class_docstr: Create confusion matrices using the `PyCM library <https://github.com/sepandhaghighi/pycm>`_.
  
  Args:
      kwargs: Additional keyword args to pass to the `ConfusionMatrix` call
docstr: Process this callback for training batches
  
  Returns:
      PyCM: self
docstr_tok: ["Process","this","callback","for","training","batches","Returns",":","PyCM",":","self"]
code: def on_train(self):
      """Process this callback for training batches
  
      Returns:
          PyCM: self
      """
      _old_start_training = self.on_start_training
  
      def wrapper(state):
          _old_start_training(state)
          self._add_metric(state)
  
      self.on_start_training = wrapper
      return self
  
imports: from __future__ import print_function
  import torch
  import torchbearer
  from torchbearer import Callback
  from torchbearer.bases import cite
  from torchbearer.metrics import EpochLambda, MetricList
label_desc: Use image node_id 3 for calling the PyCM obj's underlying member method code with example usage: obj.on_train() and returns: self