update parser code from yellow zone

inc/external/caffe_parser.h

@@ -0,0 +1,32 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef INC_EXTERNAL_ACL_GRAPH_CAFFE_H_
+#define INC_EXTERNAL_ACL_GRAPH_CAFFE_H_
+
+#include <memory>
+#include <string>
+#include <vector>
+
+#include "graph/ge_error_codes.h"
+#include "graph/types.h"
+#include "graph/graph.h"
+
+namespace ge {
+graphStatus aclgrphParseCaffe(const char *model_file, const char *weights_file, ge::Graph &graph);
+}  // namespace ge
+
+#endif  // INC_EXTERNAL_ACL_GRAPH_CAFFE_H_

inc/external/tensorflow_parser.h

@@ -0,0 +1,33 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef INC_EXTERNAL_ACL_PARSER_TENSORFLOW_H_
+#define INC_EXTERNAL_ACL_PARSER_TENSORFLOW_H_
+
+#include <atomic>
+#include <memory>
+#include <string>
+#include <vector>
+
+#include "graph/ge_error_codes.h"
+#include "graph/types.h"
+#include "graph/graph.h"
+
+namespace ge {
+graphStatus aclgrphParseTensorFlow(const char *model_file, ge::Graph &graph);
+}  // namespace ge
+
+#endif  // INC_EXTERNAL_ACL_PARSER_TENSORFLOW_H_

parser/caffe/caffe_custom_parser_adapter.cc

@@ -18,7 +18,7 @@
 #include <memory>
 #include <vector>
 #include "common/debug/log.h"
-#include "common/ge/ge_util.h"
+#include "parser/common/acl_graph_parser_util.h"
 #include "common/util.h"
 #include "framework/common/debug/ge_log.h"
 #include "framework/omg/omg_inner_types.h"
@@ -83,9 +83,10 @@ Status CaffeCustomParserAdapter::ParseWeights(const Message *op_src, ge::NodePtr
   }
 
   bool bias_en = false;
+  bool update_in_turn = (static_cast<int64_t >(op->GetAllInputsSize()) == (layer->bottom_size() + layer->blobs_size()));
   int start_pos = layer->bottom_size();
   for (int i = 0; i < layer->blobs_size(); ++i) {
-    ge::GeTensorPtr weight = ge::MakeShared<ge::GeTensor>();
+    ge::GeTensorPtr weight = ge::parser::MakeShared<ge::GeTensor>();
     GE_CHECK_NOTNULL(weight);
     GE_CHK_STATUS_RET(ConvertWeight(layer->blobs(i), layer->name(), weight), "Convert blobs(%d) for layer %s failed", i,
                       layer->name().c_str());
@@ -120,7 +121,7 @@ Status CaffeCustomParserAdapter::ParseWeights(const Message *op_src, ge::NodePtr
     GE_CHECK_NOTNULL(const_node);
     auto index = start_pos + i;
     auto valid_input_name = op->GetValidInputNameByIndex(static_cast<uint32_t>(index));
-    if (valid_input_name.empty()) {
+    if (update_in_turn || valid_input_name.empty()) {
       if (node->AddLinkFrom(static_cast<const uint32_t &>(index), const_node) != GRAPH_SUCCESS) {
         GELOGE(GRAPH_FAILED, "AddEdge failed of from Node %s output to Node %s input %d", const_node->GetName().c_str(),
                node->GetName().c_str(), index);

parser/caffe/caffe_parser.cc

@@ -22,7 +22,7 @@
 #include <memory>
 #include "parser/common/convert/pb2json.h"
 #include "common/debug/log.h"
-#include "common/ge/ge_util.h"
+#include "parser/common/acl_graph_parser_util.h"
 #include "common/op_map.h"
 #include "common/util/error_manager/error_manager.h"
 #include "common/ge_types.h"
@@ -85,7 +85,7 @@ graphStatus aclgrphParseCaffe(const char *model_file, const char *weights_file,
   (void)acl_graph_parse_util.AclParserInitialize(options);
 
   // Create an empty computegraph
-  ge::ComputeGraphPtr compute_graph = ge::MakeShared<ge::ComputeGraph>("tmpGraph");
+  ge::ComputeGraphPtr compute_graph = ge::parser::MakeShared<ge::ComputeGraph>("tmpGraph");
   GE_CHECK_NOTNULL(compute_graph);
 
   graph = ge::GraphUtils::CreateGraphFromComputeGraph(compute_graph);
@@ -107,6 +107,10 @@ graphStatus aclgrphParseCaffe(const char *model_file, const char *weights_file,
     return ret;
   }
   GELOGI("Weights parse success. graph: %s", graph.GetName().c_str());
+  if (acl_graph_parse_util.SetDefaultOutputNode(graph) != ge::SUCCESS) {
+    GELOGE(ret, "Set graph %s default output node failed.", graph.GetName().c_str());
+    return ge::FAILED;
+  }
   return ge::SUCCESS;
 }
 } // namespace ge
@@ -803,10 +807,6 @@ Status CaffeModelParser::ParseOutputNodeTopInfo(const domi::caffe::NetParameter
 
 Status CaffeModelParser::AddBlobsToMap(const domi::caffe::LayerParameter &layer,
                                        std::map<std::string, std::string> &inplace_blob_name_remapping) {
-  if (layer.type() == ge::parser::NETOUTPUT) {
-    return SUCCESS;
-  }
-
   if (layer.top_size() <= 0) {
     ErrorManager::GetInstance().ATCReportErrMessage("E19011", {"opname"}, {layer.name()});
     GELOGE(FAILED, "The output size of layer %s needs to be greater than zero.", layer.name().c_str());
@@ -1085,41 +1085,13 @@ Status CaffeModelParser::AddTensorDescToOpDesc(ge::OpDescPtr &op_desc, const dom
         "while it's original input num is: %d",
         layer.bottom_size());
   }
-
-  // Netoutput node processing
-  if (op_desc->GetType() == ge::parser::NETOUTPUT) {
-    size_t input_output_tensor_num = 0;
-    if (!ge::GetParserContext().user_out_nodes.empty()) {
-      // User specified output
-      input_output_tensor_num = ge::GetParserContext().user_out_nodes.size();
-    } else {
-      for (auto t_iter = top_blobs_map_.begin(); t_iter != top_blobs_map_.end(); t_iter++) {
-        auto b_iter = bottom_blobs_map_.find(t_iter->first);
-        // Find the output node of the network
-        if (b_iter == bottom_blobs_map_.end()) {
-          input_output_tensor_num += top_blobs_map_[t_iter->first].size();
-        }
-      }
-    }
-    // add tensordesc
-    GELOGD(
-        "Current op type is NETOUTPUT, add additional input&output num: %zu."
-        "while it's original input num is: %d, output num is: %d",
-        input_output_tensor_num, layer.bottom_size(), output_tensor_num);
-    for (size_t i = 0; i < input_output_tensor_num; i++) {
-      ge::GeTensorDesc input_tensor;
-      GE_RETURN_IF_ERROR(op_desc->AddInputDesc(input_tensor));
-      ge::GeTensorDesc output_tensor;
-      GE_RETURN_IF_ERROR(op_desc->AddOutputDesc(output_tensor));
-    }
-  }
   return SUCCESS;
 }
 
 Status CaffeModelParser::AddTensorDescToOpDescByIr(ge::OpDescPtr &op_desc, const domi::caffe::LayerParameter &layer,
                                                    const string &op_type) {
   if (std::find(kAddTensorIrSkipNodes.begin(), kAddTensorIrSkipNodes.end(), op_type) != kAddTensorIrSkipNodes.end()) {
-    op_desc = ge::MakeShared<ge::OpDesc>(layer.name(), op_type);
+    op_desc = ge::parser::MakeShared<ge::OpDesc>(layer.name(), op_type);
     GE_CHECK_NOTNULL(op_desc);
     Status ret = AddTensorDescToOpDesc(op_desc, layer);
     if (ret != SUCCESS) {
@@ -1138,44 +1110,44 @@ Status CaffeModelParser::AddTensorDescToOpDescByIr(ge::OpDescPtr &op_desc, const
   } else {
     op_desc = ge::OpDescUtils::GetOpDescFromOperator(op_factory);
     GE_CHECK_NOTNULL(op_desc);
-    auto valid_size = layer.bottom_size();
-    GELOGI("After GetOpDescFromOperator op[%s] type[%s] have all input size: %zu, caffe_input_size:%d output size: %zu",
+    auto valid_input_size = layer.bottom_size();
+    auto blob_size = layer.blobs_size();
+    GELOGI("After GetOpDescFromOperator op[%s] type[%s] have all input size: %zu, "
+           "caffe_input_size:%d blob_size %d output size: %zu",
            op_desc->GetName().c_str(), op_desc->GetType().c_str(),
-           op_desc->GetAllInputsSize(), valid_size, op_desc->GetOutputsSize());
-    for (int i = 0; i < valid_size; i++) {
+           op_desc->GetAllInputsSize(), valid_input_size,
+           blob_size, op_desc->GetOutputsSize());
+    bool update_in_turn = (static_cast<int64_t >(op_desc->GetAllInputsSize()) == (valid_input_size + blob_size));
+    for (int i = 0; i < valid_input_size; i++) {
       ge::GeTensorDesc input_tensor;
       std::string input_name;
       ge::graphStatus ret = ge::GRAPH_SUCCESS;
-      // Only two case is supported fow now when there are optional inputs
+      // Below cases are supported fow now when there are optional inputs
       // x means optional, o means requierd input
-      // a. ooxxx, layer.bottom_size=number of o and x
-      // b. oxoxoxox, layer.bottom_size=number of o
-      if (static_cast<size_t>(i) >= op_desc->GetInputsSize()) {
-        ret = op_desc->UpdateInputDesc(static_cast<uint32_t>(i), input_tensor);
+      // a. ooxxx, number of o and x>=layer.bottom_size+layer.blobs_size>=number of o
+      // b. oxoxoxox, layer.bottom_size+layer.blobs_size=number of o
+      // c. oxoxoxox, layer.bottom_size+layer.blobs_size=number of o and x
+      if (update_in_turn) {
+        ret = op_desc->UpdateInputDesc(op_desc->GetInputNameByIndex(static_cast<uint32_t>(i)), input_tensor);
       } else {
-        input_name = op_desc->GetValidInputNameByIndex(static_cast<uint32_t>(i));
-        ret = op_desc->UpdateInputDesc(input_name, input_tensor);
-      }
-
-      if (ret != ge::GRAPH_SUCCESS) {
-        GELOGW("op [%s], type[%s], update input(%d) with name %s failed", op_desc->GetName().c_str(),
-               op_desc->GetType().c_str(), i, input_name.c_str());
-      } else {
-        GELOGI("op [%s], type[%s], update input(%d) with name %s success", op_desc->GetName().c_str(),
-               op_desc->GetType().c_str(), i, input_name.c_str());
+        if (static_cast<size_t>(i) >= op_desc->GetInputsSize()) {
+          ret = op_desc->UpdateInputDesc(static_cast<uint32_t>(i), input_tensor);
+        } else {
+          input_name = op_desc->GetValidInputNameByIndex(static_cast<uint32_t>(i));
+          ret = op_desc->UpdateInputDesc(input_name, input_tensor);
+        }
       }
+      GELOGI("op [%s], type[%s], update input(%d) with name %s %s", op_desc->GetName().c_str(),
+             op_desc->GetType().c_str(), i, input_name.c_str(), ret == ge::GRAPH_SUCCESS ? "success" : "failed");
     }
 
     for (int i = 0; i < layer.top_size(); i++) {
       ge::GeTensorDesc output_tensor;
-      ge::graphStatus ret = op_desc->UpdateOutputDesc(op_desc->GetOutputNameByIndex(i), output_tensor);
-      if (ret != ge::GRAPH_SUCCESS) {
-        GELOGW("op [%s], type[%s], update output(%d) with name %s failed", op_desc->GetName().c_str(),
-               op_desc->GetType().c_str(), i, op_desc->GetOutputNameByIndex(i).c_str());
-      } else {
-        GELOGI("op [%s], type[%s], update output(%d) with name %s success", op_desc->GetName().c_str(),
-               op_desc->GetType().c_str(), i, op_desc->GetOutputNameByIndex(i).c_str());
-      }
+      auto ret = op_desc->UpdateOutputDesc(op_desc->GetOutputNameByIndex(static_cast<uint32_t>(i)), output_tensor);
+      GELOGI("op [%s], type[%s], update output(%d) with name %s %s",
+             op_desc->GetName().c_str(), op_desc->GetType().c_str(),
+             i, op_desc->GetOutputNameByIndex(i).c_str(),
+             ret == ge::GRAPH_SUCCESS ? "success" : "failed");
     }
   }
   return SUCCESS;
@@ -1226,6 +1198,12 @@ Status CaffeModelParser::AddEdges(ge::ComputeGraphPtr &graph) {
                           GELOGE(INTERNAL_ERROR, "Add link failed from op[%s] to op[%s].",
                                  top_node_iter->second->GetName().c_str(), bottom_node_iter->second->GetName().c_str());
                           return INTERNAL_ERROR;);
+          auto op_desc = bottom_node_iter->second->GetOpDesc();
+          GE_CHECK_NOTNULL(op_desc);
+          auto out_op_desc = top_node_iter->second->GetOpDesc();
+          GE_CHECK_NOTNULL(out_op_desc);
+          (void) op_desc->UpdateInputDesc((static_cast<uint32_t>(in_archor_ptr->GetIdx())),
+                                          out_op_desc->GetOutputDesc(static_cast<uint32_t>(out_archor_ptr->GetIdx())));
         }
         GE_IF_BOOL_EXEC(top_node_iter == node_map.end(), ErrorManager::GetInstance().ATCReportErrMessage(
                                                              "E11014", {"opname"}, {top_blob_layer_pair.first});
@@ -1264,46 +1242,33 @@ bool CaffeModelParser::IsOutputTop(const string &op_name, const int32_t index) {
   return ret;
 }
 
-Status CaffeModelParser::AddEdgeForUserOutNodes(ge::ComputeGraphPtr &graph) {
-  GE_CHECK_NOTNULL(graph);
-  ge::NodePtr net_output_node = graph->FindFirstNodeMatchType(ge::parser::NETOUTPUT);
-  if (net_output_node == nullptr) {
-    GELOGE(INTERNAL_ERROR, "Can not find netoutput node.");
-    return INTERNAL_ERROR;
-  }
-  uint32_t net_output_num = net_output_node->GetAllInDataAnchorsSize();
+Status CaffeModelParser::AddUserOutNodesTop() {
   int32_t index = 0;
   const std::vector<std::pair<std::string, int32_t>> &user_out_nodes = ge::GetParserContext().user_out_nodes;
+  int net_output_num = user_out_nodes.size();
   for (const auto &out_pair : user_out_nodes) {
-    auto node_iter = node_map.find(out_pair.first);
+    auto layer_iter = layer_tops_map_.find(out_pair.first);
     GELOGI("Add to output, node name: %s", out_pair.first.c_str());
-    if (node_iter != node_map.end()) {
-      if ((static_cast<uint32_t>(out_pair.second) >= node_iter->second->GetAllOutDataAnchorsSize()) ||
-          (static_cast<uint32_t>(index) >= net_output_num)) {
+    if (layer_iter != layer_tops_map_.end()) {
+      if (static_cast<uint32_t>(out_pair.second) >= (layer_iter->second).size()) {
         ErrorManager::GetInstance().ATCReportErrMessage(
             "E11016", {"opname", "outputindex", "totlaloutputindex", "inputindex", "totlalinputindex"},
             {out_pair.first.c_str(), std::to_string(out_pair.second),
-             std::to_string(node_iter->second->GetAllOutDataAnchorsSize()), std::to_string(index),
+             std::to_string((layer_iter->second).size()), std::to_string(index),
              std::to_string(net_output_num)});
         GELOGE(INTERNAL_ERROR,
                "Add op %s to NetOutput faild, current node output index:%d should < %u. NetOutput"
                "input_index:%d should < %u.",
-               out_pair.first.c_str(), out_pair.second, node_iter->second->GetAllOutDataAnchorsSize(), index,
+               out_pair.first.c_str(), out_pair.second, (layer_iter->second).size(), index,
                net_output_num);
         return INTERNAL_ERROR;
       }
-      GELOGD("Start add edge for user out node: From %s:%d To %s:%d.", node_iter->second->GetName().c_str(),
-             out_pair.second, net_output_node->GetName().c_str(), index);
-      ge::OutDataAnchorPtr out_archor_ptr = node_iter->second->GetOutDataAnchor(out_pair.second);
-      GE_CHECK_NOTNULL(out_archor_ptr);
-      ge::InDataAnchorPtr in_archor_ptr = net_output_node->GetInDataAnchor(index);
-      GE_CHECK_NOTNULL(in_archor_ptr);
-      if (ge::GraphUtils::AddEdge(out_archor_ptr, in_archor_ptr) != ge::GRAPH_SUCCESS) {
-        ErrorManager::GetInstance().ATCReportErrMessage("E11013", {"opname1", "opname2"},
-                                                        {node_iter->second->GetName(), net_output_node->GetName()});
-        GELOGE(INTERNAL_ERROR, "Add link failed from op[%s] to op[%s].", node_iter->second->GetName().c_str(),
-               net_output_node->GetName().c_str());
-        return INTERNAL_ERROR;
+
+      string top_name = layer_iter->second[out_pair.second];
+      auto top_node_iter = node_map.find(out_pair.first);
+      if (top_node_iter != node_map.end()) {
+        ge::GetParserContext().out_top_names.push_back(top_name);
+        GELOGI("The top of out node [%s] is [%s]", out_pair.first.c_str(), top_name.c_str());
       }
       ++index;
     } else {
@@ -1315,13 +1280,7 @@ Status CaffeModelParser::AddEdgeForUserOutNodes(ge::ComputeGraphPtr &graph) {
   return SUCCESS;
 }
 
