info("Phase: {}".format(Phase.TEST))
info("Checkpoint: {}".format(osp.basename(args.checkpoint)))
pprint(checkpoint["params"])
model.eval()
if torch.cuda.is_available():
After Change
data_loader = DataLoader(dataset, batch_size=1)
mean = params["train"]["dataset"]["mean"]
stddev = params["train"]["dataset"]["stddev"]
if not osp.isdir(args.output_dir):
os.makedirs(args.output_dir)