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single_op_model.cc 23 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 "single_op/single_op_model.h"
  17. #include <atomic>
  18. #include <memory>
  19. #include <string>
  20. #include <vector>
  21. #include "framework/common/debug/ge_log.h"
  22. #include "graph/debug/ge_attr_define.h"
  23. #include "graph/load/model_manager/model_utils.h"
  24. #include "graph/utils/attr_utils.h"
  25. #include "graph/utils/graph_utils.h"
  26. #include "graph/utils/tensor_utils.h"
  27. #include "runtime/rt.h"
  28. #include "task/aicpu_task_builder.h"
  29. #include "task/aicpu_kernel_task_builder.h"
  30. #include "task/tbe_task_builder.h"
  31. #include "hybrid/executor/hybrid_model_executor.h"
  32. #include "hybrid/node_executor/node_executor.h"
  33. static std::atomic<std::uint64_t> aicpu_kernel_id(0);
  34. using domi::TaskDef;
  35. using std::unique_ptr;
  36. using std::vector;
  37. namespace ge {
  38. namespace {
  39. const size_t kDataOutputNum = 1;
  40. Status IfInferDepend(GeModelPtr &ge_model, bool &flag) {
  41. auto comp_graph = GraphUtils::GetComputeGraph(ge_model->GetGraph());
  42. GE_CHECK_NOTNULL(comp_graph);
  43. for (const auto &node : comp_graph->GetAllNodes()) {
  44. auto op_desc = node->GetOpDesc();
  45. GE_CHECK_NOTNULL(op_desc);
  46. const auto &depends = op_desc->GetOpInferDepends();
  47. if (!depends.empty()) {
  48. flag = true;
  49. return SUCCESS;
  50. }
  51. }
  52. return SUCCESS;
  53. }
  54. Status NeedHybridModel(GeModelPtr &ge_model, bool &flag) {
  55. bool infer_depend_flag = false;
  56. GE_CHK_STATUS_RET(IfInferDepend(ge_model, infer_depend_flag), "[Check][InferDepend] failed.");
  57. auto tasks = ge_model->GetModelTaskDefPtr()->task();
  58. int32_t kernel_task_num = 0;
  59. for (int i = 0; i < tasks.size(); ++i) {
  60. auto task_type = static_cast<rtModelTaskType_t>(tasks[i].type());
  61. if (task_type == RT_MODEL_TASK_KERNEL || task_type == RT_MODEL_TASK_ALL_KERNEL) {
  62. const auto &context = task_type == RT_MODEL_TASK_KERNEL ? tasks[i].kernel().context() :
  63. tasks[i].kernel_with_handle().context();
  64. auto kernel_type = static_cast<ccKernelType>(context.kernel_type());
  65. if (kernel_type == ccKernelType::TE) {
  66. if (infer_depend_flag) {
  67. flag = true;
  68. return SUCCESS;
  69. }
  70. kernel_task_num++;
  71. if (kernel_task_num > 1) {
  72. flag = true;
  73. return SUCCESS;
  74. }
  75. }
  76. }
  77. }
  78. return SUCCESS;
  79. }
  80. } // namespace
  81. SingleOpModel::SingleOpModel(const std::string &model_name, const void *model_data, uint32_t model_size)
  82. : model_name_(model_name), ori_model_data_(model_data), ori_model_size_(model_size) {}
  83. Status SingleOpModel::Init() {
  84. GE_CHK_STATUS_RET_NOLOG(InitModel());
  85. return LoadAllNodes();
  86. }
  87. Status SingleOpModel::InitModel() {
  88. ge::ModelData model;
  89. model.model_len = ori_model_size_;
  90. model.model_data = const_cast<void *>(ori_model_data_);
  91. auto ret = model_helper_.LoadModel(model);
  92. if (ret != SUCCESS) {
  93. GELOGE(ret, "LoadModel failed");
  94. return ret;
  95. }
  96. return SUCCESS;
  97. }
  98. void SingleOpModel::ParseOpModelParams(ModelHelper &model_helper, SingleOpModelParam &param) {
  99. int64_t value = 0;
  100. bool ret = false;
