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kernel_runtime.cc 29 kB

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  1. /**
  2. * Copyright 2019 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 "device/kernel_runtime.h"
  17. #include <vector>
  18. #include <utility>
  19. #include <numeric>
  20. #include <functional>
  21. #include "common/utils.h"
  22. #include "common/trans.h"
  23. #include "utils/utils.h"
  24. #include "utils/context/ms_context.h"
  25. #include "operator/ops.h"
  26. #include "pipeline/parse/python_adapter.h"
  27. #include "session/kernel_graph.h"
  28. #include "session/anf_runtime_algorithm.h"
  29. #include "kernel/common_utils.h"
  30. #include "kernel/oplib/oplib.h"
  31. #include "ir/value.h"
  32. using mindspore::kernel::Address;
  33. using mindspore::kernel::AddressPtr;
  34. namespace mindspore {
  35. namespace device {
  36. KernelRuntime::~KernelRuntime() {
  37. #ifdef ENABLE_DUMP_E2E
  38. dump_conf_ptr_ = nullptr;
  39. #endif
  40. }
  41. bool KernelRuntime::Run(session::KernelGraph *graph) {
  42. bool ret = false;
  43. auto context_ptr = MsContext::GetInstance();
  44. MS_EXCEPTION_IF_NULL(context_ptr);
  45. #if defined(_WIN32) || defined(_WIN64)
  46. auto start_time = std::chrono::steady_clock::now();
  47. #else
  48. struct timeval start_time, end_time;
  49. (void)gettimeofday(&start_time, nullptr);
  50. #endif
  51. bool is_task_sink = context_ptr->enable_task_sink();
  52. if (is_task_sink) {
  53. ret = RunTask(graph);
  54. } else {
  55. ret = LaunchKernel(graph);
  56. }
  57. #if defined(_WIN32) || defined(_WIN64)
  58. auto end_time = std::chrono::steady_clock::now();
  59. std::chrono::duration<double, std::ratio<1, 1000000>> cost = end_time - start_time;
  60. MS_LOG(INFO) << "Call MS Run Success in " << cost.count() << " us";
  61. #else
  62. (void)gettimeofday(&end_time, nullptr);
  63. const uint64_t kUSecondInSecond = 1000000;
  64. uint64_t cost = kUSecondInSecond * static_cast<uint64_t>(end_time.tv_sec - start_time.tv_sec);
  65. cost += static_cast<uint64_t>(end_time.tv_usec - start_time.tv_usec);
  66. MS_LOG(INFO) << "Call MS Run Success in " << cost << " us";
  67. #endif
  68. return ret;
  69. }
  70. // for D to impl
  71. bool KernelRuntime::DumpData(mindspore::session::KernelGraph *graph) {
  72. if (graph != nullptr) {
  73. return true;
  74. }
  75. return false;
  76. }
  77. // for D to impl
  78. bool KernelRuntime::GenTask(const session::KernelGraph *graph) {
  79. if (graph != nullptr) {
  80. return true;
  81. }
  82. return false;
  83. }
  84. bool KernelRuntime::LoadTask(const session::KernelGraph *graph) {
  85. if (graph != nullptr) {
  86. return true;
  87. }
  88. return false;
  89. }
  90. // for D to impl
  91. bool KernelRuntime::RunTask(const session::KernelGraph *graph) {
  92. if (graph != nullptr) {
  93. return true;
  94. }
  95. return false;
  96. }
  97. bool KernelRuntime::NodeOutputDeviceAddressExist(const AnfNodePtr &kernel, size_t index) {
  98. MS_EXCEPTION_IF_NULL(kernel);
  99. if (AnfAlgo::OutputAddrExist(kernel, index)) {
  100. return true;
  101. }
  102. return false;
  103. }
  104. size_t KernelRuntime::CountNodeDeviceMemorySize(const mindspore::AnfNodePtr &node, size_t output_index) {
  105. MS_EXCEPTION_IF_NULL(node);
  106. if (output_index >= AnfAlgo::GetOutputTensorNum(node)) {
  107. MS_EXCEPTION(ArgumentError) << "output index [" << output_index << "] large than the output size ["
  108. << AnfAlgo::GetOutputTensorNum(node) << "] of node!";
  109. }
  110. TypeId output_type_id = AnfAlgo::GetOutputDeviceDataType(node, output_index);
  111. if (output_type_id == kTypeUnknown) {
  112. output_type_id = AnfAlgo::GetOutputInferDataType(node, output_index);
  113. }
  114. size_t type_size = GetTypeByte(TypeIdToType(output_type_id));
  115. std::vector<size_t> shape = AnfAlgo::GetOutputDeviceShape(node, output_index);
  116. auto format = AnfAlgo::GetOutputFormat(node, output_index);
  117. if (shape.empty() && format != kOpFormat_DEFAULT) {
  118. shape = trans::PaddingShapeTo4d(shape, AnfAlgo::GetOutputReshapeType(node, output_index));
