class_docstr: Wrap timm.scheduler.CosineLRScheduler so we can call scheduler.step() without passing in epoch.
  It supports resuming as well.
code: def __init__(self, *args, **kwargs):
      super().__init__(*args, **kwargs)
      self._last_epoch = -1
      self.step(epoch=0)
  
file_path: flash-attention/training/src/optim/timm_lr_scheduler.py
imports: import torch
  from torch.optim import Optimizer
  from timm.scheduler import CosineLRScheduler
label_desc: Use image node_id 1 to create a new TimmCosineLRScheduler object from inherited base classes: CosineLRScheduler, torch.optim.lr_scheduler with example: obj = TimmCosineLRScheduler()