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aicpu_constant_folding_pass.cc 23 kB

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  1. /**
  2. * Copyright 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 "graph/passes/aicpu_constant_folding_pass.h"
  17. #include <memory>
  18. #include <vector>
  19. #include "common/debug/log.h"
  20. #include "common/ge/ge_util.h"
  21. #include "common/types.h"
  22. #include "framework/common/debug/ge_log.h"
  23. #include "graph/debug/ge_attr_define.h"
  24. #include "graph/utils/attr_utils.h"
  25. #include "graph/utils/node_utils.h"
  26. #include "graph/utils/op_desc_utils.h"
  27. #include "graph/utils/type_utils.h"
  28. #include "init/gelib.h"
  29. #include "opskernel_manager/ops_kernel_builder_manager.h"
  30. namespace {
  31. const char *const kKernelLibName = "aicpu_tf_kernel";
  32. const char *const kNotSupported = "0";
  33. const uint64_t kReleaseFlag = 1;
  34. const uint64_t kOpsFlag = 1;
  35. const uint64_t kDouble = 2;
  36. } // namespace
  37. namespace ge {
  38. Status AicpuConstantFoldingPass::Run(ge::NodePtr &node) {
  39. GE_CHECK_NOTNULL(node);
  40. GELOGD("Start aicpu constant folding on node [%s]", node->GetName().c_str());
  41. if (IsSkipFold(node)) {
  42. return SUCCESS;
  43. }
  44. vector<ConstGeTensorPtr> weight_vec;
  45. bool flag = CheckInput(node, weight_vec);
  46. if (!flag) {
  47. return SUCCESS;
  48. }
  49. OpDescPtr node_desc = node->GetOpDesc(); // checked before
  50. vector<DataPtrInfo> data_vec;
  51. vector<AddrAndType> input_addrs;
  52. vector<uint64_t> output_addrs;
  53. Status ret = GetInputAddrs(weight_vec, input_addrs);
  54. if (ret != SUCCESS) {
  55. ReleaseMemory(input_addrs, output_addrs, data_vec);
  56. return SUCCESS;
  57. }
  58. ret = GetOutputAddrs(node_desc, output_addrs);
  59. if (ret != SUCCESS) {
  60. ReleaseMemory(input_addrs, output_addrs, data_vec);
  61. return SUCCESS;
  62. }
  63. ret = LaunchSingleOpRunTask(node, input_addrs, output_addrs);
  64. if (ret != SUCCESS) {
  65. ReleaseMemory(input_addrs, output_addrs, data_vec);
  66. return SUCCESS;
  67. }
  68. GELOGI("[Node:%s] Launch singleOpRunTask success", node->GetName().c_str());
  69. vector<uint64_t> data_infos;
  70. ret = GenerateDataPtrInfo(output_addrs, data_vec, data_infos);
  71. if (ret != SUCCESS) {
  72. ReleaseMemory(input_addrs, output_addrs, data_vec);
  73. return SUCCESS;
  74. }
  75. GELOGI("[Node:%s] Generate dataPtrInfo success", node->GetName().c_str());
  76. ret = LaunchMemCopyTask(data_infos);
  77. if (ret != SUCCESS) {
  78. ReleaseMemory(input_addrs, output_addrs, data_vec);
  79. return SUCCESS;
  80. }
  81. GELOGI("[Node:%s] Launch memCopyTask success", node->GetName().c_str());
  82. vector<GeTensorPtr> outputs;
  83. ret = GenerateGeTensor(node_desc, data_vec, outputs);
  84. if (ret != SUCCESS) {
  85. ReleaseMemory(input_addrs, output_addrs, data_vec);
  86. return SUCCESS;
  87. }
  88. ReleaseMemory(input_addrs, output_addrs, data_vec);
