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op_task.cc 47 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 "runtime/rt.h"
  28. #include "single_op/task/build_task_utils.h"
  29. namespace ge {
  30. namespace {
  31. constexpr int kLaunchRetryTimes = 1000;
  32. constexpr size_t kMemcpyArgCount = 2;
  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,
  55. "[Check][Size]io_addrs_for_dump_ size %zu is not equal input and output size %zu",
  56. arg_num, input_size + output_size);
  57. REPORT_INNER_ERROR("E19999", "io_addrs_for_dump_ size %zu is not equal input and output size %zu",
  58. arg_num, input_size + output_size);
  59. return ACL_ERROR_GE_INTERNAL_ERROR;
  60. }
  61. for (size_t i = 0; i < input_size; i++) {
  62. uint64_t input_addr = arg_base[i];
  63. input_addrs.emplace_back(input_addr);
  64. }
  65. for (size_t j = 0; j < output_size; j++) {
  66. uint64_t output_addr = arg_base[input_size + j];
  67. output_adds.emplace_back(output_addr);
  68. }
  69. dump_op_.SetDumpInfo(DumpManager::GetInstance().GetDumpProperties(kInferSessionId),
  70. op_desc_, input_addrs, output_adds, stream);
  71. auto status = dump_op_.LaunchDumpOp();
  72. if (status != SUCCESS) {
  73. GELOGE(status, "[Launch][DumpOp] failed in single op.");
  74. return status;
  75. }
  76. return SUCCESS;
  77. }
  78. GELOGI("Dump is not open in single op");
  79. return SUCCESS;
  80. }
  81. void TbeOpTask::SetStubFunc(const std::string &name, const void *stub_func) {
  82. this->stub_name_ = name;
  83. this->stub_func_ = stub_func;
  84. this->task_name_ = name;
  85. }
  86. void TbeOpTask::SetKernelArgs(std::unique_ptr<uint8_t[]> &&args, size_t arg_size, uint32_t block_dim,
  87. const OpDescPtr &op_desc) {
  88. args_ = std::move(args);
  89. arg_size_ = arg_size;
  90. block_dim_ = block_dim;
  91. op_desc_ = op_desc;
  92. }
  93. void TbeOpTask::SetKernelWithHandleArgs(std::unique_ptr<uint8_t[]> &&args, size_t arg_size, uint32_t block_dim,
  94. const OpDescPtr &op_desc,
  95. const domi::KernelDefWithHandle &kernel_def_with_handle) {
  96. SetKernelArgs(std::move(args), arg_size, block_dim, op_desc);
  97. original_kernel_key_ = kernel_def_with_handle.original_kernel_key();
  98. node_info_ = kernel_def_with_handle.node_info();
  99. }
  100. void TbeOpTask::SetSmDesc(void *sm_desc) { sm_desc_ = sm_desc; }
  101. void OpTask::SetModelArgs(std::string model_name, uint32_t model_id) {
  102. model_name_ = model_name;
  103. model_id_ = model_id;
  104. }
  105. Status OpTask::GetProfilingArgs(TaskDescInfo &task_desc_info, uint32_t &model_id) {
  106. uint32_t task_id = 0;
  107. uint32_t stream_id = 0;
  108. auto rt_ret = rtGetTaskIdAndStreamID(&task_id, &stream_id);
  109. if (rt_ret != RT_ERROR_NONE) {
  110. GELOGE(RT_FAILED, "[Get][TaskIdAndStreamID] failed, ret: 0x%X.", rt_ret);
  111. REPORT_CALL_ERROR("E19999", "rtGetTaskIdAndStreamID failed, ret: 0x%X.", rt_ret);
  112. return RT_ERROR_TO_GE_STATUS(rt_ret);
  113. }
  114. GE_CHECK_NOTNULL(op_desc_);
  115. string op_name = op_desc_->GetName();
  116. GELOGD("Get profiling args of op [%s] end, task_id[%u], stream_id[%u].", op_name.c_str(), task_id, stream_id);
  117. model_id = model_id_;
  118. task_desc_info.model_name = model_name_;
  119. task_desc_info.block_dim = block_dim_;
  120. task_desc_info.task_id = task_id;
  121. task_desc_info.stream_id = stream_id;
  122. task_desc_info.op_name = op_name;
  123. task_desc_info.op_type = op_desc_->GetType();
  124. auto &prof_mgr = ProfilingManager::Instance();
  125. prof_mgr.GetOpInputOutputInfo(op_desc_, task_desc_info);
  126. return SUCCESS;
  127. }
  128. Status OpTask::UpdateRunInfo() {
  129. return UNSUPPORTED;
  130. }
  131. Status OpTask::DoUpdateArgTable(const SingleOpModelParam &param, bool keep_workspace) {
  132. auto addresses = BuildTaskUtils::GetAddresses(op_desc_, param, keep_workspace);
  133. auto all_addresses = BuildTaskUtils::JoinAddresses(addresses);
  134. uintptr_t *arg_base = nullptr;
  135. size_t arg_num = 0;
  136. GetIoAddr(arg_base, arg_num);
  137. if (arg_num < all_addresses.size()) {
  138. GELOGE(ACL_ERROR_GE_INTERNAL_ERROR,
  139. "[Check][Size][%s] arg number mismatches, expect at least = %zu, but got = %zu.",
  140. op_desc_->GetName().c_str(), all_addresses.size(), arg_num);
  141. REPORT_INNER_ERROR("E19999", "%s arg number mismatches, expect at least = %zu, but got = %zu.",
  142. op_desc_->GetName().c_str(), all_addresses.size(), arg_num);
  143. return ACL_ERROR_GE_INTERNAL_ERROR;
  144. }
  145. for (void *addr : all_addresses) {
  146. *arg_base++ = reinterpret_cast<uintptr_t >(addr);
  147. }
  148. return SUCCESS;
  149. }
  150. Status OpTask::UpdateArgTable(const SingleOpModelParam &param) {
  151. return DoUpdateArgTable(param, true);
  152. }
  153. Status OpTask::LaunchKernel(const vector<GeTensorDesc> &input_desc,
  154. const vector<DataBuffer> &input_buffers,
  155. vector<GeTensorDesc> &output_desc,
  156. vector<DataBuffer> &output_buffers,
  157. rtStream_t stream) {
  158. return UNSUPPORTED;
  159. }
  160. const std::string &OpTask::GetTaskType() const { return kTaskTypeInvalid; }
  161. TbeOpTask::~TbeOpTask() {
  162. if (sm_desc_ != nullptr) {
  163. (void)rtMemFreeManaged(sm_desc_);
  164. }
  165. if (tiling_buffer_ != nullptr) {
  166. (void)rtFree(tiling_buffer_);
  167. }
  168. }
  169. const void *TbeOpTask::GetArgs() const { return args_.get(); }
  170. size_t TbeOpTask::GetArgSize() const { return arg_size_; }
  171. const std::string &TbeOpTask::GetStubName() const { return stub_name_; }
  172. const std::string &TbeOpTask::GetTaskType() const { return kTaskTypeAicore; }
  173. void TbeOpTask::SetHandle(void *handle) {
  174. this->handle_ = handle;
  175. }
  176. Status TbeOpTask::LaunchKernel(rtStream_t stream) {
  177. GELOGD("To invoke rtKernelLaunch. task = %s, block_dim = %u", this->stub_name_.c_str(), block_dim_);
