# coding=utf-8 # Copyright 2019 Hugging Face inc. # # 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. import os import unittest from transformers.tokenization_albert import AlbertTokenizer from .test_tokenization_common import TokenizerTesterMixin SAMPLE_VOCAB = os.path.join(os.path.dirname(os.path.abspath(__file__)), "fixtures/spiece.model") class AlbertTokenizationTest(TokenizerTesterMixin, unittest.TestCase): tokenizer_class = AlbertTokenizer def setUp(self): super().setUp() # We have a SentencePiece fixture for testing tokenizer = AlbertTokenizer(SAMPLE_VOCAB) tokenizer.save_pretrained(self.tmpdirname) def get_tokenizer(self, **kwargs): return AlbertTokenizer.from_pretrained(self.tmpdirname, **kwargs) def get_input_output_texts(self): input_text = "this is a test" output_text = "this is a test" return input_text, output_text def test_full_tokenizer(self): tokenizer = AlbertTokenizer(SAMPLE_VOCAB, keep_accents=True) tokens = tokenizer.tokenize("This is a test") self.assertListEqual(tokens, ["▁this", "▁is", "▁a", "▁test"]) self.assertListEqual(tokenizer.convert_tokens_to_ids(tokens), [48, 25, 21, 1289]) tokens = tokenizer.tokenize("I was born in 92000, and this is falsé.") self.assertListEqual( tokens, ["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "é", "."] ) ids = tokenizer.convert_tokens_to_ids(tokens) self.assertListEqual(ids, [31, 23, 386, 19, 561, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]) back_tokens = tokenizer.convert_ids_to_tokens(ids) self.assertListEqual( back_tokens, ["▁i", "▁was", "▁born", "▁in", "▁9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "", "."], ) def test_sequence_builders(self): tokenizer = AlbertTokenizer(SAMPLE_VOCAB) text = tokenizer.encode("sequence builders") text_2 = tokenizer.encode("multi-sequence build") 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 ]