Update CUDA_UPGRADE_GUIDE.MD

Author: atalman

CUDA_UPGRADE_GUIDE.MD

@@ -61,10 +61,11 @@ Build Magma for Linux. Our Linux CUDA jobs use conda, so we need to build magma-
 There are three types of Docker containers we maintain in order to build Linux binaries: `conda`, `libtorch`, and `manywheel`. They all require installing CUDA and then updating code references in respective build scripts/Dockerfiles.  This step is about libtorch and manywheel containers.
 
 Add setup for our Docker `libtorch` and `manywheel`:
-1. For `libtorch`, the code changes are usually copy-paste. For `manywheel`, you should manually verify the versions of the shared libraries with the CUDA you downloaded before.
-2. Create a new repo to host manylinux-cuda images, for example, https://hub.docker.com/r/pytorch/manylinux-cuda115. Then, give bots write and read access to this repo. This step can be removed once the following [issue](https://github.com/pytorch/builder/issues/901) is addressed.
-3. 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-conda-images.yml`, `.github/workflows/build-libtorch-images.yml`.
-4. 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.
+1. Follow this PR [PR 1003](https://github.com/pytorch/builder/pull/1003) for all steps in this section
+2. For `libtorch`, the code changes are usually copy-paste. For `manywheel`, you should manually verify the versions of the shared libraries with the CUDA you downloaded before.
+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-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-conda-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.
 
 ## 5. Modify code to install the new CUDA for Windows and update MAGMA for Windows