  178. auto ret = DoLaunchKernel(stream);
  179. int retry_times = 0;
  180. while (ret != RT_ERROR_NONE && retry_times < kLaunchRetryTimes) {
  181. retry_times++;
  182. GELOGW("Retry after %d ms, retry_times: %d", kSleepTime, retry_times);
  183. std::this_thread::sleep_for(std::chrono::milliseconds(kSleepTime));
  184. ret = DoLaunchKernel(stream);
  185. }
  186. if (ret != RT_ERROR_NONE) {
  187. GELOGE(ret, "[Invoke][RtKernelLaunch] failed. ret = %d, task = %s", ret, this->stub_name_.c_str());
  188. REPORT_INNER_ERROR("E19999", "invoke rtKernelLaunch failed, ret = %d, task = %s", ret, this->stub_name_.c_str());
  189. return RT_ERROR_TO_GE_STATUS(ret);
  190. }
  191. GELOGI("[TASK_INFO] %s", this->stub_name_.c_str());
  192. return SUCCESS;
  193. }
  194. Status TbeOpTask::CalcTilingInfo(optiling::utils::OpRunInfo &run_info) {
  195. auto ret = optiling::OpParaCalculateV2(*node_, run_info);
  196. if (ret != GRAPH_SUCCESS) {
  197. GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "[Invoke][OpParaCalculate] failed, ret = %u.", ret);
  198. REPORT_INNER_ERROR("E19999", "invoke OpParaCalculate failed, ret = %u.", ret);
  199. return ACL_ERROR_GE_INTERNAL_ERROR;
  200. }
  201. return SUCCESS;
  202. }
  203. Status TbeOpTask::UpdateRunInfo() {
  204. // invoke OpParaCalculate
  205. GELOGD("Start to invoke OpParaCalculate.");
  206. optiling::utils::OpRunInfo run_info(0, true, 0);
  207. GE_CHK_STATUS_RET(CalcTilingInfo(run_info), "[Calc][TilingInfo]failed.");
  208. block_dim_ = run_info.GetBlockDim();
  209. tiling_data_ = run_info.GetAllTilingData().str();
  210. tiling_key_ = run_info.GetTilingKey();
  211. clear_atomic_ = run_info.GetClearAtomic();
  212. run_info.GetAllWorkspaces(run_info_workspaces_);
  213. GELOGD("Done invoking OpParaCalculate successfully. block_dim = %u, tiling size = %zu, tiling_key = %u", block_dim_,
  214. tiling_data_.size(), tiling_key_);
  215. return SUCCESS;
  216. }
  217. Status TbeOpTask::UpdateTensorDesc(const GeTensorDesc &src_tensor, GeTensorDesc &dst_tensor) {
  218. int64_t storage_format_val = static_cast<Format>(FORMAT_RESERVED);
  219. (void)AttrUtils::GetInt(src_tensor, ge::ATTR_NAME_STORAGE_FORMAT, storage_format_val);
  220. auto storage_format = static_cast<Format>(storage_format_val);
  221. if (storage_format == FORMAT_RESERVED) {
  222. GELOGD("Storage format not set. update shape to [%s], and original shape to [%s]",
  223. src_tensor.GetShape().ToString().c_str(), src_tensor.GetOriginShape().ToString().c_str());
  224. dst_tensor.SetShape(src_tensor.GetShape());
  225. dst_tensor.SetOriginShape(src_tensor.GetOriginShape());
  226. } else {
  227. std::vector<int64_t> storage_shape;
  228. if (!AttrUtils::GetListInt(src_tensor, ge::ATTR_NAME_STORAGE_SHAPE, storage_shape)) {
  229. GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "[Get][ListInt]failed while storage_format was set.");
  230. return ACL_ERROR_GE_INTERNAL_ERROR;
  231. }
  232. GELOGD("Storage format set. update shape to [%s], and original shape to [%s]",
  233. GeShape(storage_shape).ToString().c_str(), src_tensor.GetShape().ToString().c_str());
  234. dst_tensor.SetShape(GeShape(std::move(storage_shape)));
  235. dst_tensor.SetOriginShape(src_tensor.GetShape());
  236. }
  237. return SUCCESS;
  238. }
  239. Status TbeOpTask::UpdateNodeByShape(const vector<GeTensorDesc> &input_desc, const vector<GeTensorDesc> &output_desc) {
  240. auto op_desc = node_->GetOpDesc();
  241. GE_CHECK_NOTNULL(op_desc);
  242. // Set runtime shape to node
  243. for (size_t i = 0; i < input_desc.size(); ++i) {
  244. auto tensor_desc = op_desc->MutableInputDesc(i);
  245. auto &runtime_tensor_desc = input_desc[i];
  246. GE_CHECK_NOTNULL(tensor_desc);
  247. GE_CHK_STATUS_RET(UpdateTensorDesc(runtime_tensor_desc, *tensor_desc));
  248. }
  249. for (size_t i = 0; i < output_desc.size(); ++i) {
  250. auto tensor_desc = op_desc->MutableOutputDesc(i);
  251. auto &runtime_tensor_desc = output_desc[i];
  252. GE_CHECK_NOTNULL(tensor_desc);
  253. GE_CHK_STATUS_RET(UpdateTensorDesc(runtime_tensor_desc, *tensor_desc));
  254. }
  255. return SUCCESS;
  256. }
  257. Status TbeOpTask::EnableDynamicSupport(const NodePtr &node, void *tiling_buffer, uint32_t max_tiling_size) {
  258. if (tiling_buffer != nullptr) {
  259. uintptr_t *arg_base = nullptr;
  260. size_t arg_num = 0;
  261. GetIoAddr(arg_base, arg_num);
  262. GE_CHECK_NOTNULL(node);
  263. GE_CHECK_NOTNULL(node->GetOpDesc());
  264. uint32_t inputs_num = node->GetOpDesc()->GetInputsSize();
  265. uint32_t outputs_num = node->GetOpDesc()->GetOutputsSize();
  266. uint32_t workspace_nums = node->GetOpDesc()->GetWorkspace().size();
  267. uint32_t tiling_index = inputs_num + outputs_num + workspace_nums;
  268. if (arg_num == 0 || arg_num < tiling_index) {
  269. GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "[Check][Size]Tiling index %u, arg number %zu is invalid.",
  270. tiling_index, arg_num);
  271. return ACL_ERROR_GE_INTERNAL_ERROR;
  272. }
  273. arg_base[tiling_index] = reinterpret_cast<uintptr_t>(tiling_buffer);
  274. }
  275. node_ = node;
  276. tiling_buffer_ = tiling_buffer;
  277. max_tiling_size_ = max_tiling_size;
  278. return SUCCESS;
  279. }
  280. Status TbeOpTask::AllocateWorkspaces(const vector<int64_t> &workspace_sizes) {
  281. static const std::string kPurpose("malloc workspace memory for dynamic op.");
  282. workspaces_.clear();
  283. if (workspace_sizes.empty()) {
  284. GELOGD("No need to allocate workspace.");
  285. return SUCCESS;
  286. }
  287. int64_t total_size = 0;
  288. std::vector<int64_t> ws_offsets;
  289. for (auto ws_size : workspace_sizes) {
  290. // alignment and padding should be done in OpParaCalculate
  291. if (CheckInt64AddOverflow(total_size, ws_size) != SUCCESS) {
  292. return ACL_ERROR_GE_INTERNAL_ERROR;
  293. }
  294. ws_offsets.emplace_back(total_size);
  295. total_size += ws_size;