-Status CaffeModelParser::AddEdge4Output(const domi::caffe::NetParameter &proto_message, ge::ComputeGraphPtr &graph) {
-  GE_CHECK_NOTNULL(graph);
-  ge::NodePtr node = graph->FindFirstNodeMatchType(ge::parser::NETOUTPUT);
-
-  GE_RETURN_WITH_LOG_IF_FALSE(node != nullptr, "Net without output, some phase failed in front.");
-
-  int32_t index = 0;
+Status CaffeModelParser::AddOutputTop(const domi::caffe::NetParameter &proto_message) {
   for (int32_t i = 0; i < proto_message.layer_size(); i++) {
     const domi::caffe::LayerParameter &layer = proto_message.layer(i);
 
@@ -1331,6 +1290,7 @@ Status CaffeModelParser::AddEdge4Output(const domi::caffe::NetParameter &proto_m
 
     for (int i = 0; i < layer.top_size(); i++) {
       string top = layer.top(i);
+      string top_origin = top;
       // Handling 'inplace' scenarios
       if (IsInplaceTopBlob(layer, top)) {
         top = RemapTopNameByLayer(layer, top, i);
@@ -1352,21 +1312,9 @@ Status CaffeModelParser::AddEdge4Output(const domi::caffe::NetParameter &proto_m
       auto top_node_iter = node_map.find(layer.name());
       GELOGI("output in top_blob: %s", layer.name().c_str());
       if (top_node_iter != node_map.end()) {
-        // add edge
-        // Output node, output index, input node, input index
-        GELOGD("Start add edge for out node: From %s:%d To %s:%d.", top_node_iter->second->GetName().c_str(), i,
-               node->GetName().c_str(), index);
-        ge::OutDataAnchorPtr out_archor_ptr = top_node_iter->second->GetOutDataAnchor(i);
-        GE_CHECK_NOTNULL(out_archor_ptr);
-        ge::InDataAnchorPtr in_archor_ptr = node->GetInDataAnchor(index);
-        GE_CHECK_NOTNULL(in_archor_ptr);
-        GE_IF_BOOL_EXEC(ge::GraphUtils::AddEdge(out_archor_ptr, in_archor_ptr) != ge::GRAPH_SUCCESS,
-                        ErrorManager::GetInstance().ATCReportErrMessage(
-                            "E11013", {"opname1", "opname2"}, {top_node_iter->second->GetName(), node->GetName()});
-                        GELOGE(INTERNAL_ERROR, "Add link failed from op[%s] to to op[%s].",
-                               top_node_iter->second->GetName().c_str(), node->GetName().c_str());
-                        return INTERNAL_ERROR;);
-        index++;
+        ge::GetParserContext().out_top_names.push_back(top_origin);
+        ge::GetParserContext().default_out_nodes.push_back(std::make_pair(layer.name(), (int32_t)i));
+        GELOGI("The top of out node [%s] is [%s]", layer.name().c_str(), top_origin.c_str());
       }
     }
   }
@@ -1480,12 +1428,6 @@ Status CaffeModelParser::ParseFromMemory(const char *data, uint32_t size, ge::Co
   CHECK_FALSE_EXEC(ParseInput(proto_message, input_data_flag) == SUCCESS, has_error = true;
                    GELOGE(FAILED, "ParseInput ret fail."));
 
-  // build output layer
-  domi::caffe::LayerParameter *layer = proto_message.add_layer();
-  GE_CHECK_NOTNULL(layer);
-  layer->set_name(graph->GetName() + "_" + ge::parser::NODE_NAME_NET_OUTPUT);
-  layer->set_type(ge::parser::NETOUTPUT);
-
   int32_t layer_count = proto_message.layer_size();
   std::map<std::string, std::string> inplace_blob_name_remapping;
   // Map of operator name and occurrence times
@@ -1551,9 +1493,9 @@ Status CaffeModelParser::ParseFromMemory(const char *data, uint32_t size, ge::Co
   GE_RETURN_WITH_LOG_IF_ERROR(AddEdges(graph), "Caffe parser add edges fail.");
 
   if (!(ge::GetParserContext().user_out_nodes.empty())) {
-    GE_RETURN_WITH_LOG_IF_ERROR(AddEdgeForUserOutNodes(graph), "Caffe parser add edges for user out nodes failed.");
+    GE_RETURN_WITH_LOG_IF_ERROR(AddUserOutNodesTop(), "Caffe parser add top_name for user out nodes failed.");
   } else {
-    GE_RETURN_WITH_LOG_IF_ERROR(AddEdge4Output(proto_message, graph), "Caffe parser add edges for output fail.");
+    GE_RETURN_WITH_LOG_IF_ERROR(AddOutputTop(proto_message), "Caffe parser add top_name for output fail.");
   }
   GE_RETURN_WITH_LOG_IF_ERROR(graph->TopologicalSorting(), "Caffe parser call graph topo sort fail.");
 
@@ -1655,12 +1597,6 @@ Status CaffeModelParser::Parse(const char *model_path, ge::ComputeGraphPtr &grap
   CHECK_FALSE_EXEC(ParseInput(proto_message, input_data_flag) == SUCCESS, has_error = true;
                    GELOGE(FAILED, "ParseInput ret fail."));
 
-  // build output layer
-  domi::caffe::LayerParameter *layer = proto_message.add_layer();
-  GE_CHECK_NOTNULL(layer);
-  layer->set_name(graph->GetName() + "_" + ge::parser::NODE_NAME_NET_OUTPUT);
-  layer->set_type(ge::parser::NETOUTPUT);
-
   int32_t layer_count = proto_message.layer_size();
 
   if (!ge::GetParserContext().user_out_nodes_top_vec.empty()) {
@@ -1733,12 +1669,11 @@ Status CaffeModelParser::Parse(const char *model_path, ge::ComputeGraphPtr &grap
   GE_RETURN_WITH_LOG_IF_ERROR(AddEdges(graph), "Caffe parser add edges fail.");
 
   if (!(ge::GetParserContext().user_out_nodes.empty())) {
-    GE_RETURN_WITH_LOG_IF_ERROR(AddEdgeForUserOutNodes(graph), "Caffe parser add edges for user out nodes failed.");
+    GE_RETURN_WITH_LOG_IF_ERROR(AddUserOutNodesTop(), "Caffe parser add top_name for user out nodes failed.");
   } else {
-    GE_RETURN_WITH_LOG_IF_ERROR(AddEdge4Output(proto_message, graph), "Caffe parser add edges for output fail.");
+    GE_RETURN_WITH_LOG_IF_ERROR(AddOutputTop(proto_message), "Caffe parser add top_name for output fail.");
   }
   GE_RETURN_WITH_LOG_IF_ERROR(graph->TopologicalSorting(), "Caffe parser call graph topo sort fail.");
-  GE_RETURN_WITH_LOG_IF_ERROR(GetLeafNodeTops(graph), "Caffe parser get out nodes top names failed.");
 
   auto nodes = graph->GetDirectNode();
   GELOGI("graph node size = %zu.", nodes.size());
@@ -2449,27 +2384,6 @@ Status CaffeWeightsParser::ConvertNetParameter(const NetParameter &param, ge::Co
   return SUCCESS;
 }
 
-Status CaffeModelParser::GetLeafNodeTops(ge::ComputeGraphPtr &graph) {
-  auto netout = graph->FindFirstNodeMatchType(ge::parser::NETOUTPUT);
-  GE_CHECK_NOTNULL(netout);
-  for (const auto &in_anchor : netout->GetAllInDataAnchors()) {
-    auto peer_out_data_anchor = in_anchor->GetPeerOutAnchor();
-    GE_CHECK_NOTNULL(peer_out_data_anchor);
-    auto peer_out_data_node = peer_out_data_anchor->GetOwnerNode();
-    GE_CHECK_NOTNULL(peer_out_data_node);
-    int idx = peer_out_data_anchor->GetIdx();
-    string node_name = peer_out_data_node->GetName();
-    auto layer_iter = layer_tops_map_.find(node_name);
-    if (layer_iter != layer_tops_map_.end()) {
-      ge::GetParserContext().out_top_names.push_back(layer_iter->second[idx]);
-      GELOGI("The top of out node [%s] is [%s]", node_name.c_str(), layer_iter->second[idx].c_str());
-    } else {
-      GELOGW("The out node [%s] can not find its top.", node_name.c_str());
-    }
-  }
-  return SUCCESS;
-}
-
 Status CaffeModelParser::ParseProto(const google::protobuf::Message *proto, ge::ComputeGraphPtr &graph) {
   return SUCCESS;
 }

parser/caffe/caffe_parser.h

@@ -279,12 +279,12 @@ class CaffeModelParser : public domi::ModelParser {
 
   /**
    * @ingroup domi_omg
-   * @brief Add edge information to graph
-   * @param [in|out] graph graph for saving model information
+   * @brief Add top name information to graph
+   * @param [in|out] proto_message
    * @return SUCCESS add successfully
    * @return FAILED add failed
    */
-  Status AddEdge4Output(const domi::caffe::NetParameter &proto_message, ge::ComputeGraphPtr &graph);
+  Status AddOutputTop(const domi::caffe::NetParameter &proto_message);
 
   /**
    * @ingroup domi_omg
@@ -324,7 +324,7 @@ class CaffeModelParser : public domi::ModelParser {
   Status AddTensorDescToOpDescByIr(ge::OpDescPtr &op_desc, const domi::caffe::LayerParameter &layer,
                                    const string &op_type);
 
-  Status AddEdgeForUserOutNodes(ge::ComputeGraphPtr &graph);
+  Status AddUserOutNodesTop();
 
   std::string RemapTopNameByLayer(const domi::caffe::LayerParameter &layer, const std::string &top_name, int index);
 
@@ -335,8 +335,6 @@ class CaffeModelParser : public domi::ModelParser {
   Status ParseOpParam(const domi::caffe::LayerParameter &layer, ge::OpDescPtr &op,
                       std::shared_ptr<ge::OpParser> &op_parser);
 
-  Status GetLeafNodeTops(ge::ComputeGraphPtr &graph);
-
   void SaveOrigionLayerTops(domi::caffe::LayerParameter &layer);
 
   Status ReorderInput(domi::caffe::NetParameter &net);

parser/caffe/caffe_reshape_parser.cc

@@ -17,7 +17,7 @@
 #include "parser/caffe/caffe_reshape_parser.h"
 #include <vector>
 #include "common/debug/log.h"
-#include "common/ge/ge_util.h"
+#include "parser/common/acl_graph_parser_util.h"
 #include "common/op/op_parser_util.h"
 #include "common/util.h"
 #include "framework/common/debug/ge_log.h"
@@ -109,7 +109,7 @@ Status CaffeReshapeParser::AddConstInput(ge::NodePtr &node) {
   }
 
   // construct GeTensorPtr
-  ge::GeTensorPtr constTensor = ge::MakeShared<ge::GeTensor>();
+  ge::GeTensorPtr constTensor = ge::parser::MakeShared<ge::GeTensor>();
   GE_CHECK_NOTNULL(constTensor);
   constTensor->SetTensorDesc(const_desc);
 

