






import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union

import sentencepiece

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


lowercase  :							str			  =    logging.get_logger(__name__)

lowercase  :							Optional[int]			  =    '''▁'''

lowercase  :							Optional[Any]			  =    {
    '''vocab_file''': '''vocab.json''',
    '''spm_file''': '''sentencepiece.bpe.model''',
}

lowercase  :							Optional[int]			  =    {
    '''vocab_file''': {
        '''facebook/s2t-small-librispeech-asr''': (
            '''https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/vocab.json'''
        ),
    },
    '''spm_file''': {
        '''facebook/s2t-small-librispeech-asr''': (
            '''https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/sentencepiece.bpe.model'''
        )
    },
}

lowercase  :							List[str]			  =    {
    '''facebook/s2t-small-librispeech-asr''': 10_24,
}

lowercase  :							List[Any]			  =    ['''pt''', '''fr''', '''ru''', '''nl''', '''ro''', '''it''', '''es''', '''de''']

lowercase  :							str			  =    {'''mustc''': MUSTC_LANGS}




class 		UpperCAmelCase_						(	SCREAMING_SNAKE_CASE__					):


						'''simple docstring'''




						A     :   List[Any]						=					VOCAB_FILES_NAMES
						A     :   Any						=					PRETRAINED_VOCAB_FILES_MAP
						A     :   List[str]						=					MAX_MODEL_INPUT_SIZES
						A     :   int						=					['input_ids', 'attention_mask']

						A     :   List[int]						=					[]






						def __init__(	self		,				_SCREAMING_SNAKE_CASE		,				_SCREAMING_SNAKE_CASE		,				_SCREAMING_SNAKE_CASE="<s>"		,				_SCREAMING_SNAKE_CASE="</s>"		,				_SCREAMING_SNAKE_CASE="<pad>"		,				_SCREAMING_SNAKE_CASE="<unk>"		,				_SCREAMING_SNAKE_CASE=False		,				_SCREAMING_SNAKE_CASE=False		,				_SCREAMING_SNAKE_CASE=None		,				_SCREAMING_SNAKE_CASE=None		,				_SCREAMING_SNAKE_CASE = None		,				**_SCREAMING_SNAKE_CASE		,				) ->				None:
								snake_case_				:							Tuple						 =       {} if sp_model_kwargs is None else sp_model_kwargs

								super().__init__(
								    bos_token=_SCREAMING_SNAKE_CASE		,				eos_token=_SCREAMING_SNAKE_CASE		,				unk_token=_SCREAMING_SNAKE_CASE		,				pad_token=_SCREAMING_SNAKE_CASE		,				do_upper_case=_SCREAMING_SNAKE_CASE		,				do_lower_case=_SCREAMING_SNAKE_CASE		,				tgt_lang=_SCREAMING_SNAKE_CASE		,				lang_codes=_SCREAMING_SNAKE_CASE		,				sp_model_kwargs=self.sp_model_kwargs		,				**_SCREAMING_SNAKE_CASE		,				)
								snake_case_				:							List[str]						 =       do_upper_case
								snake_case_				:							Dict						 =       do_lower_case

								snake_case_				:							Dict						 =       load_json(_SCREAMING_SNAKE_CASE				)
								snake_case_				:							Union[str, Any]						 =       {v: k for k, v in self.encoder.items()}
								snake_case_				:							Union[str, Any]						 =       spm_file
								snake_case_				:							Any						 =       load_spm(_SCREAMING_SNAKE_CASE		,				self.sp_model_kwargs				)

								if lang_codes is not None:
										snake_case_				:							List[str]						 =       lang_codes
										snake_case_				:							str						 =       LANGUAGES[lang_codes]
										snake_case_				:							List[str]						 =       [f'''<lang:{lang}>''' for lang in self.langs]
										snake_case_				:							Optional[Any]						 =       {lang: self.sp_model.PieceToId(f'''<lang:{lang}>'''				) for lang in self.langs}

										snake_case_				:							int						 =       self.lang_tokens
										snake_case_				:							Any						 =       tgt_lang if tgt_lang is not None else self.langs[0]

										self.set_tgt_lang_special_tokens(self._tgt_lang				)
								else:
										snake_case_				:							str						 =       {}