  119. shape = trans::TransShapeToDevice(shape, format);
  120. }
  121. // scalar's output shape is a empty vector
  122. size_t tensor_size = std::accumulate(shape.begin(), shape.end(), type_size, std::multiplies<size_t>());
  123. return tensor_size;
  124. }
  125. void KernelRuntime::AssignMemory(session::KernelGraph *graph) {
  126. auto context_ptr = MsContext::GetInstance();
  127. MS_EXCEPTION_IF_NULL(context_ptr);
  128. MS_EXCEPTION_IF_NULL(mem_manager_);
  129. mem_manager_->ResetDynamicMemory();
  130. AssignStaticMemory(graph);
  131. AssignDynamicMemory(graph);
  132. UpdateRefNodeOutputMem(graph);
  133. }
  134. void KernelRuntime::RunOpAssignMemory(const std::vector<tensor::TensorPtr> &input_tensors,
  135. session::KernelGraph *graph) {
  136. MS_EXCEPTION_IF_NULL(graph);
  137. RunOpAssignInputMemory(input_tensors, graph);
  138. AssignStaticMemoryValueNode(graph);
  139. for (const auto &cnode : graph->execution_order()) {
  140. RunOpAssignOutputMemory(cnode);
  141. RunOpAssignWorkSpaceMemory(cnode);
  142. }
  143. UpdateRefNodeOutputMem(graph);
  144. }
  145. void KernelRuntime::RunOpClearMemory(session::KernelGraph *graph) {
  146. MS_EXCEPTION_IF_NULL(graph);
  147. // clear input parameter memory resource
  148. for (const auto &input_node : graph->inputs()) {
  149. MS_EXCEPTION_IF_NULL(input_node);
  150. AnfAlgo::SetOutputAddr(nullptr, 0, input_node.get());
  151. }
  152. // clear input value node memory resource
  153. for (const auto &value_node : graph->graph_value_nodes()) {
  154. MS_EXCEPTION_IF_NULL(value_node);
  155. AnfAlgo::SetOutputAddr(nullptr, 0, value_node.get());
  156. }
  157. for (const auto &cnode : graph->execution_order()) {
  158. MS_EXCEPTION_IF_NULL(cnode);
  159. // clear output memory resource
  160. for (size_t index = 0; index < AnfAlgo::GetOutputTensorNum(cnode); ++index) {
  161. AnfAlgo::SetOutputAddr(nullptr, index, cnode.get());
  162. }
  163. // clear workspace memory resource
  164. auto kernel_mod = AnfAlgo::GetKernelMod(cnode);
  165. MS_EXCEPTION_IF_NULL(kernel_mod);
  166. auto workspace_lists = kernel_mod->GetWorkspaceSizeList();
  167. for (size_t index = 0; index < workspace_lists.size(); ++index) {
  168. AnfAlgo::SetWorkspaceAddr(nullptr, index, cnode.get());
  169. }
  170. }
  171. }
  172. void KernelRuntime::AssignStaticMemory(session::KernelGraph *graph) {
  173. AssignStaticMemoryInput(graph);
  174. AssignStaticMemoryValueNode(graph);
  175. AssignStaticMemoryOutput(graph);
  176. }
  177. void KernelRuntime::RunOpAssignInputMemory(const std::vector<tensor::TensorPtr> &input_tensors,
  178. const session::KernelGraph *graph) {
  179. MS_EXCEPTION_IF_NULL(graph);
  180. MS_EXCEPTION_IF_NULL(mem_manager_);
  181. if (input_tensors.size() != graph->inputs().size()) {
  182. MS_LOG(EXCEPTION) << "Input tensors size " << input_tensors.size()
  183. << " should be equal to graph input parameter size " << graph->inputs().size();
  184. }
  185. for (size_t input_index = 0; input_index < graph->inputs().size(); ++input_index) {
  186. auto item = graph->inputs()[input_index];
  187. MS_EXCEPTION_IF_NULL(item);
  188. if (!item->isa<Parameter>()) {
  189. continue;
  190. }
  191. auto output_size = AnfAlgo::GetOutputTensorNum(item);
  192. for (size_t index = 0; index < output_size; index++) {
  193. MS_EXCEPTION_IF_NULL(input_tensors[input_index]);
  194. if (input_tensors[input_index]->device_address().get() != nullptr) {
  195. AnfAlgo::SetOutputAddr(input_tensors[input_index]->device_address(), index, item.get());
  196. continue;
  197. }
  198. TypeId output_type_id = AnfAlgo::GetOutputDeviceDataType(item, index);
  199. if (output_type_id == kTypeUnknown) {
  200. output_type_id = AnfAlgo::GetOutputInferDataType(item, index);
  201. }
  202. auto tensor_size = CountNodeDeviceMemorySize(item, index);
  203. auto device_address =
  204. CreateDeviceAddress(nullptr, tensor_size, AnfAlgo::GetOutputFormat(item, index), output_type_id);
  205. MS_EXCEPTION_IF_NULL(device_address);
  206. MS_EXCEPTION_IF_NULL(mem_manager_);
  207. auto ret = mem_manager_->MallocMemFromMemPool(device_address, tensor_size);
