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model_utils.cc 20 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 "graph/load/new_model_manager/model_utils.h"
  17. #include <string>
  18. #include "common/debug/log.h"
  19. #include "common/op/ge_op_utils.h"
  20. #include "graph/debug/ge_attr_define.h"
  21. #include "graph/utils/attr_utils.h"
  22. #include "graph/utils/tensor_utils.h"
  23. #include "runtime/base.h"
  24. #include "runtime/kernel.h"
  25. #include "framework/common/debug/ge_log.h"
  26. #include "graph/manager/graph_var_manager.h"
  27. #define VALIDATE_MEM_RANGE(OP, SIZE, OFFSET) \
  28. do { \
  29. if (SIZE <= static_cast<uint64_t>(OFFSET)) { \
  30. GELOGE(OUT_OF_MEMORY, "Node: %s, memory out of range[%lu: %ld]", OP->GetName().c_str(), SIZE, OFFSET); \
  31. return {}; \
  32. } \
  33. } while (0)
  34. namespace ge {
  35. ///
  36. /// @ingroup ge
  37. /// @brief Get input size.
  38. /// @return vector<int64_t>
  39. ///
  40. vector<int64_t> ModelUtils::GetInputSize(ConstOpDescPtr op_desc) {
  41. vector<int64_t> v_input_size;
  42. GE_CHECK_NOTNULL_EXEC(op_desc, return v_input_size);
  43. const size_t inputs_size = op_desc->GetAllInputsSize();
  44. const string op_type = op_desc->GetType();
  45. const vector<bool> v_is_input_const = op_desc->GetIsInputConst();
  46. for (size_t i = 0; i < inputs_size; ++i) {
  47. const GeTensorDescPtr tensor_desc = op_desc->MutableInputDesc(i);
  48. if (tensor_desc == nullptr) {
  49. GELOGW("Op: %s, Index: %zu, Tensor Desc is null", op_desc->GetName().c_str(), i);
  50. continue;
  51. }
  52. int64_t tensor_size = 0;
  53. if ((i < v_is_input_const.size()) && v_is_input_const[i] && (op_type != NETOUTPUT)) {
  54. // TBE: add weights size to input
  55. GE_CHK_STATUS(TensorUtils::GetSize(*tensor_desc, tensor_size));
  56. if (tensor_size) {
  57. v_input_size.push_back(tensor_size);
  58. }
  59. GELOGI("[IMAS]GetInputSize op: %s, index: %lu, size:%ld", op_desc->GetName().c_str(), i, tensor_size);
  60. continue;
  61. }
  62. GE_IF_BOOL_EXEC(
  63. TensorUtils::GetSize(*tensor_desc, tensor_size) != GRAPH_SUCCESS,
  64. GELOGI("Get size from TensorDesc failed, op : %s, input index : %zu", op_desc->GetName().c_str(), i);
  65. continue);
  66. GELOGI("[IMAS]GetInputSize op: %s, index: %lu, size:%ld", op_desc->GetName().c_str(), i, tensor_size);
  67. v_input_size.push_back(tensor_size);
  68. }
  69. return v_input_size;
  70. }
  71. ///
  72. /// @ingroup ge
  73. /// @brief Get output size.
  74. /// @return vector<int64_t>
  75. ///
  76. vector<int64_t> ModelUtils::GetOutputSize(ConstOpDescPtr op_desc) {
  77. vector<int64_t> v_output_size;
  78. GE_CHECK_NOTNULL_EXEC(op_desc, return v_output_size);
  79. const size_t outputs_size = op_desc->GetOutputsSize();
  80. const vector<int64_t> v_output_offset = op_desc->GetOutputOffset();
  81. GE_IF_BOOL_EXEC(v_output_offset.size() != outputs_size,
  82. GELOGW("Output param invalid: output_offset=%zu, outputs=%zu.", v_output_offset.size(), outputs_size);
  83. return v_output_size;);
  84. for (size_t i = 0; i < outputs_size; ++i) {
  85. const GeTensorDescPtr tensor_desc = op_desc->MutableOutputDesc(i);
  86. if (tensor_desc == nullptr) {
  87. GELOGW("Op: %s, Index: %zu, Tensor Desc is null", op_desc->GetName().c_str(), i);
  88. continue;
  89. }
  90. int64_t tensor_size = 0;
  91. GE_IF_BOOL_EXEC(
  92. TensorUtils::GetSize(*tensor_desc, tensor_size) != GRAPH_SUCCESS,
  93. GELOGI("Get size from TensorDesc failed, op : %s, output index : %zu", op_desc->GetName().c_str(), i);
  94. continue);
  95. v_output_size.push_back(tensor_size);
  96. }
  97. return v_output_size;
  98. }
  99. ///
  100. /// @ingroup ge
  101. /// @brief Get workspace size.