  89. GELOGI("[Node:%s] Generate geTensor success", node->GetName().c_str());
  90. return Folding(node, outputs);
  91. }
  92. bool AicpuConstantFoldingPass::CheckInput(const NodePtr &node, vector<ConstGeTensorPtr> &weight_vec) {
  93. OpDescPtr node_desc = node->GetOpDesc();
  94. if (node_desc == nullptr) {
  95. GELOGW("Opdesc of %s is null", node->GetName().c_str());
  96. return false;
  97. }
  98. DataType data_type = node_desc->GetOutputDesc(0).GetDataType();
  99. Format format = node_desc->GetOutputDesc(0).GetFormat();
  100. GELOGD("Current [node:%s, type:%s] info: format: %s, datatype:%s", node->GetName().c_str(), node->GetType().c_str(),
  101. TypeUtils::FormatToSerialString(format).c_str(), TypeUtils::DataTypeToSerialString(data_type).c_str());
  102. auto input_nodes = OpDescUtils::GetConstInputNode(*node);
  103. if (input_nodes.empty() || input_nodes.size() != node_desc->GetInputsSize()) {
  104. GELOGD("Const input nodes size is %zu, and nodeDesc inputsSize is %zu, skip fold.", input_nodes.size(),
  105. node_desc->GetInputsSize());
  106. return false;
  107. }
  108. weight_vec = OpDescUtils::GetInputData(input_nodes);
  109. return true;
  110. }
  111. Status AicpuConstantFoldingPass::GetInputAddrs(const vector<ConstGeTensorPtr> &weight_vec,
  112. vector<AddrAndType> &input_addrs) {
  113. if (weight_vec.empty()) {
  114. GELOGE(FAILED, "Weight is null");
  115. return FAILED;
  116. }
  117. for (const ConstGeTensorPtr &weight : weight_vec) {
  118. void *input_addr = nullptr;
  119. GE_CHK_RT_RET(rtMalloc(&input_addr, weight->GetData().size(), RT_MEMORY_HBM));
  120. rtError_t rt_ret = rtMemcpy(input_addr, weight->GetData().size(), weight->GetData().data(),
  121. weight->GetData().size(), RT_MEMCPY_HOST_TO_DEVICE);
  122. if (rt_ret != RT_ERROR_NONE) {
  123. GELOGE(rt_ret, "rtMemcpy error");
  124. GE_CHK_RT(rtFree(input_addr));
  125. return FAILED;
  126. }
  127. AddrAndType input_info = {static_cast<uint64_t>(reinterpret_cast<uintptr_t>(input_addr)), kData};
  128. input_addrs.emplace_back(input_info);
  129. }
  130. return SUCCESS;
  131. }
  132. Status AicpuConstantFoldingPass::GetOutputAddrs(const OpDescPtr &node_desc, vector<uint64_t> &output_addrs) {
  133. if (node_desc->GetOutputsSize() == 0) {
  134. GELOGE(FAILED, "Output size is 0 ");
  135. return FAILED;
  136. }
  137. for (size_t i = 0; i < node_desc->GetOutputsSize(); ++i) {
  138. void *summary_addr = nullptr;
  139. GE_CHK_RT_RET(rtMalloc(&summary_addr, sizeof(aicpu::FWKAdapter::ResultSummary), RT_MEMORY_HBM));
  140. output_addrs.emplace_back(static_cast<uint64_t>(reinterpret_cast<uintptr_t>(summary_addr)));
  141. }
  142. return SUCCESS;
  143. }
  144. Status AicpuConstantFoldingPass::GenerateDataPtrInfo(const vector<uint64_t> &output_addrs,
  145. vector<DataPtrInfo> &data_vec, vector<uint64_t> &data_infos) {
  146. for (uint64_t output_addr : output_addrs) {
  147. aicpu::FWKAdapter::ResultSummary result_summary;
  148. GE_CHK_RT_RET(rtMemcpy(&result_summary, sizeof(aicpu::FWKAdapter::ResultSummary),
