






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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


__UpperCAmelCase      =				logging.get_logger(__name__)

__UpperCAmelCase      =				{
    "facebook/convnext-tiny-224": "https://huggingface.co/facebook/convnext-tiny-224/resolve/main/config.json",
    # See all ConvNeXT models at https://huggingface.co/models?filter=convnext
}
class 	a_(		lowercase__			,							lowercase__	):



     """simple docstring"""



     __snake_case		:				str  					='''convnext'''





     def __init__(		self					:	List[str]  ,  lowerCAmelCase__					:	List[Any]=3  ,  lowerCAmelCase__					:	Any=4  ,  lowerCAmelCase__					:	int=4  ,  lowerCAmelCase__					:	Tuple=None  ,  lowerCAmelCase__					:	List[str]=None  ,  lowerCAmelCase__					:	int="gelu"  ,  lowerCAmelCase__					:	List[str]=0.02  ,  lowerCAmelCase__					:	Optional[int]=1e-12  ,  lowerCAmelCase__					:	List[str]=1e-6  ,  lowerCAmelCase__					:	List[Any]=0.0  ,  lowerCAmelCase__					:	Optional[int]=2_2_4  ,  lowerCAmelCase__					:	int=None  ,  lowerCAmelCase__					:	List[Any]=None  ,  **lowerCAmelCase__					:	Union[str, Any]  ,  )							->	Union[str, Any]:

      """simple docstring"""
      super().__init__(**lowerCAmelCase__)

      SCREAMING_SNAKE_CASE				    =		num_channels
      SCREAMING_SNAKE_CASE				    =		patch_size
      SCREAMING_SNAKE_CASE				    =		num_stages
      SCREAMING_SNAKE_CASE				    =		[9_6, 1_9_2, 3_8_4, 7_6_8] if hidden_sizes is None else hidden_sizes
      SCREAMING_SNAKE_CASE				    =		[3, 3, 9, 3] if depths is None else depths
      SCREAMING_SNAKE_CASE				    =		hidden_act
      SCREAMING_SNAKE_CASE				    =		initializer_range
      SCREAMING_SNAKE_CASE				    =		layer_norm_eps
      SCREAMING_SNAKE_CASE				    =		layer_scale_init_value
      SCREAMING_SNAKE_CASE				    =		drop_path_rate
      SCREAMING_SNAKE_CASE				    =		image_size
      SCREAMING_SNAKE_CASE				    =		['stem'] + [f'''stage{idx}''' for idx in range(1  ,  len(self.depths) + 1)]
      SCREAMING_SNAKE_CASE    ,   SCREAMING_SNAKE_CASE				    =		get_aligned_output_features_output_indices(
          out_features=lowerCAmelCase__  ,  out_indices=lowerCAmelCase__  ,  stage_names=self.stage_names)

class 	a_(		lowercase__	):



     """simple docstring"""



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





     @property
     def     __UpperCamelCase						(		self					:	Union[str, Any])							->	Mapping[str, Mapping[int, str]]:

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





     @property
     def     __UpperCamelCase						(		self					:	Dict)							->	float:

      """simple docstring"""
      return 1e-5












"""simple docstring"""


_UpperCamelCase							:       str       					=		10**8




def      snake_case    (A_ :int ):







  '''simple docstring'''

  if n % 1_0 == 0:
    return False
  a	:     Optional[int]							=  str(A_ )
  return s == s[::-1]




def      snake_case    ():







  '''simple docstring'''

  a	:     Tuple							=  set()
  a	:     Optional[Any]							=  1
  a	:     List[str]							=  5
  while sum_squares < LIMIT:
    a	:     int							=  first_square + 1
    while sum_squares < LIMIT:
      if is_palindrome(A_ ):
        answer.add(A_ )
      last_square += 1
      sum_squares += last_square**2
    first_square += 1
    a	:     List[str]							=  first_square**2 + (first_square + 1) ** 2

  return sum(A_ )


if __name__ == "__main__":
   print(solution())




