR_SUSPEND) != GRAPH_SUCCESS) {
  348. GELOGE(INTERNAL_ERROR, "[%s] AnchorUtils::SetStatus failed.", node->GetName().c_str());
  349. return INTERNAL_ERROR;
  350. }
  351. } else if (peer_anchor->GetOwnerNode()->GetType() == CONSTANT) {
  352. if (AnchorUtils::SetStatus(anchor, ANCHOR_CONST) != GRAPH_SUCCESS) {
  353. GELOGE(INTERNAL_ERROR, "[%s] AnchorUtils::SetStatus failed.", node->GetName().c_str());
  354. return INTERNAL_ERROR;
  355. }
  356. } else {
  357. if (AnchorUtils::SetStatus(anchor, ANCHOR_DATA) != GRAPH_SUCCESS) {
  358. GELOGE(INTERNAL_ERROR, "[%s] AnchorUtils::SetStatus failed.", node->GetName().c_str());
  359. return INTERNAL_ERROR;
  360. }
  361. }
  362. }
  363. return SUCCESS;
  364. }
  365. Status HybridModelBuilder::DoUnlinkDataAnchors(const OutDataAnchorPtr &out_data_anchor,
  366. const InDataAnchorPtr &in_data_anchor) {
  367. GE_CHK_GRAPH_STATUS_RET(out_data_anchor->Unlink(in_data_anchor), "Failed to unlink %s:%d from %s:%d",
  368. out_data_anchor->GetOwnerNode()->GetName().c_str(),
  369. out_data_anchor->GetIdx(),
  370. in_data_anchor->GetOwnerNode()->GetName().c_str(),
  371. in_data_anchor->GetIdx());
  372. GELOGD("Succeeded in unlinking %s:%d from %s:%d",
  373. out_data_anchor->GetOwnerNode()->GetName().c_str(),
  374. out_data_anchor->GetIdx(),
  375. in_data_anchor->GetOwnerNode()->GetName().c_str(),
  376. in_data_anchor->GetIdx());
  377. return SUCCESS;
  378. }
  379. Status HybridModelBuilder::DoLinkDataAnchors(OutDataAnchorPtr &out_data_anchor, InDataAnchorPtr &in_data_anchor) {
  380. GE_CHK_GRAPH_STATUS_RET(out_data_anchor->LinkTo(in_data_anchor), "Failed to link %s:%d to %s:%d",
  381. out_data_anchor->GetOwnerNode()->GetName().c_str(),
  382. out_data_anchor->GetIdx(),
  383. in_data_anchor->GetOwnerNode()->GetName().c_str(),
  384. in_data_anchor->GetIdx());
  385. GELOGD("Succeeded in linking %s:%d to %s:%d",
  386. out_data_anchor->GetOwnerNode()->GetName().c_str(),
  387. out_data_anchor->GetIdx(),
  388. in_data_anchor->GetOwnerNode()->GetName().c_str(),
  389. in_data_anchor->GetIdx());
  390. return SUCCESS;
  391. }
  392. Status HybridModelBuilder::MergeInputNodes(ComputeGraph &graph) {
  393. const auto &wrapped_node = graph.GetParentNode();
  394. std::set<NodePtr> root_nodes;
  395. for (const auto &node : graph.GetDirectNode()) {
  396. GE_CHECK_NOTNULL(node);
  397. if (node->GetType() != DATA_TYPE) {
  398. if (node->GetInDataNodes().empty()) {
  399. root_nodes.emplace(node);
  400. }
  401. continue;
  402. }
  403. auto data_op_desc = node->GetOpDesc();
  404. GE_CHECK_NOTNULL(data_op_desc);
  405. uint32_t parent_index = 0;
  406. if (!AttrUtils::GetInt(data_op_desc, ATTR_NAME_PARENT_NODE_INDEX, parent_index)) {
  407. GELOGE(FAILED,
  408. "[%s] Failed to get attr [%s]",
  409. data_op_desc->GetName().c_str(),
  410. ATTR_NAME_PARENT_NODE_INDEX.c_str());
  411. return FAILED;
  412. }
  413. auto wrapped_node_in_anchor = wrapped_node->GetInDataAnchor(parent_index);
  414. GE_CHECK_NOTNULL(wrapped_node_in_anchor);
  415. auto src_out_anchor = wrapped_node_in_anchor->GetPeerOutAnchor();
  416. if (src_out_anchor == nullptr || src_out_anchor->GetOwnerNode() == nullptr) {
  417. continue;
  418. }
  419. wrapped_node_in_anchor->UnlinkAll();
  420. // link src to outputs of DataNode
  421. for (auto &out_data_anchor : node->GetAllOutDataAnchors()) {
  422. GE_CHECK_NOTNULL(out_data_anchor);
  423. for (auto &peer_in_data_anchor : out_data_anchor->GetPeerInDataAnchors()) {
  424. auto dst_node = peer_in_data_anchor->GetOwnerNode();
  425. GE_CHECK_NOTNULL(dst_node);
  426. root_nodes.emplace(dst_node);
  427. GE_CHK_STATUS_RET_NOLOG(DoUnlinkDataAnchors(out_data_anchor, peer_in_data_anchor));
  428. GE_CHK_STATUS_RET_NOLOG(DoLinkDataAnchors(src_out_anchor, peer_in_data_anchor));
  429. }
  430. }
  431. }
  432. // transfer in control edges to all root nodes
  433. for (auto &root_node : root_nodes) {
  434. auto in_nodes = root_node->GetInAllNodes();
  435. std::set<NodePtr> in_node_set(in_nodes.begin(), in_nodes.end());
  436. for (auto &in_control_node : wrapped_node->GetInControlNodes()) {
  437. if (in_node_set.count(in_control_node) == 0) {
  438. GELOGD("[%s] Restore control edge to [%s]", in_control_node->GetName().c_str(), root_node->GetName().c_str());
  439. GE_CHECK_NOTNULL(in_control_node->GetOutControlAnchor());
  440. (void) in_control_node->GetOutControlAnchor()->LinkTo(root_node->GetInControlAnchor());
  441. }
  442. }
  443. }
  444. wrapped_node->GetInControlAnchor()->UnlinkAll();
  445. return SUCCESS;
  446. }
  447. Status HybridModelBuilder::MergeNetOutputNode(ComputeGraph &graph) {
  448. const auto &parent_node = graph.GetParentNode();
  449. const NodePtr &net_output_node = graph.FindFirstNodeMatchType(NETOUTPUT);
  450. if (net_output_node == nullptr) {
  451. GELOGD("Graph has no netoutput no need to merge.");
  452. return SUCCESS;
  453. }
  454. const auto &net_output_desc = net_output_node->GetOpDesc();
  455. GE_CHECK_NOTNULL(net_output_desc);
  456. auto all_in_nodes = net_output_node->GetInAllNodes();
  457. auto all_out_nodes = parent_node->GetOutAllNodes();
  458. net_output_node->GetInControlAnchor()->UnlinkAll();
  459. parent_node->GetOutControlAnchor()->UnlinkAll();
  460. for (const auto &in_data_anchor : net_output_node->GetAllInDataAnchors()) {
  461. auto src_out_anchor = in_data_anchor->GetPeerOutAnchor();
  462. GE_CHECK_NOTNULL(src_out_anchor);
  463. GE_CHECK_NOTNULL(src_out_anchor->GetOwnerNode());
  464. GE_CHK_STATUS_RET_NOLOG(DoUnlinkDataAnchors(src_out_anchor, in_data_anchor));
  465. auto index = in_data_anchor->GetIdx();
  466. auto input_desc = net_output_desc->MutableInputDesc(index);
  467. if (input_desc == nullptr) {
  468. GELOGE(INTERNAL_ERROR, "[%s] Failed to get input desc[%d]", net_output_desc->GetName().c_str(), index);
  469. return INTERNAL_ERROR;
  470. }
  471. uint32_t parent_index = 0;
  472. if (!AttrUtils::GetInt(input_desc, ATTR_NAME_PARENT_NODE_INDEX, parent_index)) {
  473. GELOGW("SubGraph: %s NetOutput input tensor %d, attr %s not found.",
  474. graph.GetName().c_str(), index, ATTR_NAME_PARENT_NODE_INDEX.c_str());
  475. continue;
  476. }
  477. const OutDataAnchorPtr &parent_out_anchor = parent_node->GetOutDataAnchor(parent_index);
  478. GE_CHECK_NOTNULL(parent_out_anchor);
  479. for (InDataAnchorPtr &dst_in_anchor : parent_out_anchor->GetPeerInDataAnchors()) {