						@property
						def       _lowerCAmelCase       (	self				) ->				int:
								return len(self.encoder				)






						@property
						def       _lowerCAmelCase       (	self				) ->				str:
								return self._tgt_lang






						@tgt_lang.setter
						def       _lowerCAmelCase       (	self		,				_SCREAMING_SNAKE_CASE				) ->				None:
								snake_case_				:							List[Any]						 =       new_tgt_lang
								self.set_tgt_lang_special_tokens(_SCREAMING_SNAKE_CASE				)






						def       _lowerCAmelCase       (	self		,				_SCREAMING_SNAKE_CASE				) ->				None:
								snake_case_				:							str						 =       self.lang_code_to_id[tgt_lang]
								snake_case_				:							List[Any]						 =       [lang_code_id]






						def       _lowerCAmelCase       (	self		,				_SCREAMING_SNAKE_CASE				) ->				List[str]:
								return self.sp_model.encode(_SCREAMING_SNAKE_CASE		,				out_type=_SCREAMING_SNAKE_CASE				)






						def       _lowerCAmelCase       (	self		,				_SCREAMING_SNAKE_CASE				) ->				Optional[Any]:
								return self.encoder.get(_SCREAMING_SNAKE_CASE		,				self.encoder[self.unk_token]				)






						def       _lowerCAmelCase       (	self		,				_SCREAMING_SNAKE_CASE				) ->				str:
								return self.decoder.get(_SCREAMING_SNAKE_CASE		,				self.unk_token				)






						def       _lowerCAmelCase       (	self		,				_SCREAMING_SNAKE_CASE				) ->				str:
								snake_case_				:							Optional[Any]						 =       []
								snake_case_				:							Optional[int]						 =       ""
								for token in tokens:
										# make sure that special tokens are not decoded using sentencepiece model
										if token in self.all_special_tokens:
												snake_case_				:							str						 =       self.sp_model.decode(_SCREAMING_SNAKE_CASE				)
												out_string += (decoded.upper() if self.do_upper_case else decoded) + token + " "
												snake_case_				:							str						 =       []
										else:
												current_sub_tokens.append(_SCREAMING_SNAKE_CASE				)
								snake_case_				:							Union[str, Any]						 =       self.sp_model.decode(_SCREAMING_SNAKE_CASE				)
								out_string += decoded.upper() if self.do_upper_case else decoded
								return out_string.strip()






						def       _lowerCAmelCase       (	self		,				_SCREAMING_SNAKE_CASE		,				_SCREAMING_SNAKE_CASE=None				) ->				List[int]:
								if token_ids_a is None:
										return self.prefix_tokens + token_ids_a + [self.eos_token_id]
								# We don't expect to process pairs, but leave the pair logic for API consistency
								return self.prefix_tokens + token_ids_a + token_ids_a + [self.eos_token_id]






						def       _lowerCAmelCase       (	self		,				_SCREAMING_SNAKE_CASE		,				_SCREAMING_SNAKE_CASE = None		,				_SCREAMING_SNAKE_CASE = False				) ->				List[int]:

								if already_has_special_tokens:
										return super().get_special_tokens_mask(
										    token_ids_a=_SCREAMING_SNAKE_CASE		,				token_ids_a=_SCREAMING_SNAKE_CASE		,				already_has_special_tokens=_SCREAMING_SNAKE_CASE				)

								snake_case_				:							Optional[Any]						 =       [1] * len(self.prefix_tokens				)
								snake_case_				:							Tuple						 =       [1]
								if token_ids_a is None:
										return prefix_ones + ([0] * len(_SCREAMING_SNAKE_CASE				)) + suffix_ones
								return prefix_ones + ([0] * len(_SCREAMING_SNAKE_CASE				)) + ([0] * len(_SCREAMING_SNAKE_CASE				)) + suffix_ones






