class_docstr: Args:
      monitor (str): The quantity to monitor. (Default value = 'val_loss')
  See:
      :class:`~torch.optim.lr_scheduler.ReduceLROnPlateau`
class_docstr_tok: ["Args",":","monitor","(","str",")",":","The","quantity","to","monitor",".","(","Default","value","=","'val_loss","'",")","See",":",":","class",":","`","~torch.optim.lr_scheduler.ReduceLROnPlateau","`"]
code: def __init__(self, *args, monitor: str = "val_loss", **kwargs):
      super().__init__(
          torch_lr_scheduler=torch.optim.lr_scheduler.ReduceLROnPlateau,
          *args,
          **kwargs,
      )
      self.monitor = monitor
  
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 1 to create a new ReduceLROnPlateau object from inherited base classes: _PyTorchLRSchedulerWrapper with example: obj = ReduceLROnPlateau()