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op_task.cc 38 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/task/op_task.h"
  17. #include <google/protobuf/extension_set.h>
  18. #include <chrono>
  19. #include <thread>
  20. #include "aicpu/common/aicpu_task_struct.h"
  21. #include "common/dump/dump_manager.h"
  22. #include "common/dump/dump_op.h"
  23. #include "common/profiling/profiling_manager.h"
  24. #include "common/formats/formats.h"
  25. #include "common/math/math_util.h"
  26. #include "framework/common/debug/log.h"
  27. #include "register/op_tiling.h"
  28. #include "runtime/rt.h"
  29. #include "build_task_utils.h"
  30. namespace ge {
  31. namespace {
  32. constexpr int kLaunchRetryTimes = 1000;
  33. constexpr int kSleepTime = 10;
  34. constexpr uint64_t kReleaseFlag = 1;
  35. constexpr int kCopyNum = 2;
  36. constexpr uint64_t kInferSessionId = 0;
  37. void FreeHbm(void *var) {
  38. if (var) {
  39. (void)rtFree(var);
  40. }
  41. }
  42. } // namespace
  43. Status OpTask::OpenDump(rtStream_t stream) {
  44. if (DumpManager::GetInstance().GetDumpProperties(kInferSessionId).IsSingleOpNeedDump()) {
  45. GELOGI("Dump is open in single op, start to set dump info");
  46. std::vector<uint64_t> input_addrs;
  47. std::vector<uint64_t> output_adds;
  48. auto input_size = op_desc_->GetInputsSize();
  49. auto output_size = op_desc_->GetOutputsSize();
  50. uintptr_t *arg_base = nullptr;
  51. size_t arg_num = 0;
  52. GetIoAddr(arg_base, arg_num);
  53. if (arg_num < input_size + output_size) {
  54. GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "io_addrs_for_dump_ size %zu is not equal input and output size %zu",
  55. arg_num,
  56. input_size + output_size);
  57. return ACL_ERROR_GE_INTERNAL_ERROR;
  58. }
  59. for (size_t i = 0; i < input_size; i++) {
  60. uint64_t input_addr = arg_base[i];
  61. input_addrs.emplace_back(input_addr);
  62. }
  63. for (size_t j = 0; j < output_size; j++) {
  64. uint64_t output_addr = arg_base[input_size + j];
  65. output_adds.emplace_back(output_addr);
  66. }
  67. dump_op_.SetDumpInfo(DumpManager::GetInstance().GetDumpProperties(kInferSessionId),
  68. op_desc_, input_addrs, output_adds, stream);
  69. auto status = dump_op_.LaunchDumpOp();
  70. if (status != SUCCESS) {
  71. GELOGE(status, "Launch dump op failed in single op");
  72. return status;
  73. }
  74. return SUCCESS;
  75. }
  76. GELOGI("Dump is not open in single op");
  77. return SUCCESS;
  78. }
  79. void TbeOpTask::SetStubFunc(const std::string &name, const void *stub_func) {
  80. this->stub_name_ = name;
  81. this->stub_func_ = stub_func;
  82. }
  83. void TbeOpTask::SetKernelArgs(std::unique_ptr<uint8_t[]> &&args, size_t arg_size, uint32_t block_dim,
  84. const OpDescPtr &op_desc) {
  85. args_ = std::move(args);
  86. arg_size_ = arg_size;
  87. block_dim_ = block_dim;
  88. op_desc_ = op_desc;
  89. }
  90. void TbeOpTask::SetKernelWithHandleArgs(std::unique_ptr<uint8_t[]> &&args, size_t arg_size, uint32_t block_dim,
  91. const OpDescPtr &op_desc,
  92. const domi::KernelDefWithHandle &kernel_def_with_handle) {
  93. SetKernelArgs(std::move(args), arg_size, block_dim, op_desc);
  94. original_kernel_key_ = kernel_def_with_handle.original_kernel_key();
  95. node_info_ = kernel_def_with_handle.node_info();
  96. }
  97. void TbeOpTask::SetSmDesc(void *sm_desc) { sm_desc_ = sm_desc; }
  98. void OpTask::SetModelArgs(std::string model_name, uint32_t model_id) {
  99. model_name_ = model_name;
  100. model_id_ = model_id;
  101. }
  102. Status OpTask::GetProfilingArgs(TaskDescInfo &task_desc_info, uint32_t &model_id) {
  103. uint32_t task_id = 0;
  104. uint32_t stream_id = 0;
  105. auto rt_ret = rtGetTaskIdAndStreamID(&task_id, &stream_id);
  106. if (rt_ret != RT_ERROR_NONE) {
  107. GELOGE(RT_FAILED, "Get task_id and stream_id failed ret: 0x%X.", rt_ret);
  108. return RT_ERROR_TO_GE_STATUS(rt_ret);
  109. }
  110. GE_CHECK_NOTNULL(op_desc_);
  111. string op_name = op_desc_->GetName();
  112. GELOGD("Get profiling args of op [%s] end, task_id[%u], stream_id[%u].", op_name.c_str(), task_id, stream_id);
  113. model_id = model_id_;
  114. task_desc_info.model_name = model_name_;
  115. task_desc_info.block_dim = block_dim_;
  116. task_desc_info.task_id = task_id;
  117. task_desc_info.stream_id = stream_id;
  118. task_desc_info.op_name = op_name;
  119. task_desc_info.op_type = op_desc_->GetType();
  120. auto &prof_mgr = ProfilingManager::Instance();
  121. prof_mgr.GetOpInputOutputInfo(op_desc_, task_desc_info);
  122. return SUCCESS;
  123. }
  124. Status OpTask::UpdateRunInfo(const vector<GeTensorDesc> &input_desc, const vector<GeTensorDesc> &output_desc) {
  125. return UNSUPPORTED;
  126. }
  127. Status OpTask::DoUpdateArgTable(const SingleOpModelParam &param, bool keep_workspace) {
