pytorch
diff --git a/‎core/conversion/conversion.cpp
+26-3 b/‎core/conversion/conversion.cpp
+26-3
diff --git a/‎core/conversion/converters/converter_util.cpp
+7 b/‎core/conversion/converters/converter_util.cpp
+7
diff --git a/‎core/conversion/converters/converter_util.h
+3 b/‎core/conversion/converters/converter_util.h
+3
@@ -1,6 +1,11 @@
+<<<<<<< HEAD
 #include <sstream>
 
+=======
+>>>>>>> 367dd7bb... chore: refactor applyIdentityOp
 #include "core/conversion/conversion.h"
+#include <torch/torch.h>
+#include <sstream>
 #include "core/conversion/conversionctx/ConversionCtx.h"
 #include "core/conversion/converters/converters.h"
 #include "core/conversion/evaluators/evaluators.h"
@@ -234,10 +239,28 @@ void MarkOutputs(ConversionCtx* ctx, at::ArrayRef<const torch::jit::Value*> outp
         }
       }
     } else {
-      std::string name = std::string("output_") + std::to_string(ctx->num_outputs);
+      bool setOutput = false;
+      auto num_inputs = ctx->net->getNbInputs();
       auto out_tensor = it->second;
-      out_tensor->setName(name.c_str());
-      ctx->net->markOutput(*out_tensor);
+      std::string name = std::string("output_") + std::to_string(ctx->num_outputs);
+
+      // Check if the output tensor is one of the inputs to the network. If so, apply an identity layer to it.
+      for (int64_t i = 0; i < num_inputs; i++) {
+        if (out_tensor == ctx->net->getInput(i)) {
+          LOG_DEBUG(
+              "One of the inputs named "
+              << ctx->net->getInput(i)->getName()
+              << " to the network is marked as an output tensor. Applying an identity layer and marking this tensor as output");
+          auto id_out_tensor = converters::applyIdentityOp(ctx, out_tensor, name);
+          ctx->net->markOutput(*id_out_tensor);
+          setOutput = true;
+        }
+      }
+
+      if (!setOutput) {
+        out_tensor->setName(name.c_str());
+        ctx->net->markOutput(*out_tensor);
+      }
       LOG_INFO(
           ctx->logger, "Marking Output " << out->debugName() << " named " << name << " in engine (ctx.MarkOutput)");
       ctx->num_outputs += 1;
 
@@ -121,6 +121,13 @@ nvinfer1::ILayer* add_elementwise(
   return ele;
 }
 
+nvinfer1::ITensor* applyIdentityOp(ConversionCtx* ctx, nvinfer1::ITensor* tensor, const std::string& tensor_name) {
+  auto id_layer = ctx->net->addIdentity(*tensor);
+  auto id_out_tensor = id_layer->getOutput(0);
+  id_out_tensor->setName(tensor_name.c_str());
+  return id_out_tensor;
+}
+
 nvinfer1::ITensor* castITensor(ConversionCtx* ctx, nvinfer1::ITensor* tensor, nvinfer1::DataType dtype) {
   if (tensor->getType() != dtype) {
     std::ostringstream tensor_id;
 
@@ -41,6 +41,9 @@ nvinfer1::ILayer* add_elementwise(
     nvinfer1::ITensor* other,
     const std::string& name);
 
+// Apply an identity operation on a tensor. Used in the case where an input is an output to a network.
+nvinfer1::ITensor* applyIdentityOp(ConversionCtx* ctx, nvinfer1::ITensor* tensor, const std::string& name);
+
 // If an ITensor is of a type not dtype, add an Identity layer to cast it to dtype
 nvinfer1::ITensor* castITensor(ConversionCtx* ctx, nvinfer1::ITensor* tensor, nvinfer1::DataType dtype);