aipp config add related input name and modify proto

ge/client/proto/insert_op.proto

@@ -45,6 +45,9 @@ message AippOpParams {
 	// 标识对模型的第几个输入做AIPP处理，例如模型有两个输入，需要对第2个输入做AIPP，则配置related_input_rank为1。
 	uint32 related_input_rank = 2;
 
+        // related_input_name is optional and the top name of data node which inserts aipp
+        string related_input_name = 6;
+
 	// input_edge_idx参数为可选，类型为整型，配置范围为>=0。
 	// 配置该参数的作用，在于对Data算子不同的输出做不同的AIPP处理，如果该参数没有配置，默认对related_input_rank指定的模型输入的所有输出边做AIPP。
 	// 配置值 <= Data算子输出边的个数。

ge/common/proto/insert_op.proto

@@ -45,6 +45,9 @@ message AippOpParams {
 	// 标识对模型的第几个输入做AIPP处理，例如模型有两个输入，需要对第2个输入做AIPP，则配置related_input_rank为1。
 	uint32 related_input_rank = 2;
 
+        // related_input_name is optional and the top name of data node which inserts aipp
+        string related_input_name = 6;
+
 	// input_edge_idx参数为可选，类型为整型，配置范围为>=0。
 	// 配置该参数的作用，在于对Data算子不同的输出做不同的AIPP处理，如果该参数没有配置，默认对related_input_rank指定的模型输入的所有输出边做AIPP。
 	// 配置值 <= Data算子输出边的个数。

ge/executor/proto/insert_op.proto

@@ -45,6 +45,9 @@ message AippOpParams {
 	// 标识对模型的第几个输入做AIPP处理，例如模型有两个输入，需要对第2个输入做AIPP，则配置related_input_rank为1。
 	uint32 related_input_rank = 2;
 
+        // related_input_name is optional and the top name of data node which inserts aipp
+        string related_input_name = 6;
+
 	// input_edge_idx参数为可选，类型为整型，配置范围为>=0。
 	// 配置该参数的作用，在于对Data算子不同的输出做不同的AIPP处理，如果该参数没有配置，默认对related_input_rank指定的模型输入的所有输出边做AIPP。
 	// 配置值 <= Data算子输出边的个数。

ge/graph/preprocess/insert_op/ge_aipp_op.cc

@@ -183,6 +183,11 @@ Status AippOp::InsertAippToGraph(ComputeGraphPtr &graph, std::string &aippConfig
   GE_CHECK_NOTNULL(graph);
   NodePtr target_input = nullptr;
   std::vector<std::pair<OutDataAnchorPtr, InDataAnchorPtr>> target_edges;
+
+  if (this->ConvertRelatedInputNameToRank() != SUCCESS) {
+    GELOGE(FAILED, "AippOp: convert related input name to rank failed.");
+    return FAILED;
+  }
   GE_CHK_STATUS_RET(this->GetTargetPosition(graph, target_input, target_edges), "Get data nodes position failed");
 
   std::map<OutDataAnchorPtr, NodePtr> out_anchors_to_aipp;
@@ -410,6 +415,38 @@ Status AippOp::GetStaticTargetNode(const ComputeGraphPtr &graph, NodePtr &data_n
 
   return SUCCESS;
 }
+Status AippOp::ConvertRelatedInputNameToRank() {
+  GE_CHECK_NOTNULL(aipp_params_);
+
+  string related_input_name = aipp_params_->related_input_name();
+  if(related_input_name.empty()) {
+    return SUCCESS;
+  }
+
+  std::vector<std::string> data_top_names = domi::GetContext().data_top_names;
+  GELOGI("Convert name to rank start: data size[%zu]", data_top_names.size());
+  uint32_t index = 0;
+  bool convert_flag = false;
+  for (const auto &data_top_name : data_top_names) {
+    if (related_input_name == data_top_name) {
+      aipp_params_->set_related_input_rank(index);
+      convert_flag = true;
+      GELOGI("AippOp: rank: %u, top name: %s.", index, data_top_name.c_str());
+      break;
+    }
+    index++;
+  }
+  if (!convert_flag) {
+    string error_msg = "Top name " + related_input_name + "convert rank failed, Please"
+                       " ensure top name in aipp config is the top name of data node.";
+    ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {error_msg});
+    GELOGE(PARAM_INVALID, "Top name[%s] converts rank failed.", related_input_name.c_str());
+    return PARAM_INVALID;
+  }
+
+  return SUCCESS;
+}
+
 
