mirror of
https://github.com/huggingface/transformers.git
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46d636818b
687 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
Bo Zheng
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46d636818b
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Update model card and link of blog post. (#29928)
* Update qwen2_moe.md * update link of blogpost. * fixup --------- Co-authored-by: bozheng-hit <dsoul0621@gmail.com> |
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Bo Zheng
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1c39974a4c
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Add Qwen2MoE (#29377)
* add support for qwen2 MoE models * update docs * add support for qwen2 MoE models * update docs * update model name & test * update readme * update class names & readme & model_doc of Qwen2MoE. * update architecture name * fix qwen2_moe tests * use Qwen2Tokenizer instead of Qwen2MoeTokenizer * update modeling_qwen2_moe.py * fix model architecture * fix qwen2_moe tests * use Qwen2Tokenizer instead of Qwen2MoeTokenizer * update modeling_qwen2_moe.py * fix model architecture * fix style * fix test when there are sparse and non sparse layers * fixup * Update README.md Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * fixup * fixup * add archive back * add support for qwen2 MoE models * update docs * update model name & test * update readme * update class names & readme & model_doc of Qwen2MoE. * update architecture name * fix qwen2_moe tests * use Qwen2Tokenizer instead of Qwen2MoeTokenizer * update modeling_qwen2_moe.py * fix model architecture * fixup * fix qwen2_moe tests * use Qwen2Tokenizer instead of Qwen2MoeTokenizer * fix style * fix test when there are sparse and non sparse layers * fixup * add archive back * fix integration test * fixup --------- Co-authored-by: bozheng-hit <dsoul0621@gmail.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> |
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NielsRogge
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d91fd7f92c
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Add LLaVa-1.6, bis (#29586)
* First draft * Fix tests, add docs * Improve docstrings * Fix test * Address comments * Address comments * Remove vocab_size attribute * Remove batch_size * Address comment * Add image processor tests * Support fx * Update docstring * Add support for 34b * Convert 34b model * Add integration tests * Update checkpoints * Convert vicuna-13b, remove doc tests * Remove script * Remove file * Address comments * Improve docstrings * Deprecate vocab_size * Remove aspect_ratio_setting * Address comments * Update READMEs * Add tips about chat templates * Fix tests * Deprecate vocab_size safely * Update tests --------- Co-authored-by: Amy Roberts <22614925+amyeroberts@users.noreply.github.com> |
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Arthur Zucker
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1248f09252 | v4.40.0.dev.0 | ||
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StevenBucaille
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56baa03380
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Implementation of SuperPoint and AutoModelForKeypointDetection (#28966)
* Added SuperPoint docs * Added tests * Removed commented part * Commit to create and fix add_superpoint branch with a new branch * Fixed dummy_pt_objects * Committed missing files * Fixed README.md * Apply suggestions from code review Fixed small changes Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Moved ImagePointDescriptionOutput from modeling_outputs.py to modeling_superpoint.py * Removed AutoModelForKeypointDetection and related stuff * Fixed inconsistencies in image_processing_superpoint.py * Moved infer_on_model logic simply in test_inference * Fixed bugs, added labels to forward method with checks whether it is properly a None value, also added tests about this logic in test_modeling_superpoint.py * Added tests to SuperPointImageProcessor to ensure that images are properly converted to grayscale * Removed remaining mentions of MODEL_FOR_KEYPOINT_DETECTION_MAPPING * Apply suggestions from code review Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Fixed from (w, h) to (h, w) as input for tests * Removed unnecessary condition * Moved last_hidden_state to be the first returned * Moved last_hidden_state to be the first returned (bis) * Moved last_hidden_state to be the first returned (ter) * Switched image_width and image_height in tests to match recent changes * Added config as first SuperPointConvBlock init argument * Reordered README's after merge * Added missing first config argument to SuperPointConvBlock instantiations * Removed formatting error * Added SuperPoint to README's de, pt-br, ru, te and vi * Checked out README_fr.md * Fixed README_fr.md * Test fix README_fr.md * Test fix README_fr.md * Last make fix-copies ! * Updated checkpoint path * Removed unused SuperPoint doc * Added missing image * Update src/transformers/models/superpoint/modeling_superpoint.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Removed unnecessary import * Update src/transformers/models/superpoint/modeling_superpoint.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Added SuperPoint to _toctree.yml --------- Co-authored-by: steven <steven.bucaillle@gmail.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by: Steven Bucaille <steven.bucaille@buawei.com> |
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Yoach Lacombe
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c43b380e70
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Add MusicGen Melody (#28819)
* first modeling code * make repository * still WIP * update model * add tests * add latest change * clean docstrings and copied from * update docstrings md and readme * correct chroma function * correct copied from and remove unreleated test * add doc to toctree * correct imports * add convert script to notdoctested * Add suggestion from Sanchit Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * correct get_uncoditional_inputs docstrings * modify README according to SANCHIT feedback * add chroma to audio utils * clean librosa and torchaudio hard dependencies * fix FE * refactor audio decoder -> audio encoder for consistency with previous musicgen * refactor conditional -> encoder * modify sampling rate logics * modify license at the beginning * refactor all_self_attns->all_attentions * remove ignore copy from causallm generate * add copied from for from_sub_models * fix make copies * add warning if audio is truncated * add copied from where relevant * remove artefact * fix convert script * fix torchaudio and FE * modify chroma method according to feedback-> better naming * refactor input_values->input_features * refactor input_values->input_features and fix import fe * add input_features to docstrigs * correct inputs_embeds logics * remove dtype conversion * refactor _prepare_conditional_hidden_states_kwargs_for_generation ->_prepare_encoder_hidden_states_kwargs_for_generation * change warning for chroma length * Update src/transformers/models/musicgen_melody/convert_musicgen_melody_transformers.py Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * change way to save wav, using soundfile * correct docs and change to soundfile * fix import * fix init proj layers * remove line breaks from md * fix issue with docstrings * add FE suggestions * improve is in logics and remove useless imports * remove custom from_pretrained * simplify docstring code * add suggestions for modeling tests * make style * update converting script with sanity check * remove encoder attention mask from conditional generation * replace musicgen melody checkpoints with official orga * rename ylacombe->facebook in checkpoints * fix copies * remove unecessary warning * add shape in code docstrings * add files to slow doc tests * fix md bug and add md to not_tested * make fix-copies * fix hidden states test and batching --------- Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> |
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Saurabh Dash
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0e4a1c3401
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Cohere Model Release (#29622)
* Cohere Model Release (#1) Cohere Model Release * Remove unnecessary files and code (#2) Some cleanup * Delete cohere-model directory (#3) * Make Fix (#5) * Pr fixes (#6) * fixes for pr * pr fixes for the format * pr fixes for the format * src/transformers/models/auto/tokenization_auto.py * Tokenizer test (#8) * tokenizer test * format fix * Adding Docs and other minor changes (#7) * Add modeling tests (#9) * Smol Fix (#11) * tokenization tests are fixed * format fixes * fix pr doc tests * fix pr doc tests * fix pr doc tests * fix pr style check * small changes in cohere.md * FIX: Address final comments for transformers integration (#13) * fix modeling final nits and add proper test file * for now leave empty tests * add integration test * push new test * fix modeling cohere (#14) * Update chat templates to use the new API (#15) --------- Co-authored-by: ahmetustun <ahmetustun89@gmail.com> Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by: Matt <Rocketknight1@users.noreply.github.com> |
