




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 		lowercase							(     UpperCamelCase__,unittest.TestCase	):
     _a											=		BertJapaneseTokenizer
     _a											=		False
     _a											=		True

     def       a__			(						self       )		->							int:
           super().setUp()

           _A							:  Tuple    =		[
               """[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""",
               """、""",
               """##、""",
               """。""",
               """##。""",
           ]

           _A							:  List[str]    =		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       a__			(						self	,  _a       )		->							List[str]:
           _A							:  List[Any]    =		"""こんにちは、世界。 \nこんばんは、世界。"""
           _A							:  Optional[int]    =		"""こんにちは 、 世界 。 こんばんは 、 世界 。"""
           return input_text, output_text

     def       a__			(						self	,  _a       )		->							Dict:
           _A    ,     _A							:  List[str]    =		self.get_input_output_texts(__A       )
           _A							:  Optional[int]    =		tokenizer.encode(__A	,  add_special_tokens=__A       )
           _A							:  str    =		tokenizer.decode(__A	,  clean_up_tokenization_spaces=__A       )
           return text, ids

     def       a__			(						self       )		->							List[str]:
           pass  # TODO add if relevant

     def       a__			(						self       )		->							List[str]:
           pass  # TODO add if relevant

     def       a__			(						self       )		->							List[Any]:
           pass  # TODO add if relevant

     def       a__			(						self       )		->							Optional[Any]:
           _A							:  Dict    =		self.tokenizer_class(self.vocab_file       )

           _A							:  str    =		tokenizer.tokenize("""こんにちは、世界。\nこんばんは、世界。"""       )
           self.assertListEqual(__A	,  ["""こんにちは""", """、""", """世界""", """。""", """こん""", """##ばんは""", """、""", """世界""", """。"""]       )
           self.assertListEqual(tokenizer.convert_tokens_to_ids(__A       )	,  [3, 12, 10, 14, 4, 9, 12, 10, 14]       )

     def       a__			(						self       )		->							Union[str, Any]:
           _A							:  Any    =		self.tokenizer_class(self.vocab_file	,  word_tokenizer_type="""mecab"""       )
           self.assertIsNotNone(__A       )

           _A							:  Optional[Any]    =		"""こんにちは、世界。\nこんばんは、世界。"""
           _A							:  List[str]    =		tokenizer.tokenize(__A       )
           self.assertListEqual(__A	,  ["""こんにちは""", """、""", """世界""", """。""", """こん""", """##ばんは""", """、""", """世界""", """。"""]       )
           self.assertListEqual(tokenizer.convert_tokens_to_ids(__A       )	,  [3, 12, 10, 14, 4, 9, 12, 10, 14]       )

           _A							:  str    =		os.path.join(self.tmpdirname	,  """tokenizer.bin"""       )
           with open(__A	,  """wb"""       ) as handle:
                 pickle.dump(__A	,  __A       )

           with open(__A	,  """rb"""       ) as handle:
                 _A							:  Any    =		pickle.load(__A       )

           _A							:  List[str]    =		tokenizer_new.tokenize(__A       )

           self.assertListEqual(__A	,  __A       )

     def       a__			(						self       )		->							List[str]:
           _A							:  Any    =		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       a__			(						self       )		->							Union[str, Any]:
           try:
                 _A							:  List[Any]    =		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       a__			(						self       )		->							Any:
           try:
                 _A							:  str    =		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       a__			(						self       )		->							int:
           _A							:  str    =		MecabTokenizer(do_lower_case=__A	,  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       a__			(						self       )		->							Any:
           try:
                 _A							:  Optional[Any]    =		MecabTokenizer(
                     do_lower_case=__A	,  normalize_text=__A	,  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       a__			(						self       )		->							List[Any]:
           _A							:  int    =		MecabTokenizer(normalize_text=__A	,  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       a__			(						self       )		->							Any:
           _A							:  int    =		self.tokenizer_class(self.vocab_file	,  word_tokenizer_type="""sudachi"""       )
           self.assertIsNotNone(__A       )

           _A							:  Union[str, Any]    =		"""こんにちは、世界。\nこんばんは、世界。"""
           _A							:  Any    =		tokenizer.tokenize(__A       )
           self.assertListEqual(__A	,  ["""こんにちは""", """、""", """世界""", """。""", """こん""", """##ばんは""", """、""", """世界""", """。"""]       )
           self.assertListEqual(tokenizer.convert_tokens_to_ids(__A       )	,  [3, 12, 10, 14, 4, 9, 12, 10, 14]       )

