@@ -21,6 +21,13 @@ If you want to rebuild your image, and force the latest Apex to be cloned and in
...
@@ -21,6 +21,13 @@ If you want to rebuild your image, and force the latest Apex to be cloned and in
Currently, the non-`-devel` images on Pytorch Dockerhub do not contain the Cuda compiler `nvcc`. Therefore,
Currently, the non-`-devel` images on Pytorch Dockerhub do not contain the Cuda compiler `nvcc`. Therefore,
images whose name does not contain `-devel` are not eligible candidates for `BASE_IMAGE`.
images whose name does not contain `-devel` are not eligible candidates for `BASE_IMAGE`.
### Running your Apex container
Like any Cuda-enabled Pytorch container, a container with Apex should be run via [nvidia-docker](https://github.com/NVIDIA/nvidia-docker), for example:
```
docker run --runtime=nvidia -it --rm --ipc=host new_image_with_apex
```
## Option 2: Install Apex in a running container
## Option 2: Install Apex in a running container
Instead of building a new container, it is also a viable option to `git clone https://github.com/NVIDIA/apex.git` on bare metal, mount the Apex repo into your container at launch by running, for example,
Instead of building a new container, it is also a viable option to `git clone https://github.com/NVIDIA/apex.git` on bare metal, mount the Apex repo into your container at launch by running, for example,
