





"""simple docstring"""




import json
import os
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


a		:					int	      =     logging.get_logger(__name__)


a		:					Dict	      =     {
    '''vocab_file''': '''vocab.json''',
    '''tokenizer_config_file''': '''tokenizer_config.json''',
    '''merges_file''': '''merges.txt''',
}

a		:					Tuple	      =     {
    '''vocab_file''': {
        '''facebook/s2t-wav2vec2-large-en-de''': (
            '''https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/vocab.json'''
        ),
    },
    '''tokenizer_config_file''': {
        '''facebook/s2t-wav2vec2-large-en-de''': (
            '''https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/tokenizer_config.json'''
        ),
    },
    '''merges_file''': {
        '''facebook/s2t-wav2vec2-large-en-de''': (
            '''https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/merges.txt'''
        ),
    },
}

a		:					Optional[Any]	      =     '''</w>'''
a		:					str	      =     '''@@ '''






def  _SCREAMING_SNAKE_CASE						(      _lowercase		:       str   )					->List[str]:






	'''simple docstring'''






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


# Speech2Text2 has no max input length
a		:					Tuple	      =     {'''facebook/s2t-wav2vec2-large-en-de''': 1024}







class 			__UpperCamelCase							(		lowerCAmelCase__		):
							lowerCamelCase  :   str    =VOCAB_FILES_NAMES
							lowerCamelCase  :   List[Any]    =PRETRAINED_VOCAB_FILES_MAP
							lowerCamelCase  :   Tuple    =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowerCamelCase  :   Union[str, Any]    =["""input_ids""", """attention_mask"""]






							def __init__(  self ,   lowerCAmelCase__ ,   lowerCAmelCase__="<s>" ,   lowerCAmelCase__="<pad>" ,   lowerCAmelCase__="</s>" ,   lowerCAmelCase__="<unk>" ,   lowerCAmelCase__=False ,   lowerCAmelCase__=None ,   **lowerCAmelCase__ ,   )      ->					Dict:
								super().__init__(
								    unk_token=_lowerCamelCase ,   bos_token=_lowerCamelCase ,   eos_token=_lowerCamelCase ,   pad_token=_lowerCamelCase ,   do_lower_case=_lowerCamelCase ,   **_lowerCamelCase ,   )

								a :						Union[str, Any]      =							do_lower_case

								with open(_lowerCamelCase ,   encoding="utf-8" ) as vocab_handle:
									a :						Optional[int]      =							json.load(_lowerCamelCase )
								a :						Optional[int]      =							{v: k for k, v in self.encoder.items()}

								if merges_file is None:
									logger.info(f"""No merges files provided. {self.__class__.__name__} can only be used for decoding.""" )

									a :						Optional[int]      =							None
									a :						List[str]      =							None
								else:
									with open(_lowerCamelCase ,   encoding="utf-8" ) as merges_handle:
										a :						List[Any]      =							merges_handle.read().split("\n" )[:-1]

									a :						List[Any]      =							[tuple(merge.split()[:2] ) for merge in merges]
									a :						Any      =							dict(zip(_lowerCamelCase ,   range(len(_lowerCamelCase ) ) ) )
									a :						Dict      =							{}






							@property
							def        __a  (  self )      ->					Union[str, Any]:
								return len(self.decoder )






							def        __a  (  self )      ->					Any:
								return dict(self.encoder ,   **self.added_tokens_encoder )






							def        __a  (  self ,   lowerCAmelCase__ )      ->					Optional[int]:
								a :						Optional[Any]      =							tuple(token[:-1] ) + (token[-1] + BPE_TOKEN_MERGES,)
								if token in self.cache:
									return self.cache[token]
								a :						Optional[Any]      =							get_pairs(_lowerCamelCase )