  149. reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(output_addr)),
  150. sizeof(aicpu::FWKAdapter::ResultSummary), RT_MEMCPY_DEVICE_TO_HOST));
  151. void *raw_data_addr = nullptr;
  152. GE_CHK_RT_RET(rtMalloc(&raw_data_addr, result_summary.raw_data_size, RT_MEMORY_HBM));
  153. void *shape_data_addr = nullptr;
  154. // shape_data_size = 0 means scalar
  155. if (result_summary.shape_data_size != 0) {
  156. rtError_t rt_ret = rtMalloc(&shape_data_addr, result_summary.shape_data_size, RT_MEMORY_HBM);
  157. if (rt_ret != RT_ERROR_NONE) {
  158. GELOGE(rt_ret, "rtMalloc error");
  159. GE_CHK_RT(rtFree(raw_data_addr));
  160. return FAILED;
  161. }
  162. }
  163. DataPtrInfo raw_data_info;
  164. raw_data_info.release_flag = kReleaseFlag;
  165. raw_data_info.data_size = result_summary.raw_data_size;
  166. raw_data_info.src_ptr = result_summary.raw_data_ptr;
  167. raw_data_info.dst_ptr = static_cast<uint64_t>(reinterpret_cast<uintptr_t>(raw_data_addr));
  168. data_vec.emplace_back(raw_data_info);
  169. DataPtrInfo shape_data_info;
  170. shape_data_info.release_flag = kReleaseFlag;
  171. shape_data_info.data_size = result_summary.shape_data_size;
  172. shape_data_info.src_ptr = result_summary.shape_data_ptr;
  173. shape_data_info.dst_ptr = static_cast<uint64_t>(reinterpret_cast<uintptr_t>(shape_data_addr));
  174. data_vec.emplace_back(shape_data_info);
  175. }
  176. for (const DataPtrInfo &data_info : data_vec) {
  177. data_infos.emplace_back(static_cast<uint64_t>(reinterpret_cast<uintptr_t>(&data_info)));
  178. }
  179. return SUCCESS;
  180. }
  181. Status AicpuConstantFoldingPass::UpdateWorkSpaceAddr(string &task_info, STR_FWK_OP_KERNEL &task) {
  182. // Update the workspace_addr
  183. if (task_info.empty()) {
  184. GELOGE(FAILED, "task_info is empty ");
  185. return FAILED;
  186. }
  187. void *workspace_addr = nullptr;
  188. GE_CHK_RT_RET(rtMalloc(&workspace_addr, task_info.size(), RT_MEMORY_HBM));
  189. rtError_t rt_ret =
  190. rtMemcpy(workspace_addr, task_info.size(), task_info.data(), task_info.size(), RT_MEMCPY_HOST_TO_DEVICE);
  191. if (rt_ret != RT_ERROR_NONE) {
  192. GELOGE(rt_ret, "rtMemcpy error");
  193. GE_CHK_RT(rtFree(workspace_addr));
  194. return FAILED;
  195. }
  196. uint64_t workspace_base_addr = static_cast<uint64_t>(reinterpret_cast<uintptr_t>(workspace_addr));
  197. task.fwkKernelBase.fwk_kernel.workspaceBaseAddr = workspace_base_addr;
  198. return SUCCESS;
  199. }
  200. Status AicpuConstantFoldingPass::UpdateInputAndOutputAddr(const vector<uint64_t> &io_addrs, STR_FWK_OP_KERNEL &task) {
  201. auto addrs_size = sizeof(uint64_t) * (io_addrs.size());
  202. if (addrs_size <= 0) {
  203. GELOGE(FAILED, "addrs_size is less than 1 ");
  204. return FAILED;
  205. }
  206. void *input_output_addr = nullptr;
  207. GE_CHK_RT_RET(rtMalloc(&input_output_addr, addrs_size, RT_MEMORY_HBM));
  208. rtError_t rt_ret = rtMemcpy(input_output_addr, addrs_size, io_addrs.data(), addrs_size, RT_MEMCPY_HOST_TO_DEVICE);
