11–20 of 34 posts
Earlier quoted context omitted.
Just follow the instructions friend.
Sorry missed that other 7.5 reference, replaced with 8. Sorry copy and pasted my 7.5 instructions as they were mainly the same.
there is also a link for the list of cuda capabilities in the post.
I'm not sure what Tensorflow source you're compiling, but I've been trying many times recently and it fails in many, many different ways. It's a neverending maze of fail, basically. I've never seen the end of it yet. It failed today, too, so the code base is not getting better. I'm using Ubuntu 16.04, CUDA 8.0RC + the gcc patch, cuDNN 5.1, nvidia-driver-[367|370], tensorflow-master, python-2.7. My process is basicall…
Just follow the instructions friend.
It's also the fact that it fails in so many different ways. Bazel bombs out after ./configure; the master branch today does not even begin to build at all, the old Bazel workaround is not working anymore. Then there's the gcc issues.
You may have gotten lucky once, who knows why.
Again, do you still have the pip package you claim you've built using this procedure? If so, can you upload it somewhere? I would very much like to test it. Thank you.
Thank you so much. I tried 3 times in the last week to get it working with Cuda 8.0
https://github.com/tensorflow/tensorflow/issues/2559#issueco...
Earlier quoted context omitted.
Sorry missed that other 7.5 reference, replaced with 8. Sorry copy and pasted my 7.5 instructions as they were mainly the same.
and yes sorry thought hitting yes for gpu support was obvious and did not see the need to type that one out. there is also a link for the list of cuda capabilities in the post.
I cannot test this but possibly just use whatever version the drivers work and make sure the run file does not install different drivers.
Earlier quoted context omitted.
Just follow the instructions friend.
I may go ahead and do a literal clone of your instructions. However, looking at your process, it's what I do, step by step, AFAICT without actually going ahead and doing it. It's also the fact that it fails in so many different ways. Bazel bombs out after ./configure; the master branch today does not even begin to build at all, the old Bazel workaround is not working anymore. Then there's the gcc issues. You may have…
Earlier quoted context omitted.
Just follow the instructions friend.
I may go ahead and do a literal clone of your instructions. However, looking at your process, it's what I do, step by step, AFAICT without actually going ahead and doing it. It's also the fact that it fails in so many different ways. Bazel bombs out after ./configure; the master branch today does not even begin to build at all, the old Bazel workaround is not working anymore. Then there's the gcc issues. You may have…
Here is the pip3 wheel but I am skeptical given it was built for my system.
https://github.com/tensorflow/tensorflow/blob/master/tensorf...
Why does it just take following directions to make it to the front page of HN these days?
This probably has something to do with the fact that GPUs are flaky and idiosyncratic, and all the software that uses them depends on black-box libraries handed down by Nvidia, who is completely shit at maintaining software.
Why does it just take following directions to make it to the front page of HN these days?
Because GPU-accelerated learning is exciting, and most of the directions you find for setting it up don't work. (Judging from other replies, this post may be no different.) This probably has something to do with the fact that GPUs are flaky and idiosyncratic, and all the software that uses them depends on black-box libraries handed down by Nvidia, who is completely shit at maintaining software.
Screenshot for the skeptics.
