


from math import factorial



def 			_a      (    __UpperCamelCase	,	__UpperCamelCase			):
     return factorial(SCREAMING_SNAKE_CASE_			) / (factorial(SCREAMING_SNAKE_CASE_			) * factorial(n - r			))



def 			_a      (    ):
     a_     :  List[Any]				      =     0

     for i in range(1	,	1_0_1			):
          for j in range(1	,	i + 1			):
               if combinations(SCREAMING_SNAKE_CASE_	,	SCREAMING_SNAKE_CASE_			) > 1E6:
                    total += 1
     return total


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







from typing import TYPE_CHECKING

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


__UpperCAmelCase			:			int			      =					{"configuration_vilt": ["VILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViltConfig"]}

try:
  if not is_vision_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __UpperCAmelCase			:			Optional[Any]			      =					["ViltFeatureExtractor"]
  __UpperCAmelCase			:			Union[str, Any]			      =					["ViltImageProcessor"]
  __UpperCAmelCase			:			Dict			      =					["ViltProcessor"]

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __UpperCAmelCase			:			List[Any]			      =					[
      "VILT_PRETRAINED_MODEL_ARCHIVE_LIST",
      "ViltForImageAndTextRetrieval",
      "ViltForImagesAndTextClassification",
      "ViltForTokenClassification",
      "ViltForMaskedLM",
      "ViltForQuestionAnswering",
      "ViltLayer",
      "ViltModel",
      "ViltPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_vilt import VILT_PRETRAINED_CONFIG_ARCHIVE_MAP, ViltConfig

  try:
    if not is_vision_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .feature_extraction_vilt import ViltFeatureExtractor
    from .image_processing_vilt import ViltImageProcessor
    from .processing_vilt import ViltProcessor

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_vilt import (
        VILT_PRETRAINED_MODEL_ARCHIVE_LIST,
        ViltForImageAndTextRetrieval,
        ViltForImagesAndTextClassification,
        ViltForMaskedLM,
        ViltForQuestionAnswering,
        ViltForTokenClassification,
        ViltLayer,
        ViltModel,
        ViltPreTrainedModel,
    )


else:
  import sys

  __UpperCAmelCase			:			Any			      =					_LazyModule(__name__, globals()["__file__"], _import_structure)

