- 29 Jun, 2023 1 commit
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amyeroberts authored
* Removal of deprecated methods and specify versions * Fix tests
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- 31 May, 2023 1 commit
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amyeroberts authored
Bug fix - flip_channel_order for channels_first
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- 30 Mar, 2023 1 commit
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amyeroberts authored
* Rescale image back if it was scaled during PIL conversion * do_rescale is defined if PIL image passed in
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- 14 Mar, 2023 1 commit
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amyeroberts authored
* Don't rescale if in and in range 0-255 * Raise value error if int values too large * Update tests/test_image_transforms.py * Update tests/test_image_transforms.py
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- 07 Mar, 2023 1 commit
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amyeroberts authored
* Add check before int casting for PIL conversion * Line length * Tidier logic
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- 02 Mar, 2023 1 commit
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Arthur authored
* initial commit * update * second batch * style * fix imports * fix relative import on pipeline
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- 15 Dec, 2022 1 commit
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amyeroberts authored
* Move convert_to_rgb to image_transforms module * Fix tests
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- 13 Dec, 2022 1 commit
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dhansmair authored
`image = to_channel_dimension_format(image, ChannelDimension.LAST)` is redundant as this same conversion is also applied in to_pil_image(). This redundant call actually makes the training fail in rare cases. The problem can be reproduced with the following code snippet: ``` from transformers.models.clip import CLIPFeatureExtractor vision_processor = CLIPFeatureExtractor.from_pretrained('openai/clip-vit-large-patch14') images = [ torch.rand(size=(3, 2, 10), dtype=torch.float), torch.rand(size=(3, 10, 1), dtype=torch.float), torch.rand(size=(3, 1, 10), dtype=torch.float) ] for image in images: processed_image = vision_processor(images=image, return_tensors="pt")['pixel_values'] print(processed_image.shape) assert processed_image.shape == torch.Size([1, 3, 224, 224]) ``` The last image has a height of 1 pixel. The second call to to_channel_dimesion_format() will transpose the image, and the height dimension is wrongly treated as the channels dimension afterwards. Because of this, the following normalize() step will result in an exception.
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- 12 Dec, 2022 1 commit
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amyeroberts authored
* Add require_vision decorator * Fixup * Use requires_backends * Add requires_backend to utils functions
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- 08 Dec, 2022 1 commit
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amyeroberts authored
* fix donut image processor * Update test values * Apply lower bound on resizing size * Add in missing size param * Resolve resize channel_dimension bug * Update src/transformers/image_transforms.py
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- 29 Nov, 2022 1 commit
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amyeroberts authored
* Add Donut image processor * Update src/transformers/image_transforms.py Co-authored-by:
Alara Dirik <8944735+alaradirik@users.noreply.github.com> * Fix docstrings * Full var names in docstring Co-authored-by:
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- 23 Nov, 2022 1 commit
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Patrick von Platen authored
* Correct type checking * up
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- 18 Nov, 2022 1 commit
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amyeroberts authored
* Add padding transformation * Add in upstream changes * Update tests & docs * Code formatting tuples in docstring
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- 17 Nov, 2022 1 commit
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amyeroberts authored