 Status AippOp::GetTargetPosition(ComputeGraphPtr graph, NodePtr &target_input,
                                  std::vector<std::pair<OutDataAnchorPtr, InDataAnchorPtr>> &target_edges) {

ge/graph/preprocess/insert_op/ge_aipp_op.h

@@ -82,6 +82,7 @@ class AippOp : public InsertOpBase {
   Status AddNodeToGraph(const NodePtr &aipp_node, int64_t max_dynamic_aipp_size);
   Status AddAippAttrbutes(const OpDescPtr &op_desc, const std::string &aipp_cfg_path, const uint32_t &index);
   Status AddAttrToAippData(const OpDescPtr &aipp_data_op_desc);
+  Status ConvertRelatedInputNameToRank();
 
   domi::AippOpParams *aipp_params_ = nullptr;
   ge::NodePtr aipp_node_ = nullptr;

ge/graph/preprocess/insert_op/util_insert_aipp_op.cc

@@ -34,6 +34,7 @@
 #include "graph/utils/op_desc_utils.h"
 #include "graph/utils/tensor_utils.h"
 #include "graph/utils/type_utils.h"
+#include "util_insert_aipp_op.h"
 
 using domi::AippOpParams;
 
@@ -115,22 +116,94 @@ void InsertNewOpUtil::ClearNewOps() {
   }
 }
 
-Status InsertNewOpUtil::CheckPositionNotRepeat() {
+Status InsertNewOpUtil::CheckInputNamePositionNotRepeat() {
+  for (int i = 0; i < insert_op_conf_->aipp_op_size(); i++) {
+    const domi::AippOpParams *item = insert_op_conf_->mutable_aipp_op(i);
+    GE_CHECK_NOTNULL(item);
+
+    for (int j = i + 1; j < insert_op_conf_->aipp_op_size(); j++) {
+      const domi::AippOpParams *another_item = insert_op_conf_->mutable_aipp_op(j);
+      GE_CHECK_NOTNULL(another_item);
+      if (another_item->related_input_name().empty()) {
+        string error_msg = "Can not both set related_input_name and related_input_rank!"
+                           " Please ensure param is the same with the first aipp config(related_input_name).";
+        ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {error_msg});
+        GELOGE(PARAM_INVALID,
+               "Can not both set related_input_rank and related_input_name!"
+               " Please ensure param is the same with the first aipp config(related_input_name).");
+        return PARAM_INVALID;
+      }
+      if (item->related_input_name() == another_item->related_input_name()) {
+        string error_msg = "Can not insert aipp to the same postion! Please ensure related_input_name"
+                           " param is different in different aipp config.";
+        ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {error_msg});
+        GELOGE(PARAM_INVALID,
+               "Can not insert aipp op to the same postion! Please ensure related_input_rank param "
+               "is different in different aipp config.");
+        return PARAM_INVALID;
+      }
+    }
+  }
+
+  return SUCCESS;
+}
+
+Status InsertNewOpUtil::CheckInputRankPositionNoRepeat() {
   for (int i = 0; i < insert_op_conf_->aipp_op_size(); i++) {
     const domi::AippOpParams *item = insert_op_conf_->mutable_aipp_op(i);
+    GE_CHECK_NOTNULL(item);
 
