Run this to be sure output and input (adaptive) softmax weights are tied

def tie_weights(self):
        """ Run this to be sure output and input (adaptive) softmax weights are tied """
        # sampled softmax
        if self.sample_softmax > 0:
            if self.config.tie_weight:
                self.out_layer.weight = self.transformer.word_emb.weight
        # adaptive softmax (including standard softmax)
        else:
            if self.config.tie_weight:
                for i in range(len(self.crit.out_layers)):
                    self.crit.out_layers[i].weight = self.transformer.word_emb.emb_layers[i].weight
            if self.config.tie_projs:
                for i, tie_proj in enumerate(self.config.tie_projs):
                    if tie_proj and self.config.div_val == 1 and self.config.d_model != self.config.d_embed:
                        self.crit.out_projs[i] = self.transformer.word_emb.emb_projs[0]
                    elif tie_proj and self.config.div_val != 1:
                        self.crit.out_projs[i] = self.transformer.word_emb.emb_projs[i]