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ge_aipp_op.cc 45 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/preprocess/insert_op/ge_aipp_op.h"
  17. #include <memory>
  18. #include <set>
  19. #include <string>
  20. #include <utility>
  21. #include <vector>
  22. #include "base_insert_op.h"
  23. #include "common/dynamic_aipp.h"
  24. #include "common/ge/ge_util.h"
  25. #include "common/util.h"
  26. #include "common/util/error_manager/error_manager.h"
  27. #include "external/graph/operator_factory.h"
  28. #include "framework/common/debug/ge_log.h"
  29. #include "framework/common/ge_inner_error_codes.h"
  30. #include "framework/common/op/ge_op_utils.h"
  31. #include "framework/common/types.h"
  32. #include "framework/omg/omg_inner_types.h"
  33. #include "graph/debug/ge_attr_define.h"
  34. #include "graph/optimize/common/params.h"
  35. #include "graph/utils/graph_utils.h"
  36. #include "graph/utils/node_utils.h"
  37. #include "graph/utils/op_desc_utils.h"
  38. #include "graph/utils/tensor_utils.h"
  39. #include "graph/utils/type_utils.h"
  40. #include "proto/insert_op.pb.h"
  41. #include "graph/common/local_context.h"
  42. #define SAVE_AIPP_ATTR(KEY, SAVE_TYPE) \
  43. do { \
  44. (void)aipp_attrs.SetAttr(#KEY, GeAttrValue::CreateFrom<SAVE_TYPE>(aipp_params_->KEY())); \
  45. } while (0)
  46. #define SAVE_AIPP_ATTR_LIST(KEY, SAVE_TYPE) \
  47. do { \
  48. if (aipp_params_->KEY##_size() > 0) { \
  49. (void)aipp_attrs.SetAttr(#KEY, GeAttrValue::CreateFrom<SAVE_TYPE>(aipp_params_->KEY(0))); \
  50. } \
  51. } while (0)
  52. namespace {
  53. const int32_t DEFAULT_MATRIX_R0C0_YUV2RGB = 298;
  54. const int32_t DEFAULT_MATRIX_R0C1_YUV2RGB = 0;
  55. const int32_t DEFAULT_MATRIX_R0C2_YUV2RGB = 409;
  56. const int32_t DEFAULT_MATRIX_R1C0_YUV2RGB = 298;
  57. const int32_t DEFAULT_MATRIX_R1C1_YUV2RGB = -100;
  58. const int32_t DEFAULT_MATRIX_R1C2_YUV2RGB = -208;
  59. const int32_t DEFAULT_MATRIX_R2C0_YUV2RGB = 298;
  60. const int32_t DEFAULT_MATRIX_R2C1_YUV2RGB = 516;
  61. const int32_t DEFAULT_MATRIX_R2C2_YUV2RGB = 0;
  62. const int32_t DEFAULT_MATRIX_R0C0_RGB2YUV = 66;
  63. const int32_t DEFAULT_MATRIX_R0C1_RGB2YUV = 129;
  64. const int32_t DEFAULT_MATRIX_R0C2_RGB2YUV = 25;
  65. const int32_t DEFAULT_MATRIX_R1C0_RGB2YUV = -38;
  66. const int32_t DEFAULT_MATRIX_R1C1_RGB2YUV = -74;
  67. const int32_t DEFAULT_MATRIX_R1C2_RGB2YUV = 112;
  68. const int32_t DEFAULT_MATRIX_R2C0_RGB2YUV = 112;
  69. const int32_t DEFAULT_MATRIX_R2C1_RGB2YUV = -94;
  70. const int32_t DEFAULT_MATRIX_R2C2_RGB2YUV = -18;
  71. const int32_t DEFAULT_OUTPUT_BIAS_0 = 16;
  72. const int32_t DEFAULT_OUTPUT_BIAS_1 = 128;
  73. const int32_t DEFAULT_OUTPUT_BIAS_2 = 128;
  74. const int32_t DEFAULT_INPUT_BIAS_0 = 16;
  75. const int32_t DEFAULT_INPUT_BIAS_1 = 128;
  76. const int32_t DEFAULT_INPUT_BIAS_2 = 128;
  77. const float DEFAULT_VAR_RECI_CHN = 1.0;
  78. } // namespace
  79. namespace ge {
  80. namespace {
  81. const char *const kMbatchSwitchnName = "mbatch-switch-name";
  82. const char *const kAippConfigPath = "aipp_config_path";
  83. const char *const kCurrentAippIndex = "current_aipp_index";
  84. const char *const kDynamicAippData = "ascend_dynamic_aipp_data";
  85. const uint64_t kMinTransferShape = 3;
  86. const int kAippImageInputIndex = 0;
  87. const int kAippParamsInputIndex = 1;
  88. const int kAippDataOutputIndex = 0;
  89. const int64_t kDynamicDim = -1;
  90. // the `format` must one NCHW or NHWC
  91. Status GetDataDimN(const ge::NodePtr &data_node, ge::Format format, int64_t &batch) {
  92. auto output_desc = NodeUtils::GetOutputDesc(*data_node, 0);
  93. auto shape = output_desc.GetShape().GetDims();
  94. if (shape.size() == kMinTransferShape) {
  95. batch = 1;
  96. return SUCCESS;
  97. }
  98. if (shape.size() == DIM_DEFAULT_SIZE) {
  99. switch (format) {
  100. case FORMAT_NCHW:
  101. batch = shape[NCHW_DIM_N];
  102. return SUCCESS;
  103. case FORMAT_NHWC:
  104. batch = shape[NHWC_DIM_N];
  105. return SUCCESS;
  106. default:
  107. REPORT_INPUT_ERROR("E10001", std::vector<std::string>({"parameter", "value", "reason"}),
  108. std::vector<std::string>({
  109. data_node->GetName() + " format",
  110. TypeUtils::FormatToSerialString(format),
  111. "only format " + TypeUtils::FormatToSerialString(FORMAT_NCHW) + " and "
  112. + TypeUtils::FormatToSerialString(FORMAT_NHWC) + " supported"}));
  113. GELOGE(PARAM_INVALID, "Not support data format: %s", TypeUtils::FormatToSerialString(format).c_str());
  114. return PARAM_INVALID;
  115. }
  116. }
  117. string errormsg = "its shape size must be in range[3,4] which dynamic aipp is linked, "
  118. "maybe this input is not suitable for dynamic aipp";
  119. ErrorManager::GetInstance().ATCReportErrMessage("E10001", {"parameter", "value", "reason"},
  120. {data_node->GetName() + " shape size",
  121. to_string(shape.size()), errormsg});
  122. GELOGE(PARAM_INVALID, "The shape size of this node [%s] which linked dynamic aipp must be in range[3, 4], but is %zu",
  123. data_node->GetName().c_str(), shape.size());
  124. return PARAM_INVALID;
  125. }
  126. // the batch_count must be more than 0
  127. int64_t CalcMaxSize(int64_t batch_count) {
  128. batch_count--;
  129. if (batch_count > 0) {
  130. if (INT64_MAX / batch_count < static_cast<int64_t>(sizeof(kAippDynamicBatchPara))) {
  131. return -1;
  132. }
  133. }
