Esempio n. 1
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    def test_numpy_compare(self):
        rng = np.random.RandomState(utt.fetch_seed())

        M = tensor.matrix("A", dtype=theano.config.floatX)
        V = tensor.vector("V", dtype=theano.config.floatX)

        a = rng.rand(4, 4).astype(theano.config.floatX)
        b = rng.rand(4).astype(theano.config.floatX)

        A = (   [None, 'fro', 'inf', '-inf', 1, -1, None, 'inf', '-inf', 0, 1, -1, 2, -2],
                [M, M, M, M, M, M, V, V, V, V, V, V, V, V],
                [a, a, a, a, a, a, b, b, b, b, b, b, b, b],
                [None, 'fro', inf, -inf, 1, -1, None, inf, -inf, 0, 1, -1, 2, -2])

        for i in range(0, 14):
            f = function([A[1][i]], norm(A[1][i], A[0][i]))
            t_n = f(A[2][i])
            n_n = np.linalg.norm(A[2][i], A[3][i])
            assert _allclose(n_n, t_n)
Esempio n. 2
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 def test_tensor_input(self):
     with pytest.raises(NotImplementedError):
         norm(np.random.rand(3, 4, 5), None)
Esempio n. 3
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 def test_wrong_type_of_ord_for_matrix(self):
     with pytest.raises(ValueError):
         norm([[2, 1], [3, 4]], 0)
Esempio n. 4
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 def test_non_tensorial_input(self):
     with pytest.raises(ValueError):
         norm(3, None)
Esempio n. 5
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 def test_wrong_type_of_ord_for_vector(self):
     with pytest.raises(ValueError):
         norm([2, 1], "fro")