Tensorflow:如何保存'DNNRegressorV2‘模型？python

import tensorflow as tf
from tensorflow.estimator import DNNRegressor

# 定义特征列
feature_columns = [tf.feature_column.numeric_column('feature', shape=[1])]
# 创建DNNRegressorV2模型
model = DNNRegressor(feature_columns=feature_columns, hidden_units=[10, 10])
# 定义输入函数
train_input_fn = tf.estimator.inputs.numpy_input_fn(
    x={'feature': train_x},
    y=train_y,
    batch_size=batch_size,
    num_epochs=num_epochs,
    shuffle=True)
# 训练模型
model.train(input_fn=train_input_fn, steps=num_steps)

# 定义保存路径
export_dir = '保存路径'
# 创建特征列解析器
serving_input_fn = tf.estimator.export.build_parsing_serving_input_receiver_fn(
    tf.feature_column.make_parse_example_spec(feature_columns))
# 保存模型
model.export_savedmodel(export_dir, serving_input_receiver_fn=serving_input_fn)