code: def _validate(self, *data):
      self.model.generative()
      _ = self.model(*data)
      self.metrics.valid.src.bc_loss.update(self.model.src.bc_loss)
      self.metrics.valid.src.fc_loss.update(self.model.src.fc_loss)
      self.metrics.valid.tgt.bc_loss.update(self.model.tgt.bc_loss)
      self.metrics.valid.tgt.fc_loss.update(self.model.tgt.fc_loss)
  
imports: from typing import Callable, Optional, List, Tuple, Dict, Union
  from functools import partial
  from itertools import chain
  from pathlib import Path
  from torch import Tensor, BoolTensor
  from torch.utils.data import Dataset
  from torch.optim import AdamW
  import numpy
  from tslib.dataset import MetaDataset
  from tslib.engine import Trainer, Evaluator, HyperOptManager
  from tslib.engine.distributed import reduce_value, is_main_process
  from tslib.engine.callback import *
  from tslib.metrics import NumericalAverageMeter, BatchAverageMeter, MeanDeviationMeter, MeterDict
  from ..estimator import DomAdaptEstimator, AdversarialDomAdaptEstimator
label_desc: Use image node_id 3 for calling the AdversarialDomAdaptTrainer obj's underlying member method code with example usage: obj._validate() without return types