class_docstr: Adapted from the original WordpieceTokenizer tests.
class_docstr_tok: ["Adapted","from","the","original","WordpieceTokenizer","tests","."]
code: def testTensors(
      self,
      tokens,
      expected_subwords,
      vocab,
      max_chars_per_token=None,
      expected_start=None,
      expected_end=None,
      token_out_type=dtypes.string,
  ):
      tokenizer = FastWordpieceTokenizer(
          vocab=vocab,
          token_out_type=token_out_type,
          no_pretokenization=True,
      )
      subwords = tokenizer.tokenize(tokens)
      self.assertAllEqual(subwords, expected_subwords)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl import flags
  from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_text
  from tensorflow.lite.python import interpreter
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops.ragged import ragged_factory_ops
  from tensorflow.python.platform import gfile
  from tensorflow.python.platform import test
  from tensorflow_text.python.ops.fast_wordpiece_tokenizer import FastWordpieceTokenizer
label_desc: Use image node_id 5 for calling the FastWordpieceOpOriginalTest obj's underlying member method code with example usage: obj.testTensors(tokens, expected_subwords, vocab, max_chars_per_token, expected_start, expected_end, token_out_type) without return types