import tensorflow as tf
 
v1= tf.Variable(tf.random_normal([784, 200], stddev=0.35), name="v1")
v2= tf.Variable(tf.zeros([200]), name="v2")
saver = tf.train.Saver()
with tf.Session() as sess:
 init_op = tf.global_variables_initializer()
 sess.run(init_op)
 saver.save(sess,"checkpoint/model_test",global_step=1)

import tensorflow as tf
 
v1= tf.Variable(tf.random_normal([784, 200], stddev=0.35), name="v1")
v2= tf.Variable(tf.zeros([200]), name="v2")
saver = tf.train.Saver()
with tf.Session() as sess:
 # init_op = tf.global_variables_initializer()
 # sess.run(init_op)
 saver.restore(sess, "checkpoint/model_test-1")
 # saver.save(sess,"checkpoint/model_test",global_step=1)

import tensorflow as tf
 
v1= tf.Variable(tf.random_normal([784, 200], stddev=0.35), name="v1")
v2= tf.Variable(tf.zeros([200]), name="v2")
v3= tf.Variable(tf.zeros([100]), name="v3")
#saver = tf.train.Saver()
saver1 = tf.train.Saver([v1])
saver2 = tf.train.Saver([v2]+[v3])
with tf.Session() as sess:
 # init_op = tf.global_variables_initializer()
 # sess.run(init_op)
 saver1.restore(sess, "checkpoint/model_test-1")
 saver2.restore(sess, "checkpoint/model_test-1")
 # saver.save(sess,"checkpoint/model_test",global_step=1)