
'''simple docstring'''




import math







def 						lowerCAmelCase_							(  snake_case__						,							snake_case__		):




    '''simple docstring'''



    if 0 not in (x, y):
        # We use the relation x^y = y*log10(x), where 10 is the base.
        return y * math.logaa(snake_case__		)
    else:
        if x == 0:  # 0 raised to any number is 0
            return 0
        elif y == 0:
            return 1  # any number raised to 0 is 1
    raise AssertionError('''This should never happen'''		)


if __name__ == "__main__":  # Main function
      # Read two numbers from input and typecast them to int using map function.
      # Here x is the base and y is the power.
      lowercase     :							Dict       						=     'Enter the base and the power separated by a comma: '
      lowercase						,	lowercase     :							str       						=     map(int, input(prompt).split(','))
      lowercase						,	lowercase     :							str       						=     map(int, input(prompt).split(','))

      # We find the log of each number, using the function res(), which takes two
      # arguments.
      lowercase     :							List[str]       						=     res(xa, ya)
      lowercase     :							List[str]       						=     res(xa, ya)

      # We check for the largest number
      if resa > resa:
            print('Largest number is', xa, '^', ya)
      elif resa > resa:
            print('Largest number is', xa, '^', ya)
      else:
            print('Both are equal')






'''simple docstring'''




from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase     :							Any       						=     logging.get_logger(__name__)

lowercase     :							int       						=     {
    'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json',
}





class 					A							(				__snake_case		):
     __magic_name__          =						'''timesformer'''





     def __init__(				self		,     SCREAMING_SNAKE_CASE=224		,     SCREAMING_SNAKE_CASE=16		,     SCREAMING_SNAKE_CASE=3		,     SCREAMING_SNAKE_CASE=8		,     SCREAMING_SNAKE_CASE=768		,     SCREAMING_SNAKE_CASE=12		,     SCREAMING_SNAKE_CASE=12		,     SCREAMING_SNAKE_CASE=3072		,     SCREAMING_SNAKE_CASE="gelu"		,     SCREAMING_SNAKE_CASE=0.0		,     SCREAMING_SNAKE_CASE=0.0		,     SCREAMING_SNAKE_CASE=0.02		,     SCREAMING_SNAKE_CASE=1e-6		,     SCREAMING_SNAKE_CASE=True		,     SCREAMING_SNAKE_CASE="divided_space_time"		,     SCREAMING_SNAKE_CASE=0		,     **SCREAMING_SNAKE_CASE		,     )					->							Tuple:






         """simple docstring"""






         super().__init__(**SCREAMING_SNAKE_CASE      )

         A			:  List[Any]   =		image_size
         A			:  List[str]   =		patch_size
         A			:  List[str]   =		num_channels
         A			:  str   =		num_frames

         A			:  Any   =		hidden_size
         A			:  Dict   =		num_hidden_layers
         A			:  Any   =		num_attention_heads
         A			:  Optional[Any]   =		intermediate_size
         A			:  Union[str, Any]   =		hidden_act
         A			:  Tuple   =		hidden_dropout_prob
         A			:  Optional[int]   =		attention_probs_dropout_prob
         A			:  Tuple   =		initializer_range
         A			:  List[Any]   =		layer_norm_eps
         A			:  Union[str, Any]   =		qkv_bias

         A			:  List[str]   =		attention_type
         A			:  Union[str, Any]   =		drop_path_rate




