Try to fix segfault/bus error by holding onto temp dir

Author: jackzhxng

optimum/executorch/modeling.py

@@ -102,6 +102,30 @@ def __init__(self, models: Dict[str, "ExecuTorchModule"], config: "PretrainedCon
                 setattr(self, key, value)
 
         self.stats = Stats()
+        
+        # Initialize cleanup tracking
+        self._temp_dir = None
+
+    def __del__(self):
+        """Clean up temporary files when the model instance is destroyed."""
+        self._cleanup_temp_resources()
+    
+    def _cleanup_temp_resources(self):
+        """Clean up temporary directory and files."""
+        if hasattr(self, '_temp_dir') and self._temp_dir is not None:
+            try:
+                if hasattr(self._temp_dir, 'cleanup'):
+                    # It's a TemporaryDirectory object
+                    self._temp_dir.cleanup()
+                elif hasattr(self._temp_dir, 'rmtree') or isinstance(self._temp_dir, (str, Path)):
+                    # It's a path
+                    import shutil
+                    shutil.rmtree(self._temp_dir, ignore_errors=True)
+            except Exception:
+                # Ignore cleanup errors to avoid issues during shutdown
+                pass
+            finally:
+                self._temp_dir = None
 
     @abstractmethod
     def forward(self, *args, **kwargs):
@@ -274,7 +298,7 @@ def _export(
         for name, _ in executorch_progs.items():
             models.update(cls._from_pretrained(save_dir_path, file_name=f"{name}.pte", config=config))
 
-        return models
+        return models, save_dir
 
     def _save_pretrained(self, save_directory):
         """
@@ -345,8 +369,9 @@ def from_pretrained(
                 f"Could not infer whether the model was already converted or not to the ExecuTorch IR, keeping `export={export}`.\n{exception}"
             )
 
+        temp_dir = None
         if _export:
-            models_dict = cls._export(
+            models_dict, temp_dir = cls._export(
                 model_id=model_id,
                 config=config,
                 revision=revision,
@@ -376,7 +401,13 @@ def from_pretrained(
                     )
                 )
 
-        return cls(models_dict, config)
+        model_instance = cls(models_dict, config)
+        
+        # Store the TemporaryDirectory reference to prevent GC
+        if temp_dir is not None:
+            model_instance._temp_dir = temp_dir
+            
+        return model_instance
 
 
 class ExecuTorchModelForSeq2SeqLM(ExecuTorchModelBase):