  208. if (!ret) {
  209. MS_LOG(EXCEPTION) << "Malloc device memory failed.";
  210. }
  211. AnfAlgo::SetOutputAddr(device_address, index, item.get());
  212. }
  213. }
  214. }
  215. void KernelRuntime::RunOpAssignOutputMemory(const AnfNodePtr &kernel) {
  216. MS_EXCEPTION_IF_NULL(kernel);
  217. MS_EXCEPTION_IF_NULL(mem_manager_);
  218. auto kernel_mod = AnfAlgo::GetKernelMod(kernel);
  219. MS_EXCEPTION_IF_NULL(kernel_mod);
  220. auto output_sizes = kernel_mod->GetOutputSizeList();
  221. if (output_sizes.empty()) {
  222. return;
  223. }
  224. for (size_t i = 0; i < output_sizes.size(); ++i) {
  225. if (AnfAlgo::OutputAddrExist(kernel, i)) {
  226. continue;
  227. }
  228. if (AnfAlgo::GetCNodeName(kernel) == kApplyMomentumOpName) {
  229. auto device_address = AnfAlgo::GetPrevNodeMutableOutputAddr(kernel, i);
  230. AnfAlgo::SetOutputAddr(device_address, i, kernel.get());
  231. continue;
  232. }
  233. std::string output_format = AnfAlgo::GetOutputFormat(kernel, i);
  234. auto output_type = AnfAlgo::GetOutputDeviceDataType(kernel, i);
  235. auto device_address = CreateDeviceAddress(nullptr, output_sizes[i], output_format, output_type);
  236. MS_EXCEPTION_IF_NULL(device_address);
  237. auto ret = mem_manager_->MallocMemFromMemPool(device_address, output_sizes[i]);
  238. if (!ret) {
  239. MS_LOG(EXCEPTION) << "Malloc device memory failed.";
  240. }
  241. AnfAlgo::SetOutputAddr(device_address, i, kernel.get());
  242. }
  243. }
  244. void KernelRuntime::RunOpAssignWorkSpaceMemory(const AnfNodePtr &kernel) {
  245. MS_EXCEPTION_IF_NULL(kernel);
  246. MS_EXCEPTION_IF_NULL(mem_manager_);
  247. if (kernel->isa<CNode>()) {
  248. auto kernel_mod = AnfAlgo::GetKernelMod(kernel);
  249. MS_EXCEPTION_IF_NULL(kernel_mod);
  250. auto workspace_lists = kernel_mod->GetWorkspaceSizeList();
  251. for (size_t i = 0; i < workspace_lists.size(); ++i) {
  252. auto device_address = CreateDeviceAddress(nullptr, workspace_lists[i], "", kTypeUnknown);
  253. MS_EXCEPTION_IF_NULL(device_address);
  254. auto ret = mem_manager_->MallocMemFromMemPool(device_address, workspace_lists[i]);
  255. if (!ret) {
  256. MS_LOG(EXCEPTION) << "Malloc device memory failed.";
  257. }
  258. AnfAlgo::SetWorkspaceAddr(device_address, i, kernel.get());
  259. }
  260. }
  261. }
  262. void KernelRuntime::AssignStaticMemoryInput(const session::KernelGraph *graph) {
  263. MS_EXCEPTION_IF_NULL(graph);
  264. MS_EXCEPTION_IF_NULL(mem_manager_);
  265. auto graph_inputs = graph->inputs();
  266. auto graph_valid_input = graph->valid_inputs();
  267. for (size_t i = 0; i < graph_inputs.size(); i++) {
  268. auto item = graph_inputs[i];
  269. MS_EXCEPTION_IF_NULL(item);
  270. if (!item->isa<Parameter>()) {
  271. continue;
  272. }
  273. if (i < graph_valid_input.size() && !graph_valid_input[i]) {
  274. continue;
  275. }
  276. if (NodeOutputDeviceAddressExist(item, 0)) {
  277. continue;
  278. }
  279. auto output_size = AnfAlgo::GetOutputTensorNum(item);
  280. for (size_t index = 0; index < output_size; index++) {
  281. TypeId output_type_id = AnfAlgo::GetOutputDeviceDataType(item, index);
  282. // if graph output is a weight and doesn't link to any cnode, it's data type will be unknown
  283. if (output_type_id == kTypeUnknown) {
  284. MS_LOG(WARNING) << "It is not suggested to use a lonely weight parameter as the output of graph";
  285. output_type_id = AnfAlgo::GetOutputInferDataType(item, index);
  286. }
  287. auto tensor_size = CountNodeDeviceMemorySize(item, index);
  288. auto ptr = mem_manager_->MallocMem(kStaticMem, tensor_size);
  289. auto address = CreateDeviceAddress(ptr, tensor_size, AnfAlgo::GetOutputFormat(item, index), output_type_id);
  290. AnfAlgo::SetOutputAddr(address, index, item.get());
  291. }
  292. }
  293. }
  294. void KernelRuntime::AssignStaticMemoryOutput(const session::KernelGraph *graph) {
  295. MS_EXCEPTION_IF_NULL(graph);
  296. auto nodes = AnfAlgo::GetAllOutput(graph->output(), {prim::kPrimTupleGetItem});
  297. std::vector<session::KernelWithIndex> non_communication_op;
  298. // Assign Communicate Op Memory firstly.
