"""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


_a      :		Any           =   logging.get_logger(__name__)
@dataclass
class 						__A							( SCREAMING_SNAKE_CASE_		):
     _UpperCamelCase							:			List[str]							=		[
         "no_inference",
         "no_cuda",
         "no_tpu",
         "no_speed",
         "no_memory",
         "no_env_print",
         "no_multi_process",
     ]






     def __init__(		self				,     **a__  ):
       for deprecated_arg in self.deprecated_args:
         if deprecated_arg in kwargs:
           _lowerCAmelCase						:       Tuple  			=     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]}"  )

       _lowerCAmelCase						:       List[Any]  			=     kwargs.pop("""torchscript"""				,     self.torchscript  )
       _lowerCAmelCase						:       List[str]  			=     kwargs.pop("""torch_xla_tpu_print_metrics"""				,     self.torch_xla_tpu_print_metrics  )
       _lowerCAmelCase						:       List[str]  			=     kwargs.pop("""fp16_opt_level"""				,     self.fpaa_opt_level  )
       super().__init__(**a__  )

     _UpperCamelCase							:			bool							=		field(default=SCREAMING_SNAKE_CASE_    ,	metadata={"help": "Trace the models using torchscript"}		)
     _UpperCamelCase							:			bool							=		field(default=SCREAMING_SNAKE_CASE_    ,	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     __A  (		self  ):
       requires_backends(self				,     ["""torch"""]  )
       logger.info("""PyTorch: setting up devices"""  )
       if not self.cuda:
         _lowerCAmelCase						:       int  			=     torch.device("""cpu"""  )
         _lowerCAmelCase						:       Union[str, Any]  			=     0
       elif is_torch_tpu_available():
         _lowerCAmelCase						:       str  			=     xm.xla_device()
         _lowerCAmelCase						:       Optional[Any]  			=     0
       else:
         _lowerCAmelCase						:       Union[str, Any]  			=     torch.device("""cuda""" if torch.cuda.is_available() else """cpu"""  )
         _lowerCAmelCase						:       Optional[Any]  			=     torch.cuda.device_count()
       return device, n_gpu






     @property
     def     __A  (		self  ):
       return is_torch_tpu_available() and self.tpu






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






     @property
     def     __A  (		self  ):
       requires_backends(self				,     ["""torch"""]  )
       return self._setup_devices[0]






     @property
     def     __A  (		self  ):
       requires_backends(self				,     ["""torch"""]  )
       return self._setup_devices[1]






     @property
     def     __A  (		self  ):
       return self.n_gpu > 0





"""simple docstring"""






from ..utils import DummyObject, requires_backends





class  _A						(       metaclass=lowerCAmelCase	):
      snake_case__			:   List[str]							  =	['onnx']

      def __init__(						self		,       *__lowerCAmelCase		,       **__lowerCAmelCase						):







            """simple docstring"""



            requires_backends(self		,       ["""onnx"""]						)

      @classmethod
      def 				A__       (						cls		,       *__lowerCAmelCase		,       **__lowerCAmelCase						):







            """simple docstring"""



            requires_backends(cls		,       ["""onnx"""]						)







      @classmethod
      def 				A__       (						cls		,       *__lowerCAmelCase		,       **__lowerCAmelCase						):







            """simple docstring"""



            requires_backends(cls		,       ["""onnx"""]						)