parser/caffe/proto/ge_ir.proto

@@ -1,190 +1,190 @@
-syntax = "proto3";
-
-package ge.proto;
-
-enum DataType
-{
-    DT_UNDEFINED = 0;  // Used to indicate a DataType field has not been set.
-    DT_FLOAT     = 1;  // float type
-    DT_FLOAT16   = 2;  // fp16 type
-    DT_INT8      = 3;  // int8 type
-    DT_UINT8     = 4;  // uint8 type
-    DT_INT16     = 5;  // int16 type
-    DT_UINT16    = 6;  // uint16 type
-    DT_INT32     = 7;  //
-    DT_INT64     = 8;  // int64 type
-    DT_UINT32    = 9;  // unsigned int32
-    DT_UINT64    = 10;  // unsigned int64
-    DT_BOOL      = 11;  // bool type
-    DT_DOUBLE    = 12; // double type
-    DT_STRING = 13;            // string type
-    DT_DUAL_SUB_INT8 = 14;    /**< dual output int8 type */
-    DT_DUAL_SUB_UINT8 = 15;    /**< dual output uint8 type */
-    DT_COMPLEX64 = 16;         // complex64 type
-    DT_COMPLEX128 = 17;        // complex128 type
-    DT_QINT8 = 18;             // qint8 type
-    DT_QINT16 = 19;            // qint16 type
-    DT_QINT32 = 20;            // qint32 type
-    DT_QUINT8 = 21;            // quint8 type
-    DT_QUINT16 = 22;           // quint16 type
-    DT_RESOURCE  = 23;         // resource type
-    DT_STRING_REF = 24;        // string_ref type
-    DT_DUAL      = 25;              /**< dual output type */
-}
-
-message AttrDef
-{
-    message ListValue
-    {
-        enum ListValueType{
-          VT_LIST_NONE = 0;
-          VT_LIST_STRING = 1;
-          VT_LIST_INT = 2;
-          VT_LIST_FLOAT = 3;
-          VT_LIST_BOOL = 4;
-          VT_LIST_BYTES = 5;
-          VT_LIST_TENSOR_DESC = 6;
-          VT_LIST_TENSOR = 7;
-          VT_LIST_GRAPH = 8;
-          VT_LIST_NAMED_ATTRS = 9;
-          VT_LIST_DATA_TYPE = 10;
-        }
-        repeated bytes s             = 2;                    // "list(string)"
-        repeated int64 i             = 3;  // "list(int)"
-        repeated float f             = 4;   // "list(float)"
-        repeated bool  b             = 5;  // "list(bool)"
-        repeated bytes bt            = 7;
-        repeated TensorDescriptor td = 8;
-        repeated TensorDef t         = 9;
-        repeated GraphDef g          = 10;
-	    repeated NamedAttrs na       = 11;
-	    repeated int64 dt            = 12; // list ge::DataType
-
-	    ListValueType val_type       = 20;
-    }
-
-    message ListListInt{
-        message ListInt{
-            repeated int64 list_i             = 1; // list int
-        }
-        repeated ListInt list_list_i             = 1; // list list int
-    }
-
-    oneof value
-    {
-        bytes            s    = 2;  // "string"
-        int64            i    = 3;  // "int"
-        float            f    = 4;  // "float"
-        bool             b    = 5;  // "bool"
-        bytes            bt   = 7;
-        ListValue        list = 1;   // any "list(...)"
-        NamedAttrs       func = 10;  // Used to support attr nesting
-        TensorDescriptor td   = 11;  // GeTensorDesc type
-        TensorDef        t    = 12;  // GeTensor type
-        GraphDef         g    = 13;  // Graph type
-        ListListInt      list_list_int  = 14;  // List List Int type
-        int64            dt   = 15; // ge::DataType
-    }
-}
-
-// A list of attr names and their values. The whole list is attached
-// with a string name.  E.g., MatMul[T=float].
-message NamedAttrs
-{
-    string               name = 1;
-    map<string, AttrDef> attr = 2;
-}
-
-// Shape / dimension description, using row-major order
-message ShapeDef
-{
-    repeated int64 dim = 1;  // Size of each dimension
-}
-
-// Multidimensional data description
-message TensorDescriptor
-{
-    string   name   = 1;  // Optional parameter, tensor name
-
-    DataType dtype  = 2;  // tensor datatype
-    ShapeDef shape  = 3;  // Shape / dimension
-    string   layout = 4;  // Tensor format, eg: "NCHW", "NHWC", "CHW", "ND"
-
-    bool has_out_attr = 9;
-    int64 size = 10;
-    int64 weight_size = 11;
-    bool reuse_input = 12;
-    bool output_tensor = 13;
-    string device_type = 14;
-    bool input_tensor =15;
-    int64 real_dim_cnt = 16;
-    int64 reuse_input_index = 17;
-    int64 data_offset = 18;
-    int64 cmps_size = 19;
-    string cmps_tab = 20;
-    int64 cmps_tab_offset = 21;
-
-	map<string, AttrDef> attr = 5;  // Set of extra parameter fields
-}
-
-// GeTensor definition
-message TensorDef
-{
-    TensorDescriptor desc = 1;  // Tensor description
-    bytes            data = 2;  // Tensor data
-}
-
-
-// Operator description
-message OpDef
-{
-    string name = 1;  // name
-    string type = 2;  // type
-
-    repeated string input = 5;  // input original op name + outgoing index. op_name：index
-
-    map<string, AttrDef> attr = 10;  // Set of operator parameter fields
-
-    bool has_out_attr = 20;
-    int64 id = 21;
-    int64 stream_id =22;
-    repeated string input_name = 23;
-    repeated string src_name = 24;
-    repeated int64 src_index = 25;
-    repeated string dst_name = 26;
-    repeated int64 dst_index = 27;
-    repeated int64 input_i = 28;
-    repeated int64 output_i = 29;
-    repeated int64 workspace = 30;
-    repeated int64 workspace_bytes = 31;
-    repeated bool is_input_const = 32;
-    repeated TensorDescriptor input_desc = 33;
-    repeated TensorDescriptor output_desc = 34;
-    repeated string subgraph_name = 35;
-}
-
-// Graph definition
-message GraphDef
-{
-    string name   = 1;   //  name
-
-    repeated string input  = 4;  // Graph input
-    repeated string output = 5;  // Graph output
-
-    repeated OpDef op      = 6;  // List of operators
-
-	map<string, AttrDef> attr = 11;  // Extended field
-}
-
-// model definition
-message ModelDef
-{
-	string name         = 1;  // name
-	uint32 version      = 2;  // IR Proto verion
-	string custom_version = 3;  // User model version number, passed in by user
-
-    repeated GraphDef graph = 7;  // Graph definition，graph[0] represents the main diagram in modeldef
-
-    map<string, AttrDef> attr = 11;  // Extended field
-}
-
+syntax = "proto3";
+
+package ge.proto;
+
+enum DataType
+{
+    DT_UNDEFINED = 0;  // Used to indicate a DataType field has not been set.
+    DT_FLOAT     = 1;  // float type
+    DT_FLOAT16   = 2;  // fp16 type
+    DT_INT8      = 3;  // int8 type
+    DT_UINT8     = 4;  // uint8 type
+    DT_INT16     = 5;  // int16 type
+    DT_UINT16    = 6;  // uint16 type
+    DT_INT32     = 7;  //
+    DT_INT64     = 8;  // int64 type
+    DT_UINT32    = 9;  // unsigned int32
+    DT_UINT64    = 10;  // unsigned int64
+    DT_BOOL      = 11;  // bool type
+    DT_DOUBLE    = 12; // double type
+    DT_STRING = 13;            // string type
+    DT_DUAL_SUB_INT8 = 14;    /**< dual output int8 type */
+    DT_DUAL_SUB_UINT8 = 15;    /**< dual output uint8 type */
+    DT_COMPLEX64 = 16;         // complex64 type
+    DT_COMPLEX128 = 17;        // complex128 type
+    DT_QINT8 = 18;             // qint8 type
+    DT_QINT16 = 19;            // qint16 type
+    DT_QINT32 = 20;            // qint32 type
+    DT_QUINT8 = 21;            // quint8 type
+    DT_QUINT16 = 22;           // quint16 type
+    DT_RESOURCE  = 23;         // resource type
+    DT_STRING_REF = 24;        // string_ref type
+    DT_DUAL      = 25;              /**< dual output type */
+}
+
+message AttrDef
+{
+    message ListValue
+    {
+        enum ListValueType{
+          VT_LIST_NONE = 0;
+          VT_LIST_STRING = 1;
+          VT_LIST_INT = 2;
+          VT_LIST_FLOAT = 3;
+          VT_LIST_BOOL = 4;
+          VT_LIST_BYTES = 5;
+          VT_LIST_TENSOR_DESC = 6;
+          VT_LIST_TENSOR = 7;
+          VT_LIST_GRAPH = 8;
+          VT_LIST_NAMED_ATTRS = 9;
+          VT_LIST_DATA_TYPE = 10;
+        }
+        repeated bytes s             = 2;                    // "list(string)"
+        repeated int64 i             = 3;  // "list(int)"
+        repeated float f             = 4;   // "list(float)"
+        repeated bool  b             = 5;  // "list(bool)"
+        repeated bytes bt            = 7;
+        repeated TensorDescriptor td = 8;
+        repeated TensorDef t         = 9;
+        repeated GraphDef g          = 10;
+	    repeated NamedAttrs na       = 11;
+	    repeated int64 dt            = 12; // list ge::DataType
+
+	    ListValueType val_type       = 20;
+    }
+
+    message ListListInt{
+        message ListInt{
+            repeated int64 list_i             = 1; // list int
+        }
+        repeated ListInt list_list_i             = 1; // list list int
+    }
+
+    oneof value
+    {
+        bytes            s    = 2;  // "string"
+        int64            i    = 3;  // "int"
+        float            f    = 4;  // "float"
+        bool             b    = 5;  // "bool"
+        bytes            bt   = 7;
+        ListValue        list = 1;   // any "list(...)"
+        NamedAttrs       func = 10;  // Used to support attr nesting
+        TensorDescriptor td   = 11;  // GeTensorDesc type
+        TensorDef        t    = 12;  // GeTensor type
+        GraphDef         g    = 13;  // Graph type
+        ListListInt      list_list_int  = 14;  // List List Int type
+        int64            dt   = 15; // ge::DataType
+    }
+}
+
+// A list of attr names and their values. The whole list is attached
+// with a string name.  E.g., MatMul[T=float].
+message NamedAttrs
+{
+    string               name = 1;
+    map<string, AttrDef> attr = 2;
+}
+
+// Shape / dimension description, using row-major order
+message ShapeDef
+{
+    repeated int64 dim = 1;  // Size of each dimension
+}
+
+// Multidimensional data description
+message TensorDescriptor
+{
+    string   name   = 1;  // Optional parameter, tensor name
+
+    DataType dtype  = 2;  // tensor datatype
+    ShapeDef shape  = 3;  // Shape / dimension
+    string   layout = 4;  // Tensor format, eg: "NCHW", "NHWC", "CHW", "ND"
+
+    bool has_out_attr = 9;
+    int64 size = 10;
+    int64 weight_size = 11;
+    bool reuse_input = 12;
+    bool output_tensor = 13;
+    string device_type = 14;
+    bool input_tensor =15;
+    int64 real_dim_cnt = 16;
+    int64 reuse_input_index = 17;
+    int64 data_offset = 18;
+    int64 cmps_size = 19;
+    string cmps_tab = 20;
+    int64 cmps_tab_offset = 21;
+
+	map<string, AttrDef> attr = 5;  // Set of extra parameter fields
+}
+
+// GeTensor definition
+message TensorDef
+{
+    TensorDescriptor desc = 1;  // Tensor description
+    bytes            data = 2;  // Tensor data
+}
+
+
+// Operator description
+message OpDef
+{
+    string name = 1;  // name
+    string type = 2;  // type
+
+    repeated string input = 5;  // input original op name + outgoing index. op_name：index
+
+    map<string, AttrDef> attr = 10;  // Set of operator parameter fields
+
+    bool has_out_attr = 20;
+    int64 id = 21;
+    int64 stream_id =22;
+    repeated string input_name = 23;
+    repeated string src_name = 24;
+    repeated int64 src_index = 25;
+    repeated string dst_name = 26;
+    repeated int64 dst_index = 27;
+    repeated int64 input_i = 28;
+    repeated int64 output_i = 29;
+    repeated int64 workspace = 30;
+    repeated int64 workspace_bytes = 31;
+    repeated bool is_input_const = 32;
+    repeated TensorDescriptor input_desc = 33;
+    repeated TensorDescriptor output_desc = 34;
+    repeated string subgraph_name = 35;
+}
+
+// Graph definition
+message GraphDef
+{
+    string name   = 1;   //  name
+
+    repeated string input  = 4;  // Graph input
+    repeated string output = 5;  // Graph output
+
+    repeated OpDef op      = 6;  // List of operators
+
+	map<string, AttrDef> attr = 11;  // Extended field
+}
+
+// model definition
+message ModelDef
+{
+	string name         = 1;  // name
+	uint32 version      = 2;  // IR Proto verion
+	string custom_version = 3;  // User model version number, passed in by user
+
+    repeated GraphDef graph = 7;  // Graph definition，graph[0] represents the main diagram in modeldef
+
+    map<string, AttrDef> attr = 11;  // Extended field
+}
+

parser/common/acl_graph_parser_util.h

@@ -137,6 +137,78 @@ bool ValidateStr(const std::string &filePath, const std::string &mode);
 /// @return Time character string in the format: %Y%m%d%H%M%S, eg: 20171011083555
 ///
 std::string CurrentTimeInStr();
+
+template <typename T, typename... Args>
+static inline std::shared_ptr<T> MakeShared(Args &&... args) {
+  typedef typename std::remove_const<T>::type T_nc;
+  std::shared_ptr<T> ret(new (std::nothrow) T_nc(std::forward<Args>(args)...));
+  return ret;
+}
+
+/// @ingroup math_util
+/// @brief check whether int64 multiplication can result in overflow
+/// @param [in] a  multiplicator
+/// @param [in] b  multiplicator
+/// @return Status
+inline domi::Status Int64MulCheckOverflow(int64_t a, int64_t b) {
+  if (a > 0) {
+    if (b > 0) {
+      if (a > (INT64_MAX / b)) {
+        return domi::FAILED;
+      }
+    } else {
+      if (b < (INT64_MIN / a)) {
+        return domi::FAILED;
+      }
+    }
+  } else {
+    if (b > 0) {
+      if (a < (INT64_MIN / b)) {
+        return domi::FAILED;
+      }
+    } else {
+      if ((a != 0) && (b < (INT64_MAX / a))) {
+        return domi::FAILED;
+      }
+    }
+  }
+  return domi::SUCCESS;
+}
+
+/// @ingroup math_util
+/// @brief check whether int64 multiplication can result in overflow
+/// @param [in] a  multiplicator
+/// @param [in] b  multiplicator
+/// @return Status
+inline domi::Status CheckInt64Uint32MulOverflow(int64_t a, uint32_t b) {
+  if (a == 0 || b == 0) {
+    return domi::SUCCESS;
+  }
+  if (a > 0) {
+    if (a > (INT64_MAX / b)) {
+      return domi::FAILED;
+    }
+  } else {
+    if (a < (INT64_MIN / b)) {
+      return domi::FAILED;
+    }
+  }
+  return domi::SUCCESS;
+}
+
+#define PARSER_INT64_MULCHECK(a, b)                                                                             \
+  if (ge::parser::Int64MulCheckOverflow((a), (b)) != SUCCESS) {                                                 \
+    GELOGW("Int64 %ld and %ld multiplication can result in overflow!", static_cast<int64_t>(a), \
+           static_cast<int64_t>(b));                                                                            \
+    return INTERNAL_ERROR;                                                                                      \
+  }
+
+#define PARSER_INT64_UINT32_MULCHECK(a, b)                                                                         \
+  if (ge::parser::CheckInt64Uint32MulOverflow((a), (b)) != SUCCESS) {                                              \
+    GELOGW("Int64 %ld and UINT32 %u multiplication can result in overflow!", static_cast<uint32_t>(a), \
+           static_cast<uint32_t>(b));                                                                              \
+    return INTERNAL_ERROR;                                                                                         \
+  }
 }  // namespace parser
 }  // namespace ge
 

parser/common/data_op_parser.cc

@@ -18,7 +18,7 @@
 #include <cstdlib>
 #include "common/debug/log.h"
 #include "common/op/ge_op_utils.h"
-#include "common/math/math_util.h"
+#include "parser/common/acl_graph_parser_util.h"
 #include "common/util.h"
 #include "graph/utils/type_utils.h"
 #include "omg/omg.h"
@@ -128,10 +128,10 @@ Status DataOpParser::InitNDTensor(const vector<int64_t> &shape, ge::DataType dat
   }
   uint32_t type_size = 0;
   if (ge::TypeUtils::GetDataTypeLength(data_type, type_size)) {
-    FMK_INT64_UINT32_MULCHECK(size, type_size);
+    PARSER_INT64_UINT32_MULCHECK(size, type_size);
     size *= type_size;
   } else {
-    FMK_INT64_UINT32_MULCHECK(size, static_cast<uint32_t>(sizeof(float)));
+    PARSER_INT64_UINT32_MULCHECK(size, static_cast<uint32_t>(sizeof(float)));
     size *= sizeof(float);
   }
   ge::TensorUtils::SetSize(tensor_desc, size);
@@ -169,7 +169,7 @@ Status DataOpParser::InitInputTensor(const vector<int64_t> &shape, ge::GeTensorD
   if (input.GetShape().GetDim(0) != -1) {
     size = input.GetShape().GetShapeSize();
   }
-  FMK_INT64_UINT32_MULCHECK(size, static_cast<uint32_t>(sizeof(float)));
+  PARSER_INT64_UINT32_MULCHECK(size, static_cast<uint32_t>(sizeof(float)));
   ge::TensorUtils::SetSize(input, size * sizeof(float));
 
   return SUCCESS;

parser/common/op_parser_factory.h

@@ -23,7 +23,7 @@
 #include <mutex>
 #include <string>
 #include <vector>
-#include "common/ge/ge_util.h"
+#include "parser/common/acl_graph_parser_util.h"
 #include "framework/omg/parser/parser_types.h"
 #include "framework/common/debug/ge_log.h"
 #include "omg/omg_inner_types.h"
@@ -162,7 +162,7 @@ class CustomParserAdapterRegistrar {
  */
 #define REGISTER_OP_PARSER_CREATOR(framework, op_type, clazz)                              \
   std::shared_ptr<OpParser> Creator_##framework##_##op_type##_Op_Parser() {                \
-    std::shared_ptr<clazz> ptr = ge::MakeShared<clazz>();                                  \
+    std::shared_ptr<clazz> ptr = ge::parser::MakeShared<clazz>();                                  \
     if (ptr == nullptr) {                                                                  \
       GELOGW("MakeShared failed, result is nullptr.");                                     \
     }                                                                                      \
@@ -173,7 +173,7 @@ class CustomParserAdapterRegistrar {
 
 #define REGISTER_FUSION_OP_PARSER_CREATOR(framework, op_type, clazz)               \
   std::shared_ptr<OpParser> Creator_##framework##_##op_type##_Fusion_Op_Parser() { \
-    std::shared_ptr<clazz> ptr = ge::MakeShared<clazz>();                          \
+    std::shared_ptr<clazz> ptr = ge::parser::MakeShared<clazz>();                          \
     if (ptr == nullptr) {                                                          \
       GELOGW("MakeShared failed, result is nullptr.");                             \
     }                                                                              \
@@ -187,7 +187,7 @@ class CustomParserAdapterRegistrar {
 /// @param [in] clazz        CaffeCustomParserAdapter adaptation class
 #define REGISTER_CUSTOM_PARSER_ADAPTER_CREATOR(framework, clazz)         \
   std::shared_ptr<OpParser> Creator_##framework##_Op_Parser_Adapter() { \
-    std::shared_ptr<clazz> ptr = ge::MakeShared<clazz>();               \
+    std::shared_ptr<clazz> ptr = ge::parser::MakeShared<clazz>();               \
     if (ptr == nullptr) {                                               \
       GELOGW("MakeShared failed, result is nullptr.");                  \
     }                                                                   \