  134. int64_t size = batch_count * sizeof(kAippDynamicBatchPara);
  135. if (INT64_MAX - static_cast<int64_t>(sizeof(kAippDynamicPara)) < size) {
  136. return -1;
  137. }
  138. return size + sizeof(kAippDynamicPara);
  139. }
  140. Format GetAndCheckFormat() {
  141. switch (GetLocalOmgContext().format) {
  142. case domi::DOMI_TENSOR_NCHW:
  143. return FORMAT_NCHW;
  144. case domi::DOMI_TENSOR_NHWC:
  145. return FORMAT_NHWC;
  146. default:
  147. GELOGE(PARAM_INVALID, "Unexpected format found %d", static_cast<int>(GetLocalOmgContext().format));
  148. return FORMAT_ND;
  149. }
  150. }
  151. } // namespace
  152. Status AippOp::Init(domi::AippOpParams *aipp_params) {
  153. aipp_params_ = new (std::nothrow) domi::AippOpParams();
  154. if (aipp_params_ == nullptr) {
  155. REPORT_CALL_ERROR("E19999", "New AippOpParams failed when AippOp %s", __FUNCTION__);
  156. return FAILED;
  157. }
  158. aipp_params_->CopyFrom(*aipp_params);
  159. return SUCCESS;
  160. }
  161. AippOp::~AippOp() {
  162. if (aipp_params_ != nullptr) {
  163. delete aipp_params_;
  164. aipp_params_ = nullptr;
  165. }
  166. }
  167. Status AippOp::InsertAippToGraph(ComputeGraphPtr &graph, std::string &aippConfigPath, const uint32_t index) {
  168. GE_CHECK_NOTNULL(graph);
  169. NodePtr target_input = nullptr;
  170. std::vector<std::pair<OutDataAnchorPtr, InDataAnchorPtr>> target_edges;
  171. if (this->ConvertRelatedInputNameToRank() != SUCCESS) {
  172. GELOGE(FAILED, "AippOp: convert related input name to rank failed.");
  173. return FAILED;
  174. }
  175. GE_CHK_STATUS_RET(this->GetTargetPosition(graph, target_input, target_edges), "Get data nodes position failed");
  176. std::map<OutDataAnchorPtr, NodePtr> out_anchors_to_aipp;
  177. for (auto &out_in_anchors : target_edges) {
  178. auto iter = out_anchors_to_aipp.find(out_in_anchors.first);
  179. if (iter == out_anchors_to_aipp.end()) {
  180. auto aipp = CreateAipp(out_in_anchors.first, aippConfigPath, index);
  181. GE_CHECK_NOTNULL(aipp);
  182. out_anchors_to_aipp[out_in_anchors.first] = aipp;
  183. auto ret = GraphUtils::InsertNodeBetweenDataAnchors(out_in_anchors.first, out_in_anchors.second, aipp);
  184. if (ret != GRAPH_SUCCESS) {
  185. REPORT_CALL_ERROR("E19999", "Insert aipp:%s(%s) node between op:%s(%s) and op:%s:%s failed when AippOp %s",
  186. aipp->GetName().c_str(), aipp->GetType().c_str(),
  187. out_in_anchors.first->GetOwnerNode()->GetName().c_str(),
  188. out_in_anchors.first->GetOwnerNode()->GetType().c_str(),
  189. out_in_anchors.second->GetOwnerNode()->GetName().c_str(),
  190. out_in_anchors.second->GetOwnerNode()->GetType().c_str(),
  191. __FUNCTION__);
  192. GELOGE(INTERNAL_ERROR, "Failed to link edges for aipp node %s", aipp->GetName().c_str());
  193. return INTERNAL_ERROR;
  194. }
  195. // add aipp data if needed
  196. if (GetAippMode() == domi::AippOpParams::dynamic) {
  197. ret = CreateAippData(aipp);
  198. if (ret != SUCCESS) {
  199. GELOGE(INTERNAL_ERROR, "Failed to create aipp data for aipp %s data %s", aipp->GetName().c_str(),
  200. out_in_anchors.first->GetOwnerNode()->GetName().c_str());
  201. return INTERNAL_ERROR;
  202. }
  203. }
  204. GELOGI("Create aipp %s and insert it to the graph", aipp->GetName().c_str());
  205. } else {
  206. out_in_anchors.second->UnlinkAll();
  207. auto &aipp = iter->second;
  208. auto ret = out_in_anchors.second->LinkFrom(aipp->GetOutDataAnchor(0));
  209. if (ret != GRAPH_SUCCESS) {
  210. REPORT_CALL_ERROR("E19999", "link aipp:%s(%s) to peer op:%s(%s) failed when AippOp %s",
  211. aipp->GetName().c_str(), aipp->GetType().c_str(),
  212. out_in_anchors.second->GetOwnerNode()->GetName().c_str(),
  213. out_in_anchors.second->GetOwnerNode()->GetType().c_str(),
  214. __FUNCTION__);
  215. GELOGE(INTERNAL_ERROR, "Failed to link aipp %s to the peer node %s", aipp->GetName().c_str(),
  216. out_in_anchors.second->GetOwnerNode()->GetName().c_str());
  217. return INTERNAL_ERROR;
  218. }
  219. }
  220. }
  221. return SUCCESS;
  222. }
  223. NodePtr AippOp::CreateAipp(const OutDataAnchorPtr &out_anchor,
  224. const std::string &aippConfigPath, const uint32_t &index) {
  225. const auto &node = out_anchor->GetOwnerNode();
  226. std::string current_name = node->GetName() + "_" + std::to_string(out_anchor->GetIdx()) + "_huawei_aipp";
  227. auto aipp_opdesc_ptr = MakeShared<OpDesc>(current_name, AIPP);
  228. if (aipp_opdesc_ptr == nullptr) {
  229. REPORT_CALL_ERROR("E19999", "New OpDesc failed when AippOp %s", __FUNCTION__);
  230. GELOGE(OUT_OF_MEMORY, "Failed to alloc aipp desc, name %s", current_name.c_str());
  231. return nullptr;
  232. }
  233. // Update attributes
  234. if (AddAippAttrbutes(aipp_opdesc_ptr, aippConfigPath, index) != SUCCESS) {
  235. return nullptr;
  236. }
  237. // Update input desc, the output desc will be flushed when InferShape
  238. auto node_desc = out_anchor->GetOwnerNode()->GetOpDesc();
  239. if (node_desc == nullptr) {
  240. return nullptr;
  241. }
  242. auto opdesc_src_data = node_desc->GetOutputDesc(out_anchor->GetIdx());
  243. if (opdesc_src_data.GetDataType() != DT_FLOAT) {
  244. GELOGW("The datatype of data node %s is not FP32", node_desc->GetName().c_str());
  245. opdesc_src_data.SetDataType(DT_FLOAT);
  246. }
  247. // We must get the TensorDesc from the output anchor on the Data node,
  248. // and update the TensorDesc to the input anchor on the Aipp node.
