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Show HN: Kur by Deepgram (YC S16) – Deep Learning Made Easy

103 points by stephensonsco 10y ago

stephensonsco 10y ago
Deepgram is open sourcing Kur (http://kur.deepgram.com http://kur.deepgram.com)! Kur is the worlds first descriptive Deep Learning software. Think of a model, describe it in a simple YAML or JSON file, and train to get state-of-the-art results. There's no need to code. 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://kur.deepgram.com http://github.com/deepgram/kur http://github.com/deepgram/kur http://kurhub.com http://kurhub.com
- Hydraulix989 10y ago
  Thanks for releasing this for us, Scott! It will definitely help me test different models for my ethereum auto trading bot!
  - gallerdude 10y ago
    Do these type of systems work?
    - Hydraulix989 10y ago
      I'm about to find out. ;-)
    - stephensonsco 10y ago
      For sure. Install Kur and follow the examples. There's no voodoo, just pure clean DL fun.
      - gallerdude 10y ago
        I wasn't talking necessarily about Kur, but altcoin trading neural nets. Something I'll have to look into, I guess.
        ajsyp 10y ago
        Hi! I'm the core maintainer of Kur. I've also been intersted in altcoin trading, and I agree that Kur will be a great place to start. Let me know what progress you make (on Gitter)! Excited to here!
- Eridrus 10y ago
  There have been a few frameworks that take this declarative approach; DSSTNE, Twitter's internal framework and probably others. 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.
  - wrsh07 10y ago
    Didn't they say "faster prototyping"? That seems sane to me.
    - stephensonsco 10y ago
      Oh yeah, Kur allows MUCH faster prototyping. And if you utilize Jinja2 (Kur supports that in the Kurfiles), you really start unlocking the time savings.
    - Eridrus 10y ago
      I guess I just don't think that's true, Keras is already pretty easy to use for model definition, and this doesn't seem to solve any actual pain points I've encountered.
  - stephensonsco 10y ago
    Thanks for bringing up other frameworks in DL! Amazon's DSSTNE is restrictive, but it's great for their purposes. On the DSSTNE GitHub you can see statements like: "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 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.
deleted 10y ago
[deleted]
- stephensonsco 10y ago
  Try out the examples, tweak the models, and let us know how you get on! Also, we're hanging around on gitter if you want real time advice :)
- deleted 10y ago
  [deleted]
p1esk 10y ago
Great idea! However installation instructions are a little misleading. It says I only need Python 3, while in reality I need a whole bunch of things to be installed already. Is there a list of all requirements? Also, does it work on Windows? "DL for dummies" code should run on Windows :)
- stephensonsco 10y ago
  Thanks! We really push to keep the dependencies clean so that all you need is Python 3. Doing: 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!
  - p1esk 10y ago
    Installs all of the packages that Kur relies on 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.
    - ajsyp 10y ago
      Great questions! I'm the core maintainer of Kur. For a quick way to get it going, you can go to this link: http://kur.deepgram.com/install.html#kur-quick-install http://kur.deepgram.com/install.html#kur-quick-install And scroll just a little bit to the “Quick Start For Using pip”. It has this code: pip install virtualenv # Make sure virtualenv is present virtualenv -p $(which python3) ~/kur-env # Create a Python 3 environment for Kur . ~/kur-env/bin/activate # Activate the Kur environment pip install kur # Install Kur kur --version # Check that everything works git clone https://github.com/deepgram/kur # Get the examples cd kur/examples # Change directories kur -v train mnist.yml # Start training! The key line there is where it mentions: virtualenv -p $(which python3) ~/kur-env This line grabs your Python 3 install and makes a virtual environment. The rest of the commands just move things around into a tiny environment so you’ll find yourself in a directory where you can just run: kur train mnist.yml Then you’ll be training. :) The list of dependencies is in "setup.py" in the repo--they are all Python packages. The reason you're probably getting the Python3 error is that you need to set up a virtual environment so that your system can isolate different versions of Python (and Python packages). In fact, if you use virtual environments, all the dependencies that get install are confined to that virtual environment, and won't affect the rest of your installation. Using virtual environments is definitely a Python "best practice," and if you've never done it before, we walk you through it in our "Quick Start" section of the documentation: https://kur.deepgram.com/install.html#kur-quick-install https://kur.deepgram.com/install.html#kur-quick-install If you want to inspect the packages that are installed in the kur-env virtual environment, then (while in kur-env), just do: pip freeze And it will print out the installed python packages. You can join our gitter channel too if you need some more assistance! https://gitter.im/deepgram-kur/Lobby https://gitter.im/deepgram-kur/Lobby
lucidrains 10y ago
Nice job! I want to see another RNN net generate the yaml configs after we have collected enough of them for training. :)
- stephensonsco 10y ago
  You'll be able to easily do that once we release Kurhub.com.
mrg3_2013 10y ago
Looks very interesting! Particularly because I don't know NNs and would love to be able to get a feel for it. I'll give it a try this weekend and share my noob experience
lordvissu 10y ago
Need updates for installation on Windows. Been trying for more than a day now. -_-

