class_docstr: Hierarchical Attention Network (RNN baseline model)
docstr: Test and collect stats
code: def test_step(self, batch, batch_idx):
      """Test and collect stats"""
      ## 1. ENCODER-DECODER
      predicted = self(batch)
      ## 2. LOSS
      targets = self.transform_targets(batch["target"])
      loss = self.loss(predicted, target=targets)
  
      ## 3. METRICS
      self.log_metrics(
          predictions=predicted.detach(),
          targets=targets.detach(),
          loss=loss.detach(),
          stage="test",
          on_step=False,
          on_epoch=True,
      )
  
      return predicted.detach(), targets.detach()
  
imports: from turtle import hideturtle
  import pytorch_lightning
  import torch
  import torch.nn.functional
  import torch.nn
  from pytorch_lightning import seed_everything
  from pathlib import Path
  from src.transformer.transformer_utils import *
  from src.transformer.metrics import CorrectedBAcc, CorrectedF1, CorrectedMCC, AUL
  import torchmetrics
label_desc: Use image node_id 10 for calling the FFN obj's underlying member method code with example usage: obj.test_step(batch, batch_idx) and returns: predicted,  targets