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I tried installing the nightly version and the same error appears. I guess it is a recent problem - a few weeks ago I can also run pytorch but now it breaks (at that time there were only 3 gpus available on gpu10).
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<i class="">Thanks,</i></div>
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<i class="">Yichong</i></div>
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<div class="">On Mar 10, 2019, at 3:05 PM, Yotam Hechtlinger <<a href="mailto:yhechtli@andrew.cmu.edu" class="">yhechtli@andrew.cmu.edu</a>> wrote:</div>
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<div class="">Regarding tensorflow you don't need to compile from source.<br class="">
<pre class="gmail-lang-bsh"><code class="gmail-devsite-terminal"><span class="gmail-pln">pip install tf</span><span class="gmail-pun">-</span><span class="gmail-pln">nightly</span><span class="gmail-pun">-</span><span class="gmail-pln">gpu</span></code></pre>
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Should get it done. I think that's what I've done, but it's been few weeks ago, so try it out and if it doesn't work I'll try to debug it.</div>
<div class="">Notice that you'll have to uninstall it and install the regular version when you switch back to the other GPUs.
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<div class="">Not sure regarding pytorch, I haven't tried to install it yet.</div>
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<div class="">Yotam.</div>
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<div dir="ltr" class="gmail_attr">On Sun, Mar 10, 2019 at 2:24 PM Yichong Xu <<a href="mailto:yichongx@cs.cmu.edu" class="">yichongx@cs.cmu.edu</a>> wrote:<br class="">
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<div style="overflow-wrap: break-word;" class="">It seems like tensorflow does not support cuda10 right now - it has to be installed from source.
<div class="">But I’m mainly using pytorch though and the version with cuda10 does not run either.</div>
<div class="">Plus, I tried the original cuda example and it cannot find the gpu either:</div>
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<div class="">(base) yichongx@gpu10$ ls</div>
<div class="">Makefile readme.txt simplePrintf simplePrintf.cu simplePrintf.o</div>
<div class="">(base) yichongx@gpu10$ ./simplePrintf</div>
<div class="">CUDA error at ../../common/inc/helper_cuda.h:744 code=999(cudaErrorUnknown) "cudaGetDeviceCount(&device_count)"</div>
<div class="">(base) yichongx@gpu10$</div>
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<i class="">Thanks,</i></div>
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<i class="">Yichong</i></div>
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<div class="">On Mar 10, 2019, at 9:52 AM, Yotam Hechtlinger <<a href="mailto:yhechtli@andrew.cmu.edu" target="_blank" class="">yhechtli@andrew.cmu.edu</a>> wrote:</div>
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<div class="">It's not the same cuda version on GPU 10 and the rest, I think different version of tensorflow has to be installed.
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<div class="">Check your tensorflow version and if it supports the cuda version on gpu10.</div>
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On Saturday, March 9, 2019, Predrag Punosevac <<a href="mailto:predragp@andrew.cmu.edu" target="_blank" class="">predragp@andrew.cmu.edu</a>> wrote:<br class="">
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<div dir="auto" class="">Try CUDA 10.0 instead of 10.1</div>
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<div class="gmail_quote">On Mar 9, 2019 5:28 PM, Yichong Xu <<a href="mailto:yichongx@cs.cmu.edu" target="_blank" class="">yichongx@cs.cmu.edu</a>> wrote:<br type="attribution" class="">
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<div dir="auto" class="">Same issue here.<br class="">
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<div dir="ltr" class="">From my iPhone</div>
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On Mar 9, 2019, at 4:01 PM, Emre Yolcu <<a href="mailto:eyolcu@andrew.cmu.edu" target="_blank" class="">eyolcu@andrew.cmu.edu</a>> wrote:<br class="">
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<p class="">Hi,</p>
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<p class="">Right now on gpu10 `nvcc --version` and `nvidia-smi` seem to work, but `python -c ‘import torch; print(torch.cuda.is_available())’` prints False. Is anybody running into the same issue?</p>
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<p class="">Emre</p>
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