103 points by stephensonsco 10y ago

Deepgram is open sourcing Kur (http://kur.deepgram.com http://kur.deepgram.com)! Kur is the worlds first descriptive Deep Learning software. Think of a model, describe it in a simple YAML or JSON file, and train to get state-of-the-art results. There's no need to code. 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://kur.deepgram.com http://github.com/deepgram/kur http://github.com/deepgram/kur http://kurhub.com http://kurhub.com

Hydraulix989 10y ago
Thanks for releasing this for us, Scott! It will definitely help me test different models for my ethereum auto trading bot!
- gallerdude 10y ago
  Do these type of systems work?
  - Hydraulix989 10y ago
    I'm about to find out. ;-)
  - stephensonsco 10y ago
    For sure. Install Kur and follow the examples. There's no voodoo, just pure clean DL fun.
    - gallerdude 10y ago
      I wasn't talking necessarily about Kur, but altcoin trading neural nets. Something I'll have to look into, I guess.
      - ajsyp 10y ago
        Hi! I'm the core maintainer of Kur. I've also been intersted in altcoin trading, and I agree that Kur will be a great place to start. Let me know what progress you make (on Gitter)! Excited to here!
Eridrus 10y ago
There have been a few frameworks that take this declarative approach; DSSTNE, Twitter's internal framework and probably others. 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.
- wrsh07 10y ago
  Didn't they say "faster prototyping"? That seems sane to me.
  - stephensonsco 10y ago
    Oh yeah, Kur allows MUCH faster prototyping. And if you utilize Jinja2 (Kur supports that in the Kurfiles), you really start unlocking the time savings.
  - Eridrus 10y ago
    I guess I just don't think that's true, Keras is already pretty easy to use for model definition, and this doesn't seem to solve any actual pain points I've encountered.
- stephensonsco 10y ago
  Thanks for bringing up other frameworks in DL! Amazon's DSSTNE is restrictive, but it's great for their purposes. On the DSSTNE GitHub you can see statements like: "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 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.

deleted 10y ago

[deleted]

stephensonsco 10y ago
Try out the examples, tweak the models, and let us know how you get on! Also, we're hanging around on gitter if you want real time advice :)
deleted 10y ago
[deleted]

p1esk 10y ago

Great idea! However installation instructions are a little misleading. It says I only need Python 3, while in reality I need a whole bunch of things to be installed already. Is there a list of all requirements? Also, does it work on Windows? "DL for dummies" code should run on Windows :)

stephensonsco 10y ago
Thanks! We really push to keep the dependencies clean so that all you need is Python 3. Doing: 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!
- p1esk 10y ago
  Installs all of the packages that Kur relies on 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.
  - ajsyp 10y ago
    Great questions! I'm the core maintainer of Kur. For a quick way to get it going, you can go to this link: http://kur.deepgram.com/install.html#kur-quick-install http://kur.deepgram.com/install.html#kur-quick-install And scroll just a little bit to the “Quick Start For Using pip”. It has this code: pip install virtualenv # Make sure virtualenv is present virtualenv -p $(which python3) ~/kur-env # Create a Python 3 environment for Kur . ~/kur-env/bin/activate # Activate the Kur environment pip install kur # Install Kur kur --version # Check that everything works git clone https://github.com/deepgram/kur # Get the examples cd kur/examples # Change directories kur -v train mnist.yml # Start training! The key line there is where it mentions: virtualenv -p $(which python3) ~/kur-env This line grabs your Python 3 install and makes a virtual environment. The rest of the commands just move things around into a tiny environment so you’ll find yourself in a directory where you can just run: kur train mnist.yml Then you’ll be training. :) The list of dependencies is in "setup.py" in the repo--they are all Python packages. The reason you're probably getting the Python3 error is that you need to set up a virtual environment so that your system can isolate different versions of Python (and Python packages). In fact, if you use virtual environments, all the dependencies that get install are confined to that virtual environment, and won't affect the rest of your installation. Using virtual environments is definitely a Python "best practice," and if you've never done it before, we walk you through it in our "Quick Start" section of the documentation: https://kur.deepgram.com/install.html#kur-quick-install https://kur.deepgram.com/install.html#kur-quick-install If you want to inspect the packages that are installed in the kur-env virtual environment, then (while in kur-env), just do: pip freeze And it will print out the installed python packages. You can join our gitter channel too if you need some more assistance! https://gitter.im/deepgram-kur/Lobby https://gitter.im/deepgram-kur/Lobby

lucidrains 10y ago

Nice job! I want to see another RNN net generate the yaml configs after we have collected enough of them for training. :)

stephensonsco 10y ago
You'll be able to easily do that once we release Kurhub.com.

mrg3_2013 10y ago

Looks very interesting! Particularly because I don't know NNs and would love to be able to get a feel for it. I'll give it a try this weekend and share my noob experience

lordvissu 10y ago

Need updates for installation on Windows. Been trying for more than a day now. -_-