  299. for (const auto &node : nodes) {
  300. auto item_with_index = AnfAlgo::VisitKernelWithReturnType(node, 0, true);
  301. MS_EXCEPTION_IF_NULL(item_with_index.first);
  302. if (!item_with_index.first->isa<CNode>() || !AnfAlgo::IsRealKernel(item_with_index.first)) {
  303. continue;
  304. }
  305. if (AnfAlgo::IsCommunicationOp(item_with_index.first)) {
  306. AssignCommunicationNodeMem(kStaticMem, item_with_index.first);
  307. } else {
  308. non_communication_op.emplace_back(item_with_index);
  309. }
  310. }
  311. for (const auto &item_with_index : non_communication_op) {
  312. AssignNodeOutputMem(kStaticMem, item_with_index.first, SizeToInt(item_with_index.second));
  313. }
  314. }
  315. void KernelRuntime::UpdateRefNodeOutputMem(const session::KernelGraph *graph) {
  316. MS_EXCEPTION_IF_NULL(graph);
  317. auto &kernels = graph->execution_order();
  318. for (auto &kernel : kernels) {
  319. MS_EXCEPTION_IF_NULL(kernel);
  320. auto kernel_mod = AnfAlgo::GetKernelMod(kernel);
  321. MS_EXCEPTION_IF_NULL(kernel_mod);
  322. auto output_sizes = kernel_mod->GetOutputSizeList();
  323. if (output_sizes.empty()) {
  324. MS_LOG(INFO) << "This kernel has no output size.";
  325. continue;
  326. }
  327. for (size_t i = 0; i < output_sizes.size(); ++i) {
  328. session::AnfWithOutIndex out_pair(kernel, i);
  329. if (graph->IsInRefOutputMap(out_pair)) {
  330. auto origin_pair = graph->GetRefCorrespondOutput(out_pair);
  331. MS_EXCEPTION_IF_NULL(origin_pair.first);
  332. auto origin_node_output_addr = AnfAlgo::GetMutableOutputAddr(origin_pair.first, origin_pair.second);
  333. MS_EXCEPTION_IF_NULL(origin_node_output_addr);
  334. auto cur_node_output_addr = AnfAlgo::GetMutableOutputAddr(kernel, i);
  335. if (origin_node_output_addr.get() != cur_node_output_addr.get()) {
  336. MS_LOG(INFO) << "REF address is not same, ref node output need address update";
  337. MS_LOG(INFO) << "REF origin op is " << origin_pair.first->DebugString() << ", output index is "
  338. << origin_pair.second << ", cur op is " << kernel->DebugString() << ", out index is " << i;
  339. AnfAlgo::SetOutputAddr(origin_node_output_addr, i, kernel.get());
  340. }
  341. }
  342. }
  343. }
  344. }
  345. void KernelRuntime::AssignCommunicationNodeMem(int flag, const AnfNodePtr &node) {
  346. AssignCommunicationNodeInputMem(node);
  347. AssignCommunicationNodeOutputMem(flag, node);
  348. }
  349. void KernelRuntime::AssignCommunicationNodeOutputMem(int flag, const AnfNodePtr &node) {
  350. MS_EXCEPTION_IF_NULL(node);
  351. MS_EXCEPTION_IF_NULL(mem_manager_);
  352. auto kernel_mod = AnfAlgo::GetKernelMod(node);
  353. MS_EXCEPTION_IF_NULL(kernel_mod);
  354. auto output_sizes = kernel_mod->GetOutputSizeList();
  355. if (output_sizes.empty()) {
  356. MS_LOG(INFO) << "This kernel[" << node->DebugString() << "] has no output size.";
  357. return;
  358. }
  359. auto context_ptr = MsContext::GetInstance();
  360. MS_EXCEPTION_IF_NULL(context_ptr);
  361. size_t total_size = 0;
  362. size_t output_index = 0;
  363. std::vector<size_t> align_size_list;
  364. for (uint64_t mem_size : output_sizes) {
  365. if (AnfAlgo::OutputAddrExist(node, output_index++)) {
  366. MS_LOG(INFO) << "communication op addr exist";
  367. continue;
  368. }
  369. if (context_ptr->enable_hccl()) {
  370. mem_size = mem_manager_->GetCommonAlignSize(mem_size);
  371. }
  372. total_size += mem_size;
  373. align_size_list.emplace_back(mem_size);
  374. }
  375. uint8_t *output_ptr = mem_manager_->MallocOutputMem(node, 0, flag, total_size);
  376. for (size_t j = 0; j < align_size_list.size(); ++j) {
