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BUG: Fix delegation behaivour with atleast_3d. #514

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BUG: Fix delegation behaivour with atleast_3d. #514

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664f853
fix bad delegation behaviour with atleast_3d and improve atleast_nd u…
Enderdead Nov 6, 2025
6ba1c51
reduce atleast_test verbosity.
Enderdead Nov 9, 2025
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2 changes: 1 addition & 1 deletion src/array_api_extra/_delegation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -67,7 +67,7 @@ def atleast_nd(x: Array, /, *, ndim: int, xp: ModuleType | None = None) -> Array
if xp is None:
xp = array_namespace(x)

if 1 <= ndim <= 3 and (
if 1 <= ndim <= 2 and (
is_numpy_namespace(xp)
or is_jax_namespace(xp)
or is_dask_namespace(xp)
Expand Down
127 changes: 108 additions & 19 deletions tests/test_funcs.py
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Original file line number Diff line number Diff line change
Expand Up @@ -54,6 +54,8 @@
lazy_xp_function(setdiff1d, jax_jit=False)
lazy_xp_function(sinc)

NestedFloatList = list[float] | list["NestedFloatList"]


class TestApplyWhere:
@staticmethod
Expand Down Expand Up @@ -291,7 +293,31 @@ def test_0D(self, xp: ModuleType):
y = atleast_nd(x, ndim=5)
xp_assert_equal(y, xp.ones((1, 1, 1, 1, 1)))

def test_1D(self, xp: ModuleType):
@pytest.mark.parametrize(
("input_shape", "ndim", "expected_shape"),
[
((1,), 0, (1,)),
((5,), 1, (5,)),
((2,), 2, (1, 2)),
((3,), 3, (1, 1, 3)),
((2,), 5, (1, 1, 1, 1, 2)),
],
)
def test_1D_shapes(
self,
input_shape: tuple[int],
ndim: int,
expected_shape: tuple[int],
xp: ModuleType,
):
n = math.prod(input_shape)
x = xp.reshape(xp.asarray(list(range(n))), input_shape)
y = atleast_nd(x, ndim=ndim)

assert y.shape == expected_shape
assert xp.sum(y) == int(n * (n - 1) / 2)

def test_1D_values(self, xp: ModuleType):
x = xp.asarray([0, 1])

y = atleast_nd(x, ndim=0)
Expand All @@ -306,8 +332,32 @@ def test_1D(self, xp: ModuleType):
y = atleast_nd(x, ndim=5)
xp_assert_equal(y, xp.asarray([[[[[0, 1]]]]]))

def test_2D(self, xp: ModuleType):
x = xp.asarray([[3.0]])
@pytest.mark.parametrize(
("input_shape", "ndim", "expected_shape"),
[
((2, 1), 0, (2, 1)),
((5, 2), 1, (5, 2)),
((2, 1), 2, (2, 1)),
((3, 1), 3, (1, 3, 1)),
((2, 8), 5, (1, 1, 1, 2, 8)),
],
)
def test_2D_shapes(
self,
input_shape: tuple[int],
ndim: int,
expected_shape: tuple[int],
xp: ModuleType,
):
n = math.prod(input_shape)
x = xp.reshape(xp.asarray(list(range(n))), input_shape)
y = atleast_nd(x, ndim=ndim)

assert y.shape == expected_shape
assert xp.sum(y) == int(n * (n - 1) / 2)

def test_2D_values(self, xp: ModuleType):
x = xp.asarray([[3.0], [4.0]])

y = atleast_nd(x, ndim=0)
xp_assert_equal(y, x)
Expand All @@ -316,12 +366,36 @@ def test_2D(self, xp: ModuleType):
xp_assert_equal(y, x)

y = atleast_nd(x, ndim=3)
xp_assert_equal(y, 3 * xp.ones((1, 1, 1)))
xp_assert_equal(y, xp.asarray([[[3.0], [4.0]]]))

y = atleast_nd(x, ndim=5)
xp_assert_equal(y, 3 * xp.ones((1, 1, 1, 1, 1)))
xp_assert_equal(y, xp.asarray([[[[[3.0], [4.0]]]]]))

@pytest.mark.parametrize(
("input_shape", "ndim", "expected_shape"),
[
((2, 1, 1), 0, (2, 1, 1)),
((1, 5, 2), 1, (1, 5, 2)),
((2, 1, 1), 2, (2, 1, 1)),
((1, 3, 1), 3, (1, 3, 1)),
((2, 8, 1), 5, (1, 1, 2, 8, 1)),
],
)
def test_3D_shapes(
self,
input_shape: tuple[int],
ndim: int,
expected_shape: tuple[int],
xp: ModuleType,
):
n = math.prod(input_shape)
x = xp.reshape(xp.asarray(list(range(n))), input_shape)
y = atleast_nd(x, ndim=ndim)

assert y.shape == expected_shape
assert xp.sum(y) == int(n * (n - 1) / 2)

def test_3D(self, xp: ModuleType):
def test_3D_values(self, xp: ModuleType):
x = xp.asarray([[[3.0], [2.0]]])

y = atleast_nd(x, ndim=0)
Expand All @@ -336,8 +410,32 @@ def test_3D(self, xp: ModuleType):
y = atleast_nd(x, ndim=5)
xp_assert_equal(y, xp.asarray([[[[[3.0], [2.0]]]]]))

def test_5D(self, xp: ModuleType):
x = xp.ones((1, 1, 1, 1, 1))
@pytest.mark.parametrize(
("input_shape", "ndim", "expected_shape"),
[
((2, 1, 1, 2, 1), 0, (2, 1, 1, 2, 1)),
((1, 5, 2, 3, 2), 2, (1, 5, 2, 3, 2)),
((2, 1, 1, 5, 2), 5, (2, 1, 1, 5, 2)),
((1, 3, 1, 2, 1), 6, (1, 1, 3, 1, 2, 1)),
((2, 8, 1, 9, 8), 9, (1, 1, 1, 1, 2, 8, 1, 9, 8)),
],
)
def test_5D_shapes(
self,
input_shape: tuple[int],
ndim: int,
expected_shape: tuple[int],
xp: ModuleType,
):
n = math.prod(input_shape)
x = xp.reshape(xp.asarray(list(range(n))), input_shape)
y = atleast_nd(x, ndim=ndim)

assert y.shape == expected_shape
assert xp.sum(y) == int(n * (n - 1) / 2)

def test_5D_values(self, xp: ModuleType):
x = xp.asarray([[[[[3.0]], [[2.0]]]]])

y = atleast_nd(x, ndim=0)
xp_assert_equal(y, x)
Expand All @@ -349,19 +447,10 @@ def test_5D(self, xp: ModuleType):
xp_assert_equal(y, x)

y = atleast_nd(x, ndim=6)
xp_assert_equal(y, xp.ones((1, 1, 1, 1, 1, 1)))
xp_assert_equal(y, xp.asarray([[[[[[3.0]], [[2.0]]]]]]))

y = atleast_nd(x, ndim=9)
xp_assert_equal(y, xp.ones((1, 1, 1, 1, 1, 1, 1, 1, 1)))

def test_device(self, xp: ModuleType, device: Device):
x = xp.asarray([1, 2, 3], device=device)
assert get_device(atleast_nd(x, ndim=2)) == device

def test_xp(self, xp: ModuleType):
x = xp.asarray(1.0)
y = atleast_nd(x, ndim=1, xp=xp)
xp_assert_equal(y, xp.ones((1,)))
xp_assert_equal(y, xp.asarray([[[[[[[[[3.0]], [[2.0]]]]]]]]]))


class TestBroadcastShapes:
Expand Down