if not args.val:
trainer = Trainer(type=args.type,
dataset=args.dataset,
split=args.split,
lr=args.lr,
diter=args.diter,
vis_screen=args.vis_screen,
save_path=args.save_path,
l1_coef=args.l1_coef,
l2_coef=args.l2_coef,
pre_trained_disc=args.pre_trained_disc,
pre_trained_gen=args.pre_trained_gen,
batch_size=args.batch_size,
num_workers=args.num_workers,
epochs=args.epochs)
if not args.inference:
trainer.train(args.cls)
else:
trainer.predict()
else:
validation = Validation(type=args.type,
dataset=args.dataset,
vis_screen=args.vis_screen,
pre_trained_gen=args.pre_trained_gen,
batch_size=args.batch_size,
num_workers=args.num_workers,
epochs=args.epochs)
validation.validate()
