docstr: Clears the gradients of all optimized parameters.
docstr_tok: ["Clears","the","gradients","of","all","optimized","parameters","."]
code: def zero_grad(self):
      """Clears the gradients of all optimized parameters."""
      for p in self.fp16_params:
          p.grad = None
      self._needs_sync = False
  
imports: from itertools import chain
  import torch
  from fairseq import utils
  from fairseq.optim.fp16_optimizer import DynamicLossScaler
label_desc: Use image node_id 10 for calling the Fairseq_FP16OptimizerMixin obj's underlying member method code with example usage: obj.zero_grad() without return types