  377. std::string output_format = AnfAlgo::GetOutputFormat(node, j);
  378. auto output_type = AnfAlgo::GetOutputDeviceDataType(node, j);
  379. auto address = CreateDeviceAddress(output_ptr, output_sizes[j], output_format, output_type);
  380. AnfAlgo::SetOutputAddr(address, j, node.get());
  381. output_ptr += align_size_list[j];
  382. }
  383. }
  384. DeviceAddressPtr KernelRuntime::PreAssignCNodeMemory(const AnfNodePtr &anf_node, size_t index) {
  385. MS_EXCEPTION_IF_NULL(anf_node);
  386. auto kernel_mod = AnfAlgo::GetKernelMod(anf_node);
  387. auto output_sizes = kernel_mod->GetOutputSizeList();
  388. if (output_sizes.size() <= index) {
  389. MS_LOG(EXCEPTION) << "Previous node output size < node index";
  390. }
  391. std::string output_format = AnfAlgo::GetOutputFormat(anf_node, index);
  392. auto output_type = AnfAlgo::GetOutputDeviceDataType(anf_node, index);
  393. auto address = CreateDeviceAddress(nullptr, output_sizes[index], output_format, output_type);
  394. AnfAlgo::SetOutputAddr(address, index, anf_node.get());
  395. return address;
  396. }
  397. void KernelRuntime::AssignCommunicationNodeInputMem(const AnfNodePtr &node) {
  398. auto context_ptr = MsContext::GetInstance();
  399. MS_EXCEPTION_IF_NULL(context_ptr);
  400. MS_EXCEPTION_IF_NULL(node);
  401. MS_EXCEPTION_IF_NULL(mem_manager_);
  402. size_t total_size = 0;
  403. std::vector<std::pair<mindspore::device::DeviceAddress *, size_t>> addr_size;
  404. for (size_t i = 0; i < AnfAlgo::GetInputTensorNum(node); ++i) {
  405. auto input_node_with_index = AnfAlgo::GetPrevNodeOutput(node, i);
  406. auto input_node = input_node_with_index.first;
  407. DeviceAddressPtr address = nullptr;
  408. if (input_node->isa<CNode>()) {
  409. address = PreAssignCNodeMemory(input_node, input_node_with_index.second);
  410. } else {
  411. MS_LOG(EXCEPTION) << "Communication node inputs only support CNode";
  412. }
  413. MS_EXCEPTION_IF_NULL(address);
  414. auto mem_size = mem_manager_->GetCommonAlignSize(address->size());
  415. total_size += mem_size;
  416. addr_size.emplace_back(address.get(), mem_size);
  417. }
  418. uint8_t *input_ptr = mem_manager_->MallocOutputMem(node, 0, kDynamicMem, total_size);
  419. for (const auto &iter : addr_size) {
  420. MS_EXCEPTION_IF_NULL(iter.first);
  421. iter.first->set_ptr(input_ptr);
  422. input_ptr += iter.second;
  423. }
  424. }
  425. void KernelRuntime::AssignNodeOutputMem(int flag, const AnfNodePtr &node, int index) {
  426. MS_EXCEPTION_IF_NULL(node);
  427. MS_EXCEPTION_IF_NULL(mem_manager_);
  428. if (AnfAlgo::IsGetNext(NOT_NULL(node)) && flag == kReuseDynamicMem) {
  429. MS_LOG(INFO) << "GetNext disable mem_reuse";
  430. flag = kDynamicMem;
  431. }
  432. auto kernel_mod = AnfAlgo::GetKernelMod(node);
  433. MS_EXCEPTION_IF_NULL(kernel_mod);
  434. auto output_sizes = kernel_mod->GetOutputSizeList();
  435. if (output_sizes.empty()) {
  436. MS_LOG(INFO) << "This kernel[" << node->DebugString() << "] has no output size.";
  437. return;
  438. }
  439. for (size_t i = 0; i < output_sizes.size(); ++i) {
  440. if ((kGetAllOuts != index) && (SizeToInt(i) != index)) {
  441. continue;
  442. }
  443. if (NodeOutputDeviceAddressExist(node, i)) {
  444. MS_LOG(INFO) << "Already malloc index:" << i;
  445. continue;
  446. }
  447. auto ptr = mem_manager_->MallocOutputMem(node, i, flag, output_sizes[i]);
  448. if (ptr == nullptr) {
  449. // reused ptr, no need alloc, continue;
  450. continue;
  451. }
  452. std::string output_format = AnfAlgo::GetOutputFormat(node, i);
  453. auto output_type = AnfAlgo::GetOutputDeviceDataType(node, i);
