The low-level tensorflow API is very incomplete, e.g. missing tf.where and tf.layer.

[strelec]

Thanks for making the effort of writing this library.

I feel that because so many features are missing, it would be useful to keep the namespaces for the low-level library same as python, so people can easily see what is supported and what is not.

[eaplatanios]

No problem! I hope you find it useful! I don't think there are so many features that are missing. I have re-structured some parts because I felt I didn't like the way some things are organized in the Python API, but you should still be able to find most features.

Regarding tf.where and tf.layer that you asked for:

• tf.where is defined here and it's called tf.select in my API, because that's the actual name of the TensorFlow op being used. I'm not sure why they decided to name it where in the Python API, but still be called select in the C++ side.
• If by tf.layer you mean the way you create layers for use say with the learn API, then that is all in the learn package in my API because I don't consider it a low-level feature. It's about creating higher-level components that can be composed to create graphs. It's a bit different than the way it's done in the Python API to allow for strong typing, but it is still work-in-progress. Is that what you meant?

I'm sorry for the confusion with some of the restructuring. I could document things better and add a tutorial at some point, but I haven't gotten the chance to do that yet, because I'm working on this as a side project and using it in my research.

Let me know if you have any questions and I'd be more than happy to help! Suggestions are also super welcome. :)

[strelec]

Thanks, I am still thinking whether I should start with your library or with the Python one. I understand that you mean low and high level api are compatible. Maybe you should mention this.

And I was also not able to find RMSProp optimizer.

ps: I am also having a huge trouble instantiating a Session. It was one line with python.

[eaplatanios]

@strelec All I can say about whether you should start using this library, is that if you like and prefer Scala over Python and you like strong typing, then it might be worth giving it a try. I use it for my research and I've even built a fully fledged machine translation pipeline on top of it (I'll be releasing it soon), and I have no problems with it. It actually helps avoid a lot of issues early on, with compilation, and it's also faster than the Python API in some aspects.

I'll add support for RMSProp tonight as it's a only a few lines of code. You can use AMSGrad for now if you want, which is an improved version of Adam, that avoids a problem Adam has.

Regarding instantiating a session, can you please give me some more information? What is your trouble? It should be as simple as this:

import org.platanios.tensorflow.api._

...

val session = tf.Session()

[eaplatanios]

@strelec Sorry I just realized this last line should have been just:

val session = Session()

[eaplatanios]

@strelec I added support for RMSProp in 75584ed801f86458ea88ae1d6113f8a12f766e29. It is included in release 0.2.0-SNAPSHOT.

I'll go ahead and close this issue in this case. Please feel free to reopen if you feel there is still something missing, or if you can still not instantiate a session and I'll be happy to help. :)