code: 
  
  
  
  
  
  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
  
  
  __lowerCAmelCase							:			int				=logging.get_logger(__name__)
  
  __lowerCAmelCase							:			List[str]				={"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}
  
  __lowerCAmelCase							:			Tuple				={
      "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"
          ),
      },
  }
  
  __lowerCAmelCase							:			List[str]				={
      "allenai/longformer-base-4096": 4096,
      "allenai/longformer-large-4096": 4096,
      "allenai/longformer-large-4096-finetuned-triviaqa": 4096,
      "allenai/longformer-base-4096-extra.pos.embd.only": 4096,
      "allenai/longformer-large-4096-extra.pos.embd.only": 4096,
  }
  
  
  
  
  
  
  class      UpperCAmelCase			( UpperCamelCase__       ):
   __lowercase     	=       VOCAB_FILES_NAMES
   __lowercase     	=       PRETRAINED_VOCAB_FILES_MAP
   __lowercase     	=       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __lowercase     	=       ["""input_ids""", """attention_mask"""]
   __lowercase     	=       LongformerTokenizer
   def __init__(       self   :Union[str, Any]		, lowercase_   :int=None		, lowercase_   :Optional[Any]=None		, lowercase_   :Dict=None		, lowercase_   :List[Any]="replace"		, lowercase_   :Any="<s>"		, lowercase_   :Union[str, Any]="</s>"		, lowercase_   :Optional[Any]="</s>"		, lowercase_   :List[str]="<s>"		, lowercase_   :str="<unk>"		, lowercase_   :Optional[int]="<pad>"		, lowercase_   :Union[str, Any]="<mask>"		, lowercase_   :Dict=False		, lowercase_   :Tuple=True		, **lowercase_   :List[Any]		, )->							Tuple:
       super().__init__(
           lowercase_		, lowercase_		, tokenizer_file=lowercase_		, errors=lowercase_		, bos_token=lowercase_		, eos_token=lowercase_		, sep_token=lowercase_		, cls_token=lowercase_		, unk_token=lowercase_		, pad_token=lowercase_		, mask_token=lowercase_		, add_prefix_space=lowercase_		, trim_offsets=lowercase_		, **lowercase_		, )
  
       A__       =    json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()							)
       if pre_tok_state.get("add_prefix_space"		, lowercase_							) != add_prefix_space:
           A__       =    getattr(lowercase_		, pre_tok_state.pop("type"							)							)
           A__       =    add_prefix_space
           A__       =    pre_tok_class(**lowercase_							)
  
       A__       =    add_prefix_space
  
       A__       =    "post_processor"
       A__       =    getattr(self.backend_tokenizer		, lowercase_		, lowercase_							)
       if tokenizer_component_instance:
           A__       =    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:
               A__       =    tuple(state["sep"]							)
           if "cls" in state:
               A__       =    tuple(state["cls"]							)
  
           A__       =    False
  
           if state.get("add_prefix_space"		, lowercase_							) != add_prefix_space:
               A__       =    add_prefix_space
               A__       =    True
  
           if state.get("trim_offsets"		, lowercase_							) != trim_offsets:
               A__       =    trim_offsets
               A__       =    True
  
           if changes_to_apply:
               A__       =    getattr(lowercase_		, state.pop("type"							)							)
               A__       =    component_class(**lowercase_							)
               setattr(self.backend_tokenizer		, lowercase_		, lowercase_							)
   @property
   def   UpperCAmelCase_							(       self   :List[Any]							)->							str:
       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   :int		, lowercase_   :Optional[int]							)->							Any:
       A__       =    AddedToken(lowercase_		, lstrip=lowercase_		, rstrip=lowercase_							) if isinstance(lowercase_		, lowercase_							) else value
       A__       =    value
   def   UpperCAmelCase_							(       self   :Tuple		, *lowercase_   :Any		, **lowercase_   :Dict							)->							BatchEncoding:
       A__       =    kwargs.get("is_split_into_words"		, lowercase_							)
       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(*lowercase_		, **lowercase_							)
   def   UpperCAmelCase_							(       self   :Any		, *lowercase_   :Any		, **lowercase_   :int							)->							BatchEncoding:
       A__       =    kwargs.get("is_split_into_words"		, lowercase_							)
  
