

"""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


SCREAMING_SNAKE_CASE_            = logging.get_logger(__name__)

@dataclass
class 			a					(		lowerCamelCase__			):
						_lowercase        =     [
						    "no_inference",
						    "no_cuda",
						    "no_tpu",
						    "no_speed",
						    "no_memory",
						    "no_env_print",
						    "no_multi_process",
						]


						def __init__(    self  ,   **A_		):







										'''simple docstring'''


										for deprecated_arg in self.deprecated_args:
														if deprecated_arg in kwargs:
																		_UpperCAmelCase    :						Union[str, Any]							=      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]}'		)

										_UpperCAmelCase    :						int							=      kwargs.pop("torchscript"  ,   self.torchscript		)
										_UpperCAmelCase    :						Union[str, Any]							=      kwargs.pop("torch_xla_tpu_print_metrics"  ,   self.torch_xla_tpu_print_metrics		)
										_UpperCAmelCase    :						str							=      kwargs.pop("fp16_opt_level"  ,   self.fpaa_opt_level		)
										super().__init__(**__A		)

						_lowercase        =     field(default=lowerCamelCase__							,	metadata={"help": "Trace the models using torchscript"}			)
						_lowercase        =     field(default=lowerCamelCase__							,	metadata={"help": "Print Xla/PyTorch tpu metrics"}			)
						_lowercase        =     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		):







										'''simple docstring'''


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


						@property
						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										return is_torch_tpu_available() and self.tpu


						@property
						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


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


						@property
						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


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


						@property
						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


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





						@property
						def     _UpperCAmelCase			(    self		):







										'''simple docstring'''


										return self.n_gpu > 0





def 							__SCREAMING_SNAKE_CASE							(			lowerCAmelCase:					int	)				->    int:
				if not isinstance(lowerCAmelCase					, lowerCAmelCase	):
								raise TypeError("Input value must be an 'int' type"	)

				_UpperCAmelCase    :						List[Any]							=      0
				while number:
								position += 1
								number >>= 1

				return position


if __name__ == "__main__":
					import doctest

					doctest.testmod()


