code: def make_output_human_readable(self, output_dict):
      preds = output_dict["probs"]
      if len(preds.shape) == 1:
          output_dict["probs"] = preds.unsqueeze(0)
          output_dict["logits"] = output_dict["logits"].unsqueeze(0)
  
      classes = []
      for prediction in output_dict["probs"]:
          label_idx = prediction.argmax(dim=-1).item()
          output_dict["loss"] = self._loss(
              output_dict["logits"], torch.LongTensor([label_idx])
          )
          label_str = str(label_idx)
          classes.append(label_str)
      output_dict["label"] = classes
      return output_dict
  
file_path: allennlp/allennlp/common/testing/interpret_test.py
imports: from allennlp.predictors import TextClassifierPredictor
  from allennlp.models.model import Model
  import torch
label_desc: Use image node_id 3 for calling the FakeModelForTestingInterpret obj's underlying member method code with example usage: obj.make_output_human_readable(output_dict) and returns: output_dict