       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(*lowercase_		, **lowercase_							)
   def   UpperCAmelCase_							(       self   :int		, lowercase_   :str		, lowercase_   :Optional[str] = None							)->							Tuple[str]:
       A__       =    self._tokenizer.model.save(lowercase_		, name=lowercase_							)
       return tuple(lowercase_							)
   def   UpperCAmelCase_							(       self   :Tuple		, lowercase_   :Optional[int]		, lowercase_   :List[str]=None							)->							str:
       A__       =    [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   UpperCAmelCase_							(       self   :Optional[int]		, lowercase_   :List[int]		, lowercase_   :Optional[List[int]] = None							)->							List[int]:
       A__       =    [self.sep_token_id]
       A__       =    [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]
  
  
  
  
style_context: 
  
  
  
  
  
  '''simple docstring'''
  
  import torch
  
  from transformers import AutoTokenizer
  
  
  
  
  
  
  class      UpperCAmelCase			( UpperCamelCase__       ):
   def __init__(       self   :Any		, lowercase_   :Dict							)->							Any:
       A__       =    AutoTokenizer.from_pretrained(lowercase_							)
   def   UpperCAmelCase_							(       self   :Tuple		, lowercase_   :int							)->							Optional[int]:
  
       if isinstance(lowercase_		, lowercase_							) and all(isinstance(_x		, lowercase_							) for _x in x							):
           A__       =    None
           for l in x:
               A__       =    self.tokenizer(
                   lowercase_		, padding="max_length"		, max_length=3_84		, truncation=lowercase_		, return_tensors="pt"		, )
               A__       =    torch.tensor([len(lowercase_							)]							)
               if d is not None:
                   for k in d.keys():
                       A__       =    torch.cat((d[k], t[k])		, 0							)
               else:
                   A__       =    t
  
           A__       =    torch.tensor(self.tokenizer.convert_tokens_to_ids("[E]"							)							)
           A__       =    torch.tensor(self.tokenizer.convert_tokens_to_ids("[/E]"							)							)
  
       elif isinstance(lowercase_		, lowercase_							) and all(isinstance(_x		, lowercase_							) for _x in x							):
           A__       =    self.tokenizer(
               lowercase_		, padding="max_length"		, max_length=3_84		, truncation=lowercase_		, return_tensors="pt"		, )
  
       else:
           raise Exception(
               "Type of parameter x was not recognized! Only `list of strings` for query or `list of lists of"
               " strings` for supports are supported."							)
  
       return d
  
  
  
   def   UpperCAmelCase_							(       self   :Union[str, Any]		, lowercase_   :List[str]		, lowercase_   :str		, lowercase_   :str		, lowercase_   :List[Any]		, lowercase_   :Dict=0.7_0							)->							int:
       A__       =    []
       for idx in range(len(W_query["input_ids"]							)							):
           A__       =    A__       =    range(p_start.shape[1]							)
  
           A__       =    []
           for start_id in start_indexes:
               for end_id in end_indexes:
                   if start_id < end_id:
                       output.append(
                           (
                               start_id,
                               end_id,
                               p_start[idx][start_id].item(),
                               p_end[idx][end_id].item(),
                           )							)
  
           output.sort(key=lambda lowercase_							: (tup[2] * tup[3])		, reverse=lowercase_							)
           A__       =    []
           for k in range(len(lowercase_							)							):
               if output[k][2] * output[k][3] >= thresh:
                   A__,			A__       =    output[k][0], output[k][1]
                   A__       =    self.tokenizer.decode(W_query["input_ids"][idx][c_start_pos:c_end_pos]							)
                   temp.append((decoded, output[k][2] * output[k][3])							)
  
           final_outputs.append(lowercase_							)
  
       return final_outputs
  
  
  
  