

"""simple docstring"""





from collections import OrderedDict
from typing import List, Mapping

from packaging import version

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


__UpperCamelCase  :      List[str]							      =		logging.get_logger(__name__)

__UpperCamelCase  :      List[str]							      =		{
    '''google/efficientnet-b7''': '''https://huggingface.co/google/efficientnet-b7/resolve/main/config.json''',
}







class 				SCREAMING_SNAKE_CASE					(		a_       ):






					"""simple docstring"""



					lowercase__				 =       "efficientnet"







					def __init__(       self			:				Optional[Any]   ,lowercase_			:				int = 3   ,lowercase_			:				int = 6_0_0   ,lowercase_			:				float = 2.0   ,lowercase_			:				float = 3.1   ,lowercase_			:				int = 8   ,lowercase_			:				List[int] = [3, 3, 5, 3, 5, 5, 3]   ,lowercase_			:				List[int] = [3_2, 1_6, 2_4, 4_0, 8_0, 1_1_2, 1_9_2]   ,lowercase_			:				List[int] = [1_6, 2_4, 4_0, 8_0, 1_1_2, 1_9_2, 3_2_0]   ,lowercase_			:				List[int] = []   ,lowercase_			:				List[int] = [1, 2, 2, 2, 1, 2, 1]   ,lowercase_			:				List[int] = [1, 2, 2, 3, 3, 4, 1]   ,lowercase_			:				List[int] = [1, 6, 6, 6, 6, 6, 6]   ,lowercase_			:				float = 0.25   ,lowercase_			:				str = "swish"   ,lowercase_			:				int = 2_5_6_0   ,lowercase_			:				str = "mean"   ,lowercase_			:				float = 0.02   ,lowercase_			:				float = 0.001   ,lowercase_			:				float = 0.99   ,lowercase_			:				float = 0.5   ,lowercase_			:				float = 0.2   ,**lowercase_			:				Optional[Any]   ,):
						super().__init__(**lowercase_		)

						lowerCAmelCase__	:						List[str]  				=	num_channels
						lowerCAmelCase__	:						List[Any]  				=	image_size
						lowerCAmelCase__	:						int  				=	width_coefficient
						lowerCAmelCase__	:						int  				=	depth_coefficient
						lowerCAmelCase__	:						Dict  				=	depth_divisor
						lowerCAmelCase__	:						Optional[int]  				=	kernel_sizes
						lowerCAmelCase__	:						Union[str, Any]  				=	in_channels
						lowerCAmelCase__	:						Any  				=	out_channels
						lowerCAmelCase__	:						Tuple  				=	depthwise_padding
						lowerCAmelCase__	:						str  				=	strides
						lowerCAmelCase__	:						Optional[Any]  				=	num_block_repeats
						lowerCAmelCase__	:						Union[str, Any]  				=	expand_ratios
						lowerCAmelCase__	:						Any  				=	squeeze_expansion_ratio
						lowerCAmelCase__	:						str  				=	hidden_act
						lowerCAmelCase__	:						List[Any]  				=	hidden_dim
						lowerCAmelCase__	:						Any  				=	pooling_type
						lowerCAmelCase__	:						Dict  				=	initializer_range
						lowerCAmelCase__	:						List[str]  				=	batch_norm_eps
						lowerCAmelCase__	:						str  				=	batch_norm_momentum
						lowerCAmelCase__	:						Union[str, Any]  				=	dropout_rate
						lowerCAmelCase__	:						Optional[Any]  				=	drop_connect_rate
						lowerCAmelCase__	:						Dict  				=	sum(lowercase_		) * 4







class 				SCREAMING_SNAKE_CASE					(		a_       ):






					"""simple docstring"""



					lowercase__				 =       version.parse("1.11"       )







					@property
					def        __lowerCAmelCase (       self			:				List[str]		):
						return OrderedDict(
						    [
						        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
						    ]		)







					@property
					def        __lowerCAmelCase (       self			:				Union[str, Any]		):
						return 1E-5







"""simple docstring"""





import random

def   __SCREAMING_SNAKE_CASE  (      A_						,     A_ ):
	lowerCAmelCase__				,lowerCAmelCase__				,lowerCAmelCase__	:						Optional[int]  				=	[], [], []
	for element in data:
		if element < pivot:
			less.append(A_ )
		elif element > pivot:
			greater.append(A_ )
		else:
			equal.append(A_ )
	return less, equal, greater





def   __SCREAMING_SNAKE_CASE  (      A_						,     A_ ):
	# index = len(items) // 2 when trying to find the median
	#   (value of index when items is sorted)

	# invalid input
	if index >= len(A_ ) or index < 0:
		return None

	lowerCAmelCase__	:						str  				=	items[random.randint(0						,     len(A_ ) - 1 )]
	lowerCAmelCase__	:						Optional[Any]  				=	0
	lowerCAmelCase__				,lowerCAmelCase__				,lowerCAmelCase__	:						Any  				=	_partition(A_						,     A_ )
	lowerCAmelCase__	:						str  				=	len(A_ )
	lowerCAmelCase__	:						Optional[Any]  				=	len(A_ )

	# index is the pivot
	if m <= index < m + count:
		return pivot
	# must be in smaller
	elif m > index:
		return quick_select(A_						,     A_ )
	# must be in larger
	else:
		return quick_select(A_						,     index - (m + count) )




