Why we built Kur: Prototyping DNNs is a slow process. Most people doing deep learning want to iterate and try out different model architectures and learn from others. It's hard to do this using barebones backends like TensorFlow/Theano or even the higher abstraction of software like Keras.
Kur is not speech specific. It can be used for images (we supply two examples), speech (we supply one example and DG is open sourcing a new audio dataset with it, the DEEPGRAM10), text, etc.
There are CNN layers, RNN, dense, dropout, batch norm, etc. to pick and choose from. The best part? Kur does all the plumbing! You want one input but two outputs? Not a problem, describe that model in Kur!
We're really pumped to be releasing Kur and would love to answer questions if you've got em.
Thanks! Deepgram AI Research Team
http://kur.deepgram.com http://github.com/deepgram/kur http://kurhub.com
DSSTNE had a clearish reason for doing so: automatic model-parallel training. Twitter wanted something simpler than Torch for most of their devs to use.
But I'm not really seeing why you guys did it.
"DSSTNE currently only supports Fully Connected layers ..."
Kur supports the cutting edge: like CNN/RNN.
"DSSTNE Engine works with data only in NetCDF format."
Kur supports the data that you have on hand. You can see in the tutorial (http://kur.deepgram.com/tutorial.html) how easy it is to send brand new data in the familiar Python pickle object.
These are the kind of GOTCHAs that people doing deep learning run into all the time. And they are a major time suck. Kur relieves you of those duties so you can work on more interesting parts, like trying novel models :).
We're so glad DL tools are coming out. But there's still tons of progress to be made and Kur is one step along that path—making the user experience more efficient and enjoyable.
Also, does it work on Windows? "DL for dummies" code should run on Windows :)
The install instructions are pretty much structured as: quick,
pip install kur
install with vituralenv in a quick script
install a whole environment and include virtualenvwrapperDoing:
pip install kur
Installs all of the packages that Kur relies on, so you don't need a list to run down and install.
Anyway we can help get it installed for you?
About Windows: great point and we have had users test in Windows. It installs fully there too!
But I'd like to know what you're about to install on my machine, where can I find that list?
Anyway we can help get it installed for you?
I got "Kur requires Python 3.4 or later" error even though I have it on my Ubuntu vm:
~# python3 --version Python 3.4.3
Error says: "Command python setup.py egg_info failed with error code 1 in /tmp/pip_build_root/kur"
Why is it using python instead of python3?
A couple of weeks ago, I went through some struggles installing TF on Ubuntu 16.04 and getting it to see the CuDNN (mostly due to various paths not being setup correctly), so forgive me if doing all that with a single command sounds too good to be true, especially if it can't even see that I got the correct python already.