* Image transforms functionality used instead * Import torch * Import rather than copy * Update src/transformers/models/conditional_detr/feature_extraction_conditional_detr.py
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- 15 Nov, 2022 1 commit
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amyeroberts authored
* Add transforms for object detection * Update src/transformers/image_transforms.py Co-authored-by:
Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Better var names & docstring * Remove unused var desc in docstring * Update src/transformers/image_transforms.py Co-authored-by:
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- 11 Nov, 2022 1 commit
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amyeroberts authored
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- 02 Nov, 2022 1 commit
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amyeroberts authored
* Add CLIP image processor * Crop size as dict too * Update warning * Actually use logger this time * Normalize doesn't change dtype of input * Add perceiver image processor * Tidy up * Add DPT image processor * Add Vilt image processor * Tidy up * Add poolformer image processor * Tidy up * Add LayoutLM v2 and v3 imsge processors * Tidy up * Add Flava image processor * Tidy up * Add deit image processor * Tidy up * Add ConvNext image processor * Tidy up * Add levit image processor * Add segformer image processor * Add in post processing * Fix up * Add ImageGPT image processor * Fixup * Add mobilevit image processor * Tidy up * Add postprocessing * Fixup * Add VideoMAE image processor * Tidy up * Add ImageGPT image processor * Fixup * Add ViT image processor * Tidy up * Add beit image processor * Add mobilevit image processor * Tidy up * Add postprocessing * Fixup * Fix up * Fix flava and remove tree module * Fix image classification pipeline failing tests * Update feature extractor in trainer scripts * Update pad_if_smaller to accept tuple and int size * Update for image segmentation pipeline * Update src/transformers/models/perceiver/image_processing_perceiver.py Co-authored-by:
NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/beit/image_processing_beit.py Co-authored-by:
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- 19 Oct, 2022 1 commit
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amyeroberts authored
* Add center crop to transforms library * Return PIL images if PIL image input by default * Fixup and add docstring * Trigger CI * Update src/transformers/image_transforms.py Co-authored-by:
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- 18 Oct, 2022 1 commit
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David Yang authored
* Clean up deprecation warnings Notes: Changed some strings in tests to raw strings, which will change the literal content of the strings as they are fed into whatever machine handles them. Test cases for past in the past/past_key_values switch changed/removed due to warning of impending removal * Add PILImageResampling abstraction for PIL.Image.Resampling
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- 17 Oct, 2022 1 commit
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amyeroberts authored
* Adapt FE methods to transforms library * Mixin for saving the image processor * Base processor skeleton * BatchFeature for packaging image processor outputs * Initial image processor for GLPN * REmove accidental import * Fixup and docs * Mixin for saving the image processor * Fixup and docs * Import BatchFeature from feature_extraction_utils * Fixup and docs * Fixup and docs * Fixup and docs * Fixup and docs * BatchFeature for packaging image processor outputs * Import BatchFeature from feature_extraction_utils * Import BatchFeature from feature_extraction_utils * Fixup and docs * Fixup and docs * BatchFeature for packaging image processor outputs * Import BatchFeature from feature_extraction_utils * Fixup and docs * Mixin for saving the image processor * Fixup and docs * Add rescale back and remove ImageType * fix import mistake * Fix enum var reference * Can transform and specify image data format * Remove redundant function * Update reference * Data format flag for rescale * Fix typo * Fix dimension check * Fixes to make IP and FE outputs match * Add tests for transforms * Add test for utils * Update some docstrings * Make sure in channels last before converting to PIL * Remove default to numpy batching * Fix up * Add docstring and model_input_types * Use feature processor config from hub * Alias GLPN feature extractor to image processor * Alias feature extractor mixin * Add return_numpy=False flag for resize * Fix up * Fix up * Use different frameworks safely * Safely import PIL * Call function checking if PIL available * Only import if vision available * Address Sylvain PR comments Co-authored-by: Sylvain.gugger@gmail.com * Apply suggestions from code review Co-authored-by:
