- 06 Feb, 2023 1 commit
-
-
Sylvain Gugger authored
* Result of black 23.1 * Update target to Python 3.7 * Switch flake8 to ruff * Configure isort * Configure isort * Apply isort with line limit * Put the right black version * adapt black in check copies * Fix copies
-
- 02 Feb, 2023 1 commit
-
-
Joel Lamy-Poirier authored
* gelu_python_tanh * rename * Version check, add test * Pr comment
-
- 26 Jan, 2023 1 commit
-
-
amyeroberts authored
* Accept a batched tensor of images as input * Add to all image processors * Update oneformer
-
- 17 Jan, 2023 2 commits
-
-
Nicolas Patry authored
* Fixing offline mode for pipeline (when inferring task). * Update src/transformers/pipelines/__init__.py Co-authored-by:
Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * Updating test to reflect change in exception. * Fixing offline mode. * Clean. Co-authored-by:
-
amyeroberts authored
* Rename files * Update file names in tests
-
- 30 Nov, 2022 1 commit
-
-
Matt authored
* Fixed test_saved_model_extended * Fix TFGPT2 tests * make fixup * Make sure keras-nlp utils are available for type hinting too * Update src/transformers/testing_utils.py Co-authored-by:
Yih-Dar <2521628+ydshieh@users.noreply.github.com> * make fixup Co-authored-by:
-
- 28 Nov, 2022 2 commits
-
-
amyeroberts authored
-
Matt authored
* Add a test to ensure int dummy inputs are int64 * Move the test into the existing int64 test and update a lot of existing dummies * Fix remaining dummies * Fix remaining dummies * Test for int64 serving sigs as well * Update core tests to use tf.int64 * Add better messages to the assertions * Update all serving sigs to int64 * More sneaky hiding tf.int32s * Add an optional int32 signature in save_pretrained * make fixup * Add Amy's suggestions * Switch all serving sigs back to tf.int32 * Switch all dummies to tf.int32 * Adjust tests to check for tf.int32 instead of tf.int64 * Fix base dummy_inputs dtype * Start casting to tf.int32 in input_processing * Change dtype for unpack_inputs test * Add proper tf.int32 test * Make the alternate serving signature int64
-
- 23 Nov, 2022 1 commit
-
-
Sylvain Gugger authored
-
- 21 Nov, 2022 1 commit
-
-
Konstantin Dobler authored
* Enhance HfArgumentParser * Fix type hints for older python versions * Fix and add tests (+formatting) * Add changes * doc-builder formatting * Remove unused import "Call"
-
- 02 Nov, 2022 1 commit
-
-
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:
Alara Dirik <8944735+alaradirik@users.noreply.github.com> * Update src/transformers/image_processing_utils.py Co-authored-by:
NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/beit/image_processing_beit.py Co-authored-by:
-
- 24 Oct, 2022 1 commit
-
-
Sylvain Gugger authored
* Refactor conversion function * Remove dupe line * Fixes * Fixes * Use the right variable... * Fix last test
-
- 18 Oct, 2022 1 commit
-
-
Sylvain Gugger authored
-
- 17 Oct, 2022 1 commit
-
-
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:
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:
-
- 12 Oct, 2022 1 commit
-
-
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:
-
- 27 Sep, 2022 2 commits
-
-
IMvision12 authored
* Added tests for yaml and json * Added tests for yaml and json
-
Sylvain Gugger authored
* More tests for regression in cached non existence * Style
-
- 26 Sep, 2022 1 commit
-
-
Sylvain Gugger authored
* Fix cached_file in offline mode for cached non-existing files * Add tests * Test with offline mode
-
- 21 Sep, 2022 1 commit
-
-
Sylvain Gugger authored
-
- 02 Sep, 2022 1 commit
-
-
Sylvain Gugger authored
* Clean up utils.hub using the latest from hf_hub * Adapt test * Address review comment * Fix test
-
- 31 Aug, 2022 1 commit
-
-
Felix Schneider authored
Add an option to `HfArgumentParser.parse_{dict,json_file}` to raise an Exception when there extra keys (#18692) * Update parser to track unneeded keys, off by default * Fix formatting * Fix docstrings and defaults in HfArgparser * Fix formatting
-
- 17 Aug, 2022 1 commit
-
-
amyeroberts authored
* Update methods to optionally rescale This is necessary to allow for casting our images / videos to numpy arrays within the feature extractors' call. We want to do this to make sure the behaviour is as expected when flags like are False. If some transformations aren't applied, then the output type can't be unexpected e.g. a list of PIL images instead of numpy arrays. * Cast images to numpy arrays in call to enable consistent behaviour with different configs * Remove accidental clip changes * Update tests to reflect the scaling logic We write a generic function to handle rescaling of our arrays. In order for the API to be intuitive, we take some factor c and rescale the image values by that. This means, the rescaling done in normalize and to_numpy_array are now done with array * (1/255) instead of array / 255. This leads to small differences in the resulting image. When testing, this was in the order of 1e-8, and so deemed OK
-
- 08 Aug, 2022 1 commit
-
-
Sylvain Gugger authored
* Clean up utils.hub * Remove imports * More fixes * Last fix
