def test_awn_fit():
X = np.random.standard_normal((10, 2))
Z = np.random.standard_normal((10, 1))
loss = lambda target, prediction: squared(target, prediction[:, :target.shape[1]])
mlp = AwnNetwork(
2, [10], 1, ['rectifier'], 'identity', loss, max_iter=10)
mlp.fit(X, Z)
def test_awn_iter_fit():
X = np.random.standard_normal((10, 2))
Z = np.random.standard_normal((10, 1))
loss = lambda target, prediction: squared(target, prediction[:, :target.shape[1]])
mlp = AwnNetwork(
2, [10], 1, ['rectifier'], 'identity', loss, max_iter=10)
for i, info in enumerate(mlp.iter_fit(X, Z)):
if i >= 10:
break
