code: import json
  from typing import TYPE_CHECKING, List, Optional, Tuple
  
  from tokenizers import pre_tokenizers
  
  from ...tokenization_utils_base import AddedToken, BatchEncoding
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import logging
  from .tokenization_deberta import DebertaTokenizer
  
  
  if TYPE_CHECKING:
  		from transformers.pipelines.conversational import Conversation
  
  
  lowerCamelCase__           =				logging.get_logger(__name__)
  
  lowerCamelCase__           =				{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}
  
  lowerCamelCase__           =				{
      'vocab_file': {
          'microsoft/deberta-base': 'https://huggingface.co/microsoft/deberta-base/resolve/main/vocab.json',
          'microsoft/deberta-large': 'https://huggingface.co/microsoft/deberta-large/resolve/main/vocab.json',
          'microsoft/deberta-xlarge': 'https://huggingface.co/microsoft/deberta-xlarge/resolve/main/vocab.json',
          'microsoft/deberta-base-mnli': 'https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/vocab.json',
          'microsoft/deberta-large-mnli': 'https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/vocab.json',
          'microsoft/deberta-xlarge-mnli': (
              'https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/vocab.json'
          ),
      },
      'merges_file': {
          'microsoft/deberta-base': 'https://huggingface.co/microsoft/deberta-base/resolve/main/merges.txt',
          'microsoft/deberta-large': 'https://huggingface.co/microsoft/deberta-large/resolve/main/merges.txt',
          'microsoft/deberta-xlarge': 'https://huggingface.co/microsoft/deberta-xlarge/resolve/main/merges.txt',
          'microsoft/deberta-base-mnli': 'https://huggingface.co/microsoft/deberta-base-mnli/resolve/main/merges.txt',
          'microsoft/deberta-large-mnli': 'https://huggingface.co/microsoft/deberta-large-mnli/resolve/main/merges.txt',
          'microsoft/deberta-xlarge-mnli': (
              'https://huggingface.co/microsoft/deberta-xlarge-mnli/resolve/main/merges.txt'
          ),
      },
  }
  
  lowerCamelCase__           =				{
      'microsoft/deberta-base': 5_12,
      'microsoft/deberta-large': 5_12,
      'microsoft/deberta-xlarge': 5_12,
      'microsoft/deberta-base-mnli': 5_12,
      'microsoft/deberta-large-mnli': 5_12,
      'microsoft/deberta-xlarge-mnli': 5_12,
  }
  
  lowerCamelCase__           =				{
      'microsoft/deberta-base': {'do_lower_case': False},
      'microsoft/deberta-large': {'do_lower_case': False},
  }
  
  
  
  
  class 					UpperCamelCase	(     snake_case__      ):
  					__UpperCamelCase						=   VOCAB_FILES_NAMES
  					__UpperCamelCase						=   PRETRAINED_VOCAB_FILES_MAP
  					__UpperCamelCase						=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  					__UpperCamelCase						=   ["""input_ids""", """attention_mask""", """token_type_ids"""]
  					__UpperCamelCase						=   DebertaTokenizer
  
  
  
  
  					def __init__( self :					List[Any]      ,_lowerCAmelCase :					Optional[int]=None      ,_lowerCAmelCase :					List[str]=None      ,_lowerCAmelCase :					Optional[Any]=None      ,_lowerCAmelCase :					Any="replace"      ,_lowerCAmelCase :					Optional[Any]="[CLS]"      ,_lowerCAmelCase :					List[str]="[SEP]"      ,_lowerCAmelCase :					Dict="[SEP]"      ,_lowerCAmelCase :					Dict="[CLS]"      ,_lowerCAmelCase :					int="[UNK]"      ,_lowerCAmelCase :					Tuple="[PAD]"      ,_lowerCAmelCase :					Optional[int]="[MASK]"      ,_lowerCAmelCase :					List[Any]=False      ,**_lowerCAmelCase :					Any      ,):
  
