I found a solution: Updating the Module._parameters dictionary directly:
# Inner optimization
for k in range(n_inner_opt):
      true_objective2 = game_NN.true_objective(net2_, net1)
      grad2 = torch.autograd.grad(true_objective2, net2_.parameters(), create_graph=True)
      'In the following lines, I needed to update the ._parameters dictionary while not using with.no_grad()'
      for i, (layer_name, layer) in enumerate(net2_._parameters.items()):
            layer = layer - hp.lr_in * grad2[i]
            net2_._parameters[layer_name] = layer