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ge_aipp_op.cc 47 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, "[Check][Param] Not support data format:%s, node:%s",
  114. TypeUtils::FormatToSerialString(format).c_str(), data_node->GetName().c_str());
  115. return PARAM_INVALID;
  116. }
  117. }
  118. string errormsg = "its shape size must be in range[3,4] which dynamic aipp is linked, "
  119. "maybe this input is not suitable for dynamic aipp";
  120. ErrorManager::GetInstance().ATCReportErrMessage("E10001", {"parameter", "value", "reason"},
  121. {data_node->GetName() + " shape size",
  122. to_string(shape.size()), errormsg});
  123. GELOGE(PARAM_INVALID, "[Check][Param] The shape size of this node [%s] "
  124. "which linked dynamic aipp must be in range[3, 4], but is %zu",
  125. data_node->GetName().c_str(), shape.size());
  126. return PARAM_INVALID;
  127. }
  128. // the batch_count must be more than 0
  129. int64_t CalcMaxSize(int64_t batch_count) {
  130. batch_count--;
  131. if (batch_count > 0) {
  132. if (INT64_MAX / batch_count < static_cast<int64_t>(sizeof(kAippDynamicBatchPara))) {
  133. return -1;
  134. }
  135. }
  136. int64_t size = batch_count * sizeof(kAippDynamicBatchPara);
  137. if (INT64_MAX - static_cast<int64_t>(sizeof(kAippDynamicPara)) < size) {
  138. return -1;
  139. }
  140. return size + sizeof(kAippDynamicPara);
  141. }
  142. Format GetAndCheckFormat() {
  143. switch (GetLocalOmgContext().format) {
  144. case domi::DOMI_TENSOR_NCHW:
  145. return FORMAT_NCHW;
  146. case domi::DOMI_TENSOR_NHWC:
  147. return FORMAT_NHWC;
  148. default:
  149. GELOGE(PARAM_INVALID, "[Check][Param] Unexpected format found %d",
  150. static_cast<int>(GetLocalOmgContext().format));
  151. return FORMAT_ND;
  152. }
  153. }
  154. } // namespace
  155. Status AippOp::Init(domi::AippOpParams *aipp_params) {
  156. aipp_params_ = new (std::nothrow) domi::AippOpParams();
  157. if (aipp_params_ == nullptr) {
  158. REPORT_CALL_ERROR("E19999", "New AippOpParams failed");
  159. GELOGE(FAILED, "[New][AippOpParams] failed");
  160. return FAILED;
  161. }
  162. aipp_params_->CopyFrom(*aipp_params);
  163. return SUCCESS;
  164. }
  165. AippOp::~AippOp() {
  166. if (aipp_params_ != nullptr) {
  167. delete aipp_params_;
  168. aipp_params_ = nullptr;
  169. }
  170. }
  171. Status AippOp::InsertAippToGraph(ComputeGraphPtr &graph, std::string &aippConfigPath, const uint32_t index) {
  172. GE_CHECK_NOTNULL(graph);
  173. NodePtr target_input = nullptr;
  174. std::vector<std::pair<OutDataAnchorPtr, InDataAnchorPtr>> target_edges;
  175. if (this->ConvertRelatedInputNameToRank() != SUCCESS) {
  176. GELOGE(FAILED, "[Call][ConvertRelatedInputNameToRank] failed.");
  177. return FAILED;
  178. }
  179. GE_CHK_STATUS_RET(this->GetTargetPosition(graph, target_input, target_edges), "[Get][TargetPosition] failed");
  180. std::map<OutDataAnchorPtr, NodePtr> out_anchors_to_aipp;
  181. for (auto &out_in_anchors : target_edges) {
  182. auto iter = out_anchors_to_aipp.find(out_in_anchors.first);
  183. if (iter == out_anchors_to_aipp.end()) {
  184. auto aipp = CreateAipp(out_in_anchors.first, aippConfigPath, index);
  185. GE_CHECK_NOTNULL(aipp);
  186. out_anchors_to_aipp[out_in_anchors.first] = aipp;
  187. auto ret = GraphUtils::InsertNodeBetweenDataAnchors(out_in_anchors.first, out_in_anchors.second, aipp);
  188. if (ret != GRAPH_SUCCESS) {
  189. REPORT_CALL_ERROR("E19999", "Insert aipp:%s(%s) node between op:%s(%s) and op:%s:%s failed",
  190. aipp->GetName().c_str(), aipp->GetType().c_str(),
  191. out_in_anchors.first->GetOwnerNode()->GetName().c_str(),
  192. out_in_anchors.first->GetOwnerNode()->GetType().c_str(),
  193. out_in_anchors.second->GetOwnerNode()->GetName().c_str(),
  194. out_in_anchors.second->GetOwnerNode()->GetType().c_str());
  195. GELOGE(INTERNAL_ERROR, "[Insert][Node] %s(%s) between op:%s(%s) and op:%s:%s failed",
  196. aipp->GetName().c_str(), aipp->GetType().c_str(),
  197. out_in_anchors.first->GetOwnerNode()->GetName().c_str(),
  198. out_in_anchors.first->GetOwnerNode()->GetType().c_str(),
  199. out_in_anchors.second->GetOwnerNode()->GetName().c_str(),
  200. out_in_anchors.second->GetOwnerNode()->GetType().c_str());
  201. return INTERNAL_ERROR;
  202. }
  203. // add aipp data if needed
  204. if (GetAippMode() == domi::AippOpParams::dynamic) {
  205. ret = CreateAippData(aipp);
  206. if (ret != SUCCESS) {
  207. GELOGE(INTERNAL_ERROR, "[Create][AippData] for aipp %s data %s failed", aipp->GetName().c_str(),
  208. out_in_anchors.first->GetOwnerNode()->GetName().c_str());
  209. return INTERNAL_ERROR;
  210. }
  211. }
  212. GELOGI("Create aipp %s and insert it to the graph", aipp->GetName().c_str());
  213. } else {
  214. out_in_anchors.second->UnlinkAll();
  215. auto &aipp = iter->second;
  216. auto ret = out_in_anchors.second->LinkFrom(aipp->GetOutDataAnchor(0));
  217. if (ret != GRAPH_SUCCESS) {
  218. REPORT_CALL_ERROR("E19999", "link aipp:%s(%s) to peer op:%s(%s) failed",
  219. aipp->GetName().c_str(), aipp->GetType().c_str(),
  220. out_in_anchors.second->GetOwnerNode()->GetName().c_str(),
  221. out_in_anchors.second->GetOwnerNode()->GetType().c_str());
  222. GELOGE(INTERNAL_ERROR, "[Call][LinkFrom] Failed to link aipp %s to the peer node %s", aipp->GetName().c_str(),
  223. out_in_anchors.second->GetOwnerNode()->GetName().c_str());
  224. return INTERNAL_ERROR;
  225. }
  226. }
  227. }
  228. return SUCCESS;
  229. }
  230. NodePtr AippOp::CreateAipp(const OutDataAnchorPtr &out_anchor,
  231. const std::string &aippConfigPath, const uint32_t &index) {
  232. const auto &node = out_anchor->GetOwnerNode();
  233. std::string current_name = node->GetName() + "_" + std::to_string(out_anchor->GetIdx()) + "_huawei_aipp";
  234. auto aipp_opdesc_ptr = MakeShared<OpDesc>(current_name, AIPP);
  235. if (aipp_opdesc_ptr == nullptr) {
  236. REPORT_CALL_ERROR("E19999", "New OpDesc failed");
  237. GELOGE(OUT_OF_MEMORY, "[New][OpDesc] failed, name %s", current_name.c_str());
  238. return nullptr;
  239. }
  240. // Update attributes
  241. if (AddAippAttrbutes(aipp_opdesc_ptr, aippConfigPath, index) != SUCCESS) {
  242. return nullptr;
  243. }
  244. // Update input desc, the output desc will be flushed when InferShape
  245. auto node_desc = out_anchor->GetOwnerNode()->GetOpDesc();
  246. if (node_desc == nullptr) {
  247. return nullptr;
  248. }
  249. auto opdesc_src_data = node_desc->GetOutputDesc(out_anchor->GetIdx());
  250. if (opdesc_src_data.GetDataType() != DT_FLOAT) {
  251. GELOGW("The datatype of data node %s is not FP32", node_desc->GetName().c_str());
  252. opdesc_src_data.SetDataType(DT_FLOAT);
  253. }
  254. // We must get the TensorDesc from the output anchor on the Data node,
  255. // and update the TensorDesc to the input anchor on the Aipp node.
