class_docstr: Drop paths (Stochastic Depth) per sample  (when applied in main path of residual blocks).
      
code: def __init__(self, drop_prob=None):
      super(DropPath, self).__init__()
      self.drop_prob = drop_prob
  
file_path: PaddleSeg/paddleseg/models/backbones/transformer_utils.py
imports: import paddle
  import paddle.nn
  import paddle.nn.initializer
label_desc: Use image node_id 1 to create a new DropPath object from inherited base classes: nn with example: obj = DropPath(drop_prob)