code: def alias_tensors(*args):
      """Wraps any Tensor arguments with an identity op.
  
      Any other argument, including Variables, is returned unchanged.
  
      Args:
        *args: Any arguments. Must contain at least one element.
  
      Returns:
        Same as *args, with Tensor instances replaced as described.
  
      Raises:
        ValueError: If args doesn't meet the requirements.
      """
  
      def alias_if_tensor(a):
          return (
              array_ops.identity(a)
              if isinstance(a, tensor.Tensor)
              else a
          )
  
      # TODO(mdan): Recurse into containers?
      # TODO(mdan): Anything we can do about variables? Fake a scope reuse?
      if len(args) > 1:
          return (alias_if_tensor(a) for a in args)
      elif len(args) == 1:
          return alias_if_tensor(args[0])
  
      raise ValueError("at least one argument required")
  
imports: from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import gen_math_ops
  from tensorflow.python.ops import math_ops
label_desc: Use image node_id 1 for calling a global function with example usage: alias_tensors() and returns: unknown, unknown, alias_if_tensor