  102. /// @return vector<int64_t>
  103. ///
  104. vector<int64_t> ModelUtils::GetWorkspaceSize(ConstOpDescPtr op_desc) {
  105. vector<int64_t> v_workspace_size;
  106. GE_CHECK_NOTNULL_EXEC(op_desc, return v_workspace_size);
  107. const vector<int64_t> v_workspace_num = op_desc->GetWorkspace();
  108. const vector<int64_t> v_workspace_bytes = op_desc->GetWorkspaceBytes();
  109. if (v_workspace_num.size() != v_workspace_bytes.size()) {
  110. GELOGW("workspace_num[%zu]!= workspace_bytes[%zu]", v_workspace_num.size(), v_workspace_bytes.size());
  111. return v_workspace_size;
  112. }
  113. for (auto workspace_bytes : v_workspace_bytes) {
  114. v_workspace_size.push_back(workspace_bytes);
  115. }
  116. return v_workspace_size;
  117. }
  118. ///
  119. /// @ingroup ge
  120. /// @brief Get weight size.
  121. /// @return vector<int64_t>
  122. ///
  123. vector<int64_t> ModelUtils::GetWeightSize(ConstOpDescPtr op_desc) {
  124. vector<int64_t> v_weight_size;
  125. GE_CHECK_NOTNULL_EXEC(op_desc, return v_weight_size);
  126. // const op, get weight directly
  127. const string type_name = op_desc->GetType();
  128. if ((type_name == "Const") || (type_name == "Constant")) {
  129. ConstGeTensorPtr weight = nullptr;
  130. if (AttrUtils::GetTensor(*op_desc, ATTR_NAME_WEIGHTS, weight)) {
  131. v_weight_size.push_back(TensorUtils::GetWeightSize(weight));
  132. }
  133. return v_weight_size;
  134. }
  135. // other ops get weight from connected constop
  136. const size_t inputs_size = op_desc->GetAllInputsSize();
  137. const vector<bool> v_is_input_const = op_desc->GetIsInputConst();
  138. for (size_t i = 0; i < inputs_size; ++i) {
  139. if ((i < v_is_input_const.size()) && v_is_input_const[i]) {
  140. const GeTensorDescPtr tensor_desc = op_desc->MutableInputDesc(i);
  141. if (tensor_desc == nullptr) {
  142. GELOGW("Op: %s, Index: %zu, Tensor Desc is null", op_desc->GetName().c_str(), i);
  143. continue;
  144. }
  145. int64_t tensor_size = 0;
  146. (void)TensorUtils::GetSize(*tensor_desc, tensor_size);
  147. v_weight_size.push_back(tensor_size);
  148. }
  149. }
  150. return v_weight_size;
  151. }
  152. ///
  153. /// @ingroup ge
  154. /// @brief Get weights.
  155. /// @return vector<ConstGeTensorPtr>
  156. ///
  157. vector<ConstGeTensorPtr> ModelUtils::GetWeights(ConstOpDescPtr op_desc) {
  158. vector<ConstGeTensorPtr> v_weights;
  159. GE_CHECK_NOTNULL_EXEC(op_desc, return v_weights);
  160. // const op, get weight directly
  161. const string op_type = op_desc->GetType();
  162. if ((op_type == "Const") || (op_type == "Constant")) {
  163. ConstGeTensorPtr weight = nullptr;
  164. if (AttrUtils::GetTensor(*op_desc, ATTR_NAME_WEIGHTS, weight)) {
  165. v_weights.push_back(weight);
  166. }
  167. return v_weights;
  168. }
  169. // other ops get weight from connected constop
  170. const size_t inputs_size = op_desc->GetAllInputsSize();
  171. const vector<bool> v_is_input_const = op_desc->GetIsInputConst();
  172. for (size_t i = 0; i < inputs_size; ++i) {
  173. if ((i < v_is_input_const.size()) && v_is_input_const[i]) {
  174. const GeTensorDescPtr tensor_desc = op_desc->MutableInputDesc(i);
  175. if (tensor_desc == nullptr) {
  176. GELOGW("Op: %s, Index: %zu, Tensor Desc is null", op_desc->GetName().c_str(), i);
  177. continue;
  178. }
  179. ConstGeTensorPtr weight = nullptr;
  180. if (AttrUtils::GetTensor(*tensor_desc, ATTR_NAME_WEIGHTS, weight)) {
  181. v_weights.push_back(weight);
  182. }
  183. }
  184. }
  185. return v_weights;
  186. }
  187. ///
  188. /// @ingroup ge
  189. /// @brief Get AiCpuOp Input descriptor.
