

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      :    Any						       =    logging.get_logger(__name__)

_lowerCAmelCase      :    Optional[int]						       =    {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

_lowerCAmelCase      :    str						       =    {
    "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      :    Any						       =    {
    "allenai/longformer-base-4096": 4_096,
    "allenai/longformer-large-4096": 4_096,
    "allenai/longformer-large-4096-finetuned-triviaqa": 4_096,
    "allenai/longformer-base-4096-extra.pos.embd.only": 4_096,
    "allenai/longformer-large-4096-extra.pos.embd.only": 4_096,
}






class 			__magic_name__					(    lowerCAmelCase_   ):
			SCREAMING_SNAKE_CASE							     =		VOCAB_FILES_NAMES
			SCREAMING_SNAKE_CASE							     =		PRETRAINED_VOCAB_FILES_MAP
			SCREAMING_SNAKE_CASE							     =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			SCREAMING_SNAKE_CASE							     =		['input_ids', 'attention_mask']
			SCREAMING_SNAKE_CASE							     =		LongformerTokenizer





			def __init__(	self      ,						__snake_case=None      ,						__snake_case=None      ,						__snake_case=None      ,						__snake_case="replace"      ,						__snake_case="<s>"      ,						__snake_case="</s>"      ,						__snake_case="</s>"      ,						__snake_case="<s>"      ,						__snake_case="<unk>"      ,						__snake_case="<pad>"      ,						__snake_case="<mask>"      ,						__snake_case=False      ,						__snake_case=True      ,						**__snake_case      ,						)     ->				Optional[Any]:




						'''simple docstring'''
						super().__init__(
						    __snake_case      ,						__snake_case      ,						tokenizer_file=__snake_case      ,						errors=__snake_case      ,						bos_token=__snake_case      ,						eos_token=__snake_case      ,						sep_token=__snake_case      ,						cls_token=__snake_case      ,						unk_token=__snake_case      ,						pad_token=__snake_case      ,						mask_token=__snake_case      ,						add_prefix_space=__snake_case      ,						trim_offsets=__snake_case      ,						**__snake_case      ,						)

						__a						   =json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()      )
						if pre_tok_state.get('add_prefix_space'      ,						__snake_case      ) != add_prefix_space:
									__a						   =getattr(__snake_case      ,						pre_tok_state.pop('type'      )      )
									__a						   =add_prefix_space
									__a						   =pre_tok_class(**__snake_case      )

						__a						   =add_prefix_space

						__a						   ='post_processor'
						__a						   =getattr(self.backend_tokenizer      ,						__snake_case      ,						__snake_case      )
						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'      ,						__snake_case      ) != add_prefix_space:
												__a						   =add_prefix_space
												__a						   =True

									if state.get('trim_offsets'      ,						__snake_case      ) != trim_offsets:
												__a						   =trim_offsets
												__a						   =True

									if changes_to_apply:
												__a						   =getattr(__snake_case      ,						state.pop('type'      )      )
												__a						   =component_class(**__snake_case      )
												setattr(self.backend_tokenizer      ,						__snake_case      ,						__snake_case      )





			@property
			def 	__magic_name__					(	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 	__magic_name__					(	self      ,						__snake_case      )     ->				List[Any]:




						'''simple docstring'''
						__a						   =AddedToken(__snake_case      ,						lstrip=__snake_case      ,						rstrip=__snake_case      ) if isinstance(__snake_case      ,						__snake_case      ) else value
						__a						   =value





			def 	__magic_name__					(	self      ,						*__snake_case      ,						**__snake_case      )     ->				BatchEncoding:




						'''simple docstring'''
						__a						   =kwargs.get('is_split_into_words'      ,						__snake_case      )
						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(*__snake_case      ,						**__snake_case      )





			def 	__magic_name__					(	self      ,						*__snake_case      ,						**__snake_case      )     ->				BatchEncoding:




						'''simple docstring'''
						__a						   =kwargs.get('is_split_into_words'      ,						__snake_case      )

						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(*__snake_case      ,						**__snake_case      )





			def 	__magic_name__					(	self      ,						__snake_case      ,						__snake_case = None      )     ->				Tuple[str]:




						'''simple docstring'''
						__a						   =self._tokenizer.model.save(__snake_case      ,						name=__snake_case      )
						return tuple(__snake_case      )





			def 	__magic_name__					(	self      ,						__snake_case      ,						__snake_case=None      )     ->				Optional[Any]:




						'''simple docstring'''
						__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 	__magic_name__					(	self      ,						__snake_case      ,						__snake_case = None      )     ->				List[int]:




						'''simple docstring'''
						__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]









import os
import sys
import time

from . import transposition_cipher as trans_cipher






def  UpperCamelCase_(							):




			"""simple docstring"""






			__a						   ='Prehistoric Men.txt'
			__a						   ='Output.txt'
			__a						   =int(input('Enter key: '			)			)
			__a						   =input('Encrypt/Decrypt [e/d]: '			)

			if not os.path.exists(_snake_case			):
						print(F'File {input_file} does not exist. Quitting...'			)
						sys.exit()
			if os.path.exists(_snake_case			):
						print(F'Overwrite {output_file}? [y/n]'			)
						__a						   =input('> '			)
						if not response.lower().startswith('y'			):
									sys.exit()

			__a						   =time.time()
			if mode.lower().startswith('e'			):
						with open(_snake_case			) as f:
									__a						   =f.read()
						__a						   =trans_cipher.encrypt_message(_snake_case ,  _snake_case			)
			elif mode.lower().startswith('d'			):
						with open(_snake_case			) as f:
									__a						   =f.read()
						__a						   =trans_cipher.decrypt_message(_snake_case ,  _snake_case			)

			with open(_snake_case ,  'w'			) as output_obj:
						output_obj.write(_snake_case			)

			__a						   =round(time.time() - start_time ,  2			)
			print(('Done (', total_time, 'seconds )')			)


if __name__ == "__main__":
						main()






