

"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase__			:					Optional[Any]							  =					{
    '''configuration_wav2vec2_conformer''': [
        '''WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''Wav2Vec2ConformerConfig''',
    ],
}


try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCamelCase__			:					Any							  =					[
						    '''WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''Wav2Vec2ConformerForAudioFrameClassification''',
						    '''Wav2Vec2ConformerForCTC''',
						    '''Wav2Vec2ConformerForPreTraining''',
						    '''Wav2Vec2ConformerForSequenceClassification''',
						    '''Wav2Vec2ConformerForXVector''',
						    '''Wav2Vec2ConformerModel''',
						    '''Wav2Vec2ConformerPreTrainedModel''',
						]

if TYPE_CHECKING:
						from .configuration_wavaveca_conformer import (
						    WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
						    WavaVecaConformerConfig,
						)

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_wavaveca_conformer import (
												    WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    WavaVecaConformerForAudioFrameClassification,
												    WavaVecaConformerForCTC,
												    WavaVecaConformerForPreTraining,
												    WavaVecaConformerForSequenceClassification,
												    WavaVecaConformerForXVector,
												    WavaVecaConformerModel,
												    WavaVecaConformerPreTrainedModel,
												)

else:
						import sys

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








"""simple docstring"""






from math import factorial
def  UpperCamelCase   (     _lowerCAmelCase       :  Dict,					_lowerCAmelCase       :  List[str]	)			->     Dict:
	return factorial(_lowerCAmelCase	) / (factorial(_lowerCAmelCase	) * factorial(n - r	))
def  UpperCamelCase   (     )			->     Tuple:
	_UpperCAmelCase      :							Optional[int]       =   0

	for i in range(1,					101	):
		for j in range(1,					i + 1	):
			if combinations(_lowerCAmelCase,					_lowerCAmelCase	) > 1E6:
				total += 1
	return total


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





