
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


lowerCamelCase      =logging.get_logger(__name__)


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

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

lowerCamelCase      ={
    "allenai/led-base-16384": 1_6_3_8_4,
}


@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def 							SCREAMING_SNAKE_CASE_      (			):
      UpperCamelCase__    :   Optional[int]					=				(
          list(range(ord('''!'''		) ,		ord('''~'''		) + 1		)		) + list(range(ord('''¡'''		) ,		ord('''¬'''		) + 1		)		) + list(range(ord('''®'''		) ,		ord('''ÿ'''		) + 1		)		)
      )
      UpperCamelCase__    :   Tuple					=				bs[:]
      UpperCamelCase__    :   Any					=				0
      for b in range(2**8		):
            if b not in bs:
                  bs.append(UpperCamelCase__		)
                  cs.append(2**8 + n		)
                  n += 1
      UpperCamelCase__    :   Any					=				[chr(UpperCamelCase__		) for n in cs]
      return dict(zip(UpperCamelCase__ ,		UpperCamelCase__		)		)


def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__		):
      UpperCamelCase__    :   Union[str, Any]					=				set()
      UpperCamelCase__    :   Dict					=				word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)		)
            UpperCamelCase__    :   Any					=				char
      return pairs




class 				_lowerCamelCase (      UpperCamelCase_ ):





     """simple docstring"""







     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''']






     def __init__(							self						,						__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE="replace"						,						__SCREAMING_SNAKE_CASE="<s>"						,						__SCREAMING_SNAKE_CASE="</s>"						,						__SCREAMING_SNAKE_CASE="</s>"						,						__SCREAMING_SNAKE_CASE="<s>"						,						__SCREAMING_SNAKE_CASE="<unk>"						,						__SCREAMING_SNAKE_CASE="<pad>"						,						__SCREAMING_SNAKE_CASE="<mask>"						,						__SCREAMING_SNAKE_CASE=False						,						**__SCREAMING_SNAKE_CASE						,						)  ->   Optional[Any]:




           """simple docstring"""







           UpperCamelCase__    :   List[str]					=				AddedToken(__SCREAMING_SNAKE_CASE						,						lstrip=__SCREAMING_SNAKE_CASE						,						rstrip=__SCREAMING_SNAKE_CASE  ) if isinstance(__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE  ) else bos_token
           UpperCamelCase__    :   List[str]					=				AddedToken(__SCREAMING_SNAKE_CASE						,						lstrip=__SCREAMING_SNAKE_CASE						,						rstrip=__SCREAMING_SNAKE_CASE  ) if isinstance(__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE  ) else eos_token
           UpperCamelCase__    :   Tuple					=				AddedToken(__SCREAMING_SNAKE_CASE						,						lstrip=__SCREAMING_SNAKE_CASE						,						rstrip=__SCREAMING_SNAKE_CASE  ) if isinstance(__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE  ) else sep_token
           UpperCamelCase__    :   int					=				AddedToken(__SCREAMING_SNAKE_CASE						,						lstrip=__SCREAMING_SNAKE_CASE						,						rstrip=__SCREAMING_SNAKE_CASE  ) if isinstance(__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE  ) else cls_token
           UpperCamelCase__    :   int					=				AddedToken(__SCREAMING_SNAKE_CASE						,						lstrip=__SCREAMING_SNAKE_CASE						,						rstrip=__SCREAMING_SNAKE_CASE  ) if isinstance(__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE  ) else unk_token
           UpperCamelCase__    :   Tuple					=				AddedToken(__SCREAMING_SNAKE_CASE						,						lstrip=__SCREAMING_SNAKE_CASE						,						rstrip=__SCREAMING_SNAKE_CASE  ) if isinstance(__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE  ) else pad_token

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

           super().__init__(
               errors=__SCREAMING_SNAKE_CASE						,						bos_token=__SCREAMING_SNAKE_CASE						,						eos_token=__SCREAMING_SNAKE_CASE						,						unk_token=__SCREAMING_SNAKE_CASE						,						sep_token=__SCREAMING_SNAKE_CASE						,						cls_token=__SCREAMING_SNAKE_CASE						,						pad_token=__SCREAMING_SNAKE_CASE						,						mask_token=__SCREAMING_SNAKE_CASE						,						add_prefix_space=__SCREAMING_SNAKE_CASE						,						**__SCREAMING_SNAKE_CASE						,						)

