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[tests] enhance attention backend tests #12830

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39 changes: 25 additions & 14 deletions tests/others/test_attention_backends.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,8 +11,7 @@
pytest tests/others/test_attention_backends.py
```

Tests were conducted on an H100 with PyTorch 2.8.0 (CUDA 12.9). Slices for the compilation tests in
"native" variants were obtained with a torch nightly version (2.10.0.dev20250924+cu128).
Tests were conducted on an H100 with PyTorch 2.9.1 (CUDA 12.9).

Tests for aiter backend were conducted and slices for the aiter backend tests collected on a MI355X
with torch 2025-09-25 nightly version (ad2f7315ca66b42497047bb7951f696b50f1e81b) and
Expand All @@ -24,6 +23,8 @@
import pytest
import torch

from ..testing_utils import numpy_cosine_similarity_distance


pytestmark = pytest.mark.skipif(
os.getenv("RUN_ATTENTION_BACKEND_TESTS", "false") == "false", reason="Feature not mature enough."
Expand All @@ -36,51 +37,61 @@
FORWARD_CASES = [
(
"flash_hub",
torch.tensor([0.0820, 0.0859, 0.0918, 0.1016, 0.0957, 0.0996, 0.0996, 0.1016, 0.2188, 0.2266, 0.2363, 0.2500, 0.2539, 0.2461, 0.2422, 0.2695], dtype=torch.bfloat16)
torch.tensor([0.0820, 0.0859, 0.0918, 0.1016, 0.0957, 0.0996, 0.0996, 0.1016, 0.2188, 0.2266, 0.2363, 0.2500, 0.2539, 0.2461, 0.2422, 0.2695], dtype=torch.bfloat16),
1e-4
),
(
"_flash_3_hub",
torch.tensor([0.0820, 0.0859, 0.0938, 0.1016, 0.0977, 0.0996, 0.1016, 0.1016, 0.2188, 0.2246, 0.2344, 0.2480, 0.2539, 0.2480, 0.2441, 0.2715], dtype=torch.bfloat16),
1e-4
),
(
"native",
torch.tensor([0.0820, 0.0859, 0.0938, 0.1016, 0.0957, 0.0996, 0.0996, 0.1016, 0.2188, 0.2266, 0.2363, 0.2500, 0.2539, 0.2480, 0.2461, 0.2734], dtype=torch.bfloat16)
),
torch.tensor([0.0820, 0.0859, 0.0938, 0.1016, 0.0957, 0.0996, 0.0996, 0.1016, 0.2188, 0.2266, 0.2363, 0.2500, 0.2539, 0.2480, 0.2461, 0.2734], dtype=torch.bfloat16),
1e-4
),
(
"_native_cudnn",
torch.tensor([0.0781, 0.0840, 0.0879, 0.0957, 0.0898, 0.0957, 0.0957, 0.0977, 0.2168, 0.2246, 0.2324, 0.2500, 0.2539, 0.2480, 0.2441, 0.2695], dtype=torch.bfloat16),
5e-4
),
(
"aiter",
torch.tensor([0.0781, 0.0820, 0.0879, 0.0957, 0.0898, 0.0938, 0.0957, 0.0957, 0.2285, 0.2363, 0.2461, 0.2637, 0.2695, 0.2617, 0.2617, 0.2891], dtype=torch.bfloat16),
1e-4
)
]

COMPILE_CASES = [
(
"flash_hub",
torch.tensor([0.0410, 0.0410, 0.0449, 0.0508, 0.0488, 0.0586, 0.0605, 0.0586, 0.2324, 0.2422, 0.2539, 0.2734, 0.2832, 0.2812, 0.2773, 0.3047], dtype=torch.bfloat16),
True
True,
1e-4
),
(
"_flash_3_hub",
torch.tensor([0.0410, 0.0410, 0.0449, 0.0508, 0.0508, 0.0605, 0.0625, 0.0605, 0.2344, 0.2461, 0.2578, 0.2734, 0.2852, 0.2812, 0.2773, 0.3047], dtype=torch.bfloat16),
True,
1e-4
),
(
"native",
torch.tensor([0.0410, 0.0410, 0.0449, 0.0508, 0.0508, 0.0605, 0.0605, 0.0605, 0.2344, 0.2461, 0.2578, 0.2773, 0.2871, 0.2832, 0.2773, 0.3066], dtype=torch.bfloat16),
True,
1e-4
),
(
"_native_cudnn",
