+ if need_to_train or args.test_loaded_models:
+
+ t = time.time()
+
+ if args.compress_vignettes:
+ test_set = CompressedVignetteSet(problem_number,
+ args.nb_test_batches, args.batch_size,
+ cuda=torch.cuda.is_available())
+ else:
+ test_set = VignetteSet(problem_number,
+ args.nb_test_batches, args.batch_size,
+ cuda=torch.cuda.is_available())
+
+ log_string('data_generation {:0.2f} samples / s'.format(test_set.nb_samples / (time.time() - t)))
+