  101. std::shared_ptr<ge::GeModel> model = model_helper.GetGeModel();
  102. GE_CHECK_NOTNULL_JUST_RETURN(model);
  103. ret = ge::AttrUtils::GetInt(model, ATTR_MODEL_MEMORY_SIZE, value);
  104. param.memory_size = ret ? static_cast<uint64_t>(value) : 0;
  105. ret = ge::AttrUtils::GetInt(model, ATTR_MODEL_ZERO_COPY_MEMORY_SIZE, value);
  106. param.zero_copy_mem_size = ret ? static_cast<uint64_t>(value) : 0;
  107. ret = ge::AttrUtils::GetInt(model, ATTR_MODEL_WEIGHT_SIZE, value);
  108. param.weight_size = ret ? static_cast<uint64_t>(value) : 0;
  109. ret = ge::AttrUtils::GetInt(model, MODEL_ATTR_TASK_GEN_BASE_ADDR, value);
  110. param.base_addr = ret ? static_cast<uint64_t>(value) : 0;
  111. ret = ge::AttrUtils::GetInt(model, MODEL_ATTR_TASK_GEN_WEIGHT_ADDR, value);
  112. param.weight_addr = ret ? static_cast<uint64_t>(value) : 0;
  113. ret = ge::AttrUtils::GetInt(model, ATTR_MODEL_CORE_TYPE, value);
  114. param.core_type = ret ? value : 0;
  115. GELOGI("ParseOpModelParams(), total_memory_size:%lu, zero_copy_size:%lu, weight_size:%lu. core_type = %lu",
  116. param.memory_size, param.zero_copy_mem_size, param.weight_size, param.core_type);
  117. }
  118. Status SingleOpModel::InitModelMem(StreamResource &res) {
  119. ParseOpModelParams(model_helper_, model_params_);
  120. if (model_params_.memory_size > model_params_.zero_copy_mem_size) {
  121. const string purpose("malloc feature map memory on model execute.");
  122. GELOGI("total memory: %lu, zero_copy_mem: %lu", model_params_.memory_size, model_params_.zero_copy_mem_size);
  123. model_params_.mem_base =
  124. res.MallocMemory(purpose, model_params_.memory_size - model_params_.zero_copy_mem_size, false);
  125. if (model_params_.mem_base == nullptr) {
  126. return ACL_ERROR_GE_MEMORY_ALLOCATION;
  127. }
  128. }
  129. if (model_params_.weight_size > 0 && has_weight_) {
  130. const string purpose("malloc weights memory on model execute.");
  131. model_params_.weight_base = res.MallocWeight(purpose, model_params_.weight_size);
  132. if (model_params_.weight_base == nullptr) {
  133. // no need to free memory, for that was handled by StreamResources
  134. return ACL_ERROR_GE_MEMORY_ALLOCATION;
  135. }
  136. auto weight_buffer = model_helper_.GetGeModel()->GetWeight();
  137. GELOGI("To copy weight to device. weight size = %zu", weight_buffer.GetSize());
  138. GE_CHK_RT_RET(rtMemcpy(model_params_.weight_base,
  139. model_params_.weight_size,
  140. weight_buffer.GetData(),
  141. weight_buffer.GetSize(),
  142. RT_MEMCPY_HOST_TO_DEVICE));
  143. }
  144. return SUCCESS;
  145. }
  146. Status SingleOpModel::ParseInputNode(const OpDescPtr &op_desc) {
  147. vector<int64_t> offsets = op_desc->GetOutputOffset();
  148. if (offsets.size() != kDataOutputNum) {
  149. GELOGE(ACL_ERROR_GE_PARAM_INVALID,
  150. "Data op should have only one output, but got %zu", op_desc->GetOutputOffset().size());
  151. return ACL_ERROR_GE_PARAM_INVALID;
  152. }
  153. auto output_desc = op_desc->GetOutputDescPtr(0);
  154. GE_CHECK_NOTNULL(output_desc);
  155. int64_t tensor_size = 0;
  156. (void)TensorUtils::GetSize(*output_desc, tensor_size);
  157. input_offset_list_.emplace_back(offsets[0]);
  158. input_sizes_.emplace_back(tensor_size);
  159. GELOGI("[%s] parse input node: %s, size = %ld, offset = %u", model_name_.c_str(), op_desc->GetName().c_str(),
