




import os
import pickle
import unittest

from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
    VOCAB_FILES_NAMES,
    BertJapaneseTokenizer,
    CharacterTokenizer,
    JumanppTokenizer,
    MecabTokenizer,
    SudachiTokenizer,
    WordpieceTokenizer,
)
from transformers.testing_utils import custom_tokenizers, require_jumanpp, require_sudachi

from ...test_tokenization_common import TokenizerTesterMixin





@custom_tokenizers
class 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       BertJapaneseTokenizer
 lowercase_							       =       False
 lowercase_							       =       True



 def  lowerCAmelCase_    (				self    :						int		):
       super().setUp()

       SCREAMING_SNAKE_CASE_      		=     [
           '[UNK]',
           '[CLS]',
           '[SEP]',
           'こんにちは',
           'こん',
           'にちは',
           'ばんは',
           '##こん',
           '##にちは',
           '##ばんは',
           '世界',
           '##世界',
           '、',
           '##、',
           '。',
           '##。',
       ]

       SCREAMING_SNAKE_CASE_      		=     os.path.join(self.tmpdirname							,							VOCAB_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  lowerCAmelCase_    (				self    :						Dict							,							_lowerCAmelCase    :						int		):
       SCREAMING_SNAKE_CASE_      		=     'こんにちは、世界。 \nこんばんは、世界。'
       SCREAMING_SNAKE_CASE_      		=     'こんにちは 、 世界 。 こんばんは 、 世界 。'
       return input_text, output_text



 def  lowerCAmelCase_    (				self    :						Any							,							_lowerCAmelCase    :						Tuple		):
       SCREAMING_SNAKE_CASE_		,					SCREAMING_SNAKE_CASE_      		=     self.get_input_output_texts(_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_      		=     tokenizer.encode(_lowerCAmelCase							,							add_special_tokens=_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_      		=     tokenizer.decode(_lowerCAmelCase							,							clean_up_tokenization_spaces=_lowerCAmelCase		)
       return text, ids



 def  lowerCAmelCase_    (				self    :						str		):
       pass  # TODO add if relevant



 def  lowerCAmelCase_    (				self    :						Dict		):
       pass  # TODO add if relevant



 def  lowerCAmelCase_    (				self    :						List[Any]		):
       pass  # TODO add if relevant



 def  lowerCAmelCase_    (				self    :						str		):
       SCREAMING_SNAKE_CASE_      		=     self.tokenizer_class(self.vocab_file		)

       SCREAMING_SNAKE_CASE_      		=     tokenizer.tokenize('こんにちは、世界。\nこんばんは、世界。'		)
       self.assertListEqual(_lowerCAmelCase							,							['こんにちは', '、', '世界', '。', 'こん', '##ばんは', '、', '世界', '。']		)
       self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase		)							,							[3, 12, 10, 14, 4, 9, 12, 10, 14]		)



 def  lowerCAmelCase_    (				self    :						Union[str, Any]		):
       SCREAMING_SNAKE_CASE_      		=     self.tokenizer_class(self.vocab_file							,							word_tokenizer_type='mecab'		)
       self.assertIsNotNone(_lowerCAmelCase		)

       SCREAMING_SNAKE_CASE_      		=     'こんにちは、世界。\nこんばんは、世界。'
       SCREAMING_SNAKE_CASE_      		=     tokenizer.tokenize(_lowerCAmelCase		)
       self.assertListEqual(_lowerCAmelCase							,							['こんにちは', '、', '世界', '。', 'こん', '##ばんは', '、', '世界', '。']		)
       self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase		)							,							[3, 12, 10, 14, 4, 9, 12, 10, 14]		)

       SCREAMING_SNAKE_CASE_      		=     os.path.join(self.tmpdirname							,							'tokenizer.bin'		)
       with open(_lowerCAmelCase							,							'wb'		) as handle:
             pickle.dump(_lowerCAmelCase							,							_lowerCAmelCase		)

       with open(_lowerCAmelCase							,							'rb'		) as handle:
             SCREAMING_SNAKE_CASE_      		=     pickle.load(_lowerCAmelCase		)

