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Signed-off-by: jiqing-feng <jiqing.feng@intel.com>

* Stop building for CUDA toolkit < 11.8

* Simplify

* Drop sm70 from cu128 build targets to align with pytorch

* Include device support tags for transformers multi-backend compatability; add xpu() and cpu() to Params4bit

* Make test suite more device-agnostic

* Additional device agnostic tests

* Additional device agnosticism for tests

* Add BNB_TEST_DEVICE env var to manually select device for unit tests

* Include device support tags for transformers multi-backend compatability; add xpu() and cpu() to Params4bit

* Make test suite more device-agnostic

* Additional device agnostic tests

* Additional device agnosticism for tests

* Add BNB_TEST_DEVICE env var to manually select device for unit tests

* Small bugfix for int8 test

* Exclude backward() from code coverage reports

* Params4bit: don't try to quantize when moving to meta device

* fix: Improve CUDA version detection and error handling

* lint fix

* lint fix

* [fix] define blocksize

define blocksize as just showing number is a bit confusing

* [fix] match code with ademamix

also define blocksize as in prev commit

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

Changed return type from map object to tuple in get_cuda_version_tuple().

* Testing cleanup

* More test cleanup

* Additional deprecations/removals.

* Skip benchmark, deprecated, slow tests by default

* Drop Python 3.8 support.

* Formatting

* Sketch out first custom op registration

* Add note

* Initial int8 op registration

* Cleanup some deprecated functions.

* Int8 ops updates; tests

* Implement 4bit quant/dequant ops

* Fix nested quant

* cleanup

* Test improvements

* Clean up and improve tests

* Add higher level custom op for int8 matmul + dequant + bias

* Add gemv 4bit custom op

* Cleanup

* Implement out kwarg overloads for custom ops

* Update PyTorch minimum to 2.1

* Deprecation updates

* Deprecation updates

* Cleanup; rename int8_linear_dequant -> int8_scaled_mm

* Bump min pytorch to 2.2

* cleanup

* Test reorganization

* Remove deprecated supports_igemmlt

* More cleanup

* Cleanup obsolete C++/CUDA code

* Cleanup

* Create 'default' backend for fallback op implementations; initial CPU nf4 work

* Stub out for multi-platform

* Fix serialization tests for torch>=2.6.0

* Add example for torch.compile e2e inference

* Test update

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

Bumps the minor-patch group with 1 update in the / directory: [ruff](https://github.com/astral-sh/ruff).


Updates `ruff` from 0.6.9 to 0.9.6
- [Release notes](https://github.com/astral-sh/ruff/releases)
- [Changelog](https://github.com/astral-sh/ruff/blob/main/CHANGELOG.md)
- [Commits](https://github.com/astral-sh/ruff/compare/0.6.9...0.9.6

)

---
updated-dependencies:
- dependency-name: ruff
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: minor-patch
...
Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>