  249. // Because the InferShape function for the Aipp node needs the input tensor format,
  250. // but the InferFormat process before InferShape can not infer the format
  251. // if the tensor on the Aipp has an unknown shape
  252. if (aipp_opdesc_ptr->UpdateInputDesc(kAippImageInputIndex, opdesc_src_data) != GRAPH_SUCCESS) {
  253. REPORT_CALL_ERROR("E19999", "Update the output desc from node:%s(%s) to aipp:%s(%s) failed when AippOp %s",
  254. node_desc->GetName().c_str(), node_desc->GetType().c_str(),
  255. aipp_opdesc_ptr->GetName().c_str(), aipp_opdesc_ptr->GetType().c_str(), __FUNCTION__);
  256. GELOGE(INTERNAL_ERROR, "Failed to update the output desc from node %s to aipp %s", node_desc->GetName().c_str(),
  257. aipp_opdesc_ptr->GetName().c_str());
  258. return nullptr;
  259. }
  260. return node->GetOwnerComputeGraph()->AddNode(aipp_opdesc_ptr);
  261. }
  262. Status AippOp::AddAippAttrbutes(const OpDescPtr &op_desc, const std::string &aipp_cfg_path, const uint32_t &index) {
  263. GeAttrValue::NAMED_ATTRS aipp_attr;
  264. ConvertParamToAttr(aipp_attr);
  265. GE_CHK_BOOL_RET_STATUS(AttrUtils::SetNamedAttrs(op_desc, ATTR_NAME_AIPP, aipp_attr),
  266. INTERNAL_ERROR, "Set name attrs for aipp node failed");
  267. GE_CHK_BOOL_RET_STATUS(AttrUtils::SetStr(op_desc, kAippConfigPath, aipp_cfg_path),
  268. INTERNAL_ERROR, "Set config file path attr for aipp node failed");
  269. std::vector<std::string> empty_names;
  270. GE_CHK_BOOL_RET_STATUS(AttrUtils::SetListStr(op_desc, ATTR_NAME_DATA_DUMP_ORIGIN_OP_NAMES, empty_names),
  271. INTERNAL_ERROR, "Set ATTR_NAME_DATA_DUMP_ORIGIN_OP_NAMES attr for aipp node failed");
  272. GE_CHK_BOOL_RET_STATUS(AttrUtils::SetInt(op_desc, kCurrentAippIndex, index),
  273. INTERNAL_ERROR, "Set kCurrentAippIndex attr for aipp node failed");
  274. // add input/output desc
  275. GeTensorDesc tensor;
  276. GE_CHK_GRAPH_STATUS_RET(op_desc->AddInputDesc("images", tensor), "Failed to add input images for aipp node");
  277. if (GetAippMode() == domi::AippOpParams::dynamic) {
  278. GE_CHK_GRAPH_STATUS_RET(op_desc->AddOptionalInputDesc("params", tensor), "Failed to add params for aipp node");
  279. }
  280. GE_CHK_GRAPH_STATUS_RET(op_desc->AddOutputDesc("features", tensor), "Failed to add output features for aipp node");
  281. return SUCCESS;
  282. }
  283. domi::AippOpParams::AippMode AippOp::GetAippMode() { return aipp_params_->aipp_mode(); }
  284. NodePtr AippOp::FindDataByIndex(const ComputeGraphPtr &graph, int rank) {
  285. int64_t data_index = 0;
  286. for (auto &node : graph->GetDirectNode()) {
  287. if (node->GetType() != DATA) {
  288. continue;
  289. }
  290. // For functional multi batch, Skip Data for index.
  291. if (node->GetOpDesc()->HasAttr(ATTR_INSERT_BY_MBATCH)) {
  292. continue;
  293. }
  294. // There is no `index` attribute on the `Data` node when compile in inference scene
  295. // so we can only use the order of all `Data` nodes to infer the data index
  296. if (data_index++ != rank) {
  297. continue;
  298. }
  299. return node;
  300. }
  301. string error_msg = "Can not find the data node by aipp parameter related_input_rank " + to_string(rank);
  302. GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str());
  303. return nullptr;
  304. }
  305. Status AippOp::GetAndCheckTarget(const ComputeGraphPtr &graph, int rank, NodePtr &target,
  306. std::set<uint32_t> &edge_indexes) {
  307. auto data_node = FindDataByIndex(graph, rank);
  308. if (data_node == nullptr) {
  309. GELOGE(PARAM_INVALID, "Get target input node for rank %d failed", rank);
  310. return PARAM_INVALID;
  311. }
  312. data_node_linked_aipp = data_node;
  313. auto data_opdesc = data_node->GetOpDesc();
  314. GE_CHECK_NOTNULL(data_opdesc);
  315. string set_dt_str;
  316. if (ge::AttrUtils::GetStr(data_opdesc, ATTR_ATC_USER_DEFINE_DATATYPE, set_dt_str)) {
  317. ErrorManager::GetInstance().ATCReportErrMessage("E10034", {"opname"}, {data_opdesc->GetName()});
  318. GELOGE(INTERNAL_ERROR,
  319. "This input op [%s] is linked to aipp, can not be set to fp16, "
  320. "please check your atc parameter --insert_op_conf, --input_fp16_nodes.",
  321. data_opdesc->GetName().c_str());
  322. return PARAM_INVALID;
  323. }
  324. // add dynamic or static attr memsage to data
  325. if (GetAippMode() == domi::AippOpParams::static_) {
  326. (void)AttrUtils::SetStr(data_opdesc, ATTR_DATA_RELATED_AIPP_MODE, "static_aipp");
  327. } else if (GetAippMode() == domi::AippOpParams::dynamic) {
  328. (void)AttrUtils::SetStr(data_opdesc, ATTR_DATA_RELATED_AIPP_MODE, "dynamic_aipp");
  329. }
  330. // In scenario AIPP+CONV2D+POOLING, keep the aipp info to Data, since AIPP disappear after subgraph optimize
  331. GeAttrValue::NAMED_ATTRS aipp_attr;
  332. ConvertParamToAttr(aipp_attr);
  333. if (!AttrUtils::SetNamedAttrs(data_opdesc, ATTR_NAME_AIPP, aipp_attr)) {
  334. REPORT_INNER_ERROR("E19999", "Set Attr:%s for op:%s(%s) failed when AippOp %s", ATTR_NAME_AIPP.c_str(),
  335. data_opdesc->GetName().c_str(), data_opdesc->GetType().c_str(), __FUNCTION__);
  336. GELOGE(INTERNAL_ERROR, "Set name attrs for Data node failed. id: %d", rank);
  337. return INTERNAL_ERROR;
  338. }
  339. if (aipp_params_->input_edge_idx_size() > 0) {
  340. for (auto edge_index : aipp_params_->input_edge_idx()) {
  341. edge_indexes.insert(edge_index);
  342. }
  343. }
  344. if (!edge_indexes.empty() && (*edge_indexes.rbegin() >= data_node->GetOutDataNodes().size())) {
  345. string error_msg = "The aipp parameter input_edge_idx[" + std::to_string(*edge_indexes.rbegin()) +
  346. "] should be smaller than the target input[" +
  347. std::to_string(data_node->GetOutDataNodes().size()) +"]'s outnodes.";
  348. GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str());
  349. return PARAM_INVALID;
  350. }
  351. target = data_node;
