code: def backward(ctx, grad_output):
      return (
          ctx.saved_tensors[0] * grad_output / ctx.keep_prob,
          None,
          None,
      )
  
file_path: hivemind/hivemind/moe/server/layers/dropout.py
imports: import torch.autograd
  from torch import nn
  from hivemind.moe.server.layers.custom_experts import register_expert_class
label_desc: Use image node_id 2 for calling the DeterministicDropoutFunction obj's underlying member method code with example usage: obj.backward(ctx, grad_output) and returns: unknown,  None,  None