


'''simple docstring'''
import warnings
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


UpperCAmelCase_			:  str										=   logging.get_logger(__name__)

class     _lowerCamelCase       (     snake_case_					):




 '''simple docstring'''
 __lowercase					:		Dict     				=    ['''input_ids''', '''attention_mask''']


 def __init__(   self   ,   __lowercase="</s>"   ,   __lowercase="<unk>"   ,   __lowercase="<pad>"   ,   __lowercase=125   ,   __lowercase=None   ,   **__lowercase   ,   ):

  """simple docstring"""







  if extra_ids > 0 and additional_special_tokens is None:
   __A	:		List[Any]	  =      [F"""<extra_id_{i}>""" for i in range(__lowercase    )]
  elif extra_ids > 0 and additional_special_tokens is not None:
   # Check that we have the right number of extra_id special tokens
   __A	:		Optional[int]	  =      len(set(filter(lambda __lowercase    : bool('extra_id' in str(__lowercase    )    )   ,   __lowercase    )    )    )
   if extra_tokens != extra_ids:
    raise ValueError(
        F"""Both extra_ids ({extra_ids}) and additional_special_tokens ({additional_special_tokens}) are"""
        ' provided to ByT5Tokenizer. In this case the additional_special_tokens must include the'
        ' extra_ids tokens'    )

  __A	:		Tuple	  =      AddedToken(__lowercase   ,   lstrip=__lowercase   ,   rstrip=__lowercase    ) if isinstance(__lowercase   ,   __lowercase    ) else pad_token
  __A	:		Tuple	  =      AddedToken(__lowercase   ,   lstrip=__lowercase   ,   rstrip=__lowercase    ) if isinstance(__lowercase   ,   __lowercase    ) else eos_token
  __A	:		Any	  =      AddedToken(__lowercase   ,   lstrip=__lowercase   ,   rstrip=__lowercase    ) if isinstance(__lowercase   ,   __lowercase    ) else unk_token

  super().__init__(
      eos_token=__lowercase   ,   unk_token=__lowercase   ,   pad_token=__lowercase   ,   extra_ids=__lowercase   ,   additional_special_tokens=__lowercase   ,   **__lowercase   ,   )

  __A	:		Dict	  =      extra_ids

  __A	:		str	  =      2**8  # utf is 8 bits

  # define special tokens dict
  __A	:		Dict[int, str]	  =      {
      self.pad_token: 0,
      self.eos_token: 1,
      self.unk_token: 2,
  }
  __A	:		Tuple	  =      len(self.special_tokens_encoder    )
  __A	:		Optional[Any]	  =      len(__lowercase    )
  for i, token in enumerate(__lowercase    ):
   __A	:		Union[str, Any]	  =      self.vocab_size + i - n
  __A	:		Dict[str, int]	  =      {v: k for k, v in self.special_tokens_encoder.items()}


 @property
 def 			snake_case__ (   self    ):

  """simple docstring"""







  return self._utf_vocab_size + self._num_special_tokens + self._extra_ids


 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    )

  # normal case: some special tokens
  if token_ids_a is None:
   return ([0] * len(__lowercase    )) + [1]
  return ([0] * len(__lowercase    )) + [1] + ([0] * len(__lowercase    )) + [1]


 def 			snake_case__ (   self   ,   __lowercase    ):

  """simple docstring"""







  if len(__lowercase    ) > 0 and token_ids[-1] == self.eos_token_id:
   warnings.warn(
       F"""This sequence already has {self.eos_token}. In future versions this behavior may lead to duplicated"""
       ' eos tokens being added.'    )
   return token_ids
  else:
   return token_ids + [self.eos_token_id]


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

  """simple docstring"""







  __A	:		Any	  =      [self.eos_token_id]

  if token_ids_a is None:
   return len(token_ids_a + eos    ) * [0]
  return len(token_ids_a + eos + token_ids_a + eos    ) * [0]


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

  """simple docstring"""







  __A	:		Union[str, Any]	  =      self._add_eos_if_not_present(__lowercase    )
  if token_ids_a is None:
   return token_ids_a
  else:
   __A	:		Union[str, Any]	  =      self._add_eos_if_not_present(__lowercase    )
   return token_ids_a + token_ids_a


 def 			snake_case__ (   self   ,   __lowercase    ):

  """simple docstring"""







  __A	:		Tuple	  =      [chr(__lowercase    ) for i in text.encode('utf-8'    )]
  return tokens


 def 			snake_case__ (   self   ,   __lowercase    ):

  """simple docstring"""







  if token in self.special_tokens_encoder:
   __A	:		str	  =      self.special_tokens_encoder[token]
  elif token in self.added_tokens_encoder:
   __A	:		int	  =      self.added_tokens_encoder[token]
  elif len(__lowercase    ) != 1:
   __A	:		str	  =      self.unk_token_id
  else:
   __A	:		Dict	  =      ord(__lowercase    ) + self._num_special_tokens
  return token_id


 def 			snake_case__ (   self   ,   __lowercase    ):

  """simple docstring"""







  if index in self.special_tokens_decoder:
   __A	:		Optional[Any]	  =      self.special_tokens_decoder[index]
  else:
   __A	:		Dict	  =      chr(index - self._num_special_tokens    )
  return token


 def 			snake_case__ (   self   ,   __lowercase    ):

  """simple docstring"""







  __A	:		Optional[int]	  =      b''
  for token in tokens:
   if token in self.special_tokens_decoder:
    __A	:		Optional[int]	  =      self.special_tokens_decoder[token].encode('utf-8'    )
   elif token in self.added_tokens_decoder:
    __A	:		Tuple	  =      self.special_tokens_decoder[token].encode('utf-8'    )
   elif token in self.special_tokens_encoder:
    __A	:		int	  =      token.encode('utf-8'    )
   elif token in self.added_tokens_encoder:
    __A	:		str	  =      token.encode('utf-8'    )
   else:
    __A	:		Optional[Any]	  =      bytes([ord(__lowercase    )]    )
   bstring += tok_string
  __A	:		List[str]	  =      bstring.decode('utf-8'   ,   errors='ignore'    )
  return string







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

  """simple docstring"""







  return ()










'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path

import torch_xla.distributed.xla_multiprocessing as xmp


def       _lowercase							(					):
 __A	:		List[Any]	  =      ArgumentParser(
     description=(
         'PyTorch TPU distributed training launch helper utility that will spawn up multiple distributed processes'
     )      )

 # Optional arguments for the launch helper
 parser.add_argument('--num_cores',					type=UpperCamelCase__,					default=1,					help='Number of TPU cores to use (1 or 8).'      )

 # positional
 parser.add_argument(
     'training_script',					type=UpperCamelCase__,					help=(
         'The full path to the single TPU training '
         'program/script to be launched in parallel, '
         'followed by all the arguments for the '
         'training script'
     ),					)

 # rest from the training program
 parser.add_argument('training_script_args',					nargs=UpperCamelCase__      )

 return parser.parse_args()


def       _lowercase							(					):
 __A	:		str	  =      parse_args()

 # Import training_script as a module.
 __A	:		Tuple	  =      Path(args.training_script      )
 sys.path.append(str(script_fpath.parent.resolve()      )      )
 __A	:		str	  =      script_fpath.stem
 __A	:		Dict	  =      importlib.import_module(UpperCamelCase__      )

 # Patch sys.argv
 __A	:		Optional[Any]	  =      [args.training_script] + args.training_script_args + ['--tpu_num_cores', str(args.num_cores      )]

 xmp.spawn(mod._mp_fn,					args=(),					nprocs=args.num_cores      )


if __name__ == "__main__":
 main()






