* fix issue that some example with no trainer use accelerator.end_training in a wrong way
* reformat code
---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Add files
* Init
* Add TimmWrapperModel
* Fix up
* Some fixes
* Fix up
* Remove old file
* Sort out import orders
* Fix some model loading
* Compatible with pipeline and trainer
* Fix up
* Delete test_timm_model_1/config.json
* Remove accidentally commited files
* Delete src/transformers/models/modeling_timm_wrapper.py
* Remove empty imports; fix transformations applied
* Tidy up
* Add image classifcation model to special cases
* Create pretrained model; enable device_map='auto'
* Enable most tests; fix init order
* Sort imports
* [run-slow] timm_wrapper
* Pass num_classes into timm.create_model
* Remove train transforms from image processor
* Update timm creation with pretrained=False
* Fix gamma/beta issue for timm models
* Fixing gamma and beta renaming for timm models
* Simplify config and model creation
* Remove attn_implementation diff
* Fixup
* Docstrings
* Fix warning msg text according to test case
* Fix device_map auto
* Set dtype and device for pixel_values in forward
* Enable output hidden states
* Enable tests for hidden_states and model parallel
* Remove default scriptable arg
* Refactor inner model
* Update timm version
* Fix _find_mismatched_keys function
* Change inheritance for Classification model (fix weights loading with device_map)
* Minor bugfix
* Disable save pretrained for image processor
* Rename hook method for loaded keys correction
* Rename state dict keys on save, remove `timm_model` prefix, make checkpoint compatible with `timm`
* Managing num_labels <-> num_classes attributes
* Enable loading checkpoints in Trainer to resume training
* Update error message for output_hidden_states
* Add output hidden states test
* Decouple base and classification models
* Add more test cases
* Add save-load-to-timm test
* Fix test name
* Fixup
* Add do_pooling
* Add test for do_pooling
* Fix doc
* Add tests for TimmWrapperModel
* Add validation for `num_classes=0` in timm config + test for DINO checkpoint
* Adjust atol for test
* Fix docs
* dev-ci
* dev-ci
* Add tests for image processor
* Update docs
* Update init to new format
* Update docs in configuration
* Fix some docs in image processor
* Improve docs for modeling
* fix for is_timm_checkpoint
* Update code examples
* Fix header
* Fix typehint
* Increase tolerance a bit
* Fix Path
* Fixing model parallel tests
* Disable "parallel" tests
* Add comment for metadata
* Refactor AutoImageProcessor for timm wrapper loading
* Remove custom test_model_outputs_equivalence
* Add require_timm decorator
* Fix comment
* Make image processor work with older timm versions and tensor input
* Save config instead of whole model in image processor tests
* Add docstring for `image_processor_filename`
* Sanitize kwargs for timm image processor
* Fix doc style
* Update check for tensor input
* Update normalize
* Remove _load_timm_model function
---------
Co-authored-by: Amy Roberts <22614925+amyeroberts@users.noreply.github.com>
* Trainer - deprecate tokenizer for processing_class
* Extend chage across Seq2Seq trainer and docs
* Add tests
* Update to FutureWarning and add deprecation version
* fix redundant checkpointing in example scripts
* Update examples/pytorch/image-classification/run_image_classification_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/translation/run_translation_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/token-classification/run_ner_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/text-classification/run_glue_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/summarization/run_summarization_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/semantic-segmentation/run_semantic_segmentation_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/language-modeling/run_mlm_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/language-modeling/run_fim_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/language-modeling/run_clm_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/image-pretraining/run_mim_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/instance-segmentation/run_instance_segmentation_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/multiple-choice/run_swag_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/question-answering/run_qa_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/object-detection/run_object_detection_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Update examples/pytorch/question-answering/run_qa_beam_search_no_trainer.py
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Pass datasets trust_remote_code
* Pass trust_remote_code in more tests
* Add trust_remote_dataset_code arg to some tests
* Revert "Temporarily pin datasets upper version to fix CI"
This reverts commit b7672826ca.
* Pass trust_remote_code in librispeech_asr_dummy docstrings
* Revert "Pin datasets<2.20.0 for examples"
This reverts commit 833fc17a3e.
* Pass trust_remote_code to all examples
* Revert "Add trust_remote_dataset_code arg to some tests" to research_projects
* Pass trust_remote_code to tests
* Pass trust_remote_code to docstrings
* Fix flax examples tests requirements
* Pass trust_remote_dataset_code arg to tests
* Replace trust_remote_dataset_code with trust_remote_code in one example
* Fix duplicate trust_remote_code
* Replace args.trust_remote_dataset_code with args.trust_remote_code
* Replace trust_remote_dataset_code with trust_remote_code in parser
* Replace trust_remote_dataset_code with trust_remote_code in dataclasses
* Replace trust_remote_dataset_code with trust_remote_code arg
* Remove deprecated logic and warnings
* Add back some code that seems to be important...
* Let's just add all he nllb stuff back; removing it is a bit more involved
* Remove kwargs
* Remove more kwargs
* Update legacy Repository usage in `examples/pytorch/text-classification/run_glue_no_trainer.py`
Marked for deprecation here https://huggingface.co/docs/huggingface_hub/guides/upload#legacy-upload-files-with-git-lfs
* Fix import order
* Replace all example usage of deprecated Repository
* Fix remaining repo call and rename args variable
* Revert removing creation of gitignore files and don't change research examples
* Fix typos and grammar mistakes in docs and examples
* Fix typos in docstrings and comments
* Fix spelling of `tokenizer` in model tests
* Remove erroneous spaces in decorators
* Remove extra spaces in Markdown link texts
* Remove `task` arg in `load_dataset` in image-classification example
* Manage case where "train" is not in dataset
* Add new args to manage image and label column names
* Similar to audio-classification example
* Fix README
* Update tests
While using `run_clm.py`,[^1] I noticed that some files were being added
to my global cache, not the local cache. I set the `cache_dir` parameter
for the one call to `evaluate.load()`, which partially solved the
problem. I figured that while I was fixing the one script upstream, I
might as well fix the problem in all other example scripts that I could.
There are still some files being added to my global cache, but this
appears to be a bug in `evaluate` itself. This commit at least moves
some of the files into the local cache, which is better than before.
To create this PR, I made the following regex-based transformation:
`evaluate\.load\((.*?)\)` -> `evaluate\.load\($1,
cache_dir=model_args.cache_dir\)`. After using that, I manually fixed
all modified files with `ruff` serving as useful guidance. During the
process, I removed one existing usage of the `cache_dir` parameter in a
script that did not have a corresponding `--cache-dir` argument
declared.
[^1]: I specifically used `pytorch/language-modeling/run_clm.py` from
v4.34.1 of the library. For the original code, see the following URL:
acc394c4f5/examples/pytorch/language-modeling/run_clm.py.
* Normalize only if needed
* Update examples/pytorch/image-classification/run_image_classification.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* if else in one line
* within block
* one more place, sorry for mess
* import order
* Update examples/pytorch/image-classification/run_image_classification.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update examples/pytorch/image-classification/run_image_classification_no_trainer.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