  480. if (dst_in_anchor == nullptr) {
  481. continue;
  482. }
  483. GE_CHECK_NOTNULL(dst_in_anchor->GetOwnerNode());
  484. GE_CHK_STATUS_RET_NOLOG(DoUnlinkDataAnchors(parent_out_anchor, dst_in_anchor));
  485. GE_CHK_STATUS_RET_NOLOG(DoLinkDataAnchors(src_out_anchor, dst_in_anchor));
  486. }
  487. }
  488. // transfer out control edges
  489. std::set<NodePtr> in_node_set(all_in_nodes.begin(), all_in_nodes.end());
  490. std::set<NodePtr> out_node_set(all_out_nodes.begin(), all_out_nodes.end());
  491. for (auto &src_node : in_node_set) {
  492. GELOGD("[%s] process in node.", src_node->GetName().c_str());
  493. auto out_nodes = src_node->GetOutAllNodes();
  494. std::set<NodePtr> node_set(out_nodes.begin(), out_nodes.end());
  495. for (auto &dst_node : out_node_set) {
  496. if (node_set.count(dst_node) == 0) {
  497. src_node->GetOutControlAnchor()->LinkTo(dst_node->GetInControlAnchor());
  498. GELOGD("[%s] Restore control edge to [%s]", src_node->GetName().c_str(), dst_node->GetName().c_str());
  499. }
  500. }
  501. }
  502. return SUCCESS;
  503. }
  504. Status HybridModelBuilder::UnfoldSubgraphs(ComputeGraph &root_graph, ComputeGraphPtr &merged_graph) {
  505. merged_graph = MakeShared<ComputeGraph>("MergedGraph");
  506. for (const auto &node : root_graph.GetDirectNode()) {
  507. GE_CHECK_NOTNULL(node);
  508. auto op_desc = node->GetOpDesc();
  509. GE_CHECK_NOTNULL(op_desc);
  510. const auto &op_type = node->GetType();
  511. if (op_type != PARTITIONEDCALL) {
  512. merged_graph->AddNode(node);
  513. GELOGD("[%s] Node added to merged graph.", op_desc->GetName().c_str());
  514. continue;
  515. }
  516. auto subgraph = NodeUtils::GetSubgraph(*node, kSubgraphIndex);
  517. GE_CHECK_NOTNULL(subgraph);
  518. bool is_unknown_shape = subgraph->GetGraphUnknownFlag();
  519. if (!is_unknown_shape) {
  520. merged_graph->AddNode(node);
  521. GELOGD("[%s] Known shape partitioned call added to merged graph.", op_desc->GetName().c_str());
  522. continue;
  523. }
  524. GE_CHK_GRAPH_STATUS_RET(UnfoldSubgraph(root_graph, *merged_graph, *subgraph),
  525. "[%s] Failed to merge subgraph.",
  526. subgraph->GetName().c_str());
  527. }
  528. // invoke before adding subgraphs. in case modify node id in known-shaped subgraphs.
  529. GE_CHK_GRAPH_STATUS_RET(merged_graph->TopologicalSorting(), "Failed to invoke TopologicalSorting on merged graph.");
  530. for (auto &remained_subgraph : root_graph.GetAllSubgraphs()) {
  531. GELOGD("Adding subgraph [%s] to merged-graph.", remained_subgraph->GetName().c_str());
  532. GE_CHK_GRAPH_STATUS_RET(merged_graph->AddSubgraph(remained_subgraph),
  533. "Failed to add subgraph [%s]",
  534. remained_subgraph->GetName().c_str());
  535. }
  536. return SUCCESS;
  537. }
  538. Status HybridModelBuilder::UnfoldSubgraph(ComputeGraph &root_graph,
  539. ComputeGraph &parent_graph,
  540. ComputeGraph &sub_graph) {
  541. auto parent_node = sub_graph.GetParentNode();
  542. GE_CHECK_NOTNULL(parent_node);
  543. GE_CHK_STATUS_RET(MergeInputNodes(sub_graph),
  544. "[%s] Failed to merge data nodes for subgraph",
  545. sub_graph.GetName().c_str());
  546. GE_CHK_STATUS_RET(MergeNetOutputNode(sub_graph),
  547. "[%s] Failed to merge net output nodes for subgraph",
  548. sub_graph.GetName().c_str());
  549. GELOGD("[%s] Done merging subgraph inputs and outputs successfully.", sub_graph.GetName().c_str());
  550. for (auto &sub_node : sub_graph.GetDirectNode()) {
  551. auto sub_op_type = sub_node->GetType();
  552. if (sub_op_type == DATA_TYPE || sub_op_type == NETOUTPUT) {
  553. continue;
  554. }
  555. if (sub_op_type == PARTITIONEDCALL) {
  556. auto sub_sub_graph = NodeUtils::GetSubgraph(*sub_node, kSubgraphIndex);
  557. GE_CHECK_NOTNULL(sub_sub_graph);
  558. if (sub_sub_graph->GetGraphUnknownFlag()) {
  559. GE_CHK_STATUS_RET(UnfoldSubgraph(root_graph, parent_graph, *sub_sub_graph),
  560. "[%s] Failed to merge subgraph",
  561. sub_sub_graph->GetName().c_str());
  562. continue;
  563. }
  564. }
  565. parent_graph.AddNode(sub_node);
  566. GELOGD("[%s::%s] added to parent graph: [%s].",
  567. sub_graph.GetName().c_str(),
  568. sub_node->GetName().c_str(),
  569. parent_graph.GetName().c_str());
  570. }
  571. GELOGD("[%s] Done merging subgraph. remove it from root graph.", sub_graph.GetName().c_str());
  572. root_graph.RemoveSubgraph(sub_graph.GetName());
  573. return SUCCESS;
  574. }
  575. Status HybridModelBuilder::BuildOutputMapping(GraphItem &graph_item,
  576. const NodeItem &node_item,
  577. bool is_root_graph) {
  578. auto output_size = node_item.num_inputs;
  579. graph_item.output_edges_.resize(output_size);
  580. for (auto &in_data_anchor : node_item.node->GetAllInDataAnchors()) {
  581. auto peer_out_anchor = in_data_anchor->GetPeerOutAnchor();
  582. GE_CHECK_NOTNULL(peer_out_anchor);
  583. auto src_node = peer_out_anchor->GetOwnerNode();
  584. GE_CHECK_NOTNULL(src_node);
  585. auto src_node_item = GetNodeItem(src_node);
  586. GE_CHECK_NOTNULL(src_node_item);
  587. auto output_idx = in_data_anchor->GetIdx();
  588. auto output_offset = src_node_item->output_start + peer_out_anchor->GetIdx();
  589. GELOGI("Output[%d], node = %s, output_index = %d, output_offset = %d ",
  590. output_idx,
  591. src_node_item->NodeName().c_str(),
  592. peer_out_anchor->GetIdx(),
  593. output_offset);
  594. GE_CHECK_LE(output_idx, output_size - 1);
  595. graph_item.output_edges_[output_idx] = {src_node_item, peer_out_anchor->GetIdx()};
  596. }
  597. if (!is_root_graph) {
  598. for (uint32_t i = 0; i < static_cast<uint32_t>(output_size); ++i) {
  599. uint32_t p_index = i;
  600. // Net output of Subgraph of while do not have parent index
  601. if (AttrUtils::GetInt(node_item.op_desc->GetInputDesc(i), ATTR_NAME_PARENT_NODE_INDEX, p_index)) {
  602. GELOGD("[%s] Parent index not set for input[%u].", node_item.NodeName().c_str(), i);
  603. }
  604. graph_item.output_index_mapping_.emplace_back(p_index);
  605. }
  606. }
  607. return SUCCESS;
  608. }
  609. Status HybridModelBuilder::LoadGraph() {
  610. auto root_graph = ge_root_model_->GetRootGraph();
  611. if (!GetContext().GetHostExecFlag()) {
  612. std::shared_ptr<ComputeGraph> merged_graph;
  613. GELOGI("Before merging subgraphs DirectNodesSize = %zu, GetAllNodesSize = %zu",
  614. root_graph->GetDirectNodesSize(),
