# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved. # Copyright 2020 The HuggingFace Team. All rights reserved. # # 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 paddlenlp.transformers.roformerv2.tokenizer import ( BasicTokenizer, RoFormerv2Tokenizer, WordpieceTokenizer, ) from ...testing_utils import slow from ...transformers.test_tokenizer_common import ( TokenizerTesterMixin, filter_non_english, ) class RoFormerv2TokenizationTest(TokenizerTesterMixin, unittest.TestCase): tokenizer_class = RoFormerv2Tokenizer space_between_special_tokens = True from_pretrained_filter = filter_non_english test_seq2seq = True def setUp(self): super().setUp() vocab_tokens = [ "[UNK]", "[CLS]", "[SEP]", "[PAD]", "[MASK]", "want", "##want", "##ed", "wa", "un", "runn", "##ing", ",", "low", "lowest", ] self.vocab_file = os.path.join(self.tmpdirname, RoFormerv2Tokenizer.resource_files_names["vocab_file"]) with open(self.vocab_file, "w", encoding="utf-8") as vocab_writer: vocab_writer.write("".join([x + "\n" for x in vocab_tokens])) def get_input_output_texts(self, tokenizer): input_text = "UNwant\u00E9d,running" output_text = "unwanted, running" return input_text, output_text def test_full_tokenizer(self): tokenizer = self.tokenizer_class(self.vocab_file) tokens = tokenizer.tokenize("UNwant\u00E9d,running") self.assertListEqual(tokens, ["un", "##want", "##ed", ",", "runn", "##ing"]) self.assertListEqual(tokenizer.convert_tokens_to_ids(tokens), [9, 6, 7, 12, 10, 11]) def test_basic_tokenizer_lower_strip_accents_false(self): tokenizer = BasicTokenizer(do_lower_case=True, strip_accents=False) self.assertListEqual( tokenizer.tokenize(" \tHäLLo!how \n Are yoU? "), ["hällo", "!", "how", "are", "you", "?"] ) self.assertListEqual(tokenizer.tokenize("H\u00E9llo"), ["h\u00E9llo"]) def test_basic_tokenizer_lower_strip_accents_true(self): tokenizer = BasicTokenizer(do_lower_case=True) self.assertListEqual( tokenizer.tokenize(" \tHäLLo!how \n Are yoU? "), ["hallo", "!", "how", "are", "you", "?"] ) self.assertListEqual(tokenizer.tokenize("H\u00E9llo"), ["hello"]) def test_basic_tokenizer_lower_strip_accents_default(self): tokenizer = BasicTokenizer(do_lower_case=True) self.assertListEqual( tokenizer.tokenize(" \tHäLLo!how \n Are yoU? "), ["hallo", "!", "how", "are", "you", "?"] ) self.assertListEqual(tokenizer.tokenize("H\u00E9llo"), ["hello"]) def test_basic_tokenizer_no_lower(self): tokenizer = BasicTokenizer(do_lower_case=False) self.assertListEqual( tokenizer.tokenize(" \tHeLLo!how \n Are yoU? "), ["HeLLo", "!", "how", "Are", "yoU", "?"] ) def test_basic_tokenizer_no_lower_strip_accents_false(self): tokenizer = BasicTokenizer(do_lower_case=False, strip_accents=False) self.assertListEqual( tokenizer.tokenize(" \tHäLLo!how \n Are yoU? "), ["HäLLo", "!", "how", "Are", "yoU", "?"] ) def test_basic_tokenizer_no_lower_strip_accents_true(self): tokenizer = BasicTokenizer(do_lower_case=False, strip_accents=True) self.assertListEqual( tokenizer.tokenize(" \tHäLLo!how \n Are yoU? "), ["HaLLo", "!", "how", "Are", "yoU", "?"] ) def test_basic_tokenizer_respects_never_split_tokens(self): tokenizer = BasicTokenizer(do_lower_case=False, never_split=["[UNK]"]) self.assertListEqual( tokenizer.tokenize(" \tHeLLo!how \n Are yoU? [UNK]"), ["HeLLo", "!", "how", "Are", "yoU", "?", "[UNK]"] ) def test_wordpiece_tokenizer(self): vocab_tokens = ["[UNK]", "[CLS]", "[SEP]", "want", "##want", "##ed", "wa", "un", "runn", "##ing"] vocab = {} for (i, token) in enumerate(vocab_tokens): vocab[token] = i tokenizer = WordpieceTokenizer(vocab=vocab, unk_token="[UNK]") self.assertListEqual(tokenizer.tokenize(""), []) self.assertListEqual(tokenizer.tokenize("unwanted running"), ["un", "##want", "##ed", "runn", "##ing"]) self.assertListEqual(tokenizer.tokenize("unwantedX