code: def _cumsum_flat_values_at_ragged_rank(
      last_rp, flat_values, exclusive=False, reverse=False
  ):
      """Calculate flat_values for math_ops.cumsum when axis==ragged_rank."""
      if not exclusive:
          partial = _cumsum_flat_values_at_ragged_rank(
              last_rp, flat_values, exclusive=True, reverse=reverse
          )
          return partial + flat_values
  
      if reverse:
          youngest_sibling = (
              array_ops.gather(
                  params=last_rp.row_splits(),
                  indices=last_rp.value_rowids() + 1,
              )
              - 1
          )
          new_flat_values = math_ops.cumsum(
              flat_values, exclusive=True, reverse=True
          )
          initial_values = array_ops.gather(
              params=new_flat_values, indices=youngest_sibling
          )
  
          return new_flat_values - initial_values
      else:
          eldest_sibling = array_ops.gather(
              params=last_rp.row_splits(),
              indices=last_rp.value_rowids(),
          )
          new_flat_values = math_ops.cumsum(flat_values, exclusive=True)
          initial_values = array_ops.gather(
              params=new_flat_values, indices=eldest_sibling
          )
          return new_flat_values - initial_values
  
imports: import functools
  import typing
  import numpy
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import gen_ragged_math_ops
  from tensorflow.python.ops import map_fn
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.ops.ragged import ragged_functional_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.ops.ragged import segment_id_ops
  from tensorflow.python.util import dispatch
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 35 for calling a global function with example usage: _cumsum_flat_values_at_ragged_rank(last_rp, flat_values, exclusive, reverse) and returns: unknown, unknown, unknown