Multiple CPU interop fixes for serialization and cloning

[dantegd]

No description provided.

[copy-pr-bot]

Auto-sync is disabled for draft pull requests in this repository. Workflows must be run manually.

Contributors can view more details about this message here.

[dantegd]

/ok to test

[viclafargue]

LGTM

[betatim]

/ok to test

[betatim]

Why move this here? Maybe we should leave a comment for people from the future to explain why it can't be imported at the top of the file (or move it back if this was just for debugging)

[betatim]

Lucky number 13 :D

[betatim]

I think we should merge this PR. It improves things and fixes several things.

We can keep improving the from_/as_sklearn round tripping. I think the test from https://github.com/rapidsai/cuml/pull/6342/files#r1963552769 still doesn't pass (even if you exclude the raft handle). But lets look at that in a new PR

[betatim]

The two not optional jobs both fail with this:

 =========================== short test summary info ============================
FAILED test_basic_estimators.py::test_kernel_ridge - AssertionError: y_pred should be a np.ndarray, but is a <class 'cupy.ndarray'>
assert not True
 +  where True = isinstance(array([ 0.95477083, -0.99923366, -0.49547406, ..., -0.99986215,\n        0.91445195,  0.88462877]), <class 'cupy.ndarray'>)
 +    where <class 'cupy.ndarray'> = <module 'cupy' from '/opt/conda/envs/test/lib/python3.10/site-packages/cupy/__init__.py'>.ndarray
= 1 failed, 529 passed, 5 xfailed, 6 xpassed, 119 warnings in 96.05s (0:01:36) =

I added this test in #6327 where it passed. But, I am wondering if this test should always pass or only it he accelerator is enabled (it should be skipped if the accelerator is disabled)? When I wrote the test I meant "when the accelerator is active, it should always output a Numpy array". I didn't think about the "accelerator off" case, so happy to just skip this test in that case. I guess it depends on what the default output type is, mirror?, when the accelerator is off.

The failures in the optional jobs look more serious. They are of this type:

FAILED test_random_forest.py::test_create_classification_model[8-10-10-1.0] - AttributeError: _cpu_model

For several estimators :-/

There is also a CUDA error but maybe that is a spurious one?

[dantegd]

@betatim it was late last night, the error on the optional jobs is a small one, pushing a fix

[betatim]

I'll merge this now. I think this is a good way forward to see what is what in combination with all the other PRs that are still open. There are things here that we could discuss/improve, let's do that in follow up PRs.

[betatim]

/merge

I think those comments have been addressed/we can come back to it