Potential fix for pull request finding

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>

Author: Aishwarya-Tonpe

superbench/benchmarks/micro_benchmarks/_export_torch_to_onnx.py

@@ -18,7 +18,6 @@
 
 class torch2onnxExporter():
     """PyTorch model to ONNX exporter."""
-
     def __init__(self):
         """Constructor."""
         from transformers import BertConfig, GPT2Config, LlamaConfig
@@ -360,7 +359,6 @@ def _build_vision_export_inputs(self, model, batch_size, model_dtype, device):
         dynamic_axes = {'pixel_values': {0: 'batch_size'}, 'output': {0: 'batch_size'}}
 
         class VisionModelWrapper(torch.nn.Module):
-
             def __init__(self, model):
                 super().__init__()
                 self.model = model
@@ -398,7 +396,6 @@ def _build_nlp_export_inputs(self, model, batch_size, seq_length, device):
         }
 
         class NLPModelWrapper(torch.nn.Module):
-
             def __init__(self, model):
                 super().__init__()
                 self.model = model

superbench/benchmarks/micro_benchmarks/huggingface_model_loader.py

@@ -344,7 +344,7 @@ def _get_model_size(self, model: PreTrainedModel) -> float:
         Returns:
             Number of parameters in millions.
         """
-        return float(sum(p.numel() for p in model.parameters())) / 1_000_000
+        return float(sum(p.numel() for p in model.parameters())) / 1_000_000  # type: ignore[attr-defined]
 
     @staticmethod
     def estimate_param_count_from_config(hf_config) -> Optional[int]:

tests/benchmarks/micro_benchmarks/test_huggingface_e2e.py

@@ -28,7 +28,6 @@
 )
 class TestHuggingFaceE2E:
     """End-to-end tests for HuggingFace model loading."""
-
     @pytest.fixture
     def loader(self, tmp_path):
         """Create a loader instance with an isolated per-test cache dir."""