Tensorflow：OutOfRangeError tf.train.string_input_producer已关闭且元素不足 [英] Tensorflow: OutOfRangeError tf.train.string_input_producer is closed and has insufficient elements

问题描述

我一直在尝试以下代码段尝试输入管道

I have been trying the following code segment to experiment with the input pipeline

import tensorflow as tf 
with tf.Session() as sess:

   filename = ['/data/read/A.JPG', '/data/read/B.JPG', '/data/read/C.JPG']    
   filename_queue = tf.train.string_input_producer(filename, shuffle=False, num_epochs=5)

   reader = tf.WholeFileReader()
   key, value = reader.read(filename_queue)    
   tf.local_variables_initializer().run()    
   threads = tf.train.start_queue_runners(sess=sess)
   i = 0
   while True:
      i += 1

      image_data = sess.run(value)
      with open('/data/read/test_%d.jpg' % i, 'wb') as f:
         f.write(image_data)

运行以上代码得到以下错误消息，看起来是由 string_input_producer 生成的 filename_queue 引起的。但我不清楚问题出在哪里以及如何解决。

Running the above code gets the following error message, looks like it is caused by filename_queue generated by string_input_producer. But I am not clear what's the problem and how to correct it. Thanks.

caused by op 'ReaderReadV2', defined at:
File "test_input.py", line 12, in <module>
key, value = reader.read(filename_queue)
File "lib/python3.6/site-packages/tensorflow/python/ops/io_ops.py", line 193, in read
return gen_io_ops._reader_read_v2(self._reader_ref, queue_ref, name=name)
File "lib/python3.6/site-packages/tensorflow/python/ops/gen_io_ops.py", line 411, in _reader_read_v2
queue_handle=queue_handle, name=name)
File "lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 768, in apply_op
op_def=op_def)
File "lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2336, in create_op
original_op=self._default_original_op, op_def=op_def)
File "lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1228, in __init__
self._traceback = _extract_stack()

OutOfRangeError (see above for traceback): FIFOQueue '_1_input_producer' is closed and has insufficient elements (requested 1, current size 0)
     [[Node: ReaderReadV2 = ReaderReadV2[_device="/job:localhost/replica:0/task:0/cpu:0"](WholeFileReaderV2, input_producer)]]

推荐答案

队列运行器应该始终与 Coordinator 。

协调器帮助多个线程一起停止，并向等待它们停止的程序报告
异常。

The Coordinator helps multiple threads stop together and report exceptions to a program that waits for them to stop.

它们还捕获并处理队列生成的异常，包括 tf.errors.OutOfRangeError 异常，用于报告队列已关闭。

They also catch and handle exceptions generated by queues, including the tf.errors.OutOfRangeError exception, which is used to report that a queue was closed.

所以您的训练应该是：

with tf.Session() as sess:

   filename = ['/data/read/A.JPG', '/data/read/B.JPG', '/data/read/C.JPG']    
   filename_queue = tf.train.string_input_producer(filename, shuffle=False, num_epochs=5)

   reader = tf.WholeFileReader()
   key, value = reader.read(filename_queue)
   tf.local_variables_initializer().run() 

   # Create a coordinator, launch the queue runner threads.
   coord = tf.train.Coordinator()
   threads = tf.train.start_queue_runners(sess=sess, coord=coord)
   i = 0
   try:
       while not coord.should_stop():
          while True:
            i += 1
            image_data = sess.run(value)
            with open('test_%d.jpg' % i, 'wb') as f:
                f.write(image_data)

   except tf.errors.OutOfRangeError:
       # When done, ask the threads to stop.
       print('Done training -- epoch limit reached')
   finally:
       coord.request_stop()
       # Wait for threads to finish.
   coord.join(threads)

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