           _A							:  Any    =		os.path.join(self.tmpdirname	,  """tokenizer.bin"""       )
           with open(__A	,  """wb"""       ) as handle:
                 pickle.dump(__A	,  __A       )

           with open(__A	,  """rb"""       ) as handle:
                 _A							:  int    =		pickle.load(__A       )

           _A							:  Tuple    =		tokenizer_new.tokenize(__A       )

           self.assertListEqual(__A	,  __A       )

     @require_sudachi
     def       a__			(						self       )		->							Dict:
           _A							:  str    =		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       a__			(						self       )		->							Union[str, Any]:
           _A							:  List[Any]    =		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       a__			(						self       )		->							Optional[int]:
           _A							:  List[str]    =		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       a__			(						self       )		->							Any:
           _A							:  Union[str, Any]    =		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       a__			(						self       )		->							int:
           _A							:  List[str]    =		SudachiTokenizer(do_lower_case=__A	,  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       a__			(						self       )		->							List[Any]:
           _A							:  List[str]    =		SudachiTokenizer(normalize_text=__A	,  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       a__			(						self       )		->							List[Any]:
           _A							:  str    =		SudachiTokenizer(trim_whitespace=__A	,  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       a__			(						self       )		->							Optional[int]:
           _A							:  Optional[Any]    =		self.tokenizer_class(self.vocab_file	,  word_tokenizer_type="""jumanpp"""       )
           self.assertIsNotNone(__A       )

           _A							:  Dict    =		"""こんにちは、世界。\nこんばんは、世界。"""
           _A							:  int    =		tokenizer.tokenize(__A       )
           self.assertListEqual(__A	,  ["""こんにちは""", """、""", """世界""", """。""", """こん""", """##ばんは""", """、""", """世界""", """。"""]       )
           self.assertListEqual(tokenizer.convert_tokens_to_ids(__A       )	,  [3, 12, 10, 14, 4, 9, 12, 10, 14]       )

           _A							:  Optional[int]    =		os.path.join(self.tmpdirname	,  """tokenizer.bin"""       )
           with open(__A	,  """wb"""       ) as handle:
                 pickle.dump(__A	,  __A       )

           with open(__A	,  """rb"""       ) as handle:
                 _A							:  str    =		pickle.load(__A       )

           _A							:  Dict    =		tokenizer_new.tokenize(__A       )

           self.assertListEqual(__A	,  __A       )

     @require_jumanpp
     def       a__			(						self       )		->							Optional[Any]:
           _A							:  Dict    =		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       a__			(						self       )		->							Dict:
           _A							:  List[Any]    =		JumanppTokenizer(do_lower_case=__A       )

           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       a__			(						self       )		->							Optional[Any]:
           _A							:  Optional[Any]    =		JumanppTokenizer(normalize_text=__A       )

           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       a__			(						self       )		->							Union[str, Any]:
           _A							:  Any    =		JumanppTokenizer(trim_whitespace=__A       )

           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       a__			(						self       )		->							Union[str, Any]:
           _A							:  int    =		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       a__			(						self       )		->							Union[str, Any]:
           _A							:  Optional[int]    =		["""[UNK]""", """[CLS]""", """[SEP]""", """こんにちは""", """こん""", """にちは""", """ばんは""", """##こん""", """##にちは""", """##ばんは"""]

           _A							:  Union[str, Any]    =		{}
           for i, token in enumerate(__A       ):
                 _A							:  Tuple    =		i
           _A							:  List[str]    =		WordpieceTokenizer(vocab=__A	,  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       a__			(						self       )		->							str:
           _A							:  int    =		BertJapaneseTokenizer.from_pretrained("""nlp-waseda/roberta-base-japanese-with-auto-jumanpp"""       )
           _A							:  List[str]    =		tokenizer.subword_tokenizer

           _A							:  str    =		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(__A	,  ["""▁国境""", """▁の""", """▁長い""", """▁トンネル""", """▁を""", """▁抜ける""", """▁と""", """▁雪""", """国""", """▁であった""", """▁。"""]       )

           _A							:  Union[str, Any]    =		subword_tokenizer.tokenize("""こんばんは こんばん にち は こんにちは"""       )
           self.assertListEqual(__A	,  ["""▁こん""", """ばん""", """は""", """▁こん""", """ばん""", """▁に""", """ち""", """▁は""", """▁こんにちは"""]       )



     def       a__			(						self       )		->							Union[str, Any]:
           _A							:  int    =		self.tokenizer_class.from_pretrained("""cl-tohoku/bert-base-japanese"""       )

           _A							:  str    =		tokenizer.encode("""ありがとう。"""	,  add_special_tokens=__A       )
           _A							:  int    =		tokenizer.encode("""どういたしまして。"""	,  add_special_tokens=__A       )

