code: def _increase_ragged_rank_to(rt_input, ragged_rank, row_splits_dtype):
      """Adds ragged dimensions to `rt_input` so it has the desired ragged rank."""
      if ragged_rank > 0:
          if not ragged_tensor.is_ragged(rt_input):
              rt_input = ragged_tensor.RaggedTensor.from_tensor(
                  rt_input, row_splits_dtype=row_splits_dtype
              )
          if rt_input.ragged_rank < ragged_rank:
              rt_input = rt_input.with_values(
                  _increase_ragged_rank_to(
                      rt_input.values, ragged_rank - 1, row_splits_dtype
                  )
              )
      return rt_input
  
file_path: tensorflow-upstream/tensorflow/python/ops/ragged/ragged_concat_ops.py
imports: import typing
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_shape
  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 math_ops
  from tensorflow.python.ops.ragged import ragged_gather_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.ops.ragged import ragged_util
  from tensorflow.python.util import dispatch
  from tensorflow.python.util.tf_export import tf_export
label_desc: Use image node_id 7 for calling a global function with example usage: _increase_ragged_rank_to(rt_input, ragged_rank, row_splits_dtype) and returns: rt_input