


'''simple docstring'''



A__		:					Dict												=  [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A__		:					str												=  [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A__		:					Dict												=  {
    0: """Sunday""",
    1: """Monday""",
    2: """Tuesday""",
    3: """Wednesday""",
    4: """Thursday""",
    5: """Friday""",
    6: """Saturday""",
}



def 			UpperCAmelCase__					(	UpperCAmelCase_    :				int      ,    UpperCAmelCase_    :				int      ,    UpperCAmelCase_    :				int							)     ->		str:
     assert len(str(UpperCAmelCase_							)							) > 2, "year should be in YYYY format"
     assert 1 <= month <= 12, "month should be between 1 to 12"
     assert 1 <= day <= 31, "day should be between 1 to 31"

     # Doomsday algorithm:
     __lowerCamelCase   :	List[Any]								=		year // 1_00
     __lowerCamelCase   :	Dict								=		(5 * (century % 4) + 2) % 7
     __lowerCamelCase   :	Union[str, Any]								=		year % 1_00
     __lowerCamelCase   :	str								=		centurian % 12
     __lowerCamelCase   :	List[Any]								=		(
         (centurian // 12) + centurian_m + (centurian_m // 4) + century_anchor
     ) % 7
     __lowerCamelCase   :	Union[str, Any]								=		(
         DOOMSDAY_NOT_LEAP[month - 1]
         if (year % 4 != 0) or (centurian == 0 and (year % 4_00) == 0)
         else DOOMSDAY_LEAP[month - 1]
     )
     __lowerCamelCase   :	Union[str, Any]								=		(dooms_day + day - day_anchor) % 7
     return WEEK_DAY_NAMES[week_day]


if __name__ == "__main__":
      import doctest

      doctest.testmod()










'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_torch_available,
    is_vision_available,
)


A__		:					List[str]												=  {"""configuration_beit""": ["""BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BeitConfig""", """BeitOnnxConfig"""]}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__		:					str												=  ["""BeitFeatureExtractor"""]
      A__		:					List[str]												=  ["""BeitImageProcessor"""]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__		:					Optional[int]												=  [
          """BEIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """BeitForImageClassification""",
          """BeitForMaskedImageModeling""",
          """BeitForSemanticSegmentation""",
          """BeitModel""",
          """BeitPreTrainedModel""",
      ]


try:
      if not is_flax_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A__		:					Any												=  [
          """FlaxBeitForImageClassification""",
          """FlaxBeitForMaskedImageModeling""",
          """FlaxBeitModel""",
          """FlaxBeitPreTrainedModel""",
      ]

if TYPE_CHECKING:
      from .configuration_beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig, BeitOnnxConfig

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_beit import BeitFeatureExtractor
            from .image_processing_beit import BeitImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_beit import (
                BEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
                BeitForImageClassification,
                BeitForMaskedImageModeling,
                BeitForSemanticSegmentation,
                BeitModel,
                BeitPreTrainedModel,
            )

      try:
            if not is_flax_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_flax_beit import (
                FlaxBeitForImageClassification,
                FlaxBeitForMaskedImageModeling,
                FlaxBeitModel,
                FlaxBeitPreTrainedModel,
            )


else:
      import sys

      A__		:					Optional[Any]												=  _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






