def load_pretrain_embedding(goods_path, seller_path):model = build_model()goods_model = tf.keras.models.load_model(goods_path) # 预训练模型for i, pretrain_layer in enumerate(goods_model.layers):if isinstance(pretrain_layer, tf.keras.layers.Embedding) and pretrain_layer.name=='pretrain_goods_embedding':for layer in model.layers: # 新模型if isinstance(layer, tf.keras.layers.Embedding) and layer.name=='pretrain_goods_embedding':weights = goods_model.get_layer(index=i).get_weights()assert len(weights) == 1layer.set_weights(weights) # 赋权重return model