


'''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


lowerCamelCase__					=   logging.get_logger(__name__)






@dataclass
class 		lowerCAmelCase__	(	UpperCAmelCase__		):
			lowerCAmelCase       :		Optional[Any]				      =   [
			    "no_inference",
			    "no_cuda",
			    "no_tpu",
			    "no_speed",
			    "no_memory",
			    "no_env_print",
			    "no_multi_process",
			]




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



					'''simple docstring'''







					for deprecated_arg in self.deprecated_args:
							if deprecated_arg in kwargs:
									_UpperCAmelCase						:				int	    =					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]}"""       )

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

			lowerCAmelCase       :		bool				      =   field(default=UpperCAmelCase__			,				metadata={"help": "Trace the models using torchscript"}		)
			lowerCAmelCase       :		bool				      =   field(default=UpperCAmelCase__			,				metadata={"help": "Print Xla/PyTorch tpu metrics"}		)
			lowerCAmelCase       :		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 							lowerCAmelCase__			(						self     :   int       )      ->Tuple["torch.device", int]:



					'''simple docstring'''







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




			@property
			def 							lowerCAmelCase__			(						self     :   Union[str, Any]       )      ->Tuple:



					'''simple docstring'''







					return is_torch_tpu_available() and self.tpu




			@property
			def 							lowerCAmelCase__			(						self     :   Union[str, Any]       )      ->int:



					'''simple docstring'''







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




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



					'''simple docstring'''







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




			@property
			def 							lowerCAmelCase__			(						self     :   Union[str, Any]       )      ->Union[str, Any]:



					'''simple docstring'''







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






			@property
			def 							lowerCAmelCase__			(						self     :   str       )      ->Tuple:



					'''simple docstring'''







					return self.n_gpu > 0







'''simple docstring'''


def        __lowerCAmelCase       (__lowerCAmelCase					,       __lowerCAmelCase      ):

		if density <= 0:
				raise ValueError("Impossible fluid density"      )
		if bulk_modulus <= 0:
				raise ValueError("Impossible bulk modulus"      )

		return (bulk_modulus / density) ** 0.5


if __name__ == "__main__":
						import doctest

						doctest.testmod()



