





'''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=_snake_case			)
class __a (   _snake_case			):
   __UpperCamelCase   : Dict	      =	field(default='image-classification',   metadata={'include_in_asdict_even_if_is_default': True}			)
   __UpperCamelCase   : Tuple	      =	Features({'image': Image()}			)
   __UpperCamelCase   : List[str]	      =	Features({'labels': ClassLabel}			)
   __UpperCamelCase   : Any	      =	'image'
   __UpperCamelCase   : List[Any]	      =	'labels'





   def      UpperCAmelCase__     (					self				:			Dict				,lowerCamelCase				:			int    ):

      '''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."""    )
      __SCREAMING_SNAKE_CASE      							=       copy.deepcopy(self    )
      __SCREAMING_SNAKE_CASE      							=       self.label_schema.copy()
      __SCREAMING_SNAKE_CASE      							=       features[self.label_column]
      __SCREAMING_SNAKE_CASE      							=       label_schema
      return task_template





   @property
   def      UpperCAmelCase__     (					self				:			str    ):

      '''simple docstring'''

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









'''simple docstring'''

def 						__magic_name__       (							__UpperCAmelCase      )						->					bool:

   '''simple docstring'''







   if num < 0:
      return False

   __SCREAMING_SNAKE_CASE      							=       num
   __SCREAMING_SNAKE_CASE      							=       0
   while num > 0:
      __SCREAMING_SNAKE_CASE      							=       rev_num * 10 + (num % 10)
      num //= 10

   return num_copy == rev_num


if __name__ == "__main__":
    import doctest

    doctest.testmod()