  128. auto addresses = BuildTaskUtils::GetAddresses(op_desc_, param, keep_workspace);
  129. auto all_addresses = BuildTaskUtils::JoinAddresses(addresses);
  130. uintptr_t *arg_base = nullptr;
  131. size_t arg_num = 0;
  132. GetIoAddr(arg_base, arg_num);
  133. if (arg_num < all_addresses.size()) {
  134. GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "[%s] arg number mismatches, expect at least = %zu, but got = %zu",
  135. op_desc_->GetName().c_str(),
  136. all_addresses.size(),
  137. arg_num);
  138. return ACL_ERROR_GE_INTERNAL_ERROR;
  139. }
  140. for (void *addr : all_addresses) {
  141. *arg_base++ = reinterpret_cast<uintptr_t >(addr);
  142. }
  143. return SUCCESS;
  144. }
  145. Status OpTask::UpdateArgTable(const SingleOpModelParam &param) {
  146. return DoUpdateArgTable(param, true);
  147. }
  148. Status OpTask::LaunchKernel(const vector<GeTensorDesc> &input_desc,
  149. const vector<DataBuffer> &input_buffers,
  150. vector<GeTensorDesc> &output_desc,
  151. vector<DataBuffer> &output_buffers,
  152. rtStream_t stream) {
  153. return UNSUPPORTED;
  154. }
  155. const std::string &OpTask::GetTaskType() const { return kTaskTypeInvalid; }
  156. TbeOpTask::~TbeOpTask() {
  157. if (sm_desc_ != nullptr) {
  158. (void)rtMemFreeManaged(sm_desc_);
  159. }
  160. if (tiling_buffer_ != nullptr) {
  161. (void)rtFree(tiling_buffer_);
  162. }
  163. }
  164. const void *TbeOpTask::GetArgs() const { return args_.get(); }
  165. size_t TbeOpTask::GetArgSize() const { return arg_size_; }
  166. const std::string &TbeOpTask::GetStubName() const { return stub_name_; }
  167. const std::string &TbeOpTask::GetTaskType() const { return kTaskTypeAicore; }
  168. void TbeOpTask::SetHandle(void *handle) {
  169. this->handle_ = handle;
  170. }
  171. Status TbeOpTask::LaunchKernel(rtStream_t stream) {
  172. GELOGD("To invoke rtKernelLaunch. task = %s, block_dim = %u", this->stub_name_.c_str(), block_dim_);
  173. auto *sm_desc = reinterpret_cast<rtSmDesc_t *>(sm_desc_);
  174. auto ret = rtKernelLaunch(stub_func_, block_dim_, args_.get(), static_cast<uint32_t>(arg_size_), sm_desc, stream);
  175. int retry_times = 0;
  176. while (ret != RT_ERROR_NONE && retry_times < kLaunchRetryTimes) {
  177. retry_times++;
  178. GELOGW("Retry after %d ms, retry_times: %d", kSleepTime, retry_times);
  179. std::this_thread::sleep_for(std::chrono::milliseconds(kSleepTime));
  180. ret = rtKernelLaunch(stub_func_, block_dim_, args_.get(), arg_size_, sm_desc, stream);
  181. }
  182. if (ret != RT_ERROR_NONE) {
  183. GELOGE(ret, "Invoke rtKernelLaunch failed. ret = %d, task = %s", ret, this->stub_name_.c_str());
  184. return RT_ERROR_TO_GE_STATUS(ret);
  185. }
  186. GELOGI("[TASK_INFO] %s", this->stub_name_.c_str());
  187. return SUCCESS;
  188. }
  189. Status TbeOpTask::UpdateRunInfo(const vector<GeTensorDesc> &input_desc, const vector<GeTensorDesc> &output_desc) {
  190. GE_CHK_STATUS_RET_NOLOG(UpdateNodeByShape(input_desc, output_desc));
  191. // invoke OpParaCalculate
  192. GELOGD("Start to invoke OpParaCalculate.");
  193. optiling::OpRunInfo run_info;
  194. run_info.block_dim = 0;
  195. auto ret = optiling::OpParaCalculate(*node_, run_info);
  196. if (ret != GRAPH_SUCCESS) {
  197. GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "Failed to invoke OpParaCalculate. ret = %u", ret);
  198. return ACL_ERROR_GE_INTERNAL_ERROR;
  199. }
  200. block_dim_ = run_info.block_dim;
  201. tiling_data_ = run_info.tiling_data.str();
  202. tiling_key_ = run_info.tiling_key;
  203. GELOGD("Done invoking OpParaCalculate successfully. block_dim = %u, tiling size = %zu, tiling_key = %u", block_dim_,
  204. tiling_data_.size(), tiling_key_);
  205. GE_CHK_STATUS_RET(AllocateWorkspaces(run_info.workspaces), "Failed to allocate workspaces");
  206. return SUCCESS;
  207. }
  208. Status TbeOpTask::UpdateTensorDesc(const GeTensorDesc &src_tensor, GeTensorDesc &dst_tensor) {
  209. int64_t storage_format_val = static_cast<Format>(FORMAT_RESERVED);
  210. (void)AttrUtils::GetInt(src_tensor, ge::ATTR_NAME_STORAGE_FORMAT, storage_format_val);
  211. auto storage_format = static_cast<Format>(storage_format_val);
  212. if (storage_format == FORMAT_RESERVED) {
  213. GELOGD("Storage format not set. update shape to [%s], and original shape to [%s]",
  214. src_tensor.GetShape().ToString().c_str(), src_tensor.GetOriginShape().ToString().c_str());
  215. dst_tensor.SetShape(src_tensor.GetShape());
  216. dst_tensor.SetOriginShape(src_tensor.GetOriginShape());
  217. } else {
  218. std::vector<int64_t> storage_shape;
  219. if (!AttrUtils::GetListInt(src_tensor, ge::ATTR_NAME_STORAGE_SHAPE, storage_shape)) {
  220. GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "Failed to get storage_shape while storage_format was set");
