targets, input = degrade_input(
input, mask_generate, rho / nb_iterations, (rho + 1) / nb_iterations
)
+
input_with_mask = NTC_channel_cat(input, mask_generate, rho)
output = model(input_with_mask)
loss = NTC_masked_cross_entropy(output, targets, mask_loss)
f"test_accuracy {n_epoch} model AE setup {ns} {nb_correct} / {nb_total} ({(nb_correct*100)/nb_total:.02f}%)"
)
- filename = f"prediction_ae_{n_epoch:04d}_structure_{ns}.png"
+ filename = f"prediction_ae_{n_epoch:04d}_{ns}.png"
quiz_machine.problem.save_quizzes_as_image(
args.result_dir,
correct_parts=correct_parts,
)
- log_string(f"wrote {filename}")
+ log_string(f"wrote {filename}")
if args.test == "ae":