02d3197407487646dc5ca6abd889b8fe5fed1aef,examples/pytorch/graphsage/train_sampling.py,,run,#Any#Any#Any#,153

Before Change

def run(args, device, data):
    // Unpack data
    train_mask, val_mask, in_feats, labels, n_classes, g = data
    train_nid = th.LongTensor(np.nonzero(train_mask)[0])
    val_nid = th.LongTensor(np.nonzero(val_mask)[0])
    train_mask = th.BoolTensor(train_mask)
    val_mask = th.BoolTensor(val_mask)

    // Create sampler
    sampler = NeighborSampler(g, [int(fanout) for fanout in args.fan_out.split(",")])

After Change

        if epoch >= 5:
            avg += toc - tic
        if epoch % args.eval_every == 0 and epoch != 0:
            eval_acc = evaluate(model, g, g.ndata["features"], g.ndata["labels"], val_nid, args.batch_size, device)
            print("Eval Acc {:.4f}".format(eval_acc))

    print("Avg epoch time: {}".format(avg / (epoch - 4)))

Instances