





def   a_    ( ):
   __lowerCAmelCase								=	[31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]

   __lowerCAmelCase								=	6
   __lowerCAmelCase								=	1
   __lowerCAmelCase								=	1901

   __lowerCAmelCase								=	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
            __lowerCAmelCase								=	day - days_per_month[month - 2]
         elif day > 29 and month == 2:
            month += 1
            __lowerCAmelCase								=	day - 29
      else:
         if day > days_per_month[month - 1]:
            month += 1
            __lowerCAmelCase								=	day - days_per_month[month - 2]

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

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


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





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__lowerCAmelCase		       =							{
    '''configuration_canine''': ['''CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CanineConfig'''],
    '''tokenization_canine''': ['''CanineTokenizer'''],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCAmelCase		       =							[
     '''CANINE_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''CanineForMultipleChoice''',
     '''CanineForQuestionAnswering''',
     '''CanineForSequenceClassification''',
     '''CanineForTokenClassification''',
     '''CanineLayer''',
     '''CanineModel''',
     '''CaninePreTrainedModel''',
     '''load_tf_weights_in_canine''',
 ]


if TYPE_CHECKING:
 from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig
 from .tokenization_canine import CanineTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_canine import (
      CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,
      CanineForMultipleChoice,
      CanineForQuestionAnswering,
      CanineForSequenceClassification,
      CanineForTokenClassification,
      CanineLayer,
      CanineModel,
      CaninePreTrainedModel,
      load_tf_weights_in_canine,
  )


else:
 import sys

 __lowerCAmelCase		       =							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