  615. root_graph->GetAllNodesSize());
  616. GE_CHK_GRAPH_STATUS_RET(UnfoldSubgraphs(*root_graph, merged_graph), "Failed to unfold subgraphs.");
  617. root_graph = std::move(merged_graph);
  618. GELOGI("After merging subgraphs DirectNodesSize = %zu, GetAllNodesSize = %zu",
  619. root_graph->GetDirectNodesSize(),
  620. root_graph->GetAllNodesSize());
  621. GE_DUMP(root_graph, "hybrid_merged_graph");
  622. }
  623. GE_CHK_STATUS_RET(LoadDynamicSubgraph(*root_graph, true), "Failed to load root graph.");
  624. GELOGD("Done loading root graph successfully.");
  625. for (auto &sub_graph : root_graph->GetAllSubgraphs()) {
  626. GE_CHECK_NOTNULL(sub_graph);
  627. GELOGD("Start to load subgraph [%s]", sub_graph->GetName().c_str());
  628. auto parent_node = sub_graph->GetParentNode();
  629. GE_CHECK_NOTNULL(parent_node);
  630. auto parent_node_item = MutableNodeItem(parent_node);
  631. // parent node is in another known subgraph
  632. if (parent_node_item == nullptr) {
  633. GELOGD("[%s] Subgraph is in another known shaped subgraph, skip it.", sub_graph->GetName().c_str());
  634. continue;
  635. }
  636. if (sub_graph->GetGraphUnknownFlag()) {
  637. GE_CHK_STATUS_RET(LoadDynamicSubgraph(*sub_graph, false),
  638. "Failed to load subgraph: [%s]",
  639. sub_graph->GetName().c_str());
  640. } else {
  641. GE_CHK_STATUS_RET(IdentifyVariableOutputs(*parent_node_item),
  642. "[%s] Failed to identify ref outputs.",
  643. parent_node_item->NodeName().c_str());
  644. GE_CHK_STATUS_RET(IdentifySameInputs(*parent_node_item),
  645. "[%s] Failed to identify same outputs.",
  646. parent_node_item->NodeName().c_str());
  647. // if parent is function control op. need add a virtual partitioned call
  648. if (parent_node_item->IsControlOp()) {
  649. GE_CHK_STATUS_RET(LoadKnownShapedSubgraph(*sub_graph, parent_node_item),
  650. "Failed to load function control op subgraph [%s]",
  651. sub_graph->GetName().c_str());
  652. }
  653. }
  654. }
  655. GELOGI("Done loading all subgraphs successfully.");
  656. return SUCCESS;
  657. }
  658. const NodeItem *HybridModelBuilder::GetNodeItem(const NodePtr &node) const {
  659. return hybrid_model_.GetNodeItem(node);
  660. }
  661. NodeItem *HybridModelBuilder::MutableNodeItem(const NodePtr &node) {
  662. return hybrid_model_.MutableNodeItem(node);
  663. }
  664. Status HybridModelBuilder::VarNodeToTensor(const NodePtr &var_node, std::unique_ptr<TensorValue> &tensor) {
  665. string var_name = var_node->GetName();
  666. auto tensor_desc = var_node->GetOpDesc()->MutableOutputDesc(0);
  667. uint8_t *var_logic = nullptr;
  668. GE_CHK_STATUS_RET(var_manager_->GetVarAddr(var_name, *tensor_desc, &var_logic),
  669. "Failed to get var addr. var_name = %s, session_id = %ld",
  670. var_name.c_str(),
  671. hybrid_model_.GetSessionId());
  672. uint8_t *dev_mem = var_manager_->GetVarMemoryAddr(var_logic, RT_MEMORY_HBM);
  673. if (dev_mem == nullptr) {
  674. GELOGE(INTERNAL_ERROR,
  675. "Failed to copy var %s from device, cant not get "
  676. "var addr from logic addr %p",
  677. var_node->GetName().c_str(), var_logic);
  678. return INTERNAL_ERROR;
  679. }
  680. int64_t var_size = CalcVarSizeInBytes(*tensor_desc);
  681. // var size is only for checking, will not allocate any memory by it
  682. tensor.reset(new(std::nothrow)TensorValue(dev_mem, static_cast<size_t>(var_size)));
  683. GE_CHECK_NOTNULL(tensor);
  684. return SUCCESS;
  685. }
  686. Status HybridModelBuilder::HandleDtString(const GeTensor &tensor, void *var_addr) {
  687. auto desc = tensor.GetTensorDesc();
  688. if (desc.GetDataType() == DT_STRING) {
  689. GeShape tensor_shape = desc.GetShape();
  690. /// if tensor is a scaler, it's shape size if zero, according ge_tensor.cc.
  691. /// the logic of GetShapeSize is wrong, the scaler tensor's GetShapeSize is zero
  692. /// and that of unknown shape is zero too.
  693. /// unknown shape will not appear here, so we can use zero judge a tensor is scalar or not
  694. int64_t elem_num = tensor_shape.GetShapeSize();
  695. if (elem_num == 0 && tensor_shape.GetDims().empty()) {
  696. elem_num = 1;
  697. }
  698. auto &mutable_tensor = const_cast<GeTensor &>(tensor);
  699. uint64_t *buff = reinterpret_cast<uint64_t *>(mutable_tensor.MutableData().data());
  700. GE_CHK_BOOL_RET_STATUS(ge::CheckInt64Uint32MulOverflow(elem_num, kBytes) == SUCCESS, FAILED,
  701. "Shape size is invalid");
  702. auto offset = static_cast<uint64_t>(elem_num * kBytes);
  703. auto hbm_raw_data_base_addr =
  704. static_cast<uint64_t>(reinterpret_cast<uintptr_t>(var_addr) + offset);
  705. for (int64_t i = elem_num - 1; i >= 0; --i) {
  706. buff[i] = hbm_raw_data_base_addr + (buff[i] - buff[0]);
  707. }
  708. }
  709. return SUCCESS;
  710. }
  711. Status HybridModelBuilder::AssignUninitializedConstantOps() {
  712. if (GetContext().GetHostExecFlag()) {
  713. GELOGI("no need to assign when exec on host.");
  714. return SUCCESS;
  715. }
  716. for (auto &it : hybrid_model_.constant_op_nodes_) {
  717. const string &var_name = it.first;
  718. const NodePtr &var_node = it.second;
  719. auto tensor_desc = var_node->GetOpDesc()->MutableOutputDesc(0);
  720. if (!var_manager_->IsVarExist(var_name, *tensor_desc)) {
  721. // allocate constant
  722. GELOGD("[%s] Constant not allocated during graph building. now allocate it.", var_name.c_str());
  723. GE_CHK_STATUS_RET(var_manager_->AssignVarMem(var_name, *tensor_desc, RT_MEMORY_HBM));
  724. GE_CHK_STATUS_RET(var_manager_->SetAllocatedGraphId(var_name, runtime_param_.graph_id));
  725. }
  726. }
  727. for (auto &it : hybrid_model_.device_variable_nodes_) {
  728. const string &var_name = it.first;
  729. const NodePtr &var_node = it.second;
  730. auto tensor_desc = var_node->GetOpDesc()->MutableOutputDesc(0);
  731. if (!var_manager_->IsVarExist(var_name, *tensor_desc)) {
  732. // allocate constant
  733. GELOGD("[%s] Constant not allocated during graph building. now allocate it.", var_name.c_str());
  734. GE_CHK_STATUS_RET(var_manager_->AssignVarMem(var_name, *tensor_desc, RT_MEMORY_HBM));
  735. GE_CHK_STATUS_RET(VarMemAssignUtil::AssignData2Fp32Var(var_node, runtime_param_.session_id))
  736. GE_CHK_STATUS_RET(var_manager_->SetAllocatedGraphId(var_name, runtime_param_.graph_id));
  737. }
  738. }
  739. return SUCCESS;
  740. }
  741. Status HybridModelBuilder::InitConstantOps() {
