1、调用tf.softmax_cross_entropy_with_logits函数出错。
原因是这个函数，不能按以前的方式进行调用了，只能使用命名参数的方式来调用。
原来是这样的：tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(y, y_))
修改成这样的：tf.reduce_sum(tf.nn.softmax_cross_entropy_with_logits(logits=y, labels=y_))

2、Tensorflow 函数tf.cocat([fw,bw],2)出错：TypeError: Expected int32, got list containing Tensors of type ‘_Message’ instead.
Expected int32, got list containing Tensors of type ‘_Message’ inst
原因是11版本的函数形式为:tf.concat(2,[fw,bw]),即应把串联的维度与串联值位置调换即可.

3、Input ‘split_dim’ of ‘Split’ Op has type float32 that does not match expected type of int32
This is because in Tensorflow versions < 0.12.0 the split function takes the arguments as:
x = tf.split(0, n_steps, x) # tf.split(axis, num_or_size_splits, value)

The tutorial you are working from was written for versions > 0.12.0, which has been changed to be consistent with Numpy’s split syntax:
x = tf.split(x, n_steps, 0) # tf.split(value, num_or_size_splits, axis)

4、‘module’ object has no attribute ‘pack’
因为TF后面的版本修改了这个函数的名称，把 tf.pack 改为 tf.stack。

5、The value of a feed cannot be a tf.Tensor object. Acceptable feed values include Python scalars, strings, lists, or numpy ndarrays
数据集是feed输入的，feed的数据格式是有要求的。
解决：img,label = sess.run[img,label],用返回值。

TensorFlow遇到的问题汇总（持续更新中......）