running_loss = coach.train(trainloader, epoch=epoch)
writter.add_scalar("Loss", running_loss, epoch)
evaluate(valider=valider,
trainloader=trainloader,
testloader=testloader,
acc_logger=acc_logger,
rob_logger=rob_logger,
writter=writter,
epoch=opts.epochs)
acc_logger.plotter.plot()
rob_logger.plotter.plot()
acc_logger.plotter.save(writter)
rob_logger.plotter.save(writter)
if __name__ == "__main__":
from torch.utils.tensorboard import SummaryWriter
from src.utils import mkdirs, readme
cfg = load_cfg()
mkdirs(cfg.info_path, cfg.log_path)
readme(cfg.info_path, opts)
readme(cfg.log_path, opts, mode="a")
writter = SummaryWriter(log_dir=cfg.log_path, filename_suffix=METHOD)
main(**cfg)
cfg['coach'].save(cfg.info_path)
writter.close()
# {
# "Linf": running_distance_linf[epsilon],
# "L2": running_distance_l2[epsilon],
# },
# epsilon
# )
running_accuracy = list(map(lambda x: 1. - x, running_success))
running_accuracy = ', '.join([f"{acc:.3%}" for acc in running_accuracy])
running_distance_linf = ', '.join(
[f"{dis_linf:.5f}" for dis_linf in running_distance_linf])
running_distance_l2 = ', '.join(
[f"{dis_l2:.5f}" for dis_l2 in running_distance_l2])
print(f"Accuracy: {running_accuracy}")
print(f"Distance-Linf: {running_distance_linf}")
print(f"Distance-L2: {running_distance_l2}")
if __name__ == "__main__":
from torch.utils.tensorboard import SummaryWriter
from src.utils import mkdirs, readme
cfg, log_path = load_cfg()
mkdirs(log_path)
readme(log_path, opts, mode="a")
writter = SummaryWriter(log_dir=log_path, filename_suffix=METHOD)
main(**cfg)
writter.close()