






'''simple docstring'''



def    __UpperCAmelCase	(				)  ->			Any:

   """simple docstring"""
   __a				     =    [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]

   __a				     =    6
   __a				     =    1
   __a				     =    1901

   __a				     =    0

   while year < 2001:
      day += 7

      if (year % 4 == 0 and year % 100 != 0) or (year % 400 == 0):
         if day > days_per_month[month - 1] and month != 2:
            month += 1
            __a				     =    day - days_per_month[month - 2]
         elif day > 29 and month == 2:
            month += 1
            __a				     =    day - 29
      else:
         if day > days_per_month[month - 1]:
            month += 1
            __a				     =    day - days_per_month[month - 2]

      if month > 12:
         year += 1
         __a				     =    1

      if year < 2001 and day == 1:
         sundays += 1
   return sundays


if __name__ == "__main__":
 print(solution())







'''simple docstring'''



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


__UpperCamelCase      :       List[str]      			=      logging.get_logger(__name__)

__UpperCamelCase      :       Tuple      			=      {
    """sayakpaul/vit-msn-base""": """https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json""",
    # See all ViT MSN models at https://huggingface.co/models?filter=vit_msn
}
class 							__SCREAMING_SNAKE_CASE       (							_lowerCAmelCase     ):
      __a  					="vit_msn"




      def __init__(  self ,   lowerCamelCase=768 ,   lowerCamelCase=12 ,   lowerCamelCase=12 ,   lowerCamelCase=3072 ,   lowerCamelCase="gelu" ,   lowerCamelCase=0.0 ,   lowerCamelCase=0.0 ,   lowerCamelCase=0.02 ,   lowerCamelCase=1e-06 ,   lowerCamelCase=224 ,   lowerCamelCase=16 ,   lowerCamelCase=3 ,   lowerCamelCase=True ,   **lowerCamelCase ,   )							->Tuple:



         '''simple docstring'''
         super().__init__(**lowerCamelCase      )

         __a				     =    hidden_size
         __a				     =    num_hidden_layers
         __a				     =    num_attention_heads
         __a				     =    intermediate_size
         __a				     =    hidden_act
         __a				     =    hidden_dropout_prob
         __a				     =    attention_probs_dropout_prob
         __a				     =    initializer_range
         __a				     =    layer_norm_eps
         __a				     =    image_size
         __a				     =    patch_size
         __a				     =    num_channels
         __a				     =    qkv_bias