torch.tensor([0.0410, 0.0410, 0.0430, 0.0508, 0.0488, 0.0586, 0.0605, 0.0586, 0.2344, 0.2461, 0.2578, 0.2773, 0.2871, 0.2832, 0.2793, 0.3086], dtype=torch.bfloat16),
True,
5e-4,
),
(
"aiter",
torch.tensor([0.0391, 0.0391, 0.0430, 0.0488, 0.0469, 0.0566, 0.0586, 0.0566, 0.2402, 0.2539, 0.2637, 0.2812, 0.2930, 0.2910, 0.2891, 0.3164], dtype=torch.bfloat16),
True,
1e-4
)
]
# fmt: on
Expand All @@ -104,11 +115,11 @@ def _backend_is_probably_supported(pipe, name: str):
return False


def _check_if_slices_match(output, expected_slice):
def _check_if_slices_match(output, expected_slice, expected_diff=1e-4):
img = output.images.detach().cpu()
generated_slice = img.flatten()
generated_slice = torch.cat([generated_slice[:8], generated_slice[-8:]])
assert torch.allclose(generated_slice, expected_slice, atol=1e-4)
assert numpy_cosine_similarity_distance(generated_slice, expected_slice) < expected_diff


@pytest.fixture(scope="session")
Expand All @@ -126,23 +137,23 @@ def pipe(device):
return pipe


@pytest.mark.parametrize("backend_name,expected_slice", FORWARD_CASES, ids=[c[0] for c in FORWARD_CASES])
def test_forward(pipe, backend_name, expected_slice):
@pytest.mark.parametrize("backend_name,expected_slice,expected_diff", FORWARD_CASES, ids=[c[0] for c in FORWARD_CASES])
def test_forward(pipe, backend_name, expected_slice, expected_diff):
out = _backend_is_probably_supported(pipe, backend_name)
if isinstance(out, bool):
pytest.xfail(f"Backend '{backend_name}' not supported in this environment.")

modified_pipe = out[0]
out = modified_pipe(**INFER_KW, generator=torch.manual_seed(0))
_check_if_slices_match(out, expected_slice)
_check_if_slices_match(out, expected_slice, expected_diff)


@pytest.mark.parametrize(
"backend_name,expected_slice,error_on_recompile",
"backend_name,expected_slice,error_on_recompile,expected_diff",
COMPILE_CASES,
ids=[c[0] for c in COMPILE_CASES],
)
def test_forward_with_compile(pipe, backend_name, expected_slice, error_on_recompile):
def test_forward_with_compile(pipe, backend_name, expected_slice, error_on_recompile, expected_diff):
if "native" in backend_name and error_on_recompile and not is_torch_version(">=", "2.9.0"):
pytest.xfail(f"Test with {backend_name=} is compatible with a higher version of torch.")

Expand All @@ -160,4 +171,4 @@ def test_forward_with_compile(pipe, backend_name, expected_slice, error_on_recom
):
out = modified_pipe(**INFER_KW, generator=torch.manual_seed(0))

_check_if_slices_match(out, expected_slice)
_check_if_slices_match(out, expected_slice, expected_diff)
4 changes: 4 additions & 0 deletions tests/testing_utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -131,6 +131,10 @@ def torch_all_close(a, b, *args, **kwargs):


def numpy_cosine_similarity_distance(a, b):
if isinstance(a, torch.Tensor):
a = a.detach().cpu().float().numpy()
if isinstance(b, torch.Tensor):
b = b.detach().cpu().float().numpy()
similarity = np.dot(a, b) / (norm(a) * norm(b))
distance = 1.0 - similarity.mean()

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