




"""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


_SCREAMING_SNAKE_CASE						 =     logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE						 =     {
    'apple/mobilevitv2-1.0': 'https://huggingface.co/apple/mobilevitv2-1.0/resolve/main/config.json',
}







class  _SCREAMING_SNAKE_CASE       (     SCREAMING_SNAKE_CASE__				):



 '''simple docstring'''





 __UpperCAmelCase		   =							"""mobilevitv2"""






 def __init__(self					,     lowerCAmelCase__=3					,     lowerCAmelCase__=2_56					,     lowerCAmelCase__=2					,     lowerCAmelCase__=2.0					,     lowerCAmelCase__="swish"					,     lowerCAmelCase__=3					,     lowerCAmelCase__=32					,     lowerCAmelCase__=0.1					,     lowerCAmelCase__=0.02					,     lowerCAmelCase__=1E-5					,     lowerCAmelCase__=5_12					,     lowerCAmelCase__=[6, 12, 18]					,     lowerCAmelCase__=0.1					,     lowerCAmelCase__=2_55					,     lowerCAmelCase__=[2, 4, 3]					,     lowerCAmelCase__=[1_28, 1_92, 2_56]					,     lowerCAmelCase__=1.0					,     lowerCAmelCase__=2					,     lowerCAmelCase__=0.0					,     lowerCAmelCase__=0.0					,     **lowerCAmelCase__					,     ):

  '''simple docstring'''







  super().__init__(**snake_case__   )

  _UpperCamelCase      :	Optional[Any]					      =  num_channels
  _UpperCamelCase      :	List[Any]					      =  image_size
  _UpperCamelCase      :	str					      =  patch_size
  _UpperCamelCase      :	Any					      =  expand_ratio
  _UpperCamelCase      :	Optional[Any]					      =  hidden_act
  _UpperCamelCase      :	Dict					      =  conv_kernel_size
  _UpperCamelCase      :	List[Any]					      =  output_stride
  _UpperCamelCase      :	int					      =  initializer_range
  _UpperCamelCase      :	Optional[Any]					      =  layer_norm_eps
  _UpperCamelCase      :	Optional[int]					      =  n_attn_blocks
  _UpperCamelCase      :	Optional[int]					      =  base_attn_unit_dims
  _UpperCamelCase      :	Optional[Any]					      =  width_multiplier
  _UpperCamelCase      :	Any					      =  ffn_multiplier
  _UpperCamelCase      :	Tuple					      =  ffn_dropout
  _UpperCamelCase      :	str					      =  attn_dropout
  _UpperCamelCase      :	Any					      =  classifier_dropout_prob

  # decode head attributes for semantic segmentation
  _UpperCamelCase      :	Optional[int]					      =  aspp_out_channels
  _UpperCamelCase      :	int					      =  atrous_rates
  _UpperCamelCase      :	str					      =  aspp_dropout_prob
  _UpperCamelCase      :	Any					      =  semantic_loss_ignore_index







class  _SCREAMING_SNAKE_CASE       (     SCREAMING_SNAKE_CASE__				):



 '''simple docstring'''





 __UpperCAmelCase		   =							version.parse("""1.11"""				)






 @property
 def lowercase_      (self   ):

  '''simple docstring'''







  return OrderedDict([("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"})]   )






 @property
 def lowercase_      (self   ):

  '''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 lowercase_      (self   ):

  '''simple docstring'''







  return 1E-4







'''simple docstring'''




import math
from collections.abc import Generator

def       __UpperCamelCase     (     _A     :					int					)     ->   Generator[int, None, None]:




	"""simple docstring"""





	lowerCAmelCase       :     Generator   				=			(i for i in range(1       , (max_n + 1)					))
	for i in (n for n in numbers if n > 1):
		for j in range(2       , _A					):
			if (i % j) == 0:
				break
		else:
			yield i

def       __UpperCamelCase     (     _A     :					int					)     ->   Generator[int, None, None]:




	"""simple docstring"""





	lowerCAmelCase       :     Generator   				=			(i for i in range(1       , (max_n + 1)					))
	for i in (n for n in numbers if n > 1):
		# only need to check for factors up to sqrt(i)
		lowerCAmelCase       :     List[str]   				=			int(math.sqrt(_A					)					) + 1
		for j in range(2       , _A					):
			if (i % j) == 0:
				break
		else:
			yield i

def       __UpperCamelCase     (     _A     :					int					)     ->   Generator[int, None, None]:




	"""simple docstring"""





	lowerCAmelCase       :     Generator   				=			(i for i in range(1       , (max_n + 1)       , 2					))
	# It's useless to test even numbers as they will not be prime
	if max_n > 2:
		yield 2  # Because 2 will not be tested, it's necessary to yield it now
	for i in (n for n in numbers if n > 1):
		lowerCAmelCase       :     int   				=			int(math.sqrt(_A					)					) + 1
		for j in range(3       , _A       , 2					):
			# As we removed the even numbers, we don't need them now
			if (i % j) == 0:
				break
		else:
			yield i

def       __UpperCamelCase     (     )     ->   Dict:




	"""simple docstring"""





	from timeit import timeit

	lowerCAmelCase       :     Tuple   				=			'from __main__ import slow_primes, primes, fast_primes'
	print(timeit('slow_primes(1_000_000_000_000)'       , setup=_A       , number=1_00_00_00					)					)
	print(timeit('primes(1_000_000_000_000)'       , setup=_A       , number=1_00_00_00					)					)
	print(timeit('fast_primes(1_000_000_000_000)'       , setup=_A       , number=1_00_00_00					)					)


if __name__ == "__main__":
				_lowerCAmelCase	:		Optional[Any]		  =						int(input('Calculate primes up to:\n>> ').strip())
				for ret in primes(number):
								print(ret)
				benchmark()