  221. return ACL_ERROR_GE_INTERNAL_ERROR;
  222. }
  223. GELOGD("Storage format set. update shape to [%s], and original shape to [%s]",
  224. GeShape(storage_shape).ToString().c_str(), src_tensor.GetShape().ToString().c_str());
  225. dst_tensor.SetShape(GeShape(std::move(storage_shape)));
  226. dst_tensor.SetOriginShape(src_tensor.GetShape());
  227. }
  228. return SUCCESS;
  229. }
  230. Status TbeOpTask::UpdateNodeByShape(const vector<GeTensorDesc> &input_desc, const vector<GeTensorDesc> &output_desc) {
  231. auto op_desc = node_->GetOpDesc();
  232. GE_CHECK_NOTNULL(op_desc);
  233. // Set runtime shape to node
  234. for (size_t i = 0; i < input_desc.size(); ++i) {
  235. auto tensor_desc = op_desc->MutableInputDesc(i);
  236. auto &runtime_tensor_desc = input_desc[i];
  237. GE_CHECK_NOTNULL(tensor_desc);
  238. GE_CHK_STATUS_RET(UpdateTensorDesc(runtime_tensor_desc, *tensor_desc));
  239. }
  240. for (size_t i = 0; i < output_desc.size(); ++i) {
  241. auto tensor_desc = op_desc->MutableOutputDesc(i);
  242. auto &runtime_tensor_desc = output_desc[i];
  243. GE_CHECK_NOTNULL(tensor_desc);
  244. GE_CHK_STATUS_RET(UpdateTensorDesc(runtime_tensor_desc, *tensor_desc));
  245. }
  246. return SUCCESS;
  247. }
  248. void TbeOpTask::EnableDynamicSupport(const NodePtr &node, void *tiling_buffer, size_t max_tiling_size) {
  249. node_ = node;
  250. tiling_buffer_ = tiling_buffer;
  251. max_tiling_size_ = max_tiling_size;
  252. }
  253. Status TbeOpTask::AllocateWorkspaces(const vector<int64_t> &workspace_sizes) {
  254. static const std::string kPurpose("malloc workspace memory for dynamic op.");
  255. if (workspace_sizes.empty()) {
  256. GELOGD("No need to allocate workspace.");
  257. return SUCCESS;
  258. }
  259. int64_t total_size = 0;
  260. std::vector<int64_t> ws_offsets;
  261. for (auto ws_size : workspace_sizes) {
  262. // alignment and padding should be done in OpParaCalculate
  263. if (CheckInt64AddOverflow(total_size, ws_size) != SUCCESS) {
  264. return ACL_ERROR_GE_INTERNAL_ERROR;
  265. }
  266. ws_offsets.emplace_back(total_size);
  267. total_size += ws_size;
  268. }
  269. GELOGD("Total workspace size is %ld", total_size);
  270. GE_CHECK_NOTNULL(stream_resource_);
  271. auto ws_base = stream_resource_->MallocMemory(kPurpose, static_cast<size_t>(total_size));
  272. if (ws_base == nullptr) {
  273. GELOGE(ACL_ERROR_GE_MEMORY_ALLOCATION, "Failed to allocate memory of size: %ld", total_size);
  274. return ACL_ERROR_GE_MEMORY_ALLOCATION;
  275. }
  276. GELOGD("Done allocating workspace memory successfully.");
  277. for (auto ws_offset : ws_offsets) {
  278. workspaces_.emplace_back(ws_base + ws_offset);
  279. }
  280. return SUCCESS;
  281. }
  282. Status TbeOpTask::LaunchKernel(const vector<GeTensorDesc> &input_desc,
  283. const vector<DataBuffer> &input_buffers,
  284. vector<GeTensorDesc> &output_desc,
  285. vector<DataBuffer> &output_buffers,
  286. rtStream_t stream) {
  287. GE_CHK_STATUS_RET_NOLOG(UpdateRunInfo(input_desc, output_desc));
  288. GELOGD("[%s] Start to launch kernel", node_->GetName().c_str());
  289. std::vector<void *> args;
  290. for (auto &buffer : input_buffers) {
  291. args.emplace_back(buffer.data);
  292. }
  293. for (auto &buffer : output_buffers) {
  294. args.emplace_back(buffer.data);
  295. }
  296. for (auto &buffer : workspaces_) {
  297. args.emplace_back(buffer);
  298. }
  299. if (tiling_buffer_ != nullptr) {
  300. GELOGD("[%s] Start to copy tiling info. size = %zu", node_->GetName().c_str(), tiling_data_.size());
  301. GE_CHK_RT_RET(rtMemcpyAsync(tiling_buffer_, max_tiling_size_, tiling_data_.data(), tiling_data_.size(),
  302. RT_MEMCPY_HOST_TO_DEVICE_EX, stream));
  303. args.emplace_back(tiling_buffer_);
  304. }
  305. if (memcpy_s(args_.get(), arg_size_, args.data(), args.size() * sizeof(void *)) != EOK) {
  306. GELOGE(ACL_ERROR_GE_MEMORY_OPERATE_FAILED, "[%s] Failed to update kernel args.",
  307. node_->GetName().c_str());
  308. return ACL_ERROR_GE_MEMORY_OPERATE_FAILED;
  309. }
  310. GELOGD("[%s] Start to invoke rtKernelLaunch", node_->GetName().c_str());
  311. if (handle_ == nullptr) {
  312. GE_CHK_RT_RET(rtKernelLaunch(stub_func_, block_dim_, args_.get(), arg_size_, nullptr, stream));
  313. GELOGD("[%s] Done invoking rtKernelLaunch successfully", node_->GetName().c_str());
  314. } else {
  315. std::string dev_func = original_kernel_key_ + "_" + std::to_string(tiling_key_);
  316. std::string kernel_info = node_info_ + "/" + std::to_string(tiling_key_);
  317. GE_CHK_RT_RET(rtKernelLaunchWithHandle(handle_, dev_func.c_str(), block_dim_, args_.get(), arg_size_, nullptr,
  318. stream, kernel_info.c_str()));
  319. GELOGD("[%s] Done invoking rtKernelLaunchWithHandle successfully", node_->GetName().c_str());
  320. }
