code: def forward(ctx, x, keep_prob, mask):
      ctx.keep_prob = keep_prob
      ctx.save_for_backward(mask)
      return x * mask / keep_prob
  
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 1 for calling the DeterministicDropoutFunction obj's underlying member method code with example usage: obj.forward(ctx, x, keep_prob, mask) and returns: unknown