  160. tensor_size, static_cast<uint32_t>(offsets[0]));
  161. return SUCCESS;
  162. }
  163. void SingleOpModel::ParseOutputNode(const OpDescPtr &op_desc) {
  164. vector<int64_t> offsets = op_desc->GetInputOffset();
  165. for (uint32_t k = 0; k < static_cast<uint32_t>(offsets.size()); ++k) {
  166. auto input_desc = op_desc->GetInputDescPtr(k);
  167. if (input_desc == nullptr) {
  168. continue;
  169. }
  170. int64_t tensor_size = 0;
  171. (void)TensorUtils::GetSize(*input_desc, tensor_size);
  172. output_offset_list_.emplace_back(offsets[k]);
  173. output_sizes_.emplace_back(tensor_size);
  174. GELOGI("[%s] parse output node: %s, size = %ld, offset = %u", model_name_.c_str(), op_desc->GetName().c_str(),
  175. tensor_size, static_cast<uint32_t>(offsets[k]));
  176. }
  177. }
  178. Status SingleOpModel::LoadAllNodes() {
  179. auto ge_model = model_helper_.GetGeModel();
  180. GE_CHECK_NOTNULL(ge_model);
  181. Graph graph = ge_model->GetGraph();
  182. model_id_ = ge_model->GetModelId();
  183. auto compute_graph = GraphUtils::GetComputeGraph(graph);
  184. if (compute_graph == nullptr) {
  185. GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "[%s] compute_graph is null", model_name_.c_str());
  186. return ACL_ERROR_GE_INTERNAL_ERROR;
  187. }
  188. auto nodes = compute_graph->GetDirectNode();
  189. size_t model_op_size = nodes.size();
  190. GELOGI("[%s] node size = %zu", model_name_.c_str(), model_op_size);
  191. for (size_t i = 0; i < model_op_size; ++i) {
  192. auto node = nodes.at(i);
  193. auto op_desc = node->GetOpDesc();
  194. GE_CHECK_NOTNULL(op_desc);
  195. op_list_[op_desc->GetId()] = node;
  196. auto op_type = op_desc->GetType();
  197. GELOGI("[%s] node[%zu] = %s, type = %s", model_name_.c_str(), i, node->GetName().c_str(), op_type.c_str());
  198. if (op_type == DATA_TYPE || op_type == AIPP_DATA_TYPE) {
  199. data_ops_.emplace_back(op_desc);
  200. continue;
  201. }
  202. if (op_type == CONSTANT || op_type == CONSTANTOP) {
  203. has_weight_ = true;
  204. continue;
  205. }
  206. if (op_type == NETOUTPUT) {
  207. netoutput_op_ = op_desc;
  208. continue;
  209. }
  210. ge_model->GetTBEKernelStore().LoadTBEKernelBinToOpDesc(op_desc);
  211. ge_model->GetCustAICPUKernelStore().LoadCustAICPUKernelBinToOpDesc(op_desc);
  212. }
  213. return SUCCESS;
  214. }
  215. Status SingleOpModel::ParseInputsAndOutputs() {
  216. for (auto &op_desc : data_ops_) {
  217. GE_CHK_STATUS_RET_NOLOG(ParseInputNode(op_desc));
  218. }
  219. ParseOutputNode(netoutput_op_);
  220. return SUCCESS;
  221. }
  222. Status SingleOpModel::SetInputsAndOutputs(SingleOp &single_op) {
  223. int arg_index = 0;
  224. for (size_t i = 0; i < input_offset_list_.size(); ++i) {
  225. auto *addr = model_params_.mem_base + input_offset_list_[i];
  226. model_params_.addr_mapping_.emplace(reinterpret_cast<uintptr_t>(addr), arg_index++);
  227. single_op.input_sizes_.emplace_back(input_sizes_[i]);
  228. single_op.input_addr_list_.emplace_back(addr);
  229. }
  230. for (size_t i = 0; i < output_offset_list_.size(); ++i) {
  231. auto *addr = model_params_.mem_base + output_offset_list_[i];
  232. model_params_.addr_mapping_.emplace(reinterpret_cast<uintptr_t>(addr), arg_index++);
  233. single_op.output_sizes_.emplace_back(output_sizes_[i]);
  234. single_op.output_addr_list_.emplace_back(addr);
  235. }
