47 lines
1.9 KiB
Python
47 lines
1.9 KiB
Python
# coding=utf-8
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# Copyright 2020 The SqueezeBert authors and The HuggingFace Inc. team.
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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 transformers import SqueezeBertTokenizer, SqueezeBertTokenizerFast
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from transformers.testing_utils import require_tokenizers, slow
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from ..bert.test_tokenization_bert import BertTokenizationTest
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@require_tokenizers
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class SqueezeBertTokenizationTest(BertTokenizationTest):
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tokenizer_class = SqueezeBertTokenizer
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rust_tokenizer_class = SqueezeBertTokenizerFast
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test_rust_tokenizer = True
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from_pretrained_id = "squeezebert/squeezebert-uncased"
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def get_rust_tokenizer(self, **kwargs):
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return SqueezeBertTokenizerFast.from_pretrained(self.tmpdirname, **kwargs)
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@slow
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def test_sequence_builders(self):
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tokenizer = SqueezeBertTokenizer.from_pretrained("squeezebert/squeezebert-mnli-headless")
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text = tokenizer.encode("sequence builders", add_special_tokens=False)
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text_2 = tokenizer.encode("multi-sequence build", add_special_tokens=False)
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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 + [
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tokenizer.sep_token_id
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]
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