
'''simple docstring'''







from typing import TYPE_CHECKING

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


lowercase    :							Any      =					{
    "configuration_convnext": ["CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvNextConfig", "ConvNextOnnxConfig"]
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase    :							Optional[int]      =					["ConvNextFeatureExtractor"]
					lowercase    :							Dict      =					["ConvNextImageProcessor"]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase    :							Any      =					[
					    "CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "ConvNextForImageClassification",
					    "ConvNextModel",
					    "ConvNextPreTrainedModel",
					    "ConvNextBackbone",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowercase    :							Tuple      =					[
					    "TFConvNextForImageClassification",
					    "TFConvNextModel",
					    "TFConvNextPreTrainedModel",
					]

if TYPE_CHECKING:
					from .configuration_convnext import CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP, ConvNextConfig, ConvNextOnnxConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_convnext import ConvNextFeatureExtractor
										from .image_processing_convnext import ConvNextImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_convnext import (
										    CONVNEXT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    ConvNextBackbone,
										    ConvNextForImageClassification,
										    ConvNextModel,
										    ConvNextPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_convnext import TFConvNextForImageClassification, TFConvNextModel, TFConvNextPreTrainedModel


else:
					import sys

					lowercase    :							Dict      =					_LazyModule(__name__, globals()["__file__"], _import_structure)



"""simple docstring"""





def       lowerCamelCase__		(			__snake_case = 10_00	)							->		int:


					"""simple docstring"""





					_UpperCamelCase							 =  2**power
					_UpperCamelCase							 =  str(__snake_case	)
					_UpperCamelCase							 =  list(__snake_case	)
					_UpperCamelCase							 =  0

					for i in list_num:
										sum_of_num += int(__snake_case	)

					return sum_of_num


if __name__ == "__main__":
				_a														=		int(input("""Enter the power of 2: """).strip())
				print("""2 ^ """, power, """ = """, 2**power)
				_a														=		solution(power)
				print("""Sum of the digits is: """, result)






