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107 lines
5.1 KiB
Python
107 lines
5.1 KiB
Python
# coding=utf-8
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# Copyright 2018 The Google AI Language Team Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import absolute_import, division, print_function, unicode_literals
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import os
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import unittest
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from pytorch_transformers.tokenization_xlnet import (XLNetTokenizer, SPIECE_UNDERLINE)
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from .tokenization_tests_commons import CommonTestCases
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SAMPLE_VOCAB = os.path.join(os.path.dirname(os.path.abspath(__file__)),
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'fixtures/test_sentencepiece.model')
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class XLNetTokenizationTest(CommonTestCases.CommonTokenizerTester):
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tokenizer_class = XLNetTokenizer
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def setUp(self):
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super(XLNetTokenizationTest, self).setUp()
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# We have a SentencePiece fixture for testing
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tokenizer = XLNetTokenizer(SAMPLE_VOCAB, keep_accents=True)
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tokenizer.save_pretrained(self.tmpdirname)
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def get_tokenizer(self):
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return XLNetTokenizer.from_pretrained(self.tmpdirname)
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def get_input_output_texts(self):
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input_text = u"This is a test"
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output_text = u"This is a test"
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return input_text, output_text
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def test_full_tokenizer(self):
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tokenizer = XLNetTokenizer(SAMPLE_VOCAB, keep_accents=True)
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tokens = tokenizer.tokenize(u'This is a test')
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self.assertListEqual(tokens, [u'▁This', u'▁is', u'▁a', u'▁t', u'est'])
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self.assertListEqual(
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tokenizer.convert_tokens_to_ids(tokens), [285, 46, 10, 170, 382])
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tokens = tokenizer.tokenize(u"I was born in 92000, and this is falsé.")
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self.assertListEqual(tokens, [SPIECE_UNDERLINE + u'I', SPIECE_UNDERLINE + u'was', SPIECE_UNDERLINE + u'b',
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u'or', u'n', SPIECE_UNDERLINE + u'in', SPIECE_UNDERLINE + u'',
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u'9', u'2', u'0', u'0', u'0', u',', SPIECE_UNDERLINE + u'and', SPIECE_UNDERLINE + u'this',
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SPIECE_UNDERLINE + u'is', SPIECE_UNDERLINE + u'f', u'al', u's', u'é', u'.'])
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ids = tokenizer.convert_tokens_to_ids(tokens)
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self.assertListEqual(
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ids, [8, 21, 84, 55, 24, 19, 7, 0,
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602, 347, 347, 347, 3, 12, 66,
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46, 72, 80, 6, 0, 4])
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back_tokens = tokenizer.convert_ids_to_tokens(ids)
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self.assertListEqual(back_tokens, [SPIECE_UNDERLINE + u'I', SPIECE_UNDERLINE + u'was', SPIECE_UNDERLINE + u'b',
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u'or', u'n', SPIECE_UNDERLINE + u'in',
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SPIECE_UNDERLINE + u'', u'<unk>', u'2', u'0', u'0', u'0', u',',
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SPIECE_UNDERLINE + u'and', SPIECE_UNDERLINE + u'this',
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SPIECE_UNDERLINE + u'is', SPIECE_UNDERLINE + u'f', u'al', u's',
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u'<unk>', u'.'])
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def test_tokenizer_lower(self):
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tokenizer = XLNetTokenizer(SAMPLE_VOCAB, do_lower_case=True)
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tokens = tokenizer.tokenize(u"I was born in 92000, and this is falsé.")
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self.assertListEqual(tokens, [SPIECE_UNDERLINE + u'', u'i', SPIECE_UNDERLINE + u'was', SPIECE_UNDERLINE + u'b',
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u'or', u'n', SPIECE_UNDERLINE + u'in', SPIECE_UNDERLINE + u'',
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u'9', u'2', u'0', u'0', u'0', u',', SPIECE_UNDERLINE + u'and', SPIECE_UNDERLINE + u'this',
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SPIECE_UNDERLINE + u'is', SPIECE_UNDERLINE + u'f', u'al', u'se', u'.'])
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self.assertListEqual(tokenizer.tokenize(u"H\u00E9llo"), [u"▁he", u"ll", u"o"])
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def test_tokenizer_no_lower(self):
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tokenizer = XLNetTokenizer(SAMPLE_VOCAB, do_lower_case=False)
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tokens = tokenizer.tokenize(u"I was born in 92000, and this is falsé.")
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self.assertListEqual(tokens, [SPIECE_UNDERLINE + u'I', SPIECE_UNDERLINE + u'was', SPIECE_UNDERLINE + u'b', u'or',
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u'n', SPIECE_UNDERLINE + u'in', SPIECE_UNDERLINE + u'',
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u'9', u'2', u'0', u'0', u'0', u',', SPIECE_UNDERLINE + u'and', SPIECE_UNDERLINE + u'this',
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SPIECE_UNDERLINE + u'is', SPIECE_UNDERLINE + u'f', u'al', u'se', u'.'])
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def test_sequence_builders(self):
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tokenizer = XLNetTokenizer.from_pretrained("xlnet-base-cased")
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text = tokenizer.encode("sequence builders")
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text_2 = tokenizer.encode("multi-sequence build")
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encoded_sentence = tokenizer.add_special_tokens_single_sentence(text)
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encoded_pair = tokenizer.add_special_tokens_sentences_pair(text, text_2)
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assert encoded_sentence == text + [4, 3]
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assert encoded_pair == text + [4] + text_2 + [4, 3]
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if __name__ == '__main__':
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unittest.main()
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