"""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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


lowercase__   			=      logging.get_logger(__name__)

lowercase__   			=      {
    '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   __snake_case			(	__lowerCAmelCase			, __lowerCAmelCase							):
      a__								=						"""convnext"""



      def __init__(		self       ,     lowercase=3       ,     lowercase=4       ,     lowercase=4       ,     lowercase=None       ,     lowercase=None       ,     lowercase="gelu"       ,     lowercase=0.02       ,     lowercase=1e-12       ,     lowercase=1e-6       ,     lowercase=0.0       ,     lowercase=2_24       ,     lowercase=None       ,     lowercase=None       ,     **lowercase       ,     )      ->     Any:





        '''simple docstring'''





        super().__init__(**lowercase)

        a__:	List[str]     				=      num_channels
        a__:	Tuple     				=      patch_size
        a__:	str     				=      num_stages
        a__:	Any     				=      [96, 1_92, 3_84, 7_68] if hidden_sizes is None else hidden_sizes
        a__:	Any     				=      [3, 3, 9, 3] if depths is None else depths
        a__:	List[Any]     				=      hidden_act
        a__:	Dict     				=      initializer_range
        a__:	int     				=      layer_norm_eps
        a__:	Optional[int]     				=      layer_scale_init_value
        a__:	Optional[int]     				=      drop_path_rate
        a__:	Union[str, Any]     				=      image_size
        a__:	List[Any]     				=      ['stem'] + [f'stage{idx}' for idx in range(1       ,     len(self.depths) + 1)]
        a__				,       a__:	Optional[int]     				=      get_aligned_output_features_output_indices(
            out_features=lowercase       ,     out_indices=lowercase       ,     stage_names=self.stage_names)







class   __snake_case			(	__lowerCAmelCase							):
      a__								=						version.parse("""1.11"""							)



      @property
      def     lowerCamelCase_  (		self)      ->     Mapping[str, Mapping[int, str]]:





        '''simple docstring'''





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



      @property
      def     lowerCamelCase_  (		self)      ->     float:





        '''simple docstring'''





        return 1e-5





import os







def      snake_case__							(  ):





     """simple docstring"""







     SCREAMING_SNAKE_CASE 		=os.path.dirname(os.path.realpath(lowerCAmelCase_     )     )
     SCREAMING_SNAKE_CASE 		=os.path.join(lowerCAmelCase_,       'triangle.txt'     )

     with open(lowerCAmelCase_     ) as f:
          SCREAMING_SNAKE_CASE 		=f.readlines()

     SCREAMING_SNAKE_CASE 		=[[int(lowerCAmelCase_     ) for y in x.rstrip('\r\n'     ).split(' '     )] for x in triangle]

     for i in range(1,       len(lowerCAmelCase_     )     ):
          for j in range(len(a[i]     )     ):
               SCREAMING_SNAKE_CASE 		=a[i - 1][j] if j != len(a[i - 1]     ) else 0
               SCREAMING_SNAKE_CASE 		=a[i - 1][j - 1] if j > 0 else 0
               a[i][j] += max(lowerCAmelCase_,       lowerCAmelCase_     )
     return max(a[-1]     )


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