  352. return GetStaticTargetNode(graph, data_node, target);
  353. }
  354. Status AippOp::GetStaticTargetNode(const ComputeGraphPtr &graph, NodePtr &data_node, NodePtr &target) {
  355. if (GetAippMode() != domi::AippOpParams::static_) {
  356. return SUCCESS;
  357. }
  358. std::string related_node_name;
  359. if (AttrUtils::GetStr(data_node->GetOpDesc(), kMbatchSwitchnName, related_node_name)) {
  360. if (related_node_name.empty()) {
  361. REPORT_INNER_ERROR("E19999", "The data node %s has switchn node flag, but the value of attr:%s is empty, "
  362. "check invalid when AippOp %s", data_node->GetName().c_str(),
  363. kMbatchSwitchnName, __FUNCTION__);
  364. GELOGE(INTERNAL_ERROR, "The data node %s has switchn node flag, but the value is empty",
  365. data_node->GetName().c_str());
  366. return INTERNAL_ERROR;
  367. }
  368. auto switchn = graph->FindNode(related_node_name);
  369. if (switchn == nullptr) {
  370. REPORT_INNER_ERROR("E19999", "The data node %s has switchn node %s, but can not find it on the graph, "
  371. "check invalid when AippOp %s", data_node->GetName().c_str(), related_node_name.c_str(),
  372. __FUNCTION__);
  373. GELOGE(INTERNAL_ERROR, "The data node %s has switchn node %s, but can not find it on the graph",
  374. data_node->GetName().c_str(), related_node_name.c_str());
  375. return INTERNAL_ERROR;
  376. }
  377. target = switchn;
  378. GELOGI("Multi-batch/image size and static aipp for data %s, "
  379. "the aipp node will be insert after %s instead of origin data node",
  380. data_node->GetName().c_str(), switchn->GetName().c_str());
  381. return SUCCESS;
  382. }
  383. const auto out_anchor = data_node->GetOutDataAnchor(0);
  384. for (const auto &in_anchor : out_anchor->GetPeerInDataAnchors()) {
  385. if (in_anchor == nullptr) {
  386. continue;
  387. }
  388. const auto &case_node = in_anchor->GetOwnerNode();
  389. if (case_node->GetType() == CASE) {
  390. target = case_node;
  391. return SUCCESS;
  392. }
  393. }
  394. return SUCCESS;
  395. }
  396. Status AippOp::ConvertRelatedInputNameToRank() {
  397. GE_CHECK_NOTNULL(aipp_params_);
  398. string related_input_name = aipp_params_->related_input_name();
  399. if (related_input_name.empty()) {
  400. return SUCCESS;
  401. }
  402. std::vector<std::string> data_top_names = domi::GetContext().data_top_names;
  403. GELOGI("Convert name to rank start: data size[%zu]", data_top_names.size());
  404. uint32_t index = 0;
  405. bool convert_flag = false;
  406. for (const auto &data_top_name : data_top_names) {
  407. if (related_input_name == data_top_name) {
  408. aipp_params_->set_related_input_rank(index);
  409. convert_flag = true;
  410. GELOGI("AippOp: rank: %u, top name: %s.", index, data_top_name.c_str());
  411. break;
  412. }
  413. index++;
  414. }
  415. if (!convert_flag) {
  416. string error_msg = "Top name " + related_input_name + "convert rank failed, Please"
  417. " ensure top name in aipp config is the top name of data node.";
  418. GELOGE(PARAM_INVALID, "[Check][InputParam]%s", error_msg.c_str());
  419. REPORT_INPUT_ERROR("E19021", std::vector<std::string>({"reason"}), std::vector<std::string>({error_msg}));
  420. return PARAM_INVALID;
  421. }
  422. return SUCCESS;
  423. }
  424. Status AippOp::GetTargetPosition(ComputeGraphPtr graph, NodePtr &target_input,
  425. std::vector<std::pair<OutDataAnchorPtr, InDataAnchorPtr>> &target_edges) {
  426. GE_CHECK_NOTNULL(graph);
  427. GE_CHECK_NOTNULL(aipp_params_);
  428. std::set<uint32_t> edge_indexes;
  429. const uint32_t related_input_rank = aipp_params_->related_input_rank();
  430. auto ret = GetAndCheckTarget(graph, related_input_rank, target_input, edge_indexes);
  431. if (ret != SUCCESS) {
  432. GELOGE(ret, "Get target input node for rank %u failed", related_input_rank);
  433. return ret;
  434. }
  435. target_edges.clear();
  436. if (target_input->GetType() != CASE) {
  437. for (OutDataAnchorPtr &src_out : target_input->GetAllOutDataAnchors()) {
  438. auto dst_ins = src_out->GetPeerInDataAnchors();
  439. for (uint32_t i = 0; i < dst_ins.size(); ++i) {
  440. auto dst_in = dst_ins.at(i);
  441. if (edge_indexes.empty() || edge_indexes.count(i) > 0) {
  442. target_edges.emplace_back(src_out, dst_in);
  443. }
  444. }
  445. }
  446. } else {
  447. const auto &func_desc = target_input->GetOpDesc();
  448. for (const auto &name : func_desc->GetSubgraphInstanceNames()) {
  449. const auto &subgraph = graph->GetSubgraph(name);
  450. if (subgraph == nullptr) {
  451. REPORT_INNER_ERROR("E19999", "Subgraph:%s of op:%s(%s) not find in graph:%s, check invalid when AippOp %s",
  452. name.c_str(), func_desc->GetName().c_str(), func_desc->GetType().c_str(),
  453. graph->GetName().c_str(), __FUNCTION__);
  454. GELOGE(GE_GRAPH_EMPTY_SUBGRAPH, "Subgraph not found, name: %s", name.c_str());
  455. return GE_GRAPH_EMPTY_SUBGRAPH;
  456. }
  457. auto data_node = FindDataByIndex(subgraph, related_input_rank);
  458. if (data_node == nullptr) {
  459. GELOGE(PARAM_INVALID, "Get target input node for rank %d failed", related_input_rank);
  460. return PARAM_INVALID;
  461. }
  462. for (OutDataAnchorPtr &src_out : data_node->GetAllOutDataAnchors()) {
  463. auto dst_ins = src_out->GetPeerInDataAnchors();
  464. for (uint32_t i = 0; i < dst_ins.size(); ++i) {
  465. auto dst_in = dst_ins.at(i);
  466. if (edge_indexes.empty() || edge_indexes.count(i) > 0) {
  467. target_edges.emplace_back(src_out, dst_in);
  468. }
  469. }
  470. }
  471. }
  472. }
  473. return SUCCESS;
  474. }
  475. Status AippOp::SetDefaultParams() {
  476. GE_CHECK_NOTNULL(aipp_params_);
  477. const domi::AippOpParams::AippMode aipp_mode = aipp_params_->aipp_mode();
  478. if (aipp_mode == domi::AippOpParams::static_) {
  479. if (aipp_params_->csc_switch()) {
  480. SetCscDefaultValue();
  481. }
  482. SetDtcDefaultValue();
