Save & Load TensorFlow Models: Complete Guide

In TensorFlow, you can use the tf.train.Saver class to save and load a model. Here are the steps for saving and loading a TensorFlow model:

1. Save model:

import tensorflow as tf

# 创建一个Saver对象
saver = tf.train.Saver()

with tf.Session() as sess:
    # 训练模型

    # 保存模型
    saver.save(sess, "model.ckpt")

1. Load model:

import tensorflow as tf

# 创建一个Saver对象
saver = tf.train.Saver()

with tf.Session() as sess:
    # 加载模型
    saver.restore(sess, "model.ckpt")

    # 使用加载的模型进行推理或继续训练

When saving the model, you have the option to save it as a .ckpt file or a .pb file. The .ckpt file stores the model’s weights and variables, while the .pb file stores the entire computational graph.

Please ensure that the same computational graph structure has been built when loading the model.