code: def custom_setup(self):
      synth_packaged_as_triplets = EmbeddingsAlreadyPackagedAsTriplets()
      self.mining_funcs[
          "synth_packaged_as_triplets"
      ] = synth_packaged_as_triplets
      self.loss_names += ["g_hard_loss", "g_reg_loss"]
  
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 2 for calling the DeepAdversarialMetricLearning obj's underlying member method code with example usage: obj.custom_setup() without return types