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Nate Cibik
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1fc505b816
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Add PvT-v2 Model (#26812)
* Added pytests for pvt-v2, all passed
* Added pvt_v2 to docs/source/end/model_doc
* Ran fix-copies and fixup. All checks passed
* Added additional ReLU for linear attention mode
* pvt_v2_b2_linear converted and working
* copied models/pvt to adapt to pvt_v2
* First commit of pvt_v2
* PvT-v2 now works in AutoModel
* Reverted batch eval changes for PR
* Expanded type support for Pvt-v2 config
* Fixed config docstring. Added channels property
* Fixed model names in tests
* Fixed config backbone compat. Added additional type support for image size in config
* Fixed config backbone compat
* Allowed for batching of eval metrics
* copied models/pvt to adapt to pvt_v2
* First commit of pvt_v2
* Set key and value layers to use separate linear modules. Fixed pruning function
* Set AvgPool to 7
* Fixed issue in init
* PvT-v2 now works in AutoModel
* Successful conversion of pretrained weights for PVT-v2
* Successful conversion of pretrained weights for PVT-v2 models
* Added pytests for pvt-v2, all passed
* Ran fix-copies and fixup. All checks passed
* Added additional ReLU for linear attention mode
* pvt_v2_b2_linear converted and working
* Allowed for batching of eval metrics
* copied models/pvt to adapt to pvt_v2
* First commit of pvt_v2
* Set key and value layers to use separate linear modules. Fixed pruning function
* Set AvgPool to 7
* Fixed issue in init
* PvT-v2 now works in AutoModel
* Successful conversion of pretrained weights for PVT-v2
* Successful conversion of pretrained weights for PVT-v2 models
* Added pytests for pvt-v2, all passed
* Ran fix-copies and fixup. All checks passed
* Added additional ReLU for linear attention mode
* pvt_v2_b2_linear converted and working
* Reverted batch eval changes for PR
* Updated index.md
* Expanded type support for Pvt-v2 config
* Fixed config docstring. Added channels property
* Fixed model names in tests
* Fixed config backbone compat
* Ran fix-copies
* Fixed PvtV2Backbone tests
* Added TFRegNet to OBJECTS_TO_IGNORE in check_docstrings.py
* Fixed backbone stuff and fixed tests: all passing
* Ran make fixup
* Made modifications for code checks
* Remove ONNX config from configuration_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Use explicit image size dict in test_modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Make image_size optional in test_modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Remove _ntuple use in modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Remove reference to fp16_enabled
* Model modules now take config as first argument even when not used
* Replaced abbreviations for "SR" and "AP" with explicit "spatialreduction" and "averagepooling"
* All LayerNorm now instantiates with config.layer_norm_eps
* Added docstring for depth-wise conv layer
* PvtV2Config now only takes Union[int, Tuple[int, int]] for image size
* Refactored PVTv2 in prep for gradient checkpointing
* Gradient checkpointing ready to test
* Removed override of _set_gradient_checkpointing
* Cleaned out old code
* Applied code fixup
* Applied code fixup
* Began debug of pvt_v2 tests
* Leave handling of num_labels to base pretrained config class
* Deactivated gradient checkpointing tests until it is fixed
* Removed PvtV2ImageProcessor which duped PvtImageProcessor
* Allowed for batching of eval metrics
* copied models/pvt to adapt to pvt_v2
* First commit of pvt_v2
* Set key and value layers to use separate linear modules. Fixed pruning function
* Set AvgPool to 7
* Fixed issue in init
* PvT-v2 now works in AutoModel
* Successful conversion of pretrained weights for PVT-v2
* Successful conversion of pretrained weights for PVT-v2 models
* Added pytests for pvt-v2, all passed
* Added pvt_v2 to docs/source/end/model_doc
* Ran fix-copies and fixup. All checks passed
* Added additional ReLU for linear attention mode
* pvt_v2_b2_linear converted and working
* copied models/pvt to adapt to pvt_v2
* First commit of pvt_v2
* PvT-v2 now works in AutoModel
* Reverted batch eval changes for PR
* Expanded type support for Pvt-v2 config
* Fixed config docstring. Added channels property
* Fixed model names in tests
* Fixed config backbone compat. Added additional type support for image size in config
* Fixed config backbone compat
* Allowed for batching of eval metrics
* copied models/pvt to adapt to pvt_v2
* First commit of pvt_v2
* Set key and value layers to use separate linear modules. Fixed pruning function
* Set AvgPool to 7
* Fixed issue in init
* PvT-v2 now works in AutoModel
* Successful conversion of pretrained weights for PVT-v2
* Successful conversion of pretrained weights for PVT-v2 models
* Added pytests for pvt-v2, all passed
* Ran fix-copies and fixup. All checks passed
* Added additional ReLU for linear attention mode
* pvt_v2_b2_linear converted and working
* Allowed for batching of eval metrics
* copied models/pvt to adapt to pvt_v2
* First commit of pvt_v2
* Set key and value layers to use separate linear modules. Fixed pruning function
* Set AvgPool to 7
* Fixed issue in init
* PvT-v2 now works in AutoModel
* Successful conversion of pretrained weights for PVT-v2
* Successful conversion of pretrained weights for PVT-v2 models
* Added pytests for pvt-v2, all passed
* Ran fix-copies and fixup. All checks passed
* Added additional ReLU for linear attention mode
* pvt_v2_b2_linear converted and working
* Reverted batch eval changes for PR
* Expanded type support for Pvt-v2 config
* Fixed config docstring. Added channels property
* Fixed model names in tests
* Fixed config backbone compat
* Ran fix-copies
* Fixed PvtV2Backbone tests
* Added TFRegNet to OBJECTS_TO_IGNORE in check_docstrings.py
* Fixed backbone stuff and fixed tests: all passing
* Ran make fixup
* Made modifications for code checks
* Remove ONNX config from configuration_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Use explicit image size dict in test_modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Make image_size optional in test_modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Remove _ntuple use in modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Remove reference to fp16_enabled
* Model modules now take config as first argument even when not used
* Replaced abbreviations for "SR" and "AP" with explicit "spatialreduction" and "averagepooling"
* All LayerNorm now instantiates with config.layer_norm_eps
* Added docstring for depth-wise conv layer
* PvtV2Config now only takes Union[int, Tuple[int, int]] for image size
* Refactored PVTv2 in prep for gradient checkpointing
* Gradient checkpointing ready to test
* Removed override of _set_gradient_checkpointing
* Cleaned out old code
* Applied code fixup
* Applied code fixup
* Allowed for batching of eval metrics
* copied models/pvt to adapt to pvt_v2
* First commit of pvt_v2
* PvT-v2 now works in AutoModel
* Ran fix-copies and fixup. All checks passed
* copied models/pvt to adapt to pvt_v2
* First commit of pvt_v2
* PvT-v2 now works in AutoModel
* Reverted batch eval changes for PR
* Fixed config docstring. Added channels property
* Fixed config backbone compat
* Allowed for batching of eval metrics
* copied models/pvt to adapt to pvt_v2
* First commit of pvt_v2
* PvT-v2 now works in AutoModel
* Ran fix-copies and fixup. All checks passed
* Allowed for batching of eval metrics
* copied models/pvt to adapt to pvt_v2
* First commit of pvt_v2
* PvT-v2 now works in AutoModel
* Fixed config backbone compat
* Ran fix-copies
* Began debug of pvt_v2 tests
* Leave handling of num_labels to base pretrained config class
* Deactivated gradient checkpointing tests until it is fixed
* Removed PvtV2ImageProcessor which duped PvtImageProcessor
* Fixed issue from rebase
* Fixed issue from rebase
* Set tests for gradient checkpointing to skip those using reentrant since it isn't supported
* Fixed issue from rebase
* Fixed issue from rebase
* Changed model name in docs
* Removed duplicate PvtV2Backbone
* Work around type switching issue in tests
* Fix model name in config comments
* Update docs/source/en/model_doc/pvt_v2.md
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Changed name of variable from 'attn_reduce' to 'sr_type'
* Changed name of variable from 'attn_reduce' to 'sr_type'
* Changed from using 'sr_type' to 'linear_attention' for clarity
* Update src/transformers/models/pvt_v2/modeling_pvt_v2.py
Removed old code
* Changed from using 'sr_type' to 'linear_attention' for clarity
* Fixed Class names to be more descriptive
* Update src/transformers/models/pvt_v2/modeling_pvt_v2.py
Removed outdated code
* Moved paper abstract to single line in pvt_v2.md
* Added usage tips to pvt_v2.md
* Simplified module inits by passing layer_idx
* Fixed typing for hidden_act in PvtV2Config
* Removed unusued import
* Add pvt_v2 to docs/source/en/_toctree.yml
* Updated documentation in docs/source/en/model_doc/pvt_v2.md to be more comprehensive.
