- 19 Dec, 2022 1 commit
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Andreas Madsen authored
* Copy RoBERTa * formatting * implement RoBERTa with prelayer normalization * update test expectations * add documentation * add convertion script for DinkyTrain weights * update checkpoint repo Unfortunately the original checkpoints assumes a hacked roberta model * add to RoBERTa-PreLayerNorm docs to toc * run utils/check_copies.py * lint files * remove unused import * fix check_repo reporting wrongly a test is missing * fix import error, caused by rebase * run make fix-copies * add RobertaPreLayerNormConfig to ROBERTA_EMBEDDING_ADJUSMENT_CONFIGS * Fix documentation <Facebook> -> Facebook Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * fixup: Fix documentation <Facebook> -> Facebook Co-authored-by:
Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * make fix-copies * Remove EXPECTED_SLICE calculation comments Co-authored-by:
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- 16 Dec, 2022 2 commits
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Nicolas Patry authored
* Revert "Fixing object detection with `layoutlm` (#20776)" This reverts commit fca66abe. * Better fix for layoutlm object detection. * Style.
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Younes Belkada authored
skip feature extraction test if in `IMAGE_PROCESSOR_MAPPING`
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- 15 Dec, 2022 3 commits
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Nicolas Patry authored
* Fixing object detection with layoutlm. * Fixup.
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Younes Belkada authored
fix failing `pipeline` test
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Nicolas Patry authored
* Even more validation. * Fixing order.
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- 13 Dec, 2022 1 commit
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Yih-Dar authored
* Fix the pipeline test regarding TF * Fix the pipeline test regarding TF * update comment Co-authored-by:ydshieh <ydshieh@users.noreply.github.com>
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- 12 Dec, 2022 1 commit
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Nicolas Patry authored
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- 08 Dec, 2022 1 commit
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Nathan Raw authored
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🚧 wip video classification pipeline *🚧 wip - add is_decord_available check *🐛 add missing import *✅ add tests *🔧 add decord to setup extras *🚧 add is_decord_available *✨ add video-classification pipeline *📝 add video classification pipe to docs *🐛 add missing VideoClassificationPipeline import *📌 add decord install in test runner *✅ fix url inputs to video-classification pipeline *✨ updates from review *📝 add video cls pipeline to docs *📝 add docstring *🔥 remove unused import *🔥 remove some code *📝 docfix
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- 07 Dec, 2022 1 commit
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Yih-Dar authored
* update summarization run_pipeline_test * update Co-authored-by:
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- 06 Dec, 2022 1 commit
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Yih-Dar authored
* Remove assert exception not triggered * Fix wrong expected exception string * fix * use assertRaisesRegex Co-authored-by:
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- 05 Dec, 2022 2 commits
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Arthur authored
* Expected output for the test changed * fix failing asr test
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Yih-Dar authored
Co-authored-by:
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- 21 Nov, 2022 1 commit
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NielsRogge authored
* First draft * Make conversion script work * Add id2label mapping, run code quality * Fix copies * Add first draft of feature extractor * Update conversion script to use feature extractor * Make more tests pass * Add docs * update input_features to input_values + pad by default to max length * Fix doc tests * Add feature extractor tests * Add proper padding/truncation to feature extractor * Add support for conversion of all audioset checkpoints * Improve docs and extend conversion script * Fix README * Rename spectogram to spectrogram * Fix copies * Add integration test * Remove dummy conv * Update to ast * Update organization * Fix init * Rename model to AST * Add require_torchaudio annotator * Move import of ASTFeatureExtractor under a is_speech_available * Fix rebase * Add pipeline config * Update name of classifier head * Rename time_dimension and frequency_dimension for clarity * Remove print statement * Fix pipeline test * Fix pipeline test * Fix index table * Fix init * Fix conversion script * Rename to ForAudioClassification * Fix index table Co-authored-by:Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
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- 18 Nov, 2022 1 commit
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Nicolas Patry authored
* [Proposal] Breaking change `zero-shot-object-detection` for improved consistency. This is a proposal to modify the output of `zero-shot-object-detection` to provide better alignment with other pipelines. The output is now strictly the same as `object-detection` whereas before it would output lists of lists. The name `candidate_labels` is used throughout for consistency with other `zero-shot` pipelines. The pipeline is changed to `ChunkPipeline` to support batching cleanly. This removes all the lists and list of lists shenanigans, it's now a matter of the base pipeline handling all this not this specific one. **Breaking change**: It did remove complex calls potentials `pipe(images = [image1, image2], text_queries=[candidates1, candidates2])` to support only `pipe([{"image": image1, "candidate_labels": candidates1}, {"image": image2, "candidate_labels": candidates2}])` when dealing with lists and/or datasets. We could keep them, but it will add a lot of complexity to the code base, since the pipeline is rather young, I'd rather break to keep the code simpler, but we can revert this. **Breaking change**: The name of the argument is now `image` instead of `images` since it expects by default only 1 image. This is revertable like the previous one. **Breaking change**: The types is now simplified and flattened: `pipe(inputs) == [{**object1}, {**object2}]` instead of the previous `pipe(inputs) == [[{**object1}, {**object1}], [{**object2}]]` Where the different instances would be grouped by candidate labels within lists. IMHO this is not really desirable, since it would output empty lists and is only adding superflous indirection compared to `zero-shot-object-detection`. It is relatively change free in terms of how the results, it does change computation however since now the batching is handled by the pipeline itself. It **did** change the results for the small models so there seems to be a real difference in how the models handle this. * Fixing the doctests. * Behind is_torch_available.
