class_docstr: Stochastic depth module.
  
  See :func:`stochastic_depth`.
code: def __repr__(self) -> str:
      tmpstr = self.__class__.__name__ + "("
      tmpstr += "p=" + str(self.p)
      tmpstr += ", mode=" + str(self.mode)
      tmpstr += ")"
      return tmpstr
  
imports: import math
  from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  from einops import rearrange
  from opt_einsum import contract
label_desc: Use image node_id 3 for calling the StochasticDepth obj's underlying member method code with example usage: obj.__repr__() and returns: tmpstr