  296. }
  297. GELOGD("Total workspace size is %ld", total_size);
  298. GE_CHECK_NOTNULL(stream_resource_);
  299. auto ws_base = stream_resource_->MallocMemory(kPurpose, static_cast<size_t>(total_size));
  300. if (ws_base == nullptr) {
  301. GELOGE(ACL_ERROR_GE_MEMORY_ALLOCATION, "[Malloc][Memory] failed, size: %ld", total_size);
  302. REPORT_INNER_ERROR("E19999", "MallocMemory failed, size: %ld", total_size);
  303. return ACL_ERROR_GE_MEMORY_ALLOCATION;
  304. }
  305. GELOGD("Done allocating workspace memory successfully.");
  306. for (auto ws_offset : ws_offsets) {
  307. workspaces_.emplace_back(ws_base + ws_offset);
  308. }
  309. return SUCCESS;
  310. }
  311. Status TbeOpTask::CheckAndExecuteAtomic(const vector<GeTensorDesc> &input_desc,
  312. const vector<DataBuffer> &input_buffers,
  313. vector<GeTensorDesc> &output_desc,
  314. vector<DataBuffer> &output_buffers,
  315. rtStream_t stream) {
  316. if (clear_atomic_ && atomic_task_ != nullptr) {
  317. return atomic_task_->LaunchKernel(input_desc, input_buffers, output_desc, output_buffers, stream);
  318. }
  319. return SUCCESS;
  320. }
  321. Status TbeOpTask::UpdateTilingArgs(rtStream_t stream) {
  322. size_t args_size = input_num_ + output_num_ + workspaces_.size();
  323. if (tiling_buffer_ != nullptr) {
  324. args_size++;
  325. }
  326. size_t temp_size = args_size * sizeof(void *);
  327. if (arg_size_ < temp_size) {
  328. GELOGD("Need to reset size of args_ from %zu to %zu.", arg_size_, temp_size);
  329. std::unique_ptr<uint8_t[]> args(new (std::nothrow) uint8_t[temp_size]());
  330. GE_CHECK_NOTNULL(args);
  331. if (memcpy_s(args.get(), temp_size, args_.get(), arg_size_) != EOK) {
  332. GELOGE(ACL_ERROR_GE_MEMORY_OPERATE_FAILED, "[Update][KernelArgs] failed for [%s].", node_->GetName().c_str());
  333. REPORT_INNER_ERROR("E19999", "update kernel args failed for %s.", node_->GetName().c_str());
  334. return ACL_ERROR_GE_MEMORY_OPERATE_FAILED;
  335. }
  336. args_ = std::move(args);
  337. arg_size_ = temp_size;
  338. }
  339. uintptr_t *arg_base = reinterpret_cast<uintptr_t *>(args_.get());
  340. size_t arg_index = input_num_ + output_num_;
  341. for (size_t i = 0; i < workspaces_.size(); ++i) {
  342. arg_base[arg_index++] = reinterpret_cast<uintptr_t>(workspaces_[i]);
  343. }
  344. if (tiling_buffer_ != nullptr) {
  345. GELOGD("[%s] Start to copy tiling info. size = %zu", node_->GetName().c_str(), tiling_data_.size());
  346. GE_CHK_RT_RET(rtMemcpyAsync(tiling_buffer_, max_tiling_size_, tiling_data_.data(), tiling_data_.size(),
  347. RT_MEMCPY_HOST_TO_DEVICE_EX, stream));
  348. arg_base[arg_index] = reinterpret_cast<uintptr_t>(tiling_buffer_);
  349. }
  350. return SUCCESS;
  351. }
  352. Status TbeOpTask::SetArgIndex() {
  353. const vector<bool> v_is_input_const = op_desc_->GetIsInputConst();
  354. size_t input_index = 0;
  355. for (size_t i = 0; i < op_desc_->GetAllInputsSize(); ++i) {
  356. const GeTensorDescPtr tensor_desc = op_desc_->MutableInputDesc(static_cast<uint32_t>(i));
  357. if (tensor_desc == nullptr) {
  358. GELOGD("SingleOp: %s, Index: %zu, has no input", op_desc_->GetName().c_str(), i);
  359. continue;
  360. }
  361. if (i < v_is_input_const.size() && v_is_input_const[i]) {
  362. GELOGD("SingleOp: %s, Index: %zu, input is const", op_desc_->GetName().c_str(), i);
  363. input_index++;
  364. continue;
  365. }
  366. arg_index_.emplace_back(input_index);
  367. input_index++;
  368. }
  369. return SUCCESS;
  370. }
  371. Status TbeOpTask::UpdateIoAddr(const vector<DataBuffer> &inputs, const vector<DataBuffer> &outputs) {
  372. if (arg_index_.size() != inputs.size()) {
  373. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "[Check][Size] Args size is %zu, but get input size is %zu.",
  374. arg_index_.size(), inputs.size());
  375. REPORT_INNER_ERROR("E19999", "[Check][Size] Args size is %zu, but get input size is %zu.",
  376. arg_index_.size(), inputs.size());
  377. return ACL_ERROR_GE_PARAM_INVALID;
  378. }
  379. uintptr_t *arg_base = reinterpret_cast<uintptr_t *>(args_.get());
  380. for (size_t i = 0; i < arg_index_.size(); ++i) {
  381. arg_base[arg_index_[i]] = reinterpret_cast<uintptr_t>(inputs[i].data);
  382. }
  383. for (size_t i = 0; i < op_desc_->GetOutputsSize(); ++i) {
  384. arg_base[input_num_ + i] = reinterpret_cast<uintptr_t>(outputs[i].data);
  385. }
  386. return SUCCESS;
  387. }
  388. Status TbeOpTask::LaunchKernel(const vector<GeTensorDesc> &input_desc,
  389. const vector<DataBuffer> &input_buffers,
  390. vector<GeTensorDesc> &output_desc,
  391. vector<DataBuffer> &output_buffers,
  392. rtStream_t stream) {
  393. GELOGD("[%s] Start to launch kernel", node_->GetName().c_str());
  394. GE_CHK_STATUS_RET(UpdateIoAddr(input_buffers, output_buffers), "[Update][IoAddr] failed.");
  395. GE_CHK_STATUS_RET_NOLOG(UpdateNodeByShape(input_desc, output_desc));
  396. GE_CHK_STATUS_RET_NOLOG(UpdateRunInfo());
  397. GE_CHK_STATUS_RET(AllocateWorkspaces(run_info_workspaces_), "[Allocate][Workspaces] failed.");
  398. GE_CHK_STATUS_RET(CheckAndExecuteAtomic(input_desc, input_buffers, output_desc, output_buffers, stream),
  399. "[Execute][AtomicTask] failed.");
  400. GE_CHK_STATUS_RET(UpdateTilingArgs(stream), "[Update][TilingArgs] failed.");
  401. GELOGD("[%s] Start to invoke rtKernelLaunch", node_->GetName().c_str());
  402. GE_CHK_STATUS_RET(DoLaunchKernel(stream), "Failed to do launch kernel.");
  403. return SUCCESS;
  404. }
  405. Status TbeOpTask::DoLaunchKernel(rtStream_t stream) {
  406. auto *sm_desc = reinterpret_cast<rtSmDesc_t *>(sm_desc_);
  407. if (handle_ == nullptr) {
  408. GE_CHK_RT_RET(rtKernelLaunch(stub_func_, block_dim_, args_.get(), static_cast<uint32_t>(arg_size_),
  409. sm_desc, stream));
  410. } else {
  411. std::string dev_func = original_kernel_key_ + "_" + std::to_string(tiling_key_);
