



"""simple docstring"""






import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import ClassLabel, Features, Image
from .base import TaskTemplate






@dataclass(frozen=_lowercase)
class        __snake_case       (	_lowercase):
  snake_case__				:   str  			=						field(default="image-classification"  ,     metadata={"include_in_asdict_even_if_is_default": True})
  snake_case__				:   ClassVar[Features]  			=						Features({"image": Image()})
  snake_case__				:   ClassVar[Features]  			=						Features({"labels": ClassLabel})
  snake_case__				:   str  			=						"image"
  snake_case__				:   str  			=						"labels"




  def 						SCREAMING_SNAKE_CASE				( self     :						str						,					__lowerCAmelCase     :						Dict		):






         """simple docstring"""






         if self.label_column not in features:
                raise ValueError(f'''Column {self.label_column} is not present in features.'''		)
         if not isinstance(features[self.label_column]						,					__lowerCAmelCase		):
                raise ValueError(f'''Column {self.label_column} is not a ClassLabel.'''		)
         _lowerCamelCase						:				List[Any]    			= copy.deepcopy(self		)
         _lowerCamelCase						:				str    			= self.label_schema.copy()
         _lowerCamelCase						:				Union[str, Any]    			= features[self.label_column]
         _lowerCamelCase						:				List[str]    			= label_schema
         return task_template




  @property
  def 						SCREAMING_SNAKE_CASE				( self     :						Optional[Any]		):






         """simple docstring"""






         return {
             self.image_column: "image",
             self.label_column: "labels",
         }








import torch



def 					UpperCAmelCase__     (   ):
  if torch.cuda.is_available():
    lowercase			:Optional[int]							=  torch.cuda.device_count()
  else:
    lowercase			:Dict							=  0
  print(F"Successfully ran on {num_gpus} GPUs"      )


if __name__ == "__main__":
     main()