  209. if (rt_ret != RT_ERROR_NONE) {
  210. GELOGE(rt_ret, "rtMemcpy error");
  211. GE_CHK_RT(rtFree(input_output_addr));
  212. return FAILED;
  213. }
  214. uint64_t in_out_addr = static_cast<uint64_t>(reinterpret_cast<uintptr_t>(input_output_addr));
  215. task.fwkKernelBase.fwk_kernel.inputOutputAddr = in_out_addr;
  216. return SUCCESS;
  217. }
  218. Status AicpuConstantFoldingPass::UpdateSingleOpAddr(string &task_info, const vector<AddrAndType> &input_addrs,
  219. const vector<uint64_t> &outputs_addr_vec, STR_FWK_OP_KERNEL &task) {
  220. // Build the SingleOpAddr
  221. vector<uint64_t> inputs_addr_vec;
  222. for (const auto &item : input_addrs) {
  223. inputs_addr_vec.push_back(item.input_addr);
  224. }
  225. vector<uint64_t> io_addrs;
  226. io_addrs.insert(io_addrs.end(), inputs_addr_vec.begin(), inputs_addr_vec.end());
  227. io_addrs.insert(io_addrs.end(), outputs_addr_vec.begin(), outputs_addr_vec.end());
  228. Status ret = UpdateInputAndOutputAddr(io_addrs, task);
  229. if (ret != SUCCESS) {
  230. GELOGE(ret, "UpdateInputAndOutputAddr error");
  231. return ret;
  232. }
  233. ret = UpdateWorkSpaceAddr(task_info, task);
  234. if (ret != SUCCESS) {
  235. GELOGE(ret, "UpdateWorkSpaceAddr error");
  236. return ret;
  237. }
  238. return SUCCESS;
  239. }
  240. Status AicpuConstantFoldingPass::UpdateMemCopyAddr(string &task_info, const vector<uint64_t> &data_infos,
  241. vector<uint64_t> &internal_addrs, STR_FWK_OP_KERNEL &task) {
  242. vector<uint64_t> release_flags;
  243. vector<uint64_t> data_sizes;
  244. vector<uint64_t> src_addrs;
  245. vector<uint64_t> dst_addrs;
  246. for (auto item : data_infos) {
  247. auto *data_info_ptr = reinterpret_cast<DataPtrInfo *>(reinterpret_cast<uintptr_t>(item)); // pointer cannot be null
  248. release_flags.push_back(data_info_ptr->release_flag);
  249. data_sizes.push_back(data_info_ptr->data_size);
  250. src_addrs.push_back(data_info_ptr->src_ptr);
  251. dst_addrs.push_back(data_info_ptr->dst_ptr);
  252. }
  253. vector<vector<uint64_t>> inputs = {release_flags, data_sizes, src_addrs, dst_addrs};
  254. auto data_size = sizeof(uint64_t) * (data_infos.size());
  255. vector<uint64_t> io_addrs;
  256. if (data_infos.size() > 0) {
  257. for (const auto &item : inputs) {
  258. void *input_addr_ptr = nullptr;
  259. GE_CHK_RT_RET(rtMalloc(&input_addr_ptr, data_size, RT_MEMORY_HBM));
  260. rtError_t rt_ret = rtMemcpy(input_addr_ptr, data_size, item.data(), data_size, RT_MEMCPY_HOST_TO_DEVICE);
  261. if (rt_ret != RT_ERROR_NONE) {
  262. GELOGE(rt_ret, "rtMemcpy error");
  263. GE_CHK_RT(rtFree(input_addr_ptr));
  264. return FAILED;
  265. }
  266. uint64_t input_addr = static_cast<uint64_t>(reinterpret_cast<uintptr_t>(input_addr_ptr));
  267. io_addrs.push_back(input_addr);
  268. }
  269. }
  270. internal_addrs = io_addrs;
  271. Status ret = UpdateInputAndOutputAddr(io_addrs, task);
  272. if (ret != SUCCESS) {
  273. GELOGE(ret, "UpdateInputAndOutputAddr error");
  274. return ret;
  275. }