  412. std::string kernel_info = node_info_ + "/" + std::to_string(tiling_key_);
  413. GE_CHK_RT_RET(rtKernelLaunchWithHandle(handle_, dev_func.c_str(), block_dim_, args_.get(),
  414. static_cast<uint32_t>(arg_size_), sm_desc, stream, kernel_info.c_str()));
  415. }
  416. return SUCCESS;
  417. }
  418. void TbeOpTask::GetIoAddr(uintptr_t *&arg_base, size_t &arg_count) {
  419. arg_base = reinterpret_cast<uintptr_t *>(args_.get());
  420. arg_count = arg_size_ / sizeof(void *);
  421. if (tiling_buffer_ != nullptr) {
  422. --arg_count;
  423. }
  424. }
  425. Status AtomicAddrCleanOpTask::UpdateNodeByShape(const vector<GeTensorDesc> &input_desc,
  426. const vector<GeTensorDesc> &output_desc) {
  427. return SUCCESS;
  428. }
  429. Status AtomicAddrCleanOpTask::UpdateIoAddr(const vector<DataBuffer> &inputs, const vector<DataBuffer> &outputs) {
  430. uintptr_t *arg_base = reinterpret_cast<uintptr_t *>(args_.get());
  431. for (auto atomic_output_index : atomic_output_indices_) {
  432. if (atomic_output_index >= static_cast<int>(outputs.size())) {
  433. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "[Update][Args] failed, atomic index must smaller then data size.");
  434. REPORT_INNER_ERROR("E19999", "[Update][Args] failed, atomic index must smaller then data size.");
  435. return ACL_ERROR_GE_PARAM_INVALID;
  436. }
  437. auto &output_buffer = outputs[atomic_output_index];
  438. *arg_base++ = reinterpret_cast<uintptr_t>(output_buffer.data);
  439. auto tensor_desc = op_desc_->MutableOutputDesc(atomic_output_index);
  440. int64_t size = 0;
  441. graphStatus graph_status = TensorUtils::GetTensorMemorySizeInBytes(*tensor_desc, size);
  442. if (graph_status != GRAPH_SUCCESS) {
  443. REPORT_CALL_ERROR("E19999", "Get tensor size in bytes failed!");
  444. GELOGE(graph_status, "[Get][TensorMemorySize] In Bytes failed!");
  445. return FAILED;
  446. }
  447. TensorUtils::SetSize(*tensor_desc, size);
  448. }
  449. return SUCCESS;
  450. }
  451. Status AtomicAddrCleanOpTask::UpdateTilingArgs(rtStream_t stream) {
  452. if (tiling_buffer_ != nullptr) {
  453. GELOGD("[%s] Start to copy tiling info. size = %zu", node_->GetName().c_str(), tiling_data_.size());
  454. GE_CHK_RT_RET(rtMemcpyAsync(tiling_buffer_, max_tiling_size_, tiling_data_.data(), tiling_data_.size(),
  455. RT_MEMCPY_HOST_TO_DEVICE_EX, stream));
  456. uintptr_t *arg_base = reinterpret_cast<uintptr_t *>(args_.get());
  457. size_t idx = atomic_output_indices_.size();
  458. arg_base[idx] = reinterpret_cast<uintptr_t>(tiling_buffer_);
  459. }
  460. return SUCCESS;
  461. }
  462. Status AtomicAddrCleanOpTask::CalcTilingInfo(optiling::utils::OpRunInfo &run_info) {
  463. auto ret = optiling::OpAtomicCalculateV2(*node_, run_info);
  464. if (ret != GRAPH_SUCCESS) {
  465. GELOGE(ACL_ERROR_GE_INTERNAL_ERROR, "[Invoke][OpAtomicCalculate] failed, ret = %u.", ret);
  466. REPORT_INNER_ERROR("E19999", "invoke OpAtomicCalculate failed, ret = %u.", ret);
  467. return ACL_ERROR_GE_INTERNAL_ERROR;
  468. }
  469. return SUCCESS;
  470. }
  471. Status AtomicAddrCleanOpTask::InitAtomicAddrCleanIndices() {
  472. GELOGD("[%s] Start to setup AtomicAddrClean task.", op_desc_->GetName().c_str());
  473. std::vector<int64_t> atomic_output_indices;
  474. (void) ge::AttrUtils::GetListInt(op_desc_, ATOMIC_ATTR_OUTPUT_INDEX, atomic_output_indices);
  475. if (atomic_output_indices.empty()) {
  476. GELOGE(INTERNAL_ERROR, "[Check][Size][%s] atomic_output_indices must not be empty.", op_desc_->GetName().c_str());
  477. REPORT_INNER_ERROR("E19999", "[%s] atomic_output_indices must not be empty.", op_desc_->GetName().c_str());
  478. return INTERNAL_ERROR;
  479. }
  480. size_t max_arg_size = tiling_buffer_ == nullptr ? arg_size_ : arg_size_ - 1;
  481. if (atomic_output_indices.size() > max_arg_size) {
  482. GELOGE(INTERNAL_ERROR, "[Check][Size][%s] atomic_output_indices invalid. atomic_output_indices size is %zu,"
  483. "arg size is %zu.", op_desc_->GetName().c_str(), atomic_output_indices.size(), arg_size_);
  484. REPORT_INNER_ERROR("E19999", "[%s] atomic_output_indices invalid. atomic_output_indices size is %zu,"
  485. "arg size is %zu.", op_desc_->GetName().c_str(), atomic_output_indices.size(), arg_size_);
  486. return INTERNAL_ERROR;
  487. }
  488. for (auto output_index : atomic_output_indices) {
  489. GELOGD("[%s] Adding output index [%ld]", op_desc_->GetName().c_str(), output_index);
  490. GE_CHECK_GE(output_index, 0);
  491. GE_CHECK_LE(output_index, INT32_MAX);
  492. atomic_output_indices_.emplace_back(static_cast<int>(output_index));
  493. }
  494. return SUCCESS;
  495. }
  496. AiCpuBaseTask::~AiCpuBaseTask() {
  497. if (ext_info_addr_dev_ != nullptr) {
  498. (void)rtFree(ext_info_addr_dev_);
  499. }
  500. }
  501. Status AiCpuBaseTask::SetExtInfoAndType(const std::string &kernel_ext_info, uint64_t kernel_id) {
  502. if (kernel_ext_info.empty()) {
  503. GELOGI("Kernel_ext_info is empty, no need copy to device.");
  504. return SUCCESS;
  505. }
  506. int32_t unknown_shape_type_val = 0;
  507. (void) AttrUtils::GetInt(op_desc_, ::ge::ATTR_NAME_UNKNOWN_SHAPE_TYPE, unknown_shape_type_val);
  508. GELOGD("Get unknown_type is %d.", unknown_shape_type_val);
  509. unknown_type_ = static_cast<UnknowShapeOpType>(unknown_shape_type_val);
  510. aicpu_ext_handle_.reset(new(std::nothrow) ::ge::hybrid::AicpuExtInfoHandler(op_desc_->GetName(),
  511. num_inputs_,
  512. num_outputs_,
  513. unknown_type_));
  514. GE_CHK_BOOL_RET_STATUS(aicpu_ext_handle_ != nullptr, ACL_ERROR_GE_MEMORY_ALLOCATION,
  515. "[Malloc][Memory] failed for aicpu_ext_handle!");
  516. Status ret = aicpu_ext_handle_->Parse(kernel_ext_info);
  517. if (ret != SUCCESS) {
  518. GELOGE(ret, "[Parse][Param:kernel_ext_info] failed, kernel_ext_info_size=%zu.", kernel_ext_info.size());
  519. REPORT_INNER_ERROR("E19999",
  520. "Parse Param:kernel_ext_info failed, kernel_ext_info_size=%zu.", kernel_ext_info.size());