  256. // Because the InferShape function for the Aipp node needs the input tensor format,
  257. // but the InferFormat process before InferShape can not infer the format
  258. // if the tensor on the Aipp has an unknown shape
  259. if (aipp_opdesc_ptr->UpdateInputDesc(kAippImageInputIndex, opdesc_src_data) != GRAPH_SUCCESS) {
  260. REPORT_CALL_ERROR("E19999", "Update the output desc from node:%s(%s) to aipp:%s(%s) failed",
  261. node_desc->GetName().c_str(), node_desc->GetType().c_str(),
  262. aipp_opdesc_ptr->GetName().c_str(), aipp_opdesc_ptr->GetType().c_str());
  263. GELOGE(INTERNAL_ERROR, "[Call][UpdateInputDesc] Failed to update the output desc from node %s to aipp %s",
  264. node_desc->GetName().c_str(), aipp_opdesc_ptr->GetName().c_str());
  265. return nullptr;
  266. }
  267. return node->GetOwnerComputeGraph()->AddNode(aipp_opdesc_ptr);
  268. }
  269. Status AippOp::AddAippAttrbutes(const OpDescPtr &op_desc, const std::string &aipp_cfg_path, const uint32_t &index) {
  270. GeAttrValue::NAMED_ATTRS aipp_attr;
  271. ConvertParamToAttr(aipp_attr);
  272. GE_CHK_BOOL_RET_STATUS(AttrUtils::SetNamedAttrs(op_desc, ATTR_NAME_AIPP, aipp_attr),
  273. INTERNAL_ERROR, "[Set][NamedAttrs] %s for aipp node:%s failed", ATTR_NAME_AIPP.c_str(),
  274. op_desc->GetName().c_str());
  275. GE_CHK_BOOL_RET_STATUS(AttrUtils::SetStr(op_desc, kAippConfigPath, aipp_cfg_path),
  276. INTERNAL_ERROR, "[Set][Attr] config file path for aipp node:%s failed",
  277. op_desc->GetName().c_str());
  278. std::vector<std::string> empty_names;
  279. GE_CHK_BOOL_RET_STATUS(AttrUtils::SetListStr(op_desc, ATTR_NAME_DATA_DUMP_ORIGIN_OP_NAMES, empty_names),
  280. INTERNAL_ERROR, "[Set][Attr] %s for aipp node:%s failed",
  281. ATTR_NAME_DATA_DUMP_ORIGIN_OP_NAMES.c_str(), op_desc->GetName().c_str());
  282. GE_CHK_BOOL_RET_STATUS(AttrUtils::SetInt(op_desc, kCurrentAippIndex, index),
  283. INTERNAL_ERROR, "[Set][Attr] %s for aipp node:%s failed", kCurrentAippIndex,
  284. op_desc->GetName().c_str());
  285. // add input/output desc
  286. GeTensorDesc tensor;
  287. GE_CHK_GRAPH_STATUS_RET(op_desc->AddInputDesc("images", tensor),
  288. "[Add][InputDesc] images for aipp node:%s failed", op_desc->GetName().c_str());
  289. if (GetAippMode() == domi::AippOpParams::dynamic) {
  290. GE_CHK_GRAPH_STATUS_RET(op_desc->AddOptionalInputDesc("params", tensor),
  291. "[Call][AddOptionalInputDesc] Failed to add params for aipp node:%s",
  292. op_desc->GetName().c_str());
  293. }
  294. GE_CHK_GRAPH_STATUS_RET(op_desc->AddOutputDesc("features", tensor),
  295. "[Add][OutputDesc] features for aipp node:%s failed", op_desc->GetName().c_str());
  296. return SUCCESS;
  297. }
  298. domi::AippOpParams::AippMode AippOp::GetAippMode() { return aipp_params_->aipp_mode(); }
  299. NodePtr AippOp::FindDataByIndex(const ComputeGraphPtr &graph, int rank) {
  300. int64_t data_index = 0;
  301. for (auto &node : graph->GetDirectNode()) {
  302. if (node->GetType() != DATA) {
  303. continue;
  304. }
  305. // For functional multi batch, Skip Data for index.
