import tensorflow as tf

import os
#dir = os.path.dirname(os.path.realpath(__file__))

# First, you design your mathematical operations
# We are the default graph scope


tf.app.flags.DEFINE_string("train_dir",'./models/',"model direction")
FLAGS = tf.app.flags.FLAGS


train_dir = FLAGS.train_dir


# Let's design a variable
with tf.name_scope('Model'):
    v1= tf.Variable(1. , name="v1")
    v2 = tf.Variable(2. , name="v2")
    # Let's design an operation
    a = tf.add(v1, v2, name="add")


saver = tf.train.Saver() 

# By default the Session handles the default graph and all its included variables
with tf.Session() as sess:  
  sess.run(tf.global_variables_initializer())

  saver.save(sess, train_dir+"simple_model")

a0a2a97ec3211384ec0eed8a37cb8636ff877b2f
<mask token>

<mask token>
tf.app.flags.DEFINE_string('train_dir', './models/', 'model direction')
<mask token>
with tf.name_scope('Model'):
    v1 = tf.Variable(1.0, name='v1')
    v2 = tf.Variable(2.0, name='v2')
    a = tf.add(v1, v2, name='add')
<mask token>
with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())
    saver.save(sess, train_dir + 'simple_model')

<mask token>
tf.app.flags.DEFINE_string('train_dir', './models/', 'model direction')
FLAGS = tf.app.flags.FLAGS
train_dir = FLAGS.train_dir
with tf.name_scope('Model'):
    v1 = tf.Variable(1.0, name='v1')
    v2 = tf.Variable(2.0, name='v2')
    a = tf.add(v1, v2, name='add')
saver = tf.train.Saver()
with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())
    saver.save(sess, train_dir + 'simple_model')

import tensorflow as tf
import os
tf.app.flags.DEFINE_string('train_dir', './models/', 'model direction')
FLAGS = tf.app.flags.FLAGS
train_dir = FLAGS.train_dir
with tf.name_scope('Model'):
    v1 = tf.Variable(1.0, name='v1')
    v2 = tf.Variable(2.0, name='v2')
    a = tf.add(v1, v2, name='add')
saver = tf.train.Saver()
with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())
    saver.save(sess, train_dir + 'simple_model')

import tensorflow as tf

import os
#dir = os.path.dirname(os.path.realpath(__file__))

# First, you design your mathematical operations
# We are the default graph scope


tf.app.flags.DEFINE_string("train_dir",'./models/',"model direction")
FLAGS = tf.app.flags.FLAGS


train_dir = FLAGS.train_dir


# Let's design a variable
with tf.name_scope('Model'):
    v1= tf.Variable(1. , name="v1")
    v2 = tf.Variable(2. , name="v2")
    # Let's design an operation
    a = tf.add(v1, v2, name="add")


saver = tf.train.Saver() 

# By default the Session handles the default graph and all its included variables
with tf.Session() as sess:  
  sess.run(tf.global_variables_initializer())

  saver.save(sess, train_dir+"simple_model")
