Fix torch version for ipex tests (#545)

* fix torch version for ipex tests

* disbale tests for incompatible torch version with ipex

* fix

Author: echarlaix

.github/workflows/test_ipex.yml

@@ -30,6 +30,7 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
+        pip install torch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 --index-url https://download.pytorch.org/whl/cpu
         pip install .[ipex,tests]
     - name: Test with Pytest
       run: |

tests/neural_compressor/test_optimization.py

@@ -18,6 +18,7 @@
 import os
 import tempfile
 
+import unittest
 import evaluate
 import numpy as np
 import torch
@@ -43,6 +44,8 @@
     set_seed,
 )
 from utils_tests import SEED, INCTestMixin, _generate_dataset
+from optimum.intel.utils.import_utils import is_torch_version
+
 
 from optimum.intel import (
     INCConfig,
@@ -163,6 +166,7 @@ def test_static_quantization(self, task, model_name, expected_quantized_matmuls)
             )
 
     @parameterized.expand(SUPPORTED_ARCHITECTURES_WITH_EXPECTED_QUANTIZED_MATMULS)
+    @unittest.skipIf(is_torch_version(">=", "2.2.0"), "compatibility issue with torch 2.2.0 and IPEX latest version")
     def test_ipex_static_quantization_with_smoothquant(self, task, model_name, expected_quantized_matmuls):
         recipes = {"smooth_quant": True, "smooth_quant_args": {"alpha": 0.5}}
         num_samples = 10

tests/neural_compressor/utils_tests.py

@@ -40,18 +40,23 @@
     INCStableDiffusionPipeline,
 )
 
-from optimum.intel.ipex import (
-    IPEXModelForCausalLM,
-    IPEXModelForSequenceClassification,
-    IPEXModelForMaskedLM,
-    IPEXModelForTokenClassification,
-)
+
+from optimum.intel.utils.import_utils import is_torch_version
 
 from optimum.intel.neural_compressor.utils import _HEAD_TO_AUTOMODELS
 from optimum.intel.utils.constant import ONNX_WEIGHTS_NAME
 from optimum.onnxruntime import ORTModelForCausalLM, ORTModelForSequenceClassification
 from optimum.pipelines import ORT_SUPPORTED_TASKS
 
+if is_torch_version("<", "2.2.0"):
+    from optimum.intel.ipex import (
+        IPEXModelForCausalLM,
+        IPEXModelForSequenceClassification,
+        IPEXModelForMaskedLM,
+        IPEXModelForTokenClassification,
+    )
+
+
 SEED = 1009
 _TASK_TO_DATASET = {
     "text-classification": ("glue", "sst2", "sentence"),