  306. if (node->GetOpDesc()->HasAttr(ATTR_INSERT_BY_MBATCH)) {
  307. continue;
  308. }
  309. // There is no `index` attribute on the `Data` node when compile in inference scene
  310. // so we can only use the order of all `Data` nodes to infer the data index
  311. if (data_index++ != rank) {
  312. continue;
  313. }
  314. return node;
  315. }
  316. string error_msg = "Can not find the data node by aipp parameter related_input_rank " + to_string(rank);
  317. GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str());
  318. return nullptr;
  319. }
  320. Status AippOp::GetAndCheckTarget(const ComputeGraphPtr &graph, int rank, NodePtr &target,
  321. std::set<uint32_t> &edge_indexes) {
  322. auto data_node = FindDataByIndex(graph, rank);
  323. if (data_node == nullptr) {
  324. GELOGE(PARAM_INVALID, "[Call][FindDataByIndex] Get target input node for rank %d failed", rank);
  325. return PARAM_INVALID;
  326. }
  327. data_node_linked_aipp = data_node;
  328. auto data_opdesc = data_node->GetOpDesc();
  329. GE_CHECK_NOTNULL(data_opdesc);
  330. string set_dt_str;
  331. if (ge::AttrUtils::GetStr(data_opdesc, ATTR_ATC_USER_DEFINE_DATATYPE, set_dt_str)) {
  332. ErrorManager::GetInstance().ATCReportErrMessage("E10034", {"opname"}, {data_opdesc->GetName()});
  333. GELOGE(INTERNAL_ERROR,
  334. "[Get][Attr] This input op [%s] is linked to aipp, can not be set to fp16, "
  335. "please check your atc parameter --insert_op_conf, --input_fp16_nodes.",
  336. data_opdesc->GetName().c_str());
  337. return PARAM_INVALID;
  338. }
  339. // add dynamic or static attr memsage to data
  340. if (GetAippMode() == domi::AippOpParams::static_) {
  341. (void)AttrUtils::SetStr(data_opdesc, ATTR_DATA_RELATED_AIPP_MODE, "static_aipp");
  342. } else if (GetAippMode() == domi::AippOpParams::dynamic) {
  343. (void)AttrUtils::SetStr(data_opdesc, ATTR_DATA_RELATED_AIPP_MODE, "dynamic_aipp");
  344. }
  345. // In scenario AIPP+CONV2D+POOLING, keep the aipp info to Data, since AIPP disappear after subgraph optimize
  346. GeAttrValue::NAMED_ATTRS aipp_attr;
  347. ConvertParamToAttr(aipp_attr);
  348. if (!AttrUtils::SetNamedAttrs(data_opdesc, ATTR_NAME_AIPP, aipp_attr)) {
  349. REPORT_INNER_ERROR("E19999", "Set Attr:%s for op:%s(%s) failed", ATTR_NAME_AIPP.c_str(),
  350. data_opdesc->GetName().c_str(), data_opdesc->GetType().c_str());
  351. GELOGE(INTERNAL_ERROR, "[Set][Attr] %s for op:%s(%s) failed", ATTR_NAME_AIPP.c_str(),
  352. data_opdesc->GetName().c_str(), data_opdesc->GetType().c_str());
  353. return INTERNAL_ERROR;
  354. }
  355. if (aipp_params_->input_edge_idx_size() > 0) {
  356. for (auto edge_index : aipp_params_->input_edge_idx()) {
  357. edge_indexes.insert(edge_index);
  358. }
  359. }
  360. if (!edge_indexes.empty() && (*edge_indexes.rbegin() >= data_node->GetOutDataNodes().size())) {
  361. string error_msg = "The aipp parameter input_edge_idx[" + std::to_string(*edge_indexes.rbegin()) +
  362. "] should be smaller than the target input[" +
  363. std::to_string(data_node->GetOutDataNodes().size()) +"]'s outnodes.";
  364. GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str());
  365. return PARAM_INVALID;
  366. }
  367. target = data_node;
  368. return GetStaticTargetNode(graph, data_node, target);
  369. }
  370. Status AippOp::GetStaticTargetNode(const ComputeGraphPtr &graph, NodePtr &data_node, NodePtr &target) {
  371. if (GetAippMode() != domi::AippOpParams::static_) {
  372. return SUCCESS;
  373. }
  374. std::string related_node_name;
  375. if (AttrUtils::GetStr(data_node->GetOpDesc(), kMbatchSwitchnName, related_node_name)) {
  376. if (related_node_name.empty()) {
  377. REPORT_INNER_ERROR("E19999", "The data node %s has switchn node flag, but the value of attr:%s is empty, "
  378. "check invalid", data_node->GetName().c_str(),
  379. kMbatchSwitchnName);
  380. GELOGE(INTERNAL_ERROR, "[Check][Param] The data node %s has switchn node flag, but the value of attr:%s is empty",
  381. data_node->GetName().c_str(), kMbatchSwitchnName);
  382. return INTERNAL_ERROR;
  383. }
  384. auto switchn = graph->FindNode(related_node_name);
  385. if (switchn == nullptr) {
  386. REPORT_INNER_ERROR("E19999", "The data node %s has switchn node %s, but can not find it on the graph, "
  387. "check invalid", data_node->GetName().c_str(), related_node_name.c_str());
  388. GELOGE(INTERNAL_ERROR, "[Check][Param] The data node %s has switchn node %s, but can not find it on the graph",
  389. data_node->GetName().c_str(), related_node_name.c_str());
  390. return INTERNAL_ERROR;
  391. }
  392. target = switchn;
  393. GELOGI("Multi-batch/image size and static aipp for data %s, "
  394. "the aipp node will be insert after %s instead of origin data node",
  395. data_node->GetName().c_str(), switchn->GetName().c_str());
  396. return SUCCESS;
  397. }
  398. const auto out_anchor = data_node->GetOutDataAnchor(0);
  399. for (const auto &in_anchor : out_anchor->GetPeerInDataAnchors()) {
  400. if (in_anchor == nullptr) {
  401. continue;
  402. }
  403. const auto &case_node = in_anchor->GetOwnerNode();
  404. if (case_node->GetType() == CASE) {
  405. target = case_node;
  406. return SUCCESS;
  407. }
  408. }
  409. return SUCCESS;
  410. }
  411. Status AippOp::ConvertRelatedInputNameToRank() {
  412. GE_CHECK_NOTNULL(aipp_params_);
  413. string related_input_name = aipp_params_->related_input_name();
  414. if (related_input_name.empty()) {
  415. return SUCCESS;
  416. }
  417. std::vector<std::string> data_top_names = domi::GetContext().data_top_names;
  418. GELOGI("Convert name to rank start: data size[%zu]", data_top_names.size());
  419. uint32_t index = 0;
  420. bool convert_flag = false;
  421. for (const auto &data_top_name : data_top_names) {
