def METHOD_NAME(self):
    # (Step-0) Initialize global momentum parameters and store global copy on each gpu
    self.global_params = [torch.zeros_like(p.data) for p in self.params]
    self.smoothed_grads = [p.data.new_zeros(p.data.size()) for p in self.params]
    self.grads = [p.data.new_zeros(p.data.size()) for p in self.params]
    # saving the global model locally for calculating gradient during bmuf sync
    for param, global_param in zip(self.params, self.global_params):
        global_param.copy_(param.data)