RuntimeError: Only Tensors created explicitly by the user (graph leaves) support the deepcopy protocol at the moment when deepcopying a model

I am trying to deepcopy a model:

class Model(torch.nn.Module):
    def __init__(self, ann_private, rnn_public, policy):
        super(Model, self).__init__()
        self.ann_private = ann_private
        self.rnn_public = rnn_public
        self.policy = policy

    def forward(self, private_input, state):
      private_input = self.ann_private(private_input)
      processed_state = self.rnn_public(state)
      self.inference_state = torch.cat([processed_state, private_input], dim=-1)

      mu, sigma, state_values =  self.policy(self.inference_state)
      return mu, sigma, state_values

where the policy contains some ‘self.mu’, ‘self.sigma’ etc (which are as I suppose causes of this problem, as before I was just calling them mu, sigma and deepcopy was working, but now I explicitly need self for them).
Any solution?