code: 
  
  
  '''simple docstring'''
  
  
  
  
  import json
  import os
  import unittest
  
  from transformers import HerbertTokenizer, HerbertTokenizerFast
  from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
  from transformers.testing_utils import get_tests_dir, require_tokenizers, slow
  
  from ...test_tokenization_common import TokenizerTesterMixin
  
  
  
  
  
  @require_tokenizers
  class _snake_case   ( _UpperCAmelCase    ,   unittest.TestCase   ):
  							"""simple docstring"""
  
  
  
  
  
  							__a												=     HerbertTokenizer
  							__a												=     HerbertTokenizerFast
  							__a												=     True
  
  
  
  
  
  
  
  							def 		__SCREAMING_SNAKE_CASE(   self	)     ->Tuple:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											super().setUp()
  
  											# Use a simpler test file without japanese/chinese characters
  											with open(f'{get_tests_dir()}/fixtures/sample_text_no_unicode.txt'			,				encoding="utf-8"	) as f_data:
  															__lowerCamelCase		:      Optional[Any]											=					f_data.read().replace("\n\n"			,				"\n"	).strip()
  
  											__lowerCamelCase		:      int											=					[
  											    "<s>",
  											    "</s>",
  											    "l",
  											    "o",
  											    "w",
  											    "e",
  											    "r",
  											    "s",
  											    "t",
  											    "i",
  											    "d",
  											    "n",
  											    "w</w>",
  											    "r</w>",
  											    "t</w>",
  											    "lo",
  											    "low",
  											    "er</w>",
  											    "low</w>",
  											    "lowest</w>",
  											    "newer</w>",
  											    "wider</w>",
  											    ",</w>",
  											    "<unk>",
  											]
  											__lowerCamelCase		:      List[str]											=					dict(zip(__A			,				range(len(__A	)	)	)	)
  											__lowerCamelCase		:      Union[str, Any]											=					["l o 123", "lo w 1456", "e r</w> 1789", ""]
  
  											__lowerCamelCase		:      str											=					os.path.join(self.tmpdirname			,				VOCAB_FILES_NAMES["vocab_file"]	)
  											__lowerCamelCase		:      List[Any]											=					os.path.join(self.tmpdirname			,				VOCAB_FILES_NAMES["merges_file"]	)
  											with open(self.vocab_file			,				"w"	) as fp:
  															fp.write(json.dumps(__A	)	)
  											with open(self.merges_file			,				"w"	) as fp:
  															fp.write("\n".join(__A	)	)
  
  
  
  
  
  
  
  							def 		__SCREAMING_SNAKE_CASE(   self			,				__A	)     ->Dict:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      Tuple											=					"lower newer"
  											__lowerCamelCase		:      str											=					"lower newer"
  											return input_text, output_text
  
  
  
  
  
  
  
  							def 		__SCREAMING_SNAKE_CASE(   self	)     ->List[str]:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      Optional[Any]											=					self.tokenizer_class(vocab_file=self.vocab_file			,				merges_file=self.merges_file	)
  
  											__lowerCamelCase		:      Dict											=					"lower"
  											__lowerCamelCase		:      Optional[Any]											=					["low", "er</w>"]
  											__lowerCamelCase		:      Dict											=					tokenizer.tokenize(__A	)
  											self.assertListEqual(__A			,				__A	)
  
  											__lowerCamelCase		:      int											=					tokens + ["<unk>"]
  											__lowerCamelCase		:      Union[str, Any]											=					[16, 17, 23]
  											self.assertListEqual(tokenizer.convert_tokens_to_ids(__A	)			,				__A	)
  
  
  
  
  
  
  
  							def 		__SCREAMING_SNAKE_CASE(   self	)     ->Tuple:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											if not self.test_rust_tokenizer:
  															return
  
  											__lowerCamelCase		:      List[str]											=					self.get_tokenizer()
  											__lowerCamelCase		:      List[Any]											=					self.get_rust_tokenizer()
  
  											__lowerCamelCase		:      str											=					"lower,newer"
  
  											__lowerCamelCase		:      int											=					tokenizer.tokenize(__A	)
  											__lowerCamelCase		:      Dict											=					rust_tokenizer.tokenize(__A	)
  											self.assertListEqual(__A			,				__A	)
  
  											__lowerCamelCase		:      Union[str, Any]											=					tokenizer.encode(__A			,				add_special_tokens=__A	)
  											__lowerCamelCase		:      Dict											=					rust_tokenizer.encode(__A			,				add_special_tokens=__A	)
  											self.assertListEqual(__A			,				__A	)
  
  											__lowerCamelCase		:      Dict											=					self.get_rust_tokenizer()
  											__lowerCamelCase		:      Tuple											=					tokenizer.encode(__A	)
  											__lowerCamelCase		:      List[str]											=					rust_tokenizer.encode(__A	)
  											self.assertListEqual(__A			,				__A	)
  
