code: def _should_pack(arg):
      """Determines whether the caller needs to pack the argument in a tuple.
  
      If user-defined function returns a list of tensors, `nest.flatten()` and
      `ops.convert_to_tensor()` and would conspire to attempt to stack those tensors
      into a single tensor because the tf.data version of `nest.flatten()` does
      not recurse into lists. Since it is more likely that the list arose from
      returning the result of an operation (such as `tf.numpy_function()`) that
      returns a list of not-necessarily-stackable tensors, we treat the returned
      value as a `tuple` instead. A user wishing to pack the return value into a
      single tensor can use an explicit `tf.stack()` before returning.
  
      Args:
        arg: argument to check
  
      Returns:
        Indication of whether the caller needs to pack the argument in a tuple.
      """
      return isinstance(arg, list)
  
imports: import warnings
  from tensorflow.python.autograph.core import ag_ctx
  from tensorflow.python.autograph.impl import api
  from tensorflow.python.data.ops import debug_mode
  from tensorflow.python.data.util import nest
  from tensorflow.python.data.util import structure
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import function
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import script_ops
  from tensorflow.python.util import function_utils
  from tensorflow.python.util import variable_utils
label_desc: Use image node_id 1 for calling a global function with example usage: _should_pack(arg) and returns: isinstance