  483. GELOGI("parse aipp params:input_format:%s, csc_switch:%d.",
  484. domi::AippOpParams::InputFormat_Name(aipp_params_->input_format()).c_str(), aipp_params_->csc_switch());
  485. GELOGI("parse aipp params:mean_chn_0:%d, mean_chn_1:%d, mean_chn_2:%d, mean_chn_3:%d.", aipp_params_->mean_chn_0(),
  486. aipp_params_->mean_chn_1(), aipp_params_->mean_chn_2(), aipp_params_->mean_chn_3());
  487. GELOGI("parse aipp params:min_chn_0:%f, min_chn_1:%f, min_chn_2:%f.", aipp_params_->min_chn_0(),
  488. aipp_params_->min_chn_1(), aipp_params_->min_chn_2());
  489. GE_IF_BOOL_EXEC(!aipp_params_->crop(), aipp_params_->set_load_start_pos_h(0); aipp_params_->set_load_start_pos_w(0);
  490. aipp_params_->set_crop_size_h(0); aipp_params_->set_crop_size_w(0););
  491. GE_IF_BOOL_EXEC(!aipp_params_->resize(), aipp_params_->set_resize_output_h(0);
  492. aipp_params_->set_resize_output_w(0););
  493. GE_IF_BOOL_EXEC(!aipp_params_->padding(), aipp_params_->set_left_padding_size(0);
  494. aipp_params_->set_right_padding_size(0); aipp_params_->set_top_padding_size(0);
  495. aipp_params_->set_bottom_padding_size(0););
  496. }
  497. return SUCCESS;
  498. }
  499. Status AippOp::ValidateParams() {
  500. GE_CHECK_NOTNULL(aipp_params_);
  501. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->aipp_mode() != domi::AippOpParams::undefined, PARAM_INVALID,
  502. "When insert AIPP op, aipp_mode must be configured as static or dynamic ");
  503. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->var_reci_chn_0_size() <= 1, PARAM_INVALID,
  504. "The parameter var_reci_chn_0 can not be configed repeatedly");
  505. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->var_reci_chn_1_size() <= 1, PARAM_INVALID,
  506. "The parameter var_reci_chn_1 can not be configed repeatedly");
  507. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->var_reci_chn_2_size() <= 1, PARAM_INVALID,
  508. "The parameter var_reci_chn_2 can not be configed repeatedly");
  509. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->var_reci_chn_3_size() <= 1, PARAM_INVALID,
  510. "The parameter var_reci_chn_3 can not be configed repeatedly");
  511. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r0c0_size() <= 1, PARAM_INVALID,
  512. "The parameter matrix_r0c0 can not be configed repeatedly");
  513. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r0c1_size() <= 1, PARAM_INVALID,
  514. "The parameter matrix_r0c1 can not be configed repeatedly");
  515. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r0c2_size() <= 1, PARAM_INVALID,
  516. "The parameter matrix_r0c2 can not be configed repeatedly");
  517. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r1c0_size() <= 1, PARAM_INVALID,
  518. "The parameter matrix_r1c0 can not be configed repeatedly");
  519. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r1c1_size() <= 1, PARAM_INVALID,
  520. "The parameter matrix_r1c1 can not be configed repeatedly");
  521. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r1c2_size() <= 1, PARAM_INVALID,
  522. "The parameter matrix_r1c2 can not be configed repeatedly");
  523. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r2c0_size() <= 1, PARAM_INVALID,
  524. "The parameter matrix_r2c0 can not be configed repeatedly");
  525. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r2c1_size() <= 1, PARAM_INVALID,
  526. "The parameter matrix_r2c1 can not be configed repeatedly");
  527. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r2c2_size() <= 1, PARAM_INVALID,
  528. "The parameter matrix_r2c2 can not be configed repeatedly");
  529. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->output_bias_0_size() <= 1, PARAM_INVALID,
  530. "The parameter output_bias_0 can not be configed repeatedly");
  531. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->output_bias_1_size() <= 1, PARAM_INVALID,
  532. "The parameter output_bias_1 can not be configed repeatedly");
  533. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->output_bias_2_size() <= 1, PARAM_INVALID,
  534. "The parameter output_bias_2 can not be configed repeatedly");
  535. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->input_bias_0_size() <= 1, PARAM_INVALID,
  536. "The parameter input_bias_0 can not be configed repeatedly");
  537. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->input_bias_1_size() <= 1, PARAM_INVALID,
  538. "The parameter input_bias_1 can not be configed repeatedly");
  539. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->input_bias_2_size() <= 1, PARAM_INVALID,
  540. "The parameter input_bias_2 can not be configed repeatedly");
  541. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->input_edge_idx_size() <= 1, PARAM_INVALID,
  542. "The parameter input_edge_idx can not be configed repeatedly");
  543. const domi::AippOpParams::AippMode aipp_mode = aipp_params_->aipp_mode();
  544. if (aipp_mode == domi::AippOpParams::dynamic) {
  545. GE_CHK_LOG_AND_ERRORMSG(
  546. aipp_params_->max_src_image_size() > 0, PARAM_INVALID,
  547. "For dynamic AIPP params, max_src_image_size must be set which number should be greater than 0");
  548. } else {
  549. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->input_format() != domi::AippOpParams::UNDEFINED, PARAM_INVALID,
  550. "Input format of AIPP conf is undefined");
  551. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->src_image_size_w() >= 0, PARAM_INVALID,
  552. "Src_image_size_w must not be configed smaller than 0");
  553. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->src_image_size_h() >= 0, PARAM_INVALID,
  554. "Src_image_size_h must not be configed smaller than 0");
  555. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->load_start_pos_w() >= 0, PARAM_INVALID,
  556. "Load_start_pos_w must not be configed smaller than 0");
