### Motivation
* MI250 Cirrascale runners are currently having network timeout leading to huge queueing of binary smoke test jobs:
<img width="483" height="133" alt="image" src="https://github.com/user-attachments/assets/17293002-78ad-4fc9-954f-ddd518bf0a43" />
* MI210 Hollywood runners (with runner names such as `pytorch-rocm-hw-*`) are not suitable for these jobs, because they seem to take much longer to download artifacts: https://github.com/pytorch/pytorch/pull/153287#issuecomment-2918420345 (this is why these jobs were specifically targeting Cirrascale runners). However, it doesn't seem like Cirrascale runners are necessarily doing much better either e.g. [this recent build](https://github.com/pytorch/pytorch/actions/runs/17332256791/job/49231006755).
* Moving to MI325 runners should address the stability part at least, while also reducing load on limited MI2xx runner capacity.
* However, I'm not sure if the MI325 runners will do any better on the artifact download part (this may need to be investigated more) cc @amdfaa
* Also removing `ciflow/binaries` and `ciflow/binaries_wheel` label/tag triggers for `generated-linux-binary-manywheel-rocm-main.yml` because we already trigger ROCm binary build/test jobs via these labels/tags in `generated-linux-binary-manywheel-nightly.yml`. And for developers who want to trigger ROCm binary build/test jobs on their PRs, they can use the `ciflow/rocm-mi300` label/tag as per this PR.
### TODOs (cc @amdfaa):
* Check that the workflow runs successfully on the MI325 runners in this PR. Note how long the test jobs take esp. the "Download Build Artifacts" step
* Once this PR is merged, clear the queue of jobs targeting `linux.rocm.gpu.mi250`
Pull Request resolved: https://github.com/pytorch/pytorch/pull/162044
Approved by: https://github.com/jeffdaily
Co-authored-by: Jeff Daily <jeff.daily@amd.com>
Should be the last part of https://github.com/pytorch/pytorch/pull/150558, except for maybe s390x stuff, which I'm still not sure what's going on there
For binary builds, do the thing like we do in CI where we tag each image with a hash of the .ci/docker folder to ensure a docker image built from that commit gets used. Previously it would use imagename:arch-main, which could be a version of the image based on an older commit
After this, changing a docker image and then tagging with ciflow/binaries on the same PR should use the new docker images
Release and main builds should still pull from docker io
Cons:
* if someone rebuilds the image from main or a PR where the hash is the same (ex folder is unchanged, but retrigger docker build for some reason), the release would use that image instead of one built on the release branch
* spin wait for docker build to finish
Pull Request resolved: https://github.com/pytorch/pytorch/pull/151706
Approved by: https://github.com/atalman