* Updated documentation in docs/source/en/model_doc/pvt_v2.md to be more comprehensive.
* Update src/transformers/models/pvt_v2/modeling_pvt_v2.py
Move function parameters to single line
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/pvt_v2/modeling_pvt_v2.py
Update year of copyright to 2024
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/models/pvt_v2/modeling_pvt_v2.py
Make code more explicit
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Updated sr_ratio to be more explicit spatial_reduction_ratio
* Removed excess type hints in modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Move params to single line in modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Removed needless comment in modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update copyright date in pvt_v2.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Moved params to single line in modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Updated copyright date in configuration_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Cleaned comments in modeling_pvt_v2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Renamed spatial_reduction Conv2D operation
* Revert "Update src/transformers/models/pvt_v2/modeling_pvt_v2.py
"
This reverts commit
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Klaus Hipp
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dd1c905215
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[Docs] Fix FastSpeech2Conformer model doc links (#29574)
[Docs] Fix FastSpeech2Conformer links |
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Arthur
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fb1c62e973
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[Add Mamba] Adds support for the Mamba models (#28094)
* initial-commit
* start cleaning
* small nits
* small nits
* current updates
* add kernels
* small refactoring little step
* add comments
* styling
* nit
* nits
* Style
* Small changes
* Push dummy mambda simple slow
* nit
* Use original names
* Use original names and remove norm
* Updates for inference params
* Style nd updates
* nits
* Match logits
* Add a test
* Add expected generated text
* nits doc, imports and styling
* style
* oups
* dont install kernels, invite users to install the required kernels
* let use use the original packages
* styling
* nits
* fix some copieds
* update doc
* fix-copies
* styling done
* nits
* fix import check
* run but wrong cuda ress
* mamba CUDA works :)
* fix the fast path
* config naming nits
* conversion script is not required at this stage
* finish fixing the fast path: generation make sense now!
* nit
* Let's start working on the CIs
* style
* better style
* more nits
* test nit
* quick fix for now
* nits
* nit
* nit
* nit
* nits
* update test rest
* fixup
* update test
* nit
* some fixes
* nits
* update test values
* fix styling
* nit
* support peft
* integrations tests require torchg
* also add slow markers
* styling
* chose forward wisely
* nits
* update tests
* fix gradient checkpointing
* fixup
* nit
* fix doc
* check copies
* fix the docstring
* fix some more tests
* style
* fix beam search
* add init schene
* update
* nit
* fix
* fixup the doc
* fix the doc
* fixup
* tentative update but slow is no longer good
* nit
* should we always use float32?
* nits
* revert wrong changes
* res in float32
* cleanup
* skip fmt for now
* update generation values
* update test values running original model
* fixup
* update tests + rename inference_params to cache_params + make sure training does not use cache_params
* small nits
* more nits
* fix final CIs
* style
* nit doc
* I hope final doc nits
* nit
* 🫠
* final touch!
* fix torch import
* Apply suggestions from code review
Co-authored-by: Lysandre Debut <hi@lysand.re>
* Apply suggestions from code review
* fix fix and fix
* fix base model prefix!
* nit
* Update src/transformers/models/mamba/__init__.py
* Update docs/source/en/model_doc/mamba.md
Co-authored-by: Lysandre Debut <hi@lysand.re>
* nit
---------
Co-authored-by: Lysandre Debut <hi@lysand.re>
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Joshua Lochner
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ebccb09169
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[docs] Update starcoder2 paper link (#29418)
Update starcoder2 paper link |
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NielsRogge
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836921fdeb
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Add UDOP (#22940)
* First draft
* More improvements
* More improvements
* More fixes
* Fix copies
* More improvements
* More fixes
* More improvements
* Convert checkpoint
* More improvements, set up tests
* Fix more tests
* Add UdopModel
* More improvements
* Fix equivalence test
* More fixes
* Redesign model
* Extend conversion script
* Use real inputs for conversion script
* Add image processor
* Improve conversion script
* Add UdopTokenizer
* Add fast tokenizer
* Add converter
* Update README's
* Add processor
* Add fully fledged tokenizer
* Add fast tokenizer
* Use processor in conversion script
* Add tokenizer tests
* Fix one more test
* Fix more tests
* Fix tokenizer tests
* Enable fast tokenizer tests
* Fix more tests
* Fix additional_special_tokens of fast tokenizer
* Fix tokenizer tests
* Fix more tests
* Fix equivalence test
* Rename image to pixel_values
* Rename seg_data to bbox
* More renamings
* Remove vis_special_token
* More improvements
* Add docs
* Fix copied from
* Update slow tokenizer
* Update fast tokenizer design
* Make text input optional
* Add first draft of processor tests
* Fix more processor tests
* Fix decoder_start_token_id
* Fix test_initialization
* Add integration test
* More improvements
* Improve processor, add test
* Add more copied from
* Add more copied from
* Add more copied from
* Add more copied from
* Remove print statement
* Update README and auto mapping
* Delete files
* Delete another file
* Remove code
* Fix test
* Fix docs
* Remove asserts
* Add doc tests
* Include UDOP in exotic model tests
* Add expected tesseract decodings
* Add sentencepiece
* Use same design as T5
* Add UdopEncoderModel
* Add UdopEncoderModel to tests
* More fixes
* Fix fast tokenizer
* Fix one more test
* Remove parallelisable attribute
* Fix copies
* Remove legacy file
* Copy from T5Tokenizer
* Fix rebase
* More fixes, copy from T5
* More fixes
* Fix init
* Use ArthurZ/udop for tests
* Make all model tests pass
* Remove UdopForConditionalGeneration from auto mapping
* Fix more tests
* fixups
* more fixups
* fix the tokenizers
* remove un-necessary changes
* nits
* nits
* replace truncate_sequences_boxes with truncate_sequences for fix-copies
* nit current path
* add a test for input ids
* ids that we should get taken from
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RaymondLi0
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63caa370e6
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Starcoder2 model - bis (#29215)
* Copy model * changes * misc * fixes * add embed and residual dropout (#30) * misc * remove rms norm and gated MLP * remove copied mentions where its not a copy anymore * remove unused _shape * copied from mistral instead * fix copies * fix copies * add not doctested * fix * fix copyright * Update docs/source/en/model_doc/starcoder2.md Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/starcoder2/configuration_starcoder2.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/starcoder2/configuration_starcoder2.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * fix doc * revert some changes * add fa2 tests * fix styling nit * fix * push dummy docs --------- Co-authored-by: Joel Lamy-Poirier <joel.lamy-poirier@servicenow.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> |
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Eduardo Pacheco
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3fcfbe7549
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Adding SegGPT (#27735)
