I needed to install nvidia-docker 2.0 to use Runwayml's local GPU.
Here are the commands I ran.
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$ curl -sL https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
$ curl -sL https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list
$ sudo apt update
$ sudo apt install nvidia-docker2 -y
$ sudo pkill -SIGHUP dockerd
$ sudo docker run --runtime=nvidia --rm nvidia/cuda nvidia-smi
Probably you will see this.
7ddbc47eeb70: Pull complete
c1bbdc448b72: Pull complete
8c3b70e39044: Pull complete
45d437916d57: Pull complete
d8f1569ddae6: Pull complete
85386706b020: Pull complete
ee9b457b77d0: Pull complete
be4f3343ecd3: Pull complete
30b4effda4fd: Pull complete
Digest: sha256:31e2a1ca7b0e1f678fb1dd0c985b4223273f7c0f3dbde60053b371e2a1aee2cd
Status: Downloaded newer image for nvidia/cuda:latest
Sat Feb 8 03:11:46 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 440.33.01 Driver Version: 440.33.01 CUDA Version: 10.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce GTX 1070 On | 00000000:01:00.0 On | N/A |
| N/A 52C P8 4W / N/A | 349MiB / 8111MiB | 2% Default |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: GPU Memory |
| GPU PID Type Process name Usage |
|=============================================================================|
+-----------------------------------------------------------------------------+
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