chore: backport TypeAlias for py3.9 compat

[stillmatic]

No description provided.

[stillmatic]

see commentary here: invoke-ai/InvokeAI#302 (comment)

[magnusviri]

@Birch-san the lstein repo isn't working because of this. invoke-ai/InvokeAI#335

[magnusviri]

@Birch-san yesterday somebody downgraded the lstein mac environment to python 3.9, that's why it crashes now. This pull request makes this repo work with 3.9.

I'm not sure if we will leave it at 3.9. They are discussing it here.

[stillmatic]

I would note that this change is compatible with 3.9 and 3.10, so if this change is merged, you can use whichever version you please

[Birch-san]

thanks! I'll integrate this. I'll also rebase onto latest (Katherine added a trivial optimization crowsonkb@4567328).

I think I can simplify clone_please to be a more sensible patch, now that I found the source of the ±inf problem.
pytorch/pytorch#84364
just need to .detach().clone() the result returned from utils.py::append_dims.

Unrelated to MPS, but the following two points pertain to the patches I've made for getting good results at low sample steps (e.g. 7 or 8)…
https://twitter.com/Birchlabs/status/1565029734865584143?s=20&t=lU-1bZCq0IejmzGM3YzVrg

I think I'll delete the decorate_sigma_hat option I added to the samplers (there's already an idiomatic way to do quantization in k-diffusion: CompVisDenoiser(model, quantize=True) — admittedly it doesn't work when churn is enabled, but nobody's using churn).
crowsonkb#23 (comment)
I anticipate that k-diffusion will update soon with an official way to quantize sigma_hat, which will mean we can get time-step discretization even when churn>0:
crowsonkb#23 (comment)

likewise I'll delete the concat_zero option I added to the Karras noise schedule (it's better to increase sigma_min than to remove the zero). the same custom noise schedule of mine can be achieved without any changes to k-diffusion.
crowsonkb#23 (comment)
Birch-san/stable-diffusion@50476fa

[Birch-san]

oh, TypeAlias was only being used because of my decorate_sigma_hat patch, which is unrelated to MPS and which I'll be removing (as explained above).

so, we don't need to force python 3.9 users to install typing-extensions. I can just delete TypeAlias.

TypeAlias wasn't that important anyway (more of a nice-to-have best-practice); the type inference would do the right thing even if I hadn't explicitly declared TensorOperator as a TypeAlias.

so I think what I'll do is delete the offending code instead of integrating this PR, if that's okay with you?

[stillmatic]

sgtm, the easiest way to fix code is delete code!

[Birch-san]

thanks 🙂 I've now force-pushed a simpler branch to mps, which has no changes to sampling.py:
crowsonkb/k-diffusion@master...Birch-san:k-diffusion:mps

this removes the TypeAlias and therefore the need for this py3.9 mitigation.

anybody who's currently got my branch checked out, will not be able to pull because I force-pushed a new history. to get yourself up-to-date, cd into the k-diffusion repository (e.g. stable-diffusion/src/k-diffusion), fetch the latest mps branch and hard-reset your local mps to match the remote one:

git fetch origin mps
git reset --hard origin/mps