  
  
  
  
  
  
  							@slow
  							def 		__SCREAMING_SNAKE_CASE(   self	)     ->str:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      Union[str, Any]											=					self.tokenizer_class.from_pretrained("allegro/herbert-base-cased"	)
  
  											__lowerCamelCase		:      Tuple											=					tokenizer.encode("konstruowanie sekwencji"			,				add_special_tokens=__A	)
  											__lowerCamelCase		:      List[Any]											=					tokenizer.encode("konstruowanie wielu sekwencji"			,				add_special_tokens=__A	)
  
  											__lowerCamelCase		:      List[str]											=					tokenizer.build_inputs_with_special_tokens(__A	)
  											__lowerCamelCase		:      str											=					tokenizer.build_inputs_with_special_tokens(__A			,				__A	)
  
  											assert encoded_sentence == [0] + text + [2]
  											assert encoded_pair == [0] + text + [2] + text_a + [2]
  
  
  
  
  
  
style_context: 
  
  
  '''simple docstring'''
  
  
  
  
  import json
  from typing import List, Optional, Tuple
  
  from tokenizers import pre_tokenizers, processors
  
  from ...tokenization_utils_base import AddedToken, BatchEncoding
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import logging
  from .tokenization_longformer import LongformerTokenizer
  
  
  __lowercase  :      str      		=				logging.get_logger(__name__)
  
  __lowercase  :      Any      		=				{"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}
  
  __lowercase  :      Optional[Any]      		=				{
      """vocab_file""": {
          """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json""",
          """allenai/longformer-large-4096""": (
              """https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"""
          ),
          """allenai/longformer-large-4096-finetuned-triviaqa""": (
              """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"""
          ),
          """allenai/longformer-base-4096-extra.pos.embd.only""": (
              """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"""
          ),
          """allenai/longformer-large-4096-extra.pos.embd.only""": (
              """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"""
          ),
      },
      """merges_file""": {
          """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt""",
          """allenai/longformer-large-4096""": (
              """https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"""
          ),
          """allenai/longformer-large-4096-finetuned-triviaqa""": (
              """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"""
          ),
          """allenai/longformer-base-4096-extra.pos.embd.only""": (
              """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"""
          ),
          """allenai/longformer-large-4096-extra.pos.embd.only""": (
              """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"""
          ),
      },
      """tokenizer_file""": {
          """allenai/longformer-base-4096""": (
              """https://huggingface.co/allenai/longformer-base-4096/resolve/main/tokenizer.json"""
          ),
          """allenai/longformer-large-4096""": (
              """https://huggingface.co/allenai/longformer-large-4096/resolve/main/tokenizer.json"""
          ),
          """allenai/longformer-large-4096-finetuned-triviaqa""": (
              """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/tokenizer.json"""
          ),
          """allenai/longformer-base-4096-extra.pos.embd.only""": (
              """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/tokenizer.json"""
          ),
          """allenai/longformer-large-4096-extra.pos.embd.only""": (
              """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/tokenizer.json"""
          ),
      },
  }
  
  __lowercase  :      Tuple      		=				{
      """allenai/longformer-base-4096""": 40_96,
      """allenai/longformer-large-4096""": 40_96,
      """allenai/longformer-large-4096-finetuned-triviaqa""": 40_96,
      """allenai/longformer-base-4096-extra.pos.embd.only""": 40_96,
      """allenai/longformer-large-4096-extra.pos.embd.only""": 40_96,
  }
  
  
  
  
  
  class _snake_case   ( a__   ):
  							"""simple docstring"""
  
  
  
  
  
  							__a												=     VOCAB_FILES_NAMES
  							__a												=     PRETRAINED_VOCAB_FILES_MAP
  							__a												=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  							__a												=     ['''input_ids''', '''attention_mask''']
  							__a												=     LongformerTokenizer
  
  
  
  
  
  
  
  							def __init__(   self			,				__A=None			,				__A=None			,				__A=None			,				__A="replace"			,				__A="<s>"			,				__A="</s>"			,				__A="</s>"			,				__A="<s>"			,				__A="<unk>"			,				__A="<pad>"			,				__A="<mask>"			,				__A=False			,				__A=True			,				**__A			,				)     ->Dict:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											super().__init__(
  											    __A			,				__A			,				tokenizer_file=__A			,				errors=__A			,				bos_token=__A			,				eos_token=__A			,				sep_token=__A			,				cls_token=__A			,				unk_token=__A			,				pad_token=__A			,				mask_token=__A			,				add_prefix_space=__A			,				trim_offsets=__A			,				**__A			,				)
  
