


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


_snake_case			 =	logging.get_logger(__name__)


_snake_case			 =	{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt'''}

# See all LED models at https://huggingface.co/models?filter=LED
_snake_case			 =	{
    '''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''',
    },
}

_snake_case			 =	{
    '''allenai/led-base-16384''': 1_63_84,
}






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


  '''simple docstring'''

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






def 						lowercase_(    SCREAMING_SNAKE_CASE_      ):


  '''simple docstring'''

  lowerCamelCase					:   Any       =							set()
  lowerCamelCase					:   Dict       =							word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)      )
    lowerCamelCase					:   List[Any]       =							char
  return pairs







class       UpperCAmelCase_   (   UpperCamelCase       ):

   '''simple docstring'''




   __A					: Union[str, Any]							=						VOCAB_FILES_NAMES
   __A					: List[Any]							=						PRETRAINED_VOCAB_FILES_MAP
   __A					: str							=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __A					: Optional[Any]							=						["input_ids", "attention_mask"]






   def __init__(						self		,							__A		,							__A		,							__A="replace"		,							__A="<s>"		,							__A="</s>"		,							__A="</s>"		,							__A="<s>"		,							__A="<unk>"		,							__A="<pad>"		,							__A="<mask>"		,							__A=False		,							**__A		,							):






     """simple docstring"""





     lowerCamelCase					:   Union[str, Any]       =							AddedToken(lowerCamelCase_		,							lstrip=lowerCamelCase_		,							rstrip=lowerCamelCase_					) if isinstance(lowerCamelCase_		,							lowerCamelCase_					) else bos_token
     lowerCamelCase					:   List[str]       =							AddedToken(lowerCamelCase_		,							lstrip=lowerCamelCase_		,							rstrip=lowerCamelCase_					) if isinstance(lowerCamelCase_		,							lowerCamelCase_					) else eos_token
     lowerCamelCase					:   str       =							AddedToken(lowerCamelCase_		,							lstrip=lowerCamelCase_		,							rstrip=lowerCamelCase_					) if isinstance(lowerCamelCase_		,							lowerCamelCase_					) else sep_token
     lowerCamelCase					:   Optional[int]       =							AddedToken(lowerCamelCase_		,							lstrip=lowerCamelCase_		,							rstrip=lowerCamelCase_					) if isinstance(lowerCamelCase_		,							lowerCamelCase_					) else cls_token
     lowerCamelCase					:   Union[str, Any]       =							AddedToken(lowerCamelCase_		,							lstrip=lowerCamelCase_		,							rstrip=lowerCamelCase_					) if isinstance(lowerCamelCase_		,							lowerCamelCase_					) else unk_token
     lowerCamelCase					:   Optional[int]       =							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
     lowerCamelCase					:   Optional[int]       =							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:
       lowerCamelCase					:   List[str]       =							json.load(lowerCamelCase_					)
     lowerCamelCase					:   List[str]       =							{v: k for k, v in self.encoder.items()}
     lowerCamelCase					:   int       =							errors  # how to handle errors in decoding
     lowerCamelCase					:   List[Any]       =							bytes_to_unicode()
     lowerCamelCase					:   List[Any]       =							{v: k for k, v in self.byte_encoder.items()}
     with open(lowerCamelCase_		,							encoding="utf-8"					) as merges_handle:
       lowerCamelCase					:   Optional[Any]       =							merges_handle.read().split("\n"					)[1:-1]
     lowerCamelCase					:   List[Any]       =							[tuple(merge.split()					) for merge in bpe_merges]
     lowerCamelCase					:   List[str]       =							dict(zip(lowerCamelCase_		,							range(len(lowerCamelCase_					)					)					)					)
     lowerCamelCase					:   Tuple       =							{}
     lowerCamelCase					:   str       =							add_prefix_space

     # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
     lowerCamelCase					:   Any       =							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 _snake_case       (						self					):






     """simple docstring"""





     return len(self.encoder					)






   def _snake_case       (						self					):






     """simple docstring"""





     return dict(self.encoder		,							**self.added_tokens_encoder					)






   def _snake_case       (						self		,							__A					):






