code: def test_master_maintain_weights_from_master_to_model(self):
      self._generate_inner_optim(False)
      self._pseudo_step(self.fp16_optim.inner_optimizer.param_groups)
      self._is_all_float(self.fp16_optim.inner_optimizer.param_groups)
      self._is_all_half(self.fp16_optim.param_groups)
      self.fp16_optim.weights_update_needed = True
      self.fp16_optim._weights_from_master_to_model()
      self._is_all_half(self.fp16_optim.param_groups)
      self._is_all_float(self.fp16_optim.inner_optimizer.param_groups)
      self._is_weight_equal(
          self.fp16_optim.param_groups,
          self.fp16_optim.inner_optimizer.param_groups,
      )
  
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 5 for calling the TestFp16Optimizer obj's underlying member method code with example usage: obj.test_master_maintain_weights_from_master_to_model() without return types