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


lowerCamelCase_    :		Tuple							=	logging.get_logger(__name__)

lowerCamelCase_    :		Union[str, Any]							=	{
    """google/efficientnet-b7""": """https://huggingface.co/google/efficientnet-b7/resolve/main/config.json""",
}


class 						a__							(       __snake_case		):
			A__    :       Tuple        =      'efficientnet'



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

								__a		 =       num_channels
								__a		 =       image_size
								__a		 =       width_coefficient
								__a		 =       depth_coefficient
								__a		 =       depth_divisor
								__a		 =       kernel_sizes
								__a		 =       in_channels
								__a		 =       out_channels
								__a		 =       depthwise_padding
								__a		 =       strides
								__a		 =       num_block_repeats
								__a		 =       expand_ratios
								__a		 =       squeeze_expansion_ratio
								__a		 =       hidden_act
								__a		 =       hidden_dim
								__a		 =       pooling_type
								__a		 =       initializer_range
								__a		 =       batch_norm_eps
								__a		 =       batch_norm_momentum
								__a		 =       dropout_rate
								__a		 =       drop_connect_rate
								__a		 =       sum(UpperCAmelCase   ) * 4






class 						a__							(       __snake_case		):
			A__    :       Optional[int]        =      version.parse('1.11'		)



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







			@property
			def __SCREAMING_SNAKE_CASE							(						self   )			->   float:
								return 1e-5





from collections import defaultdict
def 							lowerCAmelCase(     __lowerCamelCase				,    __lowerCamelCase						):
					__a		 =       first_str.lower().strip()
					__a		 =       second_str.lower().strip()

					# Remove whitespace
					__a		 =       first_str.replace(' '				,    ''						)
					__a		 =       second_str.replace(' '				,    ''						)

					# Strings of different lengths are not anagrams
					if len(__lowerCamelCase						) != len(__lowerCamelCase						):
										return False

					# Default values for count should be 0
					__a		 =       defaultdict(__lowerCamelCase						)

					# For each character in input strings,
					# increment count in the corresponding
					for i in range(len(__lowerCamelCase						)						):
										count[first_str[i]] += 1
										count[second_str[i]] -= 1

					return all(_count == 0 for _count in count.values()						)


if __name__ == "__main__":
	from doctest import testmod

	testmod()
	lowerCamelCase_    :		List[str]							=	input("""Enter the first string """).strip()
	lowerCamelCase_    :		Optional[Any]							=	input("""Enter the second string """).strip()

	lowerCamelCase_    :		str							=	check_anagrams(input_a, input_b)
	print(F'''{input_a} and {input_b} are {'' if status else 'not '}anagrams.''')




