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.
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docstr: Process the given state and return the metric value for a training iteration.
  
  Returns:
      The metric value for a training iteration.
docstr_tok: ["Process","the","given","state","and","return","the","metric","value","for","a","training","iteration",".","Returns",":","The","metric","value","for","a","training","iteration","."]
code: def process_train(self, *args):
      """Process the given state and return the metric value for a training iteration.
  
      Returns:
          The metric value for a training iteration.
      """
      pass
  
imports: import inspect
  from torchbearer import Metric, no_grad
label_desc: Use image node_id 2 for calling the AdvancedMetric obj's underlying member method code with example usage: obj.process_train() without return types