transformers/pytorch_transformers/tests/tokenization_xlnet_test.py
2019-07-05 11:55:36 +02:00

91 lines
4.8 KiB
Python

# coding=utf-8
# Copyright 2018 The Google AI Language Team Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from __future__ import absolute_import, division, print_function, unicode_literals
import os
import unittest
import shutil
import pytest
from pytorch_transformers.tokenization_xlnet import (XLNetTokenizer,
PRETRAINED_VOCAB_ARCHIVE_MAP,
SPIECE_UNDERLINE)
from.tokenization_tests_commons import create_and_check_tokenizer_commons
SAMPLE_VOCAB = os.path.join(os.path.dirname(os.path.abspath(__file__)),
'fixtures/test_sentencepiece.model')
class XLNetTokenizationTest(unittest.TestCase):
def test_full_tokenizer(self):
create_and_check_tokenizer_commons(self, XLNetTokenizer, SAMPLE_VOCAB)
tokenizer = XLNetTokenizer(SAMPLE_VOCAB, keep_accents=True)
tokens = tokenizer.tokenize(u'This is a test')
self.assertListEqual(tokens, [u'▁This', u'▁is', u'▁a', u'▁t', u'est'])
self.assertListEqual(
tokenizer.convert_tokens_to_ids(tokens), [285, 46, 10, 170, 382])
tokens = tokenizer.tokenize(u"I was born in 92000, and this is falsé.")
self.assertListEqual(tokens, [SPIECE_UNDERLINE + u'I', SPIECE_UNDERLINE + u'was', SPIECE_UNDERLINE + u'b',
u'or', u'n', SPIECE_UNDERLINE + u'in', SPIECE_UNDERLINE + u'',
u'9', u'2', u'0', u'0', u'0', u',', SPIECE_UNDERLINE + u'and', SPIECE_UNDERLINE + u'this',
SPIECE_UNDERLINE + u'is', SPIECE_UNDERLINE + u'f', u'al', u's', u'é', u'.'])
ids = tokenizer.convert_tokens_to_ids(tokens)
self.assertListEqual(
ids, [8, 21, 84, 55, 24, 19, 7, 0,
602, 347, 347, 347, 3, 12, 66,
46, 72, 80, 6, 0, 4])
back_tokens = tokenizer.convert_ids_to_tokens(ids)
self.assertListEqual(back_tokens, [SPIECE_UNDERLINE + u'I', SPIECE_UNDERLINE + u'was', SPIECE_UNDERLINE + u'b',
u'or', u'n', SPIECE_UNDERLINE + u'in',
SPIECE_UNDERLINE + u'', u'<unk>', u'2', u'0', u'0', u'0', u',',
SPIECE_UNDERLINE + u'and', SPIECE_UNDERLINE + u'this',
SPIECE_UNDERLINE + u'is', SPIECE_UNDERLINE + u'f', u'al', u's',
u'<unk>', u'.'])
@pytest.mark.slow
def test_tokenizer_from_pretrained(self):
cache_dir = "/tmp/pytorch_transformers_test/"
for model_name in list(PRETRAINED_VOCAB_ARCHIVE_MAP.keys())[:1]:
tokenizer = XLNetTokenizer.from_pretrained(model_name, cache_dir=cache_dir)
shutil.rmtree(cache_dir)
self.assertIsNotNone(tokenizer)
def test_tokenizer_lower(self):
tokenizer = XLNetTokenizer(SAMPLE_VOCAB, do_lower_case=True)
tokens = tokenizer.tokenize(u"I was born in 92000, and this is falsé.")
self.assertListEqual(tokens, [SPIECE_UNDERLINE + u'', u'i', SPIECE_UNDERLINE + u'was', SPIECE_UNDERLINE + u'b',
u'or', u'n', SPIECE_UNDERLINE + u'in', SPIECE_UNDERLINE + u'',
u'9', u'2', u'0', u'0', u'0', u',', SPIECE_UNDERLINE + u'and', SPIECE_UNDERLINE + u'this',
SPIECE_UNDERLINE + u'is', SPIECE_UNDERLINE + u'f', u'al', u'se', u'.'])
self.assertListEqual(tokenizer.tokenize(u"H\u00E9llo"), [u"▁he", u"ll", u"o"])
def test_tokenizer_no_lower(self):
tokenizer = XLNetTokenizer(SAMPLE_VOCAB, do_lower_case=False)
tokens = tokenizer.tokenize(u"I was born in 92000, and this is falsé.")
self.assertListEqual(tokens, [SPIECE_UNDERLINE + u'I', SPIECE_UNDERLINE + u'was', SPIECE_UNDERLINE + u'b', u'or',
u'n', SPIECE_UNDERLINE + u'in', SPIECE_UNDERLINE + u'',
u'9', u'2', u'0', u'0', u'0', u',', SPIECE_UNDERLINE + u'and', SPIECE_UNDERLINE + u'this',
SPIECE_UNDERLINE + u'is', SPIECE_UNDERLINE + u'f', u'al', u'se', u'.'])
if __name__ == '__main__':
unittest.main()