code: def cast_to_common_dtype(tensors):
      """Cast a list of tensors to a common dtype.
  
      If any tensor is floating-point, they will all be casted to the most-precise
      floating-point dtype. Otherwise the tensors are not casted.
  
      Args:
          tensors: A list of tensors.
  
      Returns:
          Same list, casted to a common dtype.
      """
      highest_float = None
      highest_float_size = (
          -1
      )  # Initially set to an impossible value for comparison
      for x in tensors:
          dtype = backend.standardize_dtype(x.dtype)
          if is_float(dtype):
              if (
                  highest_float is None
                  or dtype_size(dtype) > highest_float_size
              ):
                  highest_float = dtype
                  highest_float_size = dtype_size(dtype)
              elif dtype == "float16" and highest_float == "bfloat16":
                  highest_float = "float32"
                  highest_float_size = dtype_size(highest_float)
      if highest_float:
          tensors = [ops.cast(x, highest_float) for x in tensors]
      return tensors
  
imports: from keras import backend
  from keras import ops
label_desc: Use image node_id 3 for calling a global function with example usage: cast_to_common_dtype(tensors) and returns: tensors