     for (int j = i + 1; j < insert_op_conf_->aipp_op_size(); j++) {
       const domi::AippOpParams *another_item = insert_op_conf_->mutable_aipp_op(j);
-      GE_IF_BOOL_EXEC(item->related_input_rank() == another_item->related_input_rank(),
-                      string errormsg = "Can not insert aipp to the same postion! Please ensure related_input_rank"
-                                        " param is different in different aipp config.";
-                      ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {errormsg});
-                      GELOGE(PARAM_INVALID,
-                             "Can not insert aipp op to the same postion! Please ensure related_input_rank param "
-                             "is different in different aipp config.");
-                      return PARAM_INVALID;);
+      GE_CHECK_NOTNULL(another_item);
+      if (!another_item->related_input_name().empty()) {
+        string error_msg = "Can not both set related_input_rank and related_input_name!"
+                           " Please ensure param is the same with the first aipp config(related_input_rank).";
+        ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {error_msg});
+        GELOGE(PARAM_INVALID,
+               "Can not both set related_input_rank and related_input_name!"
+               " Please ensure param is the same with the first aipp config(related_input_rank).");
+        return PARAM_INVALID;
+      }
+      if (item->related_input_rank() == another_item->related_input_rank()) {
+        string error_msg = "Can not insert aipp to the same postion! Please ensure related_input_rank"
+                          " param is different in different aipp config.";
+        ErrorManager::GetInstance().ATCReportErrMessage("E10043", {"reason"}, {error_msg});
+        GELOGE(PARAM_INVALID,
+               "Can not insert aipp op to the same postion! Please ensure related_input_rank param "
+               "is different in different aipp config.");
+        return PARAM_INVALID;
+      }
     }
   }
+
+  return SUCCESS;
+
+}
+
+Status InsertNewOpUtil::CheckPositionNotRepeat() {
+  GE_CHECK_NOTNULL(insert_op_conf_);
+
+  if (insert_op_conf_->aipp_op_size() <= 1) {
+    GELOGI("Aipp op size[%d] less than 2, no need to check position repeat.", insert_op_conf_->aipp_op_size());
+    return SUCCESS;
+  }
+
+  const domi::AippOpParams *item = insert_op_conf_->mutable_aipp_op(0);
+  GE_CHECK_NOTNULL(item);
+
+  string related_input_name = item->related_input_name();
+  Status ret = FAILED;
+  if (related_input_name.empty()) {
+    ret = CheckInputRankPositionNoRepeat();
+  } else {
+    ret = CheckInputNamePositionNotRepeat();
+  }
+  if (ret != SUCCESS) {
+    GELOGE(FAILED, "Check position not repeat failed.");
+    return FAILED;
+  }
+
   return SUCCESS;
 }
 

ge/graph/preprocess/insert_op/util_insert_aipp_op.h

@@ -51,6 +51,10 @@ class InsertNewOpUtil {
 
   Status GetAippParams(const std::unique_ptr<domi::AippOpParams> &aippParams, const ge::NodePtr &aipp_node);
 
+  Status CheckInputNamePositionNotRepeat();
+
+  Status CheckInputRankPositionNoRepeat();
+
   Status CheckGraph(const ge::ComputeGraphPtr &graph);
 
   InsertNewOpUtil() = default;

ge/offline/proto/insert_op.proto

@@ -45,6 +45,9 @@ message AippOpParams {
 	// 标识对模型的第几个输入做AIPP处理，例如模型有两个输入，需要对第2个输入做AIPP，则配置related_input_rank为1。
 	uint32 related_input_rank = 2;
 
+        // related_input_name is optional and the top name of data node which inserts aipp
+        string related_input_name = 6;
+
 	// input_edge_idx参数为可选，类型为整型，配置范围为>=0。
 	// 配置该参数的作用，在于对Data算子不同的输出做不同的AIPP处理，如果该参数没有配置，默认对related_input_rank指定的模型输入的所有输出边做AIPP。
 	// 配置值 <= Data算子输出边的个数。

ge/proto/insert_op.proto

@@ -45,6 +45,9 @@ message AippOpParams {
 	// 标识对模型的第几个输入做AIPP处理，例如模型有两个输入，需要对第2个输入做AIPP，则配置related_input_rank为1。
 	uint32 related_input_rank = 2;
 