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

           # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
           UpperCamelCase__    :   List[str]					=				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    __SCREAMING_SNAKE_CASE			(							self  )  ->   Optional[Any]:




           """simple docstring"""







           return len(self.encoder  )






     def    __SCREAMING_SNAKE_CASE			(							self  )  ->   int:




           """simple docstring"""







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






     def    __SCREAMING_SNAKE_CASE			(							self						,						__SCREAMING_SNAKE_CASE  )  ->   Any:




           """simple docstring"""







           if token in self.cache:
                 return self.cache[token]
           UpperCamelCase__    :   int					=				tuple(__SCREAMING_SNAKE_CASE  )
           UpperCamelCase__    :   Tuple					=				get_pairs(__SCREAMING_SNAKE_CASE  )

           if not pairs:
                 return token

           while True:
                 UpperCamelCase__    :   Union[str, Any]					=				min(__SCREAMING_SNAKE_CASE						,						key=lambda __SCREAMING_SNAKE_CASE  : self.bpe_ranks.get(__SCREAMING_SNAKE_CASE						,						float('''inf'''  )  )  )
                 if bigram not in self.bpe_ranks:
                       break
                 UpperCamelCase__				,UpperCamelCase__    :   int					=				bigram
                 UpperCamelCase__    :   Union[str, Any]					=				[]
                 UpperCamelCase__    :   Union[str, Any]					=				0
                 while i < len(__SCREAMING_SNAKE_CASE  ):
                       try:
                             UpperCamelCase__    :   Optional[int]					=				word.index(__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE  )
                       except ValueError:
                             new_word.extend(word[i:]  )
                             break
                       else:
                             new_word.extend(word[i:j]  )
                             UpperCamelCase__    :   Optional[int]					=				j

                       if word[i] == first and i < len(__SCREAMING_SNAKE_CASE  ) - 1 and word[i + 1] == second:
                             new_word.append(first + second  )
                             i += 2
                       else:
                             new_word.append(word[i]  )
                             i += 1
                 UpperCamelCase__    :   str					=				tuple(__SCREAMING_SNAKE_CASE  )
                 UpperCamelCase__    :   Optional[int]					=				new_word
                 if len(__SCREAMING_SNAKE_CASE  ) == 1:
                       break
                 else:
                       UpperCamelCase__    :   Any					=				get_pairs(__SCREAMING_SNAKE_CASE  )
           UpperCamelCase__    :   Optional[Any]					=				''' '''.join(__SCREAMING_SNAKE_CASE  )
           UpperCamelCase__    :   str					=				word
           return word






     def    __SCREAMING_SNAKE_CASE			(							self						,						__SCREAMING_SNAKE_CASE  )  ->   List[Any]:




           """simple docstring"""







           UpperCamelCase__    :   str					=				[]
           for token in re.findall(self.pat						,						__SCREAMING_SNAKE_CASE  ):
                 UpperCamelCase__    :   Any					=				''''''.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(__SCREAMING_SNAKE_CASE  ).split(''' '''  )  )
           return bpe_tokens






     def    __SCREAMING_SNAKE_CASE			(							self						,						__SCREAMING_SNAKE_CASE  )  ->   List[str]:




           """simple docstring"""







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






     def    __SCREAMING_SNAKE_CASE			(							self						,						__SCREAMING_SNAKE_CASE  )  ->   Union[str, Any]:




           """simple docstring"""







           return self.decoder.get(__SCREAMING_SNAKE_CASE  )






     def    __SCREAMING_SNAKE_CASE			(							self						,						__SCREAMING_SNAKE_CASE  )  ->   Dict:




           """simple docstring"""







           UpperCamelCase__    :   str					=				''''''.join(__SCREAMING_SNAKE_CASE  )
           UpperCamelCase__    :   List[Any]					=				bytearray([self.byte_decoder[c] for c in text]  ).decode('''utf-8'''						,						errors=self.errors  )
           return text






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




           """simple docstring"""







           if not os.path.isdir(__SCREAMING_SNAKE_CASE  ):
                 logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''  )
                 return
           UpperCamelCase__    :   Dict					=				os.path.join(
               __SCREAMING_SNAKE_CASE						,						(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']  )
           UpperCamelCase__    :   Dict					=				os.path.join(
               __SCREAMING_SNAKE_CASE						,						(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']  )

