update tests for compatibility with ov 2025.0

Author: eaidova

tests/openvino/test_exporters_cli.py

@@ -90,11 +90,11 @@ class OVCLIExportTestCase(unittest.TestCase):
         "gpt2": 2 if is_tokenizers_version("<", "0.20") or is_openvino_version(">=", "2024.5") else 0,
         "t5": 0,  # no .model file in the repository
         "albert": 0,  # not supported yet
-        "distilbert": 1,  # no detokenizer
+        "distilbert": 1 if is_openvino_version("<", "2025.0") else 2,  # no detokenizer before 2025.0
         "roberta": 2 if is_tokenizers_version("<", "0.20") or is_openvino_version(">=", "2024.5") else 0,
         "vit": 0,  # no tokenizer for image model
         "wav2vec2": 0,  # no tokenizer
-        "bert": 1,  # no detokenizer
+        "bert": 1 if is_openvino_version("<", "2025.0") else 2,  # no detokenizer before 2025.0
         "blenderbot": 2 if is_tokenizers_version("<", "0.20") or is_openvino_version(">=", "2024.5") else 0,
         "stable-diffusion": 2 if is_tokenizers_version("<", "0.20") or is_openvino_version(">=", "2024.5") else 0,
         "stable-diffusion-xl": 4 if is_tokenizers_version("<", "0.20") or is_openvino_version(">=", "2024.5") else 0,

tests/openvino/test_modeling.py

@@ -1661,7 +1661,7 @@ def test_compare_to_transformers(self, model_arch):
         with torch.no_grad():
             transformers_outputs = transformers_model(**tokens, **decoder_inputs)
         # Compare tensor outputs
-        self.assertTrue(torch.allclose(ov_outputs.logits, transformers_outputs.logits, atol=1e-4))
+        self.assertTrue(torch.allclose(ov_outputs.logits, transformers_outputs.logits, atol=5e-3))
         gen_config = GenerationConfig(
             max_new_tokens=10,
             min_new_tokens=10,

tests/openvino/test_quantization.py

@@ -1085,7 +1085,7 @@ def preprocess_function(examples, tokenizer):
 
 
 class OVTrainerTest(unittest.TestCase):
-    SUPPORTED_ARCHITECTURES_WITH_EXPECTED_QUANTIZED_MATMULS = (("albert", 63, 39),)
+    SUPPORTED_ARCHITECTURES_WITH_EXPECTED_QUANTIZED_MATMULS = (("albert", 61, 39),)
 
     @parameterized.expand(SUPPORTED_ARCHITECTURES_WITH_EXPECTED_QUANTIZED_MATMULS)
     @unittest.skipIf(