class_docstr: Drop paths (Stochastic Depth) per sample.
  
  Drops some samples in the forward pass with probability ``drop_prob``.
code: def forward(self, x):
      return drop_path(
          x, self.drop_prob, self.training, self.scale_by_keep
      )
  
file_path: nni/nni/nas/hub/pytorch/utils/nn.py
imports: from torch import nn
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