diff --git a/core/runtime/execute_engine.cpp b/core/runtime/execute_engine.cpp
index 64b111750f..11547a2312 100644
--- a/core/runtime/execute_engine.cpp
+++ b/core/runtime/execute_engine.cpp
@@ -121,7 +121,24 @@ void setup_input_tensors(
       // Shape tensor inputs are casted to int64 explicitly.
       // Refer to
       // https://github.com/NVIDIA/TensorRT/blob/d2f4ef789a9a6ffdf37b55c3f81b486225f6b380/samples/common/sampleInference.cpp#L435
-      auto input_cpu = inputs[i].clone().contiguous().cpu().to(torch::kInt64);
+      at::Tensor cloned_input;
+
+      // Check if it's a scalar tensor (0-dimensional)
+      if (inputs[i].dim() == 0 && inputs[i].numel() == 1) {
+        // It's a scalar tensor, create a proper tensor from the scalar value
+        int64_t scalar_value = inputs[i].item<int64_t>();
+        LOG_DEBUG("Input " << i << " is a scalar tensor with value: " << scalar_value);
+        cloned_input = torch::tensor({scalar_value}, torch::kInt64);
+        LOG_DEBUG("cloned_input dim: " << cloned_input.dim() << " ; numel: " << cloned_input.numel());
+      } else {
+        // It's a regular tensor
+        LOG_DEBUG(
+            "Input " << i << " is a regular tensor"
+                     << " inputs[i]: " << inputs[i]);
+        cloned_input = inputs[i].clone();
+      }
+      auto input_cpu = cloned_input.contiguous().cpu().to(torch::kInt64);
+
       std::vector<int64_t> inputs_cpu_vec(
           input_cpu.data_ptr<int64_t>(), input_cpu.data_ptr<int64_t>() + input_cpu.numel());
       inputShapeTensorValues.emplace_back(inputs_cpu_vec);
diff --git a/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py b/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
index fc76b20141..dda5929d4b 100644
--- a/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
+++ b/py/torch_tensorrt/dynamo/runtime/_PythonTorchTensorRTModule.py
@@ -430,7 +430,7 @@ def create_output_allocator(self) -> None:
     def forward(self, *inputs: torch.Tensor) -> torch.Tensor | Tuple[torch.Tensor, ...]:
 
         def run_standard_execution() -> torch.Tensor | Tuple[torch.Tensor, ...]:
-            shape_changed = self.validate_input_shapes(inputs)
+            shape_changed = self.validate_input_shapes(contiguous_inputs)
             (
                 need_cudagraphs_record,
                 can_use_pre_allocated_outputs,