

'''simple docstring'''



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


UpperCAmelCase :       str			   =     logging.get_logger(__name__)







@dataclass
class 						lowerCAmelCase__   (      __UpperCAmelCase					):



 """simple docstring"""



 lowerCAmelCase__  					=      [
     "no_inference",
     "no_cuda",
     "no_tpu",
     "no_speed",
     "no_memory",
     "no_env_print",
     "no_multi_process",
 ]
 def __init__(		self					:       Union[str, Any]					,							**__SCREAMING_SNAKE_CASE					:       Optional[Any]			)  -> Optional[int]:


      """simple docstring"""




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

      __SCREAMING_SNAKE_CASE     =      kwargs.pop("""torchscript"""					,							self.torchscript			)
      __SCREAMING_SNAKE_CASE     =      kwargs.pop("""torch_xla_tpu_print_metrics"""					,							self.torch_xla_tpu_print_metrics			)
      __SCREAMING_SNAKE_CASE     =      kwargs.pop("""fp16_opt_level"""					,							self.fpaa_opt_level			)
      super().__init__(**lowerCamelCase__			)

 lowerCAmelCase__  					=      field(default=__UpperCAmelCase ,					metadata={"help": "Trace the models using torchscript"}					)
 lowerCAmelCase__  					=      field(default=__UpperCAmelCase ,					metadata={"help": "Print Xla/PyTorch tpu metrics"}					)
 lowerCAmelCase__  					=      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       UpperCAmelCase__		(		self					:       Optional[int]			)  -> List[str]:


      """simple docstring"""




      requires_backends(self					,							["""torch"""]			)
      logger.info("""PyTorch: setting up devices"""			)
      if not self.cuda:
           __SCREAMING_SNAKE_CASE     =      torch.device("""cpu"""			)
           __SCREAMING_SNAKE_CASE     =      0
      elif is_torch_tpu_available():
           __SCREAMING_SNAKE_CASE     =      xm.xla_device()
           __SCREAMING_SNAKE_CASE     =      0
      else:
           __SCREAMING_SNAKE_CASE     =      torch.device("""cuda""" if torch.cuda.is_available() else """cpu"""			)
           __SCREAMING_SNAKE_CASE     =      torch.cuda.device_count()
      return device, n_gpu
 @property
 def       UpperCAmelCase__		(		self					:       Tuple			)  -> Optional[Any]:


      """simple docstring"""




      return is_torch_tpu_available() and self.tpu
 @property
 def       UpperCAmelCase__		(		self					:       Any			)  -> Dict:


      """simple docstring"""




      requires_backends(self					,							["""torch"""]			)
      # TODO(PVP): currently only single GPU is supported
      return torch.cuda.current_device()
 @property
 def       UpperCAmelCase__		(		self					:       Dict			)  -> int:


      """simple docstring"""




      requires_backends(self					,							["""torch"""]			)
      return self._setup_devices[0]
 @property
 def       UpperCAmelCase__		(		self					:       int			)  -> List[str]:


      """simple docstring"""




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


 @property
 def       UpperCAmelCase__		(		self					:       List[str]			)  -> Dict:


      """simple docstring"""




      return self.n_gpu > 0







"""simple docstring"""






def   a_						(					lowerCamelCase					,			lowerCamelCase       ):
				if a < 0 or b < 0:
								raise ValueError('the value of both inputs must be positive'       )

				UpperCAmelCase__             =							str(bin(lowerCamelCase       )       )[2:]  # remove the leading "0b"
				UpperCAmelCase__             =							str(bin(lowerCamelCase       )       )[2:]  # remove the leading "0b"

				UpperCAmelCase__             =							max(len(lowerCamelCase       )					,			len(lowerCamelCase       )       )

				return "0b" + "".join(
				    str(int(char_a == '1' and char_b == '1'       )       )
				    for char_a, char_b in zip(a_binary.zfill(lowerCamelCase       )					,			b_binary.zfill(lowerCamelCase       )       )       )


if __name__ == "__main__":
						import doctest

						doctest.testmod()



