def initialize()

in recompute_svrg.py [0:0]


    def initialize(self):
        for group in self.param_groups:
            for p in group['params']:
                momentum = group['momentum']

                param_state = self.state[p]

                if 'gavg' not in param_state:
                    param_state['gavg'] =  p.data.double().clone().zero_()
                    param_state['gi'] = p.data.clone().zero_()
                    param_state['gi_debug'] = p.data.clone().zero_()

                if momentum != 0:
                    if 'momentum_buffer' not in param_state:
                        buf = param_state['momentum_buffer'] = p.data.clone().zero_()

                if 'tilde_x' not in param_state:
                    param_state['tilde_x'] = p.data.clone()
                    param_state['xk'] = p.data.clone()

        # Batch norm's activation running_mean/var variables
        state = self.model.state_dict()
        for skey in state.keys():
            if skey.endswith(".running_mean") or skey.endswith(".running_var"):
                self.running_tmp[skey] = state[skey].clone()