Function np_softmax

imperative/python/test/unit/functional/test_functional.py:1694–1695

(x)

@pytest.mark.skip(reason="pytest aborted")
def test_softmax():
    def np_softmax(x):
        return np.exp(x) / np.sum(np.exp(x), axis=1, keepdims=True)

    data = (np.random.random(size=(1, 16, 224, 224)).astype(np.float32) - 0.5) * 100
    desired = np_softmax(data[:, :3, 0, 0])