code: def fill_empty_rows(ragged_input, default_value, name=None):
      """Fills empty rows in the input `RaggedTensor` with rank 2 with a default
  
      value.
  
      This op adds entries with the specified `default_value` for any row in the
      input that does not already have a value.
  
      The op also returns an indicator vector such that
  
          empty_row_indicator[i] = True iff row i was an empty row.
  
      Args:
        ragged_input: A `RaggedTensor` with rank 2.
        default_value: The value to fill for empty rows, with the same type as
          `ragged_input.`
        name: A name prefix for the returned tensors (optional)
  
      Returns:
        ragged_ordered_output: A `RaggedTensor`with all empty rows filled in with
          `default_value`.
        empty_row_indicator: A bool vector indicating whether each input row was
          empty.
  
      Raises:
        TypeError: If `ragged_input` is not a `RaggedTensor`.
      """
      with ops.name_scope(name, "RaggedFillEmptyRows", [ragged_input]):
          if not isinstance(ragged_input, ragged_tensor.RaggedTensor):
              raise TypeError(
                  "ragged_input must be RaggedTensor,             got"
                  f" {type(ragged_input)}"
              )
          default_value = ops.convert_to_tensor(
              default_value, dtype=ragged_input.dtype
          )
          (
              output_value_rowids,
              output_values,
              empty_row_indicator,
              unused_reverse_index_map,
          ) = gen_ragged_array_ops.ragged_fill_empty_rows(
              value_rowids=ragged_input.value_rowids(),
              values=ragged_input.values,
              nrows=ragged_input.nrows(),
              default_value=default_value,
          )
          return (
              ragged_tensor.RaggedTensor.from_value_rowids(
                  values=output_values,
                  value_rowids=output_value_rowids,
                  validate=False,
              ),
              empty_row_indicator,
          )
  
imports: from typing import Optional
  from typing import Union
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import data_flow_ops
  from tensorflow.python.ops import gen_ragged_array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import sort_ops
  from tensorflow.python.ops.ragged import dynamic_ragged_shape
  from tensorflow.python.ops.ragged import ragged_functional_ops
  from tensorflow.python.ops.ragged import ragged_math_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.ops.ragged import ragged_util
  from tensorflow.python.ops.ragged import segment_id_ops
  from tensorflow.python.types import core
  from tensorflow.python.util import dispatch
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 16 for calling a global function with example usage: fill_empty_rows(ragged_input, default_value, name) and returns: ragged_tensor,  empty_row_indicator