  521. return ret;
  522. }
  523. GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateSessionInfo(ULLONG_MAX, kernel_id, false),
  524. "[Update][SessionInfo] failed.");
  525. GE_CHK_RT_RET(rtMalloc(&ext_info_addr_dev_, aicpu_ext_handle_->GetExtInfoLen(), RT_MEMORY_HBM));
  526. GE_CHK_RT_RET(rtMemcpy(ext_info_addr_dev_, aicpu_ext_handle_->GetExtInfoLen(),
  527. aicpu_ext_handle_->GetExtInfo(), aicpu_ext_handle_->GetExtInfoLen(),
  528. RT_MEMCPY_HOST_TO_DEVICE));
  529. return SUCCESS;
  530. }
  531. Status AiCpuBaseTask::SetInputConst() {
  532. input_is_const_.clear();
  533. const vector<bool> v_is_input_const = op_desc_->GetIsInputConst();
  534. for (size_t i = 0; i < op_desc_->GetAllInputsSize(); ++i) {
  535. const GeTensorDescPtr tensor_desc = op_desc_->MutableInputDesc(static_cast<uint32_t>(i));
  536. if (tensor_desc == nullptr) {
  537. GELOGD("SingleOp: %s, Index: %zu, has no input", op_desc_->GetName().c_str(), i);
  538. continue;
  539. }
  540. if (i < v_is_input_const.size() && v_is_input_const[i]) {
  541. GELOGD("SingleOp: %s, Index: %zu, input is const", op_desc_->GetName().c_str(), i);
  542. input_is_const_.push_back(true);
  543. continue;
  544. }
  545. input_is_const_.push_back(false);
  546. }
  547. return SUCCESS;
  548. }
  549. Status AiCpuBaseTask::UpdateExtInfo(const std::vector<GeTensorDesc> &input_desc,
  550. std::vector<GeTensorDesc> &output_desc,
  551. rtStream_t stream) {
  552. GELOGI("Update ext info begin, unknown_type=%d.", unknown_type_);
  553. GE_CHECK_NOTNULL(aicpu_ext_handle_);
  554. GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateExecuteMode(false), "[Update][ExecuteMode] failed.");
  555. if (num_inputs_ == 0 && num_outputs_ == 0) {
  556. GELOGI("No input and output, no need update ext info.");
  557. return SUCCESS;
  558. }
  559. size_t non_const_index = 0;
  560. for (size_t input_index = 0; input_index < num_inputs_; input_index++) {
  561. if (input_index < input_is_const_.size() && input_is_const_[input_index]) {
  562. // get input_desc from op_desc if const input, num_inputs_ is op_desc_ input_size
  563. auto const_input_desc = op_desc_->MutableInputDesc(static_cast<uint32_t>(input_index));
  564. GE_CHECK_NOTNULL(const_input_desc);
  565. GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateInputShapeAndType(input_index, *const_input_desc),
  566. "[Update][InputShapeAndType] failed, input_index:%zu.", input_index);
  567. continue;
  568. }
  569. GE_CHK_BOOL_RET_STATUS(non_const_index < input_desc.size(), ACL_ERROR_GE_PARAM_INVALID,
  570. "[Check][Size]Input_desc size is %zu, but get non_const_index is %zu", input_desc.size(), non_const_index);
  571. GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateInputShapeAndType(input_index, input_desc[non_const_index]),
  572. "[Update][InputShapeAndType]failed, input_index:%zu.", input_index);
  573. if (DumpManager::GetInstance().GetDumpProperties(kInferSessionId).IsSingleOpNeedDump()) {
  574. GE_CHK_STATUS_RET(op_desc_->UpdateInputDesc(input_index, input_desc[non_const_index]),
  575. "AiCpuTask Update [%zu]th input desc failed.",input_index);
  576. }
  577. non_const_index++;
  578. }
  579. if (unknown_type_ != DEPEND_COMPUTE) {
  580. for (size_t j = 0; j < num_outputs_; ++j) {
  581. GE_CHK_STATUS_RET(aicpu_ext_handle_->UpdateOutputShapeAndType(j, output_desc[j]),
  582. "[Update][OutputShapeAndType] failed, Output:%zu.", j);
  583. if (DumpManager::GetInstance().GetDumpProperties(kInferSessionId).IsSingleOpNeedDump()) {
  584. GE_CHK_STATUS_RET(op_desc_->UpdateOutputDesc(j, output_desc[j]),
  585. "AiCpuTask Update [%zu]th output desc failed.",j);
  586. }
  587. }
  588. }
  589. GE_CHK_RT_RET(rtMemcpyAsync(ext_info_addr_dev_,
  590. aicpu_ext_handle_->GetExtInfoLen(), // check size
  591. aicpu_ext_handle_->GetExtInfo(),
  592. aicpu_ext_handle_->GetExtInfoLen(),
  593. RT_MEMCPY_HOST_TO_DEVICE_EX,
  594. stream));
  595. GELOGI("Update ext info end.");
  596. return SUCCESS;
  597. }
  598. Status AiCpuBaseTask::UpdateOutputShape(vector<GeTensorDesc> &output_desc) {
  599. if (num_outputs_ == 0) {
  600. GELOGD("AiCpuBaseTask output_num is 0, no need update output shape.");
  601. return SUCCESS;
  602. }
  603. GELOGD("Start to update DEPEND_SHAPE_RANGE AiCpuBaseTask outputshape.");
  604. GE_CHK_RT_RET(rtMemcpy(aicpu_ext_handle_->GetExtInfo(), aicpu_ext_handle_->GetExtInfoLen(), ext_info_addr_dev_,
  605. aicpu_ext_handle_->GetExtInfoLen(), RT_MEMCPY_DEVICE_TO_HOST));
  606. for (size_t i = 0; i < num_outputs_; ++i) {
  607. GeShape shape;
  608. DataType data_type;
  609. aicpu_ext_handle_->GetOutputShapeAndType(i, shape, data_type);
  610. GE_CHK_STATUS_RET(UpdateShapeToOutputDesc(shape, output_desc[i]),
  611. "[Update][ShapeToOutputDesc] failed, output:%zu.", i);
  612. if (DumpManager::GetInstance().GetDumpProperties(kInferSessionId).IsSingleOpNeedDump()) {
  613. GE_CHK_STATUS_RET(op_desc_->UpdateOutputDesc(i, output_desc[i]), "[Update][OutputDesc] failed, output:%zu.", i);
  614. }
  615. }
  616. GELOGD("Update DEPEND_SHAPE_RANGE AiCpuBaseTask outputshape finished.");
  617. return SUCCESS;
  618. }
  619. Status AiCpuBaseTask::UpdateShapeToOutputDesc(const GeShape &shape_new, GeTensorDesc &output_desc) {
  620. auto shape_old = output_desc.GetShape();
  621. output_desc.SetShape(shape_new);
  622. GELOGD("Update AiCpuBaseTask shape from %s to %s", shape_old.ToString().c_str(), shape_new.ToString().c_str());
  623. auto origin_shape_old = output_desc.GetOriginShape();
  624. auto origin_format = output_desc.GetOriginFormat();
  625. auto format = output_desc.GetFormat();
  626. if (origin_format == format) {
  627. output_desc.SetOriginShape(shape_new);
  628. return SUCCESS;
  629. }
  630. std::vector<int64_t> origin_dims_new;
  631. auto trans_ret = formats::TransShape(format, shape_new.GetDims(),
