snapshot...

modules/deeplearning/srcnn_l1b_l2.py

@@ -416,10 +416,10 @@ class SRCNN:
         self.loss = tf.keras.losses.MeanSquaredError()  # Regression
 
         # decayed_learning_rate = learning_rate * decay_rate ^ (global_step / decay_steps)
-        initial_learning_rate = 0.002
+        initial_learning_rate = 0.001
         decay_rate = 0.95
         steps_per_epoch = int(self.num_data_samples/BATCH_SIZE)  # one epoch
-        decay_steps = int(steps_per_epoch / 2)
+        decay_steps = int(steps_per_epoch)
         print('initial rate, decay rate, steps/epoch, decay steps: ', initial_learning_rate, decay_rate, steps_per_epoch, decay_steps)
 
         self.learningRateSchedule = tf.keras.optimizers.schedules.ExponentialDecay(initial_learning_rate, decay_steps, decay_rate)