Definitely, Theano is no longer active or have plans to be.

If you don't need mobile on-device D.L., take a look at pytorch. Otherwise, Tensorflow.

Fasi.ai will release some excellent self-paced coursework in January for Pytorch. Best bang for the buck (free, but time ain't) I've seen in any AI learning. Much of the lower level stuff is optimized for you, and he gives some great SOTA tricks for getting in the top 10% in kaggle competitions in like an hour or two.

Alas, no pytorch on device yet. But the state of the art is nearly 100% turnover every year, so the question becomes: do you need SOTA? Many problems are 98+% solved these days, so maybe we've reached "good enough" with some of these applications of d.l.

Does Theano meet your needs? Then no. Does TensorFlow meet them better, enough to justify the cost in switching? Then yes. "Actively developed" is a silly metric. Focus on features, flexibility, robustness etc.

For neural network libraries this isn't sensible.

For many (most?) users outside of Google and Facebook the most important feature is "is there an off-the-shelf implementation of new technique XXX or do I have to build it myself?"

For most users the sensible choice comes down to Keras+Tensorflow or PyTorch.

Depends on what you do. If you're starting a new project picking Theano indeed isn't a very good choice due to the reasons you've mentioned. However, if you already have a stable piece of software that does what you want it to do then migration won't add much value and you could spend this time doing something more important, like improving documentation or having dinner with your family and friends.

However it's worth pointing out that theano's API is somewhat similar to tensorflow so migrating shouldn't be too hard and should be fairly easy to test