





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   				=			logging.get_logger(__name__)

_lowerCamelCase   				=			{'vocab_file': 'spm_char.model'}

_lowerCamelCase   				=			{
    '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   				=			{
    'microsoft/speecht5_asr': 1024,
    'microsoft/speecht5_tts': 1024,
    'microsoft/speecht5_vc': 1024,
}




class   UpperCamelCase_       (     lowercase_    ):
							lowerCamelCase_           =					VOCAB_FILES_NAMES
							lowerCamelCase_           =					PRETRAINED_VOCAB_FILES_MAP
							lowerCamelCase_           =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowerCamelCase_           =					['''input_ids''', '''attention_mask''']


							def __init__(							self    :int							,				__A    :Optional[int]							,				__A    :Optional[Any]="<s>"							,				__A    :List[str]="</s>"							,				__A    :Any="<unk>"							,				__A    :Optional[int]="<pad>"							,				__A    :Optional[Dict[str, Any]] = None							,				**__A    :Optional[int]							,				)   ->   List[str]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__			=      {} if sp_model_kwargs is None else sp_model_kwargs

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

									SCREAMING_SNAKE_CASE__			=      vocab_file

									SCREAMING_SNAKE_CASE__			=      spm.SentencePieceProcessor(**self.sp_model_kwargs		)
									self.sp_model.Load(UpperCamelCase__		)


							@property
							def      _snake_case  (							self    :Tuple		)   ->   List[Any]:



									"""simple docstring"""



									return self.sp_model.get_piece_size()


							def      _snake_case  (							self    :Tuple		)   ->   Union[str, Any]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__			=      {self.convert_ids_to_tokens(UpperCamelCase__		): i for i in range(self.vocab_size		)}
									vocab.update(self.added_tokens_encoder		)
									return vocab


							def __getstate__(							self    :List[Any]		)   ->   str:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__			=      self.__dict__.copy()
									SCREAMING_SNAKE_CASE__			=      None
									return state


							def __setstate__(							self    :Union[str, Any]							,				__A    :Dict		)   ->   int:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__			=      d

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

									SCREAMING_SNAKE_CASE__			=      spm.SentencePieceProcessor(**self.sp_model_kwargs		)
									self.sp_model.Load(self.vocab_file		)


							def      _snake_case  (							self    :str							,				__A    :str		)   ->   List[str]:



									"""simple docstring"""



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


							def      _snake_case  (							self    :str							,				__A    :Optional[Any]		)   ->   Union[str, Any]:



									"""simple docstring"""



									return self.sp_model.piece_to_id(UpperCamelCase__		)


							def      _snake_case  (							self    :int							,				__A    :List[str]		)   ->   Union[str, Any]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__			=      self.sp_model.IdToPiece(UpperCamelCase__		)
									return token


							def      _snake_case  (							self    :List[Any]							,				__A    :Optional[int]		)   ->   List[str]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__			=      []
									SCREAMING_SNAKE_CASE__			=      """"""
									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(UpperCamelCase__		) + token
													SCREAMING_SNAKE_CASE__			=      []
											else:
													current_sub_tokens.append(UpperCamelCase__		)
									out_string += self.sp_model.decode(UpperCamelCase__		)
									return out_string.strip()


							def      _snake_case  (							self    :Any							,				__A    :Tuple							,				__A    :Union[str, Any]=None		)   ->   Optional[Any]:



									"""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      _snake_case  (							self    :List[str]							,				__A    :List[int]							,				__A    :Optional[List[int]] = None							,				__A    :bool = False		)   ->   str:



									"""simple docstring"""



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

									SCREAMING_SNAKE_CASE__			=      [1]
									if token_ids_a is None:
											return ([0] * len(UpperCamelCase__		)) + suffix_ones
									return ([0] * len(UpperCamelCase__		)) + ([0] * len(UpperCamelCase__		)) + suffix_ones


							def      _snake_case  (							self    :Any							,				__A    :str							,				__A    :Optional[str] = None		)   ->   Any:



									"""simple docstring"""



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

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

									return (out_vocab_file,)






import warnings
from functools import wraps
from typing import Callable






def 				SCREAMING_SNAKE_CASE__							(       UpperCamelCase__:							Callable    ):

		@wraps(UpperCamelCase__    )
		def _inner_fn(*UpperCamelCase__:							Dict					,   **UpperCamelCase__:							Any    ):
				warnings.warn(
				    (f'''\'{fn.__name__}\' is experimental and might be subject to breaking changes in the future.''')					,   UpperCamelCase__					,   )
				return fn(*UpperCamelCase__					,   **UpperCamelCase__    )

		return _inner_fn