

"""simple docstring"""


import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging


UpperCAmelCase													=logging.get_logger(__name__)


UpperCAmelCase													={"vocab_file": "vocab.json", "merges_file": "merges.txt"}

# See all LED models at https://huggingface.co/models?filter=LED
UpperCAmelCase													={
    "vocab_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/vocab.json",
    },
    "merges_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "allenai/led-base-16384": "https://huggingface.co/allenai/led-base-16384/resolve/main/tokenizer.json",
    },
}

UpperCAmelCase													={
    "allenai/led-base-16384": 16_384,
}



@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def   _A					(	):



      """simple docstring"""






      A				  =		(
          list(range(ord("""!"""				)     ,   ord("""~"""				) + 1				)				) + list(range(ord("""¡"""				)     ,   ord("""¬"""				) + 1				)				) + list(range(ord("""®"""				)     ,   ord("""ÿ"""				) + 1				)				)
      )
      A				  =		bs[:]
      A				  =		0
      for b in range(2**8				):
            if b not in bs:
                  bs.append(_a				)
                  cs.append(2**8 + n				)
                  n += 1
      A				  =		[chr(_a				) for n in cs]
      return dict(zip(_a     ,   _a				)				)



def   _A					(	_a	:						Optional[int]				):



      """simple docstring"""






      A				  =		set()
      A				  =		word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)				)
            A				  =		char
      return pairs





class lowerCamelCase__   (				SCREAMING_SNAKE_CASE    ):



    '''simple docstring'''




    _lowerCamelCase					=   VOCAB_FILES_NAMES
    _lowerCamelCase					=   PRETRAINED_VOCAB_FILES_MAP
    _lowerCamelCase					=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    _lowerCamelCase					=   ['''input_ids''', '''attention_mask''']




    def __init__( self ,lowerCamelCase_ ,lowerCamelCase_ ,lowerCamelCase_="replace" ,lowerCamelCase_="<s>" ,lowerCamelCase_="</s>" ,lowerCamelCase_="</s>" ,lowerCamelCase_="<s>" ,lowerCamelCase_="<unk>" ,lowerCamelCase_="<pad>" ,lowerCamelCase_="<mask>" ,lowerCamelCase_=False ,**lowerCamelCase_ ,)    ->      str:
          A				  =		AddedToken(lowerCamelCase_ ,lstrip=lowerCamelCase_ ,rstrip=lowerCamelCase_    ) if isinstance(lowerCamelCase_ ,lowerCamelCase_    ) else bos_token
          A				  =		AddedToken(lowerCamelCase_ ,lstrip=lowerCamelCase_ ,rstrip=lowerCamelCase_    ) if isinstance(lowerCamelCase_ ,lowerCamelCase_    ) else eos_token
          A				  =		AddedToken(lowerCamelCase_ ,lstrip=lowerCamelCase_ ,rstrip=lowerCamelCase_    ) if isinstance(lowerCamelCase_ ,lowerCamelCase_    ) else sep_token
          A				  =		AddedToken(lowerCamelCase_ ,lstrip=lowerCamelCase_ ,rstrip=lowerCamelCase_    ) if isinstance(lowerCamelCase_ ,lowerCamelCase_    ) else cls_token
          A				  =		AddedToken(lowerCamelCase_ ,lstrip=lowerCamelCase_ ,rstrip=lowerCamelCase_    ) if isinstance(lowerCamelCase_ ,lowerCamelCase_    ) else unk_token
          A				  =		AddedToken(lowerCamelCase_ ,lstrip=lowerCamelCase_ ,rstrip=lowerCamelCase_    ) if isinstance(lowerCamelCase_ ,lowerCamelCase_    ) else pad_token

          # Mask token behave like a normal word, i.e. include the space before it
          A				  =		AddedToken(lowerCamelCase_ ,lstrip=lowerCamelCase_ ,rstrip=lowerCamelCase_    ) if isinstance(lowerCamelCase_ ,lowerCamelCase_    ) else mask_token

          super().__init__(
              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_ ,)

          with open(lowerCamelCase_ ,encoding="""utf-8"""    ) as vocab_handle:
                A				  =		json.load(lowerCamelCase_    )
          A				  =		{v: k for k, v in self.encoder.items()}
          A				  =		errors  # how to handle errors in decoding
          A				  =		bytes_to_unicode()
          A				  =		{v: k for k, v in self.byte_encoder.items()}
          with open(lowerCamelCase_ ,encoding="""utf-8"""    ) as merges_handle:
                A				  =		merges_handle.read().split("""\n"""    )[1:-1]
          A				  =		[tuple(merge.split()    ) for merge in bpe_merges]
          A				  =		dict(zip(lowerCamelCase_ ,range(len(lowerCamelCase_    )    )    )    )
          A				  =		{}
          A				  =		add_prefix_space

          # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
          A				  =		re.compile(r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""    )




    @property
    # Copied from transformers.models.bart.tokenization_bart.BartTokenizer.vocab_size
    def UpperCamelCase__		( self    )    ->      Optional[Any]:
          return len(self.encoder    )




    def UpperCamelCase__		( self    )    ->      Optional[Any]:
          return dict(self.encoder ,**self.added_tokens_encoder    )




    def UpperCamelCase__		( self ,lowerCamelCase_    )    ->      Optional[Any]:
          if token in self.cache:
                return self.cache[token]
          A				  =		tuple(lowerCamelCase_    )
          A				  =		get_pairs(lowerCamelCase_    )

          if not pairs:
                return token

          while True:
                A				  =		min(lowerCamelCase_ ,key=lambda lowerCamelCase_    : self.bpe_ranks.get(lowerCamelCase_ ,float("""inf"""    )    )    )
                if bigram not in self.bpe_ranks:
                      break
                A  ,			A				  =		bigram
                A				  =		[]
                A				  =		0
                while i < len(lowerCamelCase_    ):
                      try:
                            A				  =		word.index(lowerCamelCase_ ,lowerCamelCase_    )
                      except ValueError:
                            new_word.extend(word[i:]    )
                            break
                      else:
                            new_word.extend(word[i:j]    )
                            A				  =		j

                      if word[i] == first and i < len(lowerCamelCase_    ) - 1 and word[i + 1] == second:
                            new_word.append(first + second    )
                            i += 2
                      else:
                            new_word.append(word[i]    )
                            i += 1
                A				  =		tuple(lowerCamelCase_    )
                A				  =		new_word
                if len(lowerCamelCase_    ) == 1:
                      break
                else:
                      A				  =		get_pairs(lowerCamelCase_    )
          A				  =		""" """.join(lowerCamelCase_    )
          A				  =		word
          return word




    def UpperCamelCase__		( self ,lowerCamelCase_    )    ->      Tuple:
          A				  =		[]
          for token in re.findall(self.pat ,lowerCamelCase_    ):
                A				  =		"""""".join(
                    self.byte_encoder[b] for b in token.encode("""utf-8"""    )    )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
                bpe_tokens.extend(bpe_token for bpe_token in self.bpe(lowerCamelCase_    ).split(""" """    )    )
          return bpe_tokens




    def UpperCamelCase__		( self ,lowerCamelCase_    )    ->      str:
          return self.encoder.get(lowerCamelCase_ ,self.encoder.get(self.unk_token    )    )




    def UpperCamelCase__		( self ,lowerCamelCase_    )    ->      Union[str, Any]:
          return self.decoder.get(lowerCamelCase_    )




    def UpperCamelCase__		( self ,lowerCamelCase_    )    ->      Optional[Any]:
          A				  =		"""""".join(lowerCamelCase_    )
          A				  =		bytearray([self.byte_decoder[c] for c in text]    ).decode("""utf-8""" ,errors=self.errors    )
          return text




    def UpperCamelCase__		( self ,lowerCamelCase_ ,lowerCamelCase_ = None    )    ->      Tuple[str]:
          if not os.path.isdir(lowerCamelCase_    ):
                logger.error(f'Vocabulary path ({save_directory}) should be a directory'    )
                return
          A				  =		os.path.join(
              lowerCamelCase_ ,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]    )
          A				  =		os.path.join(
              lowerCamelCase_ ,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]    )

          with open(lowerCamelCase_ ,"""w""" ,encoding="""utf-8"""    ) as f:
                f.write(json.dumps(self.encoder ,indent=2 ,sort_keys=lowerCamelCase_ ,ensure_ascii=lowerCamelCase_    ) + """\n"""    )

