split up CUDA-suffixed dependencies in dependencies.yaml

[jameslamb]

Description

Contributes to rapidsai/build-planning#31

cugraph-gnn does not currently used rapids-build-backend, but this will help once it does. I wrote that up here: #15

In short, RAPIDS DLFW builds want to produce wheels with unsuffixed dependencies, e.g. cudf depending on rmm, not rmm-cu12.

This PR is part of a series across all of RAPIDS to try to support that type of build by setting up CUDA-suffixed and CUDA-unsuffixed dependency lists in dependencies.yaml.

For more details, see:

• Update RAPIDS Python packages to use rapids-build-backend build-planning#31 (comment)
• split up CUDA-suffixed dependencies in dependencies.yaml cudf#16183

Notes for Reviewers

Why target 24.08?

This is targeting 24.08 because:

1. it should be very low-risk
2. getting these changes into 24.08 prevents the need to carry around patches for every library in DLFW builds using RAPIDS 24.08

[bdice]

PyTorch is never suffixed, right? Also this is a conda pinning since it includes a channel.

Suggested change

	- &pytorch_unsuffixed pytorch::pytorch>=2.0,<2.2.0a0
	- &pytorch_conda pytorch::pytorch>=2.0,<2.2.0a0

[jameslamb]

You're right, this one was a mistake from being a little over-aggressive with find-and-replace.

I went to change this and found that this anchor is actually not used at all, so pushed c72b9b8 just fully removing it.