  276. ret = UpdateWorkSpaceAddr(task_info, task);
  277. if (ret != SUCCESS) {
  278. GELOGE(ret, "UpdateWorkSpaceAddr error");
  279. return ret;
  280. }
  281. return SUCCESS;
  282. }
  283. Status AicpuConstantFoldingPass::LaunchSingleOpRunTask(const NodePtr &node, const vector<AddrAndType> &input_addrs,
  284. const vector<uint64_t> &output_addrs) {
  285. void *task_buf = nullptr;
  286. auto instance_ptr = ge::GELib::GetInstance();
  287. if (instance_ptr == nullptr || !instance_ptr->InitFlag()) {
  288. GELOGE(GE_CLI_GE_NOT_INITIALIZED, "GE is not initialized");
  289. return GE_CLI_GE_NOT_INITIALIZED;
  290. }
  291. auto kernel_builder = OpsKernelBuilderManager::Instance().GetOpsKernelBuilder(kKernelLibName);
  292. if (kernel_builder == nullptr) {
  293. GELOGE(FAILED, "Get op kernel info store failed");
  294. return FAILED;
  295. }
  296. STR_FWK_OP_KERNEL aicpu_task;
  297. aicpu_task.fwkKernelBase.fwk_kernel.inputOutputAddr = 0;
  298. aicpu_task.fwkKernelBase.fwk_kernel.workspaceBaseAddr = 0;
  299. aicpu_task.fwkKernelBase.fwk_kernel.extInfoAddr = 0;
  300. aicpu_task.fwkKernelBase.fwk_kernel.extInfoLen = 0;
  301. std::string task_info;
  302. Status ret = kernel_builder->GenSingleOpRunTask(node, aicpu_task, task_info);
  303. if (ret != SUCCESS) {
  304. return ret;
  305. }
  306. std::function<void()> callback = [&]() {
  307. void *input_output_ptr =
  308. reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(aicpu_task.fwkKernelBase.fwk_kernel.inputOutputAddr));
  309. if (input_output_ptr != nullptr) {
  310. GE_CHK_RT(rtFree(input_output_ptr));
  311. }
  312. void *workspace_addr_ptr =
  313. reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(aicpu_task.fwkKernelBase.fwk_kernel.workspaceBaseAddr));
  314. if (workspace_addr_ptr != nullptr) {
  315. GE_CHK_RT(rtFree(workspace_addr_ptr));
  316. }
  317. };
  318. GE_MAKE_GUARD(release, callback);
  319. ret = UpdateSingleOpAddr(task_info, input_addrs, output_addrs, aicpu_task);
  320. if (ret != SUCCESS) {
  321. GELOGE(ret, "UpdateSingleOpAddr error");
  322. return ret;
  323. }
  324. ret = GenerateTaskForLaunch(aicpu_task, task_buf);
  325. if (ret != SUCCESS) {
  326. GELOGE(ret, "GenerateTaskForLaunch error");
  327. return ret;
  328. }
  329. ret = KernelLaunch(task_buf);
  330. if (ret != SUCCESS) {
  331. GELOGE(ret, "KernelLaunch error");
  332. return ret;
  333. }
  334. return SUCCESS;
  335. }
  336. Status AicpuConstantFoldingPass::LaunchMemCopyTask(const vector<uint64_t> &data_infos) {
  337. void *task_buf = nullptr;
  338. auto instance_ptr = ge::GELib::GetInstance();
  339. if (instance_ptr == nullptr || !instance_ptr->InitFlag()) {
  340. GELOGE(GE_CLI_GE_NOT_INITIALIZED, "GE is not initialized");
  341. return GE_CLI_GE_NOT_INITIALIZED;
  342. }
  343. auto kernel_builder = OpsKernelBuilderManager::Instance().GetOpsKernelBuilder(kKernelLibName);
  344. if (kernel_builder == nullptr) {
  345. GELOGE(FAILED, "Get op kernel info store failed");
  346. return FAILED;
  347. }
