



from argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser







def snake_case__	(      )		->				Optional[int]:
		UpperCAmelCase_						       =					ArgumentParser("Accelerate CLI tool"      ,  usage="accelerate <command> [<args>]"      ,  allow_abbrev=UpperCamelCase__			)
		UpperCAmelCase_						       =					parser.add_subparsers(help="accelerate command helpers"			)

		# Register commands
		get_config_parser(subparsers=UpperCamelCase__			)
		env_command_parser(subparsers=UpperCamelCase__			)
		launch_command_parser(subparsers=UpperCamelCase__			)
		tpu_command_parser(subparsers=UpperCamelCase__			)
		test_command_parser(subparsers=UpperCamelCase__			)

		# Let's go
		UpperCAmelCase_						       =					parser.parse_args()

		if not hasattr(UpperCamelCase__      ,  "func"			):
				parser.print_help()
				exit(1			)

		# Run
		args.func(UpperCamelCase__			)


if __name__ == "__main__":
			main()





'''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


UpperCAmelCase_			:  Any										=   logging.get_logger(__name__)

UpperCAmelCase_			:  Tuple										=   {'vocab_file': 'spm_char.model'}

UpperCAmelCase_			:  int										=   {
    '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',
    }
}

UpperCAmelCase_			:  List[Any]										=   {
    'microsoft/speecht5_asr': 1_0_2_4,
    'microsoft/speecht5_tts': 1_0_2_4,
    'microsoft/speecht5_vc': 1_0_2_4,
}

class     _lowerCamelCase       (     snake_case_					):




 '''simple docstring'''
 __lowercase					:		Optional[Any]     				=    VOCAB_FILES_NAMES
 __lowercase					:		int     				=    PRETRAINED_VOCAB_FILES_MAP
 __lowercase					:		int     				=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowercase					:		Optional[int]     				=    ['''input_ids''', '''attention_mask''']


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

  """simple docstring"""







  __A	:		Dict	  =      {} if sp_model_kwargs is None else sp_model_kwargs

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

  __A	:		Optional[Any]	  =      vocab_file

  __A	:		Any	  =      spm.SentencePieceProcessor(**self.sp_model_kwargs    )
  self.sp_model.Load(__lowercase    )


 @property
 def 			snake_case__ (   self    ):

  """simple docstring"""







  return self.sp_model.get_piece_size()


 def 			snake_case__ (   self    ):

  """simple docstring"""







  __A	:		Tuple	  =      {self.convert_ids_to_tokens(__lowercase    ): i for i in range(self.vocab_size    )}
  vocab.update(self.added_tokens_encoder    )
  return vocab


 def __getstate__(   self    ):

  """simple docstring"""







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


 def __setstate__(   self   ,   __lowercase    ):

  """simple docstring"""







  __A	:		List[str]	  =      d

  # for backward compatibility
  if not hasattr(self   ,   'sp_model_kwargs'    ):
   __A	:		Any	  =      {}

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


 def 			snake_case__ (   self   ,   __lowercase    ):

  """simple docstring"""







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


 def 			snake_case__ (   self   ,   __lowercase    ):

  """simple docstring"""







  return self.sp_model.piece_to_id(__lowercase    )


 def 			snake_case__ (   self   ,   __lowercase    ):

  """simple docstring"""







  __A	:		Optional[Any]	  =      self.sp_model.IdToPiece(__lowercase    )
  return token


 def 			snake_case__ (   self   ,   __lowercase    ):

  """simple docstring"""







  __A	:		str	  =      []
  __A	:		str	  =      ''
  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(__lowercase    ) + token
    __A	:		Any	  =      []
   else:
    current_sub_tokens.append(__lowercase    )
  out_string += self.sp_model.decode(__lowercase    )
  return out_string.strip()


 def 			snake_case__ (   self   ,   __lowercase   ,   __lowercase=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 			snake_case__ (   self   ,   __lowercase   ,   __lowercase = None   ,   __lowercase = False    ):

  """simple docstring"""







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

  __A	:		Dict	  =      [1]
  if token_ids_a is None:
   return ([0] * len(__lowercase    )) + suffix_ones
  return ([0] * len(__lowercase    )) + ([0] * len(__lowercase    )) + suffix_ones







 def 			snake_case__ (   self   ,   __lowercase   ,   __lowercase = None    ):

  """simple docstring"""







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

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

  return (out_vocab_file,)






