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Enable TorchAO int4wo quantization tests on XPU #13537

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Merged
sayakpaul merged 5 commits into from
May 6, 2026
+8 −2
Merged

Enable TorchAO int4wo quantization tests on XPU #13537

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639a014
Enable TorchAO int4wo quantization tests on XPU
jiqing-feng Apr 22, 2026
d77dd97
add xpu to not skip
jiqing-feng May 6, 2026
02303d1
Merge branch 'main' into torchao-xpu-int4wo
jiqing-feng May 6, 2026
64cd465
Merge branch 'main' into torchao-xpu-int4wo
sayakpaul May 6, 2026
9eb2204
Apply style fixes
github-actions[bot] May 6, 2026
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10 changes: 8 additions & 2 deletions tests/models/testing_utils/quantization.py
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Original file line number Diff line number Diff line change
Expand Up @@ -805,6 +805,10 @@ class TorchAoConfigMixin:
@staticmethod
def _get_quant_config(config_name):
config_cls = getattr(_torchao_quantization, config_name)
# TorchAO int4 quantization requires plain_int32 packing format on Intel XPU
if config_name == "Int4WeightOnlyConfig" and torch_device == "xpu":
return TorchAoConfig(config_cls(int4_packing_format="plain_int32"))

return TorchAoConfig(config_cls())

def _create_quantized_model(self, config_name, **extra_kwargs):
Expand All @@ -819,8 +823,10 @@ def _verify_if_layer_quantized(self, name, module, config_kwargs):
assert isinstance(module, torch.nn.Linear), f"Layer {name} is not Linear, got {type(module)}"


# int4wo requires CUDA-specific ops (_convert_weight_to_int4pack)
_int4wo_skip = pytest.mark.skipif(torch_device != "cuda", reason="int4wo quantization requires CUDA")
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jiqing-feng marked this conversation as resolved.
# int4wo requires CUDA or XPU ops (_convert_weight_to_int4pack)
_int4wo_skip = pytest.mark.skipif(
torch_device not in ["cuda", "xpu"], reason="int4wo quantization requires CUDA or XPU"
)


@is_torchao
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