Sylvain Gugger <Sylvain.gugger@gmail.com> Co-authored-by:
Seunghwan Hong <seunghwan@scatterlab.co.kr> * Refactor `TFSwinLayer` to increase serving compatibility (#18352) * Refactor `TFSwinLayer` to increase serving compatibility Signed-off-by:
Seunghwan Hong <harrydrippin@gmail.com> Co-Authored-By:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by:
ydshieh <ydshieh@users.noreply.github.com> * Remove py.typed (#18485) * Fix pipeline tests (#18487) * Fix pipeline tests * Make sure all pipelines tests run with init changes * Use new huggingface_hub tools for download models (#18438) * Draft new cached_file * Initial draft for config and model * Small fixes * Fix first batch of tests * Look in cache when internet is down * Fix last tests * Bad black, not fixing all quality errors * Make diff less * Implement change for TF and Flax models * Add tokenizer and feature extractor * For compatibility with main * Add utils to move the cache and auto-do it at first use. * Quality * Deal with empty commit shas * Deal with empty etag * Address review comments * Fix `test_dbmdz_english` by updating expected values (#18482) Co-authored-by:
😬 (#18489) * Delete valohai.yaml * NLP => ML * typo * website supports https * datasets * 60k + modalities * unrelated link fixing for accelerate * Ok those links were actually broken * Fix link * Make `AutoTokenizer` auto-link * wording tweak * add at least one non-nlp task * `transformers-cli login` => `huggingface-cli login` (#18490) * zero chance anyone's using that constant no? * `transformers-cli login` => `huggingface-cli login` * `transformers-cli repo create` => `huggingface-cli repo create` * `make style` * Add seed setting to image classification example (#18519) * [DX fix] Fixing QA pipeline streaming a dataset. (#18516) * [DX fix] Fixing QA pipeline streaming a dataset. QuestionAnsweringArgumentHandler would iterate over the whole dataset effectively killing all properties of the pipeline. This restores nice properties when using `Dataset` or `Generator` since those are meant to be consumed lazily. * Handling TF better. * Clean up hub (#18497) * Clean up utils.hub * Remove imports * More fixes * Last fix * update fsdp docs (#18521) * updating fsdp documentation * typo fix * Fix compatibility with 1.12 (#17925) * Fix compatibility with 1.12 * Remove pin from examples requirements * Update torch scatter version * Fix compatibility with 1.12 * Remove pin from examples requirements * Update torch scatter version * fix torch.onnx.symbolic_opset12 import * Reject bad version Co-authored-by:Ankur Goyal <ankur@impira.com> * New cache fixes: add safeguard before looking in folders (#18522) * unpin resampy (#18527) Co-authored-by:
✨ update to use interlibrary links instead of Markdown (#18500) * Add example of multimodal usage to pipeline tutorial (#18498) *📝 add example of multimodal usage to pipeline tutorial *🖍 apply feedbacks *🖍 apply niels feedback * [VideoMAE] Add model to doc tests (#18523) * Add videomae to doc tests * Add pip install decord Co-authored-by:Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local> * Update perf_train_gpu_one.mdx (#18532) * Update no_trainer.py scripts to include accelerate gradient accumulation wrapper (#18473) * Added accelerate gradient accumulation wrapper to run_image_classification_no_trainer.py example script * make fixup changes * PR comments * changed input to Acceletor based on PR comment, ran make fixup * Added comment explaining the sync_gradients statement * Fixed lr scheduler max steps * Changed run_clm_no_trainer.py script to use accelerate gradient accum wrapper * Fixed all scripts except wav2vec2 pretraining to use accelerate gradient accum wrapper * Added accelerate gradient accum wrapper for wav2vec2_pretraining_no_trainer.py script * make fixup and lr_scheduler step inserted back into run_qa_beam_search_no_trainer.py * removed changes to run_wav2vec2_pretraining_no_trainer.py script and fixed using wrong constant in qa_beam_search_no_trainer.py script * Add Spanish translation of converting_tensorflow_models.mdx (#18512) * Add file in spanish docs to be translated * Finish translation to Spanish * Improve Spanish wording * Add suggested changes from review * Spanish translation of summarization.mdx (#15947) (#18477) * Add Spanish translation of summarization.mdx * Apply suggestions from code review Co-authored-by:
