inference.py

#!/usr/bin/env python2
# -*- coding: utf-8 -*-


from __future__ import print_function


import os
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt

import hy_param

from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)

# Pointing the model checkpoint
checkpoint_file = tf.train.latest_checkpoint(os.path.join(hy_param.checkpoint_dir, 'checkpoints'))
saver = tf.train.import_meta_graph("{}.meta".format(checkpoint_file))

# Loading test data
test_data = np.array([mnist.test.images[6]])

# Loading input variable from the model
input_x = tf.get_default_graph().get_operation_by_name("input_x").outputs[0]

# Loading Prediction operation
prediction = tf.get_default_graph().get_operation_by_name("prediction").outputs[0]


with tf.Session() as sess:
    # Restoring the model from the checkpoint
    saver.restore(sess, checkpoint_file)
    
    # Executing the model to make predictions    
    data = sess.run(prediction, feed_dict={input_x: test_data })
    
    print("Predicted digit: ", data.argmax() )


# Display the feed image
print ("Input image:")
plt.gray()
plt.imshow(test_data.reshape([28,28]))