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."""
      self.wrapped_optimizer.zero_grad()
      self._grads_are_scaled = 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 9 for calling the Fairseq_MemoryEfficientFP16OptimizerMixin obj's underlying member method code with example usage: obj.zero_grad() without return types