  422. if (related_input_name == data_top_name) {
  423. aipp_params_->set_related_input_rank(index);
  424. convert_flag = true;
  425. GELOGI("AippOp: rank: %u, top name: %s.", index, data_top_name.c_str());
  426. break;
  427. }
  428. index++;
  429. }
  430. if (!convert_flag) {
  431. string error_msg = "Top name " + related_input_name + "convert rank failed, Please"
  432. " ensure top name in aipp config is the top name of data node.";
  433. GELOGE(PARAM_INVALID, "[Check][InputParam]%s", error_msg.c_str());
  434. REPORT_INPUT_ERROR("E19021", std::vector<std::string>({"reason"}), std::vector<std::string>({error_msg}));
  435. return PARAM_INVALID;
  436. }
  437. return SUCCESS;
  438. }
  439. Status AippOp::GetTargetPosition(ComputeGraphPtr graph, NodePtr &target_input,
  440. std::vector<std::pair<OutDataAnchorPtr, InDataAnchorPtr>> &target_edges) {
  441. GE_CHECK_NOTNULL(graph);
  442. GE_CHECK_NOTNULL(aipp_params_);
  443. std::set<uint32_t> edge_indexes;
  444. const uint32_t related_input_rank = aipp_params_->related_input_rank();
  445. auto ret = GetAndCheckTarget(graph, related_input_rank, target_input, edge_indexes);
  446. if (ret != SUCCESS) {
  447. GELOGE(ret, "[Get][TargetInputNode] for rank %u failed", related_input_rank);
  448. return ret;
  449. }
  450. target_edges.clear();
  451. if (target_input->GetType() != CASE) {
  452. for (OutDataAnchorPtr &src_out : target_input->GetAllOutDataAnchors()) {
  453. auto dst_ins = src_out->GetPeerInDataAnchors();
  454. for (uint32_t i = 0; i < dst_ins.size(); ++i) {
  455. auto dst_in = dst_ins.at(i);
  456. if (edge_indexes.empty() || edge_indexes.count(i) > 0) {
  457. target_edges.emplace_back(src_out, dst_in);
  458. }
  459. }
  460. }
  461. } else {
  462. const auto &func_desc = target_input->GetOpDesc();
  463. for (const auto &name : func_desc->GetSubgraphInstanceNames()) {
  464. const auto &subgraph = graph->GetSubgraph(name);
  465. if (subgraph == nullptr) {
  466. REPORT_INNER_ERROR("E19999", "Subgraph:%s of op:%s(%s) not find in graph:%s, check invalid",
  467. name.c_str(), func_desc->GetName().c_str(), func_desc->GetType().c_str(),
  468. graph->GetName().c_str());
  469. GELOGE(GE_GRAPH_EMPTY_SUBGRAPH, "[Get][Subgraph] failed, Subgraph:%s of op:%s(%s) not find in graph:%s",
  470. name.c_str(), func_desc->GetName().c_str(), func_desc->GetType().c_str(), graph->GetName().c_str());
  471. return GE_GRAPH_EMPTY_SUBGRAPH;
  472. }
  473. auto data_node = FindDataByIndex(subgraph, related_input_rank);
  474. if (data_node == nullptr) {
  475. GELOGE(PARAM_INVALID, "[Get][TargetInputNode] for rank %d failed", related_input_rank);
  476. return PARAM_INVALID;
  477. }
  478. for (OutDataAnchorPtr &src_out : data_node->GetAllOutDataAnchors()) {
  479. auto dst_ins = src_out->GetPeerInDataAnchors();
  480. for (uint32_t i = 0; i < dst_ins.size(); ++i) {
  481. auto dst_in = dst_ins.at(i);
  482. if (edge_indexes.empty() || edge_indexes.count(i) > 0) {
  483. target_edges.emplace_back(src_out, dst_in);
  484. }
  485. }
  486. }
  487. }
  488. }
  489. return SUCCESS;
  490. }
  491. Status AippOp::SetDefaultParams() {
  492. GE_CHECK_NOTNULL(aipp_params_);
  493. const domi::AippOpParams::AippMode aipp_mode = aipp_params_->aipp_mode();
  494. if (aipp_mode == domi::AippOpParams::static_) {
  495. if (aipp_params_->csc_switch()) {
  496. SetCscDefaultValue();
  497. }
  498. SetDtcDefaultValue();
  499. GELOGI("parse aipp params:input_format:%s, csc_switch:%d.",
  500. domi::AippOpParams::InputFormat_Name(aipp_params_->input_format()).c_str(), aipp_params_->csc_switch());
  501. 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(),
  502. aipp_params_->mean_chn_1(), aipp_params_->mean_chn_2(), aipp_params_->mean_chn_3());
  503. GELOGI("parse aipp params:min_chn_0:%f, min_chn_1:%f, min_chn_2:%f.", aipp_params_->min_chn_0(),
  504. aipp_params_->min_chn_1(), aipp_params_->min_chn_2());
  505. GE_IF_BOOL_EXEC(!aipp_params_->crop(), aipp_params_->set_load_start_pos_h(0); aipp_params_->set_load_start_pos_w(0);
  506. aipp_params_->set_crop_size_h(0); aipp_params_->set_crop_size_w(0););
  507. GE_IF_BOOL_EXEC(!aipp_params_->resize(), aipp_params_->set_resize_output_h(0);
  508. aipp_params_->set_resize_output_w(0););
  509. GE_IF_BOOL_EXEC(!aipp_params_->padding(), aipp_params_->set_left_padding_size(0);
  510. aipp_params_->set_right_padding_size(0); aipp_params_->set_top_padding_size(0);
  511. aipp_params_->set_bottom_padding_size(0););
  512. }
  513. return SUCCESS;
  514. }
  515. Status AippOp::ValidateParams() {
  516. GE_CHECK_NOTNULL(aipp_params_);
  517. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->aipp_mode() != domi::AippOpParams::undefined, PARAM_INVALID,
  518. "When insert AIPP op, aipp_mode must be configured as static or dynamic ");
  519. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->var_reci_chn_0_size() <= 1, PARAM_INVALID,
  520. "The parameter var_reci_chn_0 can not be configed repeatedly");
  521. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->var_reci_chn_1_size() <= 1, PARAM_INVALID,
  522. "The parameter var_reci_chn_1 can not be configed repeatedly");
  523. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->var_reci_chn_2_size() <= 1, PARAM_INVALID,
  524. "The parameter var_reci_chn_2 can not be configed repeatedly");
  525. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->var_reci_chn_3_size() <= 1, PARAM_INVALID,
  526. "The parameter var_reci_chn_3 can not be configed repeatedly");
  527. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r0c0_size() <= 1, PARAM_INVALID,
  528. "The parameter matrix_r0c0 can not be configed repeatedly");
  529. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r0c1_size() <= 1, PARAM_INVALID,
