
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


A		: int								=     logging.get_logger(__name__)

A		: Union[str, Any]								=     '''▁'''

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

A		: 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'''
        )
    },
}

A		: int								=     {
    '''facebook/s2t-small-librispeech-asr''': 1_024,
}

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

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



class    a_ (			_a    ):
			a	:			str					   =							VOCAB_FILES_NAMES
			a	:			Tuple					   =							PRETRAINED_VOCAB_FILES_MAP
			a	:			Tuple					   =							MAX_MODEL_INPUT_SIZES
			a	:			Dict					   =							['''input_ids''', '''attention_mask''']

			a	:			List[int]					   =							[]






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

									super().__init__(
									    bos_token=__UpperCamelCase				,			eos_token=__UpperCamelCase				,			unk_token=__UpperCamelCase				,			pad_token=__UpperCamelCase				,			do_upper_case=__UpperCamelCase				,			do_lower_case=__UpperCamelCase				,			tgt_lang=__UpperCamelCase				,			lang_codes=__UpperCamelCase				,			sp_model_kwargs=self.sp_model_kwargs				,			**__UpperCamelCase				,			)
									_lowercase					       =					do_upper_case
									_lowercase					       =					do_lower_case

									_lowercase					       =					load_json(__UpperCamelCase  )
									_lowercase					       =					{v: k for k, v in self.encoder.items()}
									_lowercase					       =					spm_file
									_lowercase					       =					load_spm(__UpperCamelCase				,			self.sp_model_kwargs  )

									if lang_codes is not None:
															_lowercase					       =					lang_codes
															_lowercase					       =					LANGUAGES[lang_codes]
															_lowercase					       =					[f"""<lang:{lang}>""" for lang in self.langs]
															_lowercase					       =					{lang: self.sp_model.PieceToId(f"""<lang:{lang}>"""  ) for lang in self.langs}

															_lowercase					       =					self.lang_tokens
															_lowercase					       =					tgt_lang if tgt_lang is not None else self.langs[0]

															self.set_tgt_lang_special_tokens(self._tgt_lang  )
									else:
															_lowercase					       =					{}






			@property
			def    UpperCamelCase_				(      self  ):
									return len(self.encoder  )






			@property
			def    UpperCamelCase_				(      self  ):
									return self._tgt_lang






			@tgt_lang.setter
			def    UpperCamelCase_				(      self				,			__UpperCamelCase  ):
									_lowercase					       =					new_tgt_lang
									self.set_tgt_lang_special_tokens(__UpperCamelCase  )






			def    UpperCamelCase_				(      self				,			__UpperCamelCase  ):
									_lowercase					       =					self.lang_code_to_id[tgt_lang]
									_lowercase					       =					[lang_code_id]






			def    UpperCamelCase_				(      self				,			__UpperCamelCase  ):
									return self.sp_model.encode(__UpperCamelCase				,			out_type=__UpperCamelCase  )






			def    UpperCamelCase_				(      self				,			__UpperCamelCase  ):
									return self.encoder.get(__UpperCamelCase				,			self.encoder[self.unk_token]  )






			def    UpperCamelCase_				(      self				,			__UpperCamelCase  ):
									return self.decoder.get(__UpperCamelCase				,			self.unk_token  )






			def    UpperCamelCase_				(      self				,			__UpperCamelCase  ):
									_lowercase					       =					[]
									_lowercase					       =					""""""
									for token in tokens:
															# make sure that special tokens are not decoded using sentencepiece model
															if token in self.all_special_tokens:
																					_lowercase					       =					self.sp_model.decode(__UpperCamelCase  )
																					out_string += (decoded.upper() if self.do_upper_case else decoded) + token + " "
																					_lowercase					       =					[]
															else:
																					current_sub_tokens.append(__UpperCamelCase  )
									_lowercase					       =					self.sp_model.decode(__UpperCamelCase  )
									out_string += decoded.upper() if self.do_upper_case else decoded
									return out_string.strip()






			def    UpperCamelCase_				(      self				,			__UpperCamelCase				,			__UpperCamelCase=None  ):
									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    UpperCamelCase_				(      self				,			__UpperCamelCase				,			__UpperCamelCase = None				,			__UpperCamelCase = False  ):

