您必须使用dtype float为占位符张量'Placeholder'提供值

Question

我是一个更新的tensorflow,我真的不知道如何解决这个问题.

代码如下:

1. 给火车喂食价值:

   sess.run(train_op, feed_dict={images: e, labels: l, keep_prob_fc2: 0.5})
   

2. 使用CNN中的值:

   x = tf.placeholder(tf.float32, [None, 10 * 1024])
   

然后有错误

InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'Placeholder' with dtype float
     [[Node: Placeholder = Placeholder[dtype=DT_FLOAT, shape=[], _device="/job:localhost/replica:0/task:0/gpu:0"]()]]

我打印输入值类型print(e.dtype),结果是float32和e.shape:(10, 32, 32, 1).

我真的不知道为什么会发生这种错误.

---

代码格式

第一:

 define the CNN model 
       "image = tf.placeholder(tf.float32, [FLAGS.batch_size, 32,32,1])" is here

第二:

 loss funtion and train_op is here
       "label = tf.placeholder(tf.float32, [None, FLAGS.batch_size])" is here

第三是会议:

images, labels = getShuffleimage()#here will get shuffle data
num_examples = 0
init = tf.initialize_local_variables()

with tf.Session() as sess:
    # Start populating the filename queue.
    sess.run(init)
    coord = tf.train.Coordinator()
    threads = tf.train.start_queue_runners(coord=coord, sess=sess)

    try:
        step = 0
        while not coord.should_stop():
            start_time = time.time()
            image, label = sess.run([images, labels])#get shuffle images
            print(image.shape)
            print(image.dtype)
            sess.run(train_op, feed_dict={image: image, label: label , keep_prob_fc2: 0.5})
            duration = time.time() - start_time

    except tf.errors.OutOfRangeError:
        print('Done training after reading all data')
    finally:
        # When done, ask the threads to stop.
        coord.request_stop()

        # Wait for threads to finish.
        coord.join(threads)
        sess.close()

Answer 1

一些问题

首先,
为什么你使用sess = tf.InteractiveSession(),with tf.Session() as sess:同时,只是好奇

第二你有什么占位符的名称x或images？
如果名字x,{images: x_data...}不会喂x_data到x,它覆盖(？)images
我觉得feed_dict应该是{x: x_data...}

如果名称是images,images您的程序中是否有两个,placeholder并shuffle data尝试修改变量名称