class_docstr: Default class for the LR scheduling callback. Proposes default comportment for the scheduler
  loading and saving as well as for the epoch end handling.
class_docstr_tok: ["Default","class","for","the","LR","scheduling","callback",".","Proposes","default","comportment","for","the","scheduler","loading","and","saving","as","well","as","for","the","epoch","end","handling","."]
code: def on_train_begin(self, logs: Dict):
      self.scheduler = self.torch_lr_scheduler(
          self.model.optimizer, *self.args, **self.kwargs
      )
  
      # Load state if the scheduler was not initialized when the user asked
      # to load its state
      if self.state_to_load is not None:
          self.load_state_dict(self.state_to_load)
          self.state_to_load = None
  
file_path: poutyne/poutyne/framework/callbacks/lr_scheduler.py
imports: import inspect
  import sys
  from typing import BinaryIO, Dict
  import torch.optim.lr_scheduler
  from torch.optim import Optimizer
  from poutyne.framework.callbacks.callbacks import Callback
label_desc: Use image node_id 3 for calling the _PyTorchLRSchedulerWrapper obj's underlying member method code with example usage: obj.on_train_begin(logs) without return types