  321. return SUCCESS;
  322. }
  323. void TbeOpTask::GetIoAddr(uintptr_t *&arg_base, size_t &arg_count) {
  324. arg_base = reinterpret_cast<uintptr_t *>(args_.get());
  325. arg_count = arg_size_ / sizeof(void *);
  326. if (tiling_buffer_ != nullptr) {
  327. --arg_count;
  328. }
  329. }
  330. AiCpuBaseTask::~AiCpuBaseTask() {
  331. if (ext_info_addr_dev_ != nullptr) {
  332. (void)rtFree(ext_info_addr_dev_);
  333. }
  334. }
  335. Status AiCpuBaseTask::SetExtInfoAndType(const std::string &kernel_ext_info, uint64_t kernel_id) {
  336. if (kernel_ext_info.empty()) {
  337. GELOGI("Kernel_ext_info is empty, no need copy to device.");
  338. return SUCCESS;
  339. }
  340. int32_t unknown_shape_type_val = 0;
  341. (void) AttrUtils::GetInt(op_desc_, ::ge::ATTR_NAME_UNKNOWN_SHAPE_TYPE, unknown_shape_type_val);
  342. GELOGD("Get unknown_type is %d.", unknown_shape_type_val);
  343. unknown_type_ = static_cast<UnknowShapeOpType>(unknown_shape_type_val);
  344. aicpu_ext_handle_.reset(new(std::nothrow) ::ge::hybrid::AicpuExtInfoHandler(op_desc_->GetName(),
  345. num_inputs_,
  346. num_outputs_,
  347. unknown_type_));
  348. GE_CHK_BOOL_RET_STATUS(aicpu_ext_handle_ != nullptr, ACL_ERROR_GE_MEMORY_ALLOCATION,
  349. "Malloc aicpu_ext_handle mem failed!");
  350. Status ret = aicpu_ext_handle_->Parse(kernel_ext_info);
  351. if (ret != SUCCESS) {
  352. GELOGE(ret, "Parse kernel ext info failed, kernel_ext_info_size=%zu.", kernel_ext_info.size());
  353. return ret;
  354. }
  355. GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateSessionInfo(ULLONG_MAX, kernel_id, false),
  356. "UpdateSessionInfo failed.");
  357. GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateExecuteMode(true), "UpdateExecuteMode failed.");
  358. GE_CHK_RT_RET(rtMalloc(&ext_info_addr_dev_, aicpu_ext_handle_->GetExtInfoLen(), RT_MEMORY_HBM));
  359. GE_CHK_RT_RET(rtMemcpy(ext_info_addr_dev_, aicpu_ext_handle_->GetExtInfoLen(),
  360. aicpu_ext_handle_->GetExtInfo(), aicpu_ext_handle_->GetExtInfoLen(),
  361. RT_MEMCPY_HOST_TO_DEVICE));
  362. return SUCCESS;
  363. }
  364. Status AiCpuBaseTask::SetInputConst() {
  365. input_is_const_.clear();
  366. const vector<bool> v_is_input_const = op_desc_->GetIsInputConst();
  367. for (size_t i = 0; i < op_desc_->GetAllInputsSize(); ++i) {
  368. const GeTensorDescPtr tensor_desc = op_desc_->MutableInputDesc(static_cast<uint32_t>(i));
  369. if (tensor_desc == nullptr) {
  370. GELOGD("SingleOp: %s, Index: %zu, has no input", op_desc_->GetName().c_str(), i);
  371. continue;
  372. }
  373. if (i < v_is_input_const.size() && v_is_input_const[i]) {
  374. GELOGD("SingleOp: %s, Index: %zu, input is const", op_desc_->GetName().c_str(), i);
  375. input_is_const_.push_back(true);
  376. continue;
  377. }
  378. input_is_const_.push_back(false);
  379. }
  380. return SUCCESS;
  381. }
  382. Status AiCpuBaseTask::UpdateExtInfo(const std::vector<GeTensorDesc> &input_desc,
  383. std::vector<GeTensorDesc> &output_desc,
  384. rtStream_t stream) {
  385. GELOGI("Update ext info begin, unknown_type=%d.", unknown_type_);
  386. GE_CHECK_NOTNULL(aicpu_ext_handle_);
  387. GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateExecuteMode(false), "UpdateExecuteMode failed.");
  388. if (num_inputs_ == 0 && num_outputs_ == 0) {
  389. GELOGI("No input and output, no need update ext info.");
  390. return SUCCESS;
  391. }
  392. size_t non_const_index = 0;
  393. for (size_t input_index = 0; input_index < num_inputs_; input_index++) {
  394. if (input_index < input_is_const_.size() && input_is_const_[input_index]) {
  395. // get input_desc from op_desc if const input, num_inputs_ is op_desc_ input_size
  396. auto const_input_desc = op_desc_->MutableInputDesc(static_cast<uint32_t>(input_index));
  397. GE_CHECK_NOTNULL(const_input_desc);
  398. GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateInputShapeAndType(input_index, *const_input_desc),
  399. "Input[%zu] update input shape failed.", input_index);
  400. continue;
  401. }
  402. GE_CHK_BOOL_RET_STATUS(non_const_index < input_desc.size(), ACL_ERROR_GE_PARAM_INVALID,
  403. "Input_desc size is %zu, but get non_const_index is %zu", input_desc.size(),
  404. non_const_index);
  405. GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateInputShapeAndType(input_index, input_desc[non_const_index]),
  406. "Input[%zu] update input shape failed.", input_index);
  407. if (DumpManager::GetInstance().GetDumpProperties(kInferSessionId).IsSingleOpNeedDump()) {
  408. GE_CHK_STATUS_RET(op_desc_->UpdateInputDesc(input_index, input_desc[non_const_index]),
  409. "AicpuTask Update [%zu]th input desc failed", input_index);
  410. }
  411. non_const_index++;
  412. }
  413. if (unknown_type_ != DEPEND_COMPUTE) {
  414. for (size_t j = 0; j < num_outputs_; ++j) {