  
  							"""simple docstring"""
  
  
  
  
  							super().__init__(
  							    _lowerCAmelCase      ,_lowerCAmelCase      ,tokenizer_file=_lowerCAmelCase      ,errors=_lowerCAmelCase      ,bos_token=_lowerCAmelCase      ,eos_token=_lowerCAmelCase      ,unk_token=_lowerCAmelCase      ,sep_token=_lowerCAmelCase      ,cls_token=_lowerCAmelCase      ,pad_token=_lowerCAmelCase      ,mask_token=_lowerCAmelCase      ,add_prefix_space=_lowerCAmelCase      ,**_lowerCAmelCase      ,)
  							__snake_case		       =     kwargs.pop("add_bos_token"      ,_lowerCAmelCase						)
  
  							__snake_case		       =     json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()						)
  							if pre_tok_state.get("add_prefix_space"      ,_lowerCAmelCase						) != add_prefix_space:
  									__snake_case		       =     getattr(_lowerCAmelCase      ,pre_tok_state.pop("type"						)						)
  									__snake_case		       =     add_prefix_space
  									__snake_case		       =     pre_tok_class(**_lowerCAmelCase						)
  
  							__snake_case		       =     add_prefix_space
  
  
  
  
  					@property
  					def 							UpperCamelCase_						( self :					Dict						):
  
  
  							"""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 							UpperCamelCase_						( self :					Optional[int]      ,_lowerCAmelCase :					int						):
  
  
  							"""simple docstring"""
  
  
  
  
  							__snake_case		       =     AddedToken(_lowerCAmelCase      ,lstrip=_lowerCAmelCase      ,rstrip=_lowerCAmelCase						) if isinstance(_lowerCAmelCase      ,_lowerCAmelCase						) else value
  							__snake_case		       =     value
  
  
  
  
  					def 							UpperCamelCase_						( self :					Any      ,_lowerCAmelCase :					List[int]      ,_lowerCAmelCase :					Optional[List[int]] = None						):
  
  
  							"""simple docstring"""
  
  
  
  
  							if token_ids_a is None:
  									return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
  							__snake_case		       =     [self.cls_token_id]
  							__snake_case		       =     [self.sep_token_id]
  							return cls + token_ids_a + sep + token_ids_a + sep
  
  
  
  
  					def 							UpperCamelCase_						( self :					Union[str, Any]      ,_lowerCAmelCase :					List[int]      ,_lowerCAmelCase :					Optional[List[int]] = None						):
  
  
  							"""simple docstring"""
  
  
  
  
  							__snake_case		       =     [self.sep_token_id]
  							__snake_case		       =     [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						) * [0] + len(token_ids_a + sep						) * [1]
  
  
  
  
  					def 							UpperCamelCase_						( self :					List[Any]      ,*_lowerCAmelCase :					Optional[Any]      ,**_lowerCAmelCase :					Tuple						):
  
  
  							"""simple docstring"""
  
  
  
  
  							__snake_case		       =     kwargs.get("is_split_into_words"      ,_lowerCAmelCase						)
  							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(*_lowerCAmelCase      ,**_lowerCAmelCase						)
  
  
  
  
  					def 							UpperCamelCase_						( self :					str      ,*_lowerCAmelCase :					str      ,**_lowerCAmelCase :					Union[str, Any]						):
  
  
  							"""simple docstring"""
  
  
  
  
  							__snake_case		       =     kwargs.get("is_split_into_words"      ,_lowerCAmelCase						)
  
  							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(*_lowerCAmelCase      ,**_lowerCAmelCase						)
  
  
  
  
  					def 							UpperCamelCase_						( self :					str      ,_lowerCAmelCase :					str      ,_lowerCAmelCase :					Optional[str] = None						):
  
  
  							"""simple docstring"""
  
  
  
  
  							__snake_case		       =     self._tokenizer.model.save(_lowerCAmelCase      ,name=_lowerCAmelCase						)
  							return tuple(_lowerCAmelCase						)
  
