!7344 [lite] fix unsupported op print and caffe multiple inputs

Merge pull request !7344 from 徐安越/r1.0

mindspore/lite/tools/converter/parser/caffe/caffe_model_parser.cc

@@ -243,12 +243,12 @@ STATUS CaffeModelParser::ParseLayer(const caffe::NetParameter &proto, const caff
       auto status_node = nodeParser->Parse(layer, layerP, op.get(), &weightVec);
       if (status_node != RET_OK) {
         interrupt = true;
-        if (status_node == RET_NOT_SUPPORT) {
+        if (status_node == RET_NOT_FIND_OP) {
           NoSupportOp::GetInstance()->InsertOp(layer.type());
         } else {
           MS_LOG(ERROR) << "Parse weight for " << layer.name() << " Failed!";
         }
-        status = (status == RET_OK ? RET_NOT_FIND_OP : status);
+        status = (status == RET_OK ? status_node : status);
         continue;
       }
 
@@ -263,7 +263,7 @@ STATUS CaffeModelParser::ParseLayer(const caffe::NetParameter &proto, const caff
       if (status_node != RET_OK) {
         interrupt = true;
         MS_LOG(ERROR) << "Set Op " << layer.name() << " Output Index Failed!";
-        status = (status == RET_OK ? RET_NOT_FIND_OP : status);
+        status = (status == RET_OK ? status_node : status);
         continue;
       }
 
@@ -280,8 +280,15 @@ STATUS CaffeModelParser::GetModelInput(const caffe::NetParameter &proto, TensorC
       continue;
     }
     std::unique_ptr<schema::TensorT> msTensor = std::make_unique<schema::TensorT>();
-    for (int j = 0; j < proto.input_dim_size(); j++) {
-      msTensor->dims.push_back(proto.input_dim(j));
+    if (proto.input_dim_size() > 4) {
+      int step = proto.input_dim_size() / proto.input_size();
+      for (int j = i * step; j < (i + 1) * step; j++) {
+        msTensor->dims.push_back(proto.input_dim(j));
+      }
+    } else {
+      for (int j = 0; j < proto.input_dim_size(); j++) {
+        msTensor->dims.push_back(proto.input_dim(j));
+      }
     }
     msTensor->refCount = schema::NodeType::NodeType_ValueNode;
     msTensor->dataType = kNumberTypeFloat32;

mindspore/lite/tools/converter/parser/onnx/onnx_deconv_parser.cc

@@ -156,8 +156,8 @@ STATUS OnnxDeConvParser::Parse(const onnx::GraphProto &onnx_graph, const onnx::N
 
   if (attr->group != 1) {
     if (!ParseGroupDeConvolution(attr, op)) {
-      MS_LOG(ERROR) << "Convert DeConvolution to DeDepthwise failed";
-      return RET_ERROR;
+      MS_LOG(ERROR) << "Convert DeConvolution to DeDepthwise failed, generalized group deconv hasn't support";
+      return RET_NOT_SUPPORT;
     }
   } else {
     op->primitive->value.type = schema::PrimitiveType_DeConv2D;

mindspore/lite/tools/converter/parser/onnx/onnx_model_parser.cc

@@ -271,7 +271,7 @@ STATUS OnnxModelParser::ParseOnnxNodeToDstOp(const onnx::GraphProto &onnx_graph,
   auto status = node_parser->Parse(onnx_graph, onnx_node, dst_op);
   if (status != RET_OK) {
     interrupt = true;
-    if (status == RET_NOT_SUPPORT) {
+    if (status == RET_NOT_FIND_OP) {
       NoSupportOp::GetInstance()->InsertOp(onnx_node.op_type());
     } else {
       MS_LOG(ERROR) << "parser onnx node " << onnx_node.op_type() << " attr failed";

mindspore/lite/tools/converter/parser/tflite/tflite_model_parser.cc

@@ -100,10 +100,14 @@ STATUS TfliteModelParser::ConvertOp(const std::unique_ptr<tflite::ModelT> &tflit
   for (const auto &tflite_op : tflite_subgraph->operators) {
     auto tflite_op_type = (tflite_model->operator_codes[tflite_op->opcode_index])->builtin_code;
     auto op_type = GetMSOpType(tflite_op_type);
-    if (op_type == "CUSTOM") {
+    if (op_type == "Custom") {
       auto custom_type = (tflite_model->operator_codes[tflite_op->opcode_index])->custom_code;
-      MS_LOG(ERROR) << "CUSTOM op is not supported, the type is " << custom_type;
-      return RET_ERROR;
+      if (custom_type != "TFLite_Detection_PostProcess") {
+        MS_LOG(ERROR) << "CUSTOM op is not supported, the type is " << custom_type;
+        NoSupportOp::GetInstance()->InsertOp(custom_type);
+        status = (status == RET_OK ? RET_NOT_FIND_OP : status);
+        continue;
+      }
     }
 
     auto op = std::make_unique<schema::CNodeT>();
@@ -121,7 +125,7 @@ STATUS TfliteModelParser::ConvertOp(const std::unique_ptr<tflite::ModelT> &tflit
       status = node_parser->Parse(tflite_op, tflite_subgraph->tensors, tflite_model->buffers, op.get(), &tensorsId,
                                   &tensorsFormat, &tensorsIdMap);
       if (status != RET_OK) {
-        if (status == RET_NOT_SUPPORT) {
+        if (status == RET_NOT_FIND_OP) {
           NoSupportOp::GetInstance()->InsertOp(op_type);
         } else {
           MS_LOG(ERROR) << "node " << op_type.c_str() << " parser failed";

mindspore/lite/tools/converter/parser/tflite/tflite_pad_parser.cc

@@ -73,11 +73,11 @@ STATUS TflitePadParser::Parse(const std::unique_ptr<tflite::OperatorT> &tflite_o
         break;
       default:
         MS_LOG(ERROR) << "paddingmode:" << tflite_attr->mode << " don't support";
-        return RET_INVALID_OP_ATTR;
+        return RET_NOT_SUPPORT;
       }
   } else {
     MS_LOG(ERROR) << "this pad:" << node_name << " hasn't been supported";
-    return RET_NOT_SUPPORT;
+    return RET_NOT_FIND_OP;
   }
 
   op->primitive->value.type = schema::PrimitiveType_Pad;

mindspore/lite/tools/converter/parser/tflite/tflite_reduce_parser.cc

@@ -72,7 +72,7 @@ STATUS TfliteReduceParser::Parse(const std::unique_ptr<tflite::OperatorT> &tflit
   } else if (std::strcmp(node_name, "ReduceAny") == 0) {
     // attr->mode;
     MS_LOG(ERROR) << "ms-lite haven't supported REDUCE_ANY now";
-    return RET_NOT_FIND_OP;
+    return RET_NOT_SUPPORT;
   }
 
   if (GetTfliteData(tflite_op->inputs[1], tflite_tensors, tflite_model_buffer, attr->axes)) {