Open elisehuard opened 8 years ago
That's correct. Same here. Everything hangs on CUDA to pass on the computation-intensive tasks to GPU for faster computing. I had found it impossible to enable multithreaded + GPU computation with lda2vec on my Windows computer. Others say that in a Linux-based system and/or in a distributed computing cloud you can correctly install all the dependencies.
What is the issue here? That it is not optimized? As far as i know it's normal for a non-cuda training to take several days on a CPU.
how you guys get the result, I am confusing how can I run the code to see the output. except in examples/twenty_newsgroup/lda2vec/lda2vec_run.py which I got the error for cuda environment setup, most files run successfully. I want to apply on another dataset and see the result, would you please tell which files should I run in order?
Thanks:)
Hi you all! I'm also having problems setting up the CUDA environment. Can someone help us with that issue?
that's what a get by after installing: pip instal chainer==1.5.1
Thank you in advance..It's really important to me make lda2vec work in my system...
File "lda2vec_run.py", line 23, in
Well obviously you didn't set up your CUDA environment correctly. First set it up correctly and then lda2vec_run.py will work correctly.
Without CUDA, it's absolutely single-threaded, and that means that even on my machine which is reasonably recent with Intel Core i7 processor, it takes about 5 days to run the 200 epochs.