code: def _pseudo_backward(self, param_groups):
      for p in self._generate_params(param_groups):
          p.grad = None
          p = p.float()
          y = p * p * 3
          z = y.mean()
          z.backward()
  
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import copy
  import unittest
  import torch
  from pytext.optimizer import fp16_optimizer
  from torch.autograd import Variable
label_desc: Use image node_id 22 for calling the TestFp16Optimizer obj's underlying member method code with example usage: obj._pseudo_backward(param_groups) without return types