def test_invalid_axis(self):
if K.backend() != 'cntk':
return
from keras_ordered_neurons.cntk_backend import cumsum
with self.assertRaises(ValueError):
x = K.placeholder(shape=(1, 3, 4))
f = K.function([x], [cumsum(x, axis=1)])
def test_return_last_splits(self):
if K.backend() == 'cntk':
return
inputs = layers.Input(shape=(None,))
embed = layers.Embedding(input_dim=10, output_dim=100)(inputs)
outputs = ONLSTM(units=50, chunk_size=5, return_splits=True)(embed)
model = models.Model(inputs=inputs, outputs=outputs)
model.compile(optimizer='adam', loss='mse')
model.summary(line_length=120)
predicted = model.predict(np.random.randint(0, 10, (3, 7)))
self.assertEqual((3, 50), predicted[0].shape)
self.assertEqual((3, 2), predicted[1].shape)
def test_valid_last_axis(self):
if K.backend() != 'cntk':
return
from keras_ordered_neurons.cntk_backend import cumsum
x = K.placeholder(shape=(3, 4))
f = K.function([x], [cumsum(x, axis=-1)])
predicted = f([np.array([
[1.0, 1.0, 1.0, 1.0],
[1.0, 2.0, 3.0, 4.0],
[4.0, 3.0, 2.0, 1.0],
])])[0]
self.assertTrue(np.allclose(
np.array([
[1.0, 2.0, 3.0, 4.0],
[1.0, 3.0, 6.0, 10.0],
[4.0, 7.0, 9.0, 10.0],
]),
predicted
), predicted)