  190. /// @return vector<::tagCcAICPUTensor>
  191. ///
  192. vector<::tagCcAICPUTensor> ModelUtils::GetInputDescs(ConstOpDescPtr op_desc) {
  193. // AiCpuOp::GetInputDescs
  194. vector<::opTensor_t> v_input_descs;
  195. GE_CHECK_NOTNULL_EXEC(op_desc, return v_input_descs);
  196. const size_t inputs_size = op_desc->GetAllInputsSize();
  197. const vector<bool> v_is_input_const = op_desc->GetIsInputConst();
  198. for (size_t i = 0; i < inputs_size; ++i) {
  199. if ((i < v_is_input_const.size()) && v_is_input_const[i]) { // skip Const input node
  200. continue;
  201. }
  202. const GeTensorDescPtr tensor_desc = op_desc->MutableInputDesc(i);
  203. if (tensor_desc == nullptr) {
  204. GELOGW("Op: %s, Index: %zu, Tensor Desc is null", op_desc->GetName().c_str(), i);
  205. continue;
  206. }
  207. uint32_t dim_cnt = 0;
  208. GE_CHK_BOOL_EXEC_WARN(TensorUtils::GetRealDimCnt(*tensor_desc, dim_cnt) == GRAPH_SUCCESS, continue,
  209. "Get dim_cnt failed");
  210. opTensor_t tmp;
  211. uint32_t tmp_fmt = tensor_desc->GetFormat();
  212. tmp.format = tagOpTensorFormat(tmp_fmt);
  213. tmp.dim_cnt = static_cast<int32_t>(dim_cnt);
  214. uint32_t tmp_type = tensor_desc->GetDataType();
  215. tmp.data_type = tagOpDataType(tmp_type);
  216. for (int32_t j = 0; j < 4; j++) { // 4 dims
  217. tmp.dim[j] = (j < tmp.dim_cnt ? tensor_desc->GetShape().GetDim(j) : 1);
  218. }
  219. v_input_descs.push_back(tmp);
  220. }
  221. return v_input_descs;
  222. }
  223. ///
  224. /// @ingroup ge
  225. /// @brief Get AiCpuOp Output descriptor.
  226. /// @return vector<::tagCcAICPUTensor>
  227. ///
  228. vector<::tagCcAICPUTensor> ModelUtils::GetOutputDescs(ConstOpDescPtr op_desc) {
  229. // AiCpuOp::GetOutputDescs
  230. vector<::opTensor_t> v_output_descs;
  231. GE_CHECK_NOTNULL_EXEC(op_desc, return v_output_descs);
  232. // init op output opTensor_t struct
  233. const size_t output_num = op_desc->GetOutputsSize();
  234. for (size_t i = 0; i < output_num; ++i) {
  235. const GeTensorDescPtr tensor_desc = op_desc->MutableOutputDesc(i);
  236. if (tensor_desc == nullptr) {
  237. GELOGW("Op: %s, Index: %zu, Tensor Desc is null", op_desc->GetName().c_str(), i);
  238. continue;
  239. }
  240. uint32_t dim_cnt = 0;
  241. GE_CHK_BOOL_EXEC_WARN(TensorUtils::GetRealDimCnt(*tensor_desc, dim_cnt) == GRAPH_SUCCESS, continue,
  242. "Get dim_cnt failed");
  243. opTensor_t tmp;
  244. uint32_t tmp_fmt = tensor_desc->GetFormat();
  245. tmp.format = tagOpTensorFormat(tmp_fmt);
  246. tmp.dim_cnt = static_cast<int32_t>(dim_cnt);
  247. uint32_t tmp_type = tensor_desc->GetDataType();
  248. tmp.data_type = tagOpDataType(tmp_type);
  249. for (int32_t j = 0; j < 4; j++) { // 4 dims
  250. tmp.dim[j] = (j < tmp.dim_cnt ? tensor_desc->GetShape().GetDim(j) : 1);
  251. }
  252. v_output_descs.push_back(tmp);
  253. }
  254. return v_output_descs;
  255. }
  256. ///
  257. /// @ingroup ge
  258. /// @brief Get input data address.
