code: def evaluate_batch(self, batch):
      data = labels = batch
      loss = torch.nn.MSELoss()(self.model(data), labels)
      return {"loss": loss}
  
file_path: determined/harness/tests/experiment/fixtures/ancient-checkpoints/0.17.7-pytorch/code/model_def.py
imports: import torch
  from torch import nn
  from determined import pytorch
label_desc: Use image node_id 3 for calling the OneVarPytorchTrial obj's underlying member method code with example usage: obj.evaluate_batch(batch) and returns: dict