




'''simple docstring'''





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

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


__lowerCAmelCase	:       Any     =	logging.get_logger(__name__)


__lowerCAmelCase	:       Union[str, Any]     =	{
    'vocab_file': 'vocab.json',
    'tokenizer_config_file': 'tokenizer_config.json',
    'merges_file': 'merges.txt',
}

__lowerCAmelCase	:       List[str]     =	{
    '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'
        ),
    },
}

__lowerCAmelCase	:       int     =	'</w>'
__lowerCAmelCase	:       List[Any]     =	'@@ '




def     __magic_name__       (				A	:      Tuple     ):






			'''simple docstring'''







			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
__lowerCAmelCase	:       Dict     =	{'facebook/s2t-wav2vec2-large-en-de': 1024}






class 					snake_case__							(snake_case__     ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_ :							int											=      VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_ :							str											=      PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_ :							Optional[Any]											=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE_ :							Optional[Any]											=      ["""input_ids""", """attention_mask"""]





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

							a					=    do_lower_case

							with open(UpperCAmelCase_      ,   encoding="utf-8"							) as vocab_handle:
										a					=    json.load(UpperCAmelCase_							)
							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(UpperCAmelCase_      ,   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(UpperCAmelCase_      ,   range(len(UpperCAmelCase_							)							)							)							)
										a					=    {}





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





				def 							__UpperCAmelCase							(   self       :  int							)      ->  Dict:
							return dict(self.encoder      ,   **self.added_tokens_encoder							)





				def 							__UpperCAmelCase							(   self       :  int      ,   __lowerCamelCase       :  List[Any]							)      ->  List[Any]:
							a					=    tuple(token[:-1]							) + (token[-1] + BPE_TOKEN_MERGES,)
							if token in self.cache:
										return self.cache[token]
							a					=    get_pairs(UpperCAmelCase_							)

							if not pairs:
										return token

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

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

							a					=    word.replace(" "      ,   UpperCAmelCase_							)
							a					=    word
							return word





				def 							__UpperCAmelCase							(   self       :  Union[str, Any]      ,   __lowerCamelCase       :  Optional[Any]							)      ->  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(UpperCAmelCase_							).split(" "							)							)							)

							return split_tokens





				def 							__UpperCAmelCase							(   self       :  List[Any]      ,   __lowerCamelCase       :  str							)      ->  int:
							return self.encoder.get(UpperCAmelCase_      ,   self.encoder.get(self.unk_token							)							)





				def 							__UpperCAmelCase							(   self       :  List[Any]      ,   __lowerCamelCase       :  int							)      ->  str:
							a					=    self.decoder.get(UpperCAmelCase_      ,   self.unk_token							)
							return result





				def 							__UpperCAmelCase							(   self       :  Tuple      ,   __lowerCamelCase       :  List[str]							)      ->  str:
							a					=    " ".join(UpperCAmelCase_							)

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

							return string





				def 							__UpperCAmelCase							(   self       :  Any      ,   __lowerCamelCase       :  str      ,   __lowerCamelCase       :  Optional[str] = None							)      ->  Tuple[str]:



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

							a					=    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!"							)
																a					=    token_index
													writer.write(" ".join(UpperCAmelCase_							) + "\n"							)
													index += 1

							return (vocab_file, merges_file)












def     __magic_name__       (				A	:      str,						A	:      str     ):






			'''simple docstring'''







			def get_matched_characters(A	:      str,						A	:      str     ) -> str:
						a					=    []
						a					=    min(len(_stra     ),						len(_stra     )     ) // 2
						for i, l in enumerate(_stra     ):
									a					=    int(max(0,						i - limit     )     )
									a					=    int(min(i + limit + 1,						len(_stra     )     )     )
									if l in _stra[left:right]:
												matched.append(A     )
												a					=    F"""{_stra[0:_stra.index(A     )]} {_stra[_stra.index(A     ) + 1:]}"""

						return "".join(A     )

			# matching characters
			a					=    get_matched_characters(A,						A     )
			a					=    get_matched_characters(A,						A     )
			a					=    len(A     )

			# transposition
			a					=    (
			    len([(ca, ca) for ca, ca in zip(A,						A     ) if ca != ca]     ) // 2
			)

			if not match_count:
						a					=    0.0
			else:
						a					=    (
						    1
						    / 3
						    * (
						        match_count / len(A     )
						        + match_count / len(A     )
						        + (match_count - transpositions) / match_count
						    )
						)

			# common prefix up to 4 characters
			a					=    0
			for ca, ca in zip(stra[:4],						stra[:4]     ):
						if ca == ca:
									prefix_len += 1
						else:
									break

			return jaro + 0.1 * prefix_len * (1 - jaro)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		print(jaro_winkler('hello', 'world'))






