An Upgrade to SyntaxNet, New Models and a Parsing Competition • Hacker News Board

Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition

#31

Post by aseipp » Thu, Mar 16, 2017, 5:28 PM UTC

taliesinb wrote: post #22

jacquesm wrote: post #15

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 But it is a little bit out of date when it comes to version numbers.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…

Plug for Mathematica, which after its installed you can do deep learning on in one or two lines, with GPU support on all three platforms with no setup. Very concise. Getting fairly competitive in features with other high level declarative frameworks as of 11.1 (which was just released today). Very nice visualizations thanks to being in Mathematica. The language is of course closed source, paid software. Many universi…

Did y'all fix GTX 10x series compatibility with this release? Mathematica is some wonderful software, I admit -- but it was disappointing to try the NN examples and suddenly see nothing worked properly on my new GTX 1080 and I had to CPU train everything. :( I guess stuff like that's inevitable though so I'm not too upset.

Guess the only way is to upgrade to 11.1 and find out, but since you're apparently involved -- might as well ask...

Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition

#32

Post by jacquesm » Thu, Mar 16, 2017, 5:30 PM UTC

dharma1 wrote: post #27

jacquesm wrote: post #15

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 But it is a little bit out of date when it comes to version numbers.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…

Agreed it's more hassle than it should be, especially if building from source. However the main installation hassle is CUDA and CuDNN I think, not Tensorflow itself

CUDA is always fun to install but NVIDIA does a reasonably good job as long as you remember to remove the system installed nvidia stuff beforehand (otherwise you'll be in a world of pain with a computer that will likely either hang somewhere during the boot process or that will have two conflicting sets of NVIDIA code on it).

For CuDNN I've found a good solution, see below.

Tensorflow itself worked ok once I figured out what all the dependencies were, even so I have not been able to get it to use CUDA yet (it only works with the CPU), which is strange because other CUDA stuff works fine.

Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition

#33

Post by aseipp » Thu, Mar 16, 2017, 5:33 PM UTC

jorgemf wrote: post #19

jacquesm wrote: post #15

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.

This is a bit unfortunate, in a real sense. I mean, I already build enough software, so I'm not sad on missing out. But here's the thing: TensorFlow actually installed great on Windows and it took less than 10 minutes to get running, once I had Python3 installed, even with GPU support. Even worked awesome in VS Code, out of the box, with autocomplete in the python mode. Even a baby like me got started easily.

But it's a bit disappointing to hear that the build system is something of a nightmare, if I ever wanted to contribute myself. There's always plenty of things to help with, I don't care about the cutting edge of machine learning (I'm happy to submit docs, examples, etc)... Then again, the TF people can't just nerd around on their build system, for dorks like me to maybe write some patches every once in a while. Always great to make it easier, though.

Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition

#34

Post by [deleted] » Thu, Mar 16, 2017, 5:33 PM UTC

jorgemf wrote: post #19

jacquesm wrote: post #15

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.

[deleted]

Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition

#35

Post by taliesinb » Thu, Mar 16, 2017, 5:34 PM UTC

aseipp wrote: post #31

taliesinb wrote: post #22

Earlier quoted context omitted.

Plug for Mathematica, which after its installed you can do deep learning on in one or two lines, with GPU support on all three platforms with no setup. Very concise. Getting fairly competitive in features with other high level declarative frameworks as of 11.1 (which was just released today). Very nice visualizations thanks to being in Mathematica. The language is of course closed source, paid software. Many universi…

Did y'all fix GTX 10x series compatibility with this release? Mathematica is some wonderful software, I admit -- but it was disappointing to try the NN examples and suddenly see nothing worked properly on my new GTX 1080 and I had to CPU train everything. :( I guess stuff like that's inevitable though so I'm not too upset. Guess the only way is to upgrade to 11.1 and find out, but since you're apparently involved --…

Yup, it works. Sorry... GTX 10x required CUDA Toolkit 8.0 which was RC at the time we shipped 11.0.

Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition

#36

Post by greenpizza13 » Thu, Mar 16, 2017, 5:40 PM UTC

jacquesm wrote: post #15

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 strongly recommend you use Keras if you are new to Tensorflow. The API abstractions will make testing your network ideas a breeze. It won't save you from the hell of building TF, but should save you loads of time with implementation and testing.

Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition

#37

Post by loudmax » Thu, Mar 16, 2017, 5:42 PM UTC

jacquesm wrote: post #15

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 agree that Tensorflow has a mess of dependencies. The docker image worked for me: https://www.tensorflow.org/install/install_linux#InstallingD... Worked with the GPU even, on my Linux Mint gaming desktop.

Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition

#38

Post by jacquesm » Thu, Mar 16, 2017, 5:46 PM UTC

greenpizza13 wrote: post #36

jacquesm wrote: post #15

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 strongly recommend you use Keras if you are new to Tensorflow. The API abstractions will make testing your network ideas a breeze. It won't save you from the hell of building TF, but should save you loads of time with implementation and testing.

Much appreciated, thank you!

Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition

#39

Post by jacquesm » Thu, Mar 16, 2017, 5:46 PM UTC

loudmax wrote: post #37

jacquesm wrote: post #15

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 agree that Tensorflow has a mess of dependencies. The docker image worked for me: https://www.tensorflow.org/install/install_linux#InstallingD... Worked with the GPU even, on my Linux Mint gaming desktop.

That's a good idea. Will definitely try that.

Re: An Upgrade to SyntaxNet, New Models and a Parsing Competition

#40

Post by jacquesm » Thu, Mar 16, 2017, 5:48 PM UTC

aseipp wrote: post #33

jorgemf wrote: post #19

Earlier quoted context omitted.

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.

This is a bit unfortunate, in a real sense. I mean, I already build enough software, so I'm not sad on missing out. But here's the thing: TensorFlow actually installed great on Windows and it took less than 10 minutes to get running, once I had Python3 installed, even with GPU support. Even worked awesome in VS Code, out of the box, with autocomplete in the python mode. Even a baby like me got started easily. But it'…

For me the issue with such things is not so much the hassle as much as it is long term stability of an environment that I come to depend on. If I can't reproduce it from archived sources then there is a good chance that at some point in the future my stuff will suddenly and in-explicably stop working after some minor system update.

And python has a huge problem with this anyway. (Or, to put it probably more accurately, I have a huge problem with python in this way, historically my python code has had a relatively short shelf life compared to my C code (or even my PHP code)).