code: def __init__(self, model_name: Optional[str] = None):
      super().__init__()
      self.model = None
      self.data = None
      self.converted_models = None
      self.model_params = None
      self.device = None
      self.model_name = model_name or "temp"
  
imports: import abc
  from pathlib import Path
  from typing import Optional, List, Union
  from nebullvm.core.models import DeviceType, DeepLearningFramework, ModelParams
  from nebullvm.operations.base import Operation
  from nebullvm.operations.conversions.pytorch import convert_torch_to_onnx
  from nebullvm.operations.conversions.tensorflow import convert_tf_to_onnx
  from nebullvm.optional_modules.onnx import onnx
  from nebullvm.optional_modules.tensorflow import tensorflow
  from nebullvm.optional_modules.torch import torch
  from nebullvm.tools.data import DataManager
label_desc: Use image node_id 1 to create a new Converter object from inherited base classes: Operation, abc with example: obj = Converter(model_name)