Omar U. Espejel <espejelomar@gmail.com> Co-authored-by:
Thomas Wang <24695242+thomasw21@users.noreply.github.com> * more comments - added more comments on why we cast only floating point parameters * Update src/transformers/modeling_utils.py Co-authored-by:
📝 update metric with evaluate (#18535) * Restore _init_weights value in no_init_weights (#18504) * Recover _init_weights value in no_init_weights For potential nested use. In addition, users might modify private no_init_weights as well. * Apply suggestions from code review Co-authored-by:📝 update documentation build section (#18548) * `bitsandbytes` - `Linear8bitLt` integration into `transformers` models (#17901) * first commit * correct replace function * add final changes - works like charm! - cannot implement tests yet - tested * clean up a bit * add bitsandbytes dependencies * working version - added import function - added bitsandbytes utils file * small fix * small fix - fix import issue * fix import issues * Apply suggestions from code review Co-authored-by:Michael Benayoun <mickbenayoun@gmail.com> * add few comments * add more doctring + make style * more docstring * raise error when loaded in 8bit * make style * add warning if loaded on CPU * add small sanity check * fix small comment * add bitsandbytes on dockerfile * Improve documentation - improve documentation from comments * add few comments * slow tests pass on the VM but not on the CI VM * Fix merge conflict * make style * another test should pass on a multi gpu setup * fix bad import in testing file * Fix slow tests - remove dummy batches - no more CUDA illegal memory errors * odify dockerfile * Update docs/source/en/main_classes/model.mdx * Update Dockerfile * Update model.mdx * Update Dockerfile * Apply suggestions from code review * few modifications - lm head can stay on disk/cpu - change model name so that test pass * change test value - change test value to the correct output - torch bmm changed to baddmm in bloom modeling when merging * modify installation guidelines * Apply suggestions from code review Co-authored-by:
Joao Gante <joaofranciscocardosogante@gmail.com> * Update examples/tensorflow/test_tensorflow_examples.py Co-authored-by:
Julien Chaumond <julien@huggingface.co> * Address Julien's comments Co-authored-by:
📝 update philosophy to include other preprocessing classes *🖍 apply feedbacks * Properly move cache when it is not in default path (#18563) * Adds CLIP to models exportable with ONNX (#18515) * onnx config for clip * default opset as 14 * changes from the original repo * input values order fix * outputs fix * remove unused import * ran make fix-copies * black format * review comments: forward ref, import fix, model change revert, .to cleanup * make style * formatting fixes * revert groupvit * comment for cast to int32 * comment fix * make .T as .t() for onnx conversion * ran make fix-copies * remove unneeded comment Co-authored-by:Maxime Gardoni <maxime.gardoni@ecorobotix.com> * Fix resizing bug in OWL-ViT (#18573) * Fixes resizing bug in OWL-ViT * Defaults to square resize if size is set to an int * Sets do_center_crop default value to False * Fix LayoutLMv3 documentation (#17932) * fix typos * fix sequence_length docs of LayoutLMv3Model * delete trailing white spaces * fix layoutlmv3 docs more * apply make fixup & quality * change to two versions of input docstring * apply make fixup & quality * Skip broken tests * Change BartLearnedPositionalEmbedding's forward method signature to support Opacus training (#18486) * changing BartLearnedPositionalEmbedding forward signature and references to it * removing debugging dead code (thanks style checker) * blackened modeling_bart file * removing copy inconsistencies via make fix-copies * changing references to copied signatures in Bart variants * make fix-copies once more * using expand over repeat (thanks @michaelbenayoun) * expand instead of repeat for all model copies Co-authored-by:
