Exploring queue tensorflow 1

tf_queue1.py

import numpy as np
import tensorflow as tf

NUM_THREADS = 4

data = np.array([[0.2, 0.3], [0.4, 0.9], [0.8, -1.2], [-1.3, -0.2]])
target = np.array([1, 0, 1, 0])

queue = tf.FIFOQueue(capacity=3,
                     dtypes=[tf.float32, tf.int32],
                     shapes=[[2], []])

enqueue_op = queue.enqueue_many([data, target])
data_sample, label_sample = queue.dequeue()

qr = tf.train.QueueRunner(queue, [enqueue_op] * NUM_THREADS)
with tf.Session() as sess:
    coord = tf.train.Coordinator()
    enqueue_threads = qr.create_threads(sess, coord=coord, start=True)
    try:
        for step in range(8):
            if coord.should_stop():
                break
            data_batch, label_batch = sess.run([data_sample, label_sample])
            print("step = {}, x ={}, y={}".format(step, data_batch, label_batch))
    except Exception as e:
            print("Exception")
            coord.request_stop()
    finally:
        coord.request_stop()
        coord.join(enqueue_threads)