<jupyter_start><jupyter_text>def drawfunc(ax, sample):    vis.draw_dataset_sample(ax, vis.unnormalize_sample_to_numpy(sample), label=False)%matplotlib notebookvis.matplotlib_plot_iterable(ds_train, drawfunc) vis.matplotlib_plot_iterable(ds_test, drawfunc)<jupyter_code>net = models.MobilnetV1WithPointHead()
net.cuda()
%matplotlib inline
pyplot.ioff()

optimizer = optim.Adam(net.parameters(), lr=1.e-3)
scheduler = optim.lr_scheduler.MultiStepLR(optimizer, [50], gamma=0.1)

network_filename = None

n_epochs = 100

criterions = [
    train.QuatPoseLoss2(),
    train.CoordPoseLoss(),
    train.Points3dLoss(),
    train.BoxLoss(),
    train.QuaternionNormalizationRegularization(),
]
critweights = np.array([.4, .4, 0.2, 0.1, 1.e-5 ])

train.run_the_training(n_epochs,
                      optimizer,
                      net,
                      train_loader,
                      test_loader,
                      criterions,
                      critweights,
                      4,
                      join('..','model_files'),
                      network_filename,
                      other_metrics = [],
                      scheduler = scheduler)<jupyter_output><empty_output>
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