class_docstr: Drop paths (Stochastic Depth) per sample  (when applied in main path of residual blocks).
      
code: def forward(self, x):
      return drop_path(x, self.drop_prob, self.training)
  
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 2 for calling the DropPath obj's underlying member method code with example usage: obj.forward(x) and returns: drop_path