code: 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
  
  
  a     :			int					    =						logging.get_logger(__name__)
  
  a     :			str					    =						{
      """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 				_lowercase						(    UpperCAmelCase__   ,     UpperCAmelCase__ ):
  
  
  
  
  
  
      '''simple docstring'''
      SCREAMING_SNAKE_CASE:							Union[str, Any]        =						'convnext'
  
  
  
  
      def __init__(						self					,	lowerCamelCase__=3					,	lowerCamelCase__=4					,	lowerCamelCase__=4					,	lowerCamelCase__=None					,	lowerCamelCase__=None					,	lowerCamelCase__="gelu"					,	lowerCamelCase__=0.0_2					,	lowerCamelCase__=1E-12					,	lowerCamelCase__=1E-6					,	lowerCamelCase__=0.0					,	lowerCamelCase__=224					,	lowerCamelCase__=None					,	lowerCamelCase__=None					,	**lowerCamelCase__					,	):
         super().__init__(**lowerCamelCase__   )
  
         lowerCAmelCase_:       str         =  num_channels
         lowerCAmelCase_:       Optional[int]         =  patch_size
         lowerCAmelCase_:       Dict         =  num_stages
         lowerCAmelCase_:       Optional[Any]         =  [96, 192, 384, 768] if hidden_sizes is None else hidden_sizes
         lowerCAmelCase_:       List[str]         =  [3, 3, 9, 3] if depths is None else depths
         lowerCAmelCase_:       str         =  hidden_act
         lowerCAmelCase_:       int         =  initializer_range
         lowerCAmelCase_:       Union[str, Any]         =  layer_norm_eps
         lowerCAmelCase_:       int         =  layer_scale_init_value
         lowerCAmelCase_:       Optional[int]         =  drop_path_rate
         lowerCAmelCase_:       List[str]         =  image_size
         lowerCAmelCase_:       Union[str, Any]         =  ["stem"] + [F'''stage{idx}''' for idx in range(1					,	len(self.depths   ) + 1   )]
         lowerCAmelCase_     ,  lowerCAmelCase_:       str         =  get_aligned_output_features_output_indices(
             out_features=lowerCamelCase__					,	out_indices=lowerCamelCase__					,	stage_names=self.stage_names   )
  
  
  
  
  
  class 				_lowercase						(    UpperCAmelCase__ ):
  
  
  
  
  
  
      '''simple docstring'''
      SCREAMING_SNAKE_CASE:							int        =						version.parse('1.11' )
  
  
  
  
      @property
      def     _a						(						self   ):
         return OrderedDict(
             [
                 ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
             ]   )
  
  
  
  
      @property
      def     _a						(						self   ):
         return 1E-5
style_context: import itertools
  def 		snake_case__  (		lowercase				):
     return (
         int("".join(combination[0:2]				)				) * int("".join(combination[2:5]				)				)
         == int("".join(combination[5:9]				)				)
     ) or (
         int("".join(combination[0]				)				) * int("".join(combination[1:5]				)				)
         == int("".join(combination[5:9]				)				)
     )
  def 		snake_case__  (		):
     return sum(
         {
             int("".join(pandigital[5:9]				)				)
             for pandigital in itertools.permutations("123456789"				)
             if is_combination_valid(lowercase				)
         }				)
  
  
  if __name__ == "__main__":
   print(solution())