parser/common/proto/ge_ir.proto

@@ -1,190 +1,190 @@
-syntax = "proto3";
-
-package ge.proto;
-
-enum DataType
-{
-    DT_UNDEFINED = 0;  // Used to indicate a DataType field has not been set.
-    DT_FLOAT     = 1;  // float type
-    DT_FLOAT16   = 2;  // fp16 type
-    DT_INT8      = 3;  // int8 type
-    DT_UINT8     = 4;  // uint8 type
-    DT_INT16     = 5;  // int16 type
-    DT_UINT16    = 6;  // uint16 type
-    DT_INT32     = 7;  //
-    DT_INT64     = 8;  // int64 type
-    DT_UINT32    = 9;  // unsigned int32
-    DT_UINT64    = 10;  // unsigned int64
-    DT_BOOL      = 11;  // bool type
-    DT_DOUBLE    = 12; // double type
-    DT_STRING = 13;            // string type
-    DT_DUAL_SUB_INT8 = 14;    /**< dual output int8 type */
-    DT_DUAL_SUB_UINT8 = 15;    /**< dual output uint8 type */
-    DT_COMPLEX64 = 16;         // complex64 type
-    DT_COMPLEX128 = 17;        // complex128 type
-    DT_QINT8 = 18;             // qint8 type
-    DT_QINT16 = 19;            // qint16 type
-    DT_QINT32 = 20;            // qint32 type
-    DT_QUINT8 = 21;            // quint8 type
-    DT_QUINT16 = 22;           // quint16 type
-    DT_RESOURCE  = 23;         // resource type
-    DT_STRING_REF = 24;        // string_ref type
-    DT_DUAL      = 25;              /**< dual output type */
-}
-
-message AttrDef
-{
-    message ListValue
-    {
-        enum ListValueType{
-          VT_LIST_NONE = 0;
-          VT_LIST_STRING = 1;
-          VT_LIST_INT = 2;
-          VT_LIST_FLOAT = 3;
-          VT_LIST_BOOL = 4;
-          VT_LIST_BYTES = 5;
-          VT_LIST_TENSOR_DESC = 6;
-          VT_LIST_TENSOR = 7;
-          VT_LIST_GRAPH = 8;
-          VT_LIST_NAMED_ATTRS = 9;
-          VT_LIST_DATA_TYPE = 10;
-        }
-        repeated bytes s             = 2;                    // "list(string)"
-        repeated int64 i             = 3;  // "list(int)"
-        repeated float f             = 4;   // "list(float)"
-        repeated bool  b             = 5;  // "list(bool)"
-        repeated bytes bt            = 7;
-        repeated TensorDescriptor td = 8;
-        repeated TensorDef t         = 9;
-        repeated GraphDef g          = 10;
-	    repeated NamedAttrs na       = 11;
-	    repeated int64 dt            = 12; // list ge::DataType
-
-	    ListValueType val_type       = 20;
-    }
-
-    message ListListInt{
-        message ListInt{
-            repeated int64 list_i             = 1; // list int
-        }
-        repeated ListInt list_list_i             = 1; // list list int
-    }
-
-    oneof value
-    {
-        bytes            s    = 2;  // "string"
-        int64            i    = 3;  // "int"
-        float            f    = 4;  // "float"
-        bool             b    = 5;  // "bool"
-        bytes            bt   = 7;
-        ListValue        list = 1;   // any "list(...)"
-        NamedAttrs       func = 10;  // Used to support attr nesting
-        TensorDescriptor td   = 11;  // GeTensorDesc type
-        TensorDef        t    = 12;  // GeTensor type
-        GraphDef         g    = 13;  // Graph type
-        ListListInt      list_list_int  = 14;  // List List Int type
-        int64            dt   = 15; // ge::DataType
-    }
-}
-
-// A list of attr names and their values. The whole list is attached
-// with a string name.  E.g., MatMul[T=float].
-message NamedAttrs
-{
-    string               name = 1;
-    map<string, AttrDef> attr = 2;
-}
-
-// Shape / dimension description, using row-major order
-message ShapeDef
-{
-    repeated int64 dim = 1;  // Size of each dimension
-}
-
-// Multidimensional data description
-message TensorDescriptor
-{
-    string   name   = 1;  // Optional parameter, tensor name
-
-    DataType dtype  = 2;  // tensor datatype
-    ShapeDef shape  = 3;  // Shape / dimension
-    string   layout = 4;  // Tensor format, eg: "NCHW", "NHWC", "CHW", "ND"
-
-    bool has_out_attr = 9;
-    int64 size = 10;
-    int64 weight_size = 11;
-    bool reuse_input = 12;
-    bool output_tensor = 13;
-    string device_type = 14;
-    bool input_tensor =15;
-    int64 real_dim_cnt = 16;
-    int64 reuse_input_index = 17;
-    int64 data_offset = 18;
-    int64 cmps_size = 19;
-    string cmps_tab = 20;
-    int64 cmps_tab_offset = 21;
-
-	map<string, AttrDef> attr = 5;  // Set of extra parameter fields
-}
-
-// GeTensor definition
-message TensorDef
-{
-    TensorDescriptor desc = 1;  // Tensor description
-    bytes            data = 2;  // Tensor data
-}
-
-
-// Operator description
-message OpDef
-{
-    string name = 1;  // name
-    string type = 2;  // type
-
-    repeated string input = 5;  // input original op name + outgoing index. op_name：index
-
-    map<string, AttrDef> attr = 10;  // Set of operator parameter fields
-
-    bool has_out_attr = 20;
-    int64 id = 21;
-    int64 stream_id =22;
-    repeated string input_name = 23;
-    repeated string src_name = 24;
-    repeated int64 src_index = 25;
-    repeated string dst_name = 26;
-    repeated int64 dst_index = 27;
-    repeated int64 input_i = 28;
-    repeated int64 output_i = 29;
-    repeated int64 workspace = 30;
-    repeated int64 workspace_bytes = 31;
-    repeated bool is_input_const = 32;
-    repeated TensorDescriptor input_desc = 33;
-    repeated TensorDescriptor output_desc = 34;
-    repeated string subgraph_name = 35;
-}
-
-// Graph definition
-message GraphDef
-{
-    string name   = 1;   //  name
-
-    repeated string input  = 4;  // Graph input
-    repeated string output = 5;  // Graph output
-
-    repeated OpDef op      = 6;  // List of operators
-
-	map<string, AttrDef> attr = 11;  // Extended field
-}
-
-// model definition
-message ModelDef
-{
-	string name         = 1;  // name
-	uint32 version      = 2;  // IR Proto verion
-	string custom_version = 3;  // User model version number, passed in by user
-
-    repeated GraphDef graph = 7;  // Graph definition，graph[0] represents the main diagram in modeldef
-
-    map<string, AttrDef> attr = 11;  // Extended field
-}
-
+syntax = "proto3";
+
+package ge.proto;
+
+enum DataType
+{
+    DT_UNDEFINED = 0;  // Used to indicate a DataType field has not been set.
+    DT_FLOAT     = 1;  // float type
+    DT_FLOAT16   = 2;  // fp16 type
+    DT_INT8      = 3;  // int8 type
+    DT_UINT8     = 4;  // uint8 type
+    DT_INT16     = 5;  // int16 type
+    DT_UINT16    = 6;  // uint16 type
+    DT_INT32     = 7;  //
+    DT_INT64     = 8;  // int64 type
+    DT_UINT32    = 9;  // unsigned int32
+    DT_UINT64    = 10;  // unsigned int64
+    DT_BOOL      = 11;  // bool type
+    DT_DOUBLE    = 12; // double type
+    DT_STRING = 13;            // string type
+    DT_DUAL_SUB_INT8 = 14;    /**< dual output int8 type */
+    DT_DUAL_SUB_UINT8 = 15;    /**< dual output uint8 type */
+    DT_COMPLEX64 = 16;         // complex64 type
+    DT_COMPLEX128 = 17;        // complex128 type
+    DT_QINT8 = 18;             // qint8 type
+    DT_QINT16 = 19;            // qint16 type
+    DT_QINT32 = 20;            // qint32 type
+    DT_QUINT8 = 21;            // quint8 type
+    DT_QUINT16 = 22;           // quint16 type
+    DT_RESOURCE  = 23;         // resource type
+    DT_STRING_REF = 24;        // string_ref type
+    DT_DUAL      = 25;              /**< dual output type */
+}
+
+message AttrDef
+{
+    message ListValue
+    {
+        enum ListValueType{
+          VT_LIST_NONE = 0;
+          VT_LIST_STRING = 1;
+          VT_LIST_INT = 2;
+          VT_LIST_FLOAT = 3;
+          VT_LIST_BOOL = 4;
+          VT_LIST_BYTES = 5;
+          VT_LIST_TENSOR_DESC = 6;
+          VT_LIST_TENSOR = 7;
+          VT_LIST_GRAPH = 8;
+          VT_LIST_NAMED_ATTRS = 9;
+          VT_LIST_DATA_TYPE = 10;
+        }
+        repeated bytes s             = 2;                    // "list(string)"
+        repeated int64 i             = 3;  // "list(int)"
+        repeated float f             = 4;   // "list(float)"
+        repeated bool  b             = 5;  // "list(bool)"
+        repeated bytes bt            = 7;
+        repeated TensorDescriptor td = 8;
+        repeated TensorDef t         = 9;
+        repeated GraphDef g          = 10;
+	    repeated NamedAttrs na       = 11;
+	    repeated int64 dt            = 12; // list ge::DataType
+
+	    ListValueType val_type       = 20;
+    }
+
+    message ListListInt{
+        message ListInt{
+            repeated int64 list_i             = 1; // list int
+        }
+        repeated ListInt list_list_i             = 1; // list list int
+    }
+
+    oneof value
+    {
+        bytes            s    = 2;  // "string"
+        int64            i    = 3;  // "int"
+        float            f    = 4;  // "float"
+        bool             b    = 5;  // "bool"
+        bytes            bt   = 7;
+        ListValue        list = 1;   // any "list(...)"
+        NamedAttrs       func = 10;  // Used to support attr nesting
+        TensorDescriptor td   = 11;  // GeTensorDesc type
+        TensorDef        t    = 12;  // GeTensor type
+        GraphDef         g    = 13;  // Graph type
+        ListListInt      list_list_int  = 14;  // List List Int type
+        int64            dt   = 15; // ge::DataType
+    }
+}
+
+// A list of attr names and their values. The whole list is attached
+// with a string name.  E.g., MatMul[T=float].
+message NamedAttrs
+{
+    string               name = 1;
+    map<string, AttrDef> attr = 2;
+}
+
+// Shape / dimension description, using row-major order
+message ShapeDef
+{
+    repeated int64 dim = 1;  // Size of each dimension
+}
+
+// Multidimensional data description
+message TensorDescriptor
+{
+    string   name   = 1;  // Optional parameter, tensor name
+
+    DataType dtype  = 2;  // tensor datatype
+    ShapeDef shape  = 3;  // Shape / dimension
+    string   layout = 4;  // Tensor format, eg: "NCHW", "NHWC", "CHW", "ND"
+
+    bool has_out_attr = 9;
+    int64 size = 10;
+    int64 weight_size = 11;
+    bool reuse_input = 12;
+    bool output_tensor = 13;
+    string device_type = 14;
+    bool input_tensor =15;
+    int64 real_dim_cnt = 16;
+    int64 reuse_input_index = 17;
+    int64 data_offset = 18;
+    int64 cmps_size = 19;
+    string cmps_tab = 20;
+    int64 cmps_tab_offset = 21;
+
+	map<string, AttrDef> attr = 5;  // Set of extra parameter fields
+}
+
+// GeTensor definition
+message TensorDef
+{
+    TensorDescriptor desc = 1;  // Tensor description
+    bytes            data = 2;  // Tensor data
+}
+
+
+// Operator description
+message OpDef
+{
+    string name = 1;  // name
+    string type = 2;  // type
+
+    repeated string input = 5;  // input original op name + outgoing index. op_name：index
+
+    map<string, AttrDef> attr = 10;  // Set of operator parameter fields
+
+    bool has_out_attr = 20;
+    int64 id = 21;
+    int64 stream_id =22;
+    repeated string input_name = 23;
+    repeated string src_name = 24;
+    repeated int64 src_index = 25;
+    repeated string dst_name = 26;
+    repeated int64 dst_index = 27;
+    repeated int64 input_i = 28;
+    repeated int64 output_i = 29;
+    repeated int64 workspace = 30;
+    repeated int64 workspace_bytes = 31;
+    repeated bool is_input_const = 32;
+    repeated TensorDescriptor input_desc = 33;
+    repeated TensorDescriptor output_desc = 34;
+    repeated string subgraph_name = 35;
+}
+
+// Graph definition
+message GraphDef
+{
+    string name   = 1;   //  name
+
+    repeated string input  = 4;  // Graph input
+    repeated string output = 5;  // Graph output
+
+    repeated OpDef op      = 6;  // List of operators
+
+	map<string, AttrDef> attr = 11;  // Extended field
+}
+
+// model definition
+message ModelDef
+{
+	string name         = 1;  // name
+	uint32 version      = 2;  // IR Proto verion
+	string custom_version = 3;  // User model version number, passed in by user
+
+    repeated GraphDef graph = 7;  // Graph definition，graph[0] represents the main diagram in modeldef
+
+    map<string, AttrDef> attr = 11;  // Extended field
+}
+

parser/common/proto/insert_op.proto

@@ -1,136 +1,136 @@
-syntax = "proto3";
-
-package domi;
-
-message InsertNewOps {
-	repeated AippOpParams aipp_op = 1;
-	repeated MultiShapeOpParams multi_shape_op = 2;
-}
-
-message AippOpParams {
-	enum InputFormat {
-		UNDEFINED = 0;
-		YUV420SP_U8 = 1;
-		XRGB8888_U8 = 2;
-		RGB888_U8   = 3;
-		YUV400_U8   = 4;
-		NC1HWC0DI_FP16 = 5;
-		NC1HWC0DI_S8 = 6;
-		ARGB8888_U8 = 7;
-		YUYV_U8 = 8;
-		YUV422SP_U8 = 9;
-		AYUV444_U8 = 10;
-		RAW10 = 11;
-		RAW12 = 12;
-		RAW16 = 13;
-		RAW24 = 14;
-		RGB16 = 15;
-		RGB20 = 16;
-		RGB24 = 17;
-		RGB8_IR = 18;
-		RGB16_IR = 19;
-		RGB24_IR = 20;
-	}
-
-	enum AippMode {
-		undefined = 0;
-		static = 1;
-		dynamic = 2;
-	}
-
-	// AIPP模式，区分静态AIPP和动态AIPP
-	AippMode aipp_mode = 1;
-
-	// related_input_rank参数为必填，类型为整型，配置范围>=0, <=输入Data算子的个数，默认值为0。
-	// 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;
-
-	// 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。
-	repeated uint32 input_edge_idx = 3;
-
-	// [Begin] 动态AIPP参数，配置静态AIPP时无效
-	uint32 max_src_image_size = 4;
-
-	// 是否支持旋转。默认不支持，开启支持旋转时，会有额外的空间和性能损失
-	bool support_rotation = 5;
-
-	// [End] 动态AIPP参数
-
-
-	// [Begin] 静态AIPP参数，配置动态AIPP时无效
-	InputFormat input_format = 51;
-	bool csc_switch = 52;
-	float cpadding_value = 53;
-	bool rbuv_swap_switch = 54;
-	bool ax_swap_switch = 55;
-	bool single_line_mode = 56;
-
-	int32 src_image_size_w = 57;
-	int32 src_image_size_h = 58;
-
-	bool crop = 59;
-	int32 load_start_pos_w = 60;
-	int32 load_start_pos_h = 61;
-	int32 crop_size_w = 62;
-	int32 crop_size_h = 63;
-
-	bool resize = 64;
-	int32 resize_output_w = 65;
-	int32 resize_output_h = 66;
-
-	bool padding = 67;
-	int32 left_padding_size = 68;
-	int32 right_padding_size = 69;
-	int32 top_padding_size = 70;
-	int32 bottom_padding_size = 71;
-
-	int32 mean_chn_0 = 10;
-	int32 mean_chn_1 = 11;
-	int32 mean_chn_2 = 12;
-	int32 mean_chn_3 = 19;
-	float min_chn_0 = 13;
-	float min_chn_1 = 14;
-	float min_chn_2 = 15;
-	float min_chn_3 = 20;
-	repeated float var_reci_chn_0 = 16;
-	repeated float var_reci_chn_1 = 17;
-	repeated float var_reci_chn_2 = 18;
-	repeated float var_reci_chn_3 = 21;
-
-	repeated int32 matrix_r0c0 = 30;
-	repeated int32 matrix_r0c1 = 31;
-	repeated int32 matrix_r0c2 = 32;
-	repeated int32 matrix_r1c0 = 33;
-	repeated int32 matrix_r1c1 = 34;
-	repeated int32 matrix_r1c2 = 35;
-	repeated int32 matrix_r2c0 = 36;
-	repeated int32 matrix_r2c1 = 37;
-	repeated int32 matrix_r2c2 = 38;
-	repeated int32 output_bias_0 = 39;
-	repeated int32 output_bias_1 = 40;
-	repeated int32 output_bias_2 = 41;
-	repeated int32 input_bias_0 = 42;
-	repeated int32 input_bias_1 = 43;
-	repeated int32 input_bias_2 = 44;
-
-	// [End] 静态AIPP参数
-
-       // The n number that is used for raw/rgbir data into f16 transformation.
-       // The transformation equation is x/(2^n). If set to 0, no transform is performed.
-       uint32 raw_rgbir_to_f16_n = 45;
-}
-
-message MultiShapeOpParams {
-	enum MultiShapeMode {
-		batch      = 0;             //动态batch
-		resolution = 1;             //动态分辨率，扩展用
-	}
-
-	MultiShapeMode    mode                      = 1;        //算子模式
-	uint32            related_input_rank        = 2;        //新增算子插入到哪个输入
-
-
-	repeated uint32 batch_list   = 11; //batch_list值，batch_list的个数是2到8之间
-}
+syntax = "proto3";
+
+package domi;
+
+message InsertNewOps {
+	repeated AippOpParams aipp_op = 1;
+	repeated MultiShapeOpParams multi_shape_op = 2;
+}
+
+message AippOpParams {
+	enum InputFormat {
+		UNDEFINED = 0;
+		YUV420SP_U8 = 1;
+		XRGB8888_U8 = 2;
+		RGB888_U8   = 3;
+		YUV400_U8   = 4;
+		NC1HWC0DI_FP16 = 5;
+		NC1HWC0DI_S8 = 6;
+		ARGB8888_U8 = 7;
+		YUYV_U8 = 8;
+		YUV422SP_U8 = 9;
+		AYUV444_U8 = 10;
+		RAW10 = 11;
+		RAW12 = 12;
+		RAW16 = 13;
+		RAW24 = 14;
+		RGB16 = 15;
+		RGB20 = 16;
+		RGB24 = 17;
+		RGB8_IR = 18;
+		RGB16_IR = 19;
+		RGB24_IR = 20;
+	}
+
+	enum AippMode {
+		undefined = 0;
+		static = 1;
+		dynamic = 2;
+	}
+
+	// AIPP模式，区分静态AIPP和动态AIPP
+	AippMode aipp_mode = 1;
+
+	// related_input_rank参数为必填，类型为整型，配置范围>=0, <=输入Data算子的个数，默认值为0。
+	// 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;
+
+	// 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。
+	repeated uint32 input_edge_idx = 3;
+
+	// [Begin] 动态AIPP参数，配置静态AIPP时无效
+	uint32 max_src_image_size = 4;
+
+	// 是否支持旋转。默认不支持，开启支持旋转时，会有额外的空间和性能损失
+	bool support_rotation = 5;
+
+	// [End] 动态AIPP参数
+
+
+	// [Begin] 静态AIPP参数，配置动态AIPP时无效
+	InputFormat input_format = 51;
+	bool csc_switch = 52;
+	float cpadding_value = 53;
+	bool rbuv_swap_switch = 54;
+	bool ax_swap_switch = 55;
+	bool single_line_mode = 56;
+
+	int32 src_image_size_w = 57;
+	int32 src_image_size_h = 58;
+
+	bool crop = 59;
+	int32 load_start_pos_w = 60;
+	int32 load_start_pos_h = 61;
+	int32 crop_size_w = 62;
+	int32 crop_size_h = 63;
+
+	bool resize = 64;
+	int32 resize_output_w = 65;
+	int32 resize_output_h = 66;
+
+	bool padding = 67;
+	int32 left_padding_size = 68;
+	int32 right_padding_size = 69;
+	int32 top_padding_size = 70;
+	int32 bottom_padding_size = 71;
+
+	int32 mean_chn_0 = 10;
+	int32 mean_chn_1 = 11;
+	int32 mean_chn_2 = 12;
+	int32 mean_chn_3 = 19;
+	float min_chn_0 = 13;
+	float min_chn_1 = 14;
+	float min_chn_2 = 15;
+	float min_chn_3 = 20;
+	repeated float var_reci_chn_0 = 16;
+	repeated float var_reci_chn_1 = 17;
+	repeated float var_reci_chn_2 = 18;
+	repeated float var_reci_chn_3 = 21;
+
+	repeated int32 matrix_r0c0 = 30;
+	repeated int32 matrix_r0c1 = 31;
+	repeated int32 matrix_r0c2 = 32;
+	repeated int32 matrix_r1c0 = 33;
+	repeated int32 matrix_r1c1 = 34;
+	repeated int32 matrix_r1c2 = 35;
+	repeated int32 matrix_r2c0 = 36;
+	repeated int32 matrix_r2c1 = 37;
+	repeated int32 matrix_r2c2 = 38;
+	repeated int32 output_bias_0 = 39;
+	repeated int32 output_bias_1 = 40;
+	repeated int32 output_bias_2 = 41;
+	repeated int32 input_bias_0 = 42;
+	repeated int32 input_bias_1 = 43;
+	repeated int32 input_bias_2 = 44;
+
+	// [End] 静态AIPP参数
+
+       // The n number that is used for raw/rgbir data into f16 transformation.
+       // The transformation equation is x/(2^n). If set to 0, no transform is performed.
+       uint32 raw_rgbir_to_f16_n = 45;
+}
+
+message MultiShapeOpParams {
+	enum MultiShapeMode {
+		batch      = 0;             //动态batch
+		resolution = 1;             //动态分辨率，扩展用
+	}
+
+	MultiShapeMode    mode                      = 1;        //算子模式
+	uint32            related_input_rank        = 2;        //新增算子插入到哪个输入
+
+
+	repeated uint32 batch_list   = 11; //batch_list值，batch_list的个数是2到8之间
+}