  454. AnfAlgo::SetOutputAddr(CreateDeviceAddress(ptr, output_sizes[i], output_format, output_type), i, node.get());
  455. }
  456. }
  457. void KernelRuntime::AssignValueNodeTensor(const ValueNodePtr &value_node, const ValuePtr &node_value,
  458. size_t output_idx) {
  459. MS_EXCEPTION_IF_NULL(value_node);
  460. MS_EXCEPTION_IF_NULL(node_value);
  461. MS_EXCEPTION_IF_NULL(mem_manager_);
  462. auto ms_context = MsContext::GetInstance();
  463. MS_EXCEPTION_IF_NULL(ms_context);
  464. auto tensor = node_value->cast<TensorPtr>();
  465. if (tensor == nullptr) {
  466. MS_LOG(WARNING) << "Tensor is null";
  467. return;
  468. }
  469. size_t tensor_size = tensor->data().nbytes();
  470. auto node_size = CountNodeDeviceMemorySize(value_node, output_idx);
  471. TypeId output_type_id = AnfAlgo::GetOutputDeviceDataType(value_node, output_idx);
  472. if (output_type_id == kTypeUnknown) {
  473. output_type_id = AnfAlgo::GetOutputInferDataType(value_node, output_idx);
  474. }
  475. auto output_format = AnfAlgo::GetOutputFormat(value_node, output_idx);
  476. DeviceAddressPtr address = nullptr;
  477. if (ms_context->enable_pynative_infer()) {
  478. address = CreateDeviceAddress(nullptr, node_size, output_format, output_type_id);
  479. MS_EXCEPTION_IF_NULL(address);
  480. if (!mem_manager_->MallocMemFromMemPool(address, node_size)) {
  481. MS_LOG(EXCEPTION) << "Malloc value node device memory failed !";
  482. }
  483. } else {
  484. auto ptr = mem_manager_->MallocMem(kStaticMem, node_size);
  485. address = CreateDeviceAddress(ptr, node_size, output_format, output_type_id);
  486. MS_EXCEPTION_IF_NULL(address);
  487. }
  488. AnfAlgo::SetOutputAddr(address, output_idx, value_node.get());
  489. if (!address->SyncHostToDevice(trans::GetRuntimePaddingShape(value_node, 0), tensor_size, tensor->data_type(),
  490. tensor->data_c(false))) {
  491. MS_EXCEPTION(NotExistsError) << "ValueNode SyncHostToDevice fail!" << value_node->DebugString() << "node format is"
  492. << AnfAlgo::GetOutputFormat(value_node, output_idx) << "node dtype is "
  493. << AnfAlgo::GetOutputInferDataType(value_node, output_idx);
  494. }
  495. }
  496. void KernelRuntime::AssignStaticMemoryValueNode(session::KernelGraph *graph) {
  497. MS_EXCEPTION_IF_NULL(graph);
  498. MS_EXCEPTION_IF_NULL(mem_manager_);
  499. auto ms_context = MsContext::GetInstance();
  500. MS_EXCEPTION_IF_NULL(ms_context);
  501. for (auto &value_node : graph->graph_value_nodes()) {
  502. MS_EXCEPTION_IF_NULL(value_node);
  503. if (NodeOutputDeviceAddressExist(value_node, 0)) {
  504. MS_LOG(INFO) << "value_node[" << value_node->DebugString() << "] address already exist";
  505. continue;
  506. }
  507. auto &node_value = value_node->value();
  508. MS_EXCEPTION_IF_NULL(node_value);
  509. if (node_value->isa<Tensor>()) {
  510. AssignValueNodeTensor(value_node, node_value, 0);
  511. } else if (node_value->isa<StringImm>()) {
  512. auto value = GetValue<std::string>(node_value);
  513. size_t tensor_size = value.size();
  514. DeviceAddressPtr address = nullptr;
  515. if (ms_context->enable_pynative_infer()) {
  516. address = CreateDeviceAddress(nullptr, tensor_size, kOpFormat_DEFAULT, kNumberTypeUInt8);
  517. MS_EXCEPTION_IF_NULL(address);
  518. if (!mem_manager_->MallocMemFromMemPool(address, tensor_size)) {
  519. MS_LOG(EXCEPTION) << "Malloc value node device memory failed !";
  520. }
  521. } else {
  522. auto ptr = mem_manager_->MallocMem(kStaticMem, tensor_size);
  523. address = CreateDeviceAddress(ptr, tensor_size, kOpFormat_DEFAULT, kNumberTypeUInt8);
  524. MS_EXCEPTION_IF_NULL(address);
  525. }
  526. AnfAlgo::SetOutputAddr(address, 0, value_node.get());
