def calc_error_loss(self, curr_errs1, curr_errs2, target_errs1,
target_errs2):
err1_loss = torch.mean((curr_errs1 - target_errs1).pow(2))
err2_loss = torch.mean((curr_errs2 - target_errs2).pow(2))
soft_update(self._tau1,
curr_errs1.detach().mean(), self._target_update_coef)
soft_update(self._tau2,
curr_errs2.detach().mean(), self._target_update_coef)
return err1_loss + err2_loss
def update_target_networks(self):
soft_update(self._target_q_net, self._online_q_net,
self._target_update_coef)
def update_target_networks(self):
super().update_target_networks()
if self.discor:
soft_update(self._target_error_net, self._online_error_net,
self._target_update_coef)