udpate test

huggingface · Jul 4, 2024 · d8fed91 · d8fed91
1 parent 4ee9c99
commit d8fed91
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Showing 3 changed files with 3 additions and 13 deletions.
diff --git a/.github/workflows/test_openvino.yml b/.github/workflows/test_openvino.yml
@@ -21,7 +21,7 @@ jobs:
       fail-fast: false
       matrix:
         python-version: ["3.8", "3.12"]
-        transformers-version: ["4.36.0", "4.41.*","4.42.*"]
+        transformers-version: ["4.36.0","4.42.*"]
         os: [ubuntu-latest]
 
     runs-on: ${{ matrix.os }}

diff --git a/tests/openvino/test_modeling.py b/tests/openvino/test_modeling.py
@@ -748,11 +748,6 @@ def test_compare_to_transformers(self, model_arch):
         )
 
         ov_outputs = ov_model.generate(**tokens, generation_config=gen_config)
-
-        # TODO: update _update_model_kwargs_for_generation so that it's compatibile with transformers >= v4.42.0
-        if model_arch not in ["chatglm", "glm4"] and is_transformers_version(">=", "4.42.0"):
-            return
-
         transformers_outputs = transformers_model.generate(**tokens, generation_config=gen_config)
         self.assertTrue(torch.allclose(ov_outputs, transformers_outputs))
 

diff --git a/tests/openvino/test_quantization.py b/tests/openvino/test_quantization.py
@@ -75,8 +75,8 @@
 
 class OVQuantizerTest(unittest.TestCase):
     SUPPORTED_ARCHITECTURES_TORCH_MODEL = (
-        (OVModelForSequenceClassification, "bert", 22, 35),
-        (OVModelForCausalLM, "gpt2", 21, 3),
+        (OVModelForSequenceClassification, "bert", 32 if is_transformers_version("<", "4.41.0") else 22, 35),
+        (OVModelForCausalLM, "gpt2", 41 if is_transformers_version("<", "4.42.0") else 21, 3),
     )
     SUPPORTED_ARCHITECTURES_OV_MODEL = (
         (OVModelForSequenceClassification, "bert", 32, 35),
@@ -90,11 +90,6 @@ def test_automodel_static_quantization(self, model_cls, model_name, expected_fak
         dataset_name, dataset_config_name, column_name = _TASK_TO_DATASET[task]
         file_name = "openvino_quantized_model.xml"
 
-        if is_transformers_version("<", "4.41.0") and model_name == "bert":
-            expected_fake_quantize = 32
-        if is_transformers_version("<", "4.42.0") and model_name == "gpt2":
-            expected_fake_quantize = 41
-
         def preprocess_function(examples, tokenizer):
             return tokenizer(examples[column_name], padding="max_length", max_length=128, truncation=True)