           _A							:  List[str]    =		tokenizer.build_inputs_with_special_tokens(__A       )
           _A							:  str    =		tokenizer.build_inputs_with_special_tokens(__A	,  __A       )

           # 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 		lowercase							(     UpperCamelCase__,unittest.TestCase	):
     _a											=		BertJapaneseTokenizer
     _a											=		False

     def       a__			(						self       )		->							Union[str, Any]:
           super().setUp()

           _A							:  Any    =		["""[UNK]""", """[CLS]""", """[SEP]""", """こ""", """ん""", """に""", """ち""", """は""", """ば""", """世""", """界""", """、""", """。"""]

           _A							:  Optional[int]    =		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       a__			(						self	,  **_a       )		->							Dict:
           return BertJapaneseTokenizer.from_pretrained(self.tmpdirname	,  subword_tokenizer_type="""character"""	,  **__A       )

     def       a__			(						self	,  _a       )		->							Optional[int]:
           _A							:  Dict    =		"""こんにちは、世界。 \nこんばんは、世界。"""
           _A							:  Any    =		"""こ ん に ち は 、 世 界 。 こ ん ば ん は 、 世 界 。"""
           return input_text, output_text

     def       a__			(						self       )		->							List[str]:
           pass  # TODO add if relevant

     def       a__			(						self       )		->							Optional[int]:
           pass  # TODO add if relevant

     def       a__			(						self       )		->							Optional[int]:
           pass  # TODO add if relevant

     def       a__			(						self       )		->							List[str]:
           _A							:  Optional[int]    =		self.tokenizer_class(self.vocab_file	,  subword_tokenizer_type="""character"""       )

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

     def       a__			(						self       )		->							Any:
           _A							:  Any    =		["""[UNK]""", """[CLS]""", """[SEP]""", """こ""", """ん""", """に""", """ち""", """は""", """ば""", """世""", """界""", """、""", """。"""]

           _A							:  int    =		{}
           for i, token in enumerate(__A       ):
                 _A							:  Tuple    =		i
           _A							:  str    =		CharacterTokenizer(vocab=__A	,  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       a__			(						self       )		->							Dict:
           _A							:  Any    =		self.tokenizer_class.from_pretrained("""cl-tohoku/bert-base-japanese-char"""       )

           _A							:  List[Any]    =		tokenizer.encode("""ありがとう。"""	,  add_special_tokens=__A       )
           _A							:  List[str]    =		tokenizer.encode("""どういたしまして。"""	,  add_special_tokens=__A       )

           _A							:  str    =		tokenizer.build_inputs_with_special_tokens(__A       )
           _A							:  List[str]    =		tokenizer.build_inputs_with_special_tokens(__A	,  __A       )

           # 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 		lowercase							(     unittest.TestCase	):

     def       a__			(						self       )		->							List[Any]:
           _A							:  Tuple    =		"""cl-tohoku/bert-base-japanese"""
           _A							:  str    =		AutoTokenizer.from_pretrained(__A       )
           self.assertIsInstance(__A	,  __A       )







class 		lowercase							(     unittest.TestCase	):

     def       a__			(						self       )		->							List[Any]:
           _A							:  str    =		"""cl-tohoku/bert-base-japanese"""
           with self.assertLogs("""transformers"""	,  level="""WARNING"""       ) as cm:
                 BertTokenizer.from_pretrained(__A       )
                 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."""       )       )
           _A							:  int    =		"""bert-base-cased"""
           with self.assertLogs("""transformers"""	,  level="""WARNING"""       ) as cm:
                 BertJapaneseTokenizer.from_pretrained(__A       )
                 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 unittest

from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


_snake_case            = get_tests_dir("fixtures/test_sentencepiece_no_bos.model")







@require_sentencepiece
@require_tokenizers
class 		lowercase							(     UpperCamelCase__,unittest.TestCase	):
     _a											=		PegasusTokenizer
     _a											=		PegasusTokenizerFast
     _a											=		True
     _a											=		True

     def       a__			(						self       )		->							int:
           super().setUp()

           # We have a SentencePiece fixture for testing
           _A							:  List[Any]    =		PegasusTokenizer(_a       )
           tokenizer.save_pretrained(self.tmpdirname       )

