skip ipex ci

Signed-off-by: Kaihui-intel <kaihui.tang@intel.com>

Author: Kaihui-intel

test/3x/torch/quantization/test_smooth_quant.py

@@ -4,6 +4,7 @@
 
 import pytest
 import torch
+from packaging.version import Version
 
 from neural_compressor.torch.quantization import SmoothQuantConfig, convert, get_default_sq_config, prepare, quantize
 from neural_compressor.torch.utils import is_ipex_available
@@ -33,8 +34,7 @@ def forward(self, x):
 def run_fn(model):
     for i in range(10):
         model(example_inputs)
-
-
+@pytest.mark.skipif(not Version(torch.__version__) < Version("2.9.0"), reason="only for torch<2.9.0 [ipex]")
 class TestSmoothQuant:
     def teardown_class(self):
         shutil.rmtree("saved_results", ignore_errors=True)

test/3x/torch/quantization/test_static_quant.py

@@ -4,6 +4,7 @@
 
 import pytest
 import torch
+from packaging.version import Version
 
 try:
     import intel_extension_for_pytorch as ipex
@@ -52,7 +53,7 @@ def run_fn(model):
     model(torch.rand((1, 30)))
     model(torch.rand((1, 30)))
 
-
+@pytest.mark.skipif(not Version(torch.__version__) < Version("2.9.0"), reason="only for torch<2.9.0 [ipex]")
 class TestStaticQuant:
     def setup_class(self):
         self.fp32_model = build_simple_torch_model()

test/3x/torch/quantization/weight_only/test_transformers.py

@@ -23,13 +23,15 @@
 
 ipex_version = get_ipex_version()
 
+
 try:
     import auto_round
 
     auto_round_installed = True
 except ImportError:
     auto_round_installed = False
 
+@pytest.mark.skipif(not Version(torch.__version__) < Version("2.9.0"), reason="only for torch<2.9.0 [ipex]")
 class TestTansformersLikeAPI:
     def setup_class(self):
         self.model_name_or_path = "hf-tiny-model-private/tiny-random-GPTJForCausalLM"