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