* First commit * Improvements * More improvements * Converted original checkpoint to HF checkpoint * Fix style * Fixed forward * More improvements * More improvements * Update src/transformers/models/seggpt/modeling_seggpt.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Remove asserts * Remove unnecessary attributes * Changed model name to camel case * Improve forward doc * Improve tests * More improvements * Fix copies * Fix doc * Make SegGptImageProcessor more flexible * Added few-shot test * Fix style * Update READMEs and docs * Update READMEs * Make inputs required * Add SegGptForImageSegmentation * Make tests pass * Rename to out_indicies * Update src/transformers/models/seggpt/image_processing_seggpt.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/seggpt/image_processing_seggpt.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Fixed naming convention * Copying SegGptMlp from modeling_sam.py * Some minor improvements * Remove mlp_ratio * Fix docstrings * Fixed docstring match * Objects defined before use * Storing only patch_size and beta for SegGptLoss * removed _prepare_inputs method * Removed modified from headers * Renamed to output_indicies * Removed unnecessary einsums * Update tests/models/seggpt/test_modeling_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/models/seggpt/test_modeling_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/models/seggpt/test_modeling_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/image_processing_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/image_processing_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/image_processing_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/modeling_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/modeling_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Fixing issues * Raise error as soon as possible * More fixes * Fix merge * Added palette to SegGptImageProcessor * Fixed typo * Fixed shape typo * Added permute before doing palette to class mapping * Fixed style * Fixed and added tests * Fixed docstrings * Matching SegFormer API for post_processing_semantic_segmentation * Fixed copies * Fixed SegGptImageProcessor to handle both binary and RGB masks * Updated docstrings of SegGptImageProcessor * Update src/transformers/models/seggpt/image_processing_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update docs/source/en/model_doc/seggpt.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/configuration_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/convert_seggpt_to_hf.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/image_processing_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/modeling_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/image_processing_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/image_processing_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/image_processing_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/modeling_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/models/seggpt/test_image_processing_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/models/seggpt/test_modeling_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/modeling_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/modeling_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/modeling_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Object definitions above & fix style * Renamed output_indices to intermediate_feature_indices * Removed unnecessary check on bool_masked_pos * Loss first in the outputs * Added validation for do_normalize * Improved SegGptImageProcessor and added new tests * Added comment * Added docstrings to SegGptLoss * Reimplemented ensemble condition logic in SegGptEncoder * Update src/transformers/models/seggpt/__init__.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/seggpt/modeling_seggpt.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/seggpt/convert_seggpt_to_hf.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/seggpt/configuration_seggpt.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Updated docstrings to use post_process_semantic_segmentation * Fixed typo on docstrings * moved pixel values test to test_image_processing_seggpt * Addressed comments * Update src/transformers/models/seggpt/configuration_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/image_processing_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/configuration_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/models/seggpt/modeling_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Updated docstrings for SegGptLoss * Address comments * Added SegGpt example to model docs * Update src/transformers/models/seggpt/modeling_seggpt.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * moved patchify and unpatchify * Rename checkpoint * Renamed intermediate_features to intermediate_hidden_states for consistency * Update src/transformers/models/seggpt/configuration_seggpt.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Replaced post_process_masks for post_process_semantic_segmentation in the docs --------- Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: Niels <niels.rogge1@gmail.com> Co-authored-by: Eduardo Pacheco <eduardo.pacheco@limehome.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> |
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David Nguyen
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c29135046a
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[i18n-vi] Translate README.md to Vietnamese (#29229)
* Add Tiếng Việt language support * Add Vietnamese translation link to README.md * update README_vi.md |
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Arthur
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594c1277b2
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[ gemma] Adds support for Gemma 💎 (#29167)
* inital commit * update * update conversion checkpoint * update conversion script * nits * some fixes * nits * merge * fix permute * nits * fix * nits * nits * nits * fix rope * fix both rope * nites * style * make sure flax works * fix flax init code * fix foward * nits * print flax generation out * current code * nits * SIIIIIIIIIIIIIIIIIII * update * add new tokenizer * correct fast tokenizer * fix conversion * more comments * fix modeling and conversion * nits and nits * nits testing * add some tokenization tests * add some edge cases * add slow tests and fix them * fixup * fix copies for modeling * fix copies * add 7B slow tests * fix * fix * fix tests * make tokenizer cis go green * styling * last tokenizer nits * update jax tests * fix flax for 7b * add jit testing 🤗 * cleanups * isolated nit, inv_freq for rotary_emb.inv_freq * propagate to jax * Apply suggestions from code review Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * adjust test * fix conversion script * change name * correct file names * update conversion script * Fix bos and eos token ids in the model configuration (#3) * update modelling * update conversion script * add static cache for gemma * fix sdpa generate * fix batched * multiple fixes * fix FA2 * final fix * Rename a few missing strings and filenames (#4) * merge with upstream main * fix copies * fix copies * fix fixup * fix fixup * fix * fix * final tests * fix fx gemma tests * fix fx bf16/fp16 tests * update slow fx tests * fx slow tests: one logits, one generation * move jit test standalone * Apply suggestions from code review * nits * tokenizer updates * more tokenization updates: custom GemmaSentencepieceExtrator * style * Update src/transformers/cache_utils.py * Update src/transformers/models/gemma/__init__.py * Update tests/models/gemma/test_modeling_flax_gemma.py * small nits * style * update tokenization test * fix the rotary embedding * with style * fix slow tests * WARNING this commit might be very important for precisions * Update tests/models/gemma/test_modeling_flax_gemma.py * Update src/transformers/models/gemma/configuration_gemma.py Co-authored-by: Lysandre Debut <hi@lysand.re> * Update src/transformers/models/gemma/modeling_flax_gemma.py Co-authored-by: Lysandre Debut <hi@lysand.re> * small nits here and there! * forgotten nit * remove on the fly computation of inv_freq * revert previous change, let's be safe and for now re-compute freq cis to make sure it's in float * Apply suggestions from code review Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update src/transformers/models/gemma/convert_gemma_weights_to_hf.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update src/transformers/models/gemma/convert_gemma_weights_to_hf.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_flax_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_tokenization_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_tokenization_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_tokenization_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_tokenization_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update tests/models/gemma/test_modeling_gemma.py Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * nit conversion script link * fix some tests * add not doctest and pr doctest * repo consistency * fix last CIs 🚀 * update all readmes --------- Co-authored-by: younesbelkada <younesbelkada@gmail.com> Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> Co-authored-by: Pedro Cuenca <pedro@huggingface.co> Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by: sanchit-gandhi <sanchit@huggingface.co> Co-authored-by: Lysandre Debut <hi@lysand.re> |
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Arthur Zucker
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1a77f07f65 | v4.39.dev.0 | ||
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Lysandre Debut
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f497f564bb
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Update all references to canonical models (#29001)
* Script & Manual edition * Update |
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Jonathan Tow
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de6029a059
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Add StableLM (#28810)
