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)
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()