  236. single_op.args_.resize(arg_index);
  237. return SUCCESS;
  238. }
  239. Status SingleOpModel::BuildTaskList(StreamResource *stream_resource, SingleOp &single_op) {
  240. auto ge_model = model_helper_.GetGeModel();
  241. GE_CHECK_NOTNULL(ge_model);
  242. single_op.arg_table_.resize(single_op.input_sizes_.size() + single_op.output_sizes_.size());
  243. auto tasks = ge_model->GetModelTaskDefPtr()->task();
  244. for (int i = 0; i < tasks.size(); ++i) {
  245. const TaskDef &task_def = tasks[i];
  246. GELOGI("[%s] Task[%d], type = %u, DebugString = %s", model_name_.c_str(), i, task_def.type(),
  247. task_def.DebugString().c_str());
  248. auto task_type = static_cast<rtModelTaskType_t>(task_def.type());
  249. if (task_type == RT_MODEL_TASK_KERNEL || task_type == RT_MODEL_TASK_ALL_KERNEL) {
  250. const auto &context = task_type == RT_MODEL_TASK_KERNEL ? task_def.kernel().context() :
  251. task_def.kernel_with_handle().context();
  252. auto kernel_type = static_cast<ccKernelType>(context.kernel_type());
  253. if (kernel_type == ccKernelType::TE) {
  254. GELOGD("Building TBE task");
  255. TbeOpTask *tbe_task = nullptr;
  256. auto ret = BuildKernelTask(task_def, &tbe_task);
  257. if (ret != SUCCESS) {
  258. return ret;
  259. }
  260. ParseArgTable(tbe_task, single_op);
  261. tbe_task->SetModelArgs(model_name_, model_id_);
  262. if (tbe_task->tiling_buffer_ != nullptr) {
  263. tbe_task->stream_resource_ = stream_resource;
  264. }
  265. single_op.tasks_.emplace_back(tbe_task);
  266. } else if (kernel_type == ccKernelType::AI_CPU || kernel_type == ccKernelType::CUST_AI_CPU) {
  267. GELOGD("Building AICPU_CC task");
  268. OpTask *task = nullptr;
  269. uint64_t singleop_kernel_id = aicpu_kernel_id++;
  270. GELOGI("Build singleOp CCTask, kernel_id = %lu", singleop_kernel_id);
  271. auto ret = BuildCpuKernelTask(task_def.kernel(), &task, singleop_kernel_id);
  272. if (ret != SUCCESS) {
  273. return ret;
  274. }
  275. task->SetModelArgs(model_name_, model_id_);
  276. ParseArgTable(task, single_op);
  277. single_op.tasks_.emplace_back(task);
  278. } else {
  279. GELOGE(ACL_ERROR_GE_OP_KERNEL_TYPE_INVALID,
  280. "Only TBE, AI_CPU, CUST_AI_CPU kernel are supported, but got %u", context.kernel_type());
  281. return ACL_ERROR_GE_OP_KERNEL_TYPE_INVALID;
  282. }
  283. } else if (task_type == RT_MODEL_TASK_KERNEL_EX) {
  284. GELOGD("Building AICPU_TF task");
  285. AiCpuTask *aicpu_task = nullptr;
  286. bool depend_compute_flag = false;
  287. uint64_t singleop_kernel_id = aicpu_kernel_id++;
  288. GELOGI("Build singleOp TfTask, kernel_id = %lu", singleop_kernel_id);
  289. auto ret = BuildKernelExTask(task_def.kernel_ex(), &aicpu_task, false, depend_compute_flag, singleop_kernel_id);
  290. if (ret != SUCCESS) {
  291. return ret;
  292. }
  293. aicpu_task->SetModelArgs(model_name_, model_id_);
  294. ParseArgTable(aicpu_task, single_op);
  295. single_op.tasks_.emplace_back(aicpu_task);
  296. } else {
  297. // skip
  298. GELOGD("Skip task type: %d", static_cast<int>(task_type));
  299. }
  300. }
  301. return SUCCESS;
  302. }
  303. void SingleOpModel::ParseArgTable(OpTask *task, SingleOp &op) {
  304. if (task == nullptr) {
  305. GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "tbe op task is nullptr");
  306. return;
  307. }
  308. // args: addr1, addr2, addr3 ...