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

									_lowercase					       =					[1] * len(self.prefix_tokens  )
									_lowercase					       =					[1]
									if token_ids_a is None:
															return prefix_ones + ([0] * len(__UpperCamelCase  )) + suffix_ones
									return prefix_ones + ([0] * len(__UpperCamelCase  )) + ([0] * len(__UpperCamelCase  )) + suffix_ones






			def    UpperCamelCase_				(      self  ):
									_lowercase					       =					self.encoder.copy()
									vocab.update(self.added_tokens_encoder  )
									return vocab






			def __getstate__(      self  ):
									_lowercase					       =					self.__dict__.copy()
									_lowercase					       =					None
									return state






			def __setstate__(      self				,			__UpperCamelCase  ):
									_lowercase					       =					d

									# for backward compatibility
									if not hasattr(self				,			"""sp_model_kwargs"""  ):
															_lowercase					       =					{}

									_lowercase					       =					load_spm(self.spm_file				,			self.sp_model_kwargs  )






			def    UpperCamelCase_				(      self				,			__UpperCamelCase				,			__UpperCamelCase = None  ):
									_lowercase					       =					Path(__UpperCamelCase  )
									assert save_dir.is_dir(), f"""{save_directory} should be a directory"""
									_lowercase					       =					save_dir / (
									    (filename_prefix + """-""" if filename_prefix else """""") + self.vocab_files_names["""vocab_file"""]
									)
									_lowercase					       =					save_dir / (
									    (filename_prefix + """-""" if filename_prefix else """""") + self.vocab_files_names["""spm_file"""]
									)

									save_json(self.encoder				,			__UpperCamelCase  )

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

									return (str(__UpperCamelCase  ), str(__UpperCamelCase  ))







def 	UpperCamelCase__  (     SCREAMING_SNAKE_CASE_	:	str		,   SCREAMING_SNAKE_CASE_	:	Dict[str, Any]       )  ->     sentencepiece.SentencePieceProcessor:
						_lowercase					       =					sentencepiece.SentencePieceProcessor(**SCREAMING_SNAKE_CASE_       )
						spm.Load(str(SCREAMING_SNAKE_CASE_       )       )
						return spm




def 	UpperCamelCase__  (     SCREAMING_SNAKE_CASE_	:	str       )  ->     Union[Dict, List]:
						with open(SCREAMING_SNAKE_CASE_		,   """r"""       ) as f:
												return json.load(SCREAMING_SNAKE_CASE_       )




def 	UpperCamelCase__  (     SCREAMING_SNAKE_CASE_	:	List[str]		,   SCREAMING_SNAKE_CASE_	:	str       )  ->     None:
						with open(SCREAMING_SNAKE_CASE_		,   """w"""       ) as f:
												json.dump(SCREAMING_SNAKE_CASE_		,   SCREAMING_SNAKE_CASE_		,   indent=2       )

def 	UpperCamelCase__  (     SCREAMING_SNAKE_CASE_	:	int       )  ->     list:

						# bit count represents no. of bits in the gray code
						if bit_count < 0:
												raise ValueError("""The given input must be positive"""       )

						# get the generated string sequence
						_lowercase					       =					gray_code_sequence_string(SCREAMING_SNAKE_CASE_       )
						#
						# convert them to integers
						for i in range(len(SCREAMING_SNAKE_CASE_       )       ):
												_lowercase					       =					int(sequence[i]		,   2       )

						return sequence




def 	UpperCamelCase__  (     SCREAMING_SNAKE_CASE_	:	int       )  ->     list:

						# The approach is a recursive one
						# Base case achieved when either n = 0 or n=1
						if bit_count == 0:
												return ["0"]

						if bit_count == 1:
												return ["0", "1"]

						_lowercase					       =					1 << bit_count  # defines the length of the sequence
						# 1<< n is equivalent to 2^n

						# recursive answer will generate answer for n-1 bits
						_lowercase					       =					gray_code_sequence_string(bit_count - 1       )

						_lowercase					       =					[]

						# append 0 to first half of the smaller sequence generated
						for i in range(seq_len // 2       ):
												_lowercase					       =					"""0""" + smaller_sequence[i]
												sequence.append(SCREAMING_SNAKE_CASE_       )

						# append 1 to second half ... start from the end of the list
						for i in reversed(range(seq_len // 2       )       ):
												_lowercase					       =					"""1""" + smaller_sequence[i]
												sequence.append(SCREAMING_SNAKE_CASE_       )

						return sequence


if __name__ == "__main__":
		import doctest

		doctest.testmod()