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
code: def _add_metric(self, state):
      from pycm import ConfusionMatrix
  
      def make_cm(y_pred, y_true):
          _, y_pred = torch.max(y_pred, 1)
          cm = ConfusionMatrix(
              y_true.cpu().numpy(), y_pred.cpu().numpy(), **self.kwargs
          )
          for handler in self._handlers:
              handler(cm, state)
  
      my_metric = EpochLambda("pycm", make_cm, False)
      my_metric.reset(state)
      state[torchbearer.METRIC_LIST] = MetricList(
          [state[torchbearer.METRIC_LIST], my_metric]
      )
  
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 2 for calling the PyCM obj's underlying member method code with example usage: obj._add_metric(state) without return types