code: def on_start(self, state):
      try:
          self._scheduler = self._scheduler_builder(
              state[torchbearer.OPTIMIZER],
              last_epoch=state[torchbearer.EPOCH] - 1,
          )
      except TypeError:
          self._scheduler = self._scheduler_builder(
              state[torchbearer.OPTIMIZER]
          )
  
      if state[torchbearer.EPOCH] > 0 and self._step_on_batch:
          warnings.warn(
              "Resuming schedulers with the `step_on_batch` option is not currently supported and may cause"
              " unexpected behaviour."
          )
  
imports: import functools
  import warnings
  import torch
  import torchbearer
  from torchbearer.bases import get_metric, _pytorch_version_lt, _pytorch_version_gt
  from torchbearer.callbacks import Callback
label_desc: Use image node_id 3 for calling the TorchScheduler obj's underlying member method code with example usage: obj.on_start(state) without return types