21–30 of 93 posts
Hoping this will quickly make into someone's home grown self-hosted version of Alexa. Alexa, turn the lights on in the kitchen. Alexa, turn on the kitchen light. Alexa, light up the kitchen. Should all accomplish the same task using this framework.
I've been fighting Tensorflow in the last couple of days to try an application on it, never before have I seen such a convoluted build process and a maze of dependencies. The best manual on getting tensorflow with CUDA support up and running is here: http://www.nvidia.com/object/gpu-accelerated-applications-te... But it is a little bit out of date when it comes to version numbers. If you're going to try TensorBox ( h…
See http://reference.wolfram.com/language/guide/NeuralNetworks.h..., also look at Examples > Applications under http://reference.wolfram.com/language/ref/NetTrain.html for some worked examples. Fun example of live visualization during training (very easy to do, will get even easier in future versions): https://twitter.com/taliesinb/status/839013689613254656
See also: spaCy, which is an open-source NLP framework that has some integration with Keras as well: https://news.ycombinator.com/item?id=13874787 ...and apparently will release a major version update today . Ouch.
I do wish SyntaxNet were a bit easier to use. A lot of people have asked for SyntaxNet as a backend for spaCy, and I'd love to be using it in a training ensemble. When I tried this last year, I had a lot of trouble getting it to work as a library. I spent days trying to pass it text in memory from Python, and it seemed like I would have to write a new C++ tensorflow op. Has anyone gotten this to work yet?
I've been fighting Tensorflow in the last couple of days to try an application on it, never before have I seen such a convoluted build process and a maze of dependencies. The best manual on getting tensorflow with CUDA support up and running is here: http://www.nvidia.com/object/gpu-accelerated-applications-te... But it is a little bit out of date when it comes to version numbers. If you're going to try TensorBox ( h…
The annoying thing for GPU training is handling the cudNN dependency, which Google's guides are annoyingly lacking.
Hoping this will quickly make into someone's home grown self-hosted version of Alexa. Alexa, turn the lights on in the kitchen. Alexa, turn on the kitchen light. Alexa, light up the kitchen. Should all accomplish the same task using this framework.
I've been slowly working on my own simple home "Alexa" using mostly CMUSphinx for the voice detection. Honestly my most successful methods involved the least amount of complex NLP. Just simply treating the sentence as a bag of words and looking for "on" or "off" or "change" (and their synonyms) and the presence of known smart objects works extremely well. I could say "Hey Marvin, turn on the lights and TV", or "Hey M…
Same concern here... so my voice->text method is via android's google voice - forced to offline mode. The offline mode is surprisingly good.
Re mis triggers... I also have opencv running on the same android. It only activates the voice recognition when I am actually looking directly at the android device (an old phone).
Given how many areas NLP can be applied to, I can only imagine all of these future internal project proposals where someone has to explain to some C-suite exec how they are going to revolutionize the business with Parsey McParseface. Or better yet, when they have to budget a big upgrade to the "DRAGNN based ParseySaurus". Fun times ahead.
-(Eng) We need to switch to this new NLP framework
- (VP) Ok, why? Which one is it?
- (Eng) Huh, it's called Parsey McParseface, developed by ...
- (VP) WTF? Don't waste my time with jokes, go build your own
- (Eng) But ...
- (VP) Meeting's over.
I've been fighting Tensorflow in the last couple of days to try an application on it, never before have I seen such a convoluted build process and a maze of dependencies. The best manual on getting tensorflow with CUDA support up and running is here: http://www.nvidia.com/object/gpu-accelerated-applications-te... But it is a little bit out of date when it comes to version numbers. If you're going to try TensorBox ( h…
I've been fighting Tensorflow in the last couple of days to try an application on it, never before have I seen such a convoluted build process and a maze of dependencies. The best manual on getting tensorflow with CUDA support up and running is here: http://www.nvidia.com/object/gpu-accelerated-applications-te... But it is a little bit out of date when it comes to version numbers. If you're going to try TensorBox ( h…
sudo pip install tensorflow works fine as of the recent v1.0, and works out of the box for CPU training. The annoying thing for GPU training is handling the cudNN dependency, which Google's guides are annoyingly lacking.
I've found a nice workaround for that one that does not require registration with nvidia so you can automate it:
ML_REPO_PKG=nvidia-machine-learning-repo-ubuntu1404_4.0-2_amd64.deb
wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1404/x86_64/${ML_REPO_PKG} -O /tmp/${ML_REPO_PKG}
sudo dpkg -i /tmp/${ML_REPO_PKG}
rm -f /tmp/${ML_REPO_PKG}
CUDA_REPO_PKG=cuda-repo-ubuntu1404_7.5-18_amd64.deb
wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1404/x86_64/${CUDA_REPO_PKG} -O /tmp/${CUDA_REPO_PKG}
sudo dpkg -i /tmp/${CUDA_REPO_PKG}
rm -f /tmp/${CUDA_REPO_PKG}
apt-get update
apt-get install libcudnn5-dev
apt-get install libcudnn5See also: spaCy, which is an open-source NLP framework that has some integration with Keras as well: https://news.ycombinator.com/item?id=13874787 ...and apparently will release a major version update today . Ouch.
I've been fighting Tensorflow in the last couple of days to try an application on it, never before have I seen such a convoluted build process and a maze of dependencies. The best manual on getting tensorflow with CUDA support up and running is here: http://www.nvidia.com/object/gpu-accelerated-applications-te... But it is a little bit out of date when it comes to version numbers. If you're going to try TensorBox ( h…
It is not a good idea to compile TensorFlow by your own unless you really need it (for example for TensorFlow serving). Python packages are the way to go.
See this issue:
https://github.com/TensorBox/TensorBox/issues/100
and
https://github.com/TensorBox/TensorBox/issues/102
So then we're full-circle and installing from pip which doesn't work :(
sigh.
Anyway, I'll get it to work, somehow.