  348. STR_FWK_OP_KERNEL aicpu_task;
  349. aicpu_task.fwkKernelBase.fwk_kernel.inputOutputAddr = 0;
  350. aicpu_task.fwkKernelBase.fwk_kernel.workspaceBaseAddr = 0;
  351. aicpu_task.fwkKernelBase.fwk_kernel.extInfoAddr = 0;
  352. aicpu_task.fwkKernelBase.fwk_kernel.extInfoLen = 0;
  353. std::string task_info;
  354. Status ret = kernel_builder->GenMemCopyTask(data_infos.size(), aicpu_task, task_info);
  355. if (ret != SUCCESS) {
  356. return ret;
  357. }
  358. vector<uint64_t> internal_addrs;
  359. std::function<void()> callback = [&]() {
  360. for (auto item : internal_addrs) {
  361. GE_CHK_RT(rtFree(reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(item)))); // pointer cannot be null
  362. }
  363. void *input_output_ptr =
  364. reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(aicpu_task.fwkKernelBase.fwk_kernel.inputOutputAddr));
  365. if (input_output_ptr != nullptr) {
  366. GE_CHK_RT(rtFree(input_output_ptr));
  367. }
  368. void *workspace_addr_ptr =
  369. reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(aicpu_task.fwkKernelBase.fwk_kernel.workspaceBaseAddr));
  370. if (workspace_addr_ptr != nullptr) {
  371. GE_CHK_RT(rtFree(workspace_addr_ptr));
  372. }
  373. };
  374. GE_MAKE_GUARD(release, callback);
  375. ret = UpdateMemCopyAddr(task_info, data_infos, internal_addrs, aicpu_task);
  376. if (ret != SUCCESS) {
  377. GELOGE(ret, "UpdateMemCopyAddr error");
  378. return ret;
  379. }
  380. ret = GenerateTaskForLaunch(aicpu_task, task_buf);
  381. if (ret != SUCCESS) {
  382. GELOGE(ret, "GenerateTaskForLaunch error");
  383. return ret;
  384. }
  385. ret = KernelLaunch(task_buf);
  386. if (ret != SUCCESS) {
  387. GELOGE(ret, "KernelLaunch error");
  388. return ret;
  389. }
  390. return SUCCESS;
  391. }
  392. Status AicpuConstantFoldingPass::GenerateTaskForLaunch(STR_FWK_OP_KERNEL &aicpu_task, void *&task_buf) {
  393. GE_CHK_RT_RET(rtMalloc(&task_buf, sizeof(STR_FWK_OP_KERNEL), RT_MEMORY_HBM));
  394. rtError_t rt_ret = rtMemcpy(task_buf, sizeof(STR_FWK_OP_KERNEL), reinterpret_cast<void *>(&aicpu_task),
  395. sizeof(STR_FWK_OP_KERNEL), RT_MEMCPY_HOST_TO_DEVICE);
  396. if (rt_ret != RT_ERROR_NONE) {
  397. GELOGE(rt_ret, "rtMemcpy error");
  398. GE_CHK_RT(rtFree(task_buf));
  399. return FAILED;
  400. }
  401. return SUCCESS;
  402. }
  403. Status AicpuConstantFoldingPass::KernelLaunch(void *task_buf) {
  404. rtModel_t model = nullptr;
  405. rtStream_t stream = nullptr;
  406. rtStream_t stream_run = nullptr;
  407. std::function<void()> callback = [&]() {
  408. if (task_buf != nullptr) {
  409. GE_CHK_RT(rtFree(task_buf));
  410. }
  411. if (model != nullptr) {
  412. GE_CHK_RT(rtModelDestroy(model));
  413. }
  414. if (stream != nullptr) {
  415. GE_CHK_RT(rtStreamDestroy(stream));
  416. }
  417. if (stream_run != nullptr) {
  418. GE_CHK_RT(rtStreamDestroy(stream_run));
  419. }
  420. };
  421. GE_MAKE_GUARD(release, callback);
  422. rtError_t rt_ret = rtModelCreate(&model, 0);
  423. if (rt_ret != RT_ERROR_NONE) {