          A				  =		0
          with open(lowerCamelCase_ ,"""w""" ,encoding="""utf-8"""    ) as writer:
                writer.write("""#version: 0.2\n"""    )
                for bpe_tokens, token_index in sorted(self.bpe_ranks.items() ,key=lambda lowerCamelCase_    : kv[1]    ):
                      if index != token_index:
                            logger.warning(
                                f'Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'
                                """ Please check that the tokenizer is not corrupted!"""    )
                            A				  =		token_index
                      writer.write(""" """.join(lowerCamelCase_    ) + """\n"""    )
                      index += 1

          return vocab_file, merge_file




    def UpperCamelCase__		( self ,lowerCamelCase_ ,lowerCamelCase_ = None    )    ->      List[int]:
          if token_ids_a is None:
                return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          A				  =		[self.cls_token_id]
          A				  =		[self.sep_token_id]
          return cls + token_ids_a + sep + sep + token_ids_a + sep




    def UpperCamelCase__		( self ,lowerCamelCase_ ,lowerCamelCase_ = None ,lowerCamelCase_ = False    )    ->      List[int]:
          if already_has_special_tokens:
                return super().get_special_tokens_mask(
                    token_ids_a=lowerCamelCase_ ,token_ids_a=lowerCamelCase_ ,already_has_special_tokens=lowerCamelCase_    )

          if token_ids_a is None:
                return [1] + ([0] * len(lowerCamelCase_    )) + [1]
          return [1] + ([0] * len(lowerCamelCase_    )) + [1, 1] + ([0] * len(lowerCamelCase_    )) + [1]




    def UpperCamelCase__		( self ,lowerCamelCase_ ,lowerCamelCase_ = 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]




    def UpperCamelCase__		( self ,lowerCamelCase_ ,lowerCamelCase_=False ,**lowerCamelCase_    )    ->      List[Any]:
          A				  =		kwargs.pop("""add_prefix_space""" ,self.add_prefix_space    )
          if (is_split_into_words or add_prefix_space) and (len(lowerCamelCase_    ) > 0 and not text[0].isspace()):
                A				  =		""" """ + text
          return (text, kwargs)




    def UpperCamelCase__		( self ,lowerCamelCase_ ,lowerCamelCase_ = None ,lowerCamelCase_ = PaddingStrategy.DO_NOT_PAD ,lowerCamelCase_ = None ,lowerCamelCase_ = None ,)    ->      dict:
          A				  =		super()._pad(
              encoded_inputs=lowerCamelCase_ ,max_length=lowerCamelCase_ ,padding_strategy=lowerCamelCase_ ,pad_to_multiple_of=lowerCamelCase_ ,return_attention_mask=lowerCamelCase_ ,)

          # Load from model defaults
          if return_attention_mask is None:
                A				  =		"""attention_mask""" in self.model_input_names

          if return_attention_mask and "global_attention_mask" in encoded_inputs:
                A				  =		encoded_inputs[self.model_input_names[0]]
                # `global_attention_mask` need to have the same length as other (sequential) inputs.
                A				  =		len(encoded_inputs["""global_attention_mask"""]    ) != len(lowerCamelCase_    )

                if needs_to_be_padded:
                      A				  =		len(lowerCamelCase_    ) - len(encoded_inputs["""global_attention_mask"""]    )

                      if self.padding_side == "right":
                            # Use `-1` since `0` in `global_attention_mask` means `local attention` instead of `not to attend`
                            A				  =		(
                                encoded_inputs["""global_attention_mask"""] + [-1] * difference
                            )
                      elif self.padding_side == "left":
                            A				  =		[-1] * difference + encoded_inputs[
                                """global_attention_mask"""
                            ]
                      else:
                            raise ValueError("""Invalid padding strategy:""" + str(self.padding_side    )    )

          return encoded_inputs







"""simple docstring"""


import random





class lowerCamelCase__   :



    '''simple docstring'''




    @staticmethod
    def UpperCamelCase__		( lowerCamelCase_    )    ->      tuple[list[int], list[int]]:
          A				  =		[ord(lowerCamelCase_    ) for i in text]
          A				  =		[]
          A				  =		[]
          for i in plain:
                A				  =		random.randint(1 ,3_0_0    )
                A				  =		(i + k) * k
                cipher.append(lowerCamelCase_    )
                key.append(lowerCamelCase_    )
          return cipher, key




    @staticmethod
    def UpperCamelCase__		( lowerCamelCase_ ,lowerCamelCase_    )    ->      str:
          A				  =		[]
          for i in range(len(lowerCamelCase_    )    ):
                A				  =		int((cipher[i] - (key[i]) ** 2) / key[i]    )
                plain.append(chr(lowerCamelCase_    )    )
          return "".join(lowerCamelCase_    )


if __name__ == "__main__":
  UpperCAmelCase							,			UpperCAmelCase													=Onepad().encrypt("Hello")
  print(c, k)
  print(Onepad().decrypt(c, k))




