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Expose ct.abs in order to resolve https://github.com/NVIDIA/cutile-python/issues/30 #33

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Expose ct.abs in order to resolve https://github.com/NVIDIA/cutile-python/issues/30 #33

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c5bae4f
Update stub to expose ct.abs(input_tile)
NikeNano Dec 18, 2025
742aa1b
Add test for ct.add(input_tile)
NikeNano Dec 18, 2025
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2 changes: 2 additions & 0 deletions src/cuda/tile/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -55,6 +55,7 @@
Scalar,
Tile,

abs,
add,
arange,
argmax,
Expand Down Expand Up @@ -183,6 +184,7 @@
"Scalar",
"Tile",

"abs",
"add",
"arange",
"argmax",
Expand Down
14 changes: 14 additions & 0 deletions src/cuda/tile/_stub.py
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Expand Up @@ -127,6 +127,10 @@ def __eq__(self, other) -> "TileOrScalar":
def __ne__(self, other) -> "TileOrScalar":
...

@function
def __abs__(self) -> "TileOrScalar":
...


Scalar = int | float | ScalarProtocol

Expand Down Expand Up @@ -370,6 +374,10 @@ def __eq__(self, other) -> "Tile":
def __ne__(self, other) -> "Tile":
...

@function
def __abs__(self) -> "Tile":
...


Shape = Union[int, tuple[int, ...]]
Order = Union[tuple[int, ...], Literal['C'], Literal['F']]
Expand Down Expand Up @@ -1755,6 +1763,12 @@ def ceil(x, /) -> TileOrScalar:
pass


@_doc_unary_op
@function
def abs(x, /) -> TileOrScalar:
pass


@function
def negative(x, /) -> TileOrScalar:
"""Same as `-x`.
Expand Down
27 changes: 27 additions & 0 deletions test/test_unary_elementwise.py
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Expand Up @@ -223,6 +223,15 @@ def test_array_abs(shape, tile, dtype, tmp_path):
assert_equal(y, abs(x))


@pytest.mark.parametrize("dtype", bool_dtypes + int_dtypes + float_dtypes, ids=dtype_id)
def test_array_ct_abs(shape, tile, dtype, tmp_path):
x = make_tensor(shape, dtype=dtype, device='cuda')
y = torch.zeros_like(x, device="cuda")
kernel = array_kernel('ct_abs', "ty = ct.abs(tx)", tmp_path)
launch_unary(kernel, x, y, tile)
assert_equal(y, abs(x))


@pytest.mark.parametrize("is_constant", [False, True])
@pytest.mark.parametrize("dtype", int_dtypes + float_dtypes, ids=dtype_id)
def test_scalar_abs(shape, tile, is_constant, dtype, tmp_path):
Expand All @@ -241,6 +250,24 @@ def test_scalar_abs(shape, tile, is_constant, dtype, tmp_path):
assert_equal(y, abs(x))


@pytest.mark.parametrize("is_constant", [False, True])
@pytest.mark.parametrize("dtype", int_dtypes + float_dtypes, ids=dtype_id)
def test_scalar_ct_abs(shape, tile, is_constant, dtype, tmp_path):
if dtype in int_dtypes:
x = -5
dtype_str = "int"
else:
x = -5.0
dtype_str = "float"
y = torch.zeros(shape, dtype=dtype, device='cuda')
if not is_constant:
kernel = scalar_kernel('ct_abs', 'c = ct.abs(x)', tmp_path)
else:
kernel = const_scalar_kernel('ct_abs', dtype_str, 'c = ct.abs(x)', tmp_path)
launch_unary(kernel, x, y, tile)
assert_equal(y, abs(x))


@pytest.mark.parametrize("bitwise_not_func", ['~', 'ct.bitwise_not'])
@pytest.mark.parametrize("dtype", int_dtypes + bool_dtypes, ids=dtype_id)
def test_array_bitwise_not(shape, tile, dtype, tmp_path, bitwise_not_func):
Expand Down