mirror of
https://github.com/huggingface/transformers.git
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192 lines
8.4 KiB
Python
192 lines
8.4 KiB
Python
# coding=utf-8
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# Copyright 2018 The Google AI Language Team Authors.
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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 __future__ import absolute_import, division, print_function, unicode_literals
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import os
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import unittest
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from io import open
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from transformers.tokenization_bert import WordpieceTokenizer
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from transformers.tokenization_bert_japanese import (BertJapaneseTokenizer,
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MecabTokenizer, CharacterTokenizer,
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VOCAB_FILES_NAMES)
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from .tokenization_tests_commons import CommonTestCases
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from .utils import slow, custom_tokenizers
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@custom_tokenizers
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class BertJapaneseTokenizationTest(CommonTestCases.CommonTokenizerTester):
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tokenizer_class = BertJapaneseTokenizer
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def setUp(self):
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super(BertJapaneseTokenizationTest, self).setUp()
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vocab_tokens = [u"[UNK]", u"[CLS]", u"[SEP]",
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u"こんにちは", u"こん", u"にちは", u"ばんは", u"##こん", u"##にちは", u"##ばんは",
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u"世界", u"##世界", u"、", u"##、", u"。", u"##。"]
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self.vocab_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["vocab_file"])
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with open(self.vocab_file, "w", encoding="utf-8") as vocab_writer:
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vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))
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def get_tokenizer(self, **kwargs):
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return BertJapaneseTokenizer.from_pretrained(self.tmpdirname, **kwargs)
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def get_input_output_texts(self):
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input_text = u"こんにちは、世界。 \nこんばんは、世界。"
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output_text = u"こんにちは 、 世界 。 こんばんは 、 世界 。"
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return input_text, output_text
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def test_full_tokenizer(self):
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tokenizer = self.tokenizer_class(self.vocab_file)
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tokens = tokenizer.tokenize(u"こんにちは、世界。\nこんばんは、世界。")
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self.assertListEqual(tokens,
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[u"こんにちは", u"、", u"世界", u"。",
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u"こん", u"##ばんは", u"、", u"世界", "。"])
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self.assertListEqual(tokenizer.convert_tokens_to_ids(tokens),
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[3, 12, 10, 14, 4, 9, 12, 10, 14])
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def test_mecab_tokenizer(self):
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tokenizer = MecabTokenizer()
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self.assertListEqual(
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tokenizer.tokenize(u" \tｱｯﾌﾟﾙストアでiPhone８ が \n 発売された 。 "),
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[u"アップルストア", u"で", u"iPhone", u"8", u"が",
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u"発売", u"さ", u"れ", u"た", u"。"])
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def test_mecab_tokenizer_lower(self):
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tokenizer = MecabTokenizer(do_lower_case=True)
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self.assertListEqual(
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tokenizer.tokenize(u" \tｱｯﾌﾟﾙストアでiPhone８ が \n 発売された 。 "),
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[u"アップルストア", u"で", u"iphone", u"8", u"が",
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u"発売", u"さ", u"れ", u"た", u"。"])
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def test_mecab_tokenizer_no_normalize(self):
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tokenizer = MecabTokenizer(normalize_text=False)
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self.assertListEqual(
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tokenizer.tokenize(u" \tｱｯﾌﾟﾙストアでiPhone８ が \n 発売された 。 "),
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[u"ｱｯﾌﾟﾙストア", u"で", u"iPhone", u"８", u"が",
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u"発売", u"さ", u"れ", u"た", u" ", u"。"])
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def test_wordpiece_tokenizer(self):
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vocab_tokens = [u"[UNK]", u"[CLS]", u"[SEP]",
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u"こんにちは", u"こん", u"にちは" u"ばんは", u"##こん", u"##にちは", u"##ばんは"]
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vocab = {}
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for (i, token) in enumerate(vocab_tokens):
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vocab[token] = i
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tokenizer = WordpieceTokenizer(vocab=vocab, unk_token=u"[UNK]")
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self.assertListEqual(tokenizer.tokenize(u""), [])