       SCREAMING_SNAKE_CASE_      		=     tokenizer_new.tokenize(_lowerCAmelCase		)

       self.assertListEqual(_lowerCAmelCase							,							_lowerCAmelCase		)



 def  lowerCAmelCase_    (				self    :						Any		):
       SCREAMING_SNAKE_CASE_      		=     MecabTokenizer(mecab_dic='ipadic'		)

       self.assertListEqual(
           tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '		)							,							['アップルストア', 'で', 'iPhone', '8', 'が', '発売', 'さ', 'れ', 'た', '。']							,							)



 def  lowerCAmelCase_    (				self    :						int		):
       try:
             SCREAMING_SNAKE_CASE_      		=     MecabTokenizer(mecab_dic='unidic_lite'		)
       except ModuleNotFoundError:
             return

       self.assertListEqual(
           tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '		)							,							['アップル', 'ストア', 'で', 'iPhone', '8', 'が', '発売', 'さ', 'れ', 'た', '。']							,							)



 def  lowerCAmelCase_    (				self    :						Any		):
       try:
             SCREAMING_SNAKE_CASE_      		=     MecabTokenizer(mecab_dic='unidic'		)
       except ModuleNotFoundError:
             return

       self.assertListEqual(
           tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '		)							,							['アップル', 'ストア', 'で', 'iPhone', '8', 'が', '発売', 'さ', 'れ', 'た', '。']							,							)



 def  lowerCAmelCase_    (				self    :						List[str]		):
       SCREAMING_SNAKE_CASE_      		=     MecabTokenizer(do_lower_case=_lowerCAmelCase							,							mecab_dic='ipadic'		)

       self.assertListEqual(
           tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '		)							,							['アップルストア', 'で', 'iphone', '8', 'が', '発売', 'さ', 'れ', 'た', '。']							,							)



 def  lowerCAmelCase_    (				self    :						List[Any]		):
       try:
             SCREAMING_SNAKE_CASE_      		=     MecabTokenizer(
                 do_lower_case=_lowerCAmelCase							,							normalize_text=_lowerCAmelCase							,							mecab_option='-d /usr/local/lib/mecab/dic/jumandic'		)
       except RuntimeError:
             # if dict doesn't exist in the system, previous code raises this error.
             return

       self.assertListEqual(
           tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '		)							,							['ｱｯﾌﾟﾙストア', 'で', 'iPhone', '８', 'が', '発売', 'さ', 'れた', '\u3000', '。']							,							)



 def  lowerCAmelCase_    (				self    :						Optional[int]		):
       SCREAMING_SNAKE_CASE_      		=     MecabTokenizer(normalize_text=_lowerCAmelCase							,							mecab_dic='ipadic'		)

       self.assertListEqual(
           tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '		)							,							['ｱｯﾌﾟﾙストア', 'で', 'iPhone', '８', 'が', '発売', 'さ', 'れ', 'た', '　', '。']							,							)



 @require_sudachi
 def  lowerCAmelCase_    (				self    :						Dict		):
       SCREAMING_SNAKE_CASE_      		=     self.tokenizer_class(self.vocab_file							,							word_tokenizer_type='sudachi'		)
       self.assertIsNotNone(_lowerCAmelCase		)

       SCREAMING_SNAKE_CASE_      		=     'こんにちは、世界。\nこんばんは、世界。'
       SCREAMING_SNAKE_CASE_      		=     tokenizer.tokenize(_lowerCAmelCase		)
       self.assertListEqual(_lowerCAmelCase							,							['こんにちは', '、', '世界', '。', 'こん', '##ばんは', '、', '世界', '。']		)
       self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase		)							,							[3, 12, 10, 14, 4, 9, 12, 10, 14]		)

       SCREAMING_SNAKE_CASE_      		=     os.path.join(self.tmpdirname							,							'tokenizer.bin'		)
       with open(_lowerCAmelCase							,							'wb'		) as handle:
             pickle.dump(_lowerCAmelCase							,							_lowerCAmelCase		)

       with open(_lowerCAmelCase							,							'rb'		) as handle:
             SCREAMING_SNAKE_CASE_      		=     pickle.load(_lowerCAmelCase		)

       SCREAMING_SNAKE_CASE_      		=     tokenizer_new.tokenize(_lowerCAmelCase		)

       self.assertListEqual(_lowerCAmelCase							,							_lowerCAmelCase		)