  530. "The parameter matrix_r0c1 can not be configed repeatedly");
  531. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r0c2_size() <= 1, PARAM_INVALID,
  532. "The parameter matrix_r0c2 can not be configed repeatedly");
  533. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r1c0_size() <= 1, PARAM_INVALID,
  534. "The parameter matrix_r1c0 can not be configed repeatedly");
  535. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r1c1_size() <= 1, PARAM_INVALID,
  536. "The parameter matrix_r1c1 can not be configed repeatedly");
  537. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r1c2_size() <= 1, PARAM_INVALID,
  538. "The parameter matrix_r1c2 can not be configed repeatedly");
  539. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r2c0_size() <= 1, PARAM_INVALID,
  540. "The parameter matrix_r2c0 can not be configed repeatedly");
  541. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r2c1_size() <= 1, PARAM_INVALID,
  542. "The parameter matrix_r2c1 can not be configed repeatedly");
  543. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->matrix_r2c2_size() <= 1, PARAM_INVALID,
  544. "The parameter matrix_r2c2 can not be configed repeatedly");
  545. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->output_bias_0_size() <= 1, PARAM_INVALID,
  546. "The parameter output_bias_0 can not be configed repeatedly");
  547. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->output_bias_1_size() <= 1, PARAM_INVALID,
  548. "The parameter output_bias_1 can not be configed repeatedly");
  549. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->output_bias_2_size() <= 1, PARAM_INVALID,
  550. "The parameter output_bias_2 can not be configed repeatedly");
  551. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->input_bias_0_size() <= 1, PARAM_INVALID,
  552. "The parameter input_bias_0 can not be configed repeatedly");
  553. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->input_bias_1_size() <= 1, PARAM_INVALID,
  554. "The parameter input_bias_1 can not be configed repeatedly");
  555. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->input_bias_2_size() <= 1, PARAM_INVALID,
  556. "The parameter input_bias_2 can not be configed repeatedly");
  557. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->input_edge_idx_size() <= 1, PARAM_INVALID,
  558. "The parameter input_edge_idx can not be configed repeatedly");
  559. const domi::AippOpParams::AippMode aipp_mode = aipp_params_->aipp_mode();
  560. if (aipp_mode == domi::AippOpParams::dynamic) {
  561. GE_CHK_LOG_AND_ERRORMSG(
  562. aipp_params_->max_src_image_size() > 0, PARAM_INVALID,
  563. "For dynamic AIPP params, max_src_image_size must be set which number should be greater than 0");
  564. } else {
  565. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->input_format() != domi::AippOpParams::UNDEFINED, PARAM_INVALID,
  566. "Input format of AIPP conf is undefined");
  567. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->src_image_size_w() >= 0, PARAM_INVALID,
  568. "Src_image_size_w must not be configed smaller than 0");
  569. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->src_image_size_h() >= 0, PARAM_INVALID,
  570. "Src_image_size_h must not be configed smaller than 0");
  571. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->load_start_pos_w() >= 0, PARAM_INVALID,
  572. "Load_start_pos_w must not be configed smaller than 0");
  573. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->load_start_pos_h() >= 0, PARAM_INVALID,
  574. "Load_start_pos_h must not be configed smaller than 0");
  575. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->crop_size_w() >= 0, PARAM_INVALID,
  576. "Crop_size_w must not be configed smaller than 0");
  577. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->resize_output_w() >= 0, PARAM_INVALID,
  578. "Resize_output_w must not be configed smaller than 0");
  579. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->resize_output_h() >= 0, PARAM_INVALID,
  580. "Resize_output_h must not be configed smaller than 0");
  581. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->left_padding_size() >= 0, PARAM_INVALID,
  582. "Left_padding_size must not be configed smaller than 0");
  583. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->right_padding_size() >= 0, PARAM_INVALID,
  584. "Right_padding_size must not be configed smaller than 0");
  585. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->top_padding_size() >= 0, PARAM_INVALID,
  586. "Top_padding_size must not be configed smaller than 0");
  587. GE_CHK_LOG_AND_ERRORMSG(aipp_params_->bottom_padding_size() >= 0, PARAM_INVALID,
  588. "Bottom_padding_size must not be configed smaller than 0");
  589. }
  590. return SUCCESS;
  591. }
  592. void AippOp::SetCscDefaultValue() {
  593. GE_CHECK_NOTNULL_JUST_RETURN(aipp_params_);
  594. if (aipp_params_->input_format() == domi::AippOpParams::YUV420SP_U8) {
  595. CHECK_FALSE_EXEC(aipp_params_->matrix_r0c0_size() > 0, aipp_params_->add_matrix_r0c0(DEFAULT_MATRIX_R2C0_YUV2RGB));
  596. CHECK_FALSE_EXEC(aipp_params_->matrix_r0c1_size() > 0, aipp_params_->add_matrix_r0c1(DEFAULT_MATRIX_R2C1_YUV2RGB));
  597. CHECK_FALSE_EXEC(aipp_params_->matrix_r0c2_size() > 0, aipp_params_->add_matrix_r0c2(DEFAULT_MATRIX_R2C2_YUV2RGB));
  598. CHECK_FALSE_EXEC(aipp_params_->matrix_r1c0_size() > 0, aipp_params_->add_matrix_r1c0(DEFAULT_MATRIX_R1C0_YUV2RGB));
  599. CHECK_FALSE_EXEC(aipp_params_->matrix_r1c1_size() > 0, aipp_params_->add_matrix_r1c1(DEFAULT_MATRIX_R1C1_YUV2RGB));
  600. CHECK_FALSE_EXEC(aipp_params_->matrix_r1c2_size() > 0, aipp_params_->add_matrix_r1c2(DEFAULT_MATRIX_R1C2_YUV2RGB));
