





"""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


a		:				Union[str, Any]  			=     logging.get_logger(__name__)

a		:				int  			=     {
    '''google/efficientnet-b7''': '''https://huggingface.co/google/efficientnet-b7/resolve/main/config.json''',
}


class  __UpperCamelCase       (		a__		):
							lowerCamelCase     :      Any         ="""efficientnet"""






							def __init__(     self   ,      lowerCAmelCase__ = 3   ,      lowerCAmelCase__ = 600   ,      lowerCAmelCase__ = 2.0   ,      lowerCAmelCase__ = 3.1   ,      lowerCAmelCase__ = 8   ,      lowerCAmelCase__ = [3, 3, 5, 3, 5, 5, 3]   ,      lowerCAmelCase__ = [32, 16, 24, 40, 80, 112, 192]   ,      lowerCAmelCase__ = [16, 24, 40, 80, 112, 192, 320]   ,      lowerCAmelCase__ = []   ,      lowerCAmelCase__ = [1, 2, 2, 2, 1, 2, 1]   ,      lowerCAmelCase__ = [1, 2, 2, 3, 3, 4, 1]   ,      lowerCAmelCase__ = [1, 6, 6, 6, 6, 6, 6]   ,      lowerCAmelCase__ = 0.25   ,      lowerCAmelCase__ = "swish"   ,      lowerCAmelCase__ = 2560   ,      lowerCAmelCase__ = "mean"   ,      lowerCAmelCase__ = 0.02   ,      lowerCAmelCase__ = 0.001   ,      lowerCAmelCase__ = 0.99   ,      lowerCAmelCase__ = 0.5   ,      lowerCAmelCase__ = 0.2   ,      **lowerCAmelCase__   ,      )			->				Dict:
								super().__init__(**lowerCAmelCase__   )

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


class  __UpperCamelCase       (		a__		):
							lowerCamelCase     :      List[str]         =version.parse("""1.11"""		)






							@property
							def 					__a     (     self   )			->				Mapping[str, Mapping[int, str]]:
								return OrderedDict(
								    [
								        ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
								    ]   )






							@property
							def 					__a     (     self   )			->				float:
								return 1E-5









"""simple docstring"""




def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					int = 10					, _lowercase		:					int = 1000					, _lowercase		:					bool = True      )				->int:






	'''simple docstring'''






	assert (
	    isinstance(_lowercase					, _lowercase      )
	    and isinstance(_lowercase					, _lowercase      )
	    and isinstance(_lowercase					, _lowercase      )
	), "Invalid type of value(s) specified to function!"

	if min_val > max_val:
		raise ValueError("Invalid value for min_val or max_val (min_value < max_value)"      )
	return min_val if option else max_val






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					int					, _lowercase		:					int      )				->int:






	'''simple docstring'''






	return int((number_a + number_a) / 2      )






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					int					, _lowercase		:					int					, _lowercase		:					int      )				->None:






	'''simple docstring'''






	assert (
	    isinstance(_lowercase					, _lowercase      ) and isinstance(_lowercase					, _lowercase      ) and isinstance(_lowercase					, _lowercase      )
	), 'argument values must be type of "int"'

	if lower > higher:
		raise ValueError("argument value for lower and higher must be(lower > higher)"      )

	if not lower < to_guess < higher:
		raise ValueError(
		    "guess value must be within the range of lower and higher value"      )

	def answer(_lowercase		:					int      ) -> str:
		if number > to_guess:
			return "high"
		elif number < to_guess:
			return "low"
		else:
			return "same"

	print("started..."      )

	a   :	Optional[Any]			=       lower
	a   :	List[Any]			=       higher

	a   :	Tuple			=       []

	while True:
		a   :	List[Any]			=       get_avg(_lowercase					, _lowercase      )
		last_numbers.append(_lowercase      )

		if answer(_lowercase      ) == "low":
			a   :	Optional[int]			=       number
		elif answer(_lowercase      ) == "high":
			a   :	Tuple			=       number
		else:
			break

	print(F"""guess the number : {last_numbers[-1]}"""      )
	print(F"""details : {last_numbers!s}"""      )






def    _SCREAMING_SNAKE_CASE	(			)				->None:






	'''simple docstring'''






	a   :	Tuple			=       int(input("Enter lower value : "      ).strip()      )
	a   :	Dict			=       int(input("Enter high value : "      ).strip()      )
	a   :	Optional[int]			=       int(input("Enter value to guess : "      ).strip()      )
	guess_the_number(_lowercase					, _lowercase					, _lowercase      )


if __name__ == "__main__":
		main()