 @require_sudachi
 def  lowerCAmelCase_    (				self    :						List[str]		):
       SCREAMING_SNAKE_CASE_      		=     SudachiTokenizer(sudachi_dict_type='core'		)

       self.assertListEqual(
           tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '		)							,							[' ', '\t', 'アップル', 'ストア', 'で', 'iPhone', '8', ' ', 'が', ' ', ' ', '\n ', '発売', 'さ', 'れ', 'た', ' ', '。', ' ', ' ']							,							)



 @require_sudachi
 def  lowerCAmelCase_    (				self    :						Optional[Any]		):
       SCREAMING_SNAKE_CASE_      		=     SudachiTokenizer(sudachi_dict_type='core'							,							sudachi_split_mode='A'		)

       self.assertListEqual(tokenizer.tokenize('外国人参政権'		)							,							['外国', '人', '参政', '権']		)



 @require_sudachi
 def  lowerCAmelCase_    (				self    :						int		):
       SCREAMING_SNAKE_CASE_      		=     SudachiTokenizer(sudachi_dict_type='core'							,							sudachi_split_mode='B'		)

       self.assertListEqual(tokenizer.tokenize('外国人参政権'		)							,							['外国人', '参政権']		)



 @require_sudachi
 def  lowerCAmelCase_    (				self    :						List[str]		):
       SCREAMING_SNAKE_CASE_      		=     SudachiTokenizer(sudachi_dict_type='core'							,							sudachi_split_mode='C'		)

       self.assertListEqual(tokenizer.tokenize('外国人参政権'		)							,							['外国人参政権']		)



 @require_sudachi
 def  lowerCAmelCase_    (				self    :						Optional[Any]		):
       SCREAMING_SNAKE_CASE_      		=     SudachiTokenizer(do_lower_case=_lowerCAmelCase							,							sudachi_dict_type='core'		)

       self.assertListEqual(
           tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '		)							,							[' ', '\t', 'アップル', 'ストア', 'で', 'iphone', '8', ' ', 'が', ' ', ' ', '\n ', '発売', 'さ', 'れ', 'た', ' ', '。', ' ', ' ']							,							)



 @require_sudachi
 def  lowerCAmelCase_    (				self    :						str		):
       SCREAMING_SNAKE_CASE_      		=     SudachiTokenizer(normalize_text=_lowerCAmelCase							,							sudachi_dict_type='core'		)

       self.assertListEqual(
           tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '		)							,							[' ', '\t', 'ｱｯﾌﾟﾙ', 'ストア', 'で', 'iPhone', '８', ' ', 'が', ' ', ' ', '\n ', '発売', 'さ', 'れ', 'た', '\u3000', '。', ' ', ' ']							,							)



 @require_sudachi
 def  lowerCAmelCase_    (				self    :						List[Any]		):
       SCREAMING_SNAKE_CASE_      		=     SudachiTokenizer(trim_whitespace=_lowerCAmelCase							,							sudachi_dict_type='core'		)

       self.assertListEqual(
           tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '		)							,							['アップル', 'ストア', 'で', 'iPhone', '8', 'が', '発売', 'さ', 'れ', 'た', '。']							,							)



 @require_jumanpp
 def  lowerCAmelCase_    (				self    :						Dict		):
       SCREAMING_SNAKE_CASE_      		=     self.tokenizer_class(self.vocab_file							,							word_tokenizer_type='jumanpp'		)
       self.assertIsNotNone(_lowerCAmelCase		)

       SCREAMING_SNAKE_CASE_      		=     'こんにちは、世界。\nこんばんは、世界。'
       SCREAMING_SNAKE_CASE_      		=     tokenizer.tokenize(_lowerCAmelCase		)
       self.assertListEqual(_lowerCAmelCase							,							['こんにちは', '、', '世界', '。', 'こん', '##ばんは', '、', '世界', '。']		)
       self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase		)							,							[3, 12, 10, 14, 4, 9, 12, 10, 14]		)

       SCREAMING_SNAKE_CASE_      		=     os.path.join(self.tmpdirname							,							'tokenizer.bin'		)
       with open(_lowerCAmelCase							,							'wb'		) as handle:
             pickle.dump(_lowerCAmelCase							,							_lowerCAmelCase		)

       with open(_lowerCAmelCase							,							'rb'		) as handle:
             SCREAMING_SNAKE_CASE_      		=     pickle.load(_lowerCAmelCase		)

