





from dataclasses import dataclass, field
from typing import Tuple

from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments


if is_torch_available():
      import torch

if is_torch_tpu_available(check_device=False):
      import torch_xla.core.xla_model as xm


lowercase_          =		logging.get_logger(__name__)
@dataclass
class     SCREAMING_SNAKE_CASE       (UpperCAmelCase				):
   _UpperCamelCase   :		Dict			 =	[
       'no_inference',
       'no_cuda',
       'no_tpu',
       'no_speed',
       'no_memory',
       'no_env_print',
       'no_multi_process',
   ]


   def __init__(   self      :    List[Any]      ,					**a      :    List[str]	)->       Tuple:





     """simple docstring"""







     for deprecated_arg in self.deprecated_args:
       if deprecated_arg in kwargs:
         lowercase__           =  deprecated_arg[3:]
         setattr(self      ,					a      ,					not kwargs.pop(a	)	)
         logger.warning(
             f"""{deprecated_arg} is depreciated. Please use --no_{positive_arg} or"""
             f""" {positive_arg}={kwargs[positive_arg]}"""	)

     lowercase__           =  kwargs.pop('torchscript'      ,					self.torchscript	)
     lowercase__           =  kwargs.pop('torch_xla_tpu_print_metrics'      ,					self.torch_xla_tpu_print_metrics	)
     lowercase__           =  kwargs.pop('fp16_opt_level'      ,					self.fpaa_opt_level	)
     super().__init__(**a	)

   _UpperCamelCase   :		bool			 =	field(default=UpperCAmelCase      ,     metadata={'help': 'Trace the models using torchscript'}				)
   _UpperCamelCase   :		bool			 =	field(default=UpperCAmelCase      ,     metadata={'help': 'Print Xla/PyTorch tpu metrics'}				)
   _UpperCamelCase   :		str			 =	field(
       default='O1'      ,     metadata={
           'help': (
               'For fp16: Apex AMP optimization level selected in [\'O0\', \'O1\', \'O2\', and \'O3\']. '
               'See details at https://nvidia.github.io/apex/amp.html'
           )
       }      ,     )


   @cached_property
   def 	SCREAMING_SNAKE_CASE_							(   self      :    Dict	)->       Tuple["torch.device", int]:





     """simple docstring"""







     requires_backends(self      ,					['torch']	)
     logger.info('PyTorch: setting up devices'	)
     if not self.cuda:
       lowercase__           =  torch.device('cpu'	)
       lowercase__           =  0
     elif is_torch_tpu_available():
       lowercase__           =  xm.xla_device()
       lowercase__           =  0
     else:
       lowercase__           =  torch.device('cuda' if torch.cuda.is_available() else 'cpu'	)
       lowercase__           =  torch.cuda.device_count()
     return device, n_gpu


   @property
   def 	SCREAMING_SNAKE_CASE_							(   self      :    Optional[int]	)->       int:





     """simple docstring"""







     return is_torch_tpu_available() and self.tpu


   @property
   def 	SCREAMING_SNAKE_CASE_							(   self      :    int	)->       int:





     """simple docstring"""







     requires_backends(self      ,					['torch']	)
     # TODO(PVP): currently only single GPU is supported
     return torch.cuda.current_device()


   @property
   def 	SCREAMING_SNAKE_CASE_							(   self      :    int	)->       "torch.device":





     """simple docstring"""







     requires_backends(self      ,					['torch']	)
     return self._setup_devices[0]


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





     """simple docstring"""







     requires_backends(self      ,					['torch']	)
     return self._setup_devices[1]


   @property
   def 	SCREAMING_SNAKE_CASE_							(   self      :    int	)->       List[str]:





     """simple docstring"""







     return self.n_gpu > 0









def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		)    ->       int:

  if exponent == 1:
    return base
  if exponent % 2 == 0:
    lowercase__           =  _modexpt(_SCREAMING_SNAKE_CASE		,						exponent // 2		,						_SCREAMING_SNAKE_CASE		) % modulo_value
    return (x * x) % modulo_value
  else:
    return (base * _modexpt(_SCREAMING_SNAKE_CASE		,						exponent - 1		,						_SCREAMING_SNAKE_CASE		)) % modulo_value




def       __UpperCamelCase  (_SCREAMING_SNAKE_CASE = 1777		,						_SCREAMING_SNAKE_CASE = 1855		,						_SCREAMING_SNAKE_CASE = 8		)    ->       int:
  lowercase__           =  base
  for _ in range(1		,						_SCREAMING_SNAKE_CASE		):
    lowercase__           =  _modexpt(_SCREAMING_SNAKE_CASE		,						_SCREAMING_SNAKE_CASE		,						10**digits		)

  return result


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