  415. GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateOutputShapeAndType(j, output_desc[j]),
  416. "Output[%zu] UpdateOutputShapeAndType failed.", j);
  417. if (DumpManager::GetInstance().GetDumpProperties(kInferSessionId).IsSingleOpNeedDump()) {
  418. GE_CHK_STATUS_RET(op_desc_->UpdateOutputDesc(j, output_desc[j]), "AicpuTask Update [%zu]th output desc failed",
  419. j);
  420. }
  421. }
  422. }
  423. GE_CHK_RT_RET(rtMemcpyAsync(ext_info_addr_dev_,
  424. aicpu_ext_handle_->GetExtInfoLen(), // check size
  425. aicpu_ext_handle_->GetExtInfo(),
  426. aicpu_ext_handle_->GetExtInfoLen(),
  427. RT_MEMCPY_HOST_TO_DEVICE_EX,
  428. stream));
  429. GELOGI("Update ext info end.");
  430. return SUCCESS;
  431. }
  432. Status AiCpuBaseTask::UpdateOutputShape(vector<GeTensorDesc> &output_desc) {
  433. if (num_outputs_ == 0) {
  434. GELOGD("AiCpuBaseTask output_num is 0, no need update output shape.");
  435. return SUCCESS;
  436. }
  437. GELOGD("Start to update DEPEND_SHAPE_RANGE AiCpuBaseTask outputshape.");
  438. GE_CHK_RT_RET(rtMemcpy(aicpu_ext_handle_->GetExtInfo(), aicpu_ext_handle_->GetExtInfoLen(), ext_info_addr_dev_,
  439. aicpu_ext_handle_->GetExtInfoLen(), RT_MEMCPY_DEVICE_TO_HOST));
  440. for (size_t i = 0; i < num_outputs_; ++i) {
  441. GeShape shape;
  442. DataType data_type;
  443. aicpu_ext_handle_->GetOutputShapeAndType(i, shape, data_type);
  444. GE_CHK_STATUS_RET(UpdateShapeToOutputDesc(shape, output_desc[i]), "AiCpuCCTask Update [%zu]th output shape failed.",
  445. i);
  446. if (DumpManager::GetInstance().GetDumpProperties(kInferSessionId).IsSingleOpNeedDump()) {
  447. GE_CHK_STATUS_RET(op_desc_->UpdateOutputDesc(i, output_desc[i]), "AiCpuCCTask Update [%zu]th output desc failed.",
  448. i);
  449. }
  450. }
  451. GELOGD("Update DEPEND_SHAPE_RANGE AiCpuBaseTask outputshape finished.");
  452. return SUCCESS;
  453. }
  454. Status AiCpuBaseTask::UpdateShapeToOutputDesc(const GeShape &shape_new, GeTensorDesc &output_desc) {
  455. auto shape_old = output_desc.GetShape();
  456. output_desc.SetShape(shape_new);
  457. GELOGD("Update AiCpuBaseTask shape from %s to %s", shape_old.ToString().c_str(), shape_new.ToString().c_str());
  458. auto origin_shape_old = output_desc.GetOriginShape();
  459. auto origin_format = output_desc.GetOriginFormat();
  460. auto format = output_desc.GetFormat();
  461. if (origin_format == format) {
  462. output_desc.SetOriginShape(shape_new);
  463. return SUCCESS;
  464. }
  465. std::vector<int64_t> origin_dims_new;
  466. auto trans_ret = formats::TransShape(format, shape_new.GetDims(),
  467. output_desc.GetDataType(), origin_format, origin_dims_new);
  468. GE_CHK_STATUS_RET(trans_ret,
  469. "AiCpuTask originFormat[%d] is not same as format[%d], but TransShape failed, shape=%s.",
  470. origin_format, format, shape_new.ToString().c_str());
  471. auto origin_shape_new = GeShape(origin_dims_new);
  472. output_desc.SetOriginShape(origin_shape_new);
  473. GELOGD("AiCpuTask originFormat[%d] is not same as format[%d], need update from %s ro %s.",
  474. origin_format, format, origin_shape_old.ToString().c_str(), origin_shape_new.ToString().c_str());
  475. return SUCCESS;
  476. }
  477. Status AiCpuBaseTask::UpdateIoAddr(const vector<DataBuffer> &inputs, const vector<DataBuffer> &outputs) {
  478. uintptr_t *arg_base = nullptr;
  479. size_t arg_num = 0;
  480. GetIoAddr(arg_base, arg_num);
  481. // input number and output number was check in ValidateParams
  482. size_t non_const_index = 0;
  483. for (size_t input_index = 0; input_index < num_inputs_; input_index++) {
  484. if (input_index < input_is_const_.size() && input_is_const_[input_index]) {
  485. // const input no need update addr
  486. GE_CHECK_NOTNULL(arg_base);
  487. GELOGD("AICpuTask input[%zu] addr = %lu", input_index, *arg_base);
  488. arg_base++;
  489. continue;
  490. }
  491. GE_CHK_BOOL_RET_STATUS(non_const_index < inputs.size(), ACL_ERROR_GE_PARAM_INVALID,
  492. "Input size is %zu, but get non_const_index is %zu",
  493. inputs.size(), non_const_index);
  494. auto addr = inputs[non_const_index].data;
  495. GE_CHECK_NOTNULL(addr);
  496. GELOGD("AICpuTask input[%zu] addr = %p", input_index, addr);
  497. *arg_base++ = reinterpret_cast<uintptr_t>(addr);
  498. non_const_index++;
  499. }
  500. for (size_t i = 0; i < outputs.size(); ++i) {
  501. auto addr = outputs[i].data;
  502. GE_CHECK_NOTNULL(addr);
  503. GELOGD("AICpuTask output[%zu] addr = %p", i, addr);
  504. *arg_base++ = reinterpret_cast<uintptr_t>(addr);
  505. }
  506. return SUCCESS;
  507. }
  508. AiCpuTask::~AiCpuTask() {
  509. FreeHbm(args_);
  510. FreeHbm(io_addr_);
  511. if (dynamic_flag_) {
  512. FreeHbm(workspace_addr_);
  513. }
  514. FreeHbm(copy_workspace_buf_);
  515. FreeHbm(copy_ioaddr_dev_);
