class_docstr: Drop paths (Stochastic Depth) per sample.
  
  Drops some samples in the forward pass with probability ``drop_prob``.
code: def __init__(
      self, drop_prob: float = 0.0, scale_by_keep: bool = True
  ):
      super(DropPath, self).__init__()
      self.drop_prob = drop_prob
      self.scale_by_keep = scale_by_keep
  
file_path: nni/nni/nas/hub/pytorch/utils/nn.py
imports: from torch import nn
label_desc: Use image node_id 1 to create a new DropPath object from inherited base classes: nn with example: obj = DropPath(drop_prob, scale_by_keep)