81–90 of 91 posts
This is really interesting, I've been wanting to learn more about Torch for a while but have been reluctant to commit to learning Lua.
I use it more and more for hobby projects. Combine it with LuaJIT (which torch uses) and you have the fastest interpreted language around. Give it a try.
Is there any reason this might not work in windows? I see no installation docs for it.
the C libraries are compatible with Windows, they are used in Torch windows ports. We just dont have any Windows devs on the project to help and maintain it :( .
Only a few months ago people saying that the deep learning library ecosystem was starting to stabilize. I never saw that as the case. The latest frontier for deep learning libraries is ensuring efficient support for dynamic computation graphs. Dynamic computation graphs arise whenever the amount of work that needs to be done is variable. This may be when we're processing text, one example being a few words while anot…
Earlier quoted context omitted.
Lua is extremely flexible to the point where there is basically no standard library. This causes problems with code reuse and moving between codebases because everyone does things drastically differently. Compare this to Numpy in the Python world, a single fundamental package for scientific computing in Python. Lua is less used than Python in the scientific community, and a lot of the most innovative machine learning…
Thanks for the interesting and informative comment. Do I sense just a tiny bit of regret though? Yet another Python interface. YAPI. You heard it here first. And no, Py3 is not that nice. Too much cruft by far. And lua is miles faster than Python when you're outside the tensor domain, ie while you're sourcing and wrangling your data. Arguably luajit obviates the need for C , something you can't say about Python. Disc…
Is that true even if the Python used is PyPy rather than CPython?
Guess there's no escaping Python. I had hoped Lua(jit) might emerge as a scientific programming alternative but with Torch now throwing its hat into the Python ring I sense a monoculture in the making. Bit of a shame really because Lua is a nice language and was an interesting alternative.
Lua is extremely flexible to the point where there is basically no standard library. This causes problems with code reuse and moving between codebases because everyone does things drastically differently. Compare this to Numpy in the Python world, a single fundamental package for scientific computing in Python. Lua is less used than Python in the scientific community, and a lot of the most innovative machine learning…
This is really interesting, I've been wanting to learn more about Torch for a while but have been reluctant to commit to learning Lua.
Lua is a pleasure to learn and use. The language core is so simple and elegant, you can learn it in a day. Standard library is also very light, which is both strength and weakness. I use it more and more for hobby projects. Combine it with LuaJIT (which torch uses) and you have the fastest interpreted language around. Give it a try.
Only a few months ago people saying that the deep learning library ecosystem was starting to stabilize. I never saw that as the case. The latest frontier for deep learning libraries is ensuring efficient support for dynamic computation graphs. Dynamic computation graphs arise whenever the amount of work that needs to be done is variable. This may be when we're processing text, one example being a few words while anot…
Only a few months ago people saying that the deep learning library ecosystem was starting to stabilize. I never saw that as the case. The latest frontier for deep learning libraries is ensuring efficient support for dynamic computation graphs. Dynamic computation graphs arise whenever the amount of work that needs to be done is variable. This may be when we're processing text, one example being a few words while anot…
One question: how do you save a dynamic network if it changes from time to time (e.g. from sample to sample)?
Earlier quoted context omitted.
the C libraries are compatible with Windows, they are used in Torch windows ports. We just dont have any Windows devs on the project to help and maintain it :( .
Are you guys looking for Windows devs to contribute or help maintaining it? I'd be interested in helping out if I can. I currently use Chainer, but I'd like to try pytorch
Only a few months ago people saying that the deep learning library ecosystem was starting to stabilize. I never saw that as the case. The latest frontier for deep learning libraries is ensuring efficient support for dynamic computation graphs. Dynamic computation graphs arise whenever the amount of work that needs to be done is variable. This may be when we're processing text, one example being a few words while anot…