Exemple #1
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def test_equality():
    # Test `Dense.`
    a = Dense(np.random.randn(4, 2))
    yield assert_allclose, a == a, dense(a) == dense(a)

    # Test `Diagonal`.
    d = Diagonal(np.random.randn(4))
    yield assert_allclose, d == d, B.diag(d) == B.diag(d)

    # Test `LowRank`.
    lr = LowRank(left=np.random.randn(4, 2), middle=np.random.randn(2, 2))
    yield assert_allclose, lr == lr, (lr.l == lr.l, lr.m == lr.m, lr.r == lr.r)

    # Test `Woodbury`.
    yield assert_allclose, (lr + d) == (lr + d), (lr == lr, d == d)

    # Test `Constant`.
    c1 = Constant.from_(1, a)
    c1_2 = Constant(1, 4, 3)
    c2 = Constant.from_(2, a)
    yield eq, c1, c1
    yield neq, c1, c1_2
    yield neq, c1, c2

    # Test `One`.
    one1 = One(np.float64, 4, 2)
    one2 = One(np.float64, 4, 3)
    yield eq, one1, one1
    yield neq, one1, one2

    # Test `Zero`.
    zero1 = Zero(np.float64, 4, 2)
    zero2 = Zero(np.float64, 4, 3)
    yield eq, zero1, zero1
    yield neq, zero1, zero2
Exemple #2
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def test_equality():
    # Test `Dense.`
    a = Dense(np.random.randn(4, 2))
    allclose(a == a, to_np(a) == to_np(a))

    # Test `Diagonal`.
    d = Diagonal(np.random.randn(4))
    allclose(d == d, B.diag(d) == B.diag(d))

    # Test `LowRank`.
    lr = LowRank(left=np.random.randn(4, 2), middle=np.random.randn(2, 2))
    allclose(lr == lr, (lr.l == lr.l, lr.m == lr.m, lr.r == lr.r))

    # Test `Woodbury`.
    allclose((lr + d) == (lr + d), (lr == lr, d == d))

    # Test `Constant`.
    c1 = Constant.from_(1, a)
    c1_2 = Constant(1, 4, 3)
    c2 = Constant.from_(2, a)
    assert c1 == c1
    assert c1 != c1_2
    assert c1 != c2

    # Test `One`.
    one1 = One(np.float64, 4, 2)
    one2 = One(np.float64, 4, 3)
    assert one1 == one1
    assert one1 != one2

    # Test `Zero`.
    zero1 = Zero(np.float64, 4, 2)
    zero2 = Zero(np.float64, 4, 3)
    assert zero1 == zero1
    assert zero1 != zero2
Exemple #3
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def test_constant_zero_one():
    a = np.random.randn(4, 2)
    b = Dense(a)

    yield assert_allclose, Zero.from_(a), np.zeros((4, 2))
    yield assert_allclose, Zero.from_(b), np.zeros((4, 2))

    yield assert_allclose, One.from_(a), np.ones((4, 2))
    yield assert_allclose, One.from_(b), np.ones((4, 2))

    yield assert_allclose, Constant.from_(2, a), 2 * np.ones((4, 2))
    yield assert_allclose, Constant.from_(2, b), 2 * np.ones((4, 2))
Exemple #4
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def test_constant_zero_one():
    a = np.random.randn(4, 2)
    b = Dense(a)

    allclose(Zero.from_(a), np.zeros((4, 2)))
    allclose(Zero.from_(b), np.zeros((4, 2)))

    allclose(One.from_(a), np.ones((4, 2)))
    allclose(One.from_(b), np.ones((4, 2)))

    allclose(Constant.from_(2, a), 2 * np.ones((4, 2)))
    allclose(Constant.from_(2, b), 2 * np.ones((4, 2)))
Exemple #5
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def test_arithmetic_and_shapes():
    a = Dense(np.random.randn(4, 3))
    d = Diagonal(np.array([1.0, 2.0, 3.0]), rows=4, cols=3)
    lr = LowRank(left=np.random.randn(4, 2),
                 right=np.random.randn(3, 2),
                 middle=np.random.randn(2, 2))
    zero = Zero.from_(a)
    one = One.from_(a)
    constant = Constant.from_(2.0, a)
    wb = d + lr

    # Aggregate all matrices.
    candidates = [a, d, lr, wb, constant, one, zero, 2, 1, 0]

    # Check division.
    yield assert_allclose, a.__div__(5.0), dense(a) / 5.0
    yield assert_allclose, a.__truediv__(5.0), dense(a) / 5.0

    # Check shapes.
    for m in candidates:
        yield eq, B.shape(a), (4, 3)

    # Check interactions.
    for m1, m2 in product(candidates, candidates):
        yield assert_allclose, m1 * m2, dense(m1) * dense(m2)
        yield assert_allclose, m1 + m2, dense(m1) + dense(m2)
        yield assert_allclose, m1 - m2, dense(m1) - dense(m2)
Exemple #6
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def test_arithmetic_and_shapes():
    a = Dense(np.random.randn(4, 3))
    d = Diagonal(np.array([1.0, 2.0, 3.0]), rows=4, cols=3)
    lr = LowRank(left=np.random.randn(4, 2),
                 right=np.random.randn(3, 2),
                 middle=np.random.randn(2, 2))
    zero = Zero.from_(a)
    one = One.from_(a)
    constant = Constant.from_(2.0, a)
    wb = d + lr

    # Aggregate all matrices.
    candidates = [a, d, lr, wb, constant, one, zero, 2, 1, 0, 2.0, 1.0, 0.0]

    # Check division.
    allclose(a.__div__(5.0), to_np(a) / 5.0)
    allclose(a.__rdiv__(5.0), 5.0 / to_np(a))
    allclose(a.__truediv__(5.0), to_np(a) / 5.0)
    allclose(a.__rtruediv__(5.0), 5.0 / to_np(a))
    allclose(B.divide(a, 5.0), to_np(a) / 5.0)
    allclose(B.divide(a, a), B.ones(to_np(a)))

    # Check shapes.
    for m in candidates:
        assert B.shape(a) == (4, 3)

    # Check interactions.
    for m1, m2 in product(candidates, candidates):
        allclose(m1 * m2, to_np(m1) * to_np(m2))
        allclose(m1 + m2, to_np(m1) + to_np(m2))
        allclose(m1 - m2, to_np(m1) - to_np(m2))