docstr: Utility method to generate additional blobs for human readable result for
  models that use explicit labels.
docstr_tok: ["Utility","method","to","generate","additional","blobs","for","human","readable","result","for","models","that","use","explicit","labels","."]
code: def gen_additional_blobs(
      predict_net: core.Net,
      probability_out,
      model_out: torch.Tensor,
      output_name: str,
      label_names: List[str],
  ) -> List[core.BlobReference]:
      """
      Utility method to generate additional blobs for human readable result for
      models that use explicit labels.
      """
      res = []
      tmp_out_score = predict_net.Log(probability_out)
      label_scores = predict_net.Split(
          tmp_out_score, label_names, axis=model_out.dim() - 1
      )
  
      # Make sure label_scores is iterable
      if not isinstance(label_scores, tuple):
          label_scores = (label_scores,)
      for name, label_score in zip(label_names, label_scores):
          res.append(
              predict_net.Copy(
                  label_score, "{}:{}".format(output_name, name)
              )
          )
      return res
  
imports: from typing import List
  import torch
  from caffe2.python import core
  from torch import Tensor
label_desc: Use image node_id 1 for calling the OutputLayerUtils obj's underlying member method code with example usage: obj.gen_additional_blobs(predict_net, probability_out, model_out, output_name, label_names) and returns: res