+        // related_input_name is optional and the top name of data node which inserts aipp
+        string related_input_name = 6;
+
 	// input_edge_idx参数为可选，类型为整型，配置范围为>=0。
 	// 配置该参数的作用，在于对Data算子不同的输出做不同的AIPP处理，如果该参数没有配置，默认对related_input_rank指定的模型输入的所有输出边做AIPP。
 	// 配置值 <= Data算子输出边的个数。

ge/session/omg.cc

@@ -1038,6 +1038,7 @@ void UpdateOmgCtxWithParserCtx() {
   domi::GetContext().out_top_names = GetParserContext().out_top_names;
   domi::GetContext().user_out_nodes_top_vec = GetParserContext().user_out_nodes_top_vec;
   domi::GetContext().default_out_nodes = GetParserContext().default_out_nodes;
+  domi::GetContext().data_top_names = GetParserContext().data_top_names;
 }
 
 void UpdateParserCtxWithOmgCtx() {
@@ -1054,5 +1055,6 @@ void UpdateParserCtxWithOmgCtx() {
   GetParserContext().input_nodes_format_map = domi::GetContext().input_nodes_format_map;
   GetParserContext().out_top_names = domi::GetContext().out_top_names;
   GetParserContext().user_out_nodes_top_vec = domi::GetContext().user_out_nodes_top_vec;
+  GetParserContext().data_top_names = domi::GetContext().data_top_names;
 }
 }  // namespace ge

inc/framework/omg/omg_inner_types.h

@@ -100,6 +100,8 @@ struct OmgContext {
   std::vector<std::string> net_out_nodes;
   // net out nodes top names(only caffe has top)
   std::vector<std::string> out_top_names;
+  // net data nodes top names(only caffe has top)
+  std::vector<std::string> data_top_names;
   // preferential format used by the entire network
   domiTensorFormat_t net_format = DOMI_TENSOR_RESERVED;
   domi::FrameworkType type = domi::FRAMEWORK_RESERVED;

inc/framework/omg/parser/parser_inner_ctx.h

@@ -49,6 +49,8 @@ struct ParserContext {
   std::vector<std::string> user_out_nodes_top_vec;
   // net out nodes (where user_out_nodes or leaf nodes)
   std::vector<std::string> net_out_nodes;
+  // net data nodes top names(only caffe has top)
+  std::vector<std::string> data_top_names;
   // net out nodes top names(only caffe has top)
   std::vector<std::string> out_top_names;
   // Whether to use dynamic batch size or dynamic image size
@@ -57,9 +59,12 @@ struct ParserContext {
   domi::domiTensorFormat_t format = domi::DOMI_TENSOR_ND;
   domi::FrameworkType type = domi::FRAMEWORK_RESERVED;
   RunMode run_mode = ONLY_PRE_CHECK;
-  std::string custom_proto_path; // save caffe custom proto path, used by caffe parse
-  std::string caffe_proto_path; // save caffe proto path, used by caffe parse
-  std::string enable_scope_fusion_passes;  // name of the pass that needs to take effect
+  // save caffe custom proto path, used by caffe parse
+  std::string custom_proto_path;
+  // save caffe proto path, used by caffe parse
+  std::string caffe_proto_path;
+  // name of the pass that needs to take effect
+  std::string enable_scope_fusion_passes;
 };
 
 ParserContext &GetParserContext();

metadef

@@ -1 +1 @@
-Subproject commit 1cc55bcae09902b3d158993dd57bfbd1d3337066
+Subproject commit 5d06bc7547189f24195b3cedcb0bfc3d787c80a5

parser

@@ -1 +1 @@
-Subproject commit db4e6070bb2cec01cead264a44ceae07e7f3048e
+Subproject commit 5af5c72fba1315f3d52113a5e88dc618d68e7dbc