  											__lowerCamelCase		:      int											=					json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()	)
  											if pre_tok_state.get("add_prefix_space"			,				__A	) != add_prefix_space:
  															__lowerCamelCase		:      Any											=					getattr(__A			,				pre_tok_state.pop("type"	)	)
  															__lowerCamelCase		:      Any											=					add_prefix_space
  															__lowerCamelCase		:      Union[str, Any]											=					pre_tok_class(**__A	)
  
  											__lowerCamelCase		:      Any											=					add_prefix_space
  
  											__lowerCamelCase		:      int											=					"post_processor"
  											__lowerCamelCase		:      Optional[int]											=					getattr(self.backend_tokenizer			,				__A			,				__A	)
  											if tokenizer_component_instance:
  															__lowerCamelCase		:      Tuple											=					json.loads(tokenizer_component_instance.__getstate__()	)
  
  															# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
  															if "sep" in state:
  																			__lowerCamelCase		:      Dict											=					tuple(state["sep"]	)
  															if "cls" in state:
  																			__lowerCamelCase		:      Union[str, Any]											=					tuple(state["cls"]	)
  
  															__lowerCamelCase		:      Union[str, Any]											=					False
  
  															if state.get("add_prefix_space"			,				__A	) != add_prefix_space:
  																			__lowerCamelCase		:      Dict											=					add_prefix_space
  																			__lowerCamelCase		:      str											=					True
  
  															if state.get("trim_offsets"			,				__A	) != trim_offsets:
  																			__lowerCamelCase		:      Tuple											=					trim_offsets
  																			__lowerCamelCase		:      Optional[int]											=					True
  
  															if changes_to_apply:
  																			__lowerCamelCase		:      List[Any]											=					getattr(__A			,				state.pop("type"	)	)
  																			__lowerCamelCase		:      int											=					component_class(**__A	)
  																			setattr(self.backend_tokenizer			,				__A			,				__A	)
  
  
  
  
  
  
  
  							@property
  							def 		__SCREAMING_SNAKE_CASE(   self	)     ->str:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											if self._mask_token is None:
  															if self.verbose:
  																			logger.error("Using mask_token, but it is not set yet."	)
  															return None
  											return str(self._mask_token	)
  
  
  
  
  
  
  
  							@mask_token.setter
  							def 		__SCREAMING_SNAKE_CASE(   self			,				__A	)     ->int:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      List[Any]											=					AddedToken(__A			,				lstrip=__A			,				rstrip=__A	) if isinstance(__A			,				__A	) else value
  											__lowerCamelCase		:      Optional[int]											=					value
  
  
  
  
  
  
  
  							def 		__SCREAMING_SNAKE_CASE(   self			,				*__A			,				**__A	)     ->BatchEncoding:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      Optional[int]											=					kwargs.get("is_split_into_words"			,				__A	)
  											assert self.add_prefix_space or not is_split_into_words, (
  											    f'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
  											    "to use it with pretokenized inputs."
  											)
  
  											return super()._batch_encode_plus(*__A			,				**__A	)
  
  
  
  
  
  
  
  							def 		__SCREAMING_SNAKE_CASE(   self			,				*__A			,				**__A	)     ->BatchEncoding:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      str											=					kwargs.get("is_split_into_words"			,				__A	)
  
  											assert self.add_prefix_space or not is_split_into_words, (
  											    f'You need to instantiate {self.__class__.__name__} with add_prefix_space=True '
  											    "to use it with pretokenized inputs."
  											)
  
  											return super()._encode_plus(*__A			,				**__A	)
  
  
  
  
  
  
  
  							def 		__SCREAMING_SNAKE_CASE(   self			,				__A			,				__A = None	)     ->Tuple[str]:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      List[str]											=					self._tokenizer.model.save(__A			,				name=__A	)
  											return tuple(__A	)
  
  
  
  
  
  
  
  							def 		__SCREAMING_SNAKE_CASE(   self			,				__A			,				__A=None	)     ->Union[str, Any]:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      Any											=					[self.bos_token_id] + token_ids_a + [self.eos_token_id]
  											if token_ids_a is None:
  															return output
  
  											return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]
  
  
  
  
  
  
  
  							def 		__SCREAMING_SNAKE_CASE(   self			,				__A			,				__A = None	)     ->List[int]:
  
  
  
  											"""simple docstring"""
  
  
  
  
  
  
  
  											__lowerCamelCase		:      List[str]											=					[self.sep_token_id]
  											__lowerCamelCase		:      Tuple											=					[self.cls_token_id]
  
  											if token_ids_a is None:
  															return len(cls + token_ids_a + sep	) * [0]
  											return len(cls + token_ids_a + sep + sep + token_ids_a + sep	) * [0]
  
  
  
  
  
  