  516. FreeHbm(copy_input_release_flag_dev_);
  517. FreeHbm(copy_input_data_size_dev_);
  518. FreeHbm(copy_input_src_dev_);
  519. FreeHbm(copy_input_dst_dev_);
  520. FreeHbm(copy_task_args_buf_);
  521. for (auto summary : output_summary_) {
  522. FreeHbm(summary);
  523. }
  524. for (auto out_shape : out_shape_hbm_) {
  525. FreeHbm(out_shape);
  526. }
  527. }
  528. Status AiCpuTask::LaunchKernel(rtStream_t stream) {
  529. GELOGD("Start to launch kernel. task = %s", this->op_type_.c_str());
  530. auto ret = rtMemcpyAsync(io_addr_,
  531. io_addr_size_,
  532. io_addr_host_.data(),
  533. io_addr_host_.size() * sizeof(void *),
  534. RT_MEMCPY_HOST_TO_DEVICE_EX,
  535. stream);
  536. if (ret != RT_ERROR_NONE) {
  537. GELOGE(ret, "rtMemcpyAsync workspace data failed. ret = %d, task = %s", ret, this->op_type_.c_str());
  538. return RT_ERROR_TO_GE_STATUS(ret);
  539. }
  540. GELOGI("To invoke rtKernelLaunchEx. task = %s", this->op_type_.c_str());
  541. ret = rtKernelLaunchEx(args_, arg_size_, 0, stream);
  542. if (ret != RT_ERROR_NONE) {
  543. GELOGE(ret, "Invoke rtKernelLaunch failed. ret = %d, task = %s", ret, this->op_type_.c_str());
  544. return RT_ERROR_TO_GE_STATUS(ret);
  545. }
  546. GELOGI("[TASK_INFO] %lu/%s", kernel_id_, op_type_.c_str());
  547. GELOGD("Done launch kernel successfully. task = %s", this->op_type_.c_str());
  548. return SUCCESS;
  549. }
  550. Status AiCpuTask::PrepareCopyInputs(vector<DataBuffer> &outputs) {
  551. std::vector<uint64_t> copy_input_release_flag;
  552. std::vector<uint64_t> copy_input_data_size;
  553. std::vector<uint64_t> copy_input_src;
  554. std::vector<uint64_t> copy_input_dst;
  555. for (size_t i = 0; i < num_outputs_; ++i) {
  556. const auto &summary = output_summary_host_[i];
  557. GELOGI("Node out[%zu] summary, shape data=0x%lx, shape data size=%lu, raw data=0x%lx, raw data size=%lu.",
  558. i, summary.shape_data_ptr, summary.shape_data_size,
  559. summary.raw_data_ptr, summary.raw_data_size);
  560. auto output = outputs[i];
  561. copy_input_release_flag.emplace_back(kReleaseFlag);
  562. if (summary.raw_data_size > 0) {
  563. copy_input_data_size.emplace_back(output.length);
  564. } else {
  565. copy_input_data_size.emplace_back(summary.raw_data_size);
  566. }
  567. copy_input_src.emplace_back(summary.raw_data_ptr);
  568. copy_input_dst.emplace_back(reinterpret_cast<uintptr_t>(output.data));
  569. const auto &shape_buffer = out_shape_hbm_[i];
  570. copy_input_release_flag.emplace_back(kReleaseFlag);
  571. copy_input_data_size.emplace_back(summary.shape_data_size);
  572. copy_input_src.emplace_back(summary.shape_data_ptr);
  573. copy_input_dst.emplace_back(reinterpret_cast<uintptr_t>(shape_buffer));
  574. }
  575. const size_t copy_input_buf_len = num_outputs_ * kCopyNum * sizeof(uint64_t);
  576. GE_CHK_RT_RET(rtMemcpy(copy_input_release_flag_dev_, copy_input_buf_len,
  577. copy_input_release_flag.data(), copy_input_buf_len, RT_MEMCPY_HOST_TO_DEVICE));
  578. GE_CHK_RT_RET(rtMemcpy(copy_input_data_size_dev_, copy_input_buf_len,
  579. copy_input_data_size.data(), copy_input_buf_len, RT_MEMCPY_HOST_TO_DEVICE));
  580. GE_CHK_RT_RET(rtMemcpy(copy_input_src_dev_, copy_input_buf_len,
  581. copy_input_src.data(), copy_input_buf_len, RT_MEMCPY_HOST_TO_DEVICE));
  582. GE_CHK_RT_RET(rtMemcpy(copy_input_dst_dev_, copy_input_buf_len,
  583. copy_input_dst.data(), copy_input_buf_len, RT_MEMCPY_HOST_TO_DEVICE));
  584. return SUCCESS;
  585. }
  586. Status AiCpuTask::ReadResultSummaryAndPrepareMemory() {
  587. for (size_t i = 0; i < num_outputs_; ++i) {
  588. auto &result_summary = output_summary_host_[i];
  589. GE_CHK_RT_RET(rtMemcpy(&result_summary, sizeof(aicpu::FWKAdapter::ResultSummary),
  590. output_summary_[i], sizeof(aicpu::FWKAdapter::ResultSummary),
  591. RT_MEMCPY_DEVICE_TO_HOST));
  592. auto shape_data_size = result_summary.shape_data_size;
  593. void *shape_buffer = nullptr;
  594. if (shape_data_size > 0) {
  595. GE_CHK_RT_RET(rtMalloc(&shape_buffer, shape_data_size, RT_MEMORY_HBM));
  596. }
  597. out_shape_hbm_.emplace_back(shape_buffer);
  598. }
  599. return SUCCESS;
  600. }
  601. Status AiCpuTask::CopyDataToHbm(vector<DataBuffer> &outputs,
  602. rtStream_t stream) {
  603. GE_CHK_STATUS_RET_NOLOG(PrepareCopyInputs(outputs));
  604. GE_CHK_RT_RET(rtKernelLaunchEx(copy_task_args_buf_, sizeof(STR_FWK_OP_KERNEL),
  605. RT_KERNEL_DEFAULT, stream));
  606. GE_CHK_RT_RET(rtStreamSynchronize(stream));
  607. return SUCCESS;
  608. }
  609. Status AiCpuTask::UpdateShapeByHbmBuffer(vector<GeTensorDesc> &output_desc) {
  610. for (size_t i = 0; i < num_outputs_; ++i) {
  611. const auto &result_summary = output_summary_host_[i];
  612. std::vector<int64_t> shape_dims;
  613. if (result_summary.shape_data_size > 0) {
