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tests(fp8): xfail the M=1 scaled_mm apply cases #821

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Merged
joerunde merged 1 commit into from
Sep 9, 2026
Merged

tests(fp8): xfail the M=1 scaled_mm apply cases #821

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18 changes: 16 additions & 2 deletions tests/test_fp8_linear.py
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Original file line number Diff line number Diff line change
Expand Up @@ -76,6 +76,20 @@ def _make_kernel(*, granite_channel: bool = False):
)


# Non-strict: this shape still compiles on some deeptools/dxp_standalone builds,
# and an xpass is the signal that the backend fix landed.
_XFAIL_M1 = pytest.param(
1,
marks=pytest.mark.xfail(
strict=False,
reason=(
"dxp_standalone fails to compile the fused activation-quantize + "
"_scaled_mm graph for the M=1 decode shape"
),
),
)


@pytest.mark.fp8
class TestSpyreFp8LinearKernel:
def test_register(self):
Expand Down Expand Up @@ -204,7 +218,7 @@ def _run_spyre_apply(self, kernel, layer, x):
assert actual.device.type == "spyre", actual.device
return actual

@pytest.mark.parametrize("num_tokens", [1, 4, 128])
@pytest.mark.parametrize("num_tokens", [_XFAIL_M1, 4, 128])
def test_scaled_mm_apply(self, num_tokens):
"""apply_weights runs aten._scaled_mm on Spyre."""
if not spyre_available():
Expand All @@ -228,7 +242,7 @@ def test_scaled_mm_apply(self, num_tokens):
assert actual.dtype == torch.float16
assert actual.shape == (num_tokens, out_features)

@pytest.mark.parametrize("num_tokens", [1, 4, 128])
@pytest.mark.parametrize("num_tokens", [_XFAIL_M1, 4, 128])
def test_scaled_mm_apply_per_channel(self, num_tokens):
"""apply_weights with Granite per-channel weight scales + per-token acts."""
if not spyre_available():
Expand Down
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