* Add `StableLM` * fix(model): re-create from `huggingface-cli add-new-model-like persimmon` * fix: re-add changes to address comments * fix(readme): add links to paper * fix(tokenization_auto): remove `GPTNeoXTokenizerFastFast` ref * fix(tests): re-add `@slow` decorator to integration tests * fix(tests): import slow... * fix(readme_hd): remove whitespace edit * fix(tokenizer): auto tokenizer tuple * skip doctests for `modeling_stablelm` |
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NielsRogge
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ef5ab72f4b
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[Docs] Update README and default pipelines (#28864)
* Update README and docs * Update README * Update README |
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Klaus Hipp
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58e3d23e97
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[i18n-de] Translate README.md to German (#28933)
* Translate README.md to German * Add links to README_de.md * Remove invisible characters in README * Change to a formal tone and fix punctuation marks |
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Klaus Hipp
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1c31b7aa3b
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[Docs] Add missing language options and fix broken links (#28852)
* Add missing entries to the language selector * Add links to the Colab and AWS Studio notebooks for ONNX * Use anchor links in CONTRIBUTING.md * Fix broken hyperlinks due to spaces * Fix links to OpenAI research articles * Remove confusing footnote symbols from author names, as they are also considered invalid markup |
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ThibaultLengagne
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cd2eb8cb2b
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Add French translation: french README.md (#28696)
* doc: french README Signed-off-by: ThibaultLengagne <thibaultl@padok.fr> * doc: Add Depth Anything Signed-off-by: ThibaultLengagne <thibaultl@padok.fr> * doc: Add french link in other docs Signed-off-by: ThibaultLengagne <thibaultl@padok.fr> * doc: Add missing links in fr docs * doc: fix several mistakes in translation Signed-off-by: ThibaultLengagne <thibaultl@padok.fr> --------- Signed-off-by: ThibaultLengagne <thibaultl@padok.fr> Co-authored-by: Sarapuce <alexandreh@padok.fr> |
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NielsRogge
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963db81a5a
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Add Depth Anything (#28654)
* First draft * More improvements * More improvements * More improvements * More improvements * Add docs * Remove file * Add copied from * Address comments * Address comments * Address comments * Fix style * Update docs * Convert all checkpoints, add integration test * Rename checkpoints * Add pretrained backbone attributes * Fix default config * Address comment * Add figure to docs * Fix bug thanks to @xenova * Update conversion script * Fix integration test |
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Amy Roberts
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b2748a6efd | v4.38.dev.0 | ||
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Yoach Lacombe
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d2cdefb9ec
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Add new meta w2v2-conformer BERT-like model (#28165)
* first commit * correct default value non causal * update config and modeling code * update converting checkpoint * clean modeling and fix tests * make style * add new config parameters to docstring * fix copied from statements * Apply suggestions from code review Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * make position_embeddings_type docstrings clearer * clean converting script * remove function not used * clean modeling file * apply suggestion for test file + add convert script to not_doctested * modify tests according to review - cleaner logic and more tests * Apply nit suggestions from code review Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * add checker of valid position embeddings type * instantiate new layer norm layer with the right eps * fix freeze_feature_encoder since it can be None in some cases * add test same output in convert script * restore wav2vec2conformer and add new model * create processor and FE + clean * add new model code * fix convert script and set default config parameters * correct model id paths * make style * make fix-copies and cleaning files * fix copied from statements * complete .md and fixe copies * clean convert script argument defaults * fix config parameters docstrings * fix config docstring * add copied from and enrich FE tests * fix copied from and repo-consistency * add autotokenizer * make test input length shorter and change docstring code * fix docstrings and copied from * add add_adapter to ASR training example * make testing of adapters more robust * adapt to multi adapter layers * refactor input_values->input_features and remove w2v2-bert feature extractor * remove pretraining model * remove depreciated features and useless lines * add copied from and ignore statements to modeling tests * remove pretraining model #2 * change import in convert script * change default in convert script * update readme and remove useless line * Update tests/models/wav2vec2_bert/test_processor_wav2vec2_bert.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * refactor BERT to Bert for consistency * remove useless ignore copy statement * add persistent to buffer in rotary * add eps in LayerNorm init and remove copied from * add adapter activation parameters and add copied from statements * Fix copied statements and add unitest.skip reasons * add copied statement in test_processor * refactor processor * make style * replace numpy random by torch rand * remove expected output CTC * improve converting script with processor class * Apply suggestions from code review Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * remove gumbel class * remove tests related to previously deleted class * Update src/transformers/models/wav2vec2_bert/configuration_wav2vec2_bert.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * correct typos * remove uused parameters * update processor to takes both text and audio * update checkpoints * update expected output and add ctc expected output * add label_attention_mask * replace pt with np in processor tests * fix typo * revert to behaviour with labels_attention_mask --------- Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> |
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Junyang Lin
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d6ffe74dfa
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Add qwen2 (#28436)
* add config, modeling, and tokenization * add auto and init * update readme * update readme * update team name * fixup * fixup * update config * update code style * update for fixup * update for fixup * update for fixup * update for testing * update for testing * fix bug for config and tokenization * fix bug for bos token * not doctest * debug tokenizer * not doctest * debug tokenization * debug init for tokenizer * fix style * update init * delete if in token auto * add tokenizer doc * add tokenizer in init * Update dummy_tokenizers_objects.py * update * update * debug * Update tokenization_qwen2.py * debug * Update convert_slow_tokenizer.py * add copies * add copied from and make style * update files map * update test * fix style * fix merge reading and update tests * fix tests * fix tests * fix style * debug a variable in readme * Update src/transformers/models/qwen2/configuration_qwen2.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * update test and copied from * fix style * update qwen2 tokenization and tests * Update tokenization_qwen2.py * delete the copied from after property * fix style * update tests * update tests * add copied from * fix bugs * update doc * add warning for sliding window attention * update qwen2 tokenization * fix style * Update src/transformers/models/qwen2/modeling_qwen2.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * fix tokenizer fast --------- Co-authored-by: Ren Xuancheng <jklj077@users.noreply.github.com> Co-authored-by: renxuancheng.rxc <renxuancheng.rxc@alibaba-inc.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> |
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Yih-Dar
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59cd9de39d
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Byebye torch 1.10 (#28207)
* fix * fix --------- Co-authored-by: ydshieh <ydshieh@users.noreply.github.com> |
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prasatee
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ffd3710391
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Fix number of models in README.md (#28430) | ||
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NielsRogge
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3b742ea84c