								if not pairs:
									return token

								while True:
									a :						Optional[Any]      =							min(_lowerCamelCase ,   key=lambda lowerCAmelCase__ : self.bpe_ranks.get(_lowerCamelCase ,   float("inf" ) ) )
									if bigram not in self.bpe_ranks:
										break
									a :						Dict      =							bigram
									a :						Union[str, Any]      =							[]
									a :						Optional[Any]      =							0
									while i < len(_lowerCamelCase ):
										try:
											a :						Any      =							word.index(_lowerCamelCase ,   _lowerCamelCase )
										except ValueError:
											new_word.extend(word[i:] )
											break
										else:
											new_word.extend(word[i:j] )
											a :						Dict      =							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 :						Dict      =							tuple(_lowerCamelCase )
									a :						Tuple      =							new_word
									if len(_lowerCamelCase ) == 1:
										break
									else:
										a :						Any      =							get_pairs(_lowerCamelCase )
								a :						Any      =							""" """.join(_lowerCamelCase )
								if word == "\n  " + BPE_TOKEN_MERGES:
									a :						Tuple      =							"""\n""" + BPE_TOKEN_MERGES

								if word.endswith(_lowerCamelCase ):
									a :						Union[str, Any]      =							word.replace(_lowerCamelCase ,   "" )

								a :						Any      =							word.replace(" " ,   _lowerCamelCase )
								a :						Tuple      =							word
								return word






							def        __a  (  self ,   lowerCAmelCase__ )      ->					Tuple:

								if self.bpe_ranks is None:
									raise ValueError(
									    "This tokenizer was instantiated without a `merges.txt` file, so"
									    " that it can only be used for decoding, not for encoding."
									    "Make sure to provide `merges.txt` file at instantiation to enable "
									    "encoding." )

								if self.do_lower_case:
									a :						Optional[int]      =							text.lower()

								a :						Union[str, Any]      =							text.split()

								a :						int      =							[]
								for token in text:
									if token:
										split_tokens.extend(list(self.bpe(_lowerCamelCase ).split(" " ) ) )

								return split_tokens






							def        __a  (  self ,   lowerCAmelCase__ )      ->					List[Any]:
								return self.encoder.get(_lowerCamelCase ,   self.encoder.get(self.unk_token ) )






							def        __a  (  self ,   lowerCAmelCase__ )      ->					Optional[Any]:
								a :						List[Any]      =							self.decoder.get(_lowerCamelCase ,   self.unk_token )
								return result






							def        __a  (  self ,   lowerCAmelCase__ )      ->					List[Any]:
								a :						Tuple      =							""" """.join(_lowerCamelCase )

								# make sure @@ tokens are concatenated
								a :						Any      =							"""""".join(string.split(_lowerCamelCase ) )

								return string






							def        __a  (  self ,   lowerCAmelCase__ ,   lowerCAmelCase__ = None )      ->					List[str]:

								if not os.path.isdir(_lowerCamelCase ):
									logger.error(f"""Vocabulary path ({save_directory}) should be a directory""" )
									return
								a :						Optional[int]      =							os.path.join(
								    _lowerCamelCase ,   (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"] )
								a :						str      =							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 :						str      =							0
								if self.bpe_ranks is None:
									return (vocab_file,)

								with open(_lowerCamelCase ,   "w" ,   encoding="utf-8" ) as writer:
									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 {merges_file}: BPE merge indices are not consecutive."""
											    " Please check that the tokenizer is not corrupted!" )
											a :						Dict      =							token_index
										writer.write(" ".join(_lowerCamelCase ) + "\n" )
										index += 1

								return (vocab_file, merges_file)





"""simple docstring"""
from __future__ import annotations

from functools import lru_cache
from math import ceil

_A							=  1_00

_A							=  set(range(3, NUM_PRIMES, 2))
primes.add(2)
_A							=  42

for prime in range(3, ceil(NUM_PRIMES**0.5), 2):
    if prime not in primes:
        continue
    primes.difference_update(set(range(prime * prime, NUM_PRIMES, prime)))




@lru_cache(maxsize=1_00    )
def 					a__						(						lowerCAmelCase    )	-> set[int]:
      if number_to_partition < 0:
            return set()
      elif number_to_partition == 0:
            return {1}

      UpperCAmelCase__			:							set[int]							=    set()
      UpperCAmelCase__			:							int
      UpperCAmelCase__			:							int

      for prime in primes:
            if prime > number_to_partition:
                  continue
            for sub in partition(number_to_partition - prime    ):
                  ret.add(sub * prime    )

      return ret




def 					a__						(						lowerCAmelCase = 50_00    )	-> int | None:
      for number_to_partition in range(1			,	lowerCAmelCase    ):
            if len(partition(lowerCAmelCase    )    ) > number_unique_partitions:
                  return number_to_partition
      return None


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