Daniel Jones <jonesdaniel@microsoft.com> * german docs translation (#18544) * Create _config.py * Create _toctree.yml * Create index.mdx not sure about "du / ihr" oder "sie" * Create quicktour.mdx * Update _toctree.yml * Update build_documentation.yml * Update build_pr_documentation.yml * fix build * Update index.mdx * Update quicktour.mdx * Create installation.mdx * Update _toctree.yml * Deberta V2: Fix critical trace warnings to allow ONNX export (#18272) * Fix critical trace warnings to allow ONNX export * Force input to `sqrt` to be float type * Cleanup code * Remove unused import statement * Update model sew * Small refactor Co-authored-by:
dependabot[bot] <support@github.com> Signed-off-by:
dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com> * Bump nbconvert in /examples/research_projects/visual_bert (#18566) Bumps [nbconvert](https://github.com/jupyter/nbconvert) from 6.0.1 to 6.3.0. - [Release notes](https://github.com/jupyter/nbconvert/releases) - [Commits](https://github.com/jupyter/nbconvert/compare/6.0.1...6.3.0 ) --- updated-dependencies: - dependency-name: nbconvert dependency-type: direct:production ... Signed-off-by:
Wang, Yi A <yi.a.wang@intel.com> * Update docs/source/en/perf_train_cpu_many.mdx Co-authored-by:
sanchit-gandhi <sanchit@huggingface.co> * mac m1 `mps` integration (#18598) * mac m1 `mps` integration * Update docs/source/en/main_classes/trainer.mdx Co-authored-by:
Dan Saattrup Nielsen <47701536+saattrupdan@users.noreply.github.com> * resolve comment Co-authored-by:
Stas Bekman <stas00@users.noreply.github.com> * Apply suggestions from code review * Apply suggestions from code review * Apply suggestions from code review * put in one block - put bash instructions in one block * update readme - refactor a bit hardware requirements * change text a bit * Apply suggestions from code review Co-authored-by:
Yih-Dar <2521628+ydshieh@users.noreply.github.com> * apply suggestions Co-authored-by:
lewtun <lewis.c.tunstall@gmail.com> Co-authored-by:
Amy Roberts <amyeroberts@users.noreply.github.com> Co-authored-by:
regisss <15324346+regisss@users.noreply.github.com> Co-authored-by:
Nicolas Patry <patry.nicolas@protonmail.com> Co-authored-by:
Sourab Mangrulkar <13534540+pacman100@users.noreply.github.com> Co-authored-by:
Ankur Goyal <ankrgyl@gmail.com> Co-authored-by:
Steven Liu <59462357+stevhliu@users.noreply.github.com> Co-authored-by:
Mishig Davaadorj <dmishig@gmail.com> Co-authored-by:
Rasmus Arpe Fogh Jensen <Rasmus.arpe@gmail.com> Co-authored-by:
Ian Castillo <7807897+donelianc@users.noreply.github.com> Co-authored-by:
AguilaCudicio <aguila.cudicio@gmail.com> Co-authored-by:
Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by:
Niklas Hansson <niklas.sven.hansson@gmail.com> Co-authored-by:
Thomas Chaigneau <t.chaigneau.tc@gmail.com> Co-authored-by:
YouJiacheng <1503679330@qq.com> Co-authored-by:
Matt <Rocketknight1@users.noreply.github.com> Co-authored-by:
Dhruv Karan <k4r4n.dhruv@gmail.com> Co-authored-by:
Michael Wyatt <mrwyattii@gmail.com> Co-authored-by:
Maxime G <joihn@users.noreply.github.com> Co-authored-by:
Wonseok Lee (Jack) <rollerkid02@snu.ac.kr> Co-authored-by:
Dan Jones <dan.j.jones2@gmail.com> Co-authored-by:
flozi00 <flozi00.fz@gmail.com> Co-authored-by:
iiLaurens <iiLaurens@users.noreply.github.com> Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> Co-authored-by:
Niklas Muennighoff <n.muennighoff@gmail.com> Co-authored-by:
Karim Foda <35491698+KMFODA@users.noreply.github.com> Co-authored-by:
zhoutang776 <47708118+zhoutang776@users.noreply.github.com> Co-authored-by:
Stefan Schweter <stefan@schweter.it> Co-authored-by:
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- 12 Oct, 2022 1 commit
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amyeroberts authored
