class_docstr: The abstract class representing a metric which can be accumulated at each batch and calculated at the end
  of the epoch.
docstr: Update the current state of the metric. This method has to be implemented if the metric is used as an **epoch
  metric**. If used as a batch metric, it does not need to be implemented.
  
  Args:
      y_pred: The prediction of the model.
      y_true: Target to evaluate the model.
code: def update(self, y_pred, y_true) -> None:
      """
      Update the current state of the metric. This method has to be implemented if the metric is used as an **epoch
      metric**. If used as a batch metric, it does not need to be implemented.
  
      Args:
          y_pred: The prediction of the model.
          y_true: Target to evaluate the model.
      """
      raise NotImplementedError
  
file_path: poutyne/poutyne/framework/metrics/base.py
imports: from abc import ABC, abstractmethod
  import torch.nn
label_desc: Use image node_id 2 for calling the Metric obj's underlying member method code with example usage: obj.update(y_pred, y_true) without return types