docstr: Evaluate one batch.
  
  Arguments
  ---------
  batch : list of torch.Tensors
      Batch of data to use for evaluation. Default implementation assumes
      this batch has two elements: inputs and targets.
  stage : Stage
      The stage of the experiment: Stage.VALID, Stage.TEST
  
  Returns
  -------
  detached loss
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code: def evaluate_batch(self, batch, stage):
      """Evaluate one batch.
  
      Arguments
      ---------
      batch : list of torch.Tensors
          Batch of data to use for evaluation. Default implementation assumes
          this batch has two elements: inputs and targets.
      stage : Stage
          The stage of the experiment: Stage.VALID, Stage.TEST
  
      Returns
      -------
      detached loss
      """
      out = self.compute_forward(batch, stage=stage)
      loss = self.compute_objectives(out, batch, stage=stage)
      loss_g = loss["G_loss"]
      return loss_g.detach().cpu()
  
imports: import sys
  import copy
  import random
  import pathlib
  from hyperpyyaml import load_hyperpyyaml
  import speechbrain
  from speechbrain.utils.data_utils import scalarize
  import torch
  import torchaudio
  import numpy
label_desc: Use image node_id 4 for calling the HifiGanBrain obj's underlying member method code with example usage: obj.evaluate_batch(batch, stage) and returns: loss_g