  309. uintptr_t *arg_base = nullptr;
  310. size_t arg_num = 0;
  311. task->GetIoAddr(arg_base, arg_num);
  312. for (size_t i = 0; i < arg_num; ++i) {
  313. uintptr_t *ptr_to_addr = arg_base + i;
  314. uintptr_t addr = *ptr_to_addr;
  315. auto iter = model_params_.addr_mapping_.find(addr);
  316. if (iter != model_params_.addr_mapping_.end()) {
  317. int arg_index = iter->second;
  318. GELOGI("%s args[%zu] mapped to user designated args[%d]", task->GetOpdesc()->GetName().c_str(), i, arg_index);
  319. op.arg_table_[iter->second].emplace_back(ptr_to_addr);
  320. }
  321. }
  322. }
  323. Status SingleOpModel::BuildKernelTask(const domi::TaskDef &task_def, TbeOpTask **task) {
  324. GE_CHECK_NOTNULL(task);
  325. auto task_type = static_cast<rtModelTaskType_t>(task_def.type());
  326. const auto &context = task_type == RT_MODEL_TASK_KERNEL ? task_def.kernel().context() :
  327. task_def.kernel_with_handle().context();
  328. auto iter = op_list_.find(context.op_index());
  329. if (iter == op_list_.end()) {
  330. GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "op desc not found. op index = %u", context.op_index());
  331. return ACL_ERROR_GE_INTERNAL_ERROR;
  332. }
  333. auto *tbe_task = new (std::nothrow) TbeOpTask();
  334. if (tbe_task == nullptr) {
  335. GELOGE(ACL_ERROR_GE_MEMORY_ALLOCATION, "create tbe op task failed");
  336. return ACL_ERROR_GE_MEMORY_ALLOCATION;
  337. }
  338. auto builder = TbeTaskBuilder(model_name_, iter->second, task_def);
  339. auto ret = builder.BuildTask(*tbe_task, model_params_);
  340. if (ret != SUCCESS) {
  341. delete tbe_task;
  342. tbe_task = nullptr;
  343. return ret;
  344. }
  345. *task = tbe_task;
  346. return SUCCESS;
  347. }
  348. Status SingleOpModel::BuildKernelExTask(const domi::KernelExDef &kernel_def, AiCpuTask **task,
  349. bool dynamic_flag, bool& depend_compute_flag, uint64_t kernel_id) {
  350. auto iter = op_list_.find(kernel_def.op_index());
  351. if (iter == op_list_.end()) {
  352. GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "op desc not found. op index = %u", kernel_def.op_index());
  353. return ACL_ERROR_GE_INTERNAL_ERROR;
  354. }
  355. std::unique_ptr<AiCpuTask> aicpu_task(new (std::nothrow) AiCpuTask());
  356. if (aicpu_task == nullptr) {
  357. GELOGE(ACL_ERROR_GE_MEMORY_ALLOCATION, "create aicpu_TF op task failed");
  358. return ACL_ERROR_GE_MEMORY_ALLOCATION;
  359. }
  360. auto builder = AiCpuTaskBuilder(iter->second->GetOpDesc(), kernel_def);
  361. auto ret = builder.BuildTask(*aicpu_task, model_params_, dynamic_flag, kernel_id);
  362. if (ret != SUCCESS) {
  363. GELOGE(ret, "build aicpu_TF op task failed");
  364. return ret;
  365. }
  366. depend_compute_flag = (aicpu_task->GetUnknownType() == DEPEND_COMPUTE);
  367. *task = aicpu_task.release();
  368. return SUCCESS;
  369. }
  370. Status SingleOpModel::BuildCpuKernelTask(const domi::KernelDef &kernel_def, OpTask **task, uint64_t kernel_id) {
  371. const auto &context = kernel_def.context();
  372. auto iter = op_list_.find(context.op_index());
  373. if (iter == op_list_.end()) {
  374. GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "op desc not found. op index = %u", context.op_index());
  375. return ACL_ERROR_GE_INTERNAL_ERROR;
  376. }
