def test_ShannonEntropy_pytorch(self):
"""."""
loss = losses.ShannonEntropy()
inputs = torch.tensor([[0.7, 0.3], [0.9, 0.1]])
result = loss._create_pytorch_loss()(inputs).numpy()
expected = [
-np.mean([0.7 * np.log(0.7), 0.3 * np.log(0.3)]),
-np.mean([0.9 * np.log(0.9), 0.1 * np.log(0.1)])
]
assert np.allclose(expected, result)
def test_ShannonEntropy_tf(self):
"""."""
loss = losses.ShannonEntropy()
inputs = tf.constant([[0.7, 0.3], [0.9, 0.1]])
result = loss._compute_tf_loss(inputs).numpy()
expected = [
-np.mean([0.7 * np.log(0.7), 0.3 * np.log(0.3)]),
-np.mean([0.9 * np.log(0.9), 0.1 * np.log(0.1)])
]
assert np.allclose(expected, result)