  557. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->load_start_pos_h() >= 0, PARAM_INVALID,
  558. "Load_start_pos_h must not be configed smaller than 0");
  559. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->crop_size_w() >= 0, PARAM_INVALID,
  560. "Crop_size_w must not be configed smaller than 0");
  561. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->resize_output_w() >= 0, PARAM_INVALID,
  562. "Resize_output_w must not be configed smaller than 0");
  563. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->resize_output_h() >= 0, PARAM_INVALID,
  564. "Resize_output_h must not be configed smaller than 0");
  565. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->left_padding_size() >= 0, PARAM_INVALID,
  566. "Left_padding_size must not be configed smaller than 0");
  567. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->right_padding_size() >= 0, PARAM_INVALID,
  568. "Right_padding_size must not be configed smaller than 0");
  569. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->top_padding_size() >= 0, PARAM_INVALID,
  570. "Top_padding_size must not be configed smaller than 0");
  571. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->bottom_padding_size() >= 0, PARAM_INVALID,
  572. "Bottom_padding_size must not be configed smaller than 0");
  573. }
  574. return SUCCESS;
  575. }
  576. void AippOp::SetCscDefaultValue() {
  577. GE_CHECK_NOTNULL_JUST_RETURN(aipp_params_);
  578. if (aipp_params_->input_format() == domi::AippOpParams::YUV420SP_U8) {
  579. CHECK_FALSE_EXEC(aipp_params_->matrix_r0c0_size() > 0, aipp_params_->add_matrix_r0c0(DEFAULT_MATRIX_R2C0_YUV2RGB));
  580. CHECK_FALSE_EXEC(aipp_params_->matrix_r0c1_size() > 0, aipp_params_->add_matrix_r0c1(DEFAULT_MATRIX_R2C1_YUV2RGB));
  581. CHECK_FALSE_EXEC(aipp_params_->matrix_r0c2_size() > 0, aipp_params_->add_matrix_r0c2(DEFAULT_MATRIX_R2C2_YUV2RGB));
  582. CHECK_FALSE_EXEC(aipp_params_->matrix_r1c0_size() > 0, aipp_params_->add_matrix_r1c0(DEFAULT_MATRIX_R1C0_YUV2RGB));
  583. CHECK_FALSE_EXEC(aipp_params_->matrix_r1c1_size() > 0, aipp_params_->add_matrix_r1c1(DEFAULT_MATRIX_R1C1_YUV2RGB));
  584. CHECK_FALSE_EXEC(aipp_params_->matrix_r1c2_size() > 0, aipp_params_->add_matrix_r1c2(DEFAULT_MATRIX_R1C2_YUV2RGB));
  585. CHECK_FALSE_EXEC(aipp_params_->matrix_r2c0_size() > 0, aipp_params_->add_matrix_r2c0(DEFAULT_MATRIX_R0C0_YUV2RGB));
  586. CHECK_FALSE_EXEC(aipp_params_->matrix_r2c1_size() > 0, aipp_params_->add_matrix_r2c1(DEFAULT_MATRIX_R0C1_YUV2RGB));
  587. CHECK_FALSE_EXEC(aipp_params_->matrix_r2c2_size() > 0, aipp_params_->add_matrix_r2c2(DEFAULT_MATRIX_R0C2_YUV2RGB));
  588. } else {
  589. CHECK_FALSE_EXEC(aipp_params_->matrix_r0c0_size() > 0, aipp_params_->add_matrix_r0c0(DEFAULT_MATRIX_R0C0_RGB2YUV));
  590. CHECK_FALSE_EXEC(aipp_params_->matrix_r0c1_size() > 0, aipp_params_->add_matrix_r0c1(DEFAULT_MATRIX_R0C1_RGB2YUV));
  591. CHECK_FALSE_EXEC(aipp_params_->matrix_r0c2_size() > 0, aipp_params_->add_matrix_r0c2(DEFAULT_MATRIX_R0C2_RGB2YUV));
  592. CHECK_FALSE_EXEC(aipp_params_->matrix_r1c0_size() > 0, aipp_params_->add_matrix_r1c0(DEFAULT_MATRIX_R1C0_RGB2YUV));
  593. CHECK_FALSE_EXEC(aipp_params_->matrix_r1c1_size() > 0, aipp_params_->add_matrix_r1c1(DEFAULT_MATRIX_R1C1_RGB2YUV));
  594. CHECK_FALSE_EXEC(aipp_params_->matrix_r1c2_size() > 0, aipp_params_->add_matrix_r1c2(DEFAULT_MATRIX_R1C2_RGB2YUV));
  595. CHECK_FALSE_EXEC(aipp_params_->matrix_r2c0_size() > 0, aipp_params_->add_matrix_r2c0(DEFAULT_MATRIX_R2C0_RGB2YUV));
  596. CHECK_FALSE_EXEC(aipp_params_->matrix_r2c1_size() > 0, aipp_params_->add_matrix_r2c1(DEFAULT_MATRIX_R2C1_RGB2YUV));
  597. CHECK_FALSE_EXEC(aipp_params_->matrix_r2c2_size() > 0, aipp_params_->add_matrix_r2c2(DEFAULT_MATRIX_R2C2_RGB2YUV));
  598. }
  599. CHECK_FALSE_EXEC(aipp_params_->input_bias_0_size() > 0, aipp_params_->add_input_bias_0(DEFAULT_INPUT_BIAS_0));
  600. CHECK_FALSE_EXEC(aipp_params_->input_bias_1_size() > 0, aipp_params_->add_input_bias_1(DEFAULT_INPUT_BIAS_1));
  601. CHECK_FALSE_EXEC(aipp_params_->input_bias_2_size() > 0, aipp_params_->add_input_bias_2(DEFAULT_INPUT_BIAS_2));
  602. CHECK_FALSE_EXEC(aipp_params_->output_bias_0_size() > 0, aipp_params_->add_output_bias_0(DEFAULT_OUTPUT_BIAS_0));
  603. CHECK_FALSE_EXEC(aipp_params_->output_bias_1_size() > 0, aipp_params_->add_output_bias_1(DEFAULT_OUTPUT_BIAS_1));
  604. CHECK_FALSE_EXEC(aipp_params_->output_bias_2_size() > 0, aipp_params_->add_output_bias_2(DEFAULT_OUTPUT_BIAS_2));
  605. }
  606. void AippOp::SetDtcDefaultValue() {
  607. GE_CHECK_NOTNULL_JUST_RETURN(aipp_params_);
  608. CHECK_FALSE_EXEC(aipp_params_->var_reci_chn_0_size() > 0, aipp_params_->add_var_reci_chn_0(DEFAULT_VAR_RECI_CHN));
  609. GELOGD("var_reci_chn_0 is %f, size is %u.", DEFAULT_VAR_RECI_CHN, aipp_params_->var_reci_chn_0_size());
  610. CHECK_FALSE_EXEC(aipp_params_->var_reci_chn_1_size() > 0, aipp_params_->add_var_reci_chn_1(DEFAULT_VAR_RECI_CHN));
  611. GELOGD("var_reci_chn_1 is %f, size is %u.", DEFAULT_VAR_RECI_CHN, aipp_params_->var_reci_chn_1_size());
  612. CHECK_FALSE_EXEC(aipp_params_->var_reci_chn_2_size() > 0, aipp_params_->add_var_reci_chn_2(DEFAULT_VAR_RECI_CHN));
  613. GELOGD("var_reci_chn_2 is %f, size is %u.", DEFAULT_VAR_RECI_CHN, aipp_params_->var_reci_chn_2_size());
  614. CHECK_FALSE_EXEC(aipp_params_->var_reci_chn_3_size() > 0, aipp_params_->add_var_reci_chn_3(DEFAULT_VAR_RECI_CHN));
  615. GELOGD("var_reci_chn_3 is %f, size is %u.", DEFAULT_VAR_RECI_CHN, aipp_params_->var_reci_chn_3_size());
  616. }
  617. Status AippOp::GenerateOpDesc(OpDescPtr op_desc) {
  618. GE_CHECK_NOTNULL(op_desc);
  619. static std::atomic_long atomic_op_idx(0);
  620. auto op_idx = atomic_op_idx.fetch_add(1);
  621. op_desc->SetName(std::string("aipp_node").append(std::to_string(op_idx)));
  622. op_desc->SetType(AIPP);
  623. // Add two InputDesc, add the second after the first one is added successfully.
