TST Fix PEFT integration test bitsandbytes config
The PEFT integration tests still used load_in_{4,8}_bit, which is
deprecated, moving to properly setting BitsAndBytesConfig. For 4bit,
also ensure that nf4 is being used to prevent
> RuntimeError: quant_type must be nf4 on CPU, got fp4
Some PEFT integration tests involving text generation pipelines were
failing since #38129 because the base model is too small to generate
longer sequences. Setting max_new_tokens fixes this.
Two PEFT tests are actually failing:
tests/peft_integration/test_peft_integration.py::PeftIntegrationTester::test_delete_adapter
tests/peft_integration/test_peft_integration.py::PeftIntegrationTester::test_peft_pipeline_no_warning
This must have been going on for some time but was apparently never
noticed. The cause is that the tests themselves are faulty, the PEFT
integration is correct in these cases.
test_delete_adapter
The first faulty test was introduced by #34650. AFAICT, it should never
have passed in the first place, the PEFT integration logic was not
changed in the meantime. At this point, the logs for the PR CI are gone,
so I'm not sure if the test passed back then or not.
test_peft_pipeline_no_warning
This test was introduced in #36783 and should also never have passed, as
the self.assertNoLogs context manager only returns None, thus the assert
should never have worked (mea culpa for suggesting this code snippet).
Here too, the CI logs are deleted by now, so I can't check if the test
already failed back then.
* add peft model in constant
* add test
* fix formating
* make fixup execute
* change code
* check by self.task
* add test
* fixup test code
* fix minor typo
* fix pipeline test
* apply maintainers reqests
* Fix pipeline-peft interaction
* once again you have committed a debug breakpoint
* Remove extra testing line
* Add a test to check adapter loading
* Correct adapter path
* make fixup
* Remove unnecessary check
* Make check a little more stringent
* use torch.testing.assertclose instead to get more details about error in cis
* fix
* style
* test_all
* revert for I bert
* fixes and updates
* more image processing fixes
* more image processors
* fix mamba and co
* style
* less strick
* ok I won't be strict
* skip and be done
* up
* added logic for deleting adapters once loaded
* updated to the latest version of transformers, merged utility function into the source
* updated with missing check
* added peft version check
* Apply suggestions from code review
Co-authored-by: Anton Vlasjuk <73884904+vasqu@users.noreply.github.com>
* changes according to reviewer
* added test for deleting adapter(s)
* styling changes
* styling changes in test
* removed redundant code
* formatted my contributions with ruff
* optimized error handling
* ruff formatted with correct config
* resolved formatting issues
---------
Co-authored-by: Anton Vlasjuk <73884904+vasqu@users.noreply.github.com>
Original issue: https://github.com/huggingface/peft/issues/2256
There is a potential error when using load_best_model_at_end=True with a
prompt learning PEFT method. This is because Trainer uses load_adapter
under the hood but with some prompt learning methods, there is an
optimization on the saved model to remove parameters that are not
required for inference, which in turn requires a change to the model
architecture. This is why load_adapter will fail in such cases and users
should instead set load_best_model_at_end=False and use
PeftModel.from_pretrained. As this is not obvious, we now intercept the
error and add a helpful error message.
* [PEFT] Set eval mode when loading PEFT adapter
Resolves#34469
When calling model.load_adapter to load a PEFT adapter, by default the
adapter should be set to eval mode. This is now correctly done. Users
can still pass is_trainable=True to load the adapter in training mode.
* Linter
When loading a LoRA adapter, so far, there was only a warning when there
were unexpected keys in the checkpoint. Now, there is also a warning
when there are missing keys.
This change is consistent with
https://github.com/huggingface/peft/pull/2118 in PEFT and the planned PR
https://github.com/huggingface/diffusers/pull/9622 in diffusers.
Apart from this change, the error message for unexpected keys was
slightly altered for consistency (it should be more readable now). Also,
besides adding a test for the missing keys warning, a test for
unexpected keys warning was also added, as it was missing so far.
* [PEFT] Support low_cpu_mem_usage for PEFT loading
PEFT added support for low_cpu_mem_usage=True when loading adapters in
https://github.com/huggingface/peft/pull/1961. This feature is now
available when installing PEFT v0.13.0. With this PR, this option is
also supported when loading PEFT adapters directly into transformers
models.
Additionally, with this PR,
https://github.com/huggingface/diffusers/pull/9510 will be unblocked,
which implements this option in diffusers.
* Fix typo
* make use of adapter_revision
* v1 adapter kwargs
* fix CI
* fix CI
* fix CI
* fixup
* add BC
* Update src/transformers/integrations/peft.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* fixup
* change it to error
* Update src/transformers/modeling_utils.py
* Update src/transformers/modeling_utils.py
* fixup
* change
* Update src/transformers/integrations/peft.py
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* fix PEFT multi adapters support
* refactor a bit
* save pretrained + BC + added tests
* Update src/transformers/integrations/peft.py
Co-authored-by: Benjamin Bossan <BenjaminBossan@users.noreply.github.com>
* add more tests
* add suggestion
* final changes
* adapt a bit
* fixup
* Update src/transformers/integrations/peft.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* adapt from suggestions
---------
Co-authored-by: Benjamin Bossan <BenjaminBossan@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Allow PEFT model dict to be loaded
* make style
* make style
* Apply suggestions from code review
* address comments
* fixup
* final change
* added tests
* fix test
* better logic for handling if adapter has been loaded
* Update tests/peft_integration/test_peft_integration.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
---------
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* a draft version
* v2 integration
* fix
* make it more generic and works for IA3
* add set adapter and multiple adapters support
* fixup
* adapt a bit
* oops
* oops
* oops
* adapt more
* fix
* add more refactor
* now works with model class
* change it to instance method as it causes issues with `jit`.
* add CR
* change method name
* add `add_adapter` method
* clean up
* Update src/transformers/adapters/peft_mixin.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add moe utils
* fixup
* Update src/transformers/adapters/peft_mixin.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* adapt
* oops
* fixup
* add is_peft_available
* remove `requires_backend`
* trainer compatibility
* fixup + docstring
* more details
* trigger CI
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/modeling_utils.py
* fixup + is_main_process
* added `save_peft_format` in save_pretrained
* up
* fix nits here and there
* nits here and there.
* docs
* revert `encoding="utf-8"`
* comment
* added slow tests before the PEFT release.
* fixup and nits
* let's be on the safe zone
* added more comments
* v1 docs
* add remaining docs
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* move to `lib_integrations`
* fixup
* this time fixup
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* address final comments
* refactor to use `token`
* add PEFT to DockerFile for slow tests.
* added pipeline support.
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