parser/common/register_tbe.cc

@@ -19,7 +19,7 @@
 #include <memory>
 #include <string>
 #include "common/debug/log.h"
-#include "common/ge/ge_util.h"
+#include "parser/common/acl_graph_parser_util.h"
 #include "common/op/ge_op_utils.h"
 #include "common/op_map.h"
 #include "common/util.h"
@@ -79,7 +79,7 @@ bool OpRegistrationTbe::RegisterParser(const OpRegistrationData &reg_data) {
         return false;
       }
       std::shared_ptr<TensorFlowCustomParserAdapter> tf_parser_adapter =
-          ge::MakeShared<TensorFlowCustomParserAdapter>();
+          ge::parser::MakeShared<TensorFlowCustomParserAdapter>();
       if (tf_parser_adapter == nullptr) {
         GELOGE(PARAM_INVALID, "Create tf parser adapter failed.");
         return false;
@@ -95,7 +95,7 @@ bool OpRegistrationTbe::RegisterParser(const OpRegistrationData &reg_data) {
       }
       GELOGI("Register fusion custom op parser: %s", reg_data.GetOmOptype().c_str());
       std::shared_ptr<TensorFlowFusionCustomParserAdapter> tf_fusion_parser_adapter =
-          ge::MakeShared<TensorFlowFusionCustomParserAdapter>();
+          ge::parser::MakeShared<TensorFlowFusionCustomParserAdapter>();
       if (tf_fusion_parser_adapter == nullptr) {
         GELOGE(PARAM_INVALID, "Create tf fusion parser adapter failed.");
         return false;

parser/common/thread_pool.h

@@ -32,7 +32,7 @@
 #include "framework/common/ge_inner_error_codes.h"
 #include "external/ge/ge_api_error_codes.h"
 #include "graph/types.h"
-#include "common/ge/ge_util.h"
+#include "parser/common/acl_graph_parser_util.h"
 
 namespace ge {
 using ThreadTask = std::function<void()>;
@@ -53,7 +53,7 @@ class GE_FUNC_DEV_VISIBILITY GE_FUNC_HOST_VISIBILITY ThreadPool {
     }
 
     auto bindFunc = std::bind(std::forward<Func>(func), std::forward<Args>(args)...);
-    auto task = ge::MakeShared<std::packaged_task<retType()>>(bindFunc);
+    auto task = ge::parser::MakeShared<std::packaged_task<retType()>>(bindFunc);
     if (task == nullptr) {
       GELOGE(ge::FAILED, "Make shared failed.");
       return fail_future;

parser/func_to_graph/proto_python_rule.mk

@@ -1,17 +1,17 @@
-include $(BUILD_SYSTEM)/base_rules.mk
-
-FUNCTION_TO_GRAPH_OUT_TIMESTAMP := $(HOST_OUT_ROOT)/func_to_graph/.timestamp
-
-PROTO_SRC_DIR = framework/domi/parser/func_to_graph/proto
-PY_PROTO_BUILD_DIR = $(HOST_OUT_ROOT)/tmp/function_to_graph/proto
-
-$(warning PRIVATE_PROTOC is $(PRIVATE_PROTOC))
-$(warning protobuf_lib_dir is $(protobuf_lib_dir))
-
-$(FUNCTION_TO_GRAPH_OUT_TIMESTAMP): $(PRIVATE_PROTOC)
-	mkdir -p $(PY_PROTO_BUILD_DIR)
-	LD_LIBRARY_PATH=$(protobuf_lib_dir):$$LD_LIBRARY_PATH $(PRIVATE_PROTOC) -I=$(PROTO_SRC_DIR) --python_out=$(PY_PROTO_BUILD_DIR) $(PROTO_SRC_DIR)/*.proto
-
-$(LOCAL_BUILT_MODULE): $(FUNCTION_TO_GRAPH_OUT_TIMESTAMP)
-	mkdir -p $@
+include $(BUILD_SYSTEM)/base_rules.mk
+
+FUNCTION_TO_GRAPH_OUT_TIMESTAMP := $(HOST_OUT_ROOT)/func_to_graph/.timestamp
+
+PROTO_SRC_DIR = framework/domi/parser/func_to_graph/proto
+PY_PROTO_BUILD_DIR = $(HOST_OUT_ROOT)/tmp/function_to_graph/proto
+
+$(warning PRIVATE_PROTOC is $(PRIVATE_PROTOC))
+$(warning protobuf_lib_dir is $(protobuf_lib_dir))
+
+$(FUNCTION_TO_GRAPH_OUT_TIMESTAMP): $(PRIVATE_PROTOC)
+	mkdir -p $(PY_PROTO_BUILD_DIR)
+	LD_LIBRARY_PATH=$(protobuf_lib_dir):$$LD_LIBRARY_PATH $(PRIVATE_PROTOC) -I=$(PROTO_SRC_DIR) --python_out=$(PY_PROTO_BUILD_DIR) $(PROTO_SRC_DIR)/*.proto
+
+$(LOCAL_BUILT_MODULE): $(FUNCTION_TO_GRAPH_OUT_TIMESTAMP)
+	mkdir -p $@
 	cp -rf $(PY_PROTO_BUILD_DIR)/* $@

parser/onnx/module.mk

@@ -43,7 +43,6 @@ LOCAL_SHARED_LIBRARIES := \
     libparser_common \
     libgraph \
     libregister \
-    libge_common \
 
 LOCAL_LDFLAGS := -lrt
 

parser/onnx/onnx_constant_parser.cc

@@ -17,7 +17,7 @@
 #include "onnx_constant_parser.h"
 #include <map>
 #include <vector>
-#include "common/ge/ge_util.h"
+#include "parser/common/acl_graph_parser_util.h"
 #include "common/util.h"
 #include "framework/omg/parser/parser_inner_ctx.h"
 #include "graph/ge_tensor.h"

parser/proto/ge_ir.proto

@@ -1,190 +1,190 @@
-syntax = "proto3";
-
-package ge.proto;
-
-enum DataType
-{
-    DT_UNDEFINED = 0;  // Used to indicate a DataType field has not been set.
-    DT_FLOAT     = 1;  // float type
-    DT_FLOAT16   = 2;  // fp16 type
-    DT_INT8      = 3;  // int8 type
-    DT_UINT8     = 4;  // uint8 type
-    DT_INT16     = 5;  // int16 type
-    DT_UINT16    = 6;  // uint16 type
-    DT_INT32     = 7;  //
-    DT_INT64     = 8;  // int64 type
-    DT_UINT32    = 9;  // unsigned int32
-    DT_UINT64    = 10;  // unsigned int64
-    DT_BOOL      = 11;  // bool type
-    DT_DOUBLE    = 12; // double type
-    DT_STRING = 13;            // string type
-    DT_DUAL_SUB_INT8 = 14;    /**< dual output int8 type */
-    DT_DUAL_SUB_UINT8 = 15;    /**< dual output uint8 type */
-    DT_COMPLEX64 = 16;         // complex64 type
-    DT_COMPLEX128 = 17;        // complex128 type
-    DT_QINT8 = 18;             // qint8 type
-    DT_QINT16 = 19;            // qint16 type
-    DT_QINT32 = 20;            // qint32 type
-    DT_QUINT8 = 21;            // quint8 type
-    DT_QUINT16 = 22;           // quint16 type
-    DT_RESOURCE  = 23;         // resource type
-    DT_STRING_REF = 24;        // string_ref type
-    DT_DUAL      = 25;              /**< dual output type */
-}
-
-message AttrDef
-{
-    message ListValue
-    {
-        enum ListValueType{
-          VT_LIST_NONE = 0;
-          VT_LIST_STRING = 1;
-          VT_LIST_INT = 2;
-          VT_LIST_FLOAT = 3;
-          VT_LIST_BOOL = 4;
-          VT_LIST_BYTES = 5;
-          VT_LIST_TENSOR_DESC = 6;
-          VT_LIST_TENSOR = 7;
-          VT_LIST_GRAPH = 8;
-          VT_LIST_NAMED_ATTRS = 9;
-          VT_LIST_DATA_TYPE = 10;
-        }
-        repeated bytes s             = 2;                    // "list(string)"
-        repeated int64 i             = 3;  // "list(int)"
-        repeated float f             = 4;   // "list(float)"
-        repeated bool  b             = 5;  // "list(bool)"
-        repeated bytes bt            = 7;
-        repeated TensorDescriptor td = 8;
-        repeated TensorDef t         = 9;
-        repeated GraphDef g          = 10;
-	    repeated NamedAttrs na       = 11;
-	    repeated int64 dt            = 12; // list ge::DataType
-
-	    ListValueType val_type       = 20;
-    }
-
-    message ListListInt{
-        message ListInt{
-            repeated int64 list_i             = 1; // list int
-        }
-        repeated ListInt list_list_i             = 1; // list list int
-    }
-
-    oneof value
-    {
-        bytes            s    = 2;  // "string"
-        int64            i    = 3;  // "int"
-        float            f    = 4;  // "float"
-        bool             b    = 5;  // "bool"
-        bytes            bt   = 7;
-        ListValue        list = 1;   // any "list(...)"
-        NamedAttrs       func = 10;  // Used to support attr nesting
-        TensorDescriptor td   = 11;  // GeTensorDesc type
-        TensorDef        t    = 12;  // GeTensor type
-        GraphDef         g    = 13;  // Graph type
-        ListListInt      list_list_int  = 14;  // List List Int type
-        int64            dt   = 15; // ge::DataType
-    }
-}
-
-// A list of attr names and their values. The whole list is attached
-// with a string name.  E.g., MatMul[T=float].
-message NamedAttrs
-{
-    string               name = 1;
-    map<string, AttrDef> attr = 2;
-}
-
-// Shape / dimension description, using row-major order
-message ShapeDef
-{
-    repeated int64 dim = 1;  // Size of each dimension
-}
-
-// Multidimensional data description
-message TensorDescriptor
-{
-    string   name   = 1;  // Optional parameter, tensor name
-
-    DataType dtype  = 2;  // tensor datatype
-    ShapeDef shape  = 3;  // Shape / dimension
-    string   layout = 4;  // Tensor format, eg: "NCHW", "NHWC", "CHW", "ND"
-
-    bool has_out_attr = 9;
-    int64 size = 10;
-    int64 weight_size = 11;
-    bool reuse_input = 12;
-    bool output_tensor = 13;
-    string device_type = 14;
-    bool input_tensor =15;
-    int64 real_dim_cnt = 16;
-    int64 reuse_input_index = 17;
-    int64 data_offset = 18;
-    int64 cmps_size = 19;
-    string cmps_tab = 20;
-    int64 cmps_tab_offset = 21;
-
-	map<string, AttrDef> attr = 5;  // Set of extra parameter fields
-}
-
-// GeTensor definition
-message TensorDef
-{
-    TensorDescriptor desc = 1;  // Tensor description
-    bytes            data = 2;  // Tensor data
-}
-
-
-// Operator description
-message OpDef
-{
-    string name = 1;  // name
-    string type = 2;  // type
-
-    repeated string input = 5;  // input original op name + outgoing index. op_name：index
-
-    map<string, AttrDef> attr = 10;  // Set of operator parameter fields
-
-    bool has_out_attr = 20;
-    int64 id = 21;
-    int64 stream_id =22;
-    repeated string input_name = 23;
-    repeated string src_name = 24;
-    repeated int64 src_index = 25;
-    repeated string dst_name = 26;
-    repeated int64 dst_index = 27;
-    repeated int64 input_i = 28;
-    repeated int64 output_i = 29;
-    repeated int64 workspace = 30;
-    repeated int64 workspace_bytes = 31;
-    repeated bool is_input_const = 32;
-    repeated TensorDescriptor input_desc = 33;
-    repeated TensorDescriptor output_desc = 34;
-    repeated string subgraph_name = 35;
-}
-
-// Graph definition
-message GraphDef
-{
-    string name   = 1;   //  name
-
-    repeated string input  = 4;  // Graph input
-    repeated string output = 5;  // Graph output
-
-    repeated OpDef op      = 6;  // List of operators
-
-	map<string, AttrDef> attr = 11;  // Extended field
-}
-
-// model definition
-message ModelDef
-{
-	string name         = 1;  // name
-	uint32 version      = 2;  // IR Proto verion
-	string custom_version = 3;  // User model version number, passed in by user
-
-    repeated GraphDef graph = 7;  // Graph definition，graph[0] represents the main diagram in modeldef
-
-    map<string, AttrDef> attr = 11;  // Extended field
-}
-
+syntax = "proto3";
+
+package ge.proto;
+
+enum DataType
+{
+    DT_UNDEFINED = 0;  // Used to indicate a DataType field has not been set.
+    DT_FLOAT     = 1;  // float type
+    DT_FLOAT16   = 2;  // fp16 type
+    DT_INT8      = 3;  // int8 type
+    DT_UINT8     = 4;  // uint8 type
+    DT_INT16     = 5;  // int16 type
+    DT_UINT16    = 6;  // uint16 type
+    DT_INT32     = 7;  //
+    DT_INT64     = 8;  // int64 type
+    DT_UINT32    = 9;  // unsigned int32
+    DT_UINT64    = 10;  // unsigned int64
+    DT_BOOL      = 11;  // bool type
+    DT_DOUBLE    = 12; // double type
+    DT_STRING = 13;            // string type
+    DT_DUAL_SUB_INT8 = 14;    /**< dual output int8 type */
+    DT_DUAL_SUB_UINT8 = 15;    /**< dual output uint8 type */
+    DT_COMPLEX64 = 16;         // complex64 type
+    DT_COMPLEX128 = 17;        // complex128 type
+    DT_QINT8 = 18;             // qint8 type
+    DT_QINT16 = 19;            // qint16 type
+    DT_QINT32 = 20;            // qint32 type
+    DT_QUINT8 = 21;            // quint8 type
+    DT_QUINT16 = 22;           // quint16 type
+    DT_RESOURCE  = 23;         // resource type
+    DT_STRING_REF = 24;        // string_ref type
+    DT_DUAL      = 25;              /**< dual output type */
+}
+
+message AttrDef
+{
+    message ListValue
+    {
+        enum ListValueType{
+          VT_LIST_NONE = 0;
+          VT_LIST_STRING = 1;
+          VT_LIST_INT = 2;
+          VT_LIST_FLOAT = 3;
+          VT_LIST_BOOL = 4;
+          VT_LIST_BYTES = 5;
+          VT_LIST_TENSOR_DESC = 6;
+          VT_LIST_TENSOR = 7;
+          VT_LIST_GRAPH = 8;
+          VT_LIST_NAMED_ATTRS = 9;
+          VT_LIST_DATA_TYPE = 10;
+        }
+        repeated bytes s             = 2;                    // "list(string)"
+        repeated int64 i             = 3;  // "list(int)"
+        repeated float f             = 4;   // "list(float)"
+        repeated bool  b             = 5;  // "list(bool)"
+        repeated bytes bt            = 7;
+        repeated TensorDescriptor td = 8;
+        repeated TensorDef t         = 9;
+        repeated GraphDef g          = 10;
+	    repeated NamedAttrs na       = 11;
+	    repeated int64 dt            = 12; // list ge::DataType
+
+	    ListValueType val_type       = 20;
+    }
+
+    message ListListInt{
+        message ListInt{
+            repeated int64 list_i             = 1; // list int
+        }
+        repeated ListInt list_list_i             = 1; // list list int
+    }
+
+    oneof value
+    {
+        bytes            s    = 2;  // "string"
+        int64            i    = 3;  // "int"
+        float            f    = 4;  // "float"
+        bool             b    = 5;  // "bool"
+        bytes            bt   = 7;
+        ListValue        list = 1;   // any "list(...)"
+        NamedAttrs       func = 10;  // Used to support attr nesting
+        TensorDescriptor td   = 11;  // GeTensorDesc type
+        TensorDef        t    = 12;  // GeTensor type
+        GraphDef         g    = 13;  // Graph type
+        ListListInt      list_list_int  = 14;  // List List Int type
+        int64            dt   = 15; // ge::DataType
+    }
+}
+
+// A list of attr names and their values. The whole list is attached
+// with a string name.  E.g., MatMul[T=float].
+message NamedAttrs
+{
+    string               name = 1;
+    map<string, AttrDef> attr = 2;
+}
+
+// Shape / dimension description, using row-major order
+message ShapeDef
+{
+    repeated int64 dim = 1;  // Size of each dimension
+}
+
+// Multidimensional data description
+message TensorDescriptor
+{
+    string   name   = 1;  // Optional parameter, tensor name
+
+    DataType dtype  = 2;  // tensor datatype
+    ShapeDef shape  = 3;  // Shape / dimension
+    string   layout = 4;  // Tensor format, eg: "NCHW", "NHWC", "CHW", "ND"
+
+    bool has_out_attr = 9;
+    int64 size = 10;
+    int64 weight_size = 11;
+    bool reuse_input = 12;
+    bool output_tensor = 13;
+    string device_type = 14;
+    bool input_tensor =15;
+    int64 real_dim_cnt = 16;
+    int64 reuse_input_index = 17;
+    int64 data_offset = 18;
+    int64 cmps_size = 19;
+    string cmps_tab = 20;
+    int64 cmps_tab_offset = 21;
+
+	map<string, AttrDef> attr = 5;  // Set of extra parameter fields
+}
+
+// GeTensor definition
+message TensorDef
+{
+    TensorDescriptor desc = 1;  // Tensor description
+    bytes            data = 2;  // Tensor data
+}
+
+
+// Operator description
+message OpDef
+{
+    string name = 1;  // name
+    string type = 2;  // type
+
+    repeated string input = 5;  // input original op name + outgoing index. op_name：index
+
+    map<string, AttrDef> attr = 10;  // Set of operator parameter fields
+
+    bool has_out_attr = 20;
+    int64 id = 21;
+    int64 stream_id =22;
+    repeated string input_name = 23;
+    repeated string src_name = 24;
+    repeated int64 src_index = 25;
+    repeated string dst_name = 26;
+    repeated int64 dst_index = 27;
+    repeated int64 input_i = 28;
+    repeated int64 output_i = 29;
+    repeated int64 workspace = 30;
+    repeated int64 workspace_bytes = 31;
+    repeated bool is_input_const = 32;
+    repeated TensorDescriptor input_desc = 33;
+    repeated TensorDescriptor output_desc = 34;
+    repeated string subgraph_name = 35;
+}
+
+// Graph definition
+message GraphDef
+{
+    string name   = 1;   //  name
+
+    repeated string input  = 4;  // Graph input
+    repeated string output = 5;  // Graph output
+
+    repeated OpDef op      = 6;  // List of operators
+
+	map<string, AttrDef> attr = 11;  // Extended field
+}
+
+// model definition
+message ModelDef
+{
+	string name         = 1;  // name
+	uint32 version      = 2;  // IR Proto verion
+	string custom_version = 3;  // User model version number, passed in by user
+
+    repeated GraphDef graph = 7;  // Graph definition，graph[0] represents the main diagram in modeldef
+
+    map<string, AttrDef> attr = 11;  // Extended field
+}
+