						def       _lowerCAmelCase       (	self				) ->				Dict:
								snake_case_				:							Optional[Any]						 =       self.encoder.copy()
								vocab.update(self.added_tokens_encoder				)
								return vocab






						def __getstate__(	self				) ->				Dict:
								snake_case_				:							str						 =       self.__dict__.copy()
								snake_case_				:							Union[str, Any]						 =       None
								return state






						def __setstate__(	self		,				_SCREAMING_SNAKE_CASE				) ->				None:
								snake_case_				:							List[Any]						 =       d

								# for backward compatibility
								if not hasattr(self		,				"sp_model_kwargs"				):
										snake_case_				:							Optional[int]						 =       {}

								snake_case_				:							Union[str, Any]						 =       load_spm(self.spm_file		,				self.sp_model_kwargs				)






						def       _lowerCAmelCase       (	self		,				_SCREAMING_SNAKE_CASE		,				_SCREAMING_SNAKE_CASE = None				) ->				Tuple[str]:
								snake_case_				:							int						 =       Path(_SCREAMING_SNAKE_CASE				)
								assert save_dir.is_dir(), f'''{save_directory} should be a directory'''
								snake_case_				:							Optional[Any]						 =       save_dir / (
								    (filename_prefix + "-" if filename_prefix else "") + self.vocab_files_names["vocab_file"]
								)
								snake_case_				:							int						 =       save_dir / (
								    (filename_prefix + "-" if filename_prefix else "") + self.vocab_files_names["spm_file"]
								)

								save_json(self.encoder		,				_SCREAMING_SNAKE_CASE				)

								if os.path.abspath(self.spm_file				) != os.path.abspath(_SCREAMING_SNAKE_CASE				) and os.path.isfile(self.spm_file				):
										copyfile(self.spm_file		,				_SCREAMING_SNAKE_CASE				)
								elif not os.path.isfile(self.spm_file				):
										with open(_SCREAMING_SNAKE_CASE		,				"wb"				) as fi:
												snake_case_				:							Dict						 =       self.sp_model.serialized_model_proto()
												fi.write(_SCREAMING_SNAKE_CASE				)

								return (str(_SCREAMING_SNAKE_CASE				), str(_SCREAMING_SNAKE_CASE				))




def      lowerCAmelCase__	(    _a       :			str  ,      _a       :			Dict[str, Any]    ):
		snake_case_				:							Optional[int]						 =       sentencepiece.SentencePieceProcessor(**_a    )
		spm.Load(str(_a    )    )
		return spm

def      lowerCAmelCase__	(    _a       :			str    ):
		with open(_a  ,      "r"    ) as f:
				return json.load(_a    )

def      lowerCAmelCase__	(    _a       :			int  ,      _a       :			str    ):
		with open(_a  ,      "w"    ) as f:
				json.dump(_a  ,      _a  ,      indent=2    )








import math

def      lowerCAmelCase__	(    _a       :			int    ):

		if 1 < number < 4:
				# 2 and 3 are primes
				return True
		elif number < 2 or number % 2 == 0 or number % 3 == 0:
				# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
				return False

		# All primes number are in format of 6k +/- 1
		for i in range(5  ,      int(math.sqrt(_a    ) + 1    )  ,      6    ):
				if number % i == 0 or number % (i + 2) == 0:
						return False
		return True

def      lowerCAmelCase__	(    _a       :			float = 0.1    ):
		snake_case_				:							int						 =       3
		snake_case_				:							Optional[Any]						 =       3

		while primes / (2 * j - 1) >= ratio:
				for i in range(j * j + j + 1  ,      (j + 2) * (j + 2)  ,      j + 1    ):
						primes += is_prime(_a    )
				j += 2
		return j


if __name__ == "__main__":
							import doctest

							doctest.testmod()
