code: def scale_clip(self):
      if self.get_scale() == self.max_scale:
          self.set_growth_factor(1)
      elif self.get_scale() < self.max_scale:
          self.set_growth_factor(2)
      elif self.get_scale() > self.max_scale:
          self._scale.fill_(self.max_scale)
          self.set_growth_factor(1)
  
file_path: insightface/recognition/vpl/utils/utils_amp.py
imports: from typing import Dict, List
  import torch
  from torch._six import container_abcs
  from torch.cuda.amp import GradScaler
label_desc: Use image node_id 2 for calling the MaxClipGradScaler obj's underlying member method code with example usage: obj.scale_clip() without return types