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Add SigLIP (#26522)
* Add first draft * Use appropriate gelu function * More improvements * More improvements * More improvements * Convert checkpoint * More improvements * Improve docs, remove print statements * More improvements * Add link * remove unused masking function * begin tokenizer * do_lower_case * debug * set split_special_tokens=True * Remove script * Fix style * Fix rebase * Use same design as CLIP * Add fast tokenizer * Add SiglipTokenizer to init, remove extra_ids * Improve conversion script * Use smaller inputs in conversion script * Update conversion script * More improvements * Add processor to conversion script * Add tests * Remove print statements * Add tokenizer tests * Fix more tests * More improvements related to weight initialization * More improvements * Make more tests pass * More improvements * More improvements * Add copied from * Add canonicalize_text * Enable fast tokenizer tests * More improvements * Fix most slow tokenizer tests * Address comments * Fix style * Remove script * Address some comments * Add copied from to tests * Add more copied from * Add more copied from * Add more copied from * Remove is_flax_available * More updates * Address comment * Remove SiglipTokenizerFast for now * Add caching * Remove umt5 test * Add canonicalize_text inside _tokenize, thanks Arthur * Fix image processor tests * Skip tests which are not applicable * Skip test_initialization * More improvements * Compare pixel values * Fix doc tests, add integration test * Add do_normalize * Remove causal mask and leverage ignore copy * Fix attention_mask * Fix remaining tests * Fix dummies * Rename temperature and bias * Address comments * Add copied from to tokenizer tests * Add SiglipVisionModel to auto mapping * Add copied from to image processor tests * Improve doc * Remove SiglipVisionModel from index * Address comments * Improve docs * Simplify config * Add first draft * Make it like mistral * More improvements * Fix attention_mask * Fix output_attentions * Add note in docs * Convert multilingual model * Convert large checkpoint * Convert more checkpoints * Add pipeline support, correct image_mean and image_std * Use padding=max_length by default * Make processor like llava * Add code snippet * Convert more checkpoints * Set keep_punctuation_string=None as in OpenCLIP * Set normalized=False for special tokens * Fix doc test * Update integration test * Add figure * Update organization * Happy new year * Use AutoModel everywhere --------- Co-authored-by: patil-suraj <surajp815@gmail.com> |
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Kevin Herro
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5d36025ca1
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README: install transformers from conda-forge channel (#28313)
Switch to the conda-forge channel for transformer installation, as the huggingface channel does not offer the latest version. Fixes #28248 |
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Connor Henderson
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d83ff5eeff
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Add FastSpeech2Conformer (#23439)
* start - docs, SpeechT5 copy and rename * add relevant code from FastSpeech2 draft, have tests pass * make it an actual conformer, demo ex. * matching inference with original repo, includes debug code * refactor nn.Sequentials, start more desc. var names * more renaming * more renaming * vocoder scratchwork * matching vocoder outputs * hifigan vocoder conversion script * convert model script, rename some config vars * replace postnet with speecht5's implementation * passing common tests, file cleanup * expand testing, add output hidden states and attention * tokenizer + passing tokenizer tests * variety of updates and tests * g2p_en pckg setup * import structure edits * docstrings and cleanup * repo consistency * deps * small cleanup * forward signature param order * address comments except for masks and labels * address comments on attention_mask and labels * address second round of comments * remove old unneeded line * address comments part 1 * address comments pt 2 * rename auto mapping * fixes for failing tests * address comments part 3 (bart-like, train loss) * make style * pass config where possible * add forward method + tests to WithHifiGan model * make style * address arg passing and generate_speech comments * address Arthur comments * address Arthur comments pt2 * lint changes * Sanchit comment * add g2p-en to doctest deps * move up self.encoder * onnx compatible tensor method * fix is symbolic * fix paper url * move models to espnet org * make style * make fix-copies * update docstring * Arthur comments * update docstring w/ new updates * add model architecture images * header size * md wording update * make style |
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Lysandre
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3ed3e3190c | Dev version | ||
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Younes Belkada
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c7f076a00e
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Adds VIP-llava to transformers (#27932)
* v1 * add-new-model-like * revert * fix forward and conversion script * revert * fix copies * fixup * fix * Update docs/source/en/index.md * Apply suggestions from code review * push * fix * fixes here and there * up * fixup and fix tests * Apply suggestions from code review * add docs * fixup * fixes * docstring * add docstring * fixup * docstring * fixup * nit * docs * more copies * fix copies * nit * update test |
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Arthur
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accccdd008
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[Add Mixtral] Adds support for the Mixtral MoE (#27942)
* up * up * test * logits ok * up * up * few fixes * conversion script * up * nits * nits * update * nuke * more updates * nites * fix many issues * nit * scatter * nit * nuke megablocks * nits * fix conversion script * nit * remove * nits * nit * update * oupsssss * change * nits device * nits * fixup * update * merge * add copied from * fix the copy mentions * update tests * more fixes * nits * conversion script * add parts of the readme * Update tests/models/mixtral/test_modeling_mixtral.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * new test + conversion script * Apply suggestions from code review Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Apply suggestions from code review * fix * fix copies * fix copies * ooops * fix config * Apply suggestions from code review * fix nits * nit * add copies * add batched tests * docs * fix flash attention * let's add more verbose * add correct outputs * support router ouptus * ignore copies where needed * fix * cat list if list is given for now * nits * Update docs/source/en/model_doc/mixtral.md * finish router refactoring * fix forward * fix expected values * nits * fixup * fix * fix bug * fix * fix dtype mismatch * fix * grrr grrr I support item assignment * fix CI * docs * fixup * remove some copied form * fix weird diff * skip doctest fast on the config and modeling * mark that is supports flash attention in the doc * update * Update src/transformers/models/mixtral/modeling_mixtral.py Co-authored-by: Lysandre Debut <hi@lysand.re> * Update docs/source/en/model_doc/mixtral.md Co-authored-by: Lysandre Debut <hi@lysand.re> * revert router logits config issue * update doc accordingly * Update src/transformers/models/mixtral/convert_mixtral_weights_to_hf.py * nits * use torch testing asssert close * fixup * doc nits --------- Co-authored-by: younesbelkada <younesbelkada@gmail.com> Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by: Lysandre Debut <hi@lysand.re> |
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NielsRogge
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7ea21f1f03
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[LLaVa] Some improvements (#27895)
* More improvements * Improve variable names * Update READMEs, improve docs |
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Younes Belkada
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44b5506d29
|
[Llava] Add Llava to transformers (#27662)
* add model like
* logits match
* minor fixes
* fixes
* up
* up
* add todo
* llava processor
* keep the processor simple
* add conversion script
* fixup
* fix copies
* up
* add to index
* fix config + logits
* fix
* refactor
* more refactor
* more refactor
* fix copies
* add authors
* v1 tests
* add `LlavaProcessor` in init
* remove unneeded import
* up
* up
* docs
* up
* fix CI
* fix CI
* add attention mask in test
* make fixup
* remove the vision model
* that' s the dirty way to do it
* nits
* nits
* updates
* add more tests
* add input tests
* fixup
* more styling
* nits
* updates amd cleanup
* fixup the generation expected results
* fix the testing script
* some cleanup and simplification which does not work yet but almost there!
