class_docstr: Draws a learning curve with training & validation metrics
  over time as the network trains.
class_docstr_tok: ["Draws","a","learning","curve","with","training","&","validation","metrics","over","time","as","the","network","trains","."]
docstr: Update selected dataframe after a completed batch
  Parameters
  ----------
  df_name : str
      Selected dataframe name needs to be modified.
code: def _process_batch(self, param, df_name):
      """Update selected dataframe after a completed batch
      Parameters
      ----------
      df_name : str
          Selected dataframe name needs to be modified.
      """
      if param.eval_metric is not None:
          metrics = dict(param.eval_metric.get_name_value())
          param.eval_metric.reset()
      else:
          metrics = {}
      metrics["elapsed"] = datetime.datetime.now() - self.start_time
      for key, value in metrics.items():
          if key not in self._data[df_name]:
              self._data[df_name][key] = []
          self._data[df_name][key].append(value)
  
imports: import time
label_desc: Use image node_id 6 for calling the LiveLearningCurve obj's underlying member method code with example usage: obj._process_batch(param, df_name) without return types