parser/proto/insert_op.proto

@@ -1,136 +1,136 @@
-syntax = "proto3";
-
-package domi;
-
-message InsertNewOps {
-	repeated AippOpParams aipp_op = 1;
-	repeated MultiShapeOpParams multi_shape_op = 2;
-}
-
-message AippOpParams {
-	enum InputFormat {
-		UNDEFINED = 0;
-		YUV420SP_U8 = 1;
-		XRGB8888_U8 = 2;
-		RGB888_U8   = 3;
-		YUV400_U8   = 4;
-		NC1HWC0DI_FP16 = 5;
-		NC1HWC0DI_S8 = 6;
-		ARGB8888_U8 = 7;
-		YUYV_U8 = 8;
-		YUV422SP_U8 = 9;
-		AYUV444_U8 = 10;
-		RAW10 = 11;
-		RAW12 = 12;
-		RAW16 = 13;
-		RAW24 = 14;
-		RGB16 = 15;
-		RGB20 = 16;
-		RGB24 = 17;
-		RGB8_IR = 18;
-		RGB16_IR = 19;
-		RGB24_IR = 20;
-	}
-
-	enum AippMode {
-		undefined = 0;
-		static = 1;
-		dynamic = 2;
-	}
-
-	// AIPP模式，区分静态AIPP和动态AIPP
-	AippMode aipp_mode = 1;
-
-	// related_input_rank参数为必填，类型为整型，配置范围>=0, <=输入Data算子的个数，默认值为0。
-	// 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;
-
-	// 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。
-	repeated uint32 input_edge_idx = 3;
-
-	// [Begin] 动态AIPP参数，配置静态AIPP时无效
-	uint32 max_src_image_size = 4;
-
-	// 是否支持旋转。默认不支持，开启支持旋转时，会有额外的空间和性能损失
-	bool support_rotation = 5;
-
-	// [End] 动态AIPP参数
-
-
-	// [Begin] 静态AIPP参数，配置动态AIPP时无效
-	InputFormat input_format = 51;
-	bool csc_switch = 52;
-	float cpadding_value = 53;
-	bool rbuv_swap_switch = 54;
-	bool ax_swap_switch = 55;
-	bool single_line_mode = 56;
-
-	int32 src_image_size_w = 57;
-	int32 src_image_size_h = 58;
-
-	bool crop = 59;
-	int32 load_start_pos_w = 60;
-	int32 load_start_pos_h = 61;
-	int32 crop_size_w = 62;
-	int32 crop_size_h = 63;
-
-	bool resize = 64;
-	int32 resize_output_w = 65;
-	int32 resize_output_h = 66;
-
-	bool padding = 67;
-	int32 left_padding_size = 68;
-	int32 right_padding_size = 69;
-	int32 top_padding_size = 70;
-	int32 bottom_padding_size = 71;
-
-	int32 mean_chn_0 = 10;
-	int32 mean_chn_1 = 11;
-	int32 mean_chn_2 = 12;
-	int32 mean_chn_3 = 19;
-	float min_chn_0 = 13;
-	float min_chn_1 = 14;
-	float min_chn_2 = 15;
-	float min_chn_3 = 20;
-	repeated float var_reci_chn_0 = 16;
-	repeated float var_reci_chn_1 = 17;
-	repeated float var_reci_chn_2 = 18;
-	repeated float var_reci_chn_3 = 21;
-
-	repeated int32 matrix_r0c0 = 30;
-	repeated int32 matrix_r0c1 = 31;
-	repeated int32 matrix_r0c2 = 32;
-	repeated int32 matrix_r1c0 = 33;
-	repeated int32 matrix_r1c1 = 34;
-	repeated int32 matrix_r1c2 = 35;
-	repeated int32 matrix_r2c0 = 36;
-	repeated int32 matrix_r2c1 = 37;
-	repeated int32 matrix_r2c2 = 38;
-	repeated int32 output_bias_0 = 39;
-	repeated int32 output_bias_1 = 40;
-	repeated int32 output_bias_2 = 41;
-	repeated int32 input_bias_0 = 42;
-	repeated int32 input_bias_1 = 43;
-	repeated int32 input_bias_2 = 44;
-
-	// [End] 静态AIPP参数
-
-       // The n number that is used for raw/rgbir data into f16 transformation.
-       // The transformation equation is x/(2^n). If set to 0, no transform is performed.
-       uint32 raw_rgbir_to_f16_n = 45;
-}
-
-message MultiShapeOpParams {
-	enum MultiShapeMode {
-		batch      = 0;             //动态batch
-		resolution = 1;             //动态分辨率，扩展用
-	}
-
-	MultiShapeMode    mode                      = 1;        //算子模式
-	uint32            related_input_rank        = 2;        //新增算子插入到哪个输入
-
-
-	repeated uint32 batch_list   = 11; //batch_list值，batch_list的个数是2到8之间
-}
+syntax = "proto3";
+
+package domi;
+
+message InsertNewOps {
+	repeated AippOpParams aipp_op = 1;
+	repeated MultiShapeOpParams multi_shape_op = 2;
+}
+
+message AippOpParams {
+	enum InputFormat {
+		UNDEFINED = 0;
+		YUV420SP_U8 = 1;
+		XRGB8888_U8 = 2;
+		RGB888_U8   = 3;
+		YUV400_U8   = 4;
+		NC1HWC0DI_FP16 = 5;
+		NC1HWC0DI_S8 = 6;
+		ARGB8888_U8 = 7;
+		YUYV_U8 = 8;
+		YUV422SP_U8 = 9;
+		AYUV444_U8 = 10;
+		RAW10 = 11;
+		RAW12 = 12;
+		RAW16 = 13;
+		RAW24 = 14;
+		RGB16 = 15;
+		RGB20 = 16;
+		RGB24 = 17;
+		RGB8_IR = 18;
+		RGB16_IR = 19;
+		RGB24_IR = 20;
+	}
+
+	enum AippMode {
+		undefined = 0;
+		static = 1;
+		dynamic = 2;
+	}
+
+	// AIPP模式，区分静态AIPP和动态AIPP
+	AippMode aipp_mode = 1;
+
+	// related_input_rank参数为必填，类型为整型，配置范围>=0, <=输入Data算子的个数，默认值为0。
+	// 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;
+
+	// 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。
+	repeated uint32 input_edge_idx = 3;
+
+	// [Begin] 动态AIPP参数，配置静态AIPP时无效
+	uint32 max_src_image_size = 4;
+
+	// 是否支持旋转。默认不支持，开启支持旋转时，会有额外的空间和性能损失
+	bool support_rotation = 5;
+
+	// [End] 动态AIPP参数
+
+
+	// [Begin] 静态AIPP参数，配置动态AIPP时无效
+	InputFormat input_format = 51;
+	bool csc_switch = 52;
+	float cpadding_value = 53;
+	bool rbuv_swap_switch = 54;
+	bool ax_swap_switch = 55;
+	bool single_line_mode = 56;
+
+	int32 src_image_size_w = 57;
+	int32 src_image_size_h = 58;
+
+	bool crop = 59;
+	int32 load_start_pos_w = 60;
+	int32 load_start_pos_h = 61;
+	int32 crop_size_w = 62;
+	int32 crop_size_h = 63;
+
+	bool resize = 64;
+	int32 resize_output_w = 65;
+	int32 resize_output_h = 66;
+
+	bool padding = 67;
+	int32 left_padding_size = 68;
+	int32 right_padding_size = 69;
+	int32 top_padding_size = 70;
+	int32 bottom_padding_size = 71;
+
+	int32 mean_chn_0 = 10;
+	int32 mean_chn_1 = 11;
+	int32 mean_chn_2 = 12;
+	int32 mean_chn_3 = 19;
+	float min_chn_0 = 13;
+	float min_chn_1 = 14;
+	float min_chn_2 = 15;
+	float min_chn_3 = 20;
+	repeated float var_reci_chn_0 = 16;
+	repeated float var_reci_chn_1 = 17;
+	repeated float var_reci_chn_2 = 18;
+	repeated float var_reci_chn_3 = 21;
+
+	repeated int32 matrix_r0c0 = 30;
+	repeated int32 matrix_r0c1 = 31;
+	repeated int32 matrix_r0c2 = 32;
+	repeated int32 matrix_r1c0 = 33;
+	repeated int32 matrix_r1c1 = 34;
+	repeated int32 matrix_r1c2 = 35;
+	repeated int32 matrix_r2c0 = 36;
+	repeated int32 matrix_r2c1 = 37;
+	repeated int32 matrix_r2c2 = 38;
+	repeated int32 output_bias_0 = 39;
+	repeated int32 output_bias_1 = 40;
+	repeated int32 output_bias_2 = 41;
+	repeated int32 input_bias_0 = 42;
+	repeated int32 input_bias_1 = 43;
+	repeated int32 input_bias_2 = 44;
+
+	// [End] 静态AIPP参数
+
+       // The n number that is used for raw/rgbir data into f16 transformation.
+       // The transformation equation is x/(2^n). If set to 0, no transform is performed.
+       uint32 raw_rgbir_to_f16_n = 45;
+}
+
+message MultiShapeOpParams {
+	enum MultiShapeMode {
+		batch      = 0;             //动态batch
+		resolution = 1;             //动态分辨率，扩展用
+	}
+
+	MultiShapeMode    mode                      = 1;        //算子模式
+	uint32            related_input_rank        = 2;        //新增算子插入到哪个输入
+
+
+	repeated uint32 batch_list   = 11; //batch_list值，batch_list的个数是2到8之间
+}

parser/tensorflow/graph_optimizer.cc

@@ -23,7 +23,7 @@
 #include "cce/cce.h"
 #include "cce/dnn.h"
 #include "common/debug/log.h"
-#include "common/math/math_util.h"
+#include "parser/common/acl_graph_parser_util.h"
 #include "common/op/ge_op_utils.h"
 #include "common/op_map.h"
 #include "common/types_map.h"
@@ -807,7 +807,7 @@ Status CreateNodeDefBytes(ge::NodePtr n, string originalType, map<string, PIOLis
     for (uint32_t j = 0; j < ge_desc->GetShape().GetDimNum(); ++j) {
       tmp_dim = ge_desc->GetShape().GetDim(j);
       GE_CHECK_GE(tmp_dim, 0);
-      FMK_INT64_MULCHECK(real_size, tmp_dim);
+      PARSER_INT64_MULCHECK(real_size, tmp_dim);
       real_size *= tmp_dim;
     }
     ge::TensorUtils::SetSize(*ge_desc, real_size * size_type);

