Training Procedure to Achieve Presented Results

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Hi,

Thank you for your great work.
In the paper you mentioned that you train for 300K/90K iterations with and without an adversarial loss, respectively, to achieve the results presented in Tables 1-3.
I assume that you first run the train.py script with --epochs 1000 and --lambda_gan 1.0. Then, you select the best model and run the same script again with --epochs 300 and --lambda_gan 0. The best model of the second run should achieve the presented results. Is that assumption correct, or did you use a different approach?