* make correct dispatch operations
* vectorize works for batch of images and text
* last todos
* nits
* update test and modeling code
* remove useless function for now
* fix few issues
* fix generation
* some nits
* add bakllava
* nits
* remove duplicated code
* finis merge
* cleanup
* missed this line
* fill the todos
* add left padding offset
* add left and rignt padding logic
* bool to properly index
* make sure
* more cleanups
* batch is fixed 😉
* add correct device for tensor creation
* fix some dtype missmatch
* ruff
* update conversion script
* Update src/transformers/__init__.py
* fa 2 support + fix conversion script
* more
* correct reshaping
* fix test dict
* fix copies by ignoring
* fix nit
* skip clip vision model
* fixup
* fixup
* LlavaForVisionText2Text -> LlavaForCausalLM
* update
* fix
* raise correct errors
* fix
* docs
* nuke for now
* nits here and there
* fixup
* fix remaining tests
* update LlavaForConditionalGeneration instead of CausalLM
* fixups
* pipeline support
* slow and piepline tests
* supports batch
* nits
* cleanup
* fix first integration tests
* add pad token where needed
* correct etsts
* fixups
* update pipeline testr
* fix quality
* nits
* revert unneeded change
* nit
* use BatchFeature
* from ...feature_extraction_utils import BatchFeature
* nits
* nits
* properly update
* more f*** nits
* fix copies
* comment
* keep slow test slow
* Update src/transformers/models/llava/processing_llava.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* add piepline example
* add pixel values in docstrign
* update pr doctest
* fix
* fix slow tests
* remove hack
* fixup
* small note
* forward contrib credits from PR25789
* forward contrib credits from original implementation and work
* add arthur
* Update src/transformers/models/llava/processing_llava.py
Co-authored-by: Lysandre Debut <hi@lysand.re>
* update docstring
* nit
* move to not doctested because of timeout issues
* fixup
* add description
* more
* fix-copies
* fix docs
* add beam search
* add more comments
* add typehints on processor
* add speedup plot
* update slow tests and docs
* push test
* push batched test
* fix batched generation with different number of images
* remove benchmark due to a bug
* fix test
* fix copies
* add gcolab demo
---------
Co-authored-by: Arthur Zucker <arthur.zucker@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: shauray8 <shauray8@users.noreply.github.com>
Co-authored-by: haotian-liu <haotian-liu@users.noreply.github.com>
Co-authored-by: Lysandre Debut <hi@lysand.re>
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Arindam Jati
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b242d0f297
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[Time series] Add PatchTSMixer (#26247)
* patchtsmixer initial commit * x,y->context_values,target_values, unittest addded * cleanup code * minor * return hidden states * model tests, partial integration tests * ettm notebook temporary * minor * config mask bug fix, tests updated * final ETT notebooks * add selfattn * init * added docstrings * PatchTSMixerForPretraining -> PatchTSMixerForMaskPretraining * functionality tests added * add start and input docstrings * docstring edits * testcase edits * minor changes * docstring error fixed * ran make fixup * finalize integration tests and docs * minor * cleaned gitignore * added dataclass decorator, ran black formatter * ran ruff * formatting * add slow decorator * renamed in_Channel to input_size and default to 1 * shorten dataclass names * use smaller model for testing * moved the 3 heads to the modeling file * use scalers instead of revin * support forecast_channel_indices * fix regression scaling * undo reg. scaling * removed unneeded classes * forgot missing * add more layers * add copied positional_encoding * use patchmask from patchtst * removed dependency on layers directory * formatting * set seed * removed unused imports * fixed forward signature test * adding distributional head for PatchTSMixerForecasting * add generate to forecast * testcases for generate * add generate and distributional head for regression * raise Exception for negative values for neg binominal distribution * formatting changes * remove copied from patchtst and add TODO for test passing * make copies * doc edits * minor changes * format issues * minor changes * minor changes * format docstring * change some class names to PatchTSMixer + class name Transpose to PatchTSMixerTranspose GatedAttention to PatchTSMixerGatedAttention * change NormLayer to PatchTSMixerNormLayer * change MLP to PatchTSMixerMLP * change PatchMixer to PatchMixerBlock, FeatureMixer to FeatureMixerBlock * change ChannelFeatureMixer to ChannelFeatureMixerBlock * change PatchMasking to PatchTSMixerMasking * change Patchify to PatchTSMixerPatchify * list to `list` * fix docstrings * formatting * change bs to batch_size, edit forecast_masking * edit random_masking * change variable name and update docstring in PatchTSMixerMasking * change variable name and update docstring in InjectScalerStatistics4D * update forward call in PatchTSMixerTranspose * change variable name and update docstring in PatchTSMixerNormLayer * change variable name and update docstring in PatchTSMixerMLP * change variable name and update docstring in ChannelFeatureMixerBlock * formatting * formatting issues * docstring issue * fixed observed_mask type in docstrings * use FloatTensor type * formatting * fix rescaling issue in forecasting, fixed integration tests * add docstring from decorator * fix docstring * Update README.md Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/patchtsmixer/configuration_patchtsmixer.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/patchtsmixer/modeling_patchtsmixer.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/patchtsmixer/configuration_patchtsmixer.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/patchtsmixer/modeling_patchtsmixer.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * PatchTSMixerChannelFeatureMixerBlock * formatting * ForPretraining * use num_labels instead of n_classes * remove commented out code * docstring fixed * nn.functional used instead of one letter F * x_tmp renamed * one letter variable x removed from forward calls * one letter variable y removed * remove commented code * rename patch_size, in_channels, PatchTSMixerBackbone * add config to heads * add config to heads tests * code reafactoring to use config instead of passing individual params * Cdocstring fixes part 1 * docstring fixes part 2 * removed logger.debug * context_values -> past_values * formatting changes * pe -> positional_encoding * removed unused target variable * self.mode logic fixed * formatting change * edit docstring and var name * change n_targets to num_targets * rename input_size to num_input_channels * add head names with prefix PatchTSMixer * edit docstring in PatchTSMixerForRegression * fix var name change in testcases * add PatchTSMixerAttention * return dict for all exposed classes, test cases added * format * move loss function to forward call * make style * adding return dict/tuple * make repo-consistency * remove flatten mode * code refactoring * rename data * remove PatchTSMixer and keep only PatchTSMixerEncoder * docstring fixes * removed unused code * format * format * remove contiguous and formatting changes * remove model description from config * replace asserts with ValueError * remove nn.Sequential from PatchTSMixerNormLayer * replace if-else with map * remove all nn.Sequential * format * formatting * fix gradient_checkpointing error after merge, and formatting * make fix-copies * remove comments * reshape * doesnt support gradient checkpointing * corect Patchify * masking updates * batchnorm copy from * format checks * scaler edits * remove comments * format changes * remove self.config * correct class PatchTSMixerMLP(nn.Module): * makr fix * doc updates * fix-copies * scaler class correction * doc edits * scaler edits * update readme with links * injectstatistics add * fix-copies * add norm_eps option to LayerNorm * format changes * fix copies * correct make copies * use parametrize * fix doc string * add docs to toctree * make style * doc segmenting * docstring edit * change forecast to prediction * edit doc * doc edits * remove PatchTSMixerTranspose * add PatchTSMixerPositionalEncoding and init position_enc * remove positional_encoding * edit forecast_masking, remove forecast_mask_ratios * fix broken code * var rename target_values -> future_values * num_features -> d_model * fix broken code after master merge * repo consistency * use postional embedding * prediction_logits -> prediction_outputs, make fix-copies * uncommented @slow * minor changes * loss first in tuple * tuple and dict same ordering * style edits * minor changes * dict/tuple consistent enablement * Update src/transformers/models/patchtsmixer/modeling_patchtsmixer.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update tests/models/patchtsmixer/test_modeling_patchtsmixer.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/patchtsmixer/modeling_patchtsmixer.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * fix formatting * formatting * usage tip * test on cpu only * add sample usage * change PatchTSMixerForClassification to PatchTSMixerForTimeSeriesClassification * push changes * fix copies * std scaling set to default True case * minor changes * stylechanges --------- Co-authored-by: Arindam Jati <arindam.jati@ibm.com> Co-authored-by: vijaye12 <vijaye12@in.ibm.com> Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com> Co-authored-by: nnguyen <nnguyen@us.ibm.com> Co-authored-by: vijaye12 <vijaykr.e@gmail.com> Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: Nam Nguyen <namctin@gmail.com> Co-authored-by: Wesley Gifford <79663411+wgifford@users.noreply.github.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> |
