def maybe_handle_quantized_inputs(self, node: InternalTorchIRNode) -> None:
        """
        If a node's op doesn't support quantized inputs but gets one, this will wire it to
        receive a dequantized version of it.
        """

        op_type = node.kind
        if op_type in {"quantize_per_tensor", "dequantize"} or "quantized::" in op_type:
            # Op can handle quantized inputs. Nothing to do here.
            return

        for input in node.inputs:
            # In EXIR, input can be a literal and thus have no name
            if not isinstance(input, str) or self.get_quantization_info(input) is None:
                # Not a quantized tensor
                continue

            # We need a dequantized version of the input to feed to the op.
            dequantized_var, _ = self.get_dequantized_var(input)
            node.replace_name(input, dequantized_var.name)

        If a node's op doesn't support quantized inputs but gets one, this will wire it to
        receive a dequantized version of it.
        
coremltools/converters/mil/frontend/torch/converter.py