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[test][xpu] Add test_config.py, test_model_architecture.py and test_utils.py in Intel GPU CI #4526

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[test][xpu] Add test_config.py, test_model_architecture.py and test_utils.py in Intel GPU CI #4526

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5 changes: 4 additions & 1 deletion .github/scripts/ci_test_xpu.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -23,4 +23,7 @@ pytest -v -s --ignore=torchao/test/quantization/pt2e/test_x86inductor_fusion.py
torchao/test/float8/ \
torchao/test/integration/test_integration.py \
torchao/test/prototype/ \
torchao/test/quantization/quantize_/workflows/
torchao/test/quantization/quantize_/workflows/ \
torchao/test/core/test_config.py \
torchao/test/test_model_architecture.py \
torchao/test/test_utils.py
16 changes: 8 additions & 8 deletions test/test_utils.py
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Expand Up @@ -9,7 +9,6 @@
import torch
import torch.nn.functional as F

from torchao.testing.utils import skip_if_no_cuda
from torchao.utils import TorchAOBaseTensor, torch_version_at_least


Expand Down Expand Up @@ -128,14 +127,15 @@ def _test_default_impls_helper(self, lp_tensor, lp_tensor_for_copy):
self.assertTrue(torch.equal(lp_tensor.qdata, reconstructed.qdata))
self.assertEqual(lp_tensor.attr, reconstructed.attr)

device = torch.accelerator.current_accelerator()
# test _get_to_kwargs
_ = lp_tensor._get_to_kwargs(torch.strided, device="cuda")
_ = lp_tensor._get_to_kwargs(layout=torch.strided, device="cuda")
_ = lp_tensor._get_to_kwargs(torch.strided, device=device)
_ = lp_tensor._get_to_kwargs(layout=torch.strided, device=device)

# `to` / `_to_copy`
original_device = lp_tensor.device
lp_tensor = lp_tensor.to("cuda")
self.assertEqual(lp_tensor.device.type, "cuda")
lp_tensor = lp_tensor.to(device)
self.assertEqual(lp_tensor.device.type, device.type)
lp_tensor = lp_tensor.to(original_device)
self.assertEqual(lp_tensor.device, original_device)

Expand Down Expand Up @@ -218,7 +218,7 @@ def _test_default_impls_helper(self, lp_tensor, lp_tensor_for_copy):
getattr(lp_tensor, tensor_attribute_name),
)

@skip_if_no_cuda()
@unittest.skipIf(not torch.accelerator.is_available(), "Need CUDA available")
def test_default_impls(self):
"""Making sure some common functions has default implementations, such as
__tensor_unflatten__, __tensor_flatten__, _apply_fn_to_data, __repr__, to
Expand Down Expand Up @@ -248,7 +248,7 @@ def __init__(self, qdata, attr, device):
lp_tensor_for_copy = MyTensor(another_tensor, "attr", None)
self._test_default_impls_helper(lp_tensor, lp_tensor_for_copy)

@skip_if_no_cuda()
@unittest.skipIf(not torch.accelerator.is_available(), "Need GPU available")
def test_default_impls_with_optional_data(self):
class MyTensorWithOptionalData(TorchAOBaseTensor):
tensor_data_names = ["qdata"]
Expand Down Expand Up @@ -285,7 +285,7 @@ def __init__(self, qdata, attr, device, zero_point=None):
)
self._test_default_impls_helper(lp_tensor, lp_tensor_for_copy)

@skip_if_no_cuda()
@unittest.skipIf(not torch.accelerator.is_available(), "Need GPU available")
def test_default_impls_with_optional_attr(self):
class MyTensorWithOptionalData(TorchAOBaseTensor):
tensor_data_names = ["qdata"]
Expand Down
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