  
          for epoch in range(1000000):
              warped_A, target_A = get_training_data(images_A, BATCH_SIZE)
              warped_B, target_B = get_training_data(images_B, BATCH_SIZE)
  
              loss_A = autoencoder_A.train_on_batch(warped_A, target_A)
              loss_B = autoencoder_B.train_on_batch(warped_B, target_B)
 
</s> remove             if epoch % 100 == 0:
 </s> add             if epoch % self.arguments.save_interval == 0: </s> remove         else:
 </s> add         if not self.arguments.preview or self.arguments.write_image:
            if self.arguments.verbose:
                print("Iteration number {}".format(epoch + 1))
                start_time = time.time()
  
          for epoch in range(1000000):
            if self.arguments.verbose:
                print("Iteration number {}".format(epoch + 1))
                start_time = time.time()
              warped_A, target_A = get_training_data(images_A, BATCH_SIZE)
              warped_B, target_B = get_training_data(images_B, BATCH_SIZE)
  
              loss_A = autoencoder_A.train_on_batch(warped_A, target_A)
              loss_B = autoencoder_B.train_on_batch(warped_B, target_B)
keep add keep keep keep keep keep
 Improvement of the train action usability. (#37)

* Improvement of the train action usability.

* Prints the current iteration number in verbose mode.
* The number of iterations before saving the data can be changed by a command line optin.

* Added option to write training result to file even when in preview.

* Prints time elapsed for each iteration in verbose mode when training. 
lib/cli.py