parsing a tfrecord file to compute image mean

import tensorflow as tf
import numpy as np

sess = tf.Session()
init_op = tf.group(tf.global_variables_initializer(), tf.local_variables_initializer())
sess.run(init_op)

def compute_mean_op():
    count = 0
    image_sum = tf.zeros([32,32,32,3], dtype=tf.float64)
    for example in tf.python_io.tf_record_iterator('train.tfrecords'):
        features = tf.parse_single_example(example, features={'image_raw':tf.FixedLenFeature([], tf.string)})
        image = tf.decode_raw(features['image_raw'], tf.uint8)
        image = tf.cast(image, tf.float64)
        image_sum += tf.reshape(image, [32, 32, 32, 3])
        count += 1
        if count%1000==0:
            print(count)
    return count, image_sum