[enhancement] Refactor onedal/datatypes in preparation for dlpack support

[icfaust]

Description

PR #1568 is too large and too out of date to use for refactoring the onedal table object. Subsequent PRs which introduced sycl_usm_array support mixed in additional C++ code in an unsustainable/ poorly extensible manner. This PR tries to find an intermediate solution which does not rewrite onedal/datatypes but only shifts the code in a way which is clearer and better separated following #1568 in spirit. This way adding dlpack support to table will be separated cleanly from numpy and sycl_usm_array. It defines additional namespaces so that it is clear in the code which conversion mechanism is being used where. It begins standardization of the naming schemes of functions and files for simple extensibility in the future (say supporting other array or possibly dataframe types).

Therefore, because it is only namespace definitions and file movements, performance benchmarks aren't necessary.

NOTE: A function convert_from_sua_iface is renamed convert_to_table in the sycl_usm namespace.

NOTE: changes to pickling for incremental algorithms must also be done. It is clear with the changes what types of inputs/outputs are expected for __getstate__ and __setstate__, which will default to numpy (not explicitly discussed in those PRs, but may be important in future array_api discussions).

NOTE: there are definitely inconsistencies between the sycl_usm and numpy implementations, and changes to those implementations in any functional manner should be done in a follow-up PR/ticket. They are likely to be time-intensive and require benchmarking.

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PR should start as a draft, then move to ready for review state after CI is passed and all applicable checkboxes are closed.
This approach ensures that reviewers don't spend extra time asking for regular requirements.

You can remove a checkbox as not applicable only if it doesn't relate to this PR in any way.
For example, PR with docs update doesn't require checkboxes for performance while PR with any change in actual code should have checkboxes and justify how this code change is expected to affect performance (or justification should be self-evident).

Checklist to comply with before moving PR from draft:

PR completeness and readability

• I have reviewed my changes thoroughly before submitting this pull request.
• I have commented my code, particularly in hard-to-understand areas.
• I have updated the documentation to reflect the changes or created a separate PR with update and provided its number in the description, if necessary.
• Git commit message contains an appropriate signed-off-by string (see CONTRIBUTING.md for details).
• I have added a respective label(s) to PR if I have a permission for that.
• I have resolved any merge conflicts that might occur with the base branch.

Testing

• I have run it locally and tested the changes extensively.
• All CI jobs are green or I have provided justification why they aren't.
• I have extended testing suite if new functionality was introduced in this PR.

Performance

• I have measured performance for affected algorithms using scikit-learn_bench and provided at least summary table with measured data, if performance change is expected.
• I have provided justification why performance has changed or why changes are not expected.
• I have provided justification why quality metrics have changed or why changes are not expected.
• I have extended benchmarking suite and provided corresponding scikit-learn_bench PR if new measurable functionality was introduced in this PR.

[icfaust]

Introducing dlpack first requires refactoring the datatypes directory in order to reduce tech debt and simplify reviewing. This PR will drop dlpack support to a second PR and will focus on refactoring directory.

[icfaust]

/intelci: run

[codecov]

Codecov Report

Attention: Patch coverage is 16.21622% with 31 lines in your changes missing coverage. Please review.

Files with missing lines	Patch %	Lines
onedal/basic_statistics/basic_statistics.cpp	8.33%	0 Missing and 11 partials ⚠️
onedal/decomposition/pca.cpp	0.00%	2 Missing and 7 partials ⚠️
onedal/covariance/covariance.cpp	14.28%	0 Missing and 6 partials ⚠️
onedal/linear_model/linear_model.cpp	25.00%	0 Missing and 3 partials ⚠️
onedal/datatypes/table.cpp	60.00%	0 Missing and 2 partials ⚠️

Flag	Coverage Δ
azure	77.96% <ø> (ø)
github	72.07% <16.21%> (+1.05%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Files with missing lines	Coverage Δ
onedal/datatypes/table.cpp	60.52% <60.00%> (ø)
onedal/linear_model/linear_model.cpp	55.88% <25.00%> (ø)
onedal/covariance/covariance.cpp	56.73% <14.28%> (-0.56%)	⬇️
onedal/decomposition/pca.cpp	43.57% <0.00%> (-0.32%)	⬇️
onedal/basic_statistics/basic_statistics.cpp	41.93% <8.33%> (ø)

... and 5 files with indirect coverage changes