resolve conflicts

huggingface · Aug 5, 2024 · d20301a · d20301a
1 parent 5b17c76
commit d20301a
Showing 1 changed file with 5 additions and 7 deletions.
diff --git a/tests/openvino/test_training.py b/tests/openvino/test_training.py
@@ -383,7 +383,7 @@ def tearDown(self):
             CUSTOMIZED_QUANTIZATION_CONFIG_FOR_BERT,
             STRUCTURED_MOVEMENT_SPARSITY_CONFIG_FOR_BERT,
         ],
-        expected_fake_quantize=44,
+        expected_fake_quantize=22,
         expected_int8=32,
         expected_binary_masks=60,
         compression_metrics=["compression_loss"],
@@ -404,7 +404,7 @@ def tearDown(self):
             CUSTOMIZED_QUANTIZATION_CONFIG_FOR_BERT,
             STRUCTURED_MOVEMENT_SPARSITY_CONFIG_FOR_BERT,
         ],
-        expected_fake_quantize=44,
+        expected_fake_quantize=22,
         expected_int8=32,
         expected_binary_masks=60,
         compression_metrics=["compression_loss", "distillation_loss", "task_loss"],
@@ -436,7 +436,7 @@ def tearDown(self):
             CUSTOMIZED_QUANTIZATION_CONFIG_FOR_BERT,
             UNSTRUCTURED_MOVEMENT_SPARSITY_CONFIG_FOR_BERT,
         ],
-        expected_fake_quantize=44,
+        expected_fake_quantize=22,
         expected_int8=32,
         expected_binary_masks=60,
         compression_metrics=["compression_loss"],
@@ -457,7 +457,7 @@ def tearDown(self):
             CUSTOMIZED_QUANTIZATION_CONFIG_FOR_BERT,
             UNSTRUCTURED_MOVEMENT_SPARSITY_CONFIG_FOR_BERT,
         ],
-        expected_fake_quantize=44,
+        expected_fake_quantize=22,
         expected_int8=32,
         expected_binary_masks=60,
         compression_metrics=["compression_loss", "distillation_loss", "task_loss"],
@@ -479,9 +479,7 @@ def prepare_model_and_dataset(self, desc: OVTrainerTestDescriptor):
         self.num_labels = len(self.dataset["train"].features["label"].names)
 
         self.tokenizer = AutoTokenizer.from_pretrained(desc.model_id)
-        self.model = AutoModelForSequenceClassification.from_pretrained(
-            desc.model_id, num_labels=self.num_labels, attn_implementation="eager"
-        )
+        self.model = AutoModelForSequenceClassification.from_pretrained(desc.model_id, num_labels=self.num_labels)
         self.teacher_model = None
         if desc.teacher_model_id:
             self.teacher_model = AutoModelForSequenceClassification.from_pretrained(