  377. std::unique_ptr<AiCpuCCTask> aicpucc_task(new (std::nothrow) AiCpuCCTask());
  378. if (aicpucc_task == nullptr) {
  379. GELOGE(ACL_ERROR_GE_MEMORY_ALLOCATION, "create aicpu_CC op task failed");
  380. return ACL_ERROR_GE_MEMORY_ALLOCATION;
  381. }
  382. auto builder = AiCpuCCTaskBuilder(iter->second->GetOpDesc(), kernel_def);
  383. auto ret = builder.BuildTask(*aicpucc_task, kernel_id, model_params_);
  384. if (ret != SUCCESS) {
  385. GELOGE(ret, "build aicpu_CC op task failed");
  386. return ret;
  387. }
  388. *task = aicpucc_task.release();
  389. return SUCCESS;
  390. }
  391. Status SingleOpModel::BuildOp(StreamResource &resource, SingleOp &single_op) {
  392. GE_CHK_STATUS_RET_NOLOG(ParseInputsAndOutputs());
  393. GE_CHK_STATUS_RET_NOLOG(InitModelMem(resource));
  394. single_op.running_param_.reset(new (std::nothrow)SingleOpModelParam(model_params_));
  395. GE_CHECK_NOTNULL(single_op.running_param_);
  396. GE_CHK_STATUS_RET_NOLOG(SetInputsAndOutputs(single_op));
  397. return BuildTaskList(&resource, single_op);
  398. }
  399. Status SingleOpModel::BuildModelTaskKernel(const TaskDef &task_def, DynamicSingleOp &single_op) {
  400. auto task_type = static_cast<rtModelTaskType_t>(task_def.type());
  401. const auto &context = task_type == RT_MODEL_TASK_KERNEL ? task_def.kernel().context() :
  402. task_def.kernel_with_handle().context();
  403. auto kernel_type = static_cast<ccKernelType>(context.kernel_type());
  404. if (kernel_type == ccKernelType::TE) {
  405. GELOGD("Building TBE task");
  406. TbeOpTask *tbe_task = nullptr;
  407. GE_CHK_STATUS_RET_NOLOG(BuildKernelTask(task_def, &tbe_task));
  408. tbe_task->SetModelArgs(model_name_, model_id_);
  409. single_op.op_task_.reset(tbe_task);
  410. } else if (kernel_type == ccKernelType::AI_CPU || kernel_type == ccKernelType::CUST_AI_CPU) {
  411. GELOGD("Building AICPU_CC task");
  412. OpTask *task = nullptr;
  413. uint64_t dynamic_singleop_kernel_id = aicpu_kernel_id++;
  414. GELOGI("Build dynamic singleOp CCTask, kernel_id = %lu", dynamic_singleop_kernel_id);
  415. GE_CHK_STATUS_RET_NOLOG(BuildCpuKernelTask(task_def.kernel(), &task, dynamic_singleop_kernel_id));
  416. task->SetModelArgs(model_name_, model_id_);
  417. single_op.op_task_.reset(task);
  418. } else {
  419. GELOGE(ACL_ERROR_GE_OP_KERNEL_TYPE_INVALID,
  420. "Only TBE, AI_CPU, CUST_AI_CPU kernel are supported, but got %u", context.kernel_type());
  421. return ACL_ERROR_GE_OP_KERNEL_TYPE_INVALID;
  422. }
  423. return SUCCESS;
  424. }
  425. Status SingleOpModel::BuildTaskListForDynamicOp(DynamicSingleOp &single_op) {
  426. auto ge_model = model_helper_.GetGeModel();
  427. GE_CHECK_NOTNULL(ge_model);
  428. auto tasks = ge_model->GetModelTaskDefPtr()->task();
  429. for (int i = 0; i < tasks.size(); ++i) {
  430. const TaskDef &task_def = tasks[i];
  431. GELOGI("[%s] Task[%d], type = %u, DebugString = %s", model_name_.c_str(), i, task_def.type(),
  432. task_def.DebugString().c_str());
  433. auto task_type = static_cast<rtModelTaskType_t>(task_def.type());
  434. if (task_type == RT_MODEL_TASK_KERNEL || task_type == RT_MODEL_TASK_ALL_KERNEL) {
  435. if (single_op.op_task_ != nullptr) {
  436. GELOGE(ACL_ERROR_GE_OP_TASK_TYPE_INVALID, "Do not support dynamic op with multiple tasks.");