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self.assertListEqual(tokenizer.tokenize(u"こんにちは"),
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[u"こんにちは"])
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self.assertListEqual(tokenizer.tokenize(u"こんばんは"),
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[u"こん", u"##ばんは"])
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self.assertListEqual(tokenizer.tokenize(u"こんばんは こんばんにちは こんにちは"),
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[u"こん", u"##ばんは", u"[UNK]", u"こんにちは"])
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@slow
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def test_sequence_builders(self):
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tokenizer = self.tokenizer_class.from_pretrained("bert-base-japanese")
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text = tokenizer.encode(u"ありがとう。", add_special_tokens=False)
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text_2 = tokenizer.encode(u"どういたしまして。", 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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# 2 is for "[CLS]", 3 is for "[SEP]"
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assert encoded_sentence == [2] + text + [3]
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assert encoded_pair == [2] + text + [3] + text_2 + [3]
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class BertJapaneseCharacterTokenizationTest(CommonTestCases.CommonTokenizerTester):
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tokenizer_class = BertJapaneseTokenizer
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def setUp(self):
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super(BertJapaneseCharacterTokenizationTest, self).setUp()
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vocab_tokens = [u"[UNK]", u"[CLS]", u"[SEP]",
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u"こ", u"ん", u"に", u"ち", u"は", u"ば", u"世", u"界", u"、", u"。"]
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self.vocab_file = os.path.join(self.tmpdirname, VOCAB_FILES_NAMES["vocab_file"])
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with open(self.vocab_file, "w", encoding="utf-8") as vocab_writer:
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vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))
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def get_tokenizer(self, **kwargs):
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return BertJapaneseTokenizer.from_pretrained(self.tmpdirname,
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subword_tokenizer_type="character",
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**kwargs)
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def get_input_output_texts(self):
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input_text = u"こんにちは、世界。 \nこんばんは、世界。"
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output_text = u"こ ん に ち は 、 世 界 。 こ ん ば ん は 、 世 界 。"
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return input_text, output_text
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def test_full_tokenizer(self):
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tokenizer = self.tokenizer_class(self.vocab_file,
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subword_tokenizer_type="character")
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tokens = tokenizer.tokenize(u"こんにちは、世界。 \nこんばんは、世界。")
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self.assertListEqual(tokens,
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[u"こ", u"ん", u"に", u"ち", u"は", u"、", u"世", u"界", u"。",
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u"こ", u"ん", u"ば", u"ん", u"は", u"、", u"世", u"界", u"。"])
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self.assertListEqual(tokenizer.convert_tokens_to_ids(tokens),
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[3, 4, 5, 6, 7, 11, 9, 10, 12,
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3, 4, 8, 4, 7, 11, 9, 10, 12])
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def test_character_tokenizer(self):
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vocab_tokens = [u"[UNK]", u"[CLS]", u"[SEP]",
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u"こ", u"ん", u"に", u"ち", u"は", u"ば", u"世", u"界"u"、", u"。"]
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vocab = {}
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for (i, token) in enumerate(vocab_tokens):
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vocab[token] = i
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tokenizer = CharacterTokenizer(vocab=vocab, unk_token=u"[UNK]")
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self.assertListEqual(tokenizer.tokenize(u""), [])
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self.assertListEqual(tokenizer.tokenize(u"こんにちは"),
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[u"こ", u"ん", u"に", u"ち", u"は"])
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self.assertListEqual(tokenizer.tokenize(u"こんにちほ"),
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[u"こ", u"ん", u"に", u"ち", u"[UNK]"])
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@slow
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def test_sequence_builders(self):
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tokenizer = self.tokenizer_class.from_pretrained("bert-base-japanese-char")
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text = tokenizer.encode(u"ありがとう。", add_special_tokens=False)
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text_2 = tokenizer.encode(u"どういたしまして。", 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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# 2 is for "[CLS]", 3 is for "[SEP]"
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assert encoded_sentence == [2] + text + [3]
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assert encoded_pair == [2] + text + [3] + text_2 + [3]
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