-
- 22 Jul, 2022 1 commit
-
-
amyeroberts authored
* Add serving_output and serving methods to some vision models * Add serving outputs for DeiT * Don't convert hidden states - differing shapes * Make saveable * Fix up * Make swin saveable * Add in tests * Fix funnel tests (can't convert to tensor) * Fix numpy call * Tidy up a bit * Add in hidden states - resnet * Remove numpy * Fix failing tests - tensor shape and skipping tests * Remove duplicated function * PR comments - formatting and var names * PR comments Add suggestions made by Joao Gante: * Use tf.shape instead of shape_list * Use @tooslow decorator on tests * Simplify some of the logic * PR comments Address Yih-Dar Sheih comments - making tensor names consistent and make types float * Types consistent with docs; disable test on swin (slow) * CI trigger * Change input_features to float32 * Add serving_output for segformer * Fixup Co-authored-by:
-
- 19 Jul, 2022 1 commit
-
-
Joao Gante authored
* Fix TF GPT-J tests * add try/finally block
-
- 13 Jul, 2022 1 commit
-
-
Sylvain Gugger authored
* Make sharded checkpoints work in offline mode * Add test
-
- 12 Jul, 2022 1 commit
-
-
Joao Gante authored
-
- 06 Jul, 2022 1 commit
-
-
Sylvain Gugger authored
-
- 01 Jul, 2022 1 commit
-
-
Matt authored
* Copy inputs to train and test step before modifying them, as this breaks things * Add XLA tests, fix our loss functions to be XLA-compatible * make fixup * Update loss computation test to expect vector of per-sample losses * Patch loss for TFLED * Patch loss for TFAlbert * Add a tf_legacy_loss config flag that enables old loss functions * Stop using config.get() because it's not a dict * Skip loss computation test for RAG because its loss is very strange and I'm afraid to rewrite it * make fixup * Add XLA-compatible RAG loss * Fix dtype of loss mask for TFAlbert * Fix test for XLNet too because it overrides the default one * make fixup * Fix config test * No more depending on GPU NaN behaviour * Add test, avoid potential zero division * Fix test item assignment * Fix loss computation masking test * make fixup * Fix dtype bugs
-
- 10 Jun, 2022 2 commits
-
-
Simon Brandeis authored
* Raise RepoNotFoundError in case of 401 * Include changes from revert-17646-skip_repo_not_found * Add a comment *
💄 Code quality *💚 Update `get_from_cache` test *💚 Code quality & skip failing test -
Sylvain Gugger authored
-
- 01 Jun, 2022 1 commit
-
-
Joao Gante authored
-
- 17 May, 2022 1 commit
-
-
Matt authored
* Fix tests of mixed precision now that experimental is deprecated * Fix mixed precision in training_args_tf.py too
-
- 12 May, 2022 1 commit
-
-
Sylvain Gugger authored
* Black preview * Fixup too! * Fix check copies * Use the same version as the CI * Bump black
-
- 10 May, 2022 1 commit
-
-
Nicolas Brousse authored
* add support for MLFLOW_FLATTEN_PARAMS * ensure key is str * fix style and update warning msg * Empty commit to trigger CI * fix bug in check_inits.py * add unittest for flatten_dict utils * fix 'NoneType' object is not callable on __del__ * add generic flatten_dict unittest to SPECIAL_MODULE_TO_TEST_MAP * fix style
-
- 03 May, 2022 1 commit
-
-
Yih-Dar authored
* move test model folders (TODO: fix imports and others) * fix (potentially partially) imports (in model test modules) * fix (potentially partially) imports (in tokenization test modules) * fix (potentially partially) imports (in feature extraction test modules) * fix import utils.test_modeling_tf_core * fix path ../fixtures/ * fix imports about generation.test_generation_flax_utils * fix more imports * fix fixture path * fix get_test_dir * update module_to_test_file * fix get_tests_dir from wrong transformers.utils * update config.yml (CircleCI) * fix style * remove missing imports * update new model script * update check_repo * update SPECIAL_MODULE_TO_TEST_MAP * fix style * add __init__ * update self-scheduled * fix add_new_model scripts * check one way to get location back * python setup.py build install * fix import in test auto * update self-scheduled.yml * update slack notification script * Add comments about artifact names * fix for yolos Co-authored-by:
-
- 19 Apr, 2022 1 commit
-
-
Joao Gante authored
-
- 11 Apr, 2022 1 commit
-
-
SaulLu authored
* update proto sentencepiece model * Revert "update proto sentencepiece model" This reverts commit b07f671747fec35773d0b3d4788b8b15aefa0229. * add check * add test * Revert "Revert "update proto sentencepiece model"" This reverts commit 46108257b8927b73627ec8f4f3eed53a95fc700d. * test for log level * test for log level 2 * warning at the warning level * clean * format * add explanation in docstring
-
- 04 Apr, 2022 1 commit
-
-
Sylvain Gugger authored
* Add utility to find model labels * Use it in the Trainer * Update src/transformers/utils/generic.py Co-authored-by:
-
- 23 Mar, 2022 1 commit
-
-
Sylvain Gugger authored
* Make Transformers use cache files when hf.co is down * Fix tests * Was there a random circleCI failure? * Isolate patches * Style * Comment out the failure since it doesn't fail anymore * Better comment
-
