title: PyTorch can't see GPU (torch.cuda.is_availble() returns False)
body: <p>I have a problem where</p>
  <pre class="lang-py prettyprint-override"><code>import torch
  print(torch.cuda_is_available())
  </code></pre>
  <p>will print False, and I can't use the GPU available. I've tried it on <code>conda</code> environment, where I've installed the PyTorch version corresponding to the NVIDIA driver I have. I've also tried it in docker container, where I've done the same. I've tried both of these options on a remote server, but they both failed. I know that I've installed the correct driver versions because I've checked the version with <code>nvcc --version</code> before installing PyTorch, and I've checked the GPU connection with <code>nvidia-smi</code> which displays the GPUs on the machines correctly.</p>
  <p>Also, I've checked <a href="https://stackoverflow.com/questions/39649102/how-do-i-select-which-gpu-to-run-a-job-on">this</a> post and tried exporting <code>CUDA_VISIBLE_DEVICES</code>, but had no luck.</p>
  <p>On the server I have NVIDIA V100 GPUs with CUDA version 10.0 (for conda environment) and version 10.2 on a docker container I've built. Any help or push in the right direction would be greatly appreciated. Thanks!</p>