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This requires to implement the __deepcopy__ method in Int8Params.
Moreover, there was an issue in the Linear8BitLT constructor that would
assign instance attributes to the class, which is now fixed.

Please review carefully that this does not impact existing code.

Tests that I ran:

- pytest tests/test_linear8bitlt.py
- in PEFT: python -m pytest -m "single_gpu_tests and bitsandbytes" tests/test_gpu_examples.py
- in PEFT: python -m pytest -m "single_gpu_tests and bitsandbytes" tests/test_common_gpu.py
- in transformers: RUN_SLOW=1 python -m pytest tests/quantization/bnb -x

* test_nvidia_transform: fix variable reference

`out_order` is the global parametrization list, not the test fixture argument

* Make `parametrize` use more idiomatic

* Use a more deterministic helper for `dim*` determination

* Convert NO_CUBLASLT errors into skips too

* Mark slow and benchmark tests as such (allows `-k "not benchmark"`)

* Adjust Ruff configuration

* do not autofix always
* be less strict around tests and benchmarks
* adjust ignores for now

* Ruff: autofix I and F401

* Apply ruff autofixes

* Fix RUF013 complaint

* Fix mutable default in replace_linear

* Don't use bare except

* Wrap bitsandbytes.__main__ entrypoint in function; fix "sensible" typo

* Fix ruff B008 (function call in arguments)

* Add ruff noqas as suitable

* Fix RUF005 (splat instead of concatenating)

* Fix B018 (useless expression)

* Add pre-commit configuration + GitHub Actions lint workflow

* Fix unused `e` in bitsandbytes/__main__.py

* fix merge conflict resolution error

* run pre-commit hook

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Co-authored-by: Titus <9048635+Titus-von-Koeller@users.noreply.github.com>

* implicitly skip any test that implicitly uses CUDA on a non-CUDA box
* add a `requires_cuda` fixture