  527. std::vector<int> shape = {1, SizeToInt(tensor_size)};
  528. if (!address->SyncHostToDevice(shape, tensor_size, kNumberTypeUInt8, value.data())) {
  529. MS_LOG(EXCEPTION) << "kValueNode SyncHostToDevice fail!";
  530. }
  531. }
  532. }
  533. }
  534. void KernelRuntime::AssignDynamicMemory(session::KernelGraph *graph) {
  535. MS_EXCEPTION_IF_NULL(graph);
  536. MS_EXCEPTION_IF_NULL(mem_manager_);
  537. auto context_ptr = MsContext::GetInstance();
  538. MS_EXCEPTION_IF_NULL(context_ptr);
  539. bool is_enable_mem_reuse = context_ptr->enable_mem_reuse();
  540. auto mem_flag = kDynamicMem;
  541. if (is_enable_mem_reuse) {
  542. mem_manager_->MallocReusedDynamicMem(graph);
  543. mem_flag = kReuseDynamicMem;
  544. }
  545. auto &execution_nodes = graph->execution_order();
  546. std::vector<CNodePtr> compute_nodes;
  547. // communication nodes first
  548. for (auto &node : execution_nodes) {
  549. if (AnfAlgo::IsCommunicationOp(node)) {
  550. // skip if the memory is already alocated
  551. AssignCommunicationNodeMem(mem_flag, node);
  552. } else {
  553. compute_nodes.emplace_back(node);
  554. }
  555. }
  556. // then compute nodes
  557. for (auto &node : compute_nodes) {
  558. AssignNodeOutputMem(mem_flag, node, kGetAllOuts);
  559. AssignWorkSpaceMem(mem_flag, node);
  560. }
  561. }
  562. void KernelRuntime::AssignWorkSpaceMem(int flag, const AnfNodePtr &node) {
  563. MS_EXCEPTION_IF_NULL(node);
  564. MS_EXCEPTION_IF_NULL(mem_manager_);
  565. auto kernel_mod = AnfAlgo::GetKernelMod(node);
  566. MS_EXCEPTION_IF_NULL(kernel_mod);
  567. size_t index = 0;
  568. for (auto &size : kernel_mod->GetWorkspaceSizeList()) {
  569. auto ptr = mem_manager_->MallocWorkSpaceMem(node, index, flag, size);
  570. AnfAlgo::SetWorkspaceAddr(CreateDeviceAddress(ptr, size, "", kTypeUnknown), index, node.get());
  571. index++;
  572. }
  573. }
  574. void KernelRuntime::GenLaunchArgs(const mindspore::kernel::KernelMod &kernel_mod, const mindspore::AnfNodePtr &kernel,
  575. AddressPtrList *kernel_inputs, AddressPtrList *const kernel_workspaces,
  576. AddressPtrList *kernel_outputs) {
  577. MS_EXCEPTION_IF_NULL(kernel);
  578. MS_EXCEPTION_IF_NULL(kernel_inputs);
  579. MS_EXCEPTION_IF_NULL(kernel_workspaces);
  580. MS_EXCEPTION_IF_NULL(kernel_outputs);
  581. auto cnode = kernel->cast<CNodePtr>();
  582. MS_EXCEPTION_IF_NULL(cnode);
  583. if (AnfAlgo::GetCNodeName(cnode) == kAtomicAddrCleanOpName) {
  584. return GenAddrCleanLaunchArgs(cnode, kernel_inputs);
  585. }
  586. for (size_t i = 0; i < AnfAlgo::GetInputTensorNum(kernel); ++i) {
  587. auto real_input = AnfAlgo::GetRealInputIndex(kernel, i);
  588. auto device_address = AnfAlgo::GetPrevNodeOutputAddr(kernel, real_input);
  589. MS_EXCEPTION_IF_NULL(device_address);
  590. kernel::AddressPtr input = std::make_shared<kernel::Address>();
  591. MS_EXCEPTION_IF_NULL(input);
  592. input->addr = device_address->ptr_;
  593. MS_EXCEPTION_IF_NULL(input->addr);
  594. input->size = device_address->size_;
  595. kernel_inputs->emplace_back(input);
  596. }
  597. for (size_t i = 0; i < kernel_mod.GetOutputSizeList().size(); ++i) {
  598. auto device_address = AnfAlgo::GetOutputAddr(kernel, i);
  599. kernel::AddressPtr output = std::make_shared<kernel::Address>();
  600. MS_EXCEPTION_IF_NULL(output);
  601. output->addr = device_address->ptr_;
  602. MS_EXCEPTION_IF_NULL(output->addr);
  603. output->size = device_address->size_;
  604. kernel_outputs->emplace_back(output);
  605. }
  606. for (size_t i = 0; i < kernel_mod.GetWorkspaceSizeList().size(); ++i) {
  607. auto device_address = AnfAlgo::GetWorkspaceAddr(kernel, i);
