413099073a8659ac741c695f93b0b564b3188183,examples/classification/train_imagenet_multi.py,,main,#,66

Before Change

        val_data = TransformDataset(val_data, ValTransform(extractor.mean))
        print("finished loading dataset")
    else:
        train_data, val_data = None, None
    train_data = chainermn.scatter_dataset(train_data, comm, shuffle=True)
    val_data = chainermn.scatter_dataset(val_data, comm, shuffle=True)
    train_iter = chainer.iterators.MultiprocessIterator(

After Change

    print("finished loading dataset")

    if comm.rank == 0:
        train_indices = np.arange(len(train_data))
        val_indices = np.arange(len(val_data))
    else:
        train_indices = None
        val_indices = None

    train_indices = chainermn.scatter_dataset(
        train_indices, comm, shuffle=True)
    val_indices = chainermn.scatter_dataset(val_indices, comm, shuffle=True)
    train_data = train_data.slice[train_indices]
    val_data = val_data.slice[val_indices]
    train_iter = chainer.iterators.MultiprocessIterator(
        train_data, args.batchsize, n_processes=args.loaderjob)
    val_iter = iterators.MultiprocessIterator(

Instances