class_docstr: Tokenizes a tensor of UTF-8 string into words according to labels.
class_docstr_tok: ["Tokenizes","a","tensor","of","UTF-8","string","into","words","according","to","labels","."]
docstr: Initializes a new instance.
      
docstr_tok: ["Initializes","a","new","instance","."]
code: def __init__(self):
      """Initializes a new instance."""
      super(SplitMergeTokenizer, self).__init__()
      _tf_text_split_merge_tokenizer_op_create_counter.get_cell().increase_by(
          1
      )
  
file_path: text/tensorflow_text/python/ops/split_merge_tokenizer.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from tensorflow.python.eager import monitoring
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import array_ops_stack
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.ops.ragged.ragged_tensor import RaggedTensor
  from tensorflow_text.python.ops.tokenization import TokenizerWithOffsets
  from tensorflow.python.framework import load_library
  from tensorflow.python.platform import resource_loader
label_desc: Use image node_id 1 to create a new SplitMergeTokenizer object from inherited base classes: TokenizerWithOffsets with example: obj = SplitMergeTokenizer()