def test_scalar_to_array():
a = scalar_to_array(1)
assert isinstance(a, np.ndarray)
assert a.dtype == np.int64
b = scalar_to_array(1.5)
assert isinstance(b, np.ndarray)
assert b.dtype == np.float64
def test_scalar_to_array(x):
return scalar_to_array(x)
def test_distribute2(x):
return distribute(scalar_to_array(x), (1, ))
def test_distribute(x):
return distribute(scalar_to_array(x), (2, 3))
def up1(x2):
return array_map(
scalar_add, x2,
distribute(scalar_to_array(1, typeof(x)), shape(x)))
def after(xs):
return distribute(scalar_to_array(3, arr_t), shape(xs))
def up1(x):
return array_map(scalar_add, x,
distribute(scalar_to_array(1), (2, 3)))
def after(xs):
return distribute(scalar_to_array(3), (3, 5))
def test_array_operations_distribute(x, y):
xs = distribute(scalar_to_array(x), (4, 3))
ys = distribute(scalar_to_array(y), (4, 3))
div = array_map(scalar_div, xs, ys)
sm = array_reduce(scalar_add, div, ())
return array_to_scalar(sm)