  424. GELOGE(rt_ret, "create model failed.");
  425. return FAILED;
  426. }
  427. rt_ret = rtStreamCreate(&stream, 0);
  428. if (rt_ret != RT_ERROR_NONE) {
  429. GELOGE(rt_ret, "create stream failed.");
  430. return FAILED;
  431. }
  432. rt_ret = rtModelBindStream(model, stream, 0);
  433. if (rt_ret != RT_ERROR_NONE) {
  434. GELOGE(rt_ret, "rtModelBindStream failed.");
  435. return FAILED;
  436. }
  437. rt_ret = rtKernelLaunchEx(task_buf, sizeof(STR_FWK_OP_KERNEL), 0, stream);
  438. if (rt_ret != RT_ERROR_NONE) {
  439. GELOGE(rt_ret, "rtKernelLaunchEx failed.");
  440. return FAILED;
  441. }
  442. rt_ret = rtModelLoadComplete(model);
  443. if (rt_ret != RT_ERROR_NONE) {
  444. GELOGE(rt_ret, "rtModelLoadComplete failed.");
  445. return FAILED;
  446. }
  447. rt_ret = rtStreamCreate(&stream_run, 0);
  448. if (rt_ret != RT_ERROR_NONE) {
  449. GELOGE(rt_ret, "create run stream failed.");
  450. return FAILED;
  451. }
  452. rt_ret = rtModelExecute(model, stream_run, 0);
  453. if (rt_ret != RT_ERROR_NONE) {
  454. GELOGE(rt_ret, "rtModelExecute failed.");
  455. return FAILED;
  456. }
  457. rt_ret = rtStreamSynchronize(stream_run);
  458. if (rt_ret != RT_ERROR_NONE) {
  459. GELOGE(rt_ret, "rtStreamSynchronize failed.");
  460. return FAILED;
  461. }
  462. return SUCCESS;
  463. }
  464. Status AicpuConstantFoldingPass::GenerateGeTensor(const OpDescPtr &node_desc, const vector<DataPtrInfo> &data_vec,
  465. vector<GeTensorPtr> &outputs) {
  466. if ((node_desc->GetOutputsSize() * kDouble) != data_vec.size()) {
  467. GELOGE(FAILED, "node[%s] something wrong with output size", node_desc->GetName().c_str());
  468. return FAILED;
  469. }
  470. for (size_t i = 0; i < node_desc->GetOutputsSize(); i++) {
  471. auto output_tensor_desc = node_desc->GetOutputDesc(static_cast<uint32_t>(i));
  472. GeTensorPtr output_ptr = MakeShared<GeTensor>(output_tensor_desc);
  473. if (output_ptr == nullptr) {
  474. GELOGE(FAILED, "node[%s] something wrong with construct GeTensor", node_desc->GetName().c_str());
  475. return FAILED;
  476. }
  477. const DataPtrInfo &raw_data_info = data_vec.at(i * kDouble);
  478. uint64_t raw_data_size = raw_data_info.data_size;
  479. std::unique_ptr<uint8_t[]> data_addr(new (std::nothrow) uint8_t[raw_data_size]());
  480. if (data_addr == nullptr) {
  481. GELOGE(MEMALLOC_FAILED, "new data_addr failed");
  482. return INTERNAL_ERROR;
  483. }
  484. GE_CHK_RT_RET(rtMemcpy(data_addr.get(), raw_data_size,
  485. reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(raw_data_info.dst_ptr)), raw_data_size,
  486. RT_MEMCPY_DEVICE_TO_HOST));
  487. GE_IF_BOOL_EXEC(output_ptr->SetData(data_addr.get(), raw_data_size) != GRAPH_SUCCESS,
  488. GELOGE(FAILED, "set data failed");
  489. return FAILED);
  490. GELOGD("GenerateGeTensor: raw_data_size %lu", raw_data_size);
  491. const DataPtrInfo &shape_data_info = data_vec.at(i * kDouble + 1);
  492. uint64_t shape_data_size = shape_data_info.data_size;
  493. GELOGD("GenerateGeTensor: shape_data_size %lu", shape_data_size);
