code: def modify_schema(self):
      super().modify_schema()
      self.schema["models"].keys += ["generator"]
      self.schema["models"].essential += ["generator"]
      self.schema["loss_funcs"].keys += ["synth_loss", "g_adv_loss"]
      self.schema["loss_funcs"].essential += [
          "synth_loss",
          "g_adv_loss",
      ]
      self.schema["mining_funcs"].keys += ["synth_packaged_as_triplets"]
  
imports: import copy
  import torch
  from ..distances import LpDistance
  from ..losses import TripletMarginLoss
  from ..miners import EmbeddingsAlreadyPackagedAsTriplets
  from ..utils import common_functions
  from ..utils import loss_and_miner_utils
  from .train_with_classifier import TrainWithClassifier
label_desc: Use image node_id 8 for calling the DeepAdversarialMetricLearning obj's underlying member method code with example usage: obj.modify_schema() without return types