def test_elu():
    from keras.layers.advanced_activations import ELU
    np.random.seed(1337)
    inp = get_standard_values()
    for alpha in [0.1, .5, -1., 1.]:
        layer = ELU(alpha=alpha)
        layer.input = K.variable(inp)
        for train in [True, False]:
            outp = K.eval(layer.get_output(train))
            assert_allclose(outp, inp, rtol=1e-3)

        layer.input = K.variable(-inp)
        for train in [True, False]:
            outp = K.eval(layer.get_output(train))
            assert_allclose(outp, alpha*(np.exp(-inp)-1.), rtol=1e-3)

        config = layer.get_config()
        assert config['alpha'] == alpha
Exemple #2
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def test_elu():
    from keras.layers.advanced_activations import ELU
    np.random.seed(1337)
    inp = get_standard_values()
    for alpha in [0.1, .5, -1., 1.]:
        layer = ELU(alpha=alpha)
        layer.input = K.variable(inp)
        for train in [True, False]:
            outp = K.eval(layer.get_output(train))
            assert_allclose(outp, inp, rtol=1e-3)

        layer.input = K.variable(-inp)
        for train in [True, False]:
            outp = K.eval(layer.get_output(train))
            assert_allclose(outp, alpha * (np.exp(-inp) - 1.), rtol=1e-3)

        config = layer.get_config()
        assert config['alpha'] == alpha