  494. if (shape_data_size == 0) {
  495. GELOGW("node[%s] outshape is scalar, skip copy shape", node_desc->GetName().c_str());
  496. output_ptr->MutableTensorDesc().SetShape(GeShape());
  497. outputs.emplace_back(output_ptr);
  498. continue;
  499. }
  500. uint64_t dim_num = shape_data_size / sizeof(uint64_t);
  501. std::unique_ptr<int64_t[]> shape_addr(new (std::nothrow) int64_t[dim_num]());
  502. if (shape_addr == nullptr) {
  503. GELOGE(MEMALLOC_FAILED, "new shape_addr failed");
  504. return INTERNAL_ERROR;
  505. }
  506. GE_CHK_RT_RET(rtMemcpy(shape_addr.get(), shape_data_size,
  507. reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(shape_data_info.dst_ptr)),
  508. shape_data_size, RT_MEMCPY_DEVICE_TO_HOST));
  509. std::vector<int64_t> shape_dims;
  510. for (size_t j = 0; j < dim_num; j++) {
  511. shape_dims.push_back(shape_addr[j]);
  512. GELOGD("GenerateGeTensor: dim %ld", shape_addr[j]);
  513. }
  514. output_ptr->MutableTensorDesc().SetShape(GeShape(shape_dims));
  515. outputs.emplace_back(output_ptr);
  516. }
  517. return SUCCESS;
  518. }
  519. void AicpuConstantFoldingPass::ReleaseMemory(const vector<AddrAndType> &input_addrs,
  520. const vector<uint64_t> &output_addrs,
  521. const vector<DataPtrInfo> &data_vec) {
  522. for (const auto &item : input_addrs) {
  523. GE_CHK_RT(rtFree(reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(item.input_addr))));
  524. }
  525. for (auto item : output_addrs) {
  526. GE_CHK_RT(rtFree(reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(item))));
  527. }
  528. for (const auto &item : data_vec) {
  529. auto dst_ptr = reinterpret_cast<void *>(reinterpret_cast<uintptr_t>(item.dst_ptr));
  530. if (dst_ptr != nullptr) {
  531. GE_CHK_RT(rtFree(dst_ptr));
  532. }
  533. }
  534. }
  535. bool AicpuConstantFoldingPass::IsSkipFold(const ge::NodePtr &node) {
  536. GE_CHECK_NOTNULL(node);
  537. string type = node->GetType();
  538. if (type == ge::FRAMEWORKOP) {
  539. if (!ge::AttrUtils::GetStr(node->GetOpDesc(), ge::ATTR_NAME_FRAMEWORK_ORIGINAL_TYPE, type)) {
  540. GELOGW("Skip aicpu constant folding on frameworkop node [%s]", node->GetName().c_str());
  541. return true;
  542. }
  543. }
  544. auto instance_ptr = ge::GELib::GetInstance();
  545. if (instance_ptr == nullptr || !instance_ptr->InitFlag()) {
  546. GELOGE(GE_CLI_GE_NOT_INITIALIZED, "GE is not initialized");
  547. return true;
  548. }
  549. OpsKernelInfoStorePtr kernel_info = instance_ptr->OpsKernelManagerObj().GetOpsKernelInfoStore(kKernelLibName);
  550. if (kernel_info == nullptr) {
  551. GELOGE(FAILED, "Get op kernel info store failed");
  552. return true;
  553. }
  554. std::string check_result;
  555. kernel_info->opsFlagCheck(*node, check_result);
  556. if (check_result.empty()) {
  557. GELOGE(FAILED, "Get op check_result failed");
  558. return true;
  559. }
  560. return check_result.substr(0, kOpsFlag) == kNotSupported;
  561. }
  562. } // 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