def test_repeat(self):
"""Test that Repeat can be invoked."""
in_dim = 4
batch_size = 10
n_repeat = 2
in_tensor = np.random.rand(batch_size, in_dim)
with self.session() as sess:
in_tensor = tf.convert_to_tensor(in_tensor, dtype=tf.float32)
out_tensor = Repeat(n_repeat)(in_tensor)
out_tensor = out_tensor.eval()
assert out_tensor.shape == (batch_size, n_repeat, in_dim)
def test_repeat(self):
"""Test that Repeat can be invoked."""
in_dim = 4
batch_size = 10
n_repeat = 2
in_tensor = np.random.rand(batch_size, in_dim)
with self.session() as sess:
in_tensor = tf.convert_to_tensor(in_tensor, dtype=tf.float32)
out_tensor = Repeat(n_repeat)(in_tensor)
out_tensor = out_tensor.eval()
assert out_tensor.shape == (batch_size, n_repeat, in_dim)
def test_Repeat_pickle(): tg = TensorGraph() feature = Feature(shape=(tg.batch_size, 1)) layer = Repeat(n_times=10, in_layers=feature) tg.add_output(layer) tg.set_loss(layer) tg.build() tg.save()