  624. if ((op_desc->AddInputDesc(GeTensorDesc()) != GRAPH_SUCCESS) ||
  625. (op_desc->AddInputDesc(GeTensorDesc()) != GRAPH_SUCCESS)) {
  626. REPORT_CALL_ERROR("E19999", "Add input desc into op:%s(%s) failed when AippOp %s",
  627. op_desc->GetName().c_str(), op_desc->GetType().c_str(), __FUNCTION__);
  628. GELOGE(FAILED, "failed to add input desc");
  629. return FAILED;
  630. }
  631. if (op_desc->AddOutputDesc(GeTensorDesc()) != GRAPH_SUCCESS) {
  632. REPORT_CALL_ERROR("E19999", "Add output desc into op:%s(%s) failed when AippOp %s",
  633. op_desc->GetName().c_str(), op_desc->GetType().c_str(), __FUNCTION__);
  634. GELOGE(FAILED, "add output desc failed.");
  635. return FAILED;
  636. }
  637. GeAttrValue::NAMED_ATTRS aipp_attrs;
  638. ConvertParamToAttr(aipp_attrs);
  639. GE_IF_BOOL_EXEC(!AttrUtils::SetNamedAttrs(op_desc, ATTR_NAME_AIPP, aipp_attrs),
  640. REPORT_INNER_ERROR("E19999", "Set Attr:%s to op:%s(%s) failed when AippOp %s", ATTR_NAME_AIPP.c_str(),
  641. op_desc->GetName().c_str(), op_desc->GetType().c_str(), __FUNCTION__);
  642. GELOGE(FAILED, "failed to set ATTR_NAME_AIPP");
  643. return FAILED);
  644. return SUCCESS;
  645. }
  646. void AippOp::ConvertParamToAttr(GeAttrValue::NAMED_ATTRS &aipp_attrs) {
  647. GE_CHECK_NOTNULL_JUST_RETURN(aipp_params_);
  648. SAVE_AIPP_ATTR(aipp_mode, GeAttrValue::INT);
  649. SAVE_AIPP_ATTR(related_input_rank, GeAttrValue::INT);
  650. if (aipp_params_->aipp_mode() == domi::AippOpParams::static_) {
  651. SAVE_AIPP_ATTR(input_format, GeAttrValue::INT);
  652. SAVE_AIPP_ATTR(csc_switch, GeAttrValue::BOOL);
  653. SAVE_AIPP_ATTR(crop, GeAttrValue::BOOL);
  654. SAVE_AIPP_ATTR(resize, GeAttrValue::BOOL);
  655. SAVE_AIPP_ATTR(load_start_pos_w, GeAttrValue::INT);
  656. SAVE_AIPP_ATTR(load_start_pos_h, GeAttrValue::INT);
  657. SAVE_AIPP_ATTR(crop_size_w, GeAttrValue::INT);
  658. SAVE_AIPP_ATTR(crop_size_h, GeAttrValue::INT);
  659. SAVE_AIPP_ATTR(resize, GeAttrValue::BOOL);
  660. SAVE_AIPP_ATTR(resize_output_w, GeAttrValue::INT);
  661. SAVE_AIPP_ATTR(resize_output_h, GeAttrValue::INT);
  662. SAVE_AIPP_ATTR(padding, GeAttrValue::BOOL);
  663. SAVE_AIPP_ATTR(left_padding_size, GeAttrValue::INT);
  664. SAVE_AIPP_ATTR(right_padding_size, GeAttrValue::INT);
  665. SAVE_AIPP_ATTR(top_padding_size, GeAttrValue::INT);
  666. SAVE_AIPP_ATTR(bottom_padding_size, GeAttrValue::INT);
  667. SAVE_AIPP_ATTR(src_image_size_w, GeAttrValue::INT);
  668. SAVE_AIPP_ATTR(src_image_size_h, GeAttrValue::INT);
  669. SAVE_AIPP_ATTR(cpadding_value, GeAttrValue::FLOAT);
  670. SAVE_AIPP_ATTR(rbuv_swap_switch, GeAttrValue::BOOL);
  671. SAVE_AIPP_ATTR(ax_swap_switch, GeAttrValue::BOOL);
  672. SAVE_AIPP_ATTR(single_line_mode, GeAttrValue::BOOL);
  673. SAVE_AIPP_ATTR(mean_chn_0, GeAttrValue::INT);
  674. SAVE_AIPP_ATTR(mean_chn_1, GeAttrValue::INT);
  675. SAVE_AIPP_ATTR(mean_chn_2, GeAttrValue::INT);
  676. SAVE_AIPP_ATTR(mean_chn_3, GeAttrValue::INT);
  677. SAVE_AIPP_ATTR(min_chn_0, GeAttrValue::FLOAT);
  678. SAVE_AIPP_ATTR(min_chn_1, GeAttrValue::FLOAT);
  679. SAVE_AIPP_ATTR(min_chn_2, GeAttrValue::FLOAT);
  680. SAVE_AIPP_ATTR(min_chn_3, GeAttrValue::FLOAT);
  681. SAVE_AIPP_ATTR_LIST(var_reci_chn_0, GeAttrValue::FLOAT);
  682. SAVE_AIPP_ATTR_LIST(var_reci_chn_1, GeAttrValue::FLOAT);
  683. SAVE_AIPP_ATTR_LIST(var_reci_chn_2, GeAttrValue::FLOAT);
  684. SAVE_AIPP_ATTR_LIST(var_reci_chn_3, GeAttrValue::FLOAT);
  685. SAVE_AIPP_ATTR_LIST(matrix_r0c0, GeAttrValue::INT);
  686. SAVE_AIPP_ATTR_LIST(matrix_r0c1, GeAttrValue::INT);
  687. SAVE_AIPP_ATTR_LIST(matrix_r0c2, GeAttrValue::INT);
  688. SAVE_AIPP_ATTR_LIST(matrix_r1c0, GeAttrValue::INT);
  689. SAVE_AIPP_ATTR_LIST(matrix_r1c1, GeAttrValue::INT);
  690. SAVE_AIPP_ATTR_LIST(matrix_r1c2, GeAttrValue::INT);
  691. SAVE_AIPP_ATTR_LIST(matrix_r2c0, GeAttrValue::INT);
  692. SAVE_AIPP_ATTR_LIST(matrix_r2c1, GeAttrValue::INT);
  693. SAVE_AIPP_ATTR_LIST(matrix_r2c2, GeAttrValue::INT);
  694. SAVE_AIPP_ATTR_LIST(output_bias_0, GeAttrValue::INT);
  695. SAVE_AIPP_ATTR_LIST(output_bias_1, GeAttrValue::INT);
  696. SAVE_AIPP_ATTR_LIST(output_bias_2, GeAttrValue::INT);
  697. SAVE_AIPP_ATTR_LIST(input_bias_0, GeAttrValue::INT);
  698. SAVE_AIPP_ATTR_LIST(input_bias_1, GeAttrValue::INT);
  699. SAVE_AIPP_ATTR_LIST(input_bias_2, GeAttrValue::INT);
  700. } else {
  701. SAVE_AIPP_ATTR(max_src_image_size, GeAttrValue::INT);
  702. SAVE_AIPP_ATTR(support_rotation, GeAttrValue::BOOL);
  703. }
  704. }
  705. Status AippOp::CreateAippData(const NodePtr &aipp_node) {
  706. GELOGD("Enter add aipp data node process.");
  707. // get previous node, it should be DATA
  708. auto data_node = aipp_node->GetInDataNodes().at(kAippImageInputIndex);
  709. auto data_op_desc = data_node->GetOpDesc();
  710. GE_CHECK_NOTNULL(data_op_desc);
  711. auto ori_data_format = GetAndCheckFormat();
  712. if (ori_data_format != FORMAT_NCHW && ori_data_format != FORMAT_NHWC) {
  713. string format_str = TypeUtils::FormatToSerialString(ori_data_format);
  714. GELOGE(PARAM_INVALID, "when dynamic aipp, input_format must be NCHW or NHWC, but [%s] format is %s",
  715. data_node->GetName().c_str(), format_str.c_str());
  716. string reason = "format must be NCHW or NHWC in dynamic aipp process";
  717. ErrorManager::GetInstance().ATCReportErrMessage("E19014", {"opname", "value", "reason"},
  718. {data_node->GetName(), "format " + format_str, reason});
  719. return PARAM_INVALID;
  720. }
  721. // dynamic aipp shape HWC is not fixed, need to be set -1
  722. int64_t data_shape_n = 0;
  723. // dynamic batch or HW, need acquire N from ATTR_MBATCH_ORIGIN_INPUT_DIMS