       SCREAMING_SNAKE_CASE_      		=     tokenizer_new.tokenize(_lowerCAmelCase		)

       self.assertListEqual(_lowerCAmelCase							,							_lowerCAmelCase		)



 @require_jumanpp
 def  lowerCAmelCase_    (				self    :						List[Any]		):
       SCREAMING_SNAKE_CASE_      		=     JumanppTokenizer()

       self.assertListEqual(
           tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '		)							,							['アップル', 'ストア', 'で', 'iPhone', '8', '\u3000', 'が', '\u3000', '\u3000', '\u3000', '発売', 'さ', 'れた', '\u3000', '。']							,							)



 @require_jumanpp
 def  lowerCAmelCase_    (				self    :						Any		):
       SCREAMING_SNAKE_CASE_      		=     JumanppTokenizer(do_lower_case=_lowerCAmelCase		)

       self.assertListEqual(
           tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '		)							,							['アップル', 'ストア', 'で', 'iphone', '8', '\u3000', 'が', '\u3000', '\u3000', '\u3000', '発売', 'さ', 'れた', '\u3000', '。']							,							)



 @require_jumanpp
 def  lowerCAmelCase_    (				self    :						List[str]		):
       SCREAMING_SNAKE_CASE_      		=     JumanppTokenizer(normalize_text=_lowerCAmelCase		)

       self.assertListEqual(
           tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '		)							,							['ｱ', 'ｯ', 'ﾌ', 'ﾟ', 'ﾙ', 'ストア', 'で', 'iPhone', '８', '\u3000', 'が', '\u3000', '\u3000', '\u3000', '発売', 'さ', 'れた', '\u3000', '。']							,							)



 @require_jumanpp
 def  lowerCAmelCase_    (				self    :						List[Any]		):
       SCREAMING_SNAKE_CASE_      		=     JumanppTokenizer(trim_whitespace=_lowerCAmelCase		)

       self.assertListEqual(
           tokenizer.tokenize(' \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  '		)							,							['アップル', 'ストア', 'で', 'iPhone', '8', 'が', '発売', 'さ', 'れた', '。']							,							)



 @require_jumanpp
 def  lowerCAmelCase_    (				self    :						Optional[int]		):
       SCREAMING_SNAKE_CASE_      		=     JumanppTokenizer()

       self.assertListEqual(
           tokenizer.tokenize('ありがとうございますm(_ _)ｍ見つけるのが大変です。'		)							,							['ありがとう', 'ございます', 'm(_ _)m', '見つける', 'の', 'が', '大変です', '。']							,							)



 def  lowerCAmelCase_    (				self    :						List[str]		):
       SCREAMING_SNAKE_CASE_      		=     ['[UNK]', '[CLS]', '[SEP]', 'こんにちは', 'こん', 'にちは', 'ばんは', '##こん', '##にちは', '##ばんは']

       SCREAMING_SNAKE_CASE_      		=     {}
       for i, token in enumerate(_lowerCAmelCase		):
             SCREAMING_SNAKE_CASE_      		=     i
       SCREAMING_SNAKE_CASE_      		=     WordpieceTokenizer(vocab=_lowerCAmelCase							,							unk_token='[UNK]'		)

       self.assertListEqual(tokenizer.tokenize(''		)							,							[]		)

       self.assertListEqual(tokenizer.tokenize('こんにちは'		)							,							['こんにちは']		)

       self.assertListEqual(tokenizer.tokenize('こんばんは'		)							,							['こん', '##ばんは']		)

       self.assertListEqual(tokenizer.tokenize('こんばんは こんばんにちは こんにちは'		)							,							['こん', '##ばんは', '[UNK]', 'こんにちは']		)



 def  lowerCAmelCase_    (				self    :						Tuple		):
       SCREAMING_SNAKE_CASE_      		=     BertJapaneseTokenizer.from_pretrained('nlp-waseda/roberta-base-japanese-with-auto-jumanpp'		)
       SCREAMING_SNAKE_CASE_      		=     tokenizer.subword_tokenizer

       SCREAMING_SNAKE_CASE_      		=     subword_tokenizer.tokenize('国境 の 長い トンネル を 抜ける と 雪国 であった 。'		)
       self.assertListEqual(_lowerCAmelCase							,							['▁国境', '▁の', '▁長い', '▁トンネル', '▁を', '▁抜ける', '▁と', '▁雪', '国', '▁であった', '▁。']		)

