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