

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


_UpperCAmelCase		:       Optional[int]						    =	logging.get_logger(__name__)

_UpperCAmelCase		:       Optional[int]						    =	{
    """google/mobilenet_v2_1.4_224""": """https://huggingface.co/google/mobilenet_v2_1.4_224/resolve/main/config.json""",
    """google/mobilenet_v2_1.0_224""": """https://huggingface.co/google/mobilenet_v2_1.0_224/resolve/main/config.json""",
    """google/mobilenet_v2_0.75_160""": """https://huggingface.co/google/mobilenet_v2_0.75_160/resolve/main/config.json""",
    """google/mobilenet_v2_0.35_96""": """https://huggingface.co/google/mobilenet_v2_0.35_96/resolve/main/config.json""",
    # See all MobileNetV2 models at https://huggingface.co/models?filter=mobilenet_v2
}







class 			lowercase    (	lowercase_      ):
				__SCREAMING_SNAKE_CASE :			int	      =      '''mobilenet_v2'''




				def __init__( self				,       snake_case=3				,       snake_case=224				,       snake_case=1.0				,       snake_case=8				,       snake_case=8				,       snake_case=6				,       snake_case=32				,       snake_case=True				,       snake_case=True				,       snake_case="relu6"				,       snake_case=True				,       snake_case=0.8				,       snake_case=0.02				,       snake_case=0.0_01				,       snake_case=255				,       **snake_case				,       ):
											super().__init__(**snake_case	)

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

											snake_case_          =   num_channels
											snake_case_          =   image_size
											snake_case_          =   depth_multiplier
											snake_case_          =   depth_divisible_by
											snake_case_          =   min_depth
											snake_case_          =   expand_ratio
											snake_case_          =   output_stride
											snake_case_          =   first_layer_is_expansion
											snake_case_          =   finegrained_output
											snake_case_          =   hidden_act
											snake_case_          =   tf_padding
											snake_case_          =   classifier_dropout_prob
											snake_case_          =   initializer_range
											snake_case_          =   layer_norm_eps
											snake_case_          =   semantic_loss_ignore_index







class 			lowercase    (	lowercase_      ):
				__SCREAMING_SNAKE_CASE :			List[Any]	      =      version.parse('''1.11'''      )




				@property
				def    a							( self	):
											return OrderedDict([('pixel_values', {0: 'batch'})]	)




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




				@property
				def    a							( self	):
											return 1e-4







def  __lowerCamelCase     (			UpperCamelCase__				):







							'''simple docstring'''






							snake_case_          =   1
							snake_case_          =   2
							while i * i <= n:
														snake_case_          =   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'''






							snake_case_          =   1
							snake_case_          =   1

							while True:
														i += 1
														t_num += i

														if count_divisors(UpperCamelCase__				) > 500:
																					break

							return t_num


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




