



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

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


UpperCamelCase_										=					logging.get_logger(__name__)


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

UpperCamelCase_										=					{
    '''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'''
        ),
    },
}

UpperCamelCase_										=					'''</w>'''
UpperCamelCase_										=					'''@@ '''







def 	lowerCamelCase_   (  _a    :		List[Any]  ):



    '''simple docstring'''




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


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







class 	_snake_case							(			__a      ):






   '''simple docstring'''






   A__	:      List[str]    =		VOCAB_FILES_NAMES
   A__	:      Tuple    =		PRETRAINED_VOCAB_FILES_MAP
   A__	:      List[str]    =		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   A__	:      int    =		["input_ids", "attention_mask"]


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

       UpperCAmelCase_			:    Optional[Any]   						= do_lower_case

       with open(_UpperCamelCase   ,encoding="""utf-8"""				) as vocab_handle:
           UpperCAmelCase_			:    str   						= json.load(_UpperCamelCase				)
       UpperCAmelCase_			:    Tuple   						= {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.'''				)

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

           UpperCAmelCase_			:    Tuple   						= [tuple(merge.split()[:2]				) for merge in merges]
           UpperCAmelCase_			:    Optional[Any]   						= dict(zip(_UpperCamelCase   ,range(len(_UpperCamelCase				)				)				)				)
           UpperCAmelCase_			:    int   						= {}


   @property
   def 	A__  (  self:			Dict				)     ->	int:
       return len(self.decoder				)


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


   def 	A__  (  self:			Optional[Any]   ,lowerCamelCase_:			int				)     ->	Optional[int]:
       UpperCAmelCase_			:    List[Any]   						= tuple(token[:-1]				) + (token[-1] + BPE_TOKEN_MERGES,)
       if token in self.cache:
           return self.cache[token]
       UpperCAmelCase_			:    Optional[int]   						= get_pairs(_UpperCamelCase				)

       if not pairs:
           return token

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

               if word[i] == first and i < len(_UpperCamelCase				) - 1 and word[i + 1] == second:
                   new_word.append(first + second				)
                   i += 2
               else:
                   new_word.append(word[i]				)
                   i += 1
           UpperCAmelCase_			:    List[str]   						= tuple(_UpperCamelCase				)
           UpperCAmelCase_			:    List[str]   						= new_word
           if len(_UpperCamelCase				) == 1:
               break
           else:
               UpperCAmelCase_			:    Tuple   						= get_pairs(_UpperCamelCase				)
       UpperCAmelCase_			:    Tuple   						= """ """.join(_UpperCamelCase				)
       if word == "\n  " + BPE_TOKEN_MERGES:
           UpperCAmelCase_			:    Union[str, Any]   						= """\n""" + BPE_TOKEN_MERGES

       if word.endswith(_UpperCamelCase				):
           UpperCAmelCase_			:    Any   						= word.replace(_UpperCamelCase   ,""""""				)

       UpperCAmelCase_			:    Any   						= word.replace(""" """   ,_UpperCamelCase				)
       UpperCAmelCase_			:    str   						= word
       return word


   def 	A__  (  self:			Dict   ,lowerCamelCase_:			Dict				)     ->	int:

       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:
           UpperCAmelCase_			:    Tuple   						= text.lower()

       UpperCAmelCase_			:    Tuple   						= text.split()

       UpperCAmelCase_			:    str   						= []
       for token in text:
           if token:
               split_tokens.extend(list(self.bpe(_UpperCamelCase				).split(""" """				)				)				)

       return split_tokens


   def 	A__  (  self:			Tuple   ,lowerCamelCase_:			Dict				)     ->	int:
       return self.encoder.get(_UpperCamelCase   ,self.encoder.get(self.unk_token				)				)


   def 	A__  (  self:			Tuple   ,lowerCamelCase_:			List[str]				)     ->	str:
       UpperCAmelCase_			:    List[Any]   						= self.decoder.get(_UpperCamelCase   ,self.unk_token				)
       return result


   def 	A__  (  self:			List[Any]   ,lowerCamelCase_:			Optional[Any]				)     ->	str:
       UpperCAmelCase_			:    Optional[int]   						= """ """.join(_UpperCamelCase				)

       # make sure @@ tokens are concatenated
       UpperCAmelCase_			:    int   						= """""".join(string.split(_UpperCamelCase				)				)

       return string






   def 	A__  (  self:			List[Any]   ,lowerCamelCase_:			Union[str, Any]   ,lowerCamelCase_:			Optional[int] = None				)     ->	Tuple[str]:
       if not os.path.isdir(_UpperCamelCase				):
           logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''				)
           return
       UpperCAmelCase_			:    Any   						= os.path.join(
           _UpperCamelCase   ,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]				)
       UpperCAmelCase_			:    Dict   						= os.path.join(
           _UpperCamelCase   ,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]				)

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

       UpperCAmelCase_			:    Union[str, Any]   						= 0
       if self.bpe_ranks is None:
           return (vocab_file,)

       with open(_UpperCamelCase   ,"""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!"""				)
                   UpperCAmelCase_			:    str   						= token_index
               writer.write(""" """.join(_UpperCamelCase				) + """\n"""				)
               index += 1

       return (vocab_file, merges_file)


import functools






def    lowerCamelCase__				(				__lowerCAmelCase  :  str    ,							__lowerCAmelCase  :  str				):




			"""simple docstring"""


			lowerCAmelCase_						=	len(__lowerCAmelCase				)
			lowerCAmelCase_						=	len(__lowerCAmelCase				)

			@functools.cache
			def min_distance(__lowerCAmelCase  :  int    ,							__lowerCAmelCase  :  int				) -> int:
						# if first word index is overflow - delete all from the second word
						if indexa >= len_worda:
									return len_worda - indexa
						# if second word index is overflow - delete all from the first word
						if indexa >= len_worda:
									return len_worda - indexa
						lowerCAmelCase_						=	int(worda[indexa] != worda[indexa]				)  # current letters not identical
						return min(
						    1 + min_distance(indexa + 1    ,							__lowerCAmelCase				)    ,							1 + min_distance(__lowerCAmelCase    ,							indexa + 1				)    ,							diff + min_distance(indexa + 1    ,							indexa + 1				)    ,							)

			return min_distance(0    ,							0				)


if __name__ == "__main__":
			import doctest

			doctest.testmod()



