fix test

Author: echarlaix

tests/openvino/test_modeling.py

@@ -547,12 +547,12 @@ class OVModelForCausalLMIntegrationTest(unittest.TestCase):
     @parameterized.expand(SUPPORTED_ARCHITECTURES)
     def test_compare_to_transformers(self, model_arch):
         model_id = MODEL_NAMES[model_arch]
-        not_stateful = ["gpt_bigcode"]
+        not_stateful = []
         if is_openvino_version("<", "2024.0"):
             not_stateful.append("mixtral")
 
         if is_openvino_version("<", "2024.1"):
-            not_stateful.extend(["llama", "gemma"])
+            not_stateful.extend(["llama", "gemma", "gpt_bigcode"])
 
         if "gptq" in model_arch:
             self.skipTest("GPTQ model loading unsupported with AutoModelForCausalLM")

tests/openvino/test_quantization.py

@@ -657,7 +657,7 @@ def preprocess_function(examples, tokenizer):
 
 
 class OVTrainerTest(unittest.TestCase):
-    SUPPORTED_ARCHITECTURES_WITH_EXPECTED_QUANTIZED_MATMULS = (("distilbert-base-uncased", 50, 38),)
+    SUPPORTED_ARCHITECTURES_WITH_EXPECTED_QUANTIZED_MATMULS = (("distilbert-base-uncased", 49, 38),)
 
     @parameterized.expand(SUPPORTED_ARCHITECTURES_WITH_EXPECTED_QUANTIZED_MATMULS)
     def test_aware_training_quantization(self, model_name, expected_fake_quantize, expected_int8):

tests/openvino/test_training.py

@@ -322,30 +322,30 @@ def tearDown(self):
     "default_quantization": OVTrainerTestDescriptor(
         model_id="hf-internal-testing/tiny-random-bert",
         nncf_compression_config=DEFAULT_QUANTIZATION_CONFIG,
-        expected_fake_quantize=44,
+        expected_fake_quantize=34,
         expected_int8=32,
         compression_metrics=["compression_loss"],
     ),
     "distillation,default_quantization": OVTrainerTestDescriptor(
         model_id="hf-internal-testing/tiny-random-bert",
         teacher_model_id="hf-internal-testing/tiny-random-bert",
         nncf_compression_config=DEFAULT_QUANTIZATION_CONFIG,
-        expected_fake_quantize=44,
+        expected_fake_quantize=34,
         expected_int8=32,
         compression_metrics=["compression_loss", "distillation_loss", "task_loss"],
     ),
     "customized_quantization": OVTrainerTestDescriptor(
         model_id="hf-internal-testing/tiny-random-bert",
         nncf_compression_config=CUSTOMIZED_QUANTIZATION_CONFIG,
-        expected_fake_quantize=44,
+        expected_fake_quantize=34,
         expected_int8=32,
         compression_metrics=["compression_loss"],
     ),
     "distillation,customized_quantization": OVTrainerTestDescriptor(
         model_id="hf-internal-testing/tiny-random-bert",
         teacher_model_id="hf-internal-testing/tiny-random-bert",
         nncf_compression_config=CUSTOMIZED_QUANTIZATION_CONFIG,
-        expected_fake_quantize=44,
+        expected_fake_quantize=34,
         expected_int8=32,
         compression_metrics=["compression_loss", "distillation_loss", "task_loss"],
     ),
@@ -418,7 +418,7 @@ def tearDown(self):
     "default_quantization,unstructured_movement_sparsity": OVTrainerTestDescriptor(
         model_id="hf-internal-testing/tiny-random-bert",
         nncf_compression_config=[DEFAULT_QUANTIZATION_CONFIG, UNSTRUCTURED_MOVEMENT_SPARSITY_CONFIG_FOR_BERT],
-        expected_fake_quantize=44,
+        expected_fake_quantize=34,
         expected_int8=32,
         expected_binary_masks=60,
         compression_metrics=["compression_loss"],
@@ -429,7 +429,7 @@ def tearDown(self):
             CUSTOMIZED_QUANTIZATION_CONFIG,
             UNSTRUCTURED_MOVEMENT_SPARSITY_CONFIG_FOR_BERT,
         ],
-        expected_fake_quantize=44,
+        expected_fake_quantize=34,
         expected_int8=32,
         expected_binary_masks=60,
         compression_metrics=["compression_loss"],
@@ -438,7 +438,7 @@ def tearDown(self):
         model_id="hf-internal-testing/tiny-random-bert",
         teacher_model_id="hf-internal-testing/tiny-random-bert",
         nncf_compression_config=[DEFAULT_QUANTIZATION_CONFIG, UNSTRUCTURED_MOVEMENT_SPARSITY_CONFIG_FOR_BERT],
-        expected_fake_quantize=44,
+        expected_fake_quantize=34,
         expected_int8=32,
         expected_binary_masks=60,
         compression_metrics=["compression_loss", "distillation_loss", "task_loss"],
@@ -450,7 +450,7 @@ def tearDown(self):
             CUSTOMIZED_QUANTIZATION_CONFIG,
             UNSTRUCTURED_MOVEMENT_SPARSITY_CONFIG_FOR_BERT,
         ],
-        expected_fake_quantize=44,
+        expected_fake_quantize=34,
         expected_int8=32,
         expected_binary_masks=60,
         compression_metrics=["compression_loss", "distillation_loss", "task_loss"],
@@ -730,7 +730,7 @@ def check_ovmodel_reshaping(self, ovmodel: OVModel):
     "quantization": OVTrainerTestDescriptor(
         model_id="hf-internal-testing/tiny-random-Wav2Vec2Model",
         nncf_compression_config=[QUANTIZATION_CONFIG_FOR_WAV2VEC2],
-        expected_fake_quantize=48,
+        expected_fake_quantize=40,
         expected_int8=30,
         compression_metrics=["compression_loss"],
     ),
@@ -757,7 +757,7 @@ def check_ovmodel_reshaping(self, ovmodel: OVModel):
     "quantization,unstructured_movement_sparsity": OVTrainerTestDescriptor(
         model_id="hf-internal-testing/tiny-random-Wav2Vec2Model",
         nncf_compression_config=[QUANTIZATION_CONFIG_FOR_WAV2VEC2, UNSTRUCTURED_MOVEMENT_SPARSITY_CONFIG_FOR_WAV2VEC2],
-        expected_fake_quantize=48,
+        expected_fake_quantize=40,
         expected_int8=30,
         expected_binary_masks=48,
         compression_metrics=["compression_loss"],
@@ -775,7 +775,7 @@ def check_ovmodel_reshaping(self, ovmodel: OVModel):
         model_id="hf-internal-testing/tiny-random-Wav2Vec2Model",
         teacher_model_id="hf-internal-testing/tiny-random-Wav2Vec2Model",
         nncf_compression_config=[QUANTIZATION_CONFIG_FOR_WAV2VEC2, UNSTRUCTURED_MOVEMENT_SPARSITY_CONFIG_FOR_WAV2VEC2],
-        expected_fake_quantize=48,
+        expected_fake_quantize=40,
         expected_int8=30,
         expected_binary_masks=48,
         compression_metrics=["compression_loss", "distillation_loss", "task_loss"],