import tensorflow as tf
import numpy as np
# Create two variables.
x_data = http://www.mamicode.com/np.float32([1,2,3,4,5,6,7,8,9,0])
weights = tf.Variable(tf.random_normal([10, 1], stddev=0.35), name="weights")
biases = tf.Variable(tf.zeros([1]), name="biases")
y = tf.matmul(x_data.reshape((1,-1)), weights)+biases
# Add an op to initialize the variables.
init_op = tf.global_variables_initializer()
saver = tf.train.Saver()
# Later, when launching the model
with tf.Session() as sess:
    # Run the init operation.
    sess.run(init_op)
    y_ = sess.run(y)
    print(y_)
    save_path = saver.save(sess, "./tmp/model.ckpt")
    print("Model saved in file: ", save_path)

import tensorflow as tf
import numpy as np
# Create two variables.
x_data = http://www.mamicode.com/np.float32([1,2,3,4,5,6,7,8,9,0])
weights = tf.Variable(tf.random_normal([10, 1], stddev=0.35), name="weights")
biases = tf.Variable(tf.zeros([1]), name="biases")
y = tf.matmul(x_data.reshape((1,-1)), weights)+biases
saver = tf.train.Saver()
# Later, when launching the model
with tf.Session() as sess:
    saver.restore(sess, ‘./tmp/model.ckpt‘)
    y_ = sess.run(y)
    print(y_)