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| # 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 transformers.tokenization_distilbert import DistilBertTokenizer | |
| from .test_tokenization_bert import BertTokenizationTest | |
| from .utils import slow | |
| class DistilBertTokenizationTest(BertTokenizationTest): | |
| tokenizer_class = DistilBertTokenizer | |
| def get_tokenizer(self, **kwargs): | |
| return DistilBertTokenizer.from_pretrained(self.tmpdirname, **kwargs) | |
| def test_sequence_builders(self): | |
| tokenizer = DistilBertTokenizer.from_pretrained("distilbert-base-uncased") | |
| text = tokenizer.encode("sequence builders", add_special_tokens=False) | |
| text_2 = tokenizer.encode("multi-sequence build", add_special_tokens=False) | |
| encoded_sentence = tokenizer.build_inputs_with_special_tokens(text) | |
| encoded_pair = tokenizer.build_inputs_with_special_tokens(text, text_2) | |
| assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] | |
| assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_2 + [ | |
| tokenizer.sep_token_id | |
| ] | |