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