class_docstr: The :class:`AdvancedMetric` class is a metric which provides different process methods for training and
  validation. This enables running metrics which do not output intermediate steps during validation.
  
  Args:
      name (str): The name of the metric.
class_docstr_tok: ["The",":","class",":","`","AdvancedMetric","`","class","is","a","metric","which","provides","different","process","methods","for","training","and","validation",".","This","enables","running","metrics","which","do","not","output","intermediate","steps","during","validation",".","Args",":","name","(","str",")",":","The","name","of","the","metric","."]
docstr: Put the metric in train mode.
          
docstr_tok: ["Put","the","metric","in","train","mode","."]
code: def train(self):
      """Put the metric in train mode."""
      self._process = self.process_train
      self._process_final = self.process_final_train
  
imports: import inspect
  from torchbearer import Metric, no_grad
label_desc: Use image node_id 9 for calling the AdvancedMetric obj's underlying member method code with example usage: obj.train() without return types