class_docstr: Drop paths (Stochastic Depth) per sample.
docstr: Args:
      drop_prob (float): Probability to apply drop path.
docstr_tok: ["Args",":","drop_prob","(","float",")",":","Probability","to","apply","drop","path","."]
code: def __init__(self, drop_prob: float = 0.0) -> None:
      """
      Args:
          drop_prob (float): Probability to apply drop path.
      """
      super(DropPath, self).__init__()
      self.drop_prob = drop_prob
  
imports: import torch
  import torch.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)