* Adapt FE methods to transforms library * Mixin for saving the image processor * Base processor skeleton * BatchFeature for packaging image processor outputs * Initial image processor for GLPN * REmove accidental import * Fixup and docs * Mixin for saving the image processor * Fixup and docs * Import BatchFeature from feature_extraction_utils * Fixup and docs * Fixup and docs * Fixup and docs * Fixup and docs * BatchFeature for packaging image processor outputs * Import BatchFeature from feature_extraction_utils * Import BatchFeature from feature_extraction_utils * Fixup and docs * Fixup and docs * BatchFeature for packaging image processor outputs * Import BatchFeature from feature_extraction_utils * Fixup and docs * Mixin for saving the image processor * Fixup and docs * Add rescale back and remove ImageType * fix import mistake * Fix enum var reference * Can transform and specify image data format * Remove redundant function * Update reference * Data format flag for rescale * Fix typo * Fix dimension check * Fixes to make IP and FE outputs match * Add tests for transforms * Add test for utils * Update some docstrings * Make sure in channels last before converting to PIL * Remove default to numpy batching * Fix up * Add docstring and model_input_types * Use feature processor config from hub * Alias GLPN feature extractor to image processor * Alias feature extractor mixin * Add return_numpy=False flag for resize * Fix up * Fix up * Use different frameworks safely * Safely import PIL * Call function checking if PIL available * Only import if vision available * Address Sylvain PR comments Co-authored-by: Sylvain.gugger@gmail.com * Apply suggestions from code review Co-authored-by:
😬 (#18489) * Delete valohai.yaml * NLP => ML * typo * website supports https * datasets * 60k + modalities * unrelated link fixing for accelerate * Ok those links were actually broken * Fix link * Make `AutoTokenizer` auto-link * wording tweak * add at least one non-nlp task * `transformers-cli login` => `huggingface-cli login` (#18490) * zero chance anyone's using that constant no? * `transformers-cli login` => `huggingface-cli login` * `transformers-cli repo create` => `huggingface-cli repo create` * `make style` * Add seed setting to image classification example (#18519) * [DX fix] Fixing QA pipeline streaming a dataset. (#18516) * [DX fix] Fixing QA pipeline streaming a dataset. QuestionAnsweringArgumentHandler would iterate over the whole dataset effectively killing all properties of the pipeline. This restores nice properties when using `Dataset` or `Generator` since those are meant to be consumed lazily. * Handling TF better. * Clean up hub (#18497) * Clean up utils.hub * Remove imports * More fixes * Last fix * update fsdp docs (#18521) * updating fsdp documentation * typo fix * Fix compatibility with 1.12 (#17925) * Fix compatibility with 1.12 * Remove pin from examples requirements * Update torch scatter version * Fix compatibility with 1.12 * Remove pin from examples requirements * Update torch scatter version * fix torch.onnx.symbolic_opset12 import * Reject bad version Co-authored-by:✨ update to use interlibrary links instead of Markdown (#18500) * Add example of multimodal usage to pipeline tutorial (#18498) *📝 add example of multimodal usage to pipeline tutorial *🖍 apply feedbacks *🖍 apply niels feedback * [VideoMAE] Add model to doc tests (#18523) * Add videomae to doc tests * Add pip install decord Co-authored-by:📝 update metric with evaluate (#18535) * Restore _init_weights value in no_init_weights (#18504) * Recover _init_weights value in no_init_weights For potential nested use. In addition, users might modify private no_init_weights as well. * Apply suggestions from code review Co-authored-by:📝 update documentation build section (#18548) * `bitsandbytes` - `Linear8bitLt` integration into `transformers` models (#17901) * first commit * correct replace function * add final changes - works like charm! - cannot implement tests yet - tested * clean up a bit * add bitsandbytes dependencies * working version - added import function - added bitsandbytes utils file * small fix * small fix - fix import issue * fix import issues * Apply suggestions from code review Co-authored-by:📝 update philosophy to include other preprocessing classes *🖍 apply feedbacks * Properly move cache when it is not in default path (#18563) * Adds CLIP to models exportable with ONNX (#18515) * onnx config for clip * default opset as 14 * changes from the original repo * input values order fix * outputs fix * remove unused import * ran make fix-copies * black format * review comments: forward ref, import fix, model change revert, .to cleanup * make style * formatting fixes * revert groupvit * comment for cast to int32 * comment fix * make .T as .t() for onnx conversion * ran make fix-copies * remove unneeded comment Co-authored-by:
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