  601. CHECK_FALSE_EXEC(aipp_params_->matrix_r2c0_size() > 0, aipp_params_->add_matrix_r2c0(DEFAULT_MATRIX_R0C0_YUV2RGB));
  602. CHECK_FALSE_EXEC(aipp_params_->matrix_r2c1_size() > 0, aipp_params_->add_matrix_r2c1(DEFAULT_MATRIX_R0C1_YUV2RGB));
  603. CHECK_FALSE_EXEC(aipp_params_->matrix_r2c2_size() > 0, aipp_params_->add_matrix_r2c2(DEFAULT_MATRIX_R0C2_YUV2RGB));
  604. } else {
  605. CHECK_FALSE_EXEC(aipp_params_->matrix_r0c0_size() > 0, aipp_params_->add_matrix_r0c0(DEFAULT_MATRIX_R0C0_RGB2YUV));
  606. CHECK_FALSE_EXEC(aipp_params_->matrix_r0c1_size() > 0, aipp_params_->add_matrix_r0c1(DEFAULT_MATRIX_R0C1_RGB2YUV));
  607. CHECK_FALSE_EXEC(aipp_params_->matrix_r0c2_size() > 0, aipp_params_->add_matrix_r0c2(DEFAULT_MATRIX_R0C2_RGB2YUV));
  608. CHECK_FALSE_EXEC(aipp_params_->matrix_r1c0_size() > 0, aipp_params_->add_matrix_r1c0(DEFAULT_MATRIX_R1C0_RGB2YUV));
  609. CHECK_FALSE_EXEC(aipp_params_->matrix_r1c1_size() > 0, aipp_params_->add_matrix_r1c1(DEFAULT_MATRIX_R1C1_RGB2YUV));
  610. CHECK_FALSE_EXEC(aipp_params_->matrix_r1c2_size() > 0, aipp_params_->add_matrix_r1c2(DEFAULT_MATRIX_R1C2_RGB2YUV));
  611. CHECK_FALSE_EXEC(aipp_params_->matrix_r2c0_size() > 0, aipp_params_->add_matrix_r2c0(DEFAULT_MATRIX_R2C0_RGB2YUV));
  612. CHECK_FALSE_EXEC(aipp_params_->matrix_r2c1_size() > 0, aipp_params_->add_matrix_r2c1(DEFAULT_MATRIX_R2C1_RGB2YUV));
  613. CHECK_FALSE_EXEC(aipp_params_->matrix_r2c2_size() > 0, aipp_params_->add_matrix_r2c2(DEFAULT_MATRIX_R2C2_RGB2YUV));
  614. }
  615. CHECK_FALSE_EXEC(aipp_params_->input_bias_0_size() > 0, aipp_params_->add_input_bias_0(DEFAULT_INPUT_BIAS_0));
  616. CHECK_FALSE_EXEC(aipp_params_->input_bias_1_size() > 0, aipp_params_->add_input_bias_1(DEFAULT_INPUT_BIAS_1));
  617. CHECK_FALSE_EXEC(aipp_params_->input_bias_2_size() > 0, aipp_params_->add_input_bias_2(DEFAULT_INPUT_BIAS_2));
  618. CHECK_FALSE_EXEC(aipp_params_->output_bias_0_size() > 0, aipp_params_->add_output_bias_0(DEFAULT_OUTPUT_BIAS_0));
  619. CHECK_FALSE_EXEC(aipp_params_->output_bias_1_size() > 0, aipp_params_->add_output_bias_1(DEFAULT_OUTPUT_BIAS_1));
  620. CHECK_FALSE_EXEC(aipp_params_->output_bias_2_size() > 0, aipp_params_->add_output_bias_2(DEFAULT_OUTPUT_BIAS_2));
  621. }
  622. void AippOp::SetDtcDefaultValue() {
  623. GE_CHECK_NOTNULL_JUST_RETURN(aipp_params_);
  624. CHECK_FALSE_EXEC(aipp_params_->var_reci_chn_0_size() > 0, aipp_params_->add_var_reci_chn_0(DEFAULT_VAR_RECI_CHN));
  625. GELOGD("var_reci_chn_0 is %f, size is %u.", DEFAULT_VAR_RECI_CHN, aipp_params_->var_reci_chn_0_size());
  626. CHECK_FALSE_EXEC(aipp_params_->var_reci_chn_1_size() > 0, aipp_params_->add_var_reci_chn_1(DEFAULT_VAR_RECI_CHN));
  627. GELOGD("var_reci_chn_1 is %f, size is %u.", DEFAULT_VAR_RECI_CHN, aipp_params_->var_reci_chn_1_size());
  628. CHECK_FALSE_EXEC(aipp_params_->var_reci_chn_2_size() > 0, aipp_params_->add_var_reci_chn_2(DEFAULT_VAR_RECI_CHN));
  629. GELOGD("var_reci_chn_2 is %f, size is %u.", DEFAULT_VAR_RECI_CHN, aipp_params_->var_reci_chn_2_size());
  630. CHECK_FALSE_EXEC(aipp_params_->var_reci_chn_3_size() > 0, aipp_params_->add_var_reci_chn_3(DEFAULT_VAR_RECI_CHN));
  631. GELOGD("var_reci_chn_3 is %f, size is %u.", DEFAULT_VAR_RECI_CHN, aipp_params_->var_reci_chn_3_size());
  632. }
  633. Status AippOp::GenerateOpDesc(OpDescPtr op_desc) {
  634. GE_CHECK_NOTNULL(op_desc);
  635. static std::atomic_long atomic_op_idx(0);
  636. auto op_idx = atomic_op_idx.fetch_add(1);
  637. op_desc->SetName(std::string("aipp_node").append(std::to_string(op_idx)));
  638. op_desc->SetType(AIPP);
  639. // Add two InputDesc, add the second after the first one is added successfully.
  640. if ((op_desc->AddInputDesc(GeTensorDesc()) != GRAPH_SUCCESS) ||
  641. (op_desc->AddInputDesc(GeTensorDesc()) != GRAPH_SUCCESS)) {
  642. REPORT_CALL_ERROR("E19999", "Add input desc into op:%s(%s) failed",
  643. op_desc->GetName().c_str(), op_desc->GetType().c_str());
  644. GELOGE(FAILED, "[Add][InputDesc] into op:%s(%s) failed",
  645. op_desc->GetName().c_str(), op_desc->GetType().c_str());
  646. return FAILED;
  647. }
  648. if (op_desc->AddOutputDesc(GeTensorDesc()) != GRAPH_SUCCESS) {
  649. REPORT_CALL_ERROR("E19999", "Add output desc into op:%s(%s) failed",
  650. op_desc->GetName().c_str(), op_desc->GetType().c_str());
  651. GELOGE(FAILED, "[Add][OutputDesc] into op:%s(%s) failed",
  652. op_desc->GetName().c_str(), op_desc->GetType().c_str());
  653. return FAILED;
  654. }
  655. GeAttrValue::NAMED_ATTRS aipp_attrs;
  656. ConvertParamToAttr(aipp_attrs);
  657. GE_IF_BOOL_EXEC(!AttrUtils::SetNamedAttrs(op_desc, ATTR_NAME_AIPP, aipp_attrs),
  658. REPORT_INNER_ERROR("E19999", "Set Attr:%s to op:%s(%s) failed", ATTR_NAME_AIPP.c_str(),
  659. op_desc->GetName().c_str(), op_desc->GetType().c_str());
  660. GELOGE(FAILED, "[Set][Attr] %s to op:%s(%s) failed", ATTR_NAME_AIPP.c_str(),
  661. op_desc->GetName().c_str(), op_desc->GetType().c_str());
  662. return FAILED);
  663. return SUCCESS;
  664. }
  665. void AippOp::ConvertParamToAttr(GeAttrValue::NAMED_ATTRS &aipp_attrs) {
  666. GE_CHECK_NOTNULL_JUST_RETURN(aipp_params_);
  667. SAVE_AIPP_ATTR(aipp_mode, GeAttrValue::INT);
  668. SAVE_AIPP_ATTR(related_input_rank, GeAttrValue::INT);
  669. if (aipp_params_->aipp_mode() == domi::AippOpParams::static_) {
  670. SAVE_AIPP_ATTR(input_format, GeAttrValue::INT);
  671. SAVE_AIPP_ATTR(csc_switch, GeAttrValue::BOOL);
  672. SAVE_AIPP_ATTR(crop, GeAttrValue::BOOL);
  673. SAVE_AIPP_ATTR(resize, GeAttrValue::BOOL);
  674. SAVE_AIPP_ATTR(load_start_pos_w, GeAttrValue::INT);
  675. SAVE_AIPP_ATTR(load_start_pos_h, GeAttrValue::INT);
  676. SAVE_AIPP_ATTR(crop_size_w, GeAttrValue::INT);
  677. SAVE_AIPP_ATTR(crop_size_h, GeAttrValue::INT);
  678. SAVE_AIPP_ATTR(resize, GeAttrValue::BOOL);
  679. SAVE_AIPP_ATTR(resize_output_w, GeAttrValue::INT);