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- 15 Nov, 2022 2 commits
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Younes Belkada authored
* first commit * add more comments * add router v1 * clean up - remove `tf` modeling files * clean up - remove `tf` modeling files * clean up * v0 routers * added more router - Implemented `ExpertsChooseMaskedRouter` - added tests - 2 more routers to implement * last router * improved docstring - completed the docstring in `router.py` - added more args in the config * v0 sparse mlp * replace wrong naming * forward pass run * update MOE layer * small router update * fixup * consistency * remove scatter router * remove abstract layer * update test and model for integration testing * v1 conversion * update * hardcode hack * all keys match * add gin conversion, without additional libraries * update conversion sctipy * delete router file * update tests wrt router deletion * fix router issues * update expert code * update, logits match, code needsREFACTORING * Refactor code Co-authored-by:
Younes Belkada <younesbelkada@users.noreply.github.com> * add generate tests Co-authored-by:
younesbelkada <younesbelkada@gmail.com> * add support for router loss Co-authored-by:
Arthur Zucker <arthur.zucker@gmail.com> Co-authored-by:
ybelkada <younes@huggingface.co> Co-authored-by:
Arthur Zucker <arthur@huggingface.co>
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Yih-Dar authored
* Fix ImageSegmentationPipelineTests * Use 0.9 * no zip * links to show images * links to show images * rebase Co-authored-by:
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- 14 Nov, 2022 2 commits
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Nicolas Patry authored
* Very crude matching algorithm. * Fixing tests. * Removing comments * Adding warning + fix short matches. * Cleanup tests. * Quality. * Less noisy. * Fixup.
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Bartosz Szmelczynski authored
* First draft * Remove scatter dependency * Add require_torch * update vectorized sum test, add clone call * remove artifacts * fix style * fix style v2 * remove "scatter" mentions from the code base * fix isort error Co-authored-by:
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- 10 Nov, 2022 2 commits
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Sylvain Gugger authored
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Nicolas Patry authored
* Adding support for LayoutLMvX variants for `object-detection`. * Revert bogs `layoutlm` feature extractor which does not exist (it was a V2 model) . * Updated condition. * Handling the comments.
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- 03 Nov, 2022 1 commit
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Nicolas Patry authored
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- 26 Oct, 2022 1 commit
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Nicolas Patry authored
* Factored out some code in the image-segmentation pipeline Re-enable `small_model_pt`. Re-enable `small_model_pt`. Enabling the current test with the current values. Debugging the values on the CI. More logs ? Printing doesn't work ? Using the CI values instead. Seems to be a Pillow sensitivity. Added a test showcasing that models not supporting some tasks get a clear error. Factored out code. Further factor out. Fixup. Bad rebase. Put `panoptic` before `instance` as it should be a superset. * Fixing tests. * Adding subtasks tests + Fixes `instance` segmentation which was broken due to default and non kwargs arguments. * Fix bad replace.
