Question

我在Tensorflow 0.10下运行我的代码，但在将版本更新为0.12.1后，所有变量都抛出FailedPreconditionError: Attempting to use uninitialized value W error。除了我使用tf.global_variables_initializer()而不是tf.initialize_all_variables()之外，我的代码保持不变。我尝试在tf.GraphKeys.VARIABLES = tf.GraphKeys.GLOBAL_VARIABLES下添加import tensorflow as tf，但它无效。所以我打开这个问题因为我不知道错误在哪里。

我的代码如下。省略了一些更具可读性的细节。并且错误每次都不同。所有tf.Variable个已定义的变量都会出错。

class model(object):
    def __init__(self, paras):
        self.D = tf.constant(D, dtype = tf.float32)
        self.Q = tf.constant(Q, dtype = tf.float32)

        if self.USE_FEATURE:
            self.CF = tf.Variable((np.random.rand(self.rank, d_F) - 0.5) / self.rank, \
                                  dtype = tf.float32, name = 'CF')  #error here
        self.W = tf.Variable((np.random.rand(self.rank, sample_num) - 0.5) / self.rank / 200, \
                                  dtype = tf.float32, name = 'W')   #error here
        self.C = tf.Variable((np.random.rand(context_num, self.rank) - 0.5) / self.rank, \
                                   dtype = tf.float32, name = 'C')  #error here

        ED = tf.transpose(self.Q) * (1.0 / (1.0 + tf.exp(- tf.matmul(self.C, self.W))))
        recons = self.D - ED
        W_grad = tf.matmul(tf.transpose(self.C), recons)
        self.W_grad = tf.Variable(W_grad, dtype = tf.float32)  #error here

        self._build_update_W_grad()
        if not self.USE_FEATURE:
            self._build_alter_W()
        else:
            self._build_W_with_F()
        self._build_alter_C()

    def _run(self, sess):
        tf.initialize_all_variables().run()  #where the error throws

        for i in xrange(self.max_iter):
            if (i + 1) % self.prun_step == 0:
                self.mu = self.mu * self.prun_rate
            if (i + 1) % 2 == 1:
                for j in xrange(self.inner_maxiter):
                    if not self.USE_FEATURE:
                        self.up_W_grad.run()
                        self.up_W.run()
                    else:
                        self.up_W_grad.run()
                        for k in xrange(self.sgd_batch):
                            self.up_W_CF.run()
                            #raise NotImplementedError
            else:
                for j in xrange(self.inner_maxiter):
                    self.up_C.run()

        W = self.W.eval()
        C = self.C.eval()
        print 'end training. save W and C'
        return W, C

    def _build_alter_W(self):
        #codes
        self.up_W = tf.group(updata_W)

    def _build_W_with_F(self):    
        #codes
        self.up_W_CF = tf.group(updata_W, updata_CF)
        #raise NotImplementedError

    def _build_alter_C(self):
        #codes
        self.up_C = tf.group(updata_C)

    def _build_update_W_grad(self):
        #codes
        self.up_W_grad = tf.group(update_W_grad)

#main program
train_epoch = model(paras)
with tf.Session(config = config) as sess:
    W, C = train_epoch._run(sess)

有人可以帮忙吗？该程序在0.10中运行良好，但在我更新到0.12.1后崩溃了。我只更改了tf.initialize_all_variables().run()到tf.global_variables_initializer().run()。

在Tensorflow 0.12.1中初始化错误

0 个答案: