
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     __UpperCamelCase (							__a       ):






     """simple docstring"""







     lowerCAmelCase_							   =			[
         '''no_inference''',
         '''no_cuda''',
         '''no_tpu''',
         '''no_speed''',
         '''no_memory''',
         '''no_env_print''',
         '''no_multi_process''',
     ]



     def __init__(				self							:							int     ,						**_A							:							int ):







       """simple docstring"""




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

       __SCREAMING_SNAKE_CASE      :	Tuple					=		kwargs.pop('''torchscript'''     ,						self.torchscript )
       __SCREAMING_SNAKE_CASE      :	List[Any]					=		kwargs.pop('''torch_xla_tpu_print_metrics'''     ,						self.torch_xla_tpu_print_metrics )
       __SCREAMING_SNAKE_CASE      :	Union[str, Any]					=		kwargs.pop('''fp16_opt_level'''     ,						self.fpaa_opt_level )
       super().__init__(**lowercase_ )

     lowerCAmelCase_							   =			field(default=__a ,						metadata={'''help''': '''Trace the models using torchscript'''}       )
     lowerCAmelCase_							   =			field(default=__a ,						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							:							Dict ):







       """simple docstring"""




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



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







       """simple docstring"""




       return is_torch_tpu_available() and self.tpu



     @property
     def  UpperCAmelCase__							(				self							:							Tuple ):







       """simple docstring"""




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



     @property
     def  UpperCAmelCase__							(				self							:							Dict ):







       """simple docstring"""




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



     @property
     def  UpperCAmelCase__							(				self							:							Any ):







       """simple docstring"""




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




     @property
     def  UpperCAmelCase__							(				self							:							Optional[int] ):







       """simple docstring"""




       return self.n_gpu > 0

'''simple docstring'''


import warnings

from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor


__snake_case						  =		logging.get_logger(__name__)





class       _a    (		__a      ):


  """simple docstring"""

  def __init__(		self      :       int   ,				*lowercase_      :       Tuple   ,				**lowercase_      :       List[Any]      ):







    '''simple docstring'''


    warnings.warn(
        """The class PoolFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
        """ Please use PoolFormerImageProcessor instead."""   ,				lowercase_   ,				)
    super().__init__(*lowercase_   ,				**lowercase_      )

