



'''simple docstring'''






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


UpperCamelCase__:   Optional[Any]								=			logging.get_logger(__name__)

UpperCamelCase__:   Any								=			"▁"

UpperCamelCase__:   List[str]								=			{
    "vocab_file": "vocab.json",
    "spm_file": "sentencepiece.bpe.model",
}

UpperCamelCase__:   Any								=			{
    "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"
        )
    },
}

UpperCamelCase__:   Optional[int]								=			{
    "facebook/s2t-small-librispeech-asr": 1024,
}

UpperCamelCase__:   Union[str, Any]								=			["pt", "fr", "ru", "nl", "ro", "it", "es", "de"]

UpperCamelCase__:   Optional[int]								=			{"mustc": MUSTC_LANGS}

class 				SCREAMING_SNAKE_CASE(							A__			):







	"""simple docstring"""






	lowerCamelCase__			 =       VOCAB_FILES_NAMES
	lowerCamelCase__			 =       PRETRAINED_VOCAB_FILES_MAP
	lowerCamelCase__			 =       MAX_MODEL_INPUT_SIZES
	lowerCamelCase__			 =       ["""input_ids""", """attention_mask"""]

	lowerCamelCase__			 =       []







	def __init__(						self			:     List[Any]		,			__snake_case			:     str		,			__snake_case			:     Any		,			__snake_case			:     List[str]="<s>"		,			__snake_case			:     str="</s>"		,			__snake_case			:     str="<pad>"		,			__snake_case			:     Any="<unk>"		,			__snake_case			:     str=False		,			__snake_case			:     List[Any]=False		,			__snake_case			:     List[Any]=None		,			__snake_case			:     Optional[Any]=None		,			__snake_case			:     Optional[Dict[str, Any]] = None		,			**__snake_case			:     Optional[Any]		,			)			->		None:
								UpperCAmelCase :       Tuple 							=		{} if sp_model_kwargs is None else sp_model_kwargs

								super().__init__(
								    bos_token=__snake_case		,			eos_token=__snake_case		,			unk_token=__snake_case		,			pad_token=__snake_case		,			do_upper_case=__snake_case		,			do_lower_case=__snake_case		,			tgt_lang=__snake_case		,			lang_codes=__snake_case		,			sp_model_kwargs=self.sp_model_kwargs		,			**__snake_case		,			)
								UpperCAmelCase :       Union[str, Any] 							=		do_upper_case
								UpperCAmelCase :       int 							=		do_lower_case

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

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

															UpperCAmelCase :       Optional[int] 							=		self.lang_tokens
															UpperCAmelCase :       List[str] 							=		tgt_lang if tgt_lang is not None else self.langs[0]

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







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







	@property
	def      A	(						self			:     Optional[Any]		)			->		str:
								return self._tgt_lang







	@tgt_lang.setter
	def      A	(						self			:     List[str]		,			__snake_case			:     int		)			->		None:
								UpperCAmelCase :       List[Any] 							=		new_tgt_lang
								self.set_tgt_lang_special_tokens(__snake_case		)







	def      A	(						self			:     int		,			__snake_case			:     str		)			->		None:
								UpperCAmelCase :       Optional[Any] 							=		self.lang_code_to_id[tgt_lang]
								UpperCAmelCase :       Any 							=		[lang_code_id]







	def      A	(						self			:     Tuple		,			__snake_case			:     str		)			->		List[str]:
								return self.sp_model.encode(__snake_case		,			out_type=__snake_case		)







	def      A	(						self			:     str		,			__snake_case			:     Union[str, Any]		)			->		Union[str, Any]:
								return self.encoder.get(__snake_case		,			self.encoder[self.unk_token]		)







	def      A	(						self			:     str		,			__snake_case			:     int		)			->		str:
								return self.decoder.get(__snake_case		,			self.unk_token		)







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







	def      A	(						self			:     Any		,			__snake_case			:     List[str]		,			__snake_case			:     Optional[int]=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      A	(						self			:     int		,			__snake_case			:     List[int]		,			__snake_case			:     Optional[List[int]] = None		,			__snake_case			:     bool = False		)			->		List[int]:

