562871e76b2d5adbcd907bcf62ca28c0611e50e1,examples/pytorch/graphsage/experimental/train_dist.py,,run,#Any#Any#Any#,46

Before Change

        toc = time.time()
        print("Epoch Time(s): {:.4f}".format(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))

After Change

            start = time.time()
            eval_acc = evaluate(model.module, g, g.ndata["features"],
                                g.ndata["labels"], val_nid, args.batch_size_eval, device)
            print("Part {}, Eval Acc {:.4f}, time: {:.4f}".format(g.rank(), eval_acc, time.time() - start))

    profiler.stop()
    print(profiler.output_text(unicode=True, color=True))
    // clean up

Instances