code: def forward(self, x, mask):
      x = self.linear_in(self.dropout(x, mask))
      return self.linear_out(self.activation(x))
  
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 DeterministicDropoutNetwork obj's underlying member method code with example usage: obj.forward(x, mask) and returns: self