code: def evaluate_batch(
      self,
      dataloader_iter: Optional[Iterator[pytorch.TorchData]],
      batch_idx: int,
  ) -> Dict[str, Any]:
      loss = self.model.eval_batch(dataloader_iter)
      return {"loss": loss}
  
imports: from typing import Any, Dict, Iterator, Optional, Tuple, Union
  import attrdict
  import deepspeed
  import deepspeed.runtime.dataloader
  import numpy
  import torch
  import determined.pytorch.deepspeed
  import tests.experiment.fixtures.pytorch_counter_callback
  from determined import pytorch
label_desc: Use image node_id 3 for calling the LinearPipelineEngineTrial obj's underlying member method code with example usage: obj.evaluate_batch(dataloader_iter, batch_idx) and returns: dict