docker image creation is automated

Author: tinglvv

CUDA_UPGRADE_GUIDE.MD

@@ -57,10 +57,9 @@ There are two types of Docker containers we maintain in order to build Linux bin
 
 Add setup for our Docker `libtorch`:
 1. Follow this PR [PR 145789](https://github.com/pytorch/pytorch/pull/145789) for all steps in this section. For `libtorch`, the code changes are usually copy-paste. 
-3. This is Manual Step: Create a ticket for PyTorch Dev Infra team to Create a new repo to host manylinux-cuda images in docker hub, for example, https://hub.docker.com/r/pytorch/manylinux-builder:cuda115. This repo should have public visibility and read & write access for bots. This step can be removed once the following [issue](https://github.com/pytorch/builder/issues/901) is addressed.
-4. Push the images to Docker Hub. This step should be automated with the help with GitHub Actions in the `pytorch/builder` repo. Make sure to update the `cuda_version` to the version you're adding in respective YAMLs, such as `.github/workflows/build-manywheel-images.yml`, `.github/workflows/build-libtorch-images.yml`.
-5. Verify that each of the workflows that push the images succeed by selecting and verifying them in the [Actions page](https://github.com/pytorch/builder/actions/workflows/build-libtorch-images.yml) of pytorch/builder. Furthermore, check [https://hub.docker.com/r/pytorch/manylinux-builder/tags](https://hub.docker.com/r/pytorch/manylinux-builder/tags), [https://hub.docker.com/r/pytorch/libtorch-cxx11-builder/tags](https://hub.docker.com/r/pytorch/libtorch-cxx11-builder/tags) to verify that the right tags exist for manylinux and libtorch types of images.
-6. Finally before enabling nightly binaries and CI builds we should make sure we post following PRs in [PR 1015](https://github.com/pytorch/builder/pull/1015) [PR 1017](https://github.com/pytorch/builder/pull/1017) and [this commit](https://github.com/pytorch/builder/commit/7d5e98f1336c7cb84c772604c5e0d1acb59f2d72) to enable the new CUDA build in wheels.
+2. Merge the above the PR, and it should automatically push the images to Docker Hub with GitHub Actions. Make sure to update the `cuda_version` to the version you're adding in respective YAMLs, such as `.github/workflows/build-libtorch-images.yml`.
+3. Verify that each of the workflows that push the images succeed by selecting and verifying them in the [Actions page](https://github.com/pytorch/builder/actions/workflows/build-libtorch-images.yml) of pytorch/builder. Furthermore, check [https://hub.docker.com/r/pytorch/libtorch-cxx11-builder/tags](https://hub.docker.com/r/pytorch/libtorch-cxx11-builder/tags) to verify that the right tags exist for libtorch types of images.
+4. Finally before enabling nightly binaries and CI builds we should make sure we post following PRs in [PR 1015](https://github.com/pytorch/builder/pull/1015) [PR 1017](https://github.com/pytorch/builder/pull/1017) and [this commit](https://github.com/pytorch/builder/commit/7d5e98f1336c7cb84c772604c5e0d1acb59f2d72) to enable the new CUDA build in wheels.
 
 ## 5. Generate new Windows AMI, test and deploy to canary and prod.