def test_tftext_sentencepiece_tokenizer_bos_eos(self):
"""Check that the new tokenizer produces the same result that the tftext one with bos and eos."""
tftext_sp = tensorflow_text.SentencepieceTokenizer(
self.sentencepiece_model, add_bos=True, add_eos=True)
opt_sp = sentencepiece_tokenizer.SentencepieceTokenizer(
self.sentencepiece_model, add_bos=True, add_eos=True)
input_text = [
u" ", u"to be or not to be", u"ignored by length text1",
u"ignored by length text2"
]
tftext_tokenized = tftext_sp.tokenize(input_text)
opt_tokenized = opt_sp.tokenize(input_text)
self.assertAllEqual(tftext_tokenized, opt_tokenized)
def test_tftext_sentencepiece_detokenizer(self):
"""Check that the new tokenizer produces the same result that the tftext one."""
tftext_sp = tensorflow_text.SentencepieceTokenizer(
self.sentencepiece_model)
opt_sp = sentencepiece_tokenizer.SentencepieceTokenizer(
self.sentencepiece_model)
input_text = [
u" ", u"to be or not to be", u"ignored by length text1",
u"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)
def benchmarkTokenizer(self):
sp_model = _GetSentencepieceModel()
test_text = [
"This week we celebrate the casts and creatives who have come together"
" to bring us our favorite.",
"More Stacks products demonstrated commitment to excellent support.",
"Test, test, test."
]
tftext_sp = tensorflow_text.SentencepieceTokenizer(sp_model)
opt_sp = sentencepiece_tokenizer.SentencepieceTokenizer(sp_model)
iter_number = 1000
start = time.time()
for _ in range(iter_number):
_ = opt_sp.tokenize(test_text)
self.report_benchmark(iters=iter_number,
wall_time=time.time() - start,
name="opt")
start = time.time()
for _ in range(iter_number):
_ = tftext_sp.tokenize(test_text)
self.report_benchmark(iters=iter_number,
wall_time=time.time() - start,
name="tf.text")
def __init__(self, sentencepiece_model, **kwargs):
super(TokenizerLayer, self).__init__(**kwargs)
self.sp = sentencepiece_tokenizer.SentencepieceTokenizer(
sentencepiece_model)
