
"""simple docstring"""


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

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


_lowercase				 =					logging.get_logger(__name__)


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

_lowercase				 =					{
    '''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'''
        ),
    },
}

_lowercase				 =					'''</w>'''
_lowercase				 =					'''@@ '''






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


# Speech2Text2 has no max input length
_lowercase				 =					{'''facebook/s2t-wav2vec2-large-en-de''': 10_24}







class 					lowerCAmelCase_					(   _lowercase     ):



						'''simple docstring'''


						_lowerCamelCase:     Dict   =     VOCAB_FILES_NAMES
						_lowerCamelCase:     Tuple   =     PRETRAINED_VOCAB_FILES_MAP
						_lowerCamelCase:     List[Any]   =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_lowerCamelCase:     Union[str, Any]   =     ['''input_ids''', '''attention_mask''']


						def __init__(			self  :   Any	,A_  :   List[str]	,A_  :   str="<s>"	,A_  :   Optional[int]="<pad>"	,A_  :   List[str]="</s>"	,A_  :   List[Any]="<unk>"	,A_  :   List[str]=False	,A_  :   int=None	,**A_  :   Union[str, Any]	,)  -> Optional[int]:
							super().__init__(
							    unk_token=A_	,bos_token=A_	,eos_token=A_	,pad_token=A_	,do_lower_case=A_	,**A_	,)

							A     = do_lower_case

							with open(A_	,encoding='utf-8'   ) as vocab_handle:
								A     = json.load(A_   )
							A     = {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     = None
								A     = None
							else:
								with open(A_	,encoding='utf-8'   ) as merges_handle:
									A     = merges_handle.read().split('\n'   )[:-1]

								A     = [tuple(merge.split()[:2]   ) for merge in merges]
								A     = dict(zip(A_	,range(len(A_   )   )   )   )
								A     = {}


						@property
						def     _SCREAMING_SNAKE_CASE   (			self  :   str   )  -> int:
							return len(self.decoder   )


						def     _SCREAMING_SNAKE_CASE   (			self  :   List[Any]   )  -> Dict:
							return dict(self.encoder	,**self.added_tokens_encoder   )


						def     _SCREAMING_SNAKE_CASE   (			self  :   Any	,A_  :   Optional[Any]   )  -> Tuple:
							A     = tuple(token[:-1]   ) + (token[-1] + BPE_TOKEN_MERGES,)
							if token in self.cache:
								return self.cache[token]
							A     = get_pairs(A_   )

							if not pairs:
								return token

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

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

							if word.endswith(A_   ):
								A     = word.replace(A_	,''   )

							A     = word.replace(' '	,A_   )
							A     = word
							return word


						def     _SCREAMING_SNAKE_CASE   (			self  :   Any	,A_  :   str   )  -> List[str]:

							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     = text.lower()

							A     = text.split()

							A     = []
							for token in text:
								if token:
									split_tokens.extend(list(self.bpe(A_   ).split(' '   )   )   )

							return split_tokens


						def     _SCREAMING_SNAKE_CASE   (			self  :   Optional[int]	,A_  :   str   )  -> int:
							return self.encoder.get(A_	,self.encoder.get(self.unk_token   )   )


						def     _SCREAMING_SNAKE_CASE   (			self  :   Optional[Any]	,A_  :   int   )  -> str:
							A     = self.decoder.get(A_	,self.unk_token   )
							return result


						def     _SCREAMING_SNAKE_CASE   (			self  :   str	,A_  :   List[str]   )  -> str:
							A     = ' '.join(A_   )

							# make sure @@ tokens are concatenated
							A     = ''.join(string.split(A_   )   )

							return string




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

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

							A     = 0
							if self.bpe_ranks is None:
								return (vocab_file,)

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

							return (vocab_file, merges_file)
'''simple docstring'''


import math
import sys

def   A_      (       SCREAMING_SNAKE_CASE_						)			->int:
  if number != int(SCREAMING_SNAKE_CASE_						):
    raise ValueError("""the value of input must be a natural number"""						)
  if number < 0:
    raise ValueError("""the value of input must not be a negative number"""						)
  if number == 0:
    return 1
  lowercase_     =       [-1] * (number + 1)
  lowercase_     =       0
  for i in range(1 ,	number + 1						):
    lowercase_     =       sys.maxsize
    lowercase_     =       int(math.sqrt(SCREAMING_SNAKE_CASE_						)						)
    for j in range(1 ,	root + 1						):
      lowercase_     =       1 + answers[i - (j**2)]
      lowercase_     =       min(SCREAMING_SNAKE_CASE_ ,	SCREAMING_SNAKE_CASE_						)
    lowercase_     =       answer
  return answers[number]


if __name__ == "__main__":
       import doctest

       doctest.testmod()