  742. for (auto &it : hybrid_model_.constant_op_nodes_) {
  743. const string &var_name = it.first;
  744. const NodePtr &var_node = it.second;
  745. auto op_desc = var_node->GetOpDesc();
  746. auto v_weights = ModelUtils::GetWeights(op_desc);
  747. if (v_weights.empty()) {
  748. GELOGE(INTERNAL_ERROR, "[%s] Constant no not have value", var_node->GetName().c_str());
  749. return INTERNAL_ERROR;
  750. }
  751. auto *ge_tensor = const_cast<GeTensor *>(v_weights[0].get());
  752. std::unique_ptr<TensorValue> var_tensor;
  753. if (GetContext().GetHostExecFlag()) {
  754. #if (ENABLE_OPEN_SRC != True)
  755. GE_CHECK_NOTNULL(ge_tensor);
  756. // Address for eigen kernel should be aligned with 16 bytes
  757. // Tensors return by api GetWeights share data with proto, whose addr is not confirmed to be aligned
  758. GeTensor aligned_tensor = ge_tensor->Clone();
  759. GELOGD("Init tensor with host constant %s size = %zu", var_name.c_str(), aligned_tensor.MutableData().GetSize());
  760. if (MemManager::Instance().HostMemInstance(RT_MEMORY_HBM).Malloc(aligned_tensor.GetAlignedPtr(),
  761. aligned_tensor.GetData().size()) == nullptr) {
  762. GELOGE(MEMALLOC_FAILED, "Malloc host memory for an existed GeTensor failed.");
  763. return MEMALLOC_FAILED;
  764. }
  765. var_tensor.reset(new(std::nothrow)TensorValue(aligned_tensor.MutableData().data(),
  766. aligned_tensor.GetData().size()));
  767. #else
  768. auto buffer = ge_tensor->MutableData();
  769. GELOGD("Init tensor with host constant. size = %zu", buffer.GetSize());
  770. var_tensor.reset(new(std::nothrow)TensorValue(buffer.GetData(), buffer.GetSize()));
  771. #endif
  772. } else {
  773. GE_CHK_STATUS_RET_NOLOG(VarNodeToTensor(var_node, var_tensor));
  774. GELOGD("Init const op tensor. name = %s, size = %ld", var_name.c_str(), var_tensor->GetSize());
  775. var_tensor->SetName("ConstOp_" + var_name);
  776. auto v_output_size = var_tensor->GetSize();
  777. auto v_output_addr = var_tensor->MutableData();
  778. if (ge_tensor->GetData().size() > 0) {
  779. GE_CHK_STATUS_RET_NOLOG(HandleDtString(*ge_tensor, v_output_addr));
  780. GELOGI("[IMAS]InitConstant memcpy graph_%u type[V] name[%s] output[%d] memaddr[%p] mem_size[%zu] datasize[%zu]",
  781. runtime_param_.graph_id, op_desc->GetName().c_str(), 0, v_output_addr, v_output_size,
  782. ge_tensor->GetData().size());
  783. GE_CHK_RT_RET(rtMemcpy(v_output_addr, v_output_size, ge_tensor->GetData().data(), ge_tensor->GetData().size(),
  784. RT_MEMCPY_HOST_TO_DEVICE));
  785. } else {
  786. GELOGI("[%s] Const op has no weight data.", op_desc->GetName().c_str());
  787. }
  788. }
  789. hybrid_model_.variable_tensors_.emplace(var_name, std::move(var_tensor));
  790. }
  791. return SUCCESS;
  792. }
  793. Status HybridModelBuilder::InitVariableTensors() {
  794. for (auto &it : hybrid_model_.device_variable_nodes_) {
  795. string var_name = it.first;
  796. NodePtr &var_node = it.second;
  797. std::unique_ptr<TensorValue> tensor;
  798. GE_CHK_STATUS_RET_NOLOG(VarNodeToTensor(var_node, tensor));
  799. GELOGD("Init variable tensor. name = %s, size = %ld, addr = %p",
  800. var_name.c_str(),
  801. tensor->GetSize(),
  802. tensor->GetData());
  803. tensor->SetName("Var_" + var_name);
  804. hybrid_model_.variable_tensors_.emplace(var_name, std::move(tensor));
  805. }
  806. for (const auto &it : hybrid_model_.host_variable_nodes_) {
  807. auto op_desc = it.second->GetOpDesc();
  808. GE_CHECK_NOTNULL(op_desc);
  809. GeTensorDesc output_tensor = op_desc->GetOutputDesc(0);
  810. int64_t tensor_size = 0;
  811. if (TensorUtils::CalcTensorMemSize(output_tensor.GetShape(), output_tensor.GetFormat(), output_tensor.GetDataType(),
  812. tensor_size) != SUCCESS) {
  813. GELOGE(INTERNAL_ERROR, "Calculate variable size failed, node name:%s", it.first.c_str());
  814. return INTERNAL_ERROR;
  815. }
  816. SharedMemInfo mem_info(it.first, tensor_size);
  817. if (HostMemManager::Instance().MallocSharedMemory(mem_info) != SUCCESS) {
  818. GELOGE(GE_GRAPH_MALLOC_FAILED, "Host variable [%s] malloc failed.", it.first.c_str());
  819. return GE_GRAPH_MALLOC_FAILED;
  820. }
  821. #if (ENABLE_OPEN_SRC != True)
  822. if (MemManager::Instance().HostMemInstance(RT_MEMORY_HBM).Malloc(mem_info.host_aligned_ptr,
  823. tensor_size) == nullptr) {
  824. GELOGE(MEMALLOC_FAILED, "Malloc host memory for an existed GeTensor failed.");
  825. return MEMALLOC_FAILED;
  826. }
  827. GELOGD("Host variable [%s] malloc success, host_addr=%p, dev_addr=%p, size=%lld.",
  828. it.first.c_str(), mem_info.host_aligned_ptr->Get(), mem_info.device_address, tensor_size);
  829. std::unique_ptr<TensorValue> tensor(new (std::nothrow) TensorValue(mem_info.host_aligned_ptr->MutableGet(),
  830. tensor_size));
  831. #else
  832. GELOGD("Host variable [%s] malloc success.", it.first.c_str());
  833. std::unique_ptr<TensorValue> tensor(new (std::nothrow) TensorValue(mem_info.host_address, tensor_size));
  834. #endif
  835. GE_CHECK_NOTNULL(tensor);
  836. hybrid_model_.variable_tensors_.emplace(it.first, std::move(tensor));
  837. }
  838. return SUCCESS;
  839. }
  840. Status HybridModelBuilder::InitWeights() {
  841. // Train do not have weight. (only got ConstOp)
  842. return SUCCESS;
  843. }
  844. Status HybridModelBuilder::LoadTasks() {
  845. for (auto &it : hybrid_model_.node_items_) {
  846. auto &node_item = it.second;
  847. auto &node_ptr = node_item->node;
  848. if (node_item->node_type == NETOUTPUT) {
  849. continue;
  850. }
  851. GELOGD("[%s] Start to build kernel task", node_ptr->GetName().c_str());
  852. auto load_ret = node_item->node_executor->LoadTask(hybrid_model_,
  853. node_ptr,
  854. node_item->kernel_task);
  855. if (load_ret != UNSUPPORTED && load_ret != SUCCESS) {
  856. GELOGE(load_ret, "[%s] Failed to load task", node_ptr->GetName().c_str());
  857. return load_ret;
  858. }
  859. GELOGD("[%s] Done loading task successfully.", node_ptr->GetName().c_str());
  860. }
  861. return SUCCESS;
  862. }
  863. Status HybridModelBuilder::LoadGeModel(ComputeGraph &sub_graph, const GeModelPtr &ge_model) {
  864. auto parent_node = sub_graph.GetParentNode();
  865. GE_CHECK_NOTNULL(parent_node);
  866. auto op_type = parent_node->GetType();
  867. if (IsControlOp(op_type)) {
  868. GELOGD("Set ge_model for control op subgraph: [%s], task_size = %d",
  869. sub_graph.GetName().c_str(),
