diff --git a/modules/deeplearning/cloud_fraction_fcn_abi.py b/modules/deeplearning/cloud_fraction_fcn_abi.py
index 9046bd584ffcaf3aeab6798da1c033665239c6f0..3f86ac83a2dcb1ea1aa511398595a0f293aa8e94 100644
--- a/modules/deeplearning/cloud_fraction_fcn_abi.py
+++ b/modules/deeplearning/cloud_fraction_fcn_abi.py
@@ -604,7 +604,7 @@ class SRCNN:
 
         step = 0
         total_time = 0
-        best_test_loss = np.finfo(dtype=np.float).max
+        best_test_loss = np.finfo(dtype=np.float64).max
 
         if EARLY_STOP:
             es = EarlyStop()
@@ -629,7 +629,7 @@ class SRCNN:
 
                         with self.writer_train.as_default():
                             tf.summary.scalar('loss_trn', loss.numpy(), step=step)
-                            tf.summary.scalar('learning_rate', self.optimizer._decayed_lr('float32').numpy(), step=step)
+                            tf.summary.scalar('learning_rate', self.optimizer.lr.numpy(), step=step)
                             tf.summary.scalar('num_train_steps', step, step=step)
                             tf.summary.scalar('num_epochs', epoch, step=step)
 
@@ -649,7 +649,7 @@ class SRCNN:
                             tf.summary.scalar('loss_val', self.test_loss.result(), step=step)
 
                         print('****** test loss, acc, lr: ', self.test_loss.result().numpy(), self.test_accuracy.result().numpy(),
-                              self.optimizer._decayed_lr('float32').numpy())
+                              self.optimizer.lr.numpy())
 
                     step += 1
                     print('train loss: ', loss.numpy())