  680. SAVE_AIPP_ATTR(resize_output_h, GeAttrValue::INT);
  681. SAVE_AIPP_ATTR(padding, GeAttrValue::BOOL);
  682. SAVE_AIPP_ATTR(left_padding_size, GeAttrValue::INT);
  683. SAVE_AIPP_ATTR(right_padding_size, GeAttrValue::INT);
  684. SAVE_AIPP_ATTR(top_padding_size, GeAttrValue::INT);
  685. SAVE_AIPP_ATTR(bottom_padding_size, GeAttrValue::INT);
  686. SAVE_AIPP_ATTR(src_image_size_w, GeAttrValue::INT);
  687. SAVE_AIPP_ATTR(src_image_size_h, GeAttrValue::INT);
  688. SAVE_AIPP_ATTR(cpadding_value, GeAttrValue::FLOAT);
  689. SAVE_AIPP_ATTR(rbuv_swap_switch, GeAttrValue::BOOL);
  690. SAVE_AIPP_ATTR(ax_swap_switch, GeAttrValue::BOOL);
  691. SAVE_AIPP_ATTR(single_line_mode, GeAttrValue::BOOL);
  692. SAVE_AIPP_ATTR(mean_chn_0, GeAttrValue::INT);
  693. SAVE_AIPP_ATTR(mean_chn_1, GeAttrValue::INT);
  694. SAVE_AIPP_ATTR(mean_chn_2, GeAttrValue::INT);
  695. SAVE_AIPP_ATTR(mean_chn_3, GeAttrValue::INT);
  696. SAVE_AIPP_ATTR(min_chn_0, GeAttrValue::FLOAT);
  697. SAVE_AIPP_ATTR(min_chn_1, GeAttrValue::FLOAT);
  698. SAVE_AIPP_ATTR(min_chn_2, GeAttrValue::FLOAT);
  699. SAVE_AIPP_ATTR(min_chn_3, GeAttrValue::FLOAT);
  700. SAVE_AIPP_ATTR_LIST(var_reci_chn_0, GeAttrValue::FLOAT);
  701. SAVE_AIPP_ATTR_LIST(var_reci_chn_1, GeAttrValue::FLOAT);
  702. SAVE_AIPP_ATTR_LIST(var_reci_chn_2, GeAttrValue::FLOAT);
  703. SAVE_AIPP_ATTR_LIST(var_reci_chn_3, GeAttrValue::FLOAT);
  704. SAVE_AIPP_ATTR_LIST(matrix_r0c0, GeAttrValue::INT);
  705. SAVE_AIPP_ATTR_LIST(matrix_r0c1, GeAttrValue::INT);
  706. SAVE_AIPP_ATTR_LIST(matrix_r0c2, GeAttrValue::INT);
  707. SAVE_AIPP_ATTR_LIST(matrix_r1c0, GeAttrValue::INT);
  708. SAVE_AIPP_ATTR_LIST(matrix_r1c1, GeAttrValue::INT);
  709. SAVE_AIPP_ATTR_LIST(matrix_r1c2, GeAttrValue::INT);
  710. SAVE_AIPP_ATTR_LIST(matrix_r2c0, GeAttrValue::INT);
  711. SAVE_AIPP_ATTR_LIST(matrix_r2c1, GeAttrValue::INT);
  712. SAVE_AIPP_ATTR_LIST(matrix_r2c2, GeAttrValue::INT);
  713. SAVE_AIPP_ATTR_LIST(output_bias_0, GeAttrValue::INT);
  714. SAVE_AIPP_ATTR_LIST(output_bias_1, GeAttrValue::INT);
  715. SAVE_AIPP_ATTR_LIST(output_bias_2, GeAttrValue::INT);
  716. SAVE_AIPP_ATTR_LIST(input_bias_0, GeAttrValue::INT);
  717. SAVE_AIPP_ATTR_LIST(input_bias_1, GeAttrValue::INT);
  718. SAVE_AIPP_ATTR_LIST(input_bias_2, GeAttrValue::INT);
  719. } else {
  720. SAVE_AIPP_ATTR(max_src_image_size, GeAttrValue::INT);
  721. SAVE_AIPP_ATTR(support_rotation, GeAttrValue::BOOL);
  722. }
  723. }
  724. Status AippOp::CreateAippData(const NodePtr &aipp_node) {
  725. GELOGD("Enter add aipp data node process.");
  726. // get previous node, it should be DATA
  727. auto data_node = aipp_node->GetInDataNodes().at(kAippImageInputIndex);
  728. auto data_op_desc = data_node->GetOpDesc();
  729. GE_CHECK_NOTNULL(data_op_desc);
  730. auto ori_data_format = GetAndCheckFormat();
  731. if (ori_data_format != FORMAT_NCHW && ori_data_format != FORMAT_NHWC) {
  732. string format_str = TypeUtils::FormatToSerialString(ori_data_format);
  733. GELOGE(PARAM_INVALID, "[Check][Param] when dynamic aipp, input_format must be NCHW or NHWC, but [%s] format is %s",
  734. data_node->GetName().c_str(), format_str.c_str());
  735. string reason = "format must be NCHW or NHWC in dynamic aipp process";
  736. ErrorManager::GetInstance().ATCReportErrMessage("E19014", {"opname", "value", "reason"},
  737. {data_node->GetName(), "format " + format_str, reason});
  738. return PARAM_INVALID;
  739. }
  740. // dynamic aipp shape HWC is not fixed, need to be set -1
  741. int64_t data_shape_n = 0;
  742. // dynamic batch or HW, need acquire N from ATTR_MBATCH_ORIGIN_INPUT_DIMS
  743. if (data_op_desc->HasAttr(ATTR_MBATCH_ORIGIN_INPUT_DIMS)) {
  744. vector<int64_t> origin_input_dims;
  745. (void)AttrUtils::GetListInt(data_op_desc, ATTR_MBATCH_ORIGIN_INPUT_DIMS, origin_input_dims);
  746. if (!origin_input_dims.empty()) {
  747. data_shape_n = origin_input_dims[0];
  748. }
  749. } else {
  750. data_shape_n = data_op_desc->MutableInputDesc(0)->GetShape().GetDim(0);
  751. }
  752. vector<int64_t> dynamic_aipp_linked_data_shape{data_shape_n, kDynamicDim, kDynamicDim, kDynamicDim};
  753. (void)AttrUtils::SetListInt(data_op_desc, ATTR_DYNAMIC_AIPP_INPUT_DIMS, dynamic_aipp_linked_data_shape);
  754. int64_t batch_count = -1;
  755. if (GetDataDimN(data_node, ori_data_format, batch_count) != ge::SUCCESS) {
  756. string error_msg = "Get data_node dims and transfer to nchw_dims failed!";
  757. GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str());
  758. return PARAM_INVALID;
  759. }
  760. if (batch_count <= 0) {
  761. string error_msg = "Batch count[" + std::to_string(batch_count) + "] is invalid, it must positive.";
  762. GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str());
  763. return PARAM_INVALID;
  764. }
  765. int64_t max_dynamic_aipp_size = CalcMaxSize(batch_count);
  766. if (max_dynamic_aipp_size < 0) {
  767. string error_msg = "The dynamic aipp size is not positive";
  768. GE_ERRORLOG_AND_ERRORMSG(PARAM_INVALID, error_msg.c_str());
  769. return PARAM_INVALID;
  770. }
  771. GELOGI("Add aipp input data, batch count is %ld, max_dynamic_aipp_size is %ld", batch_count, max_dynamic_aipp_size);
  772. return AddNodeToGraph(aipp_node, max_dynamic_aipp_size);
  773. }
  774. Status AippOp::AddAttrToAippData(const OpDescPtr &aipp_data_op_desc) {
  775. // Add dynamic aipp config to aipp_data
  776. GeAttrValue::NAMED_ATTRS aipp_attr;
  777. ConvertParamToAttr(aipp_attr);
  778. (void)AttrUtils::SetNamedAttrs(aipp_data_op_desc, ATTR_NAME_AIPP, aipp_attr);
  779. (void)AttrUtils::SetStr(aipp_data_op_desc, ATTR_DATA_RELATED_AIPP_MODE, "dynamic_aipp_conf");
  780. // add node name attr to data linked aipp_data, it can be queried by acl.
