




"""simple docstring"""
from argparse import ArgumentParser

from . import BaseTransformersCLICommand





def      UpperCAmelCase				(			A__:    Tuple     )  ->     List[str]:
			return DownloadCommand(args.model							,				args.cache_dir							,				args.force							,				args.trust_remote_code     )






class __lowercase(      _A				):




					'''simple docstring'''


					@staticmethod
					def     snake_case_				(    __a     ):
								__lowerCamelCase					:	Any	       =				parser.add_parser('download'     )
								download_parser.add_argument(
								    '--cache-dir'						,	type=__a						,	default=__a						,	help='Path to location to store the models'     )
								download_parser.add_argument(
								    '--force'						,	action='store_true'						,	help='Force the model to be download even if already in cache-dir'     )
								download_parser.add_argument(
								    '--trust-remote-code'						,	action='store_true'						,	help='Whether or not to allow for custom models defined on the Hub in their own modeling files. Use only if you\'ve reviewed the code as it will execute on your local machine'						,	)
								download_parser.add_argument('model'						,	type=__a						,	help='Name of the model to download'     )
								download_parser.set_defaults(func=__a     )
					def __init__(    self						,	__a						,	__a						,	__a						,	__a     ):
								__lowerCamelCase					:	List[Any]	       =				model
								__lowerCamelCase					:	int	       =				cache
								__lowerCamelCase					:	Union[str, Any]	       =				force
								__lowerCamelCase					:	Dict	       =				trust_remote_code





					def     snake_case_				(    self     ):
								from ..models.auto import AutoModel, AutoTokenizer

								AutoModel.from_pretrained(
								    self._model						,	cache_dir=self._cache						,	force_download=self._force						,	trust_remote_code=self._trust_remote_code     )
								AutoTokenizer.from_pretrained(
								    self._model						,	cache_dir=self._cache						,	force_download=self._force						,	trust_remote_code=self._trust_remote_code     )









"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple

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


a_				:    Dict										=     logging.get_logger(__name__)


a_				:    List[Any]										=     {
    '''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_				:    Dict										=     '''@@ '''





def 						UpperCAmelCase				(			A__:    Optional[Any]     )  ->     Optional[int]:
			__lowerCamelCase					:	Any	       =				set()
			__lowerCamelCase					:	Optional[int]	       =				word[0]
			for char in word[1:]:
						pairs.add((prev_char, char)     )
						__lowerCamelCase					:	Optional[int]	       =				char
			return pairs


# Speech2Text2 has no max input length
a_				:    Union[str, Any]										=     {'''facebook/s2t-wav2vec2-large-en-de''': 10_24}






class __lowercase(      lowercase__				):




					'''simple docstring'''


					__a						:						List[str]     		= VOCAB_FILES_NAMES
					__a						:						Optional[int]     		= PRETRAINED_VOCAB_FILES_MAP
					__a						:						Union[str, Any]     		= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					__a						:						Dict     		= ['input_ids', 'attention_mask']
					def __init__(    self						,	__a						,	__a="<s>"						,	__a="<pad>"						,	__a="</s>"						,	__a="<unk>"						,	__a=False						,	__a=None						,	**__a						,	):
								super().__init__(
								    unk_token=__a						,	bos_token=__a						,	eos_token=__a						,	pad_token=__a						,	do_lower_case=__a						,	**__a						,	)

								__lowerCamelCase					:	List[Any]	       =				do_lower_case

								with open(__a						,	encoding='utf-8'     ) as vocab_handle:
											__lowerCamelCase					:	str	       =				json.load(__a     )
								__lowerCamelCase					:	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.'''     )

											__lowerCamelCase					:	str	       =				None
											__lowerCamelCase					:	Optional[int]	       =				None
								else:
											with open(__a						,	encoding='utf-8'     ) as merges_handle:
														__lowerCamelCase					:	Optional[int]	       =				merges_handle.read().split('\n'     )[:-1]

											__lowerCamelCase					:	List[str]	       =				[tuple(merge.split()[:2]     ) for merge in merges]
											__lowerCamelCase					:	Any	       =				dict(zip(__a						,	range(len(__a     )     )     )     )
											__lowerCamelCase					:	List[str]	       =				{}
					@property
					def     snake_case_				(    self     ):
								return len(self.decoder     )
					def     snake_case_				(    self     ):
								return dict(self.encoder						,	**self.added_tokens_encoder     )
					def     snake_case_				(    self						,	__a     ):
								__lowerCamelCase					:	Optional[Any]	       =				tuple(token[:-1]     ) + (token[-1] + BPE_TOKEN_MERGES,)
								if token in self.cache:
											return self.cache[token]
								__lowerCamelCase					:	Union[str, Any]	       =				get_pairs(__a     )

								if not pairs:
											return token

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

								if word.endswith(__a     ):
											__lowerCamelCase					:	Tuple	       =				word.replace(__a						,	''     )

								__lowerCamelCase					:	Optional[Any]	       =				word.replace(' '						,	__a     )
								__lowerCamelCase					:	Union[str, Any]	       =				word
								return word
					def     snake_case_				(    self						,	__a     ):

								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:
											__lowerCamelCase					:	Any	       =				text.lower()

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

								__lowerCamelCase					:	str	       =				[]
								for token in text:
											if token:
														split_tokens.extend(list(self.bpe(__a     ).split(' '     )     )     )

								return split_tokens
					def     snake_case_				(    self						,	__a     ):
								return self.encoder.get(__a						,	self.encoder.get(self.unk_token     )     )
					def     snake_case_				(    self						,	__a     ):
								__lowerCamelCase					:	int	       =				self.decoder.get(__a						,	self.unk_token     )
								return result
					def     snake_case_				(    self						,	__a     ):
								__lowerCamelCase					:	Any	       =				' '.join(__a     )

								# make sure @@ tokens are concatenated
								__lowerCamelCase					:	Union[str, Any]	       =				''.join(string.split(__a     )     )

								return string





					def     snake_case_				(    self						,	__a						,	__a = None     ):
								if not os.path.isdir(__a     ):
											logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''     )
											return
								__lowerCamelCase					:	int	       =				os.path.join(
								    __a						,	(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']     )
								__lowerCamelCase					:	Any	       =				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'     )

								__lowerCamelCase					:	Optional[int]	       =				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!'     )
																	__lowerCamelCase					:	Optional[int]	       =				token_index
														writer.write(' '.join(__a     ) + '\n'     )
														index += 1

								return (vocab_file, merges_file)