  870. ge_model->GetModelTaskDefPtr()->task_size());
  871. subgraph_models_.emplace(sub_graph.GetName(), ge_model);
  872. } else {
  873. GELOGD("Set ge_model for subgraph: [%s], task_size = %d",
  874. sub_graph.GetName().c_str(),
  875. ge_model->GetModelTaskDefPtr()->task_size());
  876. hybrid_model_.known_shape_sub_models_.emplace(parent_node, ge_model);
  877. }
  878. return SUCCESS;
  879. }
  880. Status HybridModelBuilder::IndexTaskDefs() {
  881. const auto &root_graph = ge_root_model_->GetRootGraph();
  882. if (SetOutputNameAttr(*root_graph) != SUCCESS) {
  883. GELOGW("Set output name attr failed.");
  884. }
  885. for (auto &it : ge_root_model_->GetSubgraphInstanceNameToModel()) {
  886. auto &name = it.first;
  887. auto &ge_model = it.second;
  888. GE_CHECK_NOTNULL(ge_model);
  889. const auto &sub_graph = root_graph->GetSubgraph(name);
  890. if (sub_graph == nullptr) {
  891. continue;
  892. }
  893. bool is_unknown_shape = sub_graph->GetGraphUnknownFlag();
  894. if (!is_unknown_shape) {
  895. GE_CHK_STATUS_RET_NOLOG(LoadGeModel(*sub_graph, ge_model));
  896. continue;
  897. }
  898. // index task defs
  899. GELOGD("To index tasks for subgraph: %s", name.c_str());
  900. std::unordered_map<int64_t, NodePtr> node_map;
  901. for (const auto &node : sub_graph->GetDirectNode()) {
  902. GE_CHECK_NOTNULL(node);
  903. GE_CHECK_NOTNULL(node->GetOpDesc());
  904. auto node_id = node->GetOpDesc()->GetId();
  905. GELOGD("op_index = %ld, node_name = %s", node_id, node->GetName().c_str());
  906. node_map.emplace(node_id, node);
  907. }
  908. auto tasks = ge_model->GetModelTaskDefPtr()->task();
  909. for (int i = 0; i < tasks.size(); ++i) {
  910. const domi::TaskDef &task_def = tasks[i];
  911. GELOGI("Task id = %d, task type = %d", i, task_def.type());
  912. auto task_type = static_cast<rtModelTaskType_t>(task_def.type());
  913. uint32_t op_index = -1;
  914. if (task_type == RT_MODEL_TASK_KERNEL) {
  915. op_index = task_def.kernel().context().op_index();
  916. } else if (task_type == RT_MODEL_TASK_KERNEL_EX) {
  917. op_index = task_def.kernel_ex().op_index();
  918. } else if (task_type == RT_MODEL_TASK_HCCL) {
  919. op_index = task_def.kernel_hccl().op_index();
  920. } else {
  921. GELOGD("Skip task type: %d", static_cast<int>(task_type));
  922. continue;
  923. }
  924. auto iter = node_map.find(op_index);
  925. if (iter == node_map.end()) {
  926. GELOGE(INTERNAL_ERROR, "Failed to get node by index = %u", op_index);
  927. return INTERNAL_ERROR;
  928. }
  929. auto &node = iter->second;
  930. if (task_type == RT_MODEL_TASK_KERNEL) {
  931. ge_model->GetTBEKernelStore().LoadTBEKernelBinToOpDesc(node->GetOpDesc());
  932. }
  933. GELOGD("Task loaded for node: %s, task type = %d, op_index = %u", node->GetName().c_str(), task_type, op_index);
  934. hybrid_model_.task_defs_[node].emplace_back(task_def);
  935. }
  936. }
  937. return SUCCESS;
  938. }
  939. Status HybridModelBuilder::IndexSpecialNodes() {
  940. GELOGD("Start to index special nodes");
  941. const auto &root_graph = ge_root_model_->GetRootGraph();
  942. for (auto &node : root_graph->GetAllNodes()) {
  943. GE_CHECK_NOTNULL(node);
  944. GE_CHECK_NOTNULL(node->GetOpDesc());
  945. auto op_type = node->GetType();
  946. GELOGD("node name = %s, node type = %s", node->GetName().c_str(), node->GetType().c_str());
  947. if (op_type == VARIABLE) {
  948. string placement;
  949. (void) AttrUtils::GetStr(node->GetOpDesc(), ATTR_VARIABLE_PLACEMENT, placement);
  950. if (placement == "host") {
  951. hybrid_model_.host_variable_nodes_.emplace(node->GetName(), node);
  952. } else {
  953. hybrid_model_.device_variable_nodes_.emplace(node->GetName(), node);
  954. }
  955. } else if (op_type == CONSTANTOP) {
  956. hybrid_model_.constant_op_nodes_.emplace(node->GetName(), node);
  957. } else if (op_type == DATA && node->GetOwnerComputeGraph() != root_graph) {
  958. NodePtr src_node;
  959. int peer_out_index = -1;
  960. GE_CHK_STATUS_RET_NOLOG(GetPeerNodeAcrossSubGraphs(node, src_node, peer_out_index));
  961. GELOGD("Got peer node for data node %s, peer node = %s(%s)",
  962. node->GetName().c_str(),
  963. src_node->GetName().c_str(),
  964. src_node->GetType().c_str());
  965. auto src_op_type = src_node->GetType();
  966. if (src_op_type == CONSTANTOP || src_op_type == VARIABLE) {
  967. for (auto &dst_node_and_in_anchor : node->GetOutDataNodesAndAnchors()) {
  968. auto &dst_node = dst_node_and_in_anchor.first;
  969. auto &in_anchor = dst_node_and_in_anchor.second;
  970. node_ref_inputs_[dst_node].emplace_back(std::make_pair(in_anchor->GetIdx(), src_node));
  971. }
  972. }
  973. }
  974. }
  975. return SUCCESS;
  976. }
  977. Status HybridModelBuilder::GetPeerNodeAcrossSubGraphs(const NodePtr &data_node,
  978. NodePtr &peer_node,
  979. int &peer_out_index) {
  980. auto sub_graph = data_node->GetOwnerComputeGraph();
  981. GE_CHECK_NOTNULL(sub_graph);
  982. GELOGD("To get peer node of %s::%s", sub_graph->GetName().c_str(), data_node->GetName().c_str());
  983. auto wrapped_node = data_node->GetOwnerComputeGraph()->GetParentNode();
  984. if (wrapped_node == nullptr) {
  985. GELOGE(INTERNAL_ERROR, "[%s] Node is in root graph.", data_node->GetName().c_str());
  986. return INTERNAL_ERROR;
  987. }
  988. auto data_op_desc = data_node->GetOpDesc();
  989. uint32_t parent_index = 0;
  990. if (!AttrUtils::GetInt(data_op_desc, ATTR_NAME_PARENT_NODE_INDEX, parent_index)) {
  991. GELOGE(INTERNAL_ERROR,
  992. "[%s] Failed to get attr [%s]",
  993. data_op_desc->GetName().c_str(),
  994. ATTR_NAME_PARENT_NODE_INDEX.c_str());
  995. return INTERNAL_ERROR;
  996. }
  997. auto wrapped_node_in_anchor = wrapped_node->GetInDataAnchor(parent_index);
  998. GE_CHECK_NOTNULL(wrapped_node_in_anchor);
  999. auto src_out_anchor = wrapped_node_in_anchor->GetPeerOutAnchor();
  1000. if (src_out_anchor == nullptr || src_out_anchor->GetOwnerNode() == nullptr) {
  1001. GELOGE(INTERNAL_ERROR, "[%s] Parent node do not have peer anchor.", data_node->GetName().c_str());
  1002. return INTERNAL_ERROR;
  1003. }
  1004. auto src_wrapped_node_out_anchor = wrapped_node_in_anchor->GetPeerOutAnchor();
  1005. GE_CHECK_NOTNULL(src_wrapped_node_out_anchor);
  1006. auto src_wrapped_node = src_wrapped_node_out_anchor->GetOwnerNode();
  1007. GE_CHECK_NOTNULL(src_wrapped_node);
  1008. // connected to root-graph's DATA
