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()