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"RNNCell objects now subclass tf.layers.Layer. The strictness described in the TensorFlow 1.1 release is gone: The first time an RNNCell is used, it caches its
by jboggan 9y ago
"RNNCell objects now subclass tf.layers.Layer. The strictness described in the TensorFlow 1.1 release is gone: The first time an RNNCell is used, it caches its scope. All future uses of the RNNCell will reuse variables from that same scope. "
I'm so glad they fixed this, I've been running 1.0 for the last few months because the 1.1 release broke their own RNN tutorials and a lot of seq2seq code that is out there. I really, really love Tensorflow and understand it is a fast moving project but I hope they do more regression testing on their example code in the future. This is an exciting release though!
- cmarschner 9y agoWhat is exciting about it, do you think?
- jboggan 9y agoOther than unbreaking the feature I use most often? Haha, I think the new versions of TensorBoard and the SavedModel CLI are great for getting a better sense of what is going on under the hood. But I'm just generally excited by the framework hitting new releases, clearing bugs, and becoming more mature.
- probably_wrong 9y agoI wouldn't upgrade just yet if I were you, because part of the seq2seq code is still broken - more specifically, "there seems to be a problem with deepcopy of RNNCell"[1]. The bug is still open[2], and has been for a while. [1] https://stackoverflow.com/a/44594376 https://stackoverflow.com/a/44594376 [2] https://github.com/tensorflow/tensorflow/issues/8191 https://github.com/tensorflow/tensorflow/issues/8191