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

           UpperCamelCase__    :   Any					=				0
           with open(__SCREAMING_SNAKE_CASE						,						'''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 __SCREAMING_SNAKE_CASE  : 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!'''  )
                             UpperCamelCase__    :   Any					=				token_index
                       writer.write(''' '''.join(__SCREAMING_SNAKE_CASE  ) + '''\n'''  )
                       index += 1

           return vocab_file, merge_file






     def    __SCREAMING_SNAKE_CASE			(							self						,						__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE = None  )  ->   List[int]:




           """simple docstring"""







           if token_ids_a is None:
                 return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
           UpperCamelCase__    :   Tuple					=				[self.cls_token_id]
           UpperCamelCase__    :   Tuple					=				[self.sep_token_id]
           return cls + token_ids_a + sep + sep + token_ids_a + sep






     def    __SCREAMING_SNAKE_CASE			(							self						,						__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE = None						,						__SCREAMING_SNAKE_CASE = False  )  ->   List[int]:




           """simple docstring"""







           if already_has_special_tokens:
                 return super().get_special_tokens_mask(
                     token_ids_a=__SCREAMING_SNAKE_CASE						,						token_ids_a=__SCREAMING_SNAKE_CASE						,						already_has_special_tokens=__SCREAMING_SNAKE_CASE  )

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






     def    __SCREAMING_SNAKE_CASE			(							self						,						__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE = None  )  ->   List[int]:




           """simple docstring"""







           UpperCamelCase__    :   int					=				[self.sep_token_id]
           UpperCamelCase__    :   int					=				[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    __SCREAMING_SNAKE_CASE			(							self						,						__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE=False						,						**__SCREAMING_SNAKE_CASE  )  ->   Tuple:




           """simple docstring"""







           UpperCamelCase__    :   int					=				kwargs.pop('''add_prefix_space'''						,						self.add_prefix_space  )
           if (is_split_into_words or add_prefix_space) and (len(__SCREAMING_SNAKE_CASE  ) > 0 and not text[0].isspace()):
                 UpperCamelCase__    :   Dict					=				''' ''' + text
           return (text, kwargs)






     def    __SCREAMING_SNAKE_CASE			(							self						,						__SCREAMING_SNAKE_CASE						,						__SCREAMING_SNAKE_CASE = None						,						__SCREAMING_SNAKE_CASE = PaddingStrategy.DO_NOT_PAD						,						__SCREAMING_SNAKE_CASE = None						,						__SCREAMING_SNAKE_CASE = None						,						)  ->   dict:




           """simple docstring"""







           UpperCamelCase__    :   Tuple					=				super()._pad(
               encoded_inputs=__SCREAMING_SNAKE_CASE						,						max_length=__SCREAMING_SNAKE_CASE						,						padding_strategy=__SCREAMING_SNAKE_CASE						,						pad_to_multiple_of=__SCREAMING_SNAKE_CASE						,						return_attention_mask=__SCREAMING_SNAKE_CASE						,						)

           # Load from model defaults
           if return_attention_mask is None:
                 UpperCamelCase__    :   Any					=				'''attention_mask''' in self.model_input_names

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

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

           return encoded_inputs




def 							SCREAMING_SNAKE_CASE_      (			UpperCamelCase__ = 5_0_0_0_0_0_0_0		):
      UpperCamelCase__    :   Any					=				set()
      UpperCamelCase__    :   Any					=				int((limit - 2_4) ** (1 / 2)		)

      UpperCamelCase__    :   Dict					=				set(range(3 ,		prime_square_limit + 1 ,		2		)		)
      primes.add(2		)
      for p in range(3 ,		prime_square_limit + 1 ,		2		):
            if p not in primes:
                  continue
            primes.difference_update(set(range(p * p ,		prime_square_limit + 1 ,		UpperCamelCase__		)		)		)

      for primea in primes:
            UpperCamelCase__    :   Dict					=				primea * primea
            for primea in primes:
                  UpperCamelCase__    :   str					=				primea * primea * primea
                  if square + cube >= limit - 1_6:
                        break
                  for primea in primes:
                        UpperCamelCase__    :   Dict					=				primea * primea * primea * primea
                        UpperCamelCase__    :   Tuple					=				square + cube + tetr
                        if total >= limit:
                              break
                        ret.add(UpperCamelCase__		)

      return len(UpperCamelCase__		)


if __name__ == "__main__":
    print(F'''{solution() = }''')


