计算状态：未找到：在检查点文件中未找到张量名称“input_producer/limit_epochs/epochs”

Question

我正在使用CIFAR10示例。我按照提供的代码对网络进行了培训。培训成功完成。由于我只想在数据集上评估每个示例一次，因此我已将cifar10_input.py中的输入修改为以下内容。

def inputs(eval_data, data_dir, batch_size): 
    filename = os.path.join(data_dir, TEST_FILE) 
    filename_queue = tf.train.string_input_producer([filename],num_epochs=1) 
    image, label = read_and_decode(filename_queue) 
    float_image = tf.image.per_image_whitening(image) 
    min_fraction_of_examples_in_queue = 0.4 
    min_queue_examples = int(NUM_EXAMPLES_PER_EPOCH_FOR_EVAL * 
          min_fraction_of_examples_in_queue) 
    images, label_batch = tf.train.batch(
     [image, label], 
     batch_size=batch_size, 
     num_threads=1, 
     capacity=min_queue_examples + 3 * batch_size) 

    tf.image_summary('images', images) 
    return images, tf.reshape(label_batch, [batch_size]) 

我已分离出的问题为以下：

tf.train_string_input_producer（[文件名]，num_epochs = 1）

如果我不设置num_epochs = 1，一切正常，因为它是。如果我这样做，我会得到以下错误。

0x2cf2700 Compute status: Not found: Tensor name "input_producer/limit_epochs/epochs" not found in checkpoint files /home/jkschin/tensorflow/my_code/data/svhn/train/model.ckpt-8000 

谢谢你的帮忙！

编辑3 @ mrry：

它仍然失败。这是跟踪。

Traceback (most recent call last): 
    File "cnn_eval.py", line 148, in <module> 
    tf.app.run() 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/default/_app.py", line 30, in run 
    sys.exit(main(sys.argv)) 
    File "cnn_eval.py", line 144, in main 
    evaluate() 
    File "cnn_eval.py", line 119, in evaluate 
    saver = tf.train.Saver([v for v in variables_to_restore if v.name != "input_producer/limit_epochs/epochs"]) 
AttributeError: 'unicode' object has no attribute 'name' 

EDIT 4 @mrry：

softmax_linear /偏压/ ExponentialMovingAverage

conv2/biases/ExponentialMovingAverage 
local4/biases/ExponentialMovingAverage 
local3/biases/ExponentialMovingAverage 
softmax_linear/weights/ExponentialMovingAverage 
conv1/biases/ExponentialMovingAverage 
local4/weights/ExponentialMovingAverage 
conv2/weights/ExponentialMovingAverage 
input_producer/limit_epochs/epochs 
local3/weights/ExponentialMovingAverage 
conv1/weights/ExponentialMovingAverage 

Traceback (most recent call last): 
    File "cnn_eval.py", line 148, in <module> 
    tf.app.run() 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/platform/default/_app.py", line 30, in run 
    sys.exit(main(sys.argv)) 
    File "cnn_eval.py", line 144, in main 
    evaluate() 
    File "cnn_eval.py", line 119, in evaluate 
    saver = tf.train.Saver([v for v in variables_to_restore if v != "input_producer/limit_epochs/epochs"]) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/saver.py", line 784, in __init__ 
    restore_sequentially=restore_sequentially) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/saver.py", line 437, in build 
    vars_to_save = self._ValidateAndSliceInputs(names_to_variables) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/saver.py", line 340, in _ValidateAndSliceInputs 
    names_to_variables = self._VarListToDict(names_to_variables) 
    File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/saver.py", line 314, in _VarListToDict 
    raise TypeError("Variable to save is not a Variable: %s" % var) 
TypeError: Variable to save is not a Variable: Tensor("Const:0", shape=(), dtype=string) 

EDIT 5 @mrry：

saver = tf.train.Saver([tf.Variable(0.0,validate_shape=False,name=v) for v in variables_to_restore if v != "input_producer/limit_epochs/epochs"]) 

0x21d0cb0 Compute status: Invalid argument: Assign requires shapes of both tensors to match. lhs shape= [] rhs shape= [10] 
    [[Node: save/Assign_8 = Assign[T=DT_FLOAT, use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/gpu:0"](softmax_linear/biases/ExponentialMovingAverage, save/restore_slice_8/_20)]] 

Answer 1

TL; DR：在cifar10_eval.py，变化这个保存器的构造函数是这样的：

saver = tf.train.Saver([v for v in variables_to_restore 
         if v != "input_producer/limit_epochs/epochs"]) 

这个问题是因为tf.train.string_input_producer()内部创建一个变量（称为"input_producer/limit_epochs/epochs"）时，其num_epochs参数不是None。当在cifar10_eval.py a tf.train.Saver is created中，它使用tf.all_variables()，其包括来自tf.nn.string_input_producer()的隐式创建的变量。该变量列表确定TensorFlow在检查点文件中查找的名称集。

目前没有一种很好的方式来引用隐式创建的变量，而不是通过它们的名称。因此，最好的解决方法是按名称排除Saver构造函数中的变量。

Answer 2

消除隐变量"input_producer/limit_epochs/epochs"的另一种方法是只装载训练的变量：

saver = tf.train.Saver(tf.trainable_variables())