tf.train.batch(

    tensors,

    batch_size,

    num_threads=1,

    capacity=32,

    enqueue_many=False,

    shapes=None,

    dynamic_pad=False,

    allow_smaller_final_batch=False,

    shared_name=None,

    name=None

)

tf.train.slice_input_producer(

    tensor_list,

    num_epochs=None,

    shuffle=True,

    seed=None,

    capacity=32,

    shared_name=None,

    name=None

)

import tensorflow as tf

import numpy as np

# 样本个数

sample_num=5

# 设置迭代次数

epoch_num = 2

# 设置一个批次中包含样本个数

batch_size = 3

# 计算每一轮epoch中含有的batch个数

batch_total = int(sample_num/batch_size)+1

# 生成4个数据和标签

def generate_data(sample_num=sample_num):

    labels = np.asarray(range(0, sample_num))

    images = np.random.random([sample_num, 224, 224, 3])

    print('image size {},label size :{}'.format(images.shape, labels.shape))

    return images,labels

def get_batch_data(batch_size=batch_size):

    images, label = generate_data()

    # 数据类型转换为tf.float32

    images = tf.cast(images, tf.float32)

    label = tf.cast(label, tf.int32)

    #从tensor列表中按顺序或随机抽取一个tensor准备放入文件名称队列

    input_queue = tf.train.slice_input_producer([images, label], num_epochs=epoch_num, shuffle=False)

    #从文件名称队列中读取文件准备放入文件队列

    image_batch, label_batch = tf.train.batch(input_queue, batch_size=batch_size, num_threads=2, capacity=64, allow_smaller_final_batch=False)

    return image_batch, label_batch

image_batch, label_batch = get_batch_data(batch_size=batch_size)

with tf.Session() as sess:

    # 先执行初始化工作

    sess.run(tf.global_variables_initializer())

    sess.run(tf.local_variables_initializer())

    # 开启一个协调器

    coord = tf.train.Coordinator()

    # 使用start_queue_runners 启动队列填充

    threads = tf.train.start_queue_runners(sess, coord)

    try:

        while not coord.should_stop():

            print ('************')

            # 获取每一个batch中batch_size个样本和标签

            image_batch_v, label_batch_v = sess.run([image_batch, label_batch])

            print(image_batch_v.shape, label_batch_v)

    except tf.errors.OutOfRangeError:  #如果读取到文件队列末尾会抛出此异常

        print("done! now lets kill all the threads……")

    finally:

        # 协调器coord发出所有线程终止信号

        coord.request_stop()

        print('all threads are asked to stop!')

    coord.join(threads) #把开启的线程加入主线程，等待threads结束

    print('all threads are stopped!')

************

((3, 224, 224, 3), array([0, 1, 2], dtype=int32))

************

((3, 224, 224, 3), array([3, 4, 0], dtype=int32))

************

((3, 224, 224, 3), array([1, 2, 3], dtype=int32))

************

done! now lets kill all the threads……

all threads are asked to stop!

all threads are stopped!