docstr: Check that the new tokenizer produces the same result that the tftext one.
docstr_tok: ["Check","that","the","new","tokenizer","produces","the","same","result","that","the","tftext","one","."]
code: def test_tftext_sentencepiece_detokenizer(self):
      """Check that the new tokenizer produces the same result that the tftext one."""
      tftext_sp = tf_text.SentencepieceTokenizer(
          self.sentencepiece_model
      )
      opt_sp = sentencepiece_tokenizer.FastSentencepieceTokenizer(
          self.sentencepiece_model
      )
  
      input_text = [
          " ",
          "to be or not to be",
          "ignored by length text1",
          "ignored by length text2",
      ]
      tftext_tokenized = tftext_sp.tokenize(input_text)
  
      # Check detokenizer
      tftext_detokenized = tftext_sp.detokenize(tftext_tokenized)
      opt_detokenized = opt_sp.detokenize(tftext_tokenized)
      self.assertAllEqual(tftext_detokenized, opt_detokenized)
  
imports: import time
  from absl import flags
  import numpy
  import tensorflow.compat.v2
  import tensorflow_text
  from tensorflow.lite.python import interpreter
  from tensorflow.python.platform import gfile
  from tensorflow_text.python.ops import fast_sentencepiece_tokenizer
label_desc: Use image node_id 3 for calling the FastSentencepieceTokenizerTest obj's underlying member method code with example usage: obj.test_tftext_sentencepiece_detokenizer() without return types