2017-09-16 1020 views
0

我是Tensorflow的新手,遇到问题。当我的程序达到x_batch = sess.run(X_mb)时,它卡住了(所以,它可以打印1和2,但不能打印4.我想这是一个无限循环)。我打印X_mb的值,结果为Tensor("batch:0", shape=(32, 39), dtype=float32)。任何人都可以帮助我吗?谢谢! mb_size = 32,g的形状是[60366,39]。Tensorflow,程序卡在sess.run()函数

更新的代码:

X = tf.placeholder(tf.float32, shape=[None, X_dim]) 

def sample_z(m, n): 
    return np.random.uniform(-1., 1., size=[m, n]) 

g = tf.unstack(data, num = 60366, axis = 0) 
X_mb, *_ = tf.train.batch(g ,mb_size, capacity = 60366) 
sess = tf.train.MonitoredSession() 


i = 0 

for it in range(2000): 
    #print(1) 
    for _ in range(5): 
     #print(2)  

     #print(X_mb) 
     x_batch = sess.run(X_mb) 
     # print(4) 
     _, D_loss_curr, _ = sess.run(
      [D_solver, D_loss, clip_D], 
      feed_dict={X: x_batch, z: sample_z(mb_size, z_dim)} 
     ) 

    _, G_loss_curr = sess.run(
     [G_solver, G_loss], 
     feed_dict={z: sample_z(mb_size, z_dim)} 
    ) 

以下是错误消息:

runfile('/Users/franklan123/.spyder-py3/temp.py', wdir='/Users/franklan123/.spyder-py3') 
Traceback (most recent call last): 

    File "<ipython-input-4-6af95f06eb7f>", line 1, in <module> 
    runfile('/Users/franklan123/.spyder-py3/temp.py', wdir='/Users/franklan123/.spyder-py3') 

    File "/Users/franklan123/anaconda/envs/tensorflow/lib/python3.6/site-packages/spyder/utils/site/sitecustomize.py", line 688, in runfile 
    execfile(filename, namespace) 

    File "/Users/franklan123/anaconda/envs/tensorflow/lib/python3.6/site-packages/spyder/utils/site/sitecustomize.py", line 101, in execfile 
    exec(compile(f.read(), filename, 'exec'), namespace) 

    File "/Users/franklan123/.spyder-py3/temp.py", line 48, in <module> 
    X = tf.placeholder(tf.float32, shape=[None, X_dim]) 

    File "/Users/franklan123/anaconda/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/ops/array_ops.py", line 1530, in placeholder 
    return gen_array_ops._placeholder(dtype=dtype, shape=shape, name=name) 

    File "/Users/franklan123/anaconda/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/ops/gen_array_ops.py", line 1954, in _placeholder 
    name=name) 

    File "/Users/franklan123/anaconda/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 767, in apply_op 
    op_def=op_def) 

    File "/Users/franklan123/anaconda/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2458, in create_op 
    self._check_not_finalized() 

    File "/Users/franklan123/anaconda/envs/tensorflow/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2181, in _check_not_finalized 
    raise RuntimeError("Graph is finalized and cannot be modified.") 

RuntimeError: Graph is finalized and cannot be modified. 

回答

0

没有死循环,tf.train.batch创建队列,你必须运行队列跑步者获取任何数据。否则,当你执行sess.run时,你的代码只会挂在queue.dequeue()操作上(因为没有线程实际上将数据放入队列中)。

简单的解决方案:

  1. 移动的X_mb线以前创建会话(!这个修改的图)
  2. 变化tf.Session到tf.train.MonitoredSession(这将运行队列为你,否则你将不得不手动运行它们+ MonitoredSession最终确定图形,以避免将来出现类似上面的错误)。一旦你这样做 - 用全局初始化器(MonitoredSession为你初始化)删除行。
+0

嗨,我做了你说的,但我得到了一个RuntimeError(图已定稿,无法修改) – FRANKfisher

+0

正如在答案中所说 - 这将最终确定你的图,你**不能**以后修改你的图(这就是TF代码的写法)。也许你忘了删除初始化程序? – lejlot

+0

这是我的代码:g = tf.unstack(data,num = 60366,axis = 0) X_mb,* _ = tf.train.batch(g,mb_size,capacity = 60366) sess = tf.train.MonitoredSession () I = 0 它在范围(2000): 为_在范围(5): x_batch = sess.run(X_mb) _,D_loss_curr,_ = sess.run( [D_solver ,D_loss,clip_D], feed_dict = {X:x_batch,z:sample_z(mb_size,z_dim)} ) – FRANKfisher