  614. const auto &shape_hbm = out_shape_hbm_[i];
  615. uint32_t dim_num = result_summary.shape_data_size / sizeof(int64_t);
  616. std::unique_ptr<int64_t[]> shape_addr(new (std::nothrow) int64_t[dim_num]());
  617. GE_CHECK_NOTNULL(shape_addr);
  618. GE_CHK_RT_RET(rtMemcpy(shape_addr.get(), result_summary.shape_data_size, shape_hbm,
  619. result_summary.shape_data_size, RT_MEMCPY_DEVICE_TO_HOST));
  620. for (uint32_t dim_idx = 0; dim_idx < dim_num; ++dim_idx) {
  621. shape_dims.emplace_back(shape_addr[dim_idx]);
  622. GELOGD("Node [%zu]th output dim[%u]=%ld.", i, dim_idx, shape_addr[dim_idx]);
  623. }
  624. }
  625. GE_CHK_STATUS_RET(UpdateShapeToOutputDesc(GeShape(shape_dims), output_desc[i]),
  626. "AiCpuTask update [%zu]th output shape failed.", i);
  627. if (DumpManager::GetInstance().GetDumpProperties(kInferSessionId).IsSingleOpNeedDump()) {
  628. GE_CHK_STATUS_RET(op_desc_->UpdateOutputDesc(i, output_desc[i]), "AiCpuTask update [%zu]th output desc failed.",
  629. i);
  630. }
  631. }
  632. return SUCCESS;
  633. }
  634. Status AiCpuTask::UpdateShapeAndDataByResultSummary(vector<GeTensorDesc> &output_desc,
  635. vector<DataBuffer> &outputs,
  636. rtStream_t stream) {
  637. if (num_outputs_ == 0) {
  638. GELOGI("Output num is 0, there is no need to update the output and size.");
  639. return SUCCESS;
  640. }
  641. GELOGI("Update shape and data by result summary begin.");
  642. for (auto out_shape : out_shape_hbm_) {
  643. FreeHbm(out_shape);
  644. }
  645. out_shape_hbm_.clear();
  646. GE_CHK_STATUS_RET(ReadResultSummaryAndPrepareMemory(),
  647. "Read ResultSummary and update output shape failed.");
  648. GE_CHK_STATUS_RET(CopyDataToHbm(outputs, stream),
  649. "Copy data to output failed.");
  650. GE_CHK_STATUS_RET(UpdateShapeByHbmBuffer(output_desc),
  651. "Update shape by hbm buffer failed.");
  652. for (auto out_shape : out_shape_hbm_) {
  653. FreeHbm(out_shape);
  654. }
  655. out_shape_hbm_.clear();
  656. GELOGI("Update shape and data by result summary end.");
  657. return SUCCESS;
  658. }
  659. Status AiCpuTask::InitForSummaryAndCopy() {
  660. if (unknown_type_ != DEPEND_COMPUTE || num_outputs_ == 0) {
  661. GELOGI("Unknown_type is %d, output num is %zu.", unknown_type_, num_outputs_);
  662. return SUCCESS;
  663. }
  664. output_summary_.resize(num_outputs_);
  665. constexpr auto result_summary_size = sizeof(aicpu::FWKAdapter::ResultSummary);
  666. for (size_t i = 0; i < num_outputs_; ++i) {
  667. GE_CHK_RT_RET(rtMalloc(&output_summary_[i], result_summary_size, RT_MEMORY_HBM));
  668. }
  669. output_summary_host_.resize(num_outputs_);
  670. const size_t copy_input_buf_len = num_outputs_ * kCopyNum * sizeof(uint64_t);
  671. GE_CHK_RT_RET(rtMalloc(&copy_input_release_flag_dev_, copy_input_buf_len, RT_MEMORY_HBM));
  672. GE_CHK_RT_RET(rtMalloc(&copy_input_data_size_dev_, copy_input_buf_len, RT_MEMORY_HBM));
  673. GE_CHK_RT_RET(rtMalloc(&copy_input_src_dev_, copy_input_buf_len, RT_MEMORY_HBM));
  674. GE_CHK_RT_RET(rtMalloc(&copy_input_dst_dev_, copy_input_buf_len, RT_MEMORY_HBM));
  675. GE_CHK_RT_RET(rtMalloc(&copy_task_args_buf_, sizeof(STR_FWK_OP_KERNEL), RT_MEMORY_HBM));
  676. std::vector<uint64_t> copy_io_addr;
  677. copy_io_addr.emplace_back(reinterpret_cast<uintptr_t>(copy_input_release_flag_dev_));
  678. copy_io_addr.emplace_back(reinterpret_cast<uintptr_t>(copy_input_data_size_dev_));
  679. copy_io_addr.emplace_back(reinterpret_cast<uintptr_t>(copy_input_src_dev_));
  680. copy_io_addr.emplace_back(reinterpret_cast<uintptr_t>(copy_input_dst_dev_));
  681. const auto copy_io_addr_size = sizeof(uint64_t) * copy_io_addr.size();
  682. GE_CHK_RT_RET(rtMalloc(&copy_ioaddr_dev_, copy_io_addr_size, RT_MEMORY_HBM));
  683. GE_CHK_RT_RET(rtMemcpy(copy_ioaddr_dev_, copy_io_addr_size,
  684. copy_io_addr.data(), copy_io_addr_size, RT_MEMCPY_HOST_TO_DEVICE));
  685. return SUCCESS;
  686. }
  687. Status AiCpuTask::SetMemCopyTask(const domi::KernelExDef &kernel_def) {
  688. if (kernel_def.args_size() > sizeof(STR_FWK_OP_KERNEL)) {
  689. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "sizeof STR_FWK_OP_KERNEL is: %lu, but args_size is: %d",
  690. sizeof(STR_FWK_OP_KERNEL), kernel_def.args_size());
  691. return ACL_ERROR_GE_PARAM_INVALID;
  692. }
  693. GE_CHK_RT_RET(rtMalloc(&copy_workspace_buf_, kernel_def.task_info_size(), RT_MEMORY_HBM));
  694. GE_CHK_RT_RET(rtMemcpy(copy_workspace_buf_, kernel_def.task_info_size(),
  695. kernel_def.task_info().data(), kernel_def.task_info_size(), RT_MEMCPY_HOST_TO_DEVICE));
  696. STR_FWK_OP_KERNEL aicpu_task = {0};
  697. auto sec_ret = memcpy_s(&aicpu_task, sizeof(STR_FWK_OP_KERNEL),
  698. kernel_def.args().data(), kernel_def.args().size());
  699. if (sec_ret != EOK) {
  700. GELOGE(ACL_ERROR_GE_MEMORY_OPERATE_FAILED, "memcpy failed, ret: %d", sec_ret);
