Tokenization tests + fixes + init
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transformers/tests/fixtures/30k-clean.model
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transformers/tests/fixtures/30k-clean.model
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transformers/tests/tokenization_albert_test.py
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transformers/tests/tokenization_albert_test.py
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# coding=utf-8
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# Copyright 2019 Hugging Face inc.
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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 transformers.tokenization_albert import (AlbertTokenizer, 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/30k-clean.model')
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class AlbertTokenizationTest(CommonTestCases.CommonTokenizerTester):
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tokenizer_class = AlbertTokenizer
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def setUp(self):
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super(AlbertTokenizationTest, self).setUp()
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# We have a SentencePiece fixture for testing
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tokenizer = AlbertTokenizer(SAMPLE_VOCAB)
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tokenizer.save_pretrained(self.tmpdirname)
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def get_tokenizer(self, **kwargs):
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return AlbertTokenizer.from_pretrained(self.tmpdirname, **kwargs)
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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 = AlbertTokenizer(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'▁test'])
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self.assertListEqual(
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tokenizer.convert_tokens_to_ids(tokens), [48, 25, 21, 1289])
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tokens = tokenizer.tokenize(u"I was born in 92000, and this is falsé.")
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self.assertListEqual(tokens, [u'▁i', u'▁was', u'▁born', u'▁in', u'▁9', u'2000', u',', u'▁and', u'▁this', u'▁is', u'▁fal', u's', u'é', u'.'])
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ids = tokenizer.convert_tokens_to_ids(tokens)
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self.assertListEqual(ids, [31, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9])
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back_tokens = tokenizer.convert_ids_to_tokens(ids)
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self.assertListEqual(back_tokens, ['▁i', '▁was', '▁born', '▁in', '▁9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', '<unk>', '.'])
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def test_sequence_builders(self):
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tokenizer = AlbertTokenizer(SAMPLE_VOCAB)
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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.build_inputs_with_special_tokens(text)
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encoded_pair = tokenizer.build_inputs_with_special_tokens(text, text_2)
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assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
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assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_2 + [tokenizer.sep_token_id]
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if __name__ == '__main__':
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unittest.main()
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