code: def __init__(self, model_type: ForwardForwardModelType):
      super().__init__()
  
      if model_type is ForwardForwardModelType.PROGRESSIVE:
          self.build_model = FCNetFFProgressiveBuildOperation()
          self.train_model = ForwardForwardTrainer()
          self.load_data = MNISTDataLoaderOperation()
      elif model_type is ForwardForwardModelType.RECURRENT:
          self.build_model = RecurrentFCNetFFBuildOperation()
          self.train_model = RecurrentForwardForwardTrainer()
          self.load_data = MNISTDataLoaderOperation()
      elif model_type is ForwardForwardModelType.NLP:
          self.build_model = LMFFNetBuildOperation()
          self.train_model = NLPForwardForwardTrainer()
          self.load_data = AesopFablesDataLoaderOperation()
  
file_path: nebuly/optimization/forward_forward/forward_forward/root_op.py
imports: from enum import Enum
  from nebullvm.operations.base import Operation
  from forward_forward.operations.build_models import FCNetFFProgressiveBuildOperation, RecurrentFCNetFFBuildOperation, LMFFNetBuildOperation
  from forward_forward.operations.data import MNISTDataLoaderOperation, AesopFablesDataLoaderOperation
  from forward_forward.operations.trainers import ForwardForwardTrainer, RecurrentForwardForwardTrainer, NLPForwardForwardTrainer
label_desc: Use image node_id 1 to create a new ForwardForwardRootOp object from inherited base classes: Operation with example: obj = ForwardForwardRootOp(model_type)