     @cached_property
     def       a__			(						self       )		->							int:
           return PegasusTokenizer.from_pretrained("""google/pegasus-large"""       )

     def       a__			(						self	,  **_a       )		->							PegasusTokenizer:
           return PegasusTokenizer.from_pretrained(self.tmpdirname	,  **_a       )

     def       a__			(						self	,  _a       )		->							List[Any]:
           return ("This is a test", "This is a test")

     def       a__			(						self       )		->							int:
           _A							:  Dict    =		"""</s>"""
           _A							:  Dict    =		1

           self.assertEqual(self.get_tokenizer()._convert_token_to_id(_a       )	,  _a       )
           self.assertEqual(self.get_tokenizer()._convert_id_to_token(_a       )	,  _a       )

     def       a__			(						self       )		->							Dict:
           _A							:  List[str]    =		list(self.get_tokenizer().get_vocab().keys()       )

           self.assertEqual(vocab_keys[0]	,  """<pad>"""       )
           self.assertEqual(vocab_keys[1]	,  """</s>"""       )
           self.assertEqual(vocab_keys[-1]	,  """v"""       )
           self.assertEqual(len(_a       )	,  1103       )

     def       a__			(						self       )		->							Optional[int]:
           self.assertEqual(self.get_tokenizer().vocab_size	,  1103       )

     def       a__			(						self       )		->							Tuple:
           _A							:  Any    =		self.rust_tokenizer_class.from_pretrained(self.tmpdirname       )
           _A							:  Optional[int]    =		self.tokenizer_class.from_pretrained(self.tmpdirname       )
           _A							:  int    =		(
               """Let's see which <unk> is the better <unk_token_11> one <mask_1> It seems like this <mask_2> was important"""
               """ </s> <pad> <pad> <pad>"""
           )
           _A							:  Optional[int]    =		rust_tokenizer([raw_input_str]	,  return_tensors=_a	,  add_special_tokens=_a       ).input_ids[0]
           _A							:  List[Any]    =		py_tokenizer([raw_input_str]	,  return_tensors=_a	,  add_special_tokens=_a       ).input_ids[0]
           self.assertListEqual(_a	,  _a       )

     def       a__			(						self       )		->							Any:
           _A							:  str    =		self._large_tokenizer
           # <mask_1> masks whole sentence while <mask_2> masks single word
           _A							:  Optional[int]    =		"""<mask_1> To ensure a <mask_2> flow of bank resolutions."""
           _A							:  Union[str, Any]    =		[2, 413, 615, 114, 3, 1971, 113, 1679, 1_0710, 107, 1]
           _A							:  Union[str, Any]    =		tokenizer([raw_input_str]	,  return_tensors=_a       ).input_ids[0]
           self.assertListEqual(_a	,  _a       )

     def       a__			(						self       )		->							List[str]:
           _A							:  Optional[int]    =		self._large_tokenizer
           # The tracebacks for the following asserts are **better** without messages or self.assertEqual
           assert tokenizer.vocab_size == 9_6103
           assert tokenizer.pad_token_id == 0
           assert tokenizer.eos_token_id == 1
           assert tokenizer.offset == 103
           assert tokenizer.unk_token_id == tokenizer.offset + 2 == 105
           assert tokenizer.unk_token == "<unk>"
           assert tokenizer.model_max_length == 1024
           _A							:  Any    =		"""To ensure a smooth flow of bank resolutions."""
           _A							:  Optional[int]    =		[413, 615, 114, 2291, 1971, 113, 1679, 1_0710, 107, 1]
           _A							:  Optional[Any]    =		tokenizer([raw_input_str]	,  return_tensors=_a       ).input_ids[0]
           self.assertListEqual(_a	,  _a       )
           assert tokenizer.convert_ids_to_tokens([0, 1, 2, 3]       ) == ["<pad>", "</s>", "<mask_1>", "<mask_2>"]

     @require_torch
     def       a__			(						self       )		->							List[str]:
           _A							:  Union[str, Any]    =		["""This is going to be way too long.""" * 150, """short example"""]
           _A							:  Optional[Any]    =		["""not super long but more than 5 tokens""", """tiny"""]
           _A							:  Union[str, Any]    =		self._large_tokenizer(_a	,  padding=_a	,  truncation=_a	,  return_tensors="""pt"""       )
           _A							:  Tuple    =		self._large_tokenizer(
               text_target=_a	,  max_length=5	,  padding=_a	,  truncation=_a	,  return_tensors="""pt"""       )

           assert batch.input_ids.shape == (2, 1024)
           assert batch.attention_mask.shape == (2, 1024)
           assert targets["input_ids"].shape == (2, 5)
           assert len(_a       ) == 2  # input_ids, attention_mask.



