


import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

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


lowerCAmelCase__			:      Optional[int]								=logging.get_logger(__name__)

lowerCAmelCase__			:      str								={"""vocab_file""": """spm_char.model"""}

lowerCAmelCase__			:      Dict								={
    """vocab_file""": {
        """microsoft/speecht5_asr""": """https://huggingface.co/microsoft/speecht5_asr/resolve/main/spm_char.model""",
        """microsoft/speecht5_tts""": """https://huggingface.co/microsoft/speecht5_tts/resolve/main/spm_char.model""",
        """microsoft/speecht5_vc""": """https://huggingface.co/microsoft/speecht5_vc/resolve/main/spm_char.model""",
    }
}

lowerCAmelCase__			:      Dict								={
    """microsoft/speecht5_asr""": 10_24,
    """microsoft/speecht5_tts""": 10_24,
    """microsoft/speecht5_vc""": 10_24,
}







class 	__lowercase    (__snake_case  ):





							"""simple docstring"""







							_UpperCAmelCase      =						VOCAB_FILES_NAMES
							_UpperCAmelCase      =						PRETRAINED_VOCAB_FILES_MAP
							_UpperCAmelCase      =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							_UpperCAmelCase      =						["""input_ids""", """attention_mask"""]






							def __init__(      self			,						lowerCAmelCase__			,						lowerCAmelCase__="<s>"			,						lowerCAmelCase__="</s>"			,						lowerCAmelCase__="<unk>"			,						lowerCAmelCase__="<pad>"			,						lowerCAmelCase__ = None			,						**lowerCAmelCase__			,						):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					{} if sp_model_kwargs is None else sp_model_kwargs

										super().__init__(
										    bos_token=lowerCAmelCase__			,						eos_token=lowerCAmelCase__			,						unk_token=lowerCAmelCase__			,						pad_token=lowerCAmelCase__			,						sp_model_kwargs=self.sp_model_kwargs			,						**lowerCAmelCase__			,						)

										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					vocab_file

										SCREAMING_SNAKE_CASE_		:     Any					=					spm.SentencePieceProcessor(**self.sp_model_kwargs       )
										self.sp_model.Load(lowerCAmelCase__       )






							@property
							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										return self.sp_model.get_piece_size()






							def 					UpperCamelCase__     (      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Dict					=					{self.convert_ids_to_tokens(lowerCAmelCase__       ): i for i in range(self.vocab_size       )}
										vocab.update(self.added_tokens_encoder       )
										return vocab






							def __getstate__(      self       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     int					=					self.__dict__.copy()
										SCREAMING_SNAKE_CASE_		:     Dict					=					None
										return state






							def __setstate__(      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Dict					=					d

										# for backward compatibility
										if not hasattr(self			,						'sp_model_kwargs'       ):
													SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					{}

										SCREAMING_SNAKE_CASE_		:     List[str]					=					spm.SentencePieceProcessor(**self.sp_model_kwargs       )
										self.sp_model.Load(self.vocab_file       )






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										return self.sp_model.encode(lowerCAmelCase__			,						out_type=lowerCAmelCase__       )






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										return self.sp_model.piece_to_id(lowerCAmelCase__       )






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Optional[Any]					=					self.sp_model.IdToPiece(lowerCAmelCase__       )
										return token






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__       ):





										"""simple docstring"""




										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					[]
										SCREAMING_SNAKE_CASE_		:     List[Any]					=					""
										for token in tokens:
													# make sure that special tokens are not decoded using sentencepiece model
													if token in self.all_special_tokens:
																out_string += self.sp_model.decode(lowerCAmelCase__       ) + token
																SCREAMING_SNAKE_CASE_		:     Any					=					[]
													else:
																current_sub_tokens.append(lowerCAmelCase__       )
										out_string += self.sp_model.decode(lowerCAmelCase__       )
										return out_string.strip()






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__			,						lowerCAmelCase__=None       ):





										"""simple docstring"""




										if token_ids_a is None:
													return token_ids_a + [self.eos_token_id]
										# We don't expect to process pairs, but leave the pair logic for API consistency
										return token_ids_a + token_ids_a + [self.eos_token_id]






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__			,						lowerCAmelCase__ = None			,						lowerCAmelCase__ = False       ):





										"""simple docstring"""




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

										SCREAMING_SNAKE_CASE_		:     Union[str, Any]					=					[1]
										if token_ids_a is None:
													return ([0] * len(lowerCAmelCase__       )) + suffix_ones
										return ([0] * len(lowerCAmelCase__       )) + ([0] * len(lowerCAmelCase__       )) + suffix_ones






							def 					UpperCamelCase__     (      self			,						lowerCAmelCase__			,						lowerCAmelCase__ = None       ):





										"""simple docstring"""




										if not os.path.isdir(lowerCAmelCase__       ):
													logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''       )
													return
										SCREAMING_SNAKE_CASE_		:     int					=					os.path.join(
										    lowerCAmelCase__			,						(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']       )

										if os.path.abspath(self.vocab_file       ) != os.path.abspath(lowerCAmelCase__       ) and os.path.isfile(self.vocab_file       ):
													copyfile(self.vocab_file			,						lowerCAmelCase__       )
										elif not os.path.isfile(self.vocab_file       ):
													with open(lowerCAmelCase__			,						'wb'       ) as fi:
																SCREAMING_SNAKE_CASE_		:     str					=					self.sp_model.serialized_model_proto()
																fi.write(lowerCAmelCase__       )

										return (out_vocab_file,)







def 		UpperCamelCase     (       _UpperCAmelCase  :   list[int] ,			_UpperCAmelCase  :   list[int]  )   ->			tuple[float, float]:






						'''simple docstring'''

						if not len(_UpperCAmelCase  ) == len(_UpperCAmelCase  ) == 3:
												raise ValueError("Please enter a valid equation."  )
						if equationa[0] == equationa[1] == equationa[0] == equationa[1] == 0:
												raise ValueError("Both a & b of two equations can't be zero."  )

						# Extract the coefficients
						_lowercase      ,    _lowercase      ,    _lowercase       :	List[str]           =   equationa
						_lowercase      ,    _lowercase      ,    _lowercase       :	List[str]           =   equationa

						# Calculate the determinants of the matrices
						_lowercase       :	List[Any]           =   aa * ba - aa * ba
						_lowercase       :	Tuple           =   ca * ba - ca * ba
						_lowercase       :	Union[str, Any]           =   aa * ca - aa * ca

						# Check if the system of linear equations has a solution (using Cramer's rule)
						if determinant == 0:
												if determinant_x == determinant_y == 0:
																		raise ValueError("Infinite solutions. (Consistent system)"  )
												else:
																		raise ValueError("No solution. (Inconsistent system)"  )
						else:
												if determinant_x == determinant_y == 0:
																		# Trivial solution (Inconsistent system)
																		return (0.0, 0.0)
												else:
																		_lowercase       :	str           =   determinant_x / determinant
																		_lowercase       :	Union[str, Any]           =   determinant_y / determinant
																		# Non-Trivial Solution (Consistent system)
																		return (x, y)




