code: def clip_grad_norm(self, max_norm, model=None):
      if max_norm is None:
          """incase max_norm is none we don't compute clip_grad_norm."""
          return None
      elif model is None:
          """Some callers are passing max_norm only instead of both the args.
          For those we treat model as max_norm.
          eg. optimizer.clip_grad_norm(max_norm)
          """
          return clip_grad_norm_(self.params, max_norm)
      else:
          return clip_grad_norm_(model.parameters(), max_norm)
  
imports: import torch
  from fairseq.utils import clip_grad_norm_
  from pytext.config import ConfigBase
  from pytext.config.component import Component, ComponentType
label_desc: Use image node_id 2 for calling the Optimizer obj's underlying member method code with example usage: obj.clip_grad_norm(max_norm, model) and returns: None, clip_grad_norm_, clip_grad_norm_