  632. output_desc.GetDataType(), origin_format, origin_dims_new);
  633. GE_CHK_STATUS_RET(trans_ret,
  634. "[Trans][Shape] failed, AiCpuTask originFormat[%d] is not same as format[%d], shape=%s.",
  635. origin_format, format, shape_new.ToString().c_str());
  636. auto origin_shape_new = GeShape(origin_dims_new);
  637. output_desc.SetOriginShape(origin_shape_new);
  638. GELOGD("AiCpuTask originFormat[%d] is not same as format[%d], need update from %s ro %s.",
  639. origin_format, format, origin_shape_old.ToString().c_str(), origin_shape_new.ToString().c_str());
  640. return SUCCESS;
  641. }
  642. Status AiCpuBaseTask::UpdateIoAddr(const vector<DataBuffer> &inputs, const vector<DataBuffer> &outputs) {
  643. uintptr_t *arg_base = nullptr;
  644. size_t arg_num = 0;
  645. GetIoAddr(arg_base, arg_num);
  646. // input number and output number was check in ValidateParams
  647. size_t non_const_index = 0;
  648. for (size_t input_index = 0; input_index < num_inputs_; input_index++) {
  649. if (input_index < input_is_const_.size() && input_is_const_[input_index]) {
  650. // const input no need update addr
  651. GE_CHECK_NOTNULL(arg_base);
  652. GELOGD("AICpuTask input[%zu] addr = %lu", input_index, *arg_base);
  653. arg_base++;
  654. continue;
  655. }
  656. GE_CHK_BOOL_RET_STATUS(non_const_index < inputs.size(), ACL_ERROR_GE_PARAM_INVALID,
  657. "[Check][Size] Input size is %zu, but get non_const_index is %zu", inputs.size(), non_const_index);
  658. auto addr = inputs[non_const_index].data;
  659. GE_CHECK_NOTNULL(addr);
  660. GELOGD("AICpuTask input[%zu] addr = %p", input_index, addr);
  661. *arg_base++ = reinterpret_cast<uintptr_t>(addr);
  662. non_const_index++;
  663. }
  664. for (size_t i = 0; i < outputs.size(); ++i) {
  665. auto addr = outputs[i].data;
  666. GE_CHECK_NOTNULL(addr);
  667. GELOGD("AICpuTask output[%zu] addr = %p", i, addr);
  668. *arg_base++ = reinterpret_cast<uintptr_t>(addr);
  669. }
  670. return SUCCESS;
  671. }
  672. AiCpuTask::~AiCpuTask() {
  673. FreeHbm(args_);
  674. FreeHbm(io_addr_);
  675. FreeHbm(workspace_addr_);
  676. FreeHbm(copy_workspace_buf_);
  677. FreeHbm(copy_ioaddr_dev_);
  678. FreeHbm(copy_input_release_flag_dev_);
  679. FreeHbm(copy_input_data_size_dev_);
  680. FreeHbm(copy_input_src_dev_);
  681. FreeHbm(copy_input_dst_dev_);
  682. FreeHbm(copy_task_args_buf_);
  683. for (auto summary : output_summary_) {
  684. FreeHbm(summary);
  685. }
  686. for (auto out_shape : out_shape_hbm_) {
  687. FreeHbm(out_shape);
  688. }
  689. }
  690. Status AiCpuTask::LaunchKernel(rtStream_t stream) {
  691. GELOGD("Start to launch kernel. task = %s", this->op_type_.c_str());
  692. auto ret = rtMemcpyAsync(io_addr_,
  693. io_addr_size_,
  694. io_addr_host_.data(),
  695. io_addr_host_.size() * sizeof(void *),
  696. RT_MEMCPY_HOST_TO_DEVICE_EX,
  697. stream);
  698. if (ret != RT_ERROR_NONE) {
  699. GELOGE(ret, "[MemcpyAsync][Date] failed. ret = %d, task = %s", ret, this->op_type_.c_str());
  700. REPORT_CALL_ERROR("E19999", "rtMemcpyAsync data failed, ret = %d, task = %s", ret, this->op_type_.c_str());
  701. return RT_ERROR_TO_GE_STATUS(ret);
  702. }
  703. GELOGI("To invoke rtKernelLaunchEx. task = %s", this->op_type_.c_str());
  704. ret = rtKernelLaunchEx(args_, arg_size_, 0, stream);
  705. if (ret != RT_ERROR_NONE) {
  706. GELOGE(ret, "[Invoke][rtKernelLaunch] failed. ret = %d, task = %s", ret, this->op_type_.c_str());
  707. REPORT_CALL_ERROR("E19999", "invoke rtKernelLaunchEx failed, ret = %d, task = %s", ret, this->op_type_.c_str());
  708. return RT_ERROR_TO_GE_STATUS(ret);
  709. }
  710. GELOGI("[TASK_INFO] %lu/%s", kernel_id_, op_type_.c_str());
  711. GELOGD("Done launch kernel successfully. task = %s", this->op_type_.c_str());
  712. return SUCCESS;
  713. }
  714. Status AiCpuTask::PrepareCopyInputs(vector<DataBuffer> &outputs) {
  715. std::vector<uint64_t> copy_input_release_flag;
  716. std::vector<uint64_t> copy_input_data_size;
  717. std::vector<uint64_t> copy_input_src;
  718. std::vector<uint64_t> copy_input_dst;
  719. for (size_t i = 0; i < num_outputs_; ++i) {
  720. const auto &summary = output_summary_host_[i];
  721. GELOGI("Node out[%zu] summary, shape data=0x%lx, shape data size=%lu, raw data=0x%lx, raw data size=%lu.",
  722. i, summary.shape_data_ptr, summary.shape_data_size,
  723. summary.raw_data_ptr, summary.raw_data_size);
  724. auto output = outputs[i];
  725. copy_input_release_flag.emplace_back(kReleaseFlag);
  726. if (summary.raw_data_size > 0) {
  727. copy_input_data_size.emplace_back(output.length);
  728. } else {
  729. copy_input_data_size.emplace_back(summary.raw_data_size);
  730. }
  731. copy_input_src.emplace_back(summary.raw_data_ptr);
  732. copy_input_dst.emplace_back(reinterpret_cast<uintptr_t>(output.data));
  733. const auto &shape_buffer = out_shape_hbm_[i];
  734. copy_input_release_flag.emplace_back(kReleaseFlag);
  735. copy_input_data_size.emplace_back(summary.shape_data_size);
  736. copy_input_src.emplace_back(summary.shape_data_ptr);
  737. copy_input_dst.emplace_back(reinterpret_cast<uintptr_t>(shape_buffer));
  738. }
  739. const size_t copy_input_buf_len = num_outputs_ * kCopyNum * sizeof(uint64_t);
  740. GE_CHK_RT_RET(rtMemcpy(copy_input_release_flag_dev_, copy_input_buf_len,
  741. copy_input_release_flag.data(), copy_input_buf_len, RT_MEMCPY_HOST_TO_DEVICE));
  742. GE_CHK_RT_RET(rtMemcpy(copy_input_data_size_dev_, copy_input_buf_len,
  743. copy_input_data_size.data(), copy_input_buf_len, RT_MEMCPY_HOST_TO_DEVICE));
  744. GE_CHK_RT_RET(rtMemcpy(copy_input_src_dev_, copy_input_buf_len,
  745. copy_input_src.data(), copy_input_buf_len, RT_MEMCPY_HOST_TO_DEVICE));
  746. GE_CHK_RT_RET(rtMemcpy(copy_input_dst_dev_, copy_input_buf_len,
  747. copy_input_dst.data(), copy_input_buf_len, RT_MEMCPY_HOST_TO_DEVICE));
  748. return SUCCESS;
  749. }
  750. Status AiCpuTask::ReadResultSummaryAndPrepareMemory() {
