
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						      =				logging.get_logger(__name__)

_A						      =				{"vocab_file": "spm_char.model"}

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







class   lowerCamelCase	(						A_						):
     UpperCAmelCase__       :							Dict     =	VOCAB_FILES_NAMES
     UpperCAmelCase__       :							Optional[int]     =	PRETRAINED_VOCAB_FILES_MAP
     UpperCAmelCase__       :							Optional[int]     =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCAmelCase__       :							Union[str, Any]     =	["input_ids", "attention_mask"]





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

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

         snake_case				  =      vocab_file

         snake_case				  =      spm.SentencePieceProcessor(**self.sp_model_kwargs     )
         self.sp_model.Load(_A     )





     @property
     def 	UpperCAmelCase(self   :					int     )		->		List[str]:
         return self.sp_model.get_piece_size()





     def 	UpperCAmelCase(self   :					List[Any]     )		->		Tuple:
         snake_case				  =      {self.convert_ids_to_tokens(_A     ): i for i in range(self.vocab_size     )}
         vocab.update(self.added_tokens_encoder     )
         return vocab





     def __getstate__(self   :					List[str]     )		->		Any:
         snake_case				  =      self.__dict__.copy()
         snake_case				  =      None
         return state





     def __setstate__(self   :					str       ,					_A   :					int     )		->		Optional[int]:
         snake_case				  =      d

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

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





     def 	UpperCAmelCase(self   :					Union[str, Any]       ,					_A   :					str     )		->		List[str]:
         return self.sp_model.encode(_A       ,					out_type=_A     )





     def 	UpperCAmelCase(self   :					Tuple       ,					_A   :					Any     )		->		Optional[Any]:
         return self.sp_model.piece_to_id(_A     )





     def 	UpperCAmelCase(self   :					Optional[Any]       ,					_A   :					Optional[Any]     )		->		Optional[int]:
         snake_case				  =      self.sp_model.IdToPiece(_A     )
         return token





     def 	UpperCAmelCase(self   :					List[Any]       ,					_A   :					List[Any]     )		->		Union[str, Any]:
         snake_case				  =      []
         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(_A     ) + token
                 snake_case				  =      []
             else:
                 current_sub_tokens.append(_A     )
         out_string += self.sp_model.decode(_A     )
         return out_string.strip()





     def 	UpperCAmelCase(self   :					Union[str, Any]       ,					_A   :					List[str]       ,					_A   :					List[Any]=None     )		->		List[int]:
         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   :					str       ,					_A   :					List[int]       ,					_A   :					Optional[List[int]] = None       ,					_A   :					bool = False     )		->		List[int]:
         if already_has_special_tokens:
             return super().get_special_tokens_mask(
                 token_ids_a=_A       ,					token_ids_a=_A       ,					already_has_special_tokens=_A     )

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





     def 	UpperCAmelCase(self   :					Union[str, Any]       ,					_A   :					str       ,					_A   :					Optional[str] = None     )		->		Tuple[str]:
         if not os.path.isdir(_A     ):
             logger.error(f'Vocabulary path ({save_directory}) should be a directory'     )
             return
         snake_case				  =      os.path.join(
             _A       ,					(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]     )

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

         return (out_vocab_file,)



def 		lowercase_    (     A__ = 1000	)							->							int:
    """simple docstring"""

    snake_case				  =      -1
    snake_case				  =      0
    for a in range(1				,	n // 3	):
        # Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
        snake_case				  =      (n * n - 2 * a * n) // (2 * n - 2 * a)
        snake_case				  =      n - a - b
        if c * c == (a * a + b * b):
            snake_case				  =      a * b * c
            if candidate >= product:
                snake_case				  =      candidate
    return product


if __name__ == "__main__":
   print(f"{solution() = }")