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

								UpperCAmelCase :       Tuple 							=		[1] * len(self.prefix_tokens		)
								UpperCAmelCase :       Optional[int] 							=		[1]
								if token_ids_a is None:
															return prefix_ones + ([0] * len(__snake_case		)) + suffix_ones
								return prefix_ones + ([0] * len(__snake_case		)) + ([0] * len(__snake_case		)) + suffix_ones







	def      A	(						self			:     Union[str, Any]		)			->		Dict:
								UpperCAmelCase :       List[Any] 							=		self.encoder.copy()
								vocab.update(self.added_tokens_encoder		)
								return vocab







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







	def __setstate__(						self			:     str		,			__snake_case			:     Dict		)			->		None:
								UpperCAmelCase :       Tuple 							=		d

								# for backward compatibility
								if not hasattr(self		,			'''sp_model_kwargs'''		):
															UpperCAmelCase :       List[str] 							=		{}

								UpperCAmelCase :       Optional[Any] 							=		load_spm(self.spm_file		,			self.sp_model_kwargs		)







	def      A	(						self			:     List[Any]		,			__snake_case			:     str		,			__snake_case			:     Optional[str] = None		)			->		Tuple[str]:
								UpperCAmelCase :       List[Any] 							=		Path(__snake_case		)
								assert save_dir.is_dir(), F"""{save_directory} should be a directory"""
								UpperCAmelCase :       Dict 							=		save_dir / (
								    (filename_prefix + '''-''' if filename_prefix else '''''') + self.vocab_files_names['''vocab_file''']
								)
								UpperCAmelCase :       Union[str, Any] 							=		save_dir / (
								    (filename_prefix + '''-''' if filename_prefix else '''''') + self.vocab_files_names['''spm_file''']
								)

								save_json(self.encoder		,			__snake_case		)

								if os.path.abspath(self.spm_file		) != os.path.abspath(__snake_case		) and os.path.isfile(self.spm_file		):
															copyfile(self.spm_file		,			__snake_case		)
								elif not os.path.isfile(self.spm_file		):
															with open(__snake_case		,			'''wb'''		) as fi:
																						UpperCAmelCase :       Optional[int] 							=		self.sp_model.serialized_model_proto()
																						fi.write(__snake_case		)

								return (str(__snake_case		), str(__snake_case		))


def  snake_case_     (					_lowerCAmelCase  :						str   ,      _lowerCAmelCase  :						Dict[str, Any]  )      ->   sentencepiece.SentencePieceProcessor:
							UpperCAmelCase :       int 							=		sentencepiece.SentencePieceProcessor(**_lowerCAmelCase  )
							spm.Load(str(_lowerCAmelCase  )  )
							return spm


def  snake_case_     (					_lowerCAmelCase  :						str  )      ->   Union[Dict, List]:
							with open(_lowerCAmelCase   ,      '''r'''  ) as f:
														return json.load(_lowerCAmelCase  )




def  snake_case_     (					_lowerCAmelCase  :						List[Any]   ,      _lowerCAmelCase  :						str  )      ->   None:
							with open(_lowerCAmelCase   ,      '''w'''  ) as f:
														json.dump(_lowerCAmelCase   ,      _lowerCAmelCase   ,      indent=2  )








from .imports import is_tqdm_available


if is_tqdm_available():
  from tqdm.auto import tqdm as _tqdm

from ..state import PartialState
def      a      (			A__	:   bool = True      ,   *A__	:   int      ,   **A__	:   Union[str, Any]     )    ->      List[str]:





      """simple docstring"""



      if not is_tqdm_available():
            raise ImportError('Accelerate\'s `tqdm` module requires `tqdm` to be installed. Please run `pip install tqdm`.'     )
      _lowercase	       =False
      if main_process_only:
            _lowercase	       =PartialState().local_process_index == 0
      return _tqdm(*A__      ,   **A__      ,   disable=A__     )


