code: def evaluate_batch(
      self, batch: pytorch.TorchData, batch_idx: int
  ) -> Dict[str, Any]:
      batch_data, labels = batch
  
      output = self.model(batch_data)
      validation_loss = self.loss_fn(output, labels).item()
  
      pred = output.argmax(dim=1, keepdim=True)
      accuracy = pred.eq(labels.view_as(pred)).sum().item() / len(
          batch_data
      )
  
      return {"validation_loss": validation_loss, "accuracy": accuracy}
  
file_path: determined/harness/tests/experiment/fixtures/pytorch_amp/train.py
imports: import logging
  import pathlib
  from typing import Any, Dict
  import data
  import model
  import torch
  from ruamel import yaml
  from torch import nn
  import determined
  from determined import pytorch
label_desc: Use image node_id 5 for calling the MNistTrial obj's underlying member method code with example usage: obj.evaluate_batch(batch, batch_idx) and returns: dict