a50128079d616cc25630471ad01d09537d38657d,python/ray/tune/examples/tf_distributed_keras_example.py,,,#,65

Before Change

        type=int,
        default=2,
        help="Sets number of workers for training.")
    parser.add_argument(
        "--use-gpu",
        action="store_true",
        default=False,
        help="enables CUDA training")
    parser.add_argument(
        "--cluster",
        action="store_true",
        default=False,

After Change

        options = dict(address="auto")
    else:
        options = dict(num_cpus=4)
    ray.init(**options)
    tf_trainable = DistributedTrainableCreator(
        train_mnist,
        num_workers=args.num_workers,
        num_workers_per_host=args.num_workers_per_host,

Instances