


'''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  :		List[Any]		     =	logging.get_logger(__name__)

_lowerCAmelCase  :		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  lowerCAmelCase				(				a							):
	_lowerCamelCase   :					Any			      = """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__=0.0_2 ,					snake_case__=0.0_0_1 ,					snake_case__=255 ,					**snake_case__ ,					):
		super().__init__(**snake_case__    )

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

		lowerCAmelCase					:    Optional[int]      							= num_channels
		lowerCAmelCase					:    int      							= image_size
		lowerCAmelCase					:    str      							= depth_multiplier
		lowerCAmelCase					:    Tuple      							= depth_divisible_by
		lowerCAmelCase					:    str      							= min_depth
		lowerCAmelCase					:    Optional[Any]      							= expand_ratio
		lowerCAmelCase					:    Optional[Any]      							= output_stride
		lowerCAmelCase					:    int      							= first_layer_is_expansion
		lowerCAmelCase					:    Tuple      							= finegrained_output
		lowerCAmelCase					:    int      							= hidden_act
		lowerCAmelCase					:    Dict      							= tf_padding
		lowerCAmelCase					:    Optional[Any]      							= classifier_dropout_prob
		lowerCAmelCase					:    List[Any]      							= initializer_range
		lowerCAmelCase					:    int      							= layer_norm_eps
		lowerCAmelCase					:    Optional[Any]      							= semantic_loss_ignore_index



class  lowerCAmelCase				(				a							):
	_lowerCamelCase   :					str			      = version.parse("""1.11"""							)



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



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




'''simple docstring'''




import math

def 			__UpperCamelCase    (    _A    :				int = 1_00				)    ->      int:




	"""simple docstring"""





	lowerCAmelCase					:    List[Any]      							= sum(i * i for i in range(1					,   n + 1				)				)
	lowerCAmelCase					:    Optional[Any]      							= int(math.pow(sum(range(1					,   n + 1				)				)					,   2				)				)
	return square_of_sum - sum_of_squares


if __name__ == "__main__":
				print(f"""{solution() = }""")
