if not torch.cuda.is_available():
util.print_log(colored("Error: CUDA not available", "red"))
quit()
torch.cuda.manual_seed(opt.seed)
After Change
parser.add_argument("--batchSize", help="training batch size", default=128)
parser.add_argument("--validSize", help="validation set size", default=256)
parser.add_argument("--oneHotDim", help="dimension for one-hot encodings", default=64)
parser.add_argument("--noStandardize", help="do not standardize observations", action="store_true")
parser.add_argument("--resume", help="resume training of the latest artifact", action="store_true")
opt = parser.parse_args()
if opt.version:
