



'''simple docstring'''



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


lowerCAmelCase	:		Any				=   logging.get_logger(__name__)

lowerCAmelCase	:		Dict				=   {
    """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__	(		_snake_case ):
					a      :     int        =							"""mobilenet_v1"""



					def __init__(    self			,				UpperCamelCase=3			,				UpperCamelCase=224			,				UpperCamelCase=1.0			,				UpperCamelCase=8			,				UpperCamelCase="relu6"			,				UpperCamelCase=True			,				UpperCamelCase=0.9_99			,				UpperCamelCase=0.02			,				UpperCamelCase=0.0_01			,				**UpperCamelCase			,				)     ->			Any:
						super().__init__(**snake_case_     )

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

						__lowerCAmelCase												=  num_channels
						__lowerCAmelCase												=  image_size
						__lowerCAmelCase												=  depth_multiplier
						__lowerCAmelCase												=  min_depth
						__lowerCAmelCase												=  hidden_act
						__lowerCAmelCase												=  tf_padding
						__lowerCAmelCase												=  classifier_dropout_prob
						__lowerCAmelCase												=  initializer_range
						__lowerCAmelCase												=  layer_norm_eps






class 					UpperCAmelCase__	(		_snake_case ):
					a      :     Optional[Any]        =							version.parse("""1.11""" )



					@property
					def        UpperCAmelCase_						(    self     )     ->			Any:
						return OrderedDict([("pixel_values", {0: "batch"})]     )



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



					@property
					def        UpperCAmelCase_						(    self     )     ->			Dict:
						return 1E-4




'''simple docstring'''



def   __lowerCAmelCase					(							lowerCamelCase   :						Union[str, Any]					):






	'''simple docstring'''




	__lowerCAmelCase												=  1
	__lowerCAmelCase												=  2
	while i * i <= n:
		__lowerCAmelCase												=  0
		while n % i == 0:
			n //= i
			multiplicity += 1
		n_divisors *= multiplicity + 1
		i += 1
	if n > 1:
		n_divisors *= 2
	return n_divisors



def   __lowerCAmelCase					(							):






	'''simple docstring'''




	__lowerCAmelCase												=  1
	__lowerCAmelCase												=  1

	while True:
		i += 1
		t_num += i

		if count_divisors(lowerCamelCase					) > 5_00:
			break

	return t_num


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