code: def _result_flat_signature_to_batchable_tensor_spec(
      result_flat_signature,
  ):
      """Converts result_flat_signature -> result_batchable_tensor_specs."""
      tensor_specs = []
      for spec in result_flat_signature:
          if not isinstance(spec, type_spec.BatchableTypeSpec):
              raise TypeError(
                  "map_fn can not generate %s outputs" % (spec,)
              )
          tensor_specs.extend(
              spec._flat_tensor_specs
          )  # pylint: disable=protected-access
      return tensor_specs
  
imports: import re
  from tensorflow.python.autograph.core import ag_ctx
  from tensorflow.python.autograph.impl import api
  from tensorflow.python.eager import context
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.framework import type_spec
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import tensor_array_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops import while_loop
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import deprecation
  from tensorflow.python.util import nest
  from tensorflow.python.util import variable_utils
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 4 for calling a global function with example usage: _result_flat_signature_to_batchable_tensor_spec(result_flat_signature) and returns: tensor_specs