       SCREAMING_SNAKE_CASE_      		=     subword_tokenizer.tokenize('こんばんは こんばん にち は こんにちは'		)
       self.assertListEqual(_lowerCAmelCase							,							['▁こん', 'ばん', 'は', '▁こん', 'ばん', '▁に', 'ち', '▁は', '▁こんにちは']		)




 def  lowerCAmelCase_    (				self    :						Optional[int]		):
       SCREAMING_SNAKE_CASE_      		=     self.tokenizer_class.from_pretrained('cl-tohoku/bert-base-japanese'		)

       SCREAMING_SNAKE_CASE_      		=     tokenizer.encode('ありがとう。'							,							add_special_tokens=_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_      		=     tokenizer.encode('どういたしまして。'							,							add_special_tokens=_lowerCAmelCase		)

       SCREAMING_SNAKE_CASE_      		=     tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_      		=     tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase							,							_lowerCAmelCase		)

       # 2 is for "[CLS]", 3 is for "[SEP]"
       assert encoded_sentence == [2] + text + [3]
       assert encoded_pair == [2] + text + [3] + text_a + [3]





@custom_tokenizers
class 			lowerCamelCase_				( _SCREAMING_SNAKE_CASE			,  unittest.TestCase   ):


 '''simple docstring'''







 lowercase_							       =       BertJapaneseTokenizer
 lowercase_							       =       False



 def  lowerCAmelCase_    (				self    :						int		):
       super().setUp()

       SCREAMING_SNAKE_CASE_      		=     ['[UNK]', '[CLS]', '[SEP]', 'こ', 'ん', 'に', 'ち', 'は', 'ば', '世', '界', '、', '。']

       SCREAMING_SNAKE_CASE_      		=     os.path.join(self.tmpdirname							,							VOCAB_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  lowerCAmelCase_    (				self    :						List[Any]							,							**_lowerCAmelCase    :						Union[str, Any]		):
       return BertJapaneseTokenizer.from_pretrained(self.tmpdirname							,							subword_tokenizer_type='character'							,							**_lowerCAmelCase		)



 def  lowerCAmelCase_    (				self    :						Union[str, Any]							,							_lowerCAmelCase    :						str		):
       SCREAMING_SNAKE_CASE_      		=     'こんにちは、世界。 \nこんばんは、世界。'
       SCREAMING_SNAKE_CASE_      		=     'こ ん に ち は 、 世 界 。 こ ん ば ん は 、 世 界 。'
       return input_text, output_text



 def  lowerCAmelCase_    (				self    :						Optional[Any]		):
       pass  # TODO add if relevant



 def  lowerCAmelCase_    (				self    :						int		):
       pass  # TODO add if relevant



 def  lowerCAmelCase_    (				self    :						List[Any]		):
       pass  # TODO add if relevant



 def  lowerCAmelCase_    (				self    :						Union[str, Any]		):
       SCREAMING_SNAKE_CASE_      		=     self.tokenizer_class(self.vocab_file							,							subword_tokenizer_type='character'		)

       SCREAMING_SNAKE_CASE_      		=     tokenizer.tokenize('こんにちは、世界。 \nこんばんは、世界。'		)
       self.assertListEqual(
           _lowerCAmelCase							,							['こ', 'ん', 'に', 'ち', 'は', '、', '世', '界', '。', 'こ', 'ん', 'ば', 'ん', 'は', '、', '世', '界', '。']		)
       self.assertListEqual(
           tokenizer.convert_tokens_to_ids(_lowerCAmelCase		)							,							[3, 4, 5, 6, 7, 11, 9, 10, 12, 3, 4, 8, 4, 7, 11, 9, 10, 12]		)



 def  lowerCAmelCase_    (				self    :						Optional[Any]		):
       SCREAMING_SNAKE_CASE_      		=     ['[UNK]', '[CLS]', '[SEP]', 'こ', 'ん', 'に', 'ち', 'は', 'ば', '世', '界', '、', '。']

