

"""simple docstring"""


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


a       :int     =			logging.get_logger(__name__)

a       :Union[str, Any]     =			{"vocab_file": "spm_char.model"}

a       :Tuple     =			{
    "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",
    }
}

a       :str     =			{
    "microsoft/speecht5_asr": 1_024,
    "microsoft/speecht5_tts": 1_024,
    "microsoft/speecht5_vc": 1_024,
}

class   __a				(UpperCamelCase_):






     '''simple docstring'''
     _SCREAMING_SNAKE_CASE    :Dict							=			VOCAB_FILES_NAMES
     _SCREAMING_SNAKE_CASE    :Dict							=			PRETRAINED_VOCAB_FILES_MAP
     _SCREAMING_SNAKE_CASE    :int							=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _SCREAMING_SNAKE_CASE    :str							=			['input_ids', 'attention_mask']

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


           """simple docstring"""


           SCREAMING_SNAKE_CASE__ :   List[Any]   		=						{} 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_						,     sp_model_kwargs=self.sp_model_kwargs						,     **SCREAMING_SNAKE_CASE_						,     )

           SCREAMING_SNAKE_CASE__ :   str   		=						vocab_file

           SCREAMING_SNAKE_CASE__ :   Union[str, Any]   		=						spm.SentencePieceProcessor(**self.sp_model_kwargs	)
           self.sp_model.Load(SCREAMING_SNAKE_CASE_	)

     @property
     def        _a      (    self	)	->   Dict:


           """simple docstring"""


           return self.sp_model.get_piece_size()

     def        _a      (    self	)	->   List[Any]:


           """simple docstring"""


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

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


           """simple docstring"""


           SCREAMING_SNAKE_CASE__ :   Any   		=						self.__dict__.copy()
           SCREAMING_SNAKE_CASE__ :   List[str]   		=						None
           return state

     def __setstate__(    self						,     _a	)	->   Union[str, Any]:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__ :   Optional[int]   		=						d

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

           SCREAMING_SNAKE_CASE__ :   Union[str, Any]   		=						spm.SentencePieceProcessor(**self.sp_model_kwargs	)
           self.sp_model.Load(self.vocab_file	)

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


           """simple docstring"""


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

     def        _a      (    self						,     _a	)	->   Optional[int]:


           """simple docstring"""


           return self.sp_model.piece_to_id(SCREAMING_SNAKE_CASE_	)

     def        _a      (    self						,     _a	)	->   Optional[int]:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__ :   List[Any]   		=						self.sp_model.IdToPiece(SCREAMING_SNAKE_CASE_	)
           return token

     def        _a      (    self						,     _a	)	->   str:


           """simple docstring"""


           SCREAMING_SNAKE_CASE__ :   List[Any]   		=						[]
           SCREAMING_SNAKE_CASE__ :   Optional[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(SCREAMING_SNAKE_CASE_	) + token
                       SCREAMING_SNAKE_CASE__ :   Any   		=						[]
                 else:
                       current_sub_tokens.append(SCREAMING_SNAKE_CASE_	)
           out_string += self.sp_model.decode(SCREAMING_SNAKE_CASE_	)
           return out_string.strip()

     def        _a      (    self						,     _a						,     _a=None	)	->   List[int]:


           """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        _a      (    self						,     _a						,     _a = None						,     _a = False	)	->   List[int]:


           """simple docstring"""


           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_	)

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





     def        _a      (    self						,     _a						,     _a = None	)	->   Tuple[str]:


           """simple docstring"""


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

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

           return (out_vocab_file,)






from __future__ import annotations




def 							a		(				snake_case__:   list[list[int]]   ):


				'''simple docstring'''

				# preprocessing the first row
				for i in range(1		,  len(matrix[0]   )   ):
								matrix[0][i] += matrix[0][i - 1]

				# preprocessing the first column
				for i in range(1		,  len(snake_case__   )   ):
								matrix[i][0] += matrix[i - 1][0]

				# updating the path cost for current position
				for i in range(1		,  len(snake_case__   )   ):
								for j in range(1		,  len(matrix[0]   )   ):
												matrix[i][j] += min(matrix[i - 1][j]		,  matrix[i][j - 1]   )

				return matrix[-1][-1]


if __name__ == "__main__":
						import doctest

						doctest.testmod()