     @slow
     def       a__			(						self       )		->							Optional[Any]:
           # fmt: off
           _A							:  List[Any]    =		{"""input_ids""": [[3_8979, 143, 1_8485, 606, 130, 2_6669, 8_7686, 121, 5_4189, 1129, 111, 2_6669, 8_7686, 121, 9114, 1_4787, 121, 1_3249, 158, 592, 956, 121, 1_4621, 3_1576, 143, 6_2613, 108, 9688, 930, 4_3430, 1_1562, 6_2613, 304, 108, 1_1443, 897, 108, 9314, 1_7415, 6_3399, 108, 1_1443, 7614, 1_8316, 118, 4284, 7148, 1_2430, 143, 1400, 2_5703, 158, 111, 4284, 7148, 1_1772, 143, 2_1297, 1064, 158, 122, 204, 3506, 1754, 1133, 1_4787, 1581, 115, 3_3224, 4482, 111, 1355, 110, 2_9173, 317, 5_0833, 108, 2_0147, 9_4665, 111, 7_7198, 107, 1], [110, 6_2613, 117, 638, 112, 1133, 121, 2_0098, 1355, 7_9050, 1_3872, 135, 1596, 5_3541, 1352, 141, 1_3039, 5542, 124, 302, 518, 111, 268, 2956, 115, 149, 4427, 107, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [139, 1235, 2799, 1_8289, 1_7780, 204, 109, 9474, 1296, 107, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], """attention_mask""": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
           # fmt: on

           self.tokenizer_integration_test_util(
               expected_encoding=_a	,  model_name="""google/bigbird-pegasus-large-arxiv"""	,  revision="""ba85d0851d708441f91440d509690f1ab6353415"""	,  )







@require_sentencepiece
@require_tokenizers
class 		lowercase							(     UpperCamelCase__,unittest.TestCase	):
     _a											=		PegasusTokenizer
     _a											=		PegasusTokenizerFast
     _a											=		True
     _a											=		True

     def       a__			(						self       )		->							Optional[Any]:
           super().setUp()

           # We have a SentencePiece fixture for testing
           _A							:  Tuple    =		PegasusTokenizer(_a	,  offset=0	,  mask_token_sent=_a	,  mask_token="""[MASK]"""       )
           tokenizer.save_pretrained(self.tmpdirname       )

     @cached_property
     def       a__			(						self       )		->							Optional[Any]:
           return PegasusTokenizer.from_pretrained("""google/bigbird-pegasus-large-arxiv"""       )

     def       a__			(						self	,  **_a       )		->							PegasusTokenizer:
           return PegasusTokenizer.from_pretrained(self.tmpdirname	,  **_a       )

     def       a__			(						self	,  _a       )		->							List[str]:
           return ("This is a test", "This is a test")

     def       a__			(						self       )		->							List[Any]:
           _A							:  List[Any]    =		self.rust_tokenizer_class.from_pretrained(self.tmpdirname       )
           _A							:  Dict    =		self.tokenizer_class.from_pretrained(self.tmpdirname       )
           _A							:  Dict    =		(
               """Let's see which <unk> is the better <unk_token> one [MASK] It seems like this [MASK] was important </s>"""
               """ <pad> <pad> <pad>"""
           )
           _A							:  Optional[Any]    =		rust_tokenizer([raw_input_str]	,  return_tensors=_a	,  add_special_tokens=_a       ).input_ids[0]
           _A							:  int    =		py_tokenizer([raw_input_str]	,  return_tensors=_a	,  add_special_tokens=_a       ).input_ids[0]
           self.assertListEqual(_a	,  _a       )

     @require_torch
     def       a__			(						self       )		->							Optional[int]:
           _A							:  Tuple    =		["""This is going to be way too long.""" * 1000, """short example"""]
           _A							:  Optional[Any]    =		["""not super long but more than 5 tokens""", """tiny"""]
           _A							:  Tuple    =		self._large_tokenizer(_a	,  padding=_a	,  truncation=_a	,  return_tensors="""pt"""       )
           _A							:  str    =		self._large_tokenizer(
               text_target=_a	,  max_length=5	,  padding=_a	,  truncation=_a	,  return_tensors="""pt"""       )

           assert batch.input_ids.shape == (2, 4096)
           assert batch.attention_mask.shape == (2, 4096)
           assert targets["input_ids"].shape == (2, 5)
           assert len(_a       ) == 2  # input_ids, attention_mask.



     def       a__			(						self       )		->							Dict:
           _A							:  Optional[int]    =		(
               """This is an example string that is used to test the original TF implementation against the HF"""
               """ implementation"""
           )

           _A							:  Any    =		self._large_tokenizer(_a       ).input_ids

           self.assertListEqual(
               _a	,  [182, 117, 142, 587, 4211, 120, 117, 263, 112, 804, 109, 856, 2_5016, 3137, 464, 109, 2_6955, 3137, 1]	,  )

