docstr: Clips gradient norm.
docstr_tok: ["Clips","gradient","norm","."]
code: def clip_grad_norm(self, max_norm, aggregate_norm_fn=None):
      """Clips gradient norm."""
      return utils.clip_grad_norm_(
          self.params, max_norm, aggregate_norm_fn
      )
  
imports: import torch
  from fairseq import utils
  from fairseq.dataclass.utils import gen_parser_from_dataclass
  from collections import defaultdict
label_desc: Use image node_id 16 for calling the FairseqOptimizer obj's underlying member method code with example usage: obj.clip_grad_norm(max_norm, aggregate_norm_fn) and returns: utils