  437. return ACL_ERROR_GE_OP_TASK_TYPE_INVALID;
  438. }
  439. GE_CHK_STATUS_RET_NOLOG(BuildModelTaskKernel(task_def, single_op));
  440. } else if (task_type == RT_MODEL_TASK_KERNEL_EX) {
  441. if (single_op.op_task_ != nullptr) {
  442. GELOGE(ACL_ERROR_GE_OP_TASK_TYPE_INVALID, "Do not support dynamic op with multiple tasks.");
  443. return ACL_ERROR_GE_OP_TASK_TYPE_INVALID;
  444. }
  445. GELOGD("Building AICPU_TF task");
  446. AiCpuTask *aicpu_task = nullptr;
  447. bool depend_compute_flag = false;
  448. uint64_t dynamic_singleop_kernel_id = aicpu_kernel_id++;
  449. GELOGI("Build dynamic singleOp TfTask, kernel_id = %lu", dynamic_singleop_kernel_id);
  450. GE_CHK_STATUS_RET_NOLOG(BuildKernelExTask(task_def.kernel_ex(), &aicpu_task, true,
  451. depend_compute_flag, dynamic_singleop_kernel_id));
  452. if (depend_compute_flag) {
  453. if (i >= tasks.size() - 1) {
  454. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "The copy task of the fourth operator was not found.");
  455. return ACL_ERROR_GE_PARAM_INVALID;
  456. }
  457. ++i;
  458. const TaskDef &copy_task_def = tasks[i];
  459. GE_CHK_STATUS_RET_NOLOG(aicpu_task->SetMemCopyTask(copy_task_def.kernel_ex()));
  460. }
  461. aicpu_task->SetModelArgs(model_name_, model_id_);
  462. single_op.op_task_.reset(aicpu_task);
  463. } else {
  464. // skip
  465. GELOGD("Skip task type: %d", static_cast<int>(task_type));
  466. }
  467. }
  468. return SUCCESS;
  469. }
  470. Status SingleOpModel::BuildDynamicOp(StreamResource &resource, DynamicSingleOp &single_op) {
  471. single_op.num_inputs_ = data_ops_.size();
  472. single_op.num_outputs_ = netoutput_op_->GetAllInputsSize();
  473. GE_CHK_STATUS_RET_NOLOG(InitModelMem(resource));
  474. model_params_.memory_size = UINT_MAX;
  475. auto ge_model = model_helper_.GetGeModel();
  476. GE_CHECK_NOTNULL(ge_model);
  477. bool need_hybrid_model = false;
  478. GE_CHK_STATUS_RET(NeedHybridModel(ge_model, need_hybrid_model), "[Check][NeedHybridModel] failed.");
  479. if (need_hybrid_model) {
  480. GELOGD("Build single op HybridModel.");
  481. GE_CHK_STATUS_RET_NOLOG(hybrid::NodeExecutorManager::GetInstance().EnsureInitialized());
  482. auto root_model = model_helper_.GetGeRootModel();
  483. GE_CHECK_NOTNULL(root_model);
  484. root_model->SetRootGraph(GraphUtils::GetComputeGraph(ge_model->GetGraph()));
  485. root_model->SetSubgraphInstanceNameToModel(root_model->GetRootGraph()->GetName(), ge_model);
  486. single_op.hybrid_model_.reset(new (std::nothrow)hybrid::HybridModel(root_model));
  487. GE_CHECK_NOTNULL(single_op.hybrid_model_);
  488. GE_CHK_STATUS_RET(single_op.hybrid_model_->Init(true), "Failed to init hybrid model");
  489. int32_t device_id = 0;
  490. GE_CHK_RT_RET(rtGetDevice(&device_id));
  491. single_op.hybrid_model_executor_.reset(new (std::nothrow)hybrid::HybridModelExecutor(single_op.hybrid_model_.get(),
  492. device_id,
  493. resource.GetStream()));
  494. GE_CHECK_NOTNULL(single_op.hybrid_model_executor_);
  495. GE_CHK_STATUS_RET(single_op.hybrid_model_executor_->Init(), "Failed to init hybrid model");
  496. return SUCCESS;
  497. }
  498. return BuildTaskListForDynamicOp(single_op);
  499. }
  500. } // 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