如何在TensorFlow中加载多个大型数据集？
我有三个大型数据集文件，分别用于训练、验证和测试。我可以通过tf.train.string_input_producer成功加载训练集，并将其提供给tf.train.shuffle_batch对象。然后，我可以迭代获取数据批次来优化模型。
但是，当我尝试以同样的方式加载验证集时，程序会不断报“OutOfRange Error”的错误，即使我没有在string_input_producer中设置num_epochs。
有人能帮忙解决吗？此外，我还在思考在TensorFlow中进行训练/验证的正确方法是什么？实际上，我没有看到任何例子（我搜索了很多），这些例子都在一个大数据集上进行训练和测试。对我来说，这太奇怪了...
以下是代码片段。
def extract_validationset(filename, batch_size):
with tf.device("/cpu:0"):
queue = tf.train.string_input_producer([filename])
reader = tf.TextLineReader()
_, line = reader.read(queue)
line = tf.decode_csv(...)
label = line[0]
feature = tf.pack(list(line[1:]))
l, f = tf.train.batch([label, feature], batch_size=batch_size, num_threads=8)
return l, f
def extract_trainset(train, batch_size):
with tf.device("/cpu:0"):
train_files = tf.train.string_input_producer([train])
reader = tf.TextLineReader()
_, train_line = reader.read(train_files)
train_line = tf.decode_csv(...)
l, f = tf.train.shuffle_batch(...,
batch_size=batch_size, capacity=50000, min_after_dequeue=10000, num_threads=8)
return l, f
....
label_batch, feature_batch = extract_trainset("train", batch_size)
label_eval, feature_eval = extract_validationset("test", batch_size)
with tf.Session() as sess:
tf.initialize_all_variables().run()
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(coord=coord)
# Loop through training steps.
for step in xrange(int(num_epochs * train_size) // batch_size):
feature, label = sess.run([feature_batch, label_batch])
feed_dict = {train_data_node: feature, train_labels_node: label}
_, l, predictions = sess.run([optimizer, loss, evaluation], feed_dict=feed_dict)
# after EVAL_FREQUENCY steps, do evaluation on whole test set
if step % EVAL_FREQUENCY == 0:
for step in xrange(steps_per_epoch):
f, l = sess.run([feature_eval, label_eval])
true_count += sess.run(evaluation, feed_dict={train_data_node: f, train_labels_node: l})
print('Precision @ 1: %0.04f' % true_count / num_examples)
<!---- ERROR ---->
tensorflow.python.framework.errors.OutOfRangeError: FIFOQueue '_5_batch/fifo_queue' is closed and has insufficient elements (requested 334, current size 0)
[[Node: batch = QueueDequeueMany[component_types=[DT_FLOAT, DT_FLOAT], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](batch/fifo_queue, batch/n)]]
由 op u'batch' 引起，定义于：