code: def _elems_flat_to_batchable(elems_flat):
      """Converts elems_flat -> elems_batchable."""
      elems_batchable = []
      for elems_tensor in elems_flat:
          spec = type_spec.type_spec_from_value(elems_tensor)
          if not isinstance(spec, type_spec.BatchableTypeSpec):
              raise TypeError(
                  "map_fn can not consume %s inputs: got %r"
                  % (spec, elems_tensor)
              )
          # pylint: disable=protected-access
          elems_batchable.extend(
              spec._to_batched_tensor_list(elems_tensor)
          )
      return elems_batchable
  
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 5 for calling a global function with example usage: _elems_flat_to_batchable(elems_flat) and returns: elems_batchable