     """simple docstring"""





     if token in self.cache:
       return self.cache[token]
     lowerCamelCase					:   Union[str, Any]       =							tuple(lowerCamelCase_					)
     lowerCamelCase					:   List[Any]       =							get_pairs(lowerCamelCase_					)

     if not pairs:
       return token

     while True:
       lowerCamelCase					:   Tuple       =							min(lowerCamelCase_		,							key=lambda __A					: self.bpe_ranks.get(lowerCamelCase_		,							float("inf"					)					)					)
       if bigram not in self.bpe_ranks:
         break
       lowerCamelCase       ,      lowerCamelCase					:   Union[str, Any]       =							bigram
       lowerCamelCase					:   Any       =							[]
       lowerCamelCase					:   Any       =							0
       while i < len(lowerCamelCase_					):
         try:
           lowerCamelCase					:   Any       =							word.index(lowerCamelCase_		,							lowerCamelCase_					)
         except ValueError:
           new_word.extend(word[i:]					)
           break
         else:
           new_word.extend(word[i:j]					)
           lowerCamelCase					:   List[str]       =							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
       lowerCamelCase					:   List[str]       =							tuple(lowerCamelCase_					)
       lowerCamelCase					:   Union[str, Any]       =							new_word
       if len(lowerCamelCase_					) == 1:
         break
       else:
         lowerCamelCase					:   List[str]       =							get_pairs(lowerCamelCase_					)
     lowerCamelCase					:   Optional[int]       =							" ".join(lowerCamelCase_					)
     lowerCamelCase					:   Optional[int]       =							word
     return word






   def _snake_case       (						self		,							__A					):






     """simple docstring"""





     lowerCamelCase					:   Dict       =							[]
     for token in re.findall(self.pat		,							lowerCamelCase_					):
       lowerCamelCase					:   str       =							"".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 _snake_case       (						self		,							__A					):






     """simple docstring"""





     return self.encoder.get(lowerCamelCase_		,							self.encoder.get(self.unk_token					)					)






   def _snake_case       (						self		,							__A					):






     """simple docstring"""





     return self.decoder.get(lowerCamelCase_					)






   def _snake_case       (						self		,							__A					):






     """simple docstring"""





     lowerCamelCase					:   int       =							"".join(lowerCamelCase_					)
     lowerCamelCase					:   Any       =							bytearray([self.byte_decoder[c] for c in text]					).decode("utf-8"		,							errors=self.errors					)
     return text






   def _snake_case       (						self		,							__A		,							__A = None					):






     """simple docstring"""





     if not os.path.isdir(lowerCamelCase_					):
       logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""					)
       return
     lowerCamelCase					:   Tuple       =							os.path.join(
         lowerCamelCase_		,							(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]					)
     lowerCamelCase					:   Optional[int]       =							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"					)

     lowerCamelCase					:   Union[str, Any]       =							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 __A					: 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!"					)
           lowerCamelCase					:   Any       =							token_index
         writer.write(" ".join(lowerCamelCase_					) + "\n"					)
         index += 1

     return vocab_file, merge_file






   def _snake_case       (						self		,							__A		,							__A = None					):






     """simple docstring"""





     if token_ids_a is None:
       return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
     lowerCamelCase					:   Union[str, Any]       =							[self.cls_token_id]
     lowerCamelCase					:   int       =							[self.sep_token_id]
     return cls + token_ids_a + sep + sep + token_ids_a + sep






   def _snake_case       (						self		,							__A		,							__A = None		,							__A = False					):






     """simple docstring"""





     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 _snake_case       (						self		,							__A		,							__A = None					):






     """simple docstring"""





     lowerCamelCase					:   Dict       =							[self.sep_token_id]
     lowerCamelCase					:   str       =							[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 _snake_case       (						self		,							__A		,							__A=False		,							**__A					):






     """simple docstring"""





     lowerCamelCase					:   List[str]       =							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()):
       lowerCamelCase					:   Union[str, Any]       =							" " + text
     return (text, kwargs)






   def _snake_case       (						self		,							__A		,							__A = None		,							__A = PaddingStrategy.DO_NOT_PAD		,							__A = None		,							__A = None		,							):






     """simple docstring"""





     lowerCamelCase					:   List[str]       =							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:
       lowerCamelCase					:   Optional[Any]       =							"attention_mask" in self.model_input_names

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

       if needs_to_be_padded:
         lowerCamelCase					:   Optional[Any]       =							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`
           lowerCamelCase					:   List[str]       =							(
               encoded_inputs["global_attention_mask"] + [-1] * difference
           )
         elif self.padding_side == "left":
           lowerCamelCase					:   Dict       =							[-1] * difference + encoded_inputs[
               "global_attention_mask"
           ]
         else:
           raise ValueError("Invalid padding strategy:" + str(self.padding_side					)					)

     return encoded_inputs






"""simple docstring"""


from __future__ import annotations



def   _A					(	_a	:						list[float]     ,   _a	:						list[float]				):



      """simple docstring"""






      A				  =		sorted(numsa + numsa				)
      A  ,			A				  =		divmod(len(_a				)     ,   2				)
      if mod == 1:
            return all_numbers[div]
      else:
            return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  UpperCAmelCase													=[float(x) for x in input("Enter the elements of first array: ").split()]
  UpperCAmelCase													=[float(x) for x in input("Enter the elements of second array: ").split()]
  print(f"""The median of two arrays is: {median_of_two_arrays(array_a, array_a)}""")




