1 files changed, 4 insertions, 8 deletions
diff --git a/src/backends/tosaCommon/operatorMappings/TransposeConv2dOperator.cpp b/src/backends/tosaCommon/operatorMappings/TransposeConv2dOperator.cpp
index 8c2ae9f2b5..81d58e04fe 100644
--- a/src/backends/tosaCommon/operatorMappings/TransposeConv2dOperator.cpp
+++ b/src/backends/tosaCommon/operatorMappings/TransposeConv2dOperator.cpp
@@ -12,7 +12,7 @@ TosaSerializationBasicBlock* ConvertTransposeConv2dToTosaOperator(const Layer* l
                                                                   const std::vector<const TensorInfo*>& outputs,
                                                                   const TransposeConvolution2dDescriptor* descriptor)
 {
-    std::string input0Name = std::string("input0_");
+    std::string input0Name = std::string("input_");
     std::string input1Name = std::string("constant_") + GetUniqueTosaMappingID();
     std::string input2Name = std::string("constant_") + GetUniqueTosaMappingID();
     std::string outputName = std::string("output0_");
@@ -22,12 +22,8 @@ TosaSerializationBasicBlock* ConvertTransposeConv2dToTosaOperator(const Layer* l
     // using the previous and following layers so the graph is connected correctly. For validation this doesn't matter.
     if(layer != nullptr)
     {
-        // Get the layers connected to the input slots and determine unique tensor names.
-        Layer& connectedInputLayer = layer->GetInputSlot(0).GetConnectedOutputSlot()->GetOwningLayer();
-        input0Name = GenerateUniqueName(connectedInputLayer, 0);
-
-        // Determine unique output tensor name.
-        outputName = GenerateUniqueOutputName(*layer, 0);
+        input0Name = GenerateUniqueInputName(layer->GetInputSlot(0));
+        outputName = GenerateUniqueOutputName(*layer);
     }
 
     std::vector<TosaSerializationTensor*> tensors;
@@ -37,7 +33,7 @@ TosaSerializationBasicBlock* ConvertTransposeConv2dToTosaOperator(const Layer* l
     // Only add tensor if connected layer is an input layer.
     // As intermediate or constant tensors will be created separately.
     // There also can't be duplicate tensors.
-    if(input0Name.find("input0_") != std::string::npos)
+    if(input0Name.find("input_") != std::string::npos)
     {
         std::vector<int32_t> inputShape0 = GetTosaTensorShape(inputs[0]->GetShape());
         DType inputDType0 = ArmNNToDType(inputs[0]->GetDataType());