import tensorflow as tf 
import time 
from datetime import datetime 
import numpy as np

FLAGS = tf.app.flags.FLAGS
tf.app.flags.DEFINE_bool('cluster', False, '')

def log(obj):
    print datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')[:-3], obj


def main(_):
    server = tf.train.Server.create_local_server()
    raw_shape = [576, 3, 220, 220]
    shape = tf.TensorShape(raw_shape)
    if FLAGS.cluster:
        sess = tf.Session(server.target)
    else:
        sess = tf.Session()
    with tf.device('/cpu:0'): 
        q = tf.FIFOQueue(10, tf.float32, shape, name = 'Q', shared_name = 'share_queue')
        rand_data = tf.zeros(shape)
        init_op = tf.initialize_local_variables()
        sess.run(init_op)
        result = q.dequeue()
        x = tf.placeholder(tf.float32, shape, 'data')
        enqueue_op = q.enqueue(x)
        while True:
            time.sleep(1)
            log('pushing')
            sess.run(enqueue_op, feed_dict = {x: np.zeros(raw_shape)})
            log('push done')
            sess.run(result)
            log('pop done')

if __name__ == '__main__':
    tf.logging.set_verbosity(tf.logging.INFO)
    tf.app.run()