  259. /// @return vector<void*>
  260. ///
  261. vector<void *> ModelUtils::GetInputDataAddrs(const RuntimeParam &model_param, ConstOpDescPtr op_desc) {
  262. vector<void *> v_input_data_addr; // init as:buf_base + op_def_->input(i));
  263. GE_CHECK_NOTNULL_EXEC(op_desc, return v_input_data_addr);
  264. uint64_t session_id = model_param.session_id;
  265. const size_t inputs_size = op_desc->GetAllInputsSize();
  266. const vector<int64_t> v_input_offset = op_desc->GetInputOffset();
  267. const string op_type = op_desc->GetType();
  268. size_t non_const_index = 0;
  269. const vector<bool> v_is_input_const = op_desc->GetIsInputConst();
  270. vector<int64_t> v_memory_type;
  271. bool has_mem_type_attr = ge::AttrUtils::GetListInt(op_desc, ATTR_NAME_INPUT_MEM_TYPE_LIST, v_memory_type);
  272. if (has_mem_type_attr && (v_memory_type.size() != inputs_size)) {
  273. GELOGE(PARAM_INVALID, "Fusion: check input size failed, op: %s, input v_memory_type size: %zu input numbers: %zu",
  274. op_desc->GetName().c_str(), v_memory_type.size(), inputs_size);
  275. return v_input_data_addr;
  276. }
  277. for (size_t i = 0; i < inputs_size; ++i) {
  278. if ((i < v_is_input_const.size()) && v_is_input_const[i] && (op_type != NETOUTPUT)) {
  279. // TBE: add weights address to input
  280. const GeTensorDescPtr tensor_desc = op_desc->MutableInputDesc(i);
  281. if (tensor_desc == nullptr) {
  282. GELOGW("Op: %s, Index: %zu, Tensor Desc is null", op_desc->GetName().c_str(), i);
  283. continue;
  284. }
  285. int64_t tensor_size = 0;
  286. GE_CHK_STATUS(TensorUtils::GetSize(*tensor_desc, tensor_size));
  287. if (tensor_size) {
  288. int64_t data_offset = 0;
  289. GE_CHK_STATUS(TensorUtils::GetDataOffset(*tensor_desc, data_offset));
  290. VALIDATE_MEM_RANGE(op_desc, model_param.weight_size, data_offset);
  291. uint8_t *weight_addr = model_param.weight_base + data_offset;
  292. v_input_data_addr.push_back(weight_addr);
  293. GELOGI("[IMAS]GetInputDataAddrs graph_%u type[C] name[%s] input[%zu] memaddr[%p]", model_param.graph_id,
  294. op_desc->GetName().c_str(), i, weight_addr);
  295. }
  296. non_const_index++;
  297. continue;
  298. }
  299. GE_IF_BOOL_EXEC(non_const_index >= v_input_offset.size(),
  300. GELOGW("offsets=%zu, inputs=%zu, index=%zu.", v_input_offset.size(), inputs_size, non_const_index);
  301. break);
  302. int64_t input_offset = v_input_offset[non_const_index];
  303. non_const_index++;
  304. GE_IF_BOOL_EXEC(model_param.var_size != 0 && ge::VarManager::Instance(session_id)->IsVarAddr(input_offset),
  305. VALIDATE_MEM_RANGE(op_desc, model_param.var_size, input_offset - model_param.logic_var_base);
  306. uint8_t *variable_addr = model_param.var_base + input_offset - model_param.logic_var_base;
  307. v_input_data_addr.push_back(variable_addr);
  308. GELOGI("[IMAS]GetInputDataAddrs graph_%u type[V] name[%s] input[%lu] memaddr[%p]",
  309. model_param.graph_id, op_desc->GetName().c_str(), i, variable_addr);
  310. continue);
  311. // feature maps
  312. uint8_t *mem_addr = nullptr;
  313. // fusion
  314. if (has_mem_type_attr && v_memory_type[i] == RT_MEMORY_L1) {
  315. mem_addr = reinterpret_cast<uint8_t *>(reinterpret_cast<intptr_t>(input_offset));
  316. v_input_data_addr.push_back(mem_addr);
  317. } else {
  318. VALIDATE_MEM_RANGE(op_desc, model_param.mem_size, input_offset);
  319. mem_addr = model_param.mem_base + input_offset;
  320. v_input_data_addr.push_back(mem_addr);
  321. }
  322. GELOGI("[IMAS]GetInputDataAddrs graph_%u type[F] name[%s] input[%zu] memaddr[%p]", model_param.graph_id,
  323. op_desc->GetName().c_str(), i, mem_addr);
  324. }
  325. return v_input_data_addr;
  326. }
  327. ///
  328. /// @ingroup ge
  329. /// @brief Get output data address.