       SCREAMING_SNAKE_CASE_      		=     {}
       for i, token in enumerate(_lowerCAmelCase		):
             SCREAMING_SNAKE_CASE_      		=     i
       SCREAMING_SNAKE_CASE_      		=     CharacterTokenizer(vocab=_lowerCAmelCase							,							unk_token='[UNK]'		)

       self.assertListEqual(tokenizer.tokenize(''		)							,							[]		)

       self.assertListEqual(tokenizer.tokenize('こんにちは'		)							,							['こ', 'ん', 'に', 'ち', 'は']		)

       self.assertListEqual(tokenizer.tokenize('こんにちほ'		)							,							['こ', 'ん', 'に', 'ち', '[UNK]']		)




 def  lowerCAmelCase_    (				self    :						List[Any]		):
       SCREAMING_SNAKE_CASE_      		=     self.tokenizer_class.from_pretrained('cl-tohoku/bert-base-japanese-char'		)

       SCREAMING_SNAKE_CASE_      		=     tokenizer.encode('ありがとう。'							,							add_special_tokens=_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_      		=     tokenizer.encode('どういたしまして。'							,							add_special_tokens=_lowerCAmelCase		)

       SCREAMING_SNAKE_CASE_      		=     tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_      		=     tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase							,							_lowerCAmelCase		)

       # 2 is for "[CLS]", 3 is for "[SEP]"
       assert encoded_sentence == [2] + text + [3]
       assert encoded_pair == [2] + text + [3] + text_a + [3]





@custom_tokenizers
class 			lowerCamelCase_				( unittest.TestCase   ):


 '''simple docstring'''







 def  lowerCAmelCase_    (				self    :						Tuple		):
       SCREAMING_SNAKE_CASE_      		=     'cl-tohoku/bert-base-japanese'
       SCREAMING_SNAKE_CASE_      		=     AutoTokenizer.from_pretrained(_lowerCAmelCase		)
       self.assertIsInstance(_lowerCAmelCase							,							_lowerCAmelCase		)





class 			lowerCamelCase_				( unittest.TestCase   ):


 '''simple docstring'''







 def  lowerCAmelCase_    (				self    :						Optional[int]		):
       SCREAMING_SNAKE_CASE_      		=     'cl-tohoku/bert-base-japanese'
       with self.assertLogs('transformers'							,							level='WARNING'		) as cm:
             BertTokenizer.from_pretrained(_lowerCAmelCase		)
             self.assertTrue(
                 cm.records[0].message.startswith(
                     'The tokenizer class you load from this checkpoint is not the same type as the class this function'
                     ' is called from.'		)		)
       SCREAMING_SNAKE_CASE_      		=     'bert-base-cased'
       with self.assertLogs('transformers'							,							level='WARNING'		) as cm:
             BertJapaneseTokenizer.from_pretrained(_lowerCAmelCase		)
             self.assertTrue(
                 cm.records[0].message.startswith(
                     'The tokenizer class you load from this checkpoint is not the same type as the class this function'
                     ' is called from.'		)		)





import numpy as np
import torch
from torch.utils.data import DataLoader

from accelerate.utils.dataclasses import DistributedType





class 			lowerCamelCase_				:


 '''simple docstring'''







 def __init__(				self    :						Any							,							_lowerCAmelCase    :						Optional[int]=2							,							_lowerCAmelCase    :						Any=3							,							_lowerCAmelCase    :						Tuple=64							,							_lowerCAmelCase    :						List[str]=None		):
       SCREAMING_SNAKE_CASE_      		=     np.random.default_rng(_lowerCAmelCase		)
       SCREAMING_SNAKE_CASE_      		=     length
       SCREAMING_SNAKE_CASE_      		=     rng.normal(size=(length,)		).astype(np.floataa		)
       SCREAMING_SNAKE_CASE_      		=     a * self.x + b + rng.normal(scale=0.1							,							size=(length,)		).astype(np.floataa		)



 def __len__(				self    :						Optional[int]		):
       return self.length




 def __getitem__(				self    :						str							,							_lowerCAmelCase    :						Union[str, Any]		):
       return {"x": self.x[i], "y": self.y[i]}





class 			lowerCamelCase_				( torch.nn.Module   ):


