def test_distribute2(v):
return distribute(v, (3, 7))
def test_distribute4(x):
return distribute(x, (2, 3))
def test_distribute(v, shp):
return distribute(v, shp)
def test_distribute(x):
return distribute(scalar_to_array(x), (2, 3))
def test_distribute2(x):
return distribute(scalar_to_array(x), (1, ))
def after(xs):
return distribute(scalar_to_array(3, arr_t), shape(xs))
def up1(x2):
return array_map(
scalar_add, x2,
distribute(scalar_to_array(1, typeof(x)), shape(x)))
def before(x):
return distribute(x, (3, 5))
def test_prim_distribute():
assert (distribute(1, (2, 3)) == np.ones((2, 3))).all()
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)
