There are following two problems with this function:-
(1)-In the function init_params it should also get a parameter "data_loader" as when then condition ( ( (start_epoch > opt.niter_step) is encountered it will give an error. So we should also pass "data_loader" as parameter from train.py
(2)- When the condition (start_epoch > opt.niter) is encountered it will call "update_learning_rate"
which is using only "optimizer_D" so it is giving an error. So there should be two update_learning_rate each for Generator and Discriminator.
Can @tcwang0509 confirm it?
There are following two problems with this function:- (1)-In the function init_params it should also get a parameter "data_loader" as when then condition ( ( (start_epoch > opt.niter_step) is encountered it will give an error. So we should also pass "data_loader" as parameter from train.py (2)- When the condition (start_epoch > opt.niter) is encountered it will call "update_learning_rate"
which is using only "optimizer_D" so it is giving an error. So there should be two update_learning_rate each for Generator and Discriminator. Can @tcwang0509 confirm it?