code: def __init__(
      self,
      stop_after: float,
      target: str,
      dtype_dict: Dict[str, str],
      input_cols: List[str],
      timeseries_settings: TimeseriesSettings,
      target_encoder: BaseEncoder,
      net: str,
      fit_on_dev: bool,
      search_hyperparameters: bool,
  ):
      super().__init__(
          stop_after,
          target,
          dtype_dict,
          input_cols,
          timeseries_settings,
          target_encoder,
          net,
          fit_on_dev,
          search_hyperparameters,
      )
  
      quantum_nets = {"QClassic": QClassicNet}
      self.net_class = quantum_nets.get(net, QClassicNet)
  
file_path: lightwood/lightwood/mixer/qclassic.py
imports: from typing import Dict, List
  from lightwood.encoder.base import BaseEncoder
  from lightwood.mixer.neural import Neural
  from lightwood.mixer.helpers.qclassic_net import QClassicNet
  from lightwood.api.types import TimeseriesSettings
label_desc: Use image node_id 1 to create a new QClassic object from inherited base classes: Neural with example: obj = QClassic(stop_after, target, dtype_dict, input_cols, timeseries_settings, target_encoder, net, fit_on_dev, search_hyperparameters)