def test_regularizator(self):
# make sure its the same as tensorflow
x = np.array([-1., 2., 3., 4.])
reg = 0.2
l1_reg = tf.keras.regularizers.l1(l=reg)
l2_reg = tf.keras.regularizers.l2(l=reg)
tf_x = l1_reg(tf.convert_to_tensor(x))
tf_x_2 = l2_reg(tf.convert_to_tensor(x))
astroNN_x = l1(x, l1=reg)
astroNN_x_2 = l2(x, l2=reg)
npt.assert_array_almost_equal(tf_x.eval(session=get_session()), astroNN_x)
npt.assert_array_almost_equal(tf_x_2.eval(session=get_session()), astroNN_x_2)
def test_regularizator(self):
# make sure its the same as tensorflow
x = np.array([-1., 2., 3., 4.])
reg = 0.2
astroNN_x = l1(x, l1=reg)
astroNN_x_2 = l2(x, l2=reg)
with tf.device("/cpu:0"), context.eager_mode():
l1_reg = tf.keras.regularizers.l1(l=reg)
l2_reg = tf.keras.regularizers.l2(l=reg)
tf_x = l1_reg(tf.convert_to_tensor(x))
tf_x_2 = l2_reg(tf.convert_to_tensor(x))
npt.assert_array_almost_equal(tf_x.numpy(), astroNN_x)
npt.assert_array_almost_equal(tf_x_2.numpy(), astroNN_x_2)