


'''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


a_       :     Dict 							=     logging.get_logger(__name__)

a_       :     int 							=     {
    "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  (  _SCREAMING_SNAKE_CASE	,					_SCREAMING_SNAKE_CASE							):
 _lowerCAmelCase			       =						"""convnext"""
 def __init__(			self   ,					__magic_name__=3   ,					__magic_name__=4   ,					__magic_name__=4   ,					__magic_name__=None   ,					__magic_name__=None   ,					__magic_name__="gelu"   ,					__magic_name__=0.0_2   ,					__magic_name__=1e-12   ,					__magic_name__=1e-6   ,					__magic_name__=0.0   ,					__magic_name__=2_24   ,					__magic_name__=None   ,					__magic_name__=None   ,					**__magic_name__   ,					)       ->				Tuple:
      super().__init__(**__magic_name__    )

      _a         =				num_channels
      _a         =				patch_size
      _a         =				num_stages
      _a         =				[96, 1_92, 3_84, 7_68] if hidden_sizes is None else hidden_sizes
      _a         =				[3, 3, 9, 3] if depths is None else depths
      _a         =				hidden_act
      _a         =				initializer_range
      _a         =				layer_norm_eps
      _a         =				layer_scale_init_value
      _a         =				drop_path_rate
      _a         =				image_size
      _a         =				['stem'] + [f'stage{idx}' for idx in range(1   ,					len(self.depths    ) + 1    )]
      _a   , _a         =				get_aligned_output_features_output_indices(
          out_features=__magic_name__   ,					out_indices=__magic_name__   ,					stage_names=self.stage_names    )





class 			a  (  _SCREAMING_SNAKE_CASE							):
 _lowerCAmelCase			       =						version.parse("""1.11"""							)
 @property
 def 				__UpperCAmelCase		(			self    )       ->				Mapping[str, Mapping[int, str]]:
      return OrderedDict(
          [
              ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
          ]    )




 @property
 def 				__UpperCAmelCase		(			self    )       ->				float:
      return 1e-5





'''simple docstring'''






import os






def 						_A					() ->	int:




     '''simple docstring'''



     _a         =				os.path.dirname(os.path.realpath(lowerCAmelCase__		)		)
     _a         =				os.path.join(lowerCAmelCase__					,    'triangle.txt'		)

     with open(lowerCAmelCase__		) as in_file:
          _a         =				[[int(lowerCAmelCase__		) for i in line.split()] for line in in_file]

     while len(lowerCAmelCase__		) != 1:
          _a         =				triangle.pop()
          _a         =				triangle[-1]
          for j in range(len(lowerCAmelCase__		) - 1		):
               curr_row[j] += max(last_row[j]					,    last_row[j + 1]		)
     return triangle[0][0]


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

