def test_l1_loss_pytorch(self):
"""Test L1Loss."""
loss = losses.L1Loss()
outputs = torch.tensor([[0.1, 0.8], [0.4, 0.6]])
labels = torch.tensor([[0.0, 1.0], [1.0, 0.0]])
result = loss._create_pytorch_loss()(outputs, labels).numpy()
expected = [[0.1, 0.2], [0.6, 0.6]]
assert np.allclose(expected, result)
def test_l1_loss_tf(self):
"""Test L1Loss."""
loss = losses.L1Loss()
outputs = tf.constant([[0.1, 0.8], [0.4, 0.6]])
labels = tf.constant([[0.0, 1.0], [1.0, 0.0]])
result = loss._compute_tf_loss(outputs, labels).numpy()
expected = [[0.1, 0.2], [0.6, 0.6]]
assert np.allclose(expected, result)
