[PT FE] Use system model cache when running torch hub tests locally (o…

…penvinotoolkit#21047) * Use system model cache when running torch hub tests locally * Update tests/model_hub_tests/torch_tests/test_torchvision_models.py * Update tests/model_hub_tests/torch_tests/test_torchvision_models.py
jiwaszki · Nov 14, 2023 · 369831c · 369831c
1 parent 5ef7c02
commit 369831c
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Showing 3 changed files with 6 additions and 4 deletions.
diff --git a/.github/workflows/linux.yml b/.github/workflows/linux.yml
@@ -1435,6 +1435,7 @@ jobs:
         env:
           TYPE: ${{ github.event_name == 'schedule' && 'nightly' || 'precommit'}}
           TEST_DEVICE: CPU
+          USE_SYSTEM_CACHE: False
 
       - name: Available storage after tests
         run: |

diff --git a/tests/model_hub_tests/models_hub_common/constants.py b/tests/model_hub_tests/models_hub_common/constants.py
@@ -9,9 +9,9 @@
                                   os.path.join(tempfile.gettempdir(), "tfhub_modules"))
 os.environ['TFHUB_CACHE_DIR'] = tf_hub_cache_dir
 
-hf_hub_cache_dir = os.environ.get('HUGGINGFACE_HUB_CACHE',
-                                  tempfile.gettempdir())
-os.environ['HUGGINGFACE_HUB_CACHE'] = hf_hub_cache_dir
+hf_hub_cache_dir = tempfile.gettempdir()
+if os.environ.get('USE_SYSTEM_CACHE', 'True') == 'False':
+    os.environ['HUGGINGFACE_HUB_CACHE'] = hf_hub_cache_dir
 
 # supported_devices : CPU, GPU, GNA
 test_device = os.environ.get('TEST_DEVICE', 'CPU;GPU').split(';')
diff --git a/tests/model_hub_tests/torch_tests/test_torchvision_models.py b/tests/model_hub_tests/torch_tests/test_torchvision_models.py
@@ -56,7 +56,8 @@ class TestTorchHubConvertModel(TestConvertModel):
     def setup_class(self):
         self.cache_dir = tempfile.TemporaryDirectory()
         # set temp dir for torch cache
-        torch.hub.set_dir(str(self.cache_dir.name))
+        if os.environ.get('USE_SYSTEM_CACHE', 'True') == 'False':
+            torch.hub.set_dir(str(self.cache_dir.name))
 
     def load_model(self, model_name, model_link):
         m = torch.hub.load("pytorch/vision", model_name,