  1009. auto src_node_type = src_wrapped_node->GetType();
  1010. if (src_node_type != PARTITIONEDCALL) {
  1011. peer_node = src_wrapped_node;
  1012. peer_out_index = kVarOutputIndex;
  1013. GELOGD("[%s] Node is connected to root graph's node: %s",
  1014. data_node->GetName().c_str(),
  1015. peer_node->GetName().c_str());
  1016. return SUCCESS;
  1017. }
  1018. auto src_graph = NodeUtils::GetSubgraph(*src_wrapped_node, kSubgraphIndex);
  1019. GE_CHECK_NOTNULL(src_graph);
  1020. auto src_net_output_node = src_graph->FindFirstNodeMatchType(NETOUTPUT);
  1021. GE_CHK_BOOL_TRUE_EXEC_WITH_LOG(src_net_output_node == nullptr,
  1022. return INTERNAL_ERROR,
  1023. "Failed to find NetOutput in subgraph: %s",
  1024. src_graph->GetName().c_str());
  1025. auto net_output_desc = src_net_output_node->GetOpDesc();
  1026. GE_CHECK_NOTNULL(net_output_desc);
  1027. auto out_index = static_cast<uint32_t>(src_wrapped_node_out_anchor->GetIdx());
  1028. GELOGD("src graph = %s, src parent output index = %u", src_graph->GetName().c_str(), out_index);
  1029. // link src to outputs of DataNode
  1030. auto input_size = net_output_desc->GetAllInputsSize();
  1031. GE_CHECK_LE(input_size, UINT32_MAX);
  1032. for (uint32_t i = 0; i < static_cast<uint32_t>(input_size); ++i) {
  1033. uint32_t p_index = 0;
  1034. if (!AttrUtils::GetInt(net_output_desc->GetInputDesc(i), ATTR_NAME_PARENT_NODE_INDEX, p_index)) {
  1035. GELOGW("SubGraph: %s input tensor %u attr %s not found.",
  1036. src_graph->GetName().c_str(), i, ATTR_NAME_PARENT_NODE_INDEX.c_str());
  1037. continue;
  1038. }
  1039. GELOGD("NetOutput's input[%u], parent_node_index = %u", i, p_index);
  1040. if (p_index == out_index) {
  1041. auto in_anchor = src_net_output_node->GetInDataAnchor(i);
  1042. GE_CHECK_NOTNULL(in_anchor);
  1043. auto peer_out_anchor = in_anchor->GetPeerOutAnchor();
  1044. GE_CHECK_NOTNULL(peer_out_anchor);
  1045. peer_node = peer_out_anchor->GetOwnerNode();
  1046. GE_CHECK_NOTNULL(peer_node);
  1047. peer_out_index = peer_out_anchor->GetIdx();
  1048. GELOGD("Found peer node of Data node: %s::%s is %s::%s",
  1049. sub_graph->GetName().c_str(),
  1050. data_node->GetName().c_str(),
  1051. src_graph->GetName().c_str(),
  1052. peer_node->GetName().c_str());
  1053. return SUCCESS;
  1054. }
  1055. }
  1056. GELOGE(FAILED,
  1057. "Failed to find peer node for %s::%s",
  1058. sub_graph->GetName().c_str(),
  1059. data_node->GetName().c_str());
  1060. return FAILED;
  1061. }
  1062. Status HybridModelBuilder::InitRuntimeParams() {
  1063. int64_t value = 0;
  1064. bool ret = false;
  1065. if (ge_root_model_->GetSubgraphInstanceNameToModel().empty()) {
  1066. GELOGE(INTERNAL_ERROR, "Root model has no sub model");
  1067. return INTERNAL_ERROR;
  1068. }
  1069. // session id and var size is same for every model
  1070. auto first_model = ge_root_model_->GetSubgraphInstanceNameToModel().begin()->second;
  1071. ret = ge::AttrUtils::GetInt(first_model, ge::MODEL_ATTR_SESSION_ID, value);
  1072. runtime_param_.session_id = ret ? static_cast<uint64_t>(value) : 0;
  1073. ret = ge::AttrUtils::GetInt(first_model, ATTR_MODEL_TASK_GEN_VAR_ADDR, value);
  1074. runtime_param_.logic_var_base = ret ? static_cast<uint64_t>(value) : 0;
  1075. runtime_param_.graph_id = ge_root_model_->GetRootGraph()->GetGraphID();
  1076. value = 0;
  1077. for (auto &it : ge_root_model_->GetSubgraphInstanceNameToModel()) {
  1078. (void) ge::AttrUtils::GetInt(it.second, ATTR_MODEL_VAR_SIZE, value);
  1079. if (value > 0) {
  1080. runtime_param_.var_size = static_cast<uint64_t>(value);
  1081. break;
  1082. }
  1083. }
  1084. GELOGI("InitRuntimeParams(), session_id:%lu, var_size:%lu. graph_id = %u",
  1085. runtime_param_.session_id, runtime_param_.var_size, runtime_param_.graph_id);
  1086. var_manager_ = VarManager::Instance(runtime_param_.session_id);
  1087. GE_CHECK_NOTNULL(var_manager_);
  1088. return SUCCESS;
  1089. }
  1090. Status HybridModelBuilder::IdentifySameInputs(NodeItem &node_item) {
  1091. GELOGD("Start to parse same inputs on net output: %s", node_item.NodeName().c_str());
  1092. auto subgraph = NodeUtils::GetSubgraph(*node_item.node, kSubgraphIndex);
  1093. GE_CHECK_NOTNULL(subgraph);
  1094. auto net_output_node = subgraph->FindFirstNodeMatchType(NETOUTPUT);
  1095. if (net_output_node == nullptr) {
  1096. GELOGD("Subgraph [%s] does not have net output", subgraph->GetName().c_str());
  1097. return SUCCESS;
  1098. }
  1099. auto net_output_desc = net_output_node->GetOpDesc();
  1100. GE_CHECK_NOTNULL(net_output_desc);
  1101. std::map<std::string, int> connected_inputs;
  1102. for (const auto &in_data_anchor : net_output_node->GetAllInDataAnchors()) {
  1103. auto out_data_anchor = in_data_anchor->GetPeerOutAnchor();
  1104. if (out_data_anchor == nullptr) {
  1105. continue;
  1106. }
  1107. auto src_node = out_data_anchor->GetOwnerNode();
  1108. GE_CHECK_NOTNULL(src_node);
  1109. auto op_desc = src_node->GetOpDesc();
  1110. GE_CHECK_NOTNULL(op_desc);
  1111. std::string input_key = std::to_string(op_desc->GetId()) + "_" + std::to_string(out_data_anchor->GetIdx());
  1112. auto it = connected_inputs.find(input_key);
  1113. if (it == connected_inputs.end()) {
  1114. connected_inputs.emplace(input_key, in_data_anchor->GetIdx());
  1115. } else {
  1116. GELOGD("[%s] output [%d] reuse output [%d] input node = %s, idx = %d.", node_item.NodeName().c_str(),
  1117. in_data_anchor->GetIdx(),
  1118. it->second,
  1119. src_node->GetName().c_str(),
  1120. out_data_anchor->GetIdx());
  1121. node_item.reuse_outputs.emplace(in_data_anchor->GetIdx(), it->second);
  1122. }
  1123. }
  1124. return SUCCESS;
  1125. }
  1126. Status HybridModelBuilder::IdentifyVariableOutputs(NodeItem &node_item) {
  1127. GELOGD("Start to parse outputs of node: %s", node_item.NodeName().c_str());
  1128. auto subgraph = NodeUtils::GetSubgraph(*node_item.node, kSubgraphIndex);
  1129. GE_CHECK_NOTNULL(subgraph);
  1130. auto net_output_node = subgraph->FindFirstNodeMatchType(NETOUTPUT);
  1131. if (net_output_node == nullptr) {
  1132. GELOGD("[%s] Subgraph do not got net output", subgraph->GetName().c_str());
  1133. return SUCCESS;
  1134. }
  1135. auto net_output_desc = net_output_node->GetOpDesc();
  1136. GE_CHECK_NOTNULL(net_output_desc);
  1137. // constant/variable connected to net output