  608. kernel::AddressPtr workspace = std::make_shared<kernel::Address>();
  609. MS_EXCEPTION_IF_NULL(workspace);
  610. workspace->addr = device_address->ptr_;
  611. MS_EXCEPTION_IF_NULL(workspace->addr);
  612. workspace->size = device_address->size_;
  613. kernel_workspaces->emplace_back(workspace);
  614. }
  615. }
  616. void KernelRuntime::GenAddrCleanLaunchArgs(const CNodePtr &cnode, AddressPtrList *kernel_inputs) {
  617. if (cnode->inputs().size() != 2) {
  618. MS_LOG(EXCEPTION) << "Atomic Addr clean Node Input nodes not equal 2.";
  619. }
  620. MS_EXCEPTION_IF_NULL(cnode->inputs()[1]);
  621. auto pre_node = (cnode->inputs()[1])->cast<CNodePtr>();
  622. // set clean output address
  623. if (AnfAlgo::HasNodeAttr(kAttrAutomicOutputIndexs, pre_node)) {
  624. auto clean_output_indexs = AnfAlgo::GetNodeAttr<std::vector<size_t>>(pre_node, kAttrAutomicOutputIndexs);
  625. for (auto index : clean_output_indexs) {
  626. auto device_address = AnfAlgo::GetOutputAddr(pre_node, index);
  627. kernel::AddressPtr input = std::make_shared<kernel::Address>();
  628. MS_EXCEPTION_IF_NULL(input);
  629. input->addr = device_address->ptr_;
  630. MS_EXCEPTION_IF_NULL(input->addr);
  631. input->size = device_address->size_;
  632. kernel_inputs->emplace_back(input);
  633. }
  634. MS_LOG(INFO) << "AtomicAddClean clean output size:" << clean_output_indexs.size();
  635. }
  636. // set clean workspace address
  637. if (AnfAlgo::HasNodeAttr(kAttrAutomicWorkspaceSize, pre_node)) {
  638. auto clean_workspaces = AnfAlgo::GetNodeAttr<int>(pre_node, kAttrAutomicWorkspaceSize);
  639. if (clean_workspaces != 0) {
  640. auto device_address = AnfAlgo::GetWorkspaceAddr(pre_node, 0);
  641. kernel::AddressPtr workspace = std::make_shared<kernel::Address>();
  642. MS_EXCEPTION_IF_NULL(workspace);
  643. workspace->addr = device_address->ptr_;
  644. MS_EXCEPTION_IF_NULL(workspace->addr);
  645. workspace->size = device_address->size_;
  646. kernel_inputs->emplace_back(workspace);
  647. }
  648. MS_LOG(INFO) << "AtomicAddClean clean workspace size" << clean_workspaces;
  649. }
  650. }
  651. bool KernelRuntime::LaunchKernelMod(const session::KernelGraph &graph) {
  652. auto &kernels = graph.execution_order();
  653. for (const auto &kernel : kernels) {
  654. auto kernel_mod = AnfAlgo::GetKernelMod(kernel);
  655. MS_EXCEPTION_IF_NULL(kernel_mod);
  656. AddressPtrList kernel_inputs;
  657. AddressPtrList kernel_workspaces;
  658. AddressPtrList kernel_outputs;
  659. GenLaunchArgs(*kernel_mod, kernel, &kernel_inputs, &kernel_workspaces, &kernel_outputs);
  660. auto ret = kernel_mod->Launch(kernel_inputs, kernel_workspaces, kernel_outputs, stream_);
  661. if (!ret) {
  662. MS_LOG(ERROR) << "Launch kernel failed.";
  663. return false;
  664. }
  665. }
  666. return true;
  667. }
  668. bool KernelRuntime::LaunchKernel(const session::KernelGraph *graph) {
  669. MS_EXCEPTION_IF_NULL(graph);
  670. if (!LaunchKernelMod(*graph)) {
  671. MS_LOG(ERROR) << "LaunchKernelMod failed!";
  672. return false;
  673. }
  674. return true;
  675. }
  676. void KernelRuntime::ClearGraphRuntimeResource(uint32_t graph_id) {
  677. MS_LOG(INFO) << "Clear graph:" << graph_id << " runtime resource";
  678. }
  679. #ifdef ENABLE_DUMP_E2E
  680. bool KernelRuntime::SetDumpConf() {
  681. dump_conf_ptr_ = std::make_shared<Dump>();
  682. MS_EXCEPTION_IF_NULL(dump_conf_ptr_);
  683. bool ret = dump_conf_ptr_->SetDumpConfFromJsonFile();
  684. return ret;
  685. }
  686. DumpConfPtr KernelRuntime::GetDumpConf() { return dump_conf_ptr_; }
  687. #endif
  688. } // namespace device
  689. } // namespace mindspore