






from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowercase  :							Optional[Any]			  =    logging.get_logger(__name__)

lowercase  :							Optional[Any]			  =    {
    '''google/mobilenet_v1_1.0_224''': '''https://huggingface.co/google/mobilenet_v1_1.0_224/resolve/main/config.json''',
    '''google/mobilenet_v1_0.75_192''': '''https://huggingface.co/google/mobilenet_v1_0.75_192/resolve/main/config.json''',
    # See all MobileNetV1 models at https://huggingface.co/models?filter=mobilenet_v1
}




class 		UpperCAmelCase_						(	SCREAMING_SNAKE_CASE__					):


						'''simple docstring'''




						A     :   Optional[Any]						=					'mobilenet_v1'






						def __init__(	self		,				_SCREAMING_SNAKE_CASE=3		,				_SCREAMING_SNAKE_CASE=224		,				_SCREAMING_SNAKE_CASE=1.0		,				_SCREAMING_SNAKE_CASE=8		,				_SCREAMING_SNAKE_CASE="relu6"		,				_SCREAMING_SNAKE_CASE=True		,				_SCREAMING_SNAKE_CASE=0.999		,				_SCREAMING_SNAKE_CASE=0.02		,				_SCREAMING_SNAKE_CASE=0.001		,				**_SCREAMING_SNAKE_CASE		,				) ->				Any:
								super().__init__(**_SCREAMING_SNAKE_CASE				)

								if depth_multiplier <= 0:
										raise ValueError("depth_multiplier must be greater than zero."				)

								snake_case_				:							int						 =       num_channels
								snake_case_				:							Tuple						 =       image_size
								snake_case_				:							Optional[Any]						 =       depth_multiplier
								snake_case_				:							List[str]						 =       min_depth
								snake_case_				:							Optional[int]						 =       hidden_act
								snake_case_				:							int						 =       tf_padding
								snake_case_				:							Union[str, Any]						 =       classifier_dropout_prob
								snake_case_				:							str						 =       initializer_range
								snake_case_				:							List[Any]						 =       layer_norm_eps




class 		UpperCAmelCase_						(	SCREAMING_SNAKE_CASE__					):


						'''simple docstring'''




						A     :   Any						=					version.parse('1.11'					)






						@property
						def       _lowerCAmelCase       (	self				) ->				Mapping[str, Mapping[int, str]]:
								return OrderedDict([("pixel_values", {0: "batch"})]				)






						@property
						def       _lowerCAmelCase       (	self				) ->				Mapping[str, Mapping[int, str]]:
								if self.task == "image-classification":
										return OrderedDict([("logits", {0: "batch"})]				)
								else:
										return OrderedDict([("last_hidden_state", {0: "batch"}), ("pooler_output", {0: "batch"})]				)






						@property
						def       _lowerCAmelCase       (	self				) ->				float:
								return 1e-4








def      lowerCAmelCase__	(    _a       :			int    ):
		snake_case_				:							str						 =       1
		for i in range(1  ,      num + 1    ):
				fact *= i
		return fact

def      lowerCAmelCase__	(    _a       :			int    ):
		snake_case_				:							List[str]						 =       0
		while number > 0:
				snake_case_				:							Dict						 =       number % 10
				sum_of_digits += last_digit
				snake_case_				:							List[Any]						 =       number // 10  # Removing the last_digit from the given number
		return sum_of_digits

def      lowerCAmelCase__	(    _a       :			int = 1_00    ):
		snake_case_				:							Optional[Any]						 =       factorial(_a    )
		snake_case_				:							Optional[int]						 =       split_and_add(_a    )
		return result


if __name__ == "__main__":
							print(solution(int(input('''Enter the Number: ''').strip())))