  1138. for (const auto &in_data_anchor : net_output_node->GetAllInDataAnchors()) {
  1139. auto src_node = GetPeerNode(in_data_anchor);
  1140. GE_CHECK_NOTNULL(src_node);
  1141. auto src_op_type = src_node->GetType();
  1142. GELOGD("Node %s, output %d, src node = %s, src node type = %s",
  1143. node_item.NodeName().c_str(),
  1144. in_data_anchor->GetIdx(),
  1145. src_node->GetName().c_str(),
  1146. src_op_type.c_str());
  1147. if (src_op_type != CONSTANTOP && src_op_type != VARIABLE) {
  1148. continue;
  1149. }
  1150. uint32_t parent_index = 0;
  1151. GE_CHK_STATUS_RET_NOLOG(GetParentNodeOutputIndex(*net_output_desc, in_data_anchor->GetIdx(), parent_index));
  1152. GELOGD("Got parent output index = %u", parent_index);
  1153. GE_CHECK_LE(parent_index, INT32_MAX);
  1154. node_item.ref_outputs.emplace(static_cast<int>(parent_index), src_node);
  1155. }
  1156. // Data nodes marked with REF_VAR_SRC_VAR_NAME
  1157. // Using variable tensor as data's output
  1158. for (auto &node : subgraph->GetDirectNode()) {
  1159. if (node->GetType() != DATA) {
  1160. continue;
  1161. }
  1162. string ref_var_name;
  1163. (void) AttrUtils::GetStr(node->GetOpDesc(), REF_VAR_SRC_VAR_NAME, ref_var_name);
  1164. if (ref_var_name.empty()) {
  1165. continue;
  1166. }
  1167. GELOGD("Data node ref to variable: %s", ref_var_name.c_str());
  1168. NodePtr src_node;
  1169. auto var_node = hybrid_model_.GetVariableNode(ref_var_name);
  1170. GE_CHECK_NOTNULL(var_node);
  1171. GELOGD("Found var node [%s] by ref_var_name [%s]", var_node->GetName().c_str(), ref_var_name.c_str());
  1172. int peer_output_index = -1;
  1173. GE_CHK_STATUS_RET_NOLOG(GetPeerNodeAcrossSubGraphs(node, src_node, peer_output_index));
  1174. auto src_node_item = MutableNodeItem(src_node);
  1175. GE_CHECK_NOTNULL(src_node_item);
  1176. src_node_item->ref_outputs.emplace(peer_output_index, var_node);
  1177. }
  1178. return SUCCESS;
  1179. }
  1180. NodePtr HybridModelBuilder::GetPeerNode(const InDataAnchorPtr &in_data_anchor) {
  1181. auto peer_out_anchor = in_data_anchor->GetPeerOutAnchor();
  1182. if (peer_out_anchor != nullptr) {
  1183. return peer_out_anchor->GetOwnerNode();
  1184. }
  1185. return nullptr;
  1186. }
  1187. Status HybridModelBuilder::GetParentNodeOutputIndex(const OpDesc &op_desc, int index, uint32_t &out_index) {
  1188. auto input_desc = op_desc.MutableInputDesc(index);
  1189. GE_CHECK_NOTNULL(input_desc);
  1190. if (!AttrUtils::GetInt(input_desc, ATTR_NAME_PARENT_NODE_INDEX, out_index)) {
  1191. GELOGE(INTERNAL_ERROR, "NetOutput input tensor %d, attr %s not found.",
  1192. index, ATTR_NAME_PARENT_NODE_INDEX.c_str());
  1193. return INTERNAL_ERROR;
  1194. }
  1195. return SUCCESS;
  1196. }
  1197. Status HybridModelBuilder::InitModelMem() {
  1198. hybrid_model_.var_mem_base_ = var_manager_->GetVarMemoryBase(RT_MEMORY_HBM);
  1199. auto total_var_size = hybrid_model_.TotalVarMemSize();
  1200. if (total_var_size == 0 && !hybrid_model_.constant_op_nodes_.empty()) {
  1201. total_var_size = var_manager_->GetVarMemSize(RT_MEMORY_HBM) > 0 ? var_manager_->GetVarMemMaxSize() : 0;
  1202. GELOGD("Model var size = 0. but got uninitialized constant. set var size to %zu.", total_var_size);
  1203. }
  1204. if (total_var_size > 0 && hybrid_model_.var_mem_base_ == nullptr) {
  1205. GE_CHK_STATUS_RET(var_manager_->MallocVarMemory(total_var_size),
  1206. "Malloc Var Memory Fail.");
  1207. hybrid_model_.var_mem_base_ = var_manager_->GetVarMemoryBase(RT_MEMORY_HBM);
  1208. }
  1209. runtime_param_.var_base = hybrid_model_.var_mem_base_;
  1210. return SUCCESS;
  1211. }
  1212. Status HybridModelBuilder::TransAllVarData() {
  1213. GELOGI("TransAllVarData start: session_id:%lu, graph_id: %u.", runtime_param_.session_id, runtime_param_.graph_id);
  1214. rtContext_t ctx = nullptr;
  1215. rtError_t rt_ret = rtCtxGetCurrent(&ctx);
  1216. if (rt_ret != RT_ERROR_NONE) {
  1217. GELOGE(RT_FAILED, "Failed to get current context, error_code is: 0x%X.", rt_ret);
  1218. return RT_FAILED;
  1219. }
  1220. std::vector<NodePtr> variable_node_list;
  1221. for (auto &it : hybrid_model_.device_variable_nodes_) {
  1222. variable_node_list.emplace_back(it.second);
  1223. GELOGD("[%s] added for trans var data", it.first.c_str());
  1224. }
  1225. GE_CHK_STATUS_RET(TransVarDataUtils::TransAllVarData(variable_node_list,
  1226. runtime_param_.session_id,
  1227. ctx,
  1228. runtime_param_.graph_id),
  1229. "TransAllVarData failed.");
  1230. GELOGI("TransAllVarData success.");
  1231. return SUCCESS;
  1232. }
  1233. Status HybridModelBuilder::CopyVarData() {
  1234. GE_CHK_STATUS_RET(TransVarDataUtils::CopyVarData(ge_root_model_->GetRootGraph(),
  1235. runtime_param_.session_id,
  1236. hybrid_model_.device_id_),
  1237. "CopyVarData failed.");
  1238. GELOGI("CopyVarData success.");
  1239. return SUCCESS;
  1240. }
  1241. Status HybridModelBuilder::LoadKnownShapedSubgraph(ComputeGraph &graph, NodeItem *parent_node_item) {
  1242. GELOGD("Start to load known shaped subgraph [%s]", graph.GetName().c_str());
  1243. auto graph_item = std::unique_ptr<GraphItem>(new(std::nothrow)GraphItem());
  1244. GE_CHECK_NOTNULL(graph_item);
  1245. graph_item->is_dynamic_ = false;
  1246. auto subgraph_name = graph.GetName();
  1247. auto wrapper_op_desc = MakeShared<OpDesc>(subgraph_name + "_partitioned_call", PARTITIONEDCALL);
  1248. GE_CHECK_NOTNULL(wrapper_op_desc);
  1249. for (auto &node : graph.GetDirectNode()) {
  1250. GE_CHECK_NOTNULL(node);
  1251. auto op_desc = node->GetOpDesc();
  1252. GE_CHECK_NOTNULL(op_desc);
  1253. const auto &op_type = node->GetType();
  1254. if (op_type == DATA) {
  1255. int32_t data_index = 0;
  1256. if (!AttrUtils::GetInt(node->GetOpDesc(), ATTR_NAME_PARENT_NODE_INDEX, data_index)) {
  1257. GELOGE(FAILED,
  1258. "[%s] Failed to get attr [%s]",
  1259. node->GetName().c_str(),
  1260. ATTR_NAME_PARENT_NODE_INDEX.c_str());
  1261. return FAILED;
  1262. }
  1263. (void) wrapper_op_desc->AddInputDesc(op_desc->GetInputDesc(0));
  1264. graph_item->input_index_mapping_.emplace_back(data_index);
  1265. } else if (op_type == NETOUTPUT) {
  1266. int output_index = 0;
  1267. for (const auto &output_desc : op_desc->GetAllInputsDescPtr()) {
  1268. int32_t data_index = output_index++;
  1269. if (!AttrUtils::GetInt(output_desc, ATTR_NAME_PARENT_NODE_INDEX, data_index)) {
