


'''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


__UpperCAmelCase       							=				logging.get_logger(__name__)

__UpperCAmelCase       							=				{
    '''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 						a__							(				a__    ):





							'''simple docstring'''






							lowercase__     :  Union[str, Any]      		= "mobilenet_v1"







							def __init__(						self   ,       lowerCamelCase_=3   ,       lowerCamelCase_=2_24   ,       lowerCamelCase_=1.0   ,       lowerCamelCase_=8   ,       lowerCamelCase_="relu6"   ,       lowerCamelCase_=True   ,       lowerCamelCase_=0.999   ,       lowerCamelCase_=0.02   ,       lowerCamelCase_=0.001   ,       **lowerCamelCase_   ,       )			->				List[str]:
														super().__init__(**lowerCamelCase_  )

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

														lowerCAmelCase__			  =      num_channels
														lowerCAmelCase__			  =      image_size
														lowerCAmelCase__			  =      depth_multiplier
														lowerCAmelCase__			  =      min_depth
														lowerCAmelCase__			  =      hidden_act
														lowerCAmelCase__			  =      tf_padding
														lowerCAmelCase__			  =      classifier_dropout_prob
														lowerCAmelCase__			  =      initializer_range
														lowerCAmelCase__			  =      layer_norm_eps




class 						a__							(				a__    ):





							'''simple docstring'''






							lowercase__     :  Optional[int]      		= version.parse("1.11"    )







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







							@property
							def     __SCREAMING_SNAKE_CASE				(						self  )			->				Mapping[str, Mapping[int, str]]:
														if self.task == "image-classification":
																					return OrderedDict([('''logits''', {0: '''batch'''})]  )
														else:
																					return OrderedDict([('''last_hidden_state''', {0: '''batch'''}), ('''pooler_output''', {0: '''batch'''})]  )







							@property
							def     __SCREAMING_SNAKE_CASE				(						self  )			->				float:
														return 1e-4





'''simple docstring'''


from math import isqrt, loga
def 						lowerCamelCase__   (				a							):
						__snake_case						 =   [True] * max_number
						for i in range(2    ,	isqrt(max_number - 1							) + 1							):
												if is_prime[i]:
																		for j in range(i**2    ,	a    ,	a							):
																								__snake_case						 =   False

						return [i for i in range(2    ,	a							) if is_prime[i]]
def 						lowerCamelCase__   (				a = 800800    ,	a = 800800							):
						__snake_case						 =   degree * loga(a							)
						__snake_case						 =   int(a							)
						__snake_case						 =   calculate_prime_numbers(a							)

						__snake_case						 =   0
						__snake_case						 =   0
						__snake_case						 =   len(a							) - 1
						while left < right:
												while (
												    prime_numbers[right] * loga(prime_numbers[left]							)
												    + prime_numbers[left] * loga(prime_numbers[right]							)
												    > upper_bound
												):
																		right -= 1
												hybrid_integers_count += right - left
												left += 1

						return hybrid_integers_count


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