  701. return ACL_ERROR_GE_MEMORY_OPERATE_FAILED;
  702. }
  703. aicpu_task.fwkKernelBase.fwk_kernel.inputOutputAddr = reinterpret_cast<uintptr_t>(copy_ioaddr_dev_);
  704. aicpu_task.fwkKernelBase.fwk_kernel.workspaceBaseAddr = reinterpret_cast<uintptr_t>(copy_workspace_buf_);
  705. aicpu_task.fwkKernelBase.fwk_kernel.extInfoAddr = 0;
  706. aicpu_task.fwkKernelBase.fwk_kernel.extInfoLen = 0;
  707. GE_CHK_RT_RET(rtMemcpy(copy_task_args_buf_, sizeof(STR_FWK_OP_KERNEL),
  708. &aicpu_task, sizeof(STR_FWK_OP_KERNEL), RT_MEMCPY_HOST_TO_DEVICE));
  709. return SUCCESS;
  710. }
  711. Status AiCpuTask::LaunchKernel(const std::vector<GeTensorDesc> &input_desc,
  712. const std::vector<DataBuffer> &input_buffers,
  713. std::vector<GeTensorDesc> &output_desc,
  714. std::vector<DataBuffer> &output_buffers,
  715. rtStream_t stream) {
  716. GE_CHK_STATUS_RET_NOLOG(UpdateExtInfo(input_desc, output_desc, stream));
  717. if (unknown_type_ == DEPEND_COMPUTE) {
  718. std::vector<DataBuffer> summary_buffers;
  719. for (size_t i = 0; i < num_outputs_; ++i) {
  720. summary_buffers.emplace_back(output_summary_[i], sizeof(aicpu::FWKAdapter::ResultSummary), false);
  721. }
  722. GE_CHK_STATUS_RET_NOLOG(UpdateIoAddr(input_buffers, summary_buffers));
  723. } else {
  724. GE_CHK_STATUS_RET_NOLOG(UpdateIoAddr(input_buffers, output_buffers));
  725. }
  726. GE_CHK_STATUS_RET_NOLOG(LaunchKernel(stream));
  727. if (unknown_type_ == DEPEND_SHAPE_RANGE) {
  728. GE_CHK_RT_RET(rtStreamSynchronize(stream));
  729. GE_CHK_STATUS_RET_NOLOG(UpdateOutputShape(output_desc));
  730. } else if (unknown_type_ == DEPEND_COMPUTE) {
  731. GE_CHK_RT_RET(rtStreamSynchronize(stream));
  732. GE_CHK_STATUS_RET_NOLOG(UpdateShapeAndDataByResultSummary(output_desc, output_buffers, stream));
  733. }
  734. return SUCCESS;
  735. }
  736. Status AiCpuBaseTask::UpdateArgTable(const SingleOpModelParam &param) {
  737. // aicpu do not have workspace, for now
  738. return DoUpdateArgTable(param, false);
  739. }
  740. const std::string &AiCpuBaseTask::GetTaskType() const { return kTaskTypeAicpu; }
  741. void AiCpuTask::GetIoAddr(uintptr_t *&arg_base, size_t &arg_count) {
  742. arg_base = reinterpret_cast<uintptr_t *>(io_addr_host_.data());
  743. arg_count = io_addr_host_.size();
  744. }
  745. void AiCpuCCTask::SetKernelArgs(std::unique_ptr<uint8_t[]> args, size_t arg_size) {
  746. args_ = std::move(args);
  747. arg_size_ = arg_size;
  748. // The blockdim value is defult "1" for rtCpuKernelLaunch
  749. block_dim_ = 1;
  750. }
  751. void AiCpuCCTask::SetSoName(const std::string &so_name) { so_name_ = so_name; }
  752. void AiCpuCCTask::SetkernelName(const std::string &kernel_Name) { kernel_name_ = kernel_Name; }
  753. void AiCpuCCTask::SetIoAddr(uintptr_t *io_addr) { io_addr_ = io_addr; }
  754. const void *AiCpuCCTask::GetArgs() const { return args_.get(); }
  755. size_t AiCpuCCTask::GetArgSize() const { return arg_size_; }
  756. AiCpuCCTask::~AiCpuCCTask() {
  757. }
  758. Status AiCpuCCTask::LaunchKernel(rtStream_t stream) {
  759. GELOGI("To invoke rtCpuKernelLaunch. block_dim = %u, so_name is %s, kernel_name is %s", block_dim_, so_name_.data(),
  760. kernel_name_.data());
  761. // sm_desc is nullptr, because l2 buffer does not support
  762. auto *sm_desc = reinterpret_cast<rtSmDesc_t *>(sm_desc_);
  763. auto ret = rtCpuKernelLaunchWithFlag(static_cast<const void *>(so_name_.data()),
  764. static_cast<const void *>(kernel_name_.data()),
  765. block_dim_, args_.get(), static_cast<uint32_t>(arg_size_),
  766. sm_desc, stream, dump_flag_);
  767. if (ret != RT_ERROR_NONE) {
  768. GELOGE(ret, "Invoke rtCpuKernelLaunch failed. ret = %d", ret);
  769. return RT_ERROR_TO_GE_STATUS(ret);
  770. }
  771. GELOGI("[TASK_INFO] %lu/%s", kernel_id_, op_type_.c_str());
  772. GELOGD("Invoke rtCpuKernelLaunch succeeded");
  773. return SUCCESS;
  774. }
  775. Status AiCpuCCTask::LaunchKernel(const std::vector<GeTensorDesc> &input_desc,
  776. const std::vector<DataBuffer> &input_buffers,
  777. std::vector<GeTensorDesc> &output_desc,
  778. std::vector<DataBuffer> &output_buffers,
  779. rtStream_t stream) {
  780. GE_CHK_STATUS_RET_NOLOG(UpdateExtInfo(input_desc, output_desc, stream));
  781. GE_CHK_STATUS_RET_NOLOG(UpdateIoAddr(input_buffers, output_buffers));
  782. GE_CHK_STATUS_RET_NOLOG(LaunchKernel(stream));
  783. if (unknown_type_ == DEPEND_SHAPE_RANGE) {
  784. GE_CHK_RT_RET(rtStreamSynchronize(stream));
  785. GE_CHK_STATUS_RET_NOLOG(UpdateOutputShape(output_desc));
  786. }
  787. return SUCCESS;
  788. }
  789. void AiCpuCCTask::GetIoAddr(uintptr_t *&arg_base, size_t &arg_count) {
  790. arg_base = io_addr_;
  791. arg_count = io_addr_num_;
  792. }
  793. } // 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