  1270. GELOGI("[%s] Failed to get attr [%s]", node->GetName().c_str(), ATTR_NAME_PARENT_NODE_INDEX.c_str());
  1271. }
  1272. GE_CHK_GRAPH_STATUS_RET(wrapper_op_desc->AddOutputDesc(*output_desc),
  1273. "[%s] Failed to add output desc. output index = %d",
  1274. graph.GetName().c_str(),
  1275. output_index);
  1276. graph_item->output_index_mapping_.emplace_back(data_index);
  1277. }
  1278. }
  1279. }
  1280. auto temp_graph = MakeShared<ComputeGraph>("temp");
  1281. GE_CHECK_NOTNULL(temp_graph);
  1282. auto wrapper_node = temp_graph->AddNode(wrapper_op_desc);
  1283. GeModelPtr ge_model = subgraph_models_[subgraph_name];
  1284. GE_CHECK_NOTNULL(ge_model);
  1285. hybrid_model_.known_shape_sub_models_.emplace(wrapper_node, ge_model);
  1286. NodeItem *node_item = nullptr;
  1287. GE_CHK_STATUS_RET_NOLOG(GetOrCreateNodeItem(wrapper_node, &node_item));
  1288. node_item->input_start = 0;
  1289. node_item->output_start = 0;
  1290. node_item->outputs.resize(node_item->num_outputs);
  1291. graph_item->node_items_.emplace_back(node_item);
  1292. graph_item->output_node_ = node_item;
  1293. graph_item->total_inputs_ = node_item->num_inputs;
  1294. graph_item->total_outputs_ = node_item->num_outputs;
  1295. GELOGD("NodeItem create for known shape subgraph [%s], NodeItem = %s",
  1296. graph.GetName().c_str(),
  1297. node_item->DebugString().c_str());
  1298. GELOGD("Done parse known shape subgraph successfully. graph = [%s]", graph.GetName().c_str());
  1299. graph_item->SetName(graph.GetName());
  1300. GELOGD("Done loading known shape subgraph: [%s]", graph_item->GetName().c_str());
  1301. hybrid_model_.subgraph_items_.emplace(graph.GetName(), std::move(graph_item));
  1302. return SUCCESS;
  1303. }
  1304. Status HybridModelBuilder::RecoverGraphUnknownFlag() {
  1305. const auto &root_graph = ge_root_model_->GetRootGraph();
  1306. for (auto &sub_graph : root_graph->GetAllSubgraphs()) {
  1307. GE_CHECK_NOTNULL(sub_graph);
  1308. for (const auto &node : sub_graph->GetDirectNode()) {
  1309. bool is_unknown_shape = false;
  1310. (void)AttrUtils::GetBool(node->GetOpDesc(), kOwnerGraphIsUnknown, is_unknown_shape);
  1311. sub_graph->SetGraphUnknownFlag(is_unknown_shape);
  1312. break;
  1313. }
  1314. }
  1315. return SUCCESS;
  1316. }
  1317. Status HybridModelBuilder::LoadDynamicSubgraph(ComputeGraph &graph, bool is_root_graph) {
  1318. GELOGD("Start to load subgraph [%s]", graph.GetName().c_str());
  1319. // for known partitioned call, load all nodes
  1320. auto graph_item = std::unique_ptr<GraphItem>(new(std::nothrow)GraphItem());
  1321. GE_CHECK_NOTNULL(graph_item);
  1322. graph_item->is_dynamic_ = true;
  1323. graph_item->node_items_.reserve(graph.GetDirectNodesSize());
  1324. int input_start = 0;
  1325. int output_start = 0;
  1326. std::vector<NodeItem *> data_nodes;
  1327. for (auto &node : graph.GetDirectNode()) {
  1328. GE_CHECK_NOTNULL(node);
  1329. GE_CHECK_NOTNULL(node->GetOpDesc());
  1330. const auto &op_type = node->GetType();
  1331. NodeItem *node_item = nullptr;
  1332. GE_CHK_STATUS_RET_NOLOG(GetOrCreateNodeItem(node, &node_item));
  1333. GE_CHK_STATUS_RET_NOLOG(BuildNodeItem(node, *node_item));
  1334. GE_CHK_STATUS_RET_NOLOG(UpdateAnchorStatus(node)); // needed by FE generate task
  1335. node_item->input_start = input_start;
  1336. node_item->output_start = output_start;
  1337. input_start += node_item->num_inputs;
  1338. output_start += node_item->num_outputs;
  1339. if (op_type == DATA_TYPE || op_type == AIPP_DATA_TYPE) {
  1340. data_nodes.emplace_back(node_item);
  1341. } else if (op_type == NETOUTPUT) {
  1342. graph_item->output_node_ = node_item;
  1343. GE_CHK_STATUS_RET_NOLOG(BuildOutputMapping(*graph_item, *node_item, is_root_graph));
  1344. }
  1345. graph_item->node_items_.emplace_back(node_item);
  1346. // parse var outputs
  1347. GE_CHK_STATUS_RET_NOLOG(ParseVarOutputs(*node_item));
  1348. GELOGD("NodeItem created: %s", node_item->DebugString().c_str());
  1349. }
  1350. graph_item->total_inputs_ = input_start;
  1351. graph_item->total_outputs_ = output_start;
  1352. GE_CHK_STATUS_RET_NOLOG(BuildInputMapping(*graph_item, data_nodes, is_root_graph));
  1353. if (is_root_graph) {
  1354. graph_item->SetName("Root-Graph");
  1355. GELOGD("Done loading dynamic subgraph: [%s]", graph_item->GetName().c_str());
  1356. hybrid_model_.root_graph_item_ = std::move(graph_item);
  1357. } else {
  1358. graph_item->SetName(graph.GetName());
  1359. GELOGD("Done loading dynamic subgraph: [%s]", graph_item->GetName().c_str());
  1360. hybrid_model_.subgraph_items_.emplace(graph.GetName(), std::move(graph_item));
  1361. }
  1362. return SUCCESS;
  1363. }
  1364. Status HybridModelBuilder::ParseVarOutputs(NodeItem &node_item) {
  1365. for (int i = 0; i < node_item.num_outputs; ++i) {
  1366. auto output_tensor_desc = node_item.op_desc->GetOutputDesc(i);
  1367. std::string var_name;
  1368. (void) AttrUtils::GetStr(output_tensor_desc, ASSIGN_VAR_NAME, var_name);
  1369. if (!var_name.empty()) {
  1370. auto var_node = hybrid_model_.GetVariableNode(var_name);
  1371. GE_CHECK_NOTNULL(var_node);
  1372. node_item.ref_outputs.emplace(i, var_node);
  1373. }
  1374. }
  1375. return SUCCESS;
  1376. }
  1377. Status HybridModelBuilder::BuildInputMapping(GraphItem &graph_item,
  1378. vector<NodeItem *> &data_nodes,
  1379. bool is_root_graph) {
  1380. uint32_t data_op_index = 0;
  1381. for (auto &node_item : data_nodes) {
  1382. auto node = node_item->node;
  1383. int data_index = data_op_index;
  1384. if (is_root_graph) {
  1385. if (AttrUtils::GetInt(node->GetOpDesc(), ATTR_NAME_INDEX, data_index)) {
  1386. GELOGI("ge_train: get new index %u, old %u", data_index, data_op_index);
  1387. }
  1388. data_op_index++;
  1389. } else {
  1390. if (!AttrUtils::GetInt(node->GetOpDesc(), ATTR_NAME_PARENT_NODE_INDEX, data_index)) {
  1391. GELOGE(FAILED,
  1392. "[%s] Failed to get attr [%s]",
  1393. node->GetName().c_str(),
  1394. ATTR_NAME_PARENT_NODE_INDEX.c_str());
  1395. return FAILED;
  1396. }
  1397. }
  1398. if (graph_item.input_nodes_.size() <= static_cast<size_t>(data_index)) {
  1399. graph_item.input_nodes_.resize(data_index + 1);
  1400. }
  1401. graph_item.input_nodes_[data_index] = node_item;
  1402. }
  1403. return SUCCESS;
  1404. }
  1405. } // namespace hybrid
  1406. } // 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