  724. if (data_op_desc->HasAttr(ATTR_MBATCH_ORIGIN_INPUT_DIMS)) {
  725. vector<int64_t> origin_input_dims;
  726. (void)AttrUtils::GetListInt(data_op_desc, ATTR_MBATCH_ORIGIN_INPUT_DIMS, origin_input_dims);
  727. if (!origin_input_dims.empty()) {
  728. data_shape_n = origin_input_dims[0];
  729. }
  730. } else {
  731. data_shape_n = data_op_desc->MutableInputDesc(0)->GetShape().GetDim(0);
  732. }
  733. vector<int64_t> dynamic_aipp_linked_data_shape{data_shape_n, kDynamicDim, kDynamicDim, kDynamicDim};
  734. (void)AttrUtils::SetListInt(data_op_desc, ATTR_DYNAMIC_AIPP_INPUT_DIMS, dynamic_aipp_linked_data_shape);
  735. int64_t batch_count = -1;
  736. if (GetDataDimN(data_node, ori_data_format, batch_count) != ge::SUCCESS) {
  737. string error_msg = "Get data_node dims and transfer to nchw_dims failed!";
  738. GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str());
  739. return PARAM_INVALID;
  740. }
  741. if (batch_count <= 0) {
  742. string error_msg = "Batch count[" + std::to_string(batch_count) + "] is invalid, it must positive.";
  743. GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str());
  744. return PARAM_INVALID;
  745. }
  746. int64_t max_dynamic_aipp_size = CalcMaxSize(batch_count);
  747. if (max_dynamic_aipp_size < 0) {
  748. string error_msg = "The dynamic aipp size is not positive";
  749. GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str());
  750. return PARAM_INVALID;
  751. }
  752. GELOGI("Add aipp input data, batch count is %ld, max_dynamic_aipp_size is %ld", batch_count, max_dynamic_aipp_size);
  753. return AddNodeToGraph(aipp_node, max_dynamic_aipp_size);
  754. }
  755. Status AippOp::AddAttrToAippData(const OpDescPtr &aipp_data_op_desc) {
  756. // Add dynamic aipp config to aipp_data
  757. GeAttrValue::NAMED_ATTRS aipp_attr;
  758. ConvertParamToAttr(aipp_attr);
  759. (void)AttrUtils::SetNamedAttrs(aipp_data_op_desc, ATTR_NAME_AIPP, aipp_attr);
  760. (void)AttrUtils::SetStr(aipp_data_op_desc, ATTR_DATA_RELATED_AIPP_MODE, "dynamic_aipp_conf");
  761. // add node name attr to data linked aipp_data, it can be queried by acl.
  762. GE_CHECK_NOTNULL(data_node_linked_aipp);
  763. auto data_op_desc = data_node_linked_aipp->GetOpDesc();
  764. GE_CHECK_NOTNULL(data_op_desc);
  765. (void)AttrUtils::SetStr(data_op_desc, ATTR_DATA_AIPP_DATA_NAME_MAP, aipp_data_op_desc->GetName());
  766. (void)AttrUtils::SetStr(aipp_data_op_desc, ATTR_DATA_AIPP_DATA_NAME_MAP, data_op_desc->GetName());
  767. return SUCCESS;
  768. }
  769. Status AippOp::AddNodeToGraph(const NodePtr &aipp_node, int64_t max_dynamic_aipp_size) {
  770. std::vector<int64_t> input_shape_dim(1, max_dynamic_aipp_size);
  771. GeShape input_shape(input_shape_dim);
  772. // construct input tensor
  773. GeTensorDesc input_tensor(input_shape, FORMAT_ND, DT_UINT8);
  774. TensorUtils::SetReuseInput(input_tensor, false);
  775. TensorUtils::SetSize(input_tensor, max_dynamic_aipp_size);
  776. GE_CHECK_NOTNULL(aipp_node);
  777. const ComputeGraphPtr &graph = aipp_node->GetOwnerComputeGraph();
  778. string node_name;
  779. // First aippdata name should be definite.
  780. if (graph->FindFirstNodeMatchType(AIPPDATA) == nullptr) {
  781. GELOGI("Current graph has no aippdata node, so the name of it must be definite.");
  782. node_name = kDynamicAippData;
  783. } else {
  784. node_name = string(kDynamicAippData) + "_" + aipp_node->GetName();
  785. }
  786. GELOGI("Current add aippdata node name is %s", node_name.c_str());
  787. // new add aipp_data ops for dynamic aipp param input
  788. OpDescPtr op_desc_ptr_data = MakeShared<OpDesc>(node_name, AIPPDATA);
  789. GE_CHECK_NOTNULL(op_desc_ptr_data);
  790. if (AddAttrToAippData(op_desc_ptr_data) != SUCCESS) {
  791. return INTERNAL_ERROR;
  792. }
  793. auto stat1 = op_desc_ptr_data->AddInputDesc(input_tensor);
  794. GeShape output_shape(input_shape_dim);
  795. // construct output tensor
  796. GeTensorDesc output_tensor(output_shape, FORMAT_ND, DT_UINT8);
  797. TensorUtils::SetReuseInput(output_tensor, false);
  798. TensorUtils::SetSize(output_tensor, max_dynamic_aipp_size);
  799. auto stat2 = op_desc_ptr_data->AddOutputDesc(output_tensor);
  800. NodePtr aipp_data_node_ptr = graph->AddNode(op_desc_ptr_data);
  801. GE_CHECK_NOTNULL(aipp_data_node_ptr);
  802. // add node desc for aipp node
  803. auto stat3 = aipp_node->GetOpDesc()->UpdateInputDesc(kAippParamsInputIndex, output_tensor);
  804. if (stat1 != GRAPH_SUCCESS || stat2 != GRAPH_SUCCESS || stat3 != GRAPH_SUCCESS) {
  805. REPORT_CALL_ERROR("E19999", "Add and Update InputDesc to op:%s(%s) failed, index:%d, when AippOp %s",
  806. aipp_node->GetName().c_str(), aipp_node->GetType().c_str(), kAippParamsInputIndex, __FUNCTION__);
  807. GELOGE(INTERNAL_ERROR, "node process desc failed!");
  808. return INTERNAL_ERROR;
  809. }
  810. // aipp_node should have two input data but now tbe only one input
  811. if (GraphUtils::AddEdge(aipp_data_node_ptr->GetOutDataAnchor(kAippDataOutputIndex),
  812. aipp_node->GetInDataAnchor(kAippParamsInputIndex)) != GRAPH_SUCCESS) {
  813. REPORT_INNER_ERROR("E19999", "Add edge between op:%s(%s)(out_index:%u) and op:%s(%s)(in_index:%u) failed "
  814. "when AippOp %s", aipp_data_node_ptr->GetName().c_str(), aipp_data_node_ptr->GetType().c_str(),
  815. kAippDataOutputIndex, aipp_node->GetName().c_str(), aipp_node->GetType().c_str(),
  816. kAippParamsInputIndex, __FUNCTION__);
  817. GELOGE(INTERNAL_ERROR, "Add Anchor anchor between aipp data node and aipp failed!");
  818. return INTERNAL_ERROR;
  819. }
  820. return SUCCESS;
  821. }
  822. } // 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