  330. /// @return vector<void*>
  331. ///
  332. vector<void *> ModelUtils::GetOutputDataAddrs(const RuntimeParam &model_param, ConstOpDescPtr op_desc) {
  333. vector<void *> v_output_data_addr; // init as:buf_base + op_def_->output(i)
  334. GE_CHECK_NOTNULL_EXEC(op_desc, return v_output_data_addr);
  335. uint64_t session_id = model_param.session_id;
  336. const size_t outputs_size = op_desc->GetOutputsSize();
  337. const vector<int64_t> v_output_offset = op_desc->GetOutputOffset();
  338. GE_IF_BOOL_EXEC(v_output_offset.size() != outputs_size,
  339. GELOGW("Output param invalid: output_offset=%zu, outputs=%zu.", v_output_offset.size(), outputs_size);
  340. return v_output_data_addr);
  341. vector<int64_t> v_memory_type;
  342. bool has_mem_type_attr = ge::AttrUtils::GetListInt(op_desc, ATTR_NAME_OUTPUT_MEM_TYPE_LIST, v_memory_type);
  343. if (has_mem_type_attr && (v_memory_type.size() != outputs_size)) {
  344. GELOGE(PARAM_INVALID,
  345. "Fusion: check output size failed, op: %s, output v_memory_type size: %lu output numbers: %zu",
  346. op_desc->GetName().c_str(), v_memory_type.size(), outputs_size);
  347. return v_output_data_addr;
  348. }
  349. for (size_t i = 0; i < outputs_size; ++i) {
  350. GE_IF_BOOL_EXEC(model_param.var_size != 0 && ge::VarManager::Instance(session_id)->IsVarAddr(v_output_offset[i]),
  351. VALIDATE_MEM_RANGE(op_desc, model_param.var_size, v_output_offset[i] - model_param.logic_var_base);
  352. uint8_t *variable_addr = model_param.var_base + v_output_offset[i] - model_param.logic_var_base;
  353. v_output_data_addr.push_back(variable_addr);
  354. GELOGI("[IMAS]GetOutputDataAddrs graph_%u type[V] name[%s] output[%zu] memaddr[%p]",
  355. model_param.graph_id, op_desc->GetName().c_str(), i, variable_addr);
  356. continue);
  357. // feature maps
  358. uint8_t *mem_addr = nullptr;
  359. // fusion
  360. if (has_mem_type_attr && v_memory_type[i] == RT_MEMORY_L1) {
  361. mem_addr = reinterpret_cast<uint8_t *>(reinterpret_cast<intptr_t>(v_output_offset[i]));
  362. v_output_data_addr.push_back(mem_addr);
  363. } else {
  364. VALIDATE_MEM_RANGE(op_desc, model_param.mem_size, v_output_offset[i]);
  365. mem_addr = static_cast<uint8_t *>(model_param.mem_base + v_output_offset[i]);
  366. v_output_data_addr.push_back(mem_addr);
  367. }
  368. GELOGI("[IMAS]GetOutputDataAddrs graph_%u type[F] name[%s] output[%zu] memaddr[%p]", model_param.graph_id,
  369. op_desc->GetName().c_str(), i, mem_addr);
  370. }
  371. return v_output_data_addr;
  372. }
  373. ///
  374. /// @ingroup ge
  375. /// @brief Get workspace data address.
