def test_categorical_cross_entropy_pytorch(self):
"""Test CategoricalCrossEntropy."""
loss = losses.CategoricalCrossEntropy()
outputs = torch.tensor([[0.2, 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 = [-np.log(0.8), -np.log(0.4)]
assert np.allclose(expected, result)
def test_categorical_cross_entropy_tf(self):
"""Test CategoricalCrossEntropy."""
loss = losses.CategoricalCrossEntropy()
outputs = tf.constant([[0.2, 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 = [-np.log(0.8), -np.log(0.4)]
assert np.allclose(expected, result)
