Exemple #1
0
def test_grbm_reload():
    vis_layer = layers.BernoulliLayer(num_vis, center=True)
    hid_layer = layers.GaussianLayer(num_hid, center=True)

    # create some extrinsics
    grbm = BoltzmannMachine([vis_layer, hid_layer])
    data = batch.Batch({
        'train':
        batch.InMemoryTable(be.randn((10 * num_samples, num_vis)), num_samples)
    })
    grbm.initialize(data)
    with tempfile.NamedTemporaryFile() as file:
        # save the model
        store = pandas.HDFStore(file.name, mode='w')
        grbm.save(store)
        store.close()
        # reload
        store = pandas.HDFStore(file.name, mode='r')
        grbm_reload = BoltzmannMachine.from_saved(store)
        store.close()
    # check the two models are consistent
    vis_data = vis_layer.random((num_samples, num_vis))
    data_state = State.from_visible(vis_data, grbm)
    vis_orig = grbm.deterministic_iteration(1, data_state)[0]
    vis_reload = grbm_reload.deterministic_iteration(1, data_state)[0]
    assert be.allclose(vis_orig, vis_reload)
    assert be.allclose(grbm.layers[0].moments.mean,
                       grbm_reload.layers[0].moments.mean)
    assert be.allclose(grbm.layers[0].moments.var,
                       grbm_reload.layers[0].moments.var)
    assert be.allclose(grbm.layers[1].moments.mean,
                       grbm_reload.layers[1].moments.mean)
    assert be.allclose(grbm.layers[1].moments.var,
                       grbm_reload.layers[1].moments.var)
Exemple #2
0
def test_grbm_save():
    vis_layer = layers.BernoulliLayer(num_vis, center=True)
    hid_layer = layers.GaussianLayer(num_hid, center=True)
    grbm = BoltzmannMachine([vis_layer, hid_layer])
    data = batch.Batch({
        'train':
        batch.InMemoryTable(be.randn((10 * num_samples, num_vis)), num_samples)
    })
    grbm.initialize(data)
    with tempfile.NamedTemporaryFile() as file:
        store = pandas.HDFStore(file.name, mode='w')
        grbm.save(store)
        store.close()