  781. GE_CHECK_NOTNULL(data_node_linked_aipp);
  782. auto data_op_desc = data_node_linked_aipp->GetOpDesc();
  783. GE_CHECK_NOTNULL(data_op_desc);
  784. (void)AttrUtils::SetStr(data_op_desc, ATTR_DATA_AIPP_DATA_NAME_MAP, aipp_data_op_desc->GetName());
  785. (void)AttrUtils::SetStr(aipp_data_op_desc, ATTR_DATA_AIPP_DATA_NAME_MAP, data_op_desc->GetName());
  786. return SUCCESS;
  787. }
  788. Status AippOp::AddNodeToGraph(const NodePtr &aipp_node, int64_t max_dynamic_aipp_size) {
  789. std::vector<int64_t> input_shape_dim(1, max_dynamic_aipp_size);
  790. GeShape input_shape(input_shape_dim);
  791. // construct input tensor
  792. GeTensorDesc input_tensor(input_shape, FORMAT_ND, DT_UINT8);
  793. TensorUtils::SetReuseInput(input_tensor, false);
  794. TensorUtils::SetSize(input_tensor, max_dynamic_aipp_size);
  795. GE_CHECK_NOTNULL(aipp_node);
  796. const ComputeGraphPtr &graph = aipp_node->GetOwnerComputeGraph();
  797. string node_name;
  798. // First aippdata name should be definite.
  799. if (graph->FindFirstNodeMatchType(AIPPDATA) == nullptr) {
  800. GELOGI("Current graph has no aippdata node, so the name of it must be definite.");
  801. node_name = kDynamicAippData;
  802. } else {
  803. node_name = string(kDynamicAippData) + "_" + aipp_node->GetName();
  804. }
  805. GELOGI("Current add aippdata node name is %s", node_name.c_str());
  806. // new add aipp_data ops for dynamic aipp param input
  807. OpDescPtr op_desc_ptr_data = MakeShared<OpDesc>(node_name, AIPPDATA);
  808. GE_CHECK_NOTNULL(op_desc_ptr_data);
  809. if (AddAttrToAippData(op_desc_ptr_data) != SUCCESS) {
  810. return INTERNAL_ERROR;
  811. }
  812. auto stat1 = op_desc_ptr_data->AddInputDesc(input_tensor);
  813. GeShape output_shape(input_shape_dim);
  814. // construct output tensor
  815. GeTensorDesc output_tensor(output_shape, FORMAT_ND, DT_UINT8);
  816. TensorUtils::SetReuseInput(output_tensor, false);
  817. TensorUtils::SetSize(output_tensor, max_dynamic_aipp_size);
  818. auto stat2 = op_desc_ptr_data->AddOutputDesc(output_tensor);
  819. NodePtr aipp_data_node_ptr = graph->AddNode(op_desc_ptr_data);
  820. GE_CHECK_NOTNULL(aipp_data_node_ptr);
  821. // add node desc for aipp node
  822. auto stat3 = aipp_node->GetOpDesc()->UpdateInputDesc(kAippParamsInputIndex, output_tensor);
  823. if (stat1 != GRAPH_SUCCESS || stat2 != GRAPH_SUCCESS || stat3 != GRAPH_SUCCESS) {
  824. REPORT_CALL_ERROR("E19999", "Add and Update InputDesc to op:%s(%s) failed, index:%d",
  825. aipp_node->GetName().c_str(), aipp_node->GetType().c_str(), kAippParamsInputIndex);
  826. GELOGE(INTERNAL_ERROR, "[Update][InputDesc] to op:%s(%s) failed, index:%d",
  827. aipp_node->GetName().c_str(), aipp_node->GetType().c_str(), kAippParamsInputIndex);
  828. return INTERNAL_ERROR;
  829. }
  830. // aipp_node should have two input data but now tbe only one input
  831. if (GraphUtils::AddEdge(aipp_data_node_ptr->GetOutDataAnchor(kAippDataOutputIndex),
  832. aipp_node->GetInDataAnchor(kAippParamsInputIndex)) != GRAPH_SUCCESS) {
  833. REPORT_INNER_ERROR("E19999", "Add edge between op:%s(%s)(out_index:%u) and op:%s(%s)(in_index:%u) failed",
  834. aipp_data_node_ptr->GetName().c_str(), aipp_data_node_ptr->GetType().c_str(),
  835. kAippDataOutputIndex, aipp_node->GetName().c_str(), aipp_node->GetType().c_str(),
  836. kAippParamsInputIndex);
  837. GELOGE(INTERNAL_ERROR, "[Add][Edge] between op:%s(%s)(out_index:%u) and op:%s(%s)(in_index:%u) failed",
  838. aipp_data_node_ptr->GetName().c_str(), aipp_data_node_ptr->GetType().c_str(),
  839. kAippDataOutputIndex, aipp_node->GetName().c_str(), aipp_node->GetType().c_str(),
  840. kAippParamsInputIndex);
  841. return INTERNAL_ERROR;
  842. }
  843. return SUCCESS;
  844. }
  845. } // 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