def test_Vector_ndarray():
v = Vector([[1, 2, 3], [4, 5, 6]])
n = np.array([[1, 4], [2, 5], [3, 6]])
assert matmul(v, n) == Vector([[14, 32], [32, 27]])
v = Vector([1, 4])
n = np.array([1, 4])
assert matmul(v, n) == np.array([17])
def test_ndarray_Tensor():
n = np.array([[1, 2, 3], [4, 5, 6]])
t = Tensor([[1, 4], [2, 5], [3, 6]])
assert matmul(n, t) == Tensor([[14, 32], [32, 27]])
def test_Tensor_ndarray():
t = Tensor([[1, 4], [2, 5], [3, 6]])
n = np.array([[1, 2, 3], [4, 5, 6]])
assert matmul(t, n) == Tensor([[17, 22, 27], [22, 29, 36], [27, 36, 45]])
def test_Vector_Vector():
v1 = Vector([[1, 2, 3], [4, 5, 6]])
v2 = Vector([[1, 4], [2, 5], [3, 6]])
assert matmul(v1, v2) == Vector([[14, 32], [32, 27]])
def test_Tensor_Tensor():
t1 = Tensor([[1, 4], [2, 5], [3, 6]])
t2 = Tensor([[1, 2, 3], [4, 5, 6]])
assert matmul(t1, t2) == Tensor([[17, 22, 27], [22, 29, 36], [27, 36, 45]])
def test_Matrix_Matrix():
m1 = Matrix([[1, 4], [2, 5], [3, 6]])
m2 = Matrix([[1, 2, 3], [4, 5, 6]])
assert matmul(m1, m2) == Matrix([[17, 22, 27], [22, 29, 36], [27, 36, 45]])
def test_Vector_Matrix():
v = Vector([[1, 4], [2, 5], [3, 6]])
m = Matrix([[1, 2, 3], [4, 5, 6]])
assert matmul(v, m) == Vector([[17, 22, 27], [22, 29, 36], [27, 36, 45]])
def test_Matrix_Vector():
m = Matrix([[1, 2, 3], [4, 5, 6]])
v = Vector([[1, 4], [2, 5], [3, 6]])
assert matmul(m, v) == Vector([[14, 32], [32, 27]])
def __matmul__(self, t):
return matmul(self, t)
def __rmatmaul__(self, t):
return matmul(t, self)
def _(x, y):
return x.fmap(lambda _: matmul(_, y.unbox()))
def _(x, y):
return y.fmap(lambda _: matmul(x, _))
def _(x, y):
return x.fmap(lambda _: matmul(_, y))
def _(x, y):
return y.fmap(lambda _: matmul(x.unbox(), _))
def _(x, y):
if y.ndim <= 1:
return x.unbox() @ y
return x.fmap(lambda _: matmul(_, y))