  751. for (size_t i = 0; i < num_outputs_; ++i) {
  752. auto &result_summary = output_summary_host_[i];
  753. GE_CHK_RT_RET(rtMemcpy(&result_summary, sizeof(aicpu::FWKAdapter::ResultSummary),
  754. output_summary_[i], sizeof(aicpu::FWKAdapter::ResultSummary),
  755. RT_MEMCPY_DEVICE_TO_HOST));
  756. auto shape_data_size = result_summary.shape_data_size;
  757. void *shape_buffer = nullptr;
  758. if (shape_data_size > 0) {
  759. GE_CHK_RT_RET(rtMalloc(&shape_buffer, shape_data_size, RT_MEMORY_HBM));
  760. }
  761. out_shape_hbm_.emplace_back(shape_buffer);
  762. }
  763. return SUCCESS;
  764. }
  765. Status AiCpuTask::CopyDataToHbm(vector<DataBuffer> &outputs,
  766. rtStream_t stream) {
  767. GE_CHK_STATUS_RET_NOLOG(PrepareCopyInputs(outputs));
  768. GE_CHK_RT_RET(rtKernelLaunchEx(copy_task_args_buf_, sizeof(STR_FWK_OP_KERNEL),
  769. RT_KERNEL_DEFAULT, stream));
  770. GE_CHK_RT_RET(rtStreamSynchronize(stream));
  771. return SUCCESS;
  772. }
  773. Status AiCpuTask::UpdateShapeByHbmBuffer(vector<GeTensorDesc> &output_desc) {
  774. for (size_t i = 0; i < num_outputs_; ++i) {
  775. const auto &result_summary = output_summary_host_[i];
  776. std::vector<int64_t> shape_dims;
  777. if (result_summary.shape_data_size > 0) {
  778. const auto &shape_hbm = out_shape_hbm_[i];
  779. uint32_t dim_num = result_summary.shape_data_size / sizeof(int64_t);
  780. std::unique_ptr<int64_t[]> shape_addr(new (std::nothrow) int64_t[dim_num]());
  781. GE_CHECK_NOTNULL(shape_addr);
  782. GE_CHK_RT_RET(rtMemcpy(shape_addr.get(), result_summary.shape_data_size, shape_hbm,
  783. result_summary.shape_data_size, RT_MEMCPY_DEVICE_TO_HOST));
  784. for (uint32_t dim_idx = 0; dim_idx < dim_num; ++dim_idx) {
  785. shape_dims.emplace_back(shape_addr[dim_idx]);
  786. GELOGD("Node [%zu]th output dim[%u]=%ld.", i, dim_idx, shape_addr[dim_idx]);
  787. }
  788. }
  789. GE_CHK_STATUS_RET(UpdateShapeToOutputDesc(GeShape(shape_dims), output_desc[i]),
  790. "[Update][ShapeToOutputDesc] failed , output:%zu.", i);
  791. if (DumpManager::GetInstance().GetDumpProperties(kInferSessionId).IsSingleOpNeedDump()) {
  792. GE_CHK_STATUS_RET(op_desc_->UpdateOutputDesc(i, output_desc[i]), "[Update][OutputDesc] failed, output:%zu.", i);
  793. }
  794. }
  795. return SUCCESS;
  796. }
  797. Status AiCpuTask::UpdateShapeAndDataByResultSummary(vector<GeTensorDesc> &output_desc,
  798. vector<DataBuffer> &outputs,
  799. rtStream_t stream) {
  800. if (num_outputs_ == 0) {
  801. GELOGI("Output num is 0, there is no need to update the output and size.");
  802. return SUCCESS;
  803. }
  804. GELOGI("Update shape and data by result summary begin.");
  805. for (auto out_shape : out_shape_hbm_) {
  806. FreeHbm(out_shape);
  807. }
  808. out_shape_hbm_.clear();
  809. GE_CHK_STATUS_RET(ReadResultSummaryAndPrepareMemory(),
  810. "[Read][ResultSummaryAndPrepareMemory] failed.");
  811. GE_CHK_STATUS_RET(CopyDataToHbm(outputs, stream),
  812. "[Copy][DataToHbm] failed.");
  813. GE_CHK_STATUS_RET(UpdateShapeByHbmBuffer(output_desc),
  814. "[Update][ShapeByHbmBuffer] failed.");
  815. for (auto out_shape : out_shape_hbm_) {
  816. FreeHbm(out_shape);
  817. }
  818. out_shape_hbm_.clear();
  819. GELOGI("Update shape and data by result summary end.");
  820. return SUCCESS;
  821. }
  822. Status AiCpuTask::InitForSummaryAndCopy() {
  823. if (unknown_type_ != DEPEND_COMPUTE || num_outputs_ == 0) {
  824. GELOGI("Unknown_type is %d, output num is %zu.", unknown_type_, num_outputs_);
  825. return SUCCESS;
  826. }
  827. output_summary_.resize(num_outputs_);
  828. constexpr auto result_summary_size = sizeof(aicpu::FWKAdapter::ResultSummary);
  829. for (size_t i = 0; i < num_outputs_; ++i) {
  830. GE_CHK_RT_RET(rtMalloc(&output_summary_[i], result_summary_size, RT_MEMORY_HBM));
  831. }
  832. output_summary_host_.resize(num_outputs_);
  833. const size_t copy_input_buf_len = num_outputs_ * kCopyNum * sizeof(uint64_t);
  834. GE_CHK_RT_RET(rtMalloc(&copy_input_release_flag_dev_, copy_input_buf_len, RT_MEMORY_HBM));
  835. GE_CHK_RT_RET(rtMalloc(&copy_input_data_size_dev_, copy_input_buf_len, RT_MEMORY_HBM));
  836. GE_CHK_RT_RET(rtMalloc(&copy_input_src_dev_, copy_input_buf_len, RT_MEMORY_HBM));
  837. GE_CHK_RT_RET(rtMalloc(&copy_input_dst_dev_, copy_input_buf_len, RT_MEMORY_HBM));
  838. GE_CHK_RT_RET(rtMalloc(&copy_task_args_buf_, sizeof(STR_FWK_OP_KERNEL), RT_MEMORY_HBM));
  839. std::vector<uint64_t> copy_io_addr;
  840. copy_io_addr.emplace_back(reinterpret_cast<uintptr_t>(copy_input_release_flag_dev_));
  841. copy_io_addr.emplace_back(reinterpret_cast<uintptr_t>(copy_input_data_size_dev_));
  842. copy_io_addr.emplace_back(reinterpret_cast<uintptr_t>(copy_input_src_dev_));
  843. copy_io_addr.emplace_back(reinterpret_cast<uintptr_t>(copy_input_dst_dev_));
  844. const auto copy_io_addr_size = sizeof(uint64_t) * copy_io_addr.size();
  845. GE_CHK_RT_RET(rtMalloc(&copy_ioaddr_dev_, copy_io_addr_size, RT_MEMORY_HBM));
  846. GE_CHK_RT_RET(rtMemcpy(copy_ioaddr_dev_, copy_io_addr_size,
  847. copy_io_addr.data(), copy_io_addr_size, RT_MEMCPY_HOST_TO_DEVICE));
  848. return SUCCESS;
  849. }
  850. Status AiCpuTask::SetMemCopyTask(const domi::KernelExDef &kernel_def) {
  851. if (kernel_def.args_size() > sizeof(STR_FWK_OP_KERNEL)) {
  852. GELOGE(ACL_ERROR_GE_PARAM_INVALID, "[Check][Size]sizeof STR_FWK_OP_KERNEL is: %lu, but args_size is: %d",
  853. sizeof(STR_FWK_OP_KERNEL), kernel_def.args_size());
  854. REPORT_INNER_ERROR("E19999", "[sizeof STR_FWK_OP_KERNEL is: %lu, but args_size is: %d",
  855. sizeof(STR_FWK_OP_KERNEL), kernel_def.args_size());
  856. return ACL_ERROR_GE_PARAM_INVALID;
  857. }
  858. GE_CHK_RT_RET(rtMalloc(&copy_workspace_buf_, kernel_def.task_info_size(), RT_MEMORY_HBM));
  859. GE_CHK_RT_RET(rtMemcpy(copy_workspace_buf_, kernel_def.task_info_size(),
  860. kernel_def.task_info().data(), kernel_def.task_info_size(), RT_MEMCPY_HOST_TO_DEVICE));
