(self, lr_policy, loss)
| 135 | return decayed_lr |
| 136 | |
| 137 | def adam_optimizer(self, lr_policy, loss): |
| 138 | decayed_lr = self.get_lr(lr_policy) |
| 139 | optimizer = fluid.optimizer.Adam( |
| 140 | learning_rate=decayed_lr, |
| 141 | beta1=self.momentum, |
| 142 | beta2=self.momentum2, |
| 143 | regularization=fluid.regularizer.L2Decay( |
| 144 | regularization_coeff=self.weight_decay), |
| 145 | ) |
| 146 | optimizer.minimize(loss) |
| 147 | return decayed_lr |
| 148 | |
| 149 | def optimise(self, loss): |
| 150 | lr_policy = cfg.SOLVER.LR_POLICY |