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- 24 Oct, 2022 1 commit
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Rak Alexey authored
* fix image2test args forwarding * fix issues * Proposing the update to the PR. * Fixup. Co-authored-by:Nicolas Patry <patry.nicolas@protonmail.com>
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- 21 Oct, 2022 2 commits
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Alara Dirik authored
* Fix panoptic segmentation and pipeline * Update ImageSegmentationPipeline tests and reenable test_small_model_pt * Resolve backward compatibility issues
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Yih-Dar authored
* update expected values for the correct TF checkpoint * Run test * Clean up * fix Co-authored-by:
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- 20 Oct, 2022 1 commit
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Nicolas Patry authored
* Re-enable `small_model_pt`. Re-enable `small_model_pt`. Enabling the current test with the current values. Debugging the values on the CI. More logs ? Printing doesn't work ? Using the CI values instead. Seems to be a Pillow sensitivity. * Update src/transformers/pipelines/image_segmentation.py Co-authored-by:
Alara Dirik <8944735+alaradirik@users.noreply.github.com> Co-authored-by:
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- 19 Oct, 2022 1 commit
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Yih-Dar authored
Co-authored-by:
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- 18 Oct, 2022 6 commits
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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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Yih-Dar authored
Co-authored-by: -
Nicolas Patry authored
This PR (https://github.com/huggingface/transformers/pull/19367) introduced a few breaking changes: - Removed an argument `mask_threshold`. - Broke the default behavior (instance vs panoptic in the function call) https://github.com/huggingface/transformers/pull/19367/files#diff-60f846b86fb6a21d4caf60f5b3d593a04accb8f248de3029cccae2ff898c5bc3R119-R120 - Broke the actual masks: https://github.com/huggingface/transformers/pull/1961 This PR is the start of a handful that will aim at bringing back the old behavior(s). - tests should not have to specify `task` by default, unless we want to modify the behavior and have a lower form of segmentation running) - `test_small_model_pt` should be working. This specific PR starts with adding more information to the masks hash because missing the actual mask was actual easy to miss (the hashes do change, but it was easy to miss that one code path wasn't properly updated). So we go from a simple `hash` to ``` {"hash": #smaller hash, "shape": (h, w), "white_pixels": n} ``` The `shape` should help make sure the interpolation of the mask works correctly, the `white_pixels` hopefully helps detect big regressions in their amount when the hash gets modified.
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Nicolas Patry authored
* add return_tensors parameter for feature_extraction w/ test add return_tensor parameter for feature extraction Revert "Merge branch 'feature-extraction-return-tensor' of https://github.com/ajsanjoaquin/transformers into feature-extraction-return-tensor" This reverts commit d559da743b87914e111a84a98ba6dbb70d08ad88, reversing changes made to bbef89278650c04c090beb65637a8e9572dba222. call parameter directly Co-authored-by:
AJ San Joaquin <ajsanjoaquin@gmail.com> Co-authored-by:
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Nicolas Patry authored
🚨 🚨 🚨 [Breaking change] Deformable DETR intermediate representations (#19678) * [Breaking change] Deformable DETR intermediate representations - Fixes naturally the `object-detection` pipeline. - Moves from `[n_decoders, batch_size, ...]` to `[batch_size, n_decoders, ...]` instead. * Apply suggestions from code review Co-authored-by: -
Arthur authored
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- 17 Oct, 2022 5 commits
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Sylvain Gugger authored
This reverts commit 35bd089a.
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Ayrton San Joaquin authored
* add return_tensors parameter for feature_extraction w/ test add return_tensor parameter for feature extraction Revert "Merge branch 'feature-extraction-return-tensor' of https://github.com/ajsanjoaquin/transformers into feature-extraction-return-tensor" This reverts commit d559da743b87914e111a84a98ba6dbb70d08ad88, reversing changes made to bbef89278650c04c090beb65637a8e9572dba222. * call parameter directly Co-authored-by:
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Ankur Goyal authored
* Fixes * update expected values * style * fix Co-authored-by: -
Matt authored
* Partial TF port for ESM model * Add ESM-TF tests * Add the various imports for TF-ESM * TF weight conversion almost ready * Stop ignoring the decoder weights in PT * Add tests and lots of fixes * fix-copies * Fix imports, add model docs * Add get_vocab() to tokenizer * Fix vocab links for pretrained files * Allow multiple inputs with a sep * Use EOS as SEP token because ESM vocab lacks SEP * Correctly return special tokens mask from ESM tokenizer * make fixup * Stop testing unsupported embedding resizing * Handle TF bias correctly * Skip all models with slow tokenizers in the token classification test * Fixing the batch/unbatcher of pipelines to accomodate the `None` being passed around. * Fixing pipeline bug caused by slow tokenizer being different. * Update src/transformers/models/esm/modeling_tf_esm.py Co-authored-by:
Joao Gante <joaofranciscocardosogante@gmail.com> * Update src/transformers/models/esm/modeling_tf_esm.py Co-authored-by:
Your Name <you@example.com> Co-authored-by:
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Sivaudha authored
* Remove key word argument X from pipeline predict and transform methods As __call__ of pipeline clasees require one positional argument, passing the input as a keyword argument inside predict, transform methods, causing __call__ to fail. Hence in this commit the keyword argument is modified into positional argument. * Implement basic tests for scikitcompat pipeline interface * Seperate tests instead of running with parameterized based on framework as both frameworks will not be active at the same time
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- 14 Oct, 2022 1 commit
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Nicolas Patry authored
* Improve error messaging for ASR pipeline. - Raise error early (in `_sanitize`) so users don't waste time trying to run queries with invalid params. - Fix the error was after using `config.inputs_to_logits_ratio` so our check was masked by the failing property does not exist. - Added some manual check on s2t for the error message. No non ctc model seems to be used by the default runner (they are all skipped). * Removing pdb. * Stop the early error it doesn't really work :(.
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