



'''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


snake_case_ :	int         =  logging.get_logger(__name__)

snake_case_ :	Union[str, 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 							lowercase__	(							lowercase   ):
	lowercase__  				=			"""mobilenet_v1"""





	def __init__( self					:				List[Any] ,lowerCamelCase__					:				List[str]=3 ,lowerCamelCase__					:				Tuple=224 ,lowerCamelCase__					:				str=1.0 ,lowerCamelCase__					:				List[str]=8 ,lowerCamelCase__					:				int="relu6" ,lowerCamelCase__					:				str=True ,lowerCamelCase__					:				Optional[Any]=0.9_9_9 ,lowerCamelCase__					:				str=0.0_2 ,lowerCamelCase__					:				Optional[Any]=0.0_0_1 ,**lowerCamelCase__					:				Dict ,):







							'''simple docstring'''
							super().__init__(**lowerCamelCase__ )

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

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






class 							lowercase__	(							lowercase   ):
	lowercase__  				=			version.parse("""1.11"""   )





	@property
	def 	UpperCamelCase_  ( self					:				str ):







							'''simple docstring'''
							return OrderedDict([('pixel_values', {0: 'batch'})] )





	@property
	def 	UpperCamelCase_  ( self					:				Optional[Any] ):







							'''simple docstring'''
							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					:				Optional[int] ):







							'''simple docstring'''
							return 1E-4










"""simple docstring"""



def 						lowercase    (				__snake_case				: Optional[int]	):
		lowercase_ : int							       =   0
		lowercase_ : Optional[Any]							       =   len(__snake_case	)

		for i in range(n - 1	):
				for j in range(i + 1		,					__snake_case	):
						if arr[i] > arr[j]:
								num_inversions += 1

		return num_inversions



def 						lowercase    (				__snake_case				: str	):
		if len(__snake_case	) <= 1:
				return arr, 0
		lowercase_ : Optional[Any]							       =   len(__snake_case	) // 2
		lowercase_ : List[Any]							       =   arr[0:mid]
		lowercase_ : Union[str, Any]							       =   arr[mid:]

		lowercase_       ,					lowercase_ : Tuple							       =   count_inversions_recursive(__snake_case	)
		lowercase_       ,					lowercase_ : List[Any]							       =   count_inversions_recursive(__snake_case	)
		lowercase_       ,					lowercase_ : List[Any]							       =   _count_cross_inversions(__snake_case		,					__snake_case	)

		lowercase_ : List[Any]							       =   inversion_p + inversions_q + cross_inversions
		return c, num_inversions



def 						lowercase    (				__snake_case				: str		,					__snake_case				: Optional[int]	):
		lowercase_ : Optional[Any]							       =   []
		lowercase_ : Any							       =   0
		while i < len(__snake_case	) and j < len(__snake_case	):
				if p[i] > q[j]:
						# if P[1] > Q[j], then P[k] > Q[k] for all  i < k <= len(P)
						# These are all inversions. The claim emerges from the
						# property that P is sorted.
						num_inversion += len(__snake_case	) - i
						r.append(q[j]	)
						j += 1
				else:
						r.append(p[i]	)
						i += 1

		if i < len(__snake_case	):
				r.extend(p[i:]	)
		else:
				r.extend(q[j:]	)

		return r, num_inversion



def 						lowercase    (				):
		lowercase_ : Union[str, Any]							       =   [1_0, 2, 1, 5, 5, 2, 1_1]

		# this arr has 8 inversions:
		# (10, 2), (10, 1), (10, 5), (10, 5), (10, 2), (2, 1), (5, 2), (5, 2)

		lowercase_ : int							       =   count_inversions_bf(__snake_case	)
		lowercase_       ,					lowercase_ : Dict							       =   count_inversions_recursive(__snake_case	)

		assert num_inversions_bf == num_inversions_recursive == 8

		print('''number of inversions = '''		,					__snake_case	)

		# testing an array with zero inversion (a sorted arr_1)

		arr_a.sort()
		lowercase_ : Dict							       =   count_inversions_bf(__snake_case	)
		lowercase_       ,					lowercase_ : Dict							       =   count_inversions_recursive(__snake_case	)

		assert num_inversions_bf == num_inversions_recursive == 0
		print('''number of inversions = '''		,					__snake_case	)

		# an empty list should also have zero inversions
		lowercase_ : List[Any]							       =   []
		lowercase_ : Any							       =   count_inversions_bf(__snake_case	)
		lowercase_       ,					lowercase_ : List[str]							       =   count_inversions_recursive(__snake_case	)

		assert num_inversions_bf == num_inversions_recursive == 0
		print('''number of inversions = '''		,					__snake_case	)


if __name__ == "__main__":
						main()