parser/tensorflow/proto/ge_ir.proto

@@ -1,190 +1,190 @@
-syntax = "proto3";
-
-package ge.proto;
-
-enum DataType
-{
-    DT_UNDEFINED = 0;  // Used to indicate a DataType field has not been set.
-    DT_FLOAT     = 1;  // float type
-    DT_FLOAT16   = 2;  // fp16 type
-    DT_INT8      = 3;  // int8 type
-    DT_UINT8     = 4;  // uint8 type
-    DT_INT16     = 5;  // int16 type
-    DT_UINT16    = 6;  // uint16 type
-    DT_INT32     = 7;  //
-    DT_INT64     = 8;  // int64 type
-    DT_UINT32    = 9;  // unsigned int32
-    DT_UINT64    = 10;  // unsigned int64
-    DT_BOOL      = 11;  // bool type
-    DT_DOUBLE    = 12; // double type
-    DT_STRING = 13;            // string type
-    DT_DUAL_SUB_INT8 = 14;    /**< dual output int8 type */
-    DT_DUAL_SUB_UINT8 = 15;    /**< dual output uint8 type */
-    DT_COMPLEX64 = 16;         // complex64 type
-    DT_COMPLEX128 = 17;        // complex128 type
-    DT_QINT8 = 18;             // qint8 type
-    DT_QINT16 = 19;            // qint16 type
-    DT_QINT32 = 20;            // qint32 type
-    DT_QUINT8 = 21;            // quint8 type
-    DT_QUINT16 = 22;           // quint16 type
-    DT_RESOURCE  = 23;         // resource type
-    DT_STRING_REF = 24;        // string_ref type
-    DT_DUAL      = 25;              /**< dual output type */
-}
-
-message AttrDef
-{
-    message ListValue
-    {
-        enum ListValueType{
-          VT_LIST_NONE = 0;
-          VT_LIST_STRING = 1;
-          VT_LIST_INT = 2;
-          VT_LIST_FLOAT = 3;
-          VT_LIST_BOOL = 4;
-          VT_LIST_BYTES = 5;
-          VT_LIST_TENSOR_DESC = 6;
-          VT_LIST_TENSOR = 7;
-          VT_LIST_GRAPH = 8;
-          VT_LIST_NAMED_ATTRS = 9;
-          VT_LIST_DATA_TYPE = 10;
-        }
-        repeated bytes s             = 2;                    // "list(string)"
-        repeated int64 i             = 3;  // "list(int)"
-        repeated float f             = 4;   // "list(float)"
-        repeated bool  b             = 5;  // "list(bool)"
-        repeated bytes bt            = 7;
-        repeated TensorDescriptor td = 8;
-        repeated TensorDef t         = 9;
-        repeated GraphDef g          = 10;
-	    repeated NamedAttrs na       = 11;
-	    repeated int64 dt            = 12; // list ge::DataType
-
-	    ListValueType val_type       = 20;
-    }
-
-    message ListListInt{
-        message ListInt{
-            repeated int64 list_i             = 1; // list int
-        }
-        repeated ListInt list_list_i             = 1; // list list int
-    }
-
-    oneof value
-    {
-        bytes            s    = 2;  // "string"
-        int64            i    = 3;  // "int"
-        float            f    = 4;  // "float"
-        bool             b    = 5;  // "bool"
-        bytes            bt   = 7;
-        ListValue        list = 1;   // any "list(...)"
-        NamedAttrs       func = 10;  // Used to support attr nesting
-        TensorDescriptor td   = 11;  // GeTensorDesc type
-        TensorDef        t    = 12;  // GeTensor type
-        GraphDef         g    = 13;  // Graph type
-        ListListInt      list_list_int  = 14;  // List List Int type
-        int64            dt   = 15; // ge::DataType
-    }
-}
-
-// A list of attr names and their values. The whole list is attached
-// with a string name.  E.g., MatMul[T=float].
-message NamedAttrs
-{
-    string               name = 1;
-    map<string, AttrDef> attr = 2;
-}
-
-// Shape / dimension description, using row-major order
-message ShapeDef
-{
-    repeated int64 dim = 1;  // Size of each dimension
-}
-
-// Multidimensional data description
-message TensorDescriptor
-{
-    string   name   = 1;  // Optional parameter, tensor name
-
-    DataType dtype  = 2;  // tensor datatype
-    ShapeDef shape  = 3;  // Shape / dimension
-    string   layout = 4;  // Tensor format, eg: "NCHW", "NHWC", "CHW", "ND"
-
-    bool has_out_attr = 9;
-    int64 size = 10;
-    int64 weight_size = 11;
-    bool reuse_input = 12;
-    bool output_tensor = 13;
-    string device_type = 14;
-    bool input_tensor =15;
-    int64 real_dim_cnt = 16;
-    int64 reuse_input_index = 17;
-    int64 data_offset = 18;
-    int64 cmps_size = 19;
-    string cmps_tab = 20;
-    int64 cmps_tab_offset = 21;
-
-	map<string, AttrDef> attr = 5;  // Set of extra parameter fields
-}
-
-// GeTensor definition
-message TensorDef
-{
-    TensorDescriptor desc = 1;  // Tensor description
-    bytes            data = 2;  // Tensor data
-}
-
-
-// Operator description
-message OpDef
-{
-    string name = 1;  // name
-    string type = 2;  // type
-
-    repeated string input = 5;  // input original op name + outgoing index. op_name：index
-
-    map<string, AttrDef> attr = 10;  // Set of operator parameter fields
-
-    bool has_out_attr = 20;
-    int64 id = 21;
-    int64 stream_id =22;
-    repeated string input_name = 23;
-    repeated string src_name = 24;
-    repeated int64 src_index = 25;
-    repeated string dst_name = 26;
-    repeated int64 dst_index = 27;
-    repeated int64 input_i = 28;
-    repeated int64 output_i = 29;
-    repeated int64 workspace = 30;
-    repeated int64 workspace_bytes = 31;
-    repeated bool is_input_const = 32;
-    repeated TensorDescriptor input_desc = 33;
-    repeated TensorDescriptor output_desc = 34;
-    repeated string subgraph_name = 35;
-}
-
-// Graph definition
-message GraphDef
-{
-    string name   = 1;   //  name
-
-    repeated string input  = 4;  // Graph input
-    repeated string output = 5;  // Graph output
-
-    repeated OpDef op      = 6;  // List of operators
-
-	map<string, AttrDef> attr = 11;  // Extended field
-}
-
-// model definition
-message ModelDef
-{
-	string name         = 1;  // name
-	uint32 version      = 2;  // IR Proto verion
-	string custom_version = 3;  // User model version number, passed in by user
-
-    repeated GraphDef graph = 7;  // Graph definition，graph[0] represents the main diagram in modeldef
-
-    map<string, AttrDef> attr = 11;  // Extended field
-}
-
+syntax = "proto3";
+
+package ge.proto;
+
+enum DataType
+{
+    DT_UNDEFINED = 0;  // Used to indicate a DataType field has not been set.
+    DT_FLOAT     = 1;  // float type
+    DT_FLOAT16   = 2;  // fp16 type
+    DT_INT8      = 3;  // int8 type
+    DT_UINT8     = 4;  // uint8 type
+    DT_INT16     = 5;  // int16 type
+    DT_UINT16    = 6;  // uint16 type
+    DT_INT32     = 7;  //
+    DT_INT64     = 8;  // int64 type
+    DT_UINT32    = 9;  // unsigned int32
+    DT_UINT64    = 10;  // unsigned int64
+    DT_BOOL      = 11;  // bool type
+    DT_DOUBLE    = 12; // double type
+    DT_STRING = 13;            // string type
+    DT_DUAL_SUB_INT8 = 14;    /**< dual output int8 type */
+    DT_DUAL_SUB_UINT8 = 15;    /**< dual output uint8 type */
+    DT_COMPLEX64 = 16;         // complex64 type
+    DT_COMPLEX128 = 17;        // complex128 type
+    DT_QINT8 = 18;             // qint8 type
+    DT_QINT16 = 19;            // qint16 type
+    DT_QINT32 = 20;            // qint32 type
+    DT_QUINT8 = 21;            // quint8 type
+    DT_QUINT16 = 22;           // quint16 type
+    DT_RESOURCE  = 23;         // resource type
+    DT_STRING_REF = 24;        // string_ref type
+    DT_DUAL      = 25;              /**< dual output type */
+}
+
+message AttrDef
+{
+    message ListValue
+    {
+        enum ListValueType{
+          VT_LIST_NONE = 0;
+          VT_LIST_STRING = 1;
+          VT_LIST_INT = 2;
+          VT_LIST_FLOAT = 3;
+          VT_LIST_BOOL = 4;
+          VT_LIST_BYTES = 5;
+          VT_LIST_TENSOR_DESC = 6;
+          VT_LIST_TENSOR = 7;
+          VT_LIST_GRAPH = 8;
+          VT_LIST_NAMED_ATTRS = 9;
+          VT_LIST_DATA_TYPE = 10;
+        }
+        repeated bytes s             = 2;                    // "list(string)"
+        repeated int64 i             = 3;  // "list(int)"
+        repeated float f             = 4;   // "list(float)"
+        repeated bool  b             = 5;  // "list(bool)"
+        repeated bytes bt            = 7;
+        repeated TensorDescriptor td = 8;
+        repeated TensorDef t         = 9;
+        repeated GraphDef g          = 10;
+	    repeated NamedAttrs na       = 11;
+	    repeated int64 dt            = 12; // list ge::DataType
+
+	    ListValueType val_type       = 20;
+    }
+
+    message ListListInt{
+        message ListInt{
+            repeated int64 list_i             = 1; // list int
+        }
+        repeated ListInt list_list_i             = 1; // list list int
+    }
+
+    oneof value
+    {
+        bytes            s    = 2;  // "string"
+        int64            i    = 3;  // "int"
+        float            f    = 4;  // "float"
+        bool             b    = 5;  // "bool"
+        bytes            bt   = 7;
+        ListValue        list = 1;   // any "list(...)"
+        NamedAttrs       func = 10;  // Used to support attr nesting
+        TensorDescriptor td   = 11;  // GeTensorDesc type
+        TensorDef        t    = 12;  // GeTensor type
+        GraphDef         g    = 13;  // Graph type
+        ListListInt      list_list_int  = 14;  // List List Int type
+        int64            dt   = 15; // ge::DataType
+    }
+}
+
+// A list of attr names and their values. The whole list is attached
+// with a string name.  E.g., MatMul[T=float].
+message NamedAttrs
+{
+    string               name = 1;
+    map<string, AttrDef> attr = 2;
+}
+
+// Shape / dimension description, using row-major order
+message ShapeDef
+{
+    repeated int64 dim = 1;  // Size of each dimension
+}
+
+// Multidimensional data description
+message TensorDescriptor
+{
+    string   name   = 1;  // Optional parameter, tensor name
+
+    DataType dtype  = 2;  // tensor datatype
+    ShapeDef shape  = 3;  // Shape / dimension
+    string   layout = 4;  // Tensor format, eg: "NCHW", "NHWC", "CHW", "ND"
+
+    bool has_out_attr = 9;
+    int64 size = 10;
+    int64 weight_size = 11;
+    bool reuse_input = 12;
+    bool output_tensor = 13;
+    string device_type = 14;
+    bool input_tensor =15;
+    int64 real_dim_cnt = 16;
+    int64 reuse_input_index = 17;
+    int64 data_offset = 18;
+    int64 cmps_size = 19;
+    string cmps_tab = 20;
+    int64 cmps_tab_offset = 21;
+
+	map<string, AttrDef> attr = 5;  // Set of extra parameter fields
+}
+
+// GeTensor definition
+message TensorDef
+{
+    TensorDescriptor desc = 1;  // Tensor description
+    bytes            data = 2;  // Tensor data
+}
+
+
+// Operator description
+message OpDef
+{
+    string name = 1;  // name
+    string type = 2;  // type
+
+    repeated string input = 5;  // input original op name + outgoing index. op_name：index
+
+    map<string, AttrDef> attr = 10;  // Set of operator parameter fields
+
+    bool has_out_attr = 20;
+    int64 id = 21;
+    int64 stream_id =22;
+    repeated string input_name = 23;
+    repeated string src_name = 24;
+    repeated int64 src_index = 25;
+    repeated string dst_name = 26;
+    repeated int64 dst_index = 27;
+    repeated int64 input_i = 28;
+    repeated int64 output_i = 29;
+    repeated int64 workspace = 30;
+    repeated int64 workspace_bytes = 31;
+    repeated bool is_input_const = 32;
+    repeated TensorDescriptor input_desc = 33;
+    repeated TensorDescriptor output_desc = 34;
+    repeated string subgraph_name = 35;
+}
+
+// Graph definition
+message GraphDef
+{
+    string name   = 1;   //  name
+
+    repeated string input  = 4;  // Graph input
+    repeated string output = 5;  // Graph output
+
+    repeated OpDef op      = 6;  // List of operators
+
+	map<string, AttrDef> attr = 11;  // Extended field
+}
+
+// model definition
+message ModelDef
+{
+	string name         = 1;  // name
+	uint32 version      = 2;  // IR Proto verion
+	string custom_version = 3;  // User model version number, passed in by user
+
+    repeated GraphDef graph = 7;  // Graph definition，graph[0] represents the main diagram in modeldef
+
+    map<string, AttrDef> attr = 11;  // Extended field
+}
+