  
  
  
  
  
  
  					def 							UpperCamelCase_						( self :					Union[str, Any]      ,_lowerCAmelCase :					"Conversation"						):
  
  
  							"""simple docstring"""
  
  
  
  
  							__snake_case		       =     []
  							for is_user, text in conversation.iter_texts():
  									input_ids.extend(self.encode(_lowerCAmelCase      ,add_special_tokens=_lowerCAmelCase						) + [self.eos_token_id]						)
  
  							if len(_lowerCAmelCase						) > self.model_max_length:
  									__snake_case		       =     input_ids[-self.model_max_length :]
  							return input_ids
  
  
  
  
  
  
style_context: import os
  from shutil import copyfile
  from typing import Optional, Tuple
  
  from ...tokenization_utils_fast import PreTrainedTokenizerFast
  from ...utils import is_sentencepiece_available, logging
  
  
  if is_sentencepiece_available():
  		from .tokenization_reformer import ReformerTokenizer
  else:
  		lowerCamelCase__           =				None
  
  
  lowerCamelCase__           =				logging.get_logger(__name__)
  
  
  lowerCamelCase__           =				'▁'
  
  lowerCamelCase__           =				{'vocab_file': 'spiece.model', 'tokenizer_file': 'tokenizer.json'}
  
  lowerCamelCase__           =				{
      'vocab_file': {
          'google/reformer-crime-and-punishment': (
              'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/spiece.model'
          )
      },
      'tokenizer_file': {
          'google/reformer-crime-and-punishment': (
              'https://huggingface.co/google/reformer-crime-and-punishment/resolve/main/tokenizer.json'
          )
      },
  }
  
  lowerCamelCase__           =				{
      'google/reformer-crime-and-punishment': 52_42_88,
  }
  
  
  
  
  class 					UpperCamelCase	(     snake_case__      ):
  					__UpperCamelCase						=   VOCAB_FILES_NAMES
  					__UpperCamelCase						=   PRETRAINED_VOCAB_FILES_MAP
  					__UpperCamelCase						=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  					__UpperCamelCase						=   ["""input_ids""", """attention_mask"""]
  					__UpperCamelCase						=   ReformerTokenizer
  
  
  
  
  					def __init__( self :					Tuple      ,_lowerCAmelCase :					Dict=None      ,_lowerCAmelCase :					Union[str, Any]=None      ,_lowerCAmelCase :					int="</s>"      ,_lowerCAmelCase :					Dict="<unk>"      ,_lowerCAmelCase :					Dict=[]      ,**_lowerCAmelCase :					Optional[Any]      ,):
  
  
  							"""simple docstring"""
  
  
  
  
  							super().__init__(
  							    _lowerCAmelCase      ,tokenizer_file=_lowerCAmelCase      ,eos_token=_lowerCAmelCase      ,unk_token=_lowerCAmelCase      ,additional_special_tokens=_lowerCAmelCase      ,**_lowerCAmelCase      ,)
  
  							__snake_case		       =     vocab_file
  							__snake_case		       =     False if not self.vocab_file else True
  
  
  
  
  
  
  
  					def 							UpperCamelCase_						( self :					Dict      ,_lowerCAmelCase :					str      ,_lowerCAmelCase :					Optional[str] = None						):
  
  
  							"""simple docstring"""
  
  
  
  
  							if not self.can_save_slow_tokenizer:
  									raise ValueError(
  									    "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
  									    "tokenizer."						)
  
  							if not os.path.isdir(_lowerCAmelCase						):
  									logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""						)
  									return
  							__snake_case		       =     os.path.join(
  							    _lowerCAmelCase      ,(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]						)
  
  							if os.path.abspath(self.vocab_file						) != os.path.abspath(_lowerCAmelCase						):
  									copyfile(self.vocab_file      ,_lowerCAmelCase						)
  
  							return (out_vocab_file,)
  
  
  
  
  
  