  861. STR_FWK_OP_KERNEL aicpu_task = {0};
  862. auto sec_ret = memcpy_s(&aicpu_task, sizeof(STR_FWK_OP_KERNEL),
  863. kernel_def.args().data(), kernel_def.args().size());
  864. if (sec_ret != EOK) {
  865. GELOGE(ACL_ERROR_GE_MEMORY_OPERATE_FAILED, "[Update][TaskArgs] failed, ret: %d", sec_ret);
  866. REPORT_INNER_ERROR("E19999", "update STR_FWK_OP_KERNEL args failed because memcpy_s return %d.", sec_ret);
  867. return ACL_ERROR_GE_MEMORY_OPERATE_FAILED;
  868. }
  869. aicpu_task.fwkKernelBase.fwk_kernel.inputOutputAddr = reinterpret_cast<uintptr_t>(copy_ioaddr_dev_);
  870. aicpu_task.fwkKernelBase.fwk_kernel.workspaceBaseAddr = reinterpret_cast<uintptr_t>(copy_workspace_buf_);
  871. aicpu_task.fwkKernelBase.fwk_kernel.extInfoAddr = 0;
  872. aicpu_task.fwkKernelBase.fwk_kernel.extInfoLen = 0;
  873. GE_CHK_RT_RET(rtMemcpy(copy_task_args_buf_, sizeof(STR_FWK_OP_KERNEL),
  874. &aicpu_task, sizeof(STR_FWK_OP_KERNEL), RT_MEMCPY_HOST_TO_DEVICE));
  875. return SUCCESS;
  876. }
  877. Status AiCpuTask::LaunchKernel(const std::vector<GeTensorDesc> &input_desc,
  878. const std::vector<DataBuffer> &input_buffers,
  879. std::vector<GeTensorDesc> &output_desc,
  880. std::vector<DataBuffer> &output_buffers,
  881. rtStream_t stream) {
  882. GE_CHK_STATUS_RET_NOLOG(UpdateExtInfo(input_desc, output_desc, stream));
  883. if (unknown_type_ == DEPEND_COMPUTE) {
  884. std::vector<DataBuffer> summary_buffers;
  885. for (size_t i = 0; i < num_outputs_; ++i) {
  886. summary_buffers.emplace_back(output_summary_[i], sizeof(aicpu::FWKAdapter::ResultSummary), false);
  887. }
  888. GE_CHK_STATUS_RET_NOLOG(UpdateIoAddr(input_buffers, summary_buffers));
  889. } else {
  890. GE_CHK_STATUS_RET_NOLOG(UpdateIoAddr(input_buffers, output_buffers));
  891. }
  892. GE_CHK_STATUS_RET_NOLOG(LaunchKernel(stream));
  893. if (unknown_type_ == DEPEND_SHAPE_RANGE) {
  894. GE_CHK_RT_RET(rtStreamSynchronize(stream));
  895. GE_CHK_STATUS_RET_NOLOG(UpdateOutputShape(output_desc));
  896. } else if (unknown_type_ == DEPEND_COMPUTE) {
  897. GE_CHK_RT_RET(rtStreamSynchronize(stream));
  898. GE_CHK_STATUS_RET_NOLOG(UpdateShapeAndDataByResultSummary(output_desc, output_buffers, stream));
  899. }
  900. return SUCCESS;
  901. }
  902. Status AiCpuBaseTask::UpdateArgTable(const SingleOpModelParam &param) {
  903. // aicpu do not have workspace, for now
  904. return DoUpdateArgTable(param, false);
  905. }
  906. const std::string &AiCpuBaseTask::GetTaskType() const { return kTaskTypeAicpu; }
  907. void AiCpuTask::GetIoAddr(uintptr_t *&arg_base, size_t &arg_count) {
  908. arg_base = reinterpret_cast<uintptr_t *>(io_addr_host_.data());
  909. arg_count = io_addr_host_.size();
  910. }
  911. void AiCpuCCTask::SetKernelArgs(std::unique_ptr<uint8_t[]> args, size_t arg_size) {
  912. args_ = std::move(args);
  913. arg_size_ = arg_size;
  914. // The blockdim value is defult "1" for rtCpuKernelLaunch
  915. block_dim_ = 1;
  916. }
  917. void AiCpuCCTask::SetSoName(const std::string &so_name) { so_name_ = so_name; }
  918. void AiCpuCCTask::SetkernelName(const std::string &kernel_Name) { kernel_name_ = kernel_Name; }
  919. void AiCpuCCTask::SetIoAddr(uintptr_t *io_addr) { io_addr_ = io_addr; }
  920. const void *AiCpuCCTask::GetArgs() const { return args_.get(); }
  921. size_t AiCpuCCTask::GetArgSize() const { return arg_size_; }
  922. AiCpuCCTask::~AiCpuCCTask() {
  923. }
  924. Status AiCpuCCTask::LaunchKernel(rtStream_t stream) {
  925. GELOGI("To invoke rtCpuKernelLaunch. block_dim = %u, so_name is %s, kernel_name is %s", block_dim_, so_name_.data(),
  926. kernel_name_.data());
  927. // sm_desc is nullptr, because l2 buffer does not support
  928. auto *sm_desc = reinterpret_cast<rtSmDesc_t *>(sm_desc_);
  929. auto ret = rtCpuKernelLaunchWithFlag(static_cast<const void *>(so_name_.data()),
  930. static_cast<const void *>(kernel_name_.data()),
  931. block_dim_, args_.get(), static_cast<uint32_t>(arg_size_),
  932. sm_desc, stream, dump_flag_);
  933. if (ret != RT_ERROR_NONE) {
  934. GELOGE(ret, "[Invoke][rtCpuKernelLaunchWithFlag] failed. ret = %d.", ret);
  935. REPORT_CALL_ERROR("E19999", "invoke rtCpuKernelLaunchWithFlag failed, ret:%d.", ret);
  936. return RT_ERROR_TO_GE_STATUS(ret);
  937. }
  938. GELOGI("[TASK_INFO] %lu/%s", kernel_id_, op_type_.c_str());
  939. GELOGD("Invoke rtCpuKernelLaunch succeeded");
  940. return SUCCESS;
  941. }
  942. Status AiCpuCCTask::LaunchKernel(const std::vector<GeTensorDesc> &input_desc,
  943. const std::vector<DataBuffer> &input_buffers,
  944. std::vector<GeTensorDesc> &output_desc,
  945. std::vector<DataBuffer> &output_buffers,
  946. rtStream_t stream) {
  947. GE_CHK_STATUS_RET_NOLOG(UpdateExtInfo(input_desc, output_desc, stream));
  948. GE_CHK_STATUS_RET_NOLOG(UpdateIoAddr(input_buffers, output_buffers));
  949. GE_CHK_STATUS_RET_NOLOG(LaunchKernel(stream));
  950. if (unknown_type_ == DEPEND_SHAPE_RANGE) {
  951. GE_CHK_RT_RET(rtStreamSynchronize(stream));
  952. GE_CHK_STATUS_RET_NOLOG(UpdateOutputShape(output_desc));
  953. }
  954. return SUCCESS;
  955. }
  956. void AiCpuCCTask::GetIoAddr(uintptr_t *&arg_base, size_t &arg_count) {
  957. arg_base = io_addr_;
  958. arg_count = io_addr_num_;
  959. }
  960. Status MemcpyAsyncTask::LaunchKernel(rtStream_t stream) {
  961. auto src_addr = reinterpret_cast<void *>(addresses_[0]);
  962. auto dst_addr = reinterpret_cast<void *>(addresses_[1]);
  963. kind_ = (kind_ == RT_MEMCPY_ADDR_DEVICE_TO_DEVICE) ? RT_MEMCPY_DEVICE_TO_DEVICE : kind_;
  964. GE_CHK_RT_RET(rtMemcpyAsync(dst_addr, dst_max_, src_addr, count_, kind_, stream));
  965. return SUCCESS;
  966. }
  967. void MemcpyAsyncTask::GetIoAddr(uintptr_t *&arg_base, size_t &arg_count) {
  968. arg_base = addresses_;
  969. arg_count = kMemcpyArgCount;
  970. }
  971. } // 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