running"), ["[UNK]", "runn", "##ing"]) def test_clean_text(self): tokenizer = self.get_tokenizer() # Example taken from the issue https://github.com/huggingface/tokenizers/issues/340 self.assertListEqual([tokenizer.tokenize(t) for t in ["Test", "\xad", "test"]], [["[UNK]"], [], ["[UNK]"]]) @slow def test_sequence_builders(self): tokenizer = self.tokenizer_class.from_pretrained("roformer_v2_chinese_char_small") text = tokenizer.encode("sequence builders", return_token_type_ids=None, add_special_tokens=False)["input_ids"] text_2 = tokenizer.encode("multi-sequence build", return_token_type_ids=None, add_special_tokens=False)[ "input_ids" ] print(text) encoded_sentence = tokenizer.build_inputs_with_special_tokens(text) print(encoded_sentence) encoded_pair = tokenizer.build_inputs_with_special_tokens(text, text_2) assert encoded_sentence == [101] + text + [102] assert encoded_pair == [101] + text + [102] + text_2 + [102] def test_offsets_with_special_characters(self): for tokenizer, pretrained_name, kwargs in self.tokenizers_list: with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"): tokenizer = self.tokenizer_class.from_pretrained(pretrained_name, **kwargs) sentence = f"A, naïve {tokenizer.mask_token} AllenNLP sentence." tokens = tokenizer.encode( sentence, return_attention_mask=False, return_token_type_ids=False, return_offsets_mapping=True, add_special_tokens=True, ) do_lower_case = tokenizer.do_lower_case if hasattr(tokenizer, "do_lower_case") else False expected_results = ( [ ((0, 0), tokenizer.cls_token), ((0, 1), "A"), ((1, 2), ","), ((3, 5), "na"), ((5, 6), "##ï"), ((6, 8), "##ve"), ((9, 15), tokenizer.mask_token), ((16, 21), "Allen"), ((21, 23), "##NL"), ((23, 24), "##P"), ((25, 33), "sentence"), ((33, 34), "."), ((0, 0), tokenizer.sep_token), ] if not do_lower_case else [ ((0, 0), tokenizer.cls_token), ((0, 1), "a"), ((1, 2), ","), ((3, 5), "na"), ((5, 8), "##ive"), ((9, 15), tokenizer.mask_token), ((16, 21), "allen"), ((21, 22), "##n"), ((22, 24), "##lp"), ((25, 27), "se"), ((27, 29), "##nt"), ((29, 33), "##ence"), ((33, 34), "."), ((0, 0), tokenizer.sep_token), ] ) self.assertEqual( [e[1] for e in expected_results], tokenizer.convert_ids_to_tokens(tokens["input_ids"]) ) self.assertEqual([e[0] for e in expected_results], tokens["offset_mapping"]) def test_change_tokenize_chinese_chars(self): list_of_commun_chinese_char = ["的", "人", "有"] text_with_chinese_char = "".join(list_of_commun_chinese_char) for tokenizer, pretrained_name, kwargs in self.tokenizers_list: with self.subTest(f"{tokenizer.__class__.__name__} ({pretrained_name})"): kwargs["tokenize_chinese_chars"] = True tokenizer = self.tokenizer_class.from_pretrained(pretrained_name, **kwargs) ids_without_spe_char_p = tokenizer.encode( text_with_chinese_char, return_token_type_ids=None, add_special_tokens=False )["input_ids"] tokens_without_spe_char_p = tokenizer.convert_ids_to_tokens(ids_without_spe_char_p) # it is expected that each Chinese character is not preceded by "##" self.assertListEqual(tokens_without_spe_char_p, list_of_commun_chinese_char) @slow def test_with_emoji(self): tokenizer = self.tokenizer_class.from_pretrained("roformer_v2_chinese_char_small") text = "好👌🏻" prompt = "评价维度" encoding = tokenizer( text=text, text_pair=prompt, runcation=True, pad_to_max_seq_len=True, return_attention_mask=True, return_position_ids=True, return_offsets_mapping=True, ) self.assertEqual(len(encoding["input_ids"]), 10) self.assertEqual(len(encoding["offset_mapping"]), 10) text = "好👌🏻👌🏻👌🏻👌🏻👌🏻👌🏻" prompt = "评价维度" encoding = tokenizer( text=text, text_pair=prompt, runcation=True, pad_to_max_seq_len=True, return_attention_mask=True, return_position_ids=True, return_offsets_mapping=True, ) self.assertEqual(len(encoding["input_ids"]), 20) self.assertEqual(len(encoding["offset_mapping"]), 20)