parser/tensorflow/proto/insert_op.proto

@@ -1,136 +1,136 @@
-syntax = "proto3";
-
-package domi;
-
-message InsertNewOps {
-	repeated AippOpParams aipp_op = 1;
-	repeated MultiShapeOpParams multi_shape_op = 2;
-}
-
-message AippOpParams {
-	enum InputFormat {
-		UNDEFINED = 0;
-		YUV420SP_U8 = 1;
-		XRGB8888_U8 = 2;
-		RGB888_U8   = 3;
-		YUV400_U8   = 4;
-		NC1HWC0DI_FP16 = 5;
-		NC1HWC0DI_S8 = 6;
-		ARGB8888_U8 = 7;
-		YUYV_U8 = 8;
-		YUV422SP_U8 = 9;
-		AYUV444_U8 = 10;
-		RAW10 = 11;
-		RAW12 = 12;
-		RAW16 = 13;
-		RAW24 = 14;
-		RGB16 = 15;
-		RGB20 = 16;
-		RGB24 = 17;
-		RGB8_IR = 18;
-		RGB16_IR = 19;
-		RGB24_IR = 20;
-	}
-
-	enum AippMode {
-		undefined = 0;
-		static = 1;
-		dynamic = 2;
-	}
-
-	// AIPP模式，区分静态AIPP和动态AIPP
-	AippMode aipp_mode = 1;
-
-	// related_input_rank参数为必填，类型为整型，配置范围>=0, <=输入Data算子的个数，默认值为0。
-	// 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;
-
-	// 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。
-	repeated uint32 input_edge_idx = 3;
-
-	// [Begin] 动态AIPP参数，配置静态AIPP时无效
-	uint32 max_src_image_size = 4;
-
-	// 是否支持旋转。默认不支持，开启支持旋转时，会有额外的空间和性能损失
-	bool support_rotation = 5;
-
-	// [End] 动态AIPP参数
-
-
-	// [Begin] 静态AIPP参数，配置动态AIPP时无效
-	InputFormat input_format = 51;
-	bool csc_switch = 52;
-	float cpadding_value = 53;
-	bool rbuv_swap_switch = 54;
-	bool ax_swap_switch = 55;
-	bool single_line_mode = 56;
-
-	int32 src_image_size_w = 57;
-	int32 src_image_size_h = 58;
-
-	bool crop = 59;
-	int32 load_start_pos_w = 60;
-	int32 load_start_pos_h = 61;
-	int32 crop_size_w = 62;
-	int32 crop_size_h = 63;
-
-	bool resize = 64;
-	int32 resize_output_w = 65;
-	int32 resize_output_h = 66;
-
-	bool padding = 67;
-	int32 left_padding_size = 68;
-	int32 right_padding_size = 69;
-	int32 top_padding_size = 70;
-	int32 bottom_padding_size = 71;
-
-	int32 mean_chn_0 = 10;
-	int32 mean_chn_1 = 11;
-	int32 mean_chn_2 = 12;
-	int32 mean_chn_3 = 19;
-	float min_chn_0 = 13;
-	float min_chn_1 = 14;
-	float min_chn_2 = 15;
-	float min_chn_3 = 20;
-	repeated float var_reci_chn_0 = 16;
-	repeated float var_reci_chn_1 = 17;
-	repeated float var_reci_chn_2 = 18;
-	repeated float var_reci_chn_3 = 21;
-
-	repeated int32 matrix_r0c0 = 30;
-	repeated int32 matrix_r0c1 = 31;
-	repeated int32 matrix_r0c2 = 32;
-	repeated int32 matrix_r1c0 = 33;
-	repeated int32 matrix_r1c1 = 34;
-	repeated int32 matrix_r1c2 = 35;
-	repeated int32 matrix_r2c0 = 36;
-	repeated int32 matrix_r2c1 = 37;
-	repeated int32 matrix_r2c2 = 38;
-	repeated int32 output_bias_0 = 39;
-	repeated int32 output_bias_1 = 40;
-	repeated int32 output_bias_2 = 41;
-	repeated int32 input_bias_0 = 42;
-	repeated int32 input_bias_1 = 43;
-	repeated int32 input_bias_2 = 44;
-
-	// [End] 静态AIPP参数
-
-       // The n number that is used for raw/rgbir data into f16 transformation.
-       // The transformation equation is x/(2^n). If set to 0, no transform is performed.
-       uint32 raw_rgbir_to_f16_n = 45;
-}
-
-message MultiShapeOpParams {
-	enum MultiShapeMode {
-		batch      = 0;             //动态batch
-		resolution = 1;             //动态分辨率，扩展用
-	}
-
-	MultiShapeMode    mode                      = 1;        //算子模式
-	uint32            related_input_rank        = 2;        //新增算子插入到哪个输入
-
-
-	repeated uint32 batch_list   = 11; //batch_list值，batch_list的个数是2到8之间
-}
+syntax = "proto3";
+
+package domi;
+
+message InsertNewOps {
+	repeated AippOpParams aipp_op = 1;
+	repeated MultiShapeOpParams multi_shape_op = 2;
+}
+
+message AippOpParams {
+	enum InputFormat {
+		UNDEFINED = 0;
+		YUV420SP_U8 = 1;
+		XRGB8888_U8 = 2;
+		RGB888_U8   = 3;
+		YUV400_U8   = 4;
+		NC1HWC0DI_FP16 = 5;
+		NC1HWC0DI_S8 = 6;
+		ARGB8888_U8 = 7;
+		YUYV_U8 = 8;
+		YUV422SP_U8 = 9;
+		AYUV444_U8 = 10;
+		RAW10 = 11;
+		RAW12 = 12;
+		RAW16 = 13;
+		RAW24 = 14;
+		RGB16 = 15;
+		RGB20 = 16;
+		RGB24 = 17;
+		RGB8_IR = 18;
+		RGB16_IR = 19;
+		RGB24_IR = 20;
+	}
+
+	enum AippMode {
+		undefined = 0;
+		static = 1;
+		dynamic = 2;
+	}
+
+	// AIPP模式，区分静态AIPP和动态AIPP
+	AippMode aipp_mode = 1;
+
+	// related_input_rank参数为必填，类型为整型，配置范围>=0, <=输入Data算子的个数，默认值为0。
+	// 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;
+
+	// 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。
+	repeated uint32 input_edge_idx = 3;
+
+	// [Begin] 动态AIPP参数，配置静态AIPP时无效
+	uint32 max_src_image_size = 4;
+
+	// 是否支持旋转。默认不支持，开启支持旋转时，会有额外的空间和性能损失
+	bool support_rotation = 5;
+
+	// [End] 动态AIPP参数
+
+
+	// [Begin] 静态AIPP参数，配置动态AIPP时无效
+	InputFormat input_format = 51;
+	bool csc_switch = 52;
+	float cpadding_value = 53;
+	bool rbuv_swap_switch = 54;
+	bool ax_swap_switch = 55;
+	bool single_line_mode = 56;
+
+	int32 src_image_size_w = 57;
+	int32 src_image_size_h = 58;
+
+	bool crop = 59;
+	int32 load_start_pos_w = 60;
+	int32 load_start_pos_h = 61;
+	int32 crop_size_w = 62;
+	int32 crop_size_h = 63;
+
+	bool resize = 64;
+	int32 resize_output_w = 65;
+	int32 resize_output_h = 66;
+
+	bool padding = 67;
+	int32 left_padding_size = 68;
+	int32 right_padding_size = 69;
+	int32 top_padding_size = 70;
+	int32 bottom_padding_size = 71;
+
+	int32 mean_chn_0 = 10;
+	int32 mean_chn_1 = 11;
+	int32 mean_chn_2 = 12;
+	int32 mean_chn_3 = 19;
+	float min_chn_0 = 13;
+	float min_chn_1 = 14;
+	float min_chn_2 = 15;
+	float min_chn_3 = 20;
+	repeated float var_reci_chn_0 = 16;
+	repeated float var_reci_chn_1 = 17;
+	repeated float var_reci_chn_2 = 18;
+	repeated float var_reci_chn_3 = 21;
+
+	repeated int32 matrix_r0c0 = 30;
+	repeated int32 matrix_r0c1 = 31;
+	repeated int32 matrix_r0c2 = 32;
+	repeated int32 matrix_r1c0 = 33;
+	repeated int32 matrix_r1c1 = 34;
+	repeated int32 matrix_r1c2 = 35;
+	repeated int32 matrix_r2c0 = 36;
+	repeated int32 matrix_r2c1 = 37;
+	repeated int32 matrix_r2c2 = 38;
+	repeated int32 output_bias_0 = 39;
+	repeated int32 output_bias_1 = 40;
+	repeated int32 output_bias_2 = 41;
+	repeated int32 input_bias_0 = 42;
+	repeated int32 input_bias_1 = 43;
+	repeated int32 input_bias_2 = 44;
+
+	// [End] 静态AIPP参数
+
+       // The n number that is used for raw/rgbir data into f16 transformation.
+       // The transformation equation is x/(2^n). If set to 0, no transform is performed.
+       uint32 raw_rgbir_to_f16_n = 45;
+}
+
+message MultiShapeOpParams {
+	enum MultiShapeMode {
+		batch      = 0;             //动态batch
+		resolution = 1;             //动态分辨率，扩展用
+	}
+
+	MultiShapeMode    mode                      = 1;        //算子模式
+	uint32            related_input_rank        = 2;        //新增算子插入到哪个输入
+
+
+	repeated uint32 batch_list   = 11; //batch_list值，batch_list的个数是2到8之间
+}

parser/tensorflow/scope/scope_pass_manager.cc

@@ -15,7 +15,7 @@
  */
 
 #include "parser/tensorflow/scope/scope_pass_manager.h"
-#include "common/ge/ge_util.h"
+#include "parser/common/acl_graph_parser_util.h"
 #include "common/util.h"
 #include "common/util/error_manager/error_manager.h"
 #include "framework/common/debug/ge_log.h"
@@ -25,7 +25,7 @@
 namespace ge {
 shared_ptr<ScopeGraph> ScopePassManager::BuildScopeGraph(domi::tensorflow::GraphDef *graph_def) {
   GE_CHK_BOOL_EXEC(graph_def != nullptr, return nullptr, "graph_def is nullptr");
-  scope_graph_ = ge::MakeShared<ScopeGraph>();
+  scope_graph_ = ge::parser::MakeShared<ScopeGraph>();
   if (scope_graph_ == nullptr) {
     GELOGE(FAILED, "Scope graph make shared failed.");
     return nullptr;

parser/tensorflow/tensorflow_constant_parser.cc

@@ -19,7 +19,7 @@
 #include <memory>
 #include <vector>
 #include "common/debug/log.h"
-#include "common/ge/ge_util.h"
+#include "parser/common/acl_graph_parser_util.h"
 #include "common/op/ge_op_utils.h"
 #include "parser/common/op_def/constant_op.h"
 #include "parser/common/op_def/ir_pb_converter.h"
@@ -68,7 +68,7 @@ Status TensorFlowConstantParser::ParseValue(const domi::tensorflow::NodeDef *nod
 
   const domi::tensorflow::TensorProto &tensor = attr_value.tensor();
 
-  GeTensorPtr weight = ge::MakeShared<ge::GeTensor>();
+  GeTensorPtr weight = ge::parser::MakeShared<ge::GeTensor>();
   GE_CHECK_NOTNULL(weight);
   int64_t dataType = 0;
   GE_CHK_BOOL_RET_STATUS(ge::AttrUtils::GetInt(opDesc, TENSORFLOW_ATTR_DTYPE, dataType), INTERNAL_ERROR,

parser/tensorflow/tensorflow_fusion_op_parser.cc

@@ -17,7 +17,7 @@
 #include "parser/tensorflow/tensorflow_fusion_op_parser.h"
 #include <memory>
 #include "common/debug/log.h"
-#include "common/ge/ge_util.h"
+#include "parser/common/acl_graph_parser_util.h"
 #include "common/util.h"
 #include "framework/common/debug/ge_log.h"
 #include "omg/omg.h"
@@ -132,7 +132,7 @@ Status TensorFlowFusionOpParser::ParseWeightFromConst(const NodeDef *node_def, g
   GE_CHECK_NOTNULL(node_def);
   TensorProto tensor;
   GE_CHK_STATUS_RET(GetTensorFromNode(node_def, tensor), "get tensor failed.");
-  weight = ge::MakeShared<ge::GeTensor>();
+  weight = ge::parser::MakeShared<ge::GeTensor>();
   GE_CHECK_NOTNULL(weight);
   domi::tensorflow::DataType data_type = tensor.dtype();
   GE_CHK_STATUS_RET(

parser/tensorflow/tensorflow_parser.cc

@@ -19,7 +19,7 @@
 #include <iostream>
 #include "parser/common/convert/pb2json.h"
 #include "common/debug/log.h"
-#include "common/ge/ge_util.h"
+#include "parser/common/acl_graph_parser_util.h"
 #include "common/util/error_manager/error_manager.h"
 #include "external/graph/operator_factory.h"
 #include "external/parser/tensorflow_parser.h"
@@ -99,7 +99,7 @@ graphStatus aclgrphParseTensorFlow(const char *model_file, ge::Graph &graph) {
   (void)acl_graph_parse_util.AclParserInitialize(options);
 
   // Create an empty computegraph
-  ge::ComputeGraphPtr compute_graph = ge::MakeShared<ge::ComputeGraph>("tmpGraph");
+  ge::ComputeGraphPtr compute_graph = ge::parser::MakeShared<ge::ComputeGraph>("tmpGraph");
   GE_CHECK_NOTNULL(compute_graph);
 
   graph = ge::GraphUtils::CreateGraphFromComputeGraph(compute_graph);
@@ -172,7 +172,7 @@ Status GenSubgraphParseTasks(const ge::ComputeGraphPtr &parent_graph, std::deque
 
       // A function may be referenced multiple times in TF, change the graph name to ensure it is unique in GE
       auto unique_name = node->GetName() + std::to_string(i) + subgraph_iname;
-      auto subgraph = ge::MakeShared<ge::ComputeGraph>(unique_name);
+      auto subgraph = ge::parser::MakeShared<ge::ComputeGraph>(unique_name);
       if (subgraph == nullptr) {
         GELOGE(OUT_OF_MEMORY, "Failed to alloc subgraph %s", subgraph_iname.c_str());
         return OUT_OF_MEMORY;
@@ -246,7 +246,7 @@ Status TensorFlowModelParser::DefunToPartitionedCall(const domi::tensorflow::Nod
     return FAILED;
   }
 
-  op = ge::MakeShared<ge::OpDesc>(op_name, ge::parser::PARTITIONEDCALL);
+  op = ge::parser::MakeShared<ge::OpDesc>(op_name, ge::parser::PARTITIONEDCALL);
   GE_CHECK_NOTNULL(op);
 
   size_t input_tensor_num = 0;
@@ -284,7 +284,7 @@ Status TensorFlowModelParser::TransNodeToOpDesc(const domi::tensorflow::NodeDef
   ge::Operator op_factory = ge::OperatorFactory::CreateOperator(node_name, op_type);
   if (op_factory.GetName() != node_name || op_type == ge::parser::DATA) {
     if (std::find(kMakeOperatorNotByIr.begin(), kMakeOperatorNotByIr.end(), op_type) != kMakeOperatorNotByIr.end()) {
-      op = ge::MakeShared<ge::OpDesc>(node_name, op_type);
+      op = ge::parser::MakeShared<ge::OpDesc>(node_name, op_type);
       GE_CHECK_NOTNULL(op);
     } else if (node_name == op_type) {
       // Trans @tensorflow.python.framework.Defun(...) to PartitionedCall.
@@ -809,7 +809,7 @@ Status TensorFlowModelParser::ParseNodeDef(TensorFlowModelParser *parser, ge::Co
   ge::Operator op_factory = ge::OperatorFactory::CreateOperator(node_name, op_type);
   if (op_factory.GetName() != node_name) {
     if (std::find(kMakeOperatorNotByIr.begin(), kMakeOperatorNotByIr.end(), op_type) != kMakeOperatorNotByIr.end()) {
-      op = ge::MakeShared<ge::OpDesc>(node_name, op_type);
+      op = ge::parser::MakeShared<ge::OpDesc>(node_name, op_type);
       GE_CHECK_NOTNULL(op);
     } else if (node_name == op_type) {
       GE_RETURN_IF_ERROR(parser->DefunToPartitionedCall(node_def, op));
@@ -939,7 +939,7 @@ Status TensorFlowModelParser::AddFmkNode(ge::ComputeGraphPtr &graph, shared_ptr<
   ThreadPool executor(kThreadNum);
   std::mutex graphMutex;
   std::vector<std::future<Status>> vectorFuture(op_node_list_size);
-  ge::ComputeGraphPtr graph_tmp = ge::MakeShared<ge::ComputeGraph>("tmpGraph");
+  ge::ComputeGraphPtr graph_tmp = ge::parser::MakeShared<ge::ComputeGraph>("tmpGraph");
   GE_CHECK_NOTNULL(graph_tmp);
   for (size_t j = 0; j < op_node_list_size; j++) {
     const string op_node_name = op_node_name_list[j];

parser/tensorflow/tensorflow_parser_register.h

@@ -25,7 +25,7 @@
 #include "framework/omg/parser/op_parser.h"
 #include "parser/common/op_def/ir_pb_converter.h"
 #include "parser/common/op_def/operator.h"
-#include "common/ge/ge_util.h"
+#include "parser/common/acl_graph_parser_util.h"
 #include "parser/common/op_parser_factory.h"
 #include "parser/tensorflow/tensorflow_op_parser.h"
 #include "proto/tensorflow/node_def.pb.h"
@@ -72,7 +72,7 @@ class TensorflowParserBuilder : public TensorflowWeightParserBuilder {
   }
 
   bool Finalize() override {
-    auto op_parser_adapter = ge::MakeShared<TensorflowOpParserAdapter<Param>>(*this);
+    auto op_parser_adapter = ge::parser::MakeShared<TensorflowOpParserAdapter<Param>>(*this);
     if (op_parser_adapter == nullptr) {
       GELOGE(FAILED, "Op parser adapter is null.");
     }
@@ -102,7 +102,7 @@ class TensorflowOpParserAdapter : public TensorFlowOpParser {
   Status ParseParams(const Message *op_src, ge::OpDescPtr &op_dest) override {
     const domi::tensorflow::NodeDef *node = static_cast<const domi::tensorflow::NodeDef *>(op_src);
     GE_CHECK_NOTNULL(node);
-    std::shared_ptr<Param> param = ge::MakeShared<Param>();
+    std::shared_ptr<Param> param = ge::parser::MakeShared<Param>();
     if (param == nullptr) {
       GELOGE(domi::FAILED, "Param is null");
       return domi::FAILED;

parser/tensorflow/tensorflow_reshape_parser.cc

@@ -22,7 +22,7 @@
 #include "graph/utils/type_utils.h"
 #include "parser/common/op_parser_factory.h"
 #include "parser/tensorflow/tensorflow_util.h"
-#include "common/math/math_util.h"
+#include "parser/common/acl_graph_parser_util.h"
 
 using domi::TENSORFLOW;
 using namespace ge::parser;
@@ -48,7 +48,7 @@ Status TensorFlowReshapeParser::ParseDesc(const domi::tensorflow::AttrValue &att
     GE_IF_BOOL_EXEC(tmp_dim < 0, real_size = tmp_dim * (-1) * real_size; continue;);
     real_size *= tmp_dim;
   }
-  FMK_INT64_MULCHECK(real_size, size_type);
+  PARSER_INT64_MULCHECK(real_size, size_type);
   ge::TensorUtils::SetSize(ge_desc, real_size * size_type);
   ge::TensorUtils::SetRealDimCnt(ge_desc, ge_desc.GetShape().GetDimNum());
   GELOGI("after translate tf_desc, datatype: %s, format: %s, real size: %u, size_type: %u",

parser/tensorflow/tensorflow_squeeze_parser.cc

@@ -25,7 +25,7 @@
 #include "framework/omg/parser/parser_inner_ctx.h"
 #include "graph/utils/type_utils.h"
 #include "parser/common/op_parser_factory.h"
-#include "common/math/math_util.h"
+#include "parser/common/acl_graph_parser_util.h"
 
 using domi::tensorflow::AttrValue;
 using std::vector;
@@ -52,10 +52,10 @@ Status TensorFlowSqueezeParser::ParseDesc(const domi::tensorflow::AttrValue &att
   for (uint32_t j = 0; j < ge_desc.GetShape().GetDimNum(); ++j) {
     tmp_dim = ge_desc.GetShape().GetDim(j);
     GE_IF_BOOL_EXEC(tmp_dim < 0, real_size = tmp_dim * (-1) * real_size; continue;);
-    FMK_INT64_MULCHECK(real_size, tmp_dim);
+    PARSER_INT64_MULCHECK(real_size, tmp_dim);
     real_size *= tmp_dim;
   }
-  FMK_INT64_MULCHECK(real_size, size_type);
+  PARSER_INT64_MULCHECK(real_size, size_type);
   ge::TensorUtils::SetSize(ge_desc, real_size * size_type);
   ge::TensorUtils::SetRealDimCnt(ge_desc, ge_desc.GetShape().GetDimNum());
   GELOGD("after translate tf_desc, datatype: %s, format: %s, real size: %u, size_type: %u",

parser/tensorflow/tensorflow_util.cc

@@ -19,7 +19,6 @@
 #include <cstdlib>
 #include <iostream>
 #include <memory>
-#include "common/math/math_util.h"
 #include "framework/common/debug/ge_log.h"
 #include "framework/common/debug/log.h"
 #include "framework/common/op/ge_op_utils.h"