mirror of
https://github.com/huggingface/transformers.git
synced 2025-07-04 05:10:06 +06:00
55 lines
2.3 KiB
Python
55 lines
2.3 KiB
Python
# Copyright 2020 The SqueezeBert authors and The HuggingFace Inc. team.
|
|
#
|
|
# 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 functools import lru_cache
|
|
|
|
from transformers import SqueezeBertTokenizer, SqueezeBertTokenizerFast
|
|
from transformers.testing_utils import require_tokenizers, slow
|
|
|
|
from ...test_tokenization_common import use_cache_if_possible
|
|
|
|
# Avoid import `BertTokenizationTest` directly as it will run as `test_tokenization_squeezebert.py::BertTokenizationTest`
|
|
# together with `test_tokenization_bert.py::BertTokenizationTest`.
|
|
from ..bert import test_tokenization_bert
|
|
|
|
|
|
@require_tokenizers
|
|
class SqueezeBertTokenizationTest(test_tokenization_bert.BertTokenizationTest):
|
|
tokenizer_class = SqueezeBertTokenizer
|
|
rust_tokenizer_class = SqueezeBertTokenizerFast
|
|
test_rust_tokenizer = True
|
|
from_pretrained_id = "squeezebert/squeezebert-uncased"
|
|
|
|
@classmethod
|
|
@use_cache_if_possible
|
|
@lru_cache(maxsize=64)
|
|
def get_rust_tokenizer(cls, pretrained_name=None, **kwargs):
|
|
pretrained_name = pretrained_name or cls.tmpdirname
|
|
return SqueezeBertTokenizerFast.from_pretrained(pretrained_name, **kwargs)
|
|
|
|
@slow
|
|
def test_sequence_builders(self):
|
|
tokenizer = SqueezeBertTokenizer.from_pretrained("squeezebert/squeezebert-mnli-headless")
|
|
|
|
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
|
|
]
|