  376. /// @return vector<void*>
  377. ///
  378. vector<void *> ModelUtils::GetWorkspaceDataAddrs(const RuntimeParam &model_param, ConstOpDescPtr op_desc) {
  379. vector<void *> v_workspace_data_addr;
  380. GE_CHECK_NOTNULL_EXEC(op_desc, return v_workspace_data_addr);
  381. const vector<int64_t> v_workspace_offset = op_desc->GetWorkspace();
  382. const vector<int64_t> v_workspace_bytes = op_desc->GetWorkspaceBytes();
  383. if (v_workspace_offset.size() != v_workspace_bytes.size()) {
  384. GELOGW("v_workspace_offset.size()[%zu] != v_workspace_bytes.size()[%zu]", v_workspace_offset.size(),
  385. v_workspace_bytes.size());
  386. return v_workspace_data_addr;
  387. }
  388. vector<int64_t> v_memory_type;
  389. bool has_mem_type_attr = ge::AttrUtils::GetListInt(op_desc, TVM_ATTR_NAME_WORKSPACE_TYPE, v_memory_type);
  390. for (size_t i = 0; i < v_workspace_bytes.size(); ++i) {
  391. if (has_mem_type_attr && v_memory_type[i] == RT_MEMORY_L1) {
  392. v_workspace_data_addr.push_back(reinterpret_cast<uint8_t *>(reinterpret_cast<intptr_t>(v_workspace_offset[i])));
  393. GELOGI("[IMAS]GetWorkspaceDataAddrs graph_%u type[L1] name[%s], mem_addr[workspace index %zu]:0x%lx",
  394. model_param.graph_id, op_desc->GetName().c_str(), i, v_workspace_offset[i]);
  395. } else if (v_workspace_bytes[i] == 0) {
  396. v_workspace_data_addr.push_back(nullptr);
  397. GELOGI("[IMAS]GetWorkspaceDataAddrs graph_%u type[F] name[%s] workspace[%zu] offset[%ld] bytes[%ld] Null addr",
  398. model_param.graph_id, op_desc->GetName().c_str(), i, v_workspace_offset[i], v_workspace_bytes[i]);
  399. } else {
  400. VALIDATE_MEM_RANGE(op_desc, model_param.mem_size, v_workspace_offset[i]);
  401. uint8_t *mem_addr = model_param.mem_base + v_workspace_offset[i];
  402. v_workspace_data_addr.push_back(mem_addr);
  403. GELOGI("[IMAS]GetWorkspaceDataAddrs graph_%u type[F] name[%s] workspace[%zu] offset[%ld] bytes[%ld] memaddr[%p]",
  404. model_param.graph_id, op_desc->GetName().c_str(), i, v_workspace_offset[i], v_workspace_bytes[i],
  405. mem_addr);
  406. }
  407. }
  408. return v_workspace_data_addr;
  409. }
  410. ///
  411. /// @ingroup ge
  412. /// @brief Get runtime memory address.
  413. /// @return Status
  414. ///
  415. Status ModelUtils::GetRtAddress(const RuntimeParam &param, uintptr_t logic_addr, uint8_t *&mem_addr) {
  416. uint8_t *runtime_base_addr = nullptr;
  417. if ((param.logic_mem_base <= logic_addr) && (logic_addr < param.logic_mem_base + param.mem_size)) {
  418. runtime_base_addr = param.mem_base - param.logic_mem_base;
  419. GELOGI("The logic addr:0x%lx is data address, base:0x%lx, size:%lu", logic_addr, param.logic_mem_base,
  420. param.mem_size);
  421. } else if ((param.logic_weight_base <= logic_addr) && (logic_addr < param.logic_weight_base + param.weight_size)) {
  422. runtime_base_addr = param.weight_base - param.logic_weight_base;
  423. GELOGI("The logic addr:0x%lx is weight address, base:0x%lx, size:%lu", logic_addr, param.logic_weight_base,
  424. param.weight_size);
  425. } else if ((param.logic_var_base <= logic_addr) && (logic_addr < param.logic_var_base + param.var_size)) {
  426. runtime_base_addr = param.var_base - param.logic_var_base;
  427. GELOGI("The logic addr:0x%lx is variable address, base:0x%lx, size:%lu", logic_addr, param.logic_var_base,
  428. param.var_size);
  429. } else if (logic_addr != 0) {
  430. mem_addr = nullptr;
  431. GELOGE(PARAM_INVALID, "The logic addr:0x%lx is abnormal", logic_addr);
  432. return PARAM_INVALID;
  433. }
  434. mem_addr = runtime_base_addr + logic_addr;
  435. return SUCCESS;
  436. }
  437. } // 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