 '''simple docstring'''







 def __init__(				self    :						Tuple							,							_lowerCAmelCase    :						Dict=0							,							_lowerCAmelCase    :						List[str]=0							,							_lowerCAmelCase    :						str=False		):
       super().__init__()
       SCREAMING_SNAKE_CASE_      		=     torch.nn.Parameter(torch.tensor([2, 3]		).float()		)
       SCREAMING_SNAKE_CASE_      		=     torch.nn.Parameter(torch.tensor([2, 3]		).float()		)
       SCREAMING_SNAKE_CASE_      		=     True




 def  lowerCAmelCase_    (				self    :						Dict							,							_lowerCAmelCase    :						Union[str, Any]=None		):
       if self.first_batch:
             print(F"Model dtype: {self.a.dtype}, {self.b.dtype}. Input dtype: {x.dtype}"		)
             SCREAMING_SNAKE_CASE_      		=     False
       return x * self.a[0] + self.b[0]





class 			lowerCamelCase_				( torch.nn.Module   ):


 '''simple docstring'''







 def __init__(				self    :						Optional[int]							,							_lowerCAmelCase    :						Any=0							,							_lowerCAmelCase    :						Any=0							,							_lowerCAmelCase    :						Optional[Any]=False		):
       super().__init__()
       SCREAMING_SNAKE_CASE_      		=     torch.nn.Parameter(torch.tensor(_lowerCAmelCase		).float()		)
       SCREAMING_SNAKE_CASE_      		=     torch.nn.Parameter(torch.tensor(_lowerCAmelCase		).float()		)
       SCREAMING_SNAKE_CASE_      		=     True




 def  lowerCAmelCase_    (				self    :						Optional[Any]							,							_lowerCAmelCase    :						Optional[int]=None		):
       if self.first_batch:
             print(F"Model dtype: {self.a.dtype}, {self.b.dtype}. Input dtype: {x.dtype}"		)
             SCREAMING_SNAKE_CASE_      		=     False
       return x * self.a + self.b


def    UpperCAmelCase_				( __UpperCAmelCase		:      Dict     ,     __UpperCAmelCase		:      int = 16				)   ->					Union[str, Any]:
      from datasets import load_dataset
      from transformers import AutoTokenizer

      SCREAMING_SNAKE_CASE_      		=     AutoTokenizer.from_pretrained('bert-base-cased'				)
      SCREAMING_SNAKE_CASE_      		=     {'train': 'tests/test_samples/MRPC/train.csv', 'validation': 'tests/test_samples/MRPC/dev.csv'}
      SCREAMING_SNAKE_CASE_      		=     load_dataset('csv'     ,     data_files=__UpperCAmelCase				)
      SCREAMING_SNAKE_CASE_      		=     datasets['train'].unique('label'				)

      SCREAMING_SNAKE_CASE_      		=     {v: i for i, v in enumerate(__UpperCAmelCase				)}

      def tokenize_function(__UpperCAmelCase		:      Optional[int]				):
            # max_length=None => use the model max length (it's actually the default)
            SCREAMING_SNAKE_CASE_      		=     tokenizer(
                examples['sentence1']     ,     examples['sentence2']     ,     truncation=__UpperCAmelCase     ,     max_length=__UpperCAmelCase     ,     padding='max_length'				)
            if "label" in examples:
                  SCREAMING_SNAKE_CASE_      		=     [label_to_id[l] for l in examples['label']]
            return outputs

      # Apply the method we just defined to all the examples in all the splits of the dataset
      SCREAMING_SNAKE_CASE_      		=     datasets.map(
          __UpperCAmelCase     ,     batched=__UpperCAmelCase     ,     remove_columns=['sentence1', 'sentence2', 'label']     ,     )

      def collate_fn(__UpperCAmelCase		:      Dict				):
            # On TPU it's best to pad everything to the same length or training will be very slow.
            if accelerator.distributed_type == DistributedType.TPU:
                  return tokenizer.pad(__UpperCAmelCase     ,     padding='max_length'     ,     max_length=1_28     ,     return_tensors='pt'				)
            return tokenizer.pad(__UpperCAmelCase     ,     padding='longest'     ,     return_tensors='pt'				)

      # Instantiate dataloaders.
      SCREAMING_SNAKE_CASE_      		=     DataLoader(tokenized_datasets['train']     ,     shuffle=__UpperCAmelCase     ,     collate_fn=__UpperCAmelCase     ,     batch_size=2				)
      SCREAMING_SNAKE_CASE_      		=     DataLoader(tokenized_datasets['validation']     ,     shuffle=__UpperCAmelCase     ,     collate_fn=__UpperCAmelCase     ,     batch_size=1				)

      return train_dataloader, eval_dataloader