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Joshua Lochner
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0ad4e7e6da
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[SeamlessM4Tv2] Fix links in README (#27782)
Fix typo in README |
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Yoach Lacombe
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29f1aee3b6
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Add SeamlessM4T v2 (#27779)
* add working convertion script * first non-working version of modeling code * update modeling code (working) * make style * make fix-copies * add config docstrings * add config to ignore docstrings formatage due to unconventional markdown * fix copies * fix generation num_return_sequences * enrich docs * add and fix tests beside integration tests * update integration tests * update repo id * add tie weights and make style * correct naming in .md * fix imports and so on * correct docstrings * fix fp16 speech forward * fix speechencoder attention * make style * fix copied from * rename SeamlessM4Tv2-v2 to SeamlessM4Tv2 * Apply suggestions on configuration Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * remove useless public models * fix private models + better naming for T2U models * clean speech encoder relative position embeddings * refactor chunk attention * add docstrings to chunk attention method * improve naming and docstrings * rename some attention variables + add temperature sampling in T2U model * rename DOCSTRINGS variable names * make style + remove 2 useless config parameters * enrich model card * remove any attention_head reference + fix temperature in T2U * new fmt and make style * Apply suggestions from code review Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * rename spkr_id->speaker_id and change docstrings of get_char_input_ids * simplify v2attention * make style * Update seamless_m4t_v2.md * update code and tests with last update * update repo ids * fill article name, abstract andauthors * update not_doctested and slow_doc tests --------- Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> |
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Kashif Rasul
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af8acc4760
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[Time series] Add patchtst (#27581)
* add distribution head to forecasting
* formatting
* Add generate function for forecasting
* Add generate function to prediction task
* formatting
* use argsort
* add past_observed_mask ordering
* fix arguments
* docs
* add back test_model_outputs_equivalence test
* formatting
* cleanup
* formatting
* use ACT2CLS
* formatting
* fix add_start_docstrings decorator
* add distribution head and generate function to regression task
add distribution head and generate function to regression task. Also made add PatchTSTForForecastingOutput, PatchTSTForRegressionOutput.
* add distribution head and generate function to regression task
add distribution head and generate function to regression task. Also made add PatchTSTForForecastingOutput, PatchTSTForRegressionOutput.
* fix typos
* add forecast_masking
* fixed tests
* use set_seed
* fix doc test
* formatting
* Update docs/source/en/model_doc/patchtst.md
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* better var names
* rename PatchTSTTranspose
* fix argument names and docs string
* remove compute_num_patches and unused class
* remove assert
* renamed to PatchTSTMasking
* use num_labels for classification
* use num_labels
* use default num_labels from super class
* move model_type after docstring
* renamed PatchTSTForMaskPretraining
* bs -> batch_size
* more review fixes
* use hidden_state
* rename encoder layer and block class
* remove commented seed_number
* edit docstring
* Add docstring
* formatting
* use past_observed_mask
* doc suggestion
* make fix-copies
* use Args:
* add docstring
* add docstring
* change some variable names and add PatchTST before some class names
* formatting
* fix argument types
* fix tests
* change x variable to patch_input
* format
* formatting
* fix-copies
* Update tests/models/patchtst/test_modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* move loss to forward
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/patchtst/modeling_patchtst.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* formatting
* fix a bug when pre_norm is set to True
* output_hidden_states is set to False as default
* set pre_norm=True as default
* format docstring
* format
* output_hidden_states is None by default
* add missing docs
* better var names
* docstring: remove default to False in output_hidden_states
* change labels name to target_values in regression task
* format
* fix tests
* change to forecast_mask_ratios and random_mask_ratio
* change mask names
* change future_values to target_values param in the prediction class
* remove nn.Sequential and make PatchTSTBatchNorm class
* black
* fix argument name for prediction
* add output_attentions option
* add output_attentions to PatchTSTEncoder
* formatting
* Add attention output option to all classes
* Remove PatchTSTEncoderBlock
* create PatchTSTEmbedding class
* use config in PatchTSTPatchify
* Use config in PatchTSTMasking class
* add channel_attn_weights
* Add PatchTSTScaler class
* add output_attentions arg to test function
* format
* Update doc with image patchtst.md
* fix-copies
* rename Forecast <-> Prediction
* change name of a few parameters to match with PatchTSMixer.
* Remove *ForForecasting class to match with other time series models.
* make style
* Remove PatchTSTForForecasting in the test
* remove PatchTSTForForecastingOutput class
* change test_forecast_head to test_prediction_head
* style
* fix docs
* fix tests
* change num_labels to num_targets
* Remove PatchTSTTranspose
* remove arguments in PatchTSTMeanScaler
* remove arguments in PatchTSTStdScaler
* add config as an argument to all the scaler classes
* reformat
* Add norm_eps for batchnorm and layernorm
* reformat.
* reformat
* edit docstring
* update docstring
* change variable name pooling to pooling_type
* fix output_hidden_states as tuple
* fix bug when calling PatchTSTBatchNorm
* change stride to patch_stride
* create PatchTSTPositionalEncoding class and restructure the PatchTSTEncoder
* formatting
* initialize scalers with configs
* edit output_hidden_states
* style
* fix forecast_mask_patches doc string
* doc improvements
* move summary to the start
* typo
* fix docstring
* turn off masking when using prediction, regression, classification
* return scaled output
* adjust output when using distribution head
* remove _num_patches function in the config
* get config.num_patches from patchifier init
* add output_attentions docstring, remove tuple in output_hidden_states
* change SamplePatchTSTPredictionOutput and SamplePatchTSTRegressionOutput to SamplePatchTSTOutput
* remove print("model_class: ", model_class)
* change encoder_attention_heads to num_attention_heads
* change norm to norm_layer
* change encoder_layers to num_hidden_layers
* change shared_embedding to share_embedding, shared_projection to share_projection
* add output_attentions
* more robust check of norm_type
* change dropout_path to path_dropout
* edit docstring
* remove positional_encoding function and add _init_pe in PatchTSTPositionalEncoding
* edit shape of cls_token and initialize it
* add a check on the num_input_channels.
* edit head_dim in the Prediction class to allow the use of cls_token
* remove some positional_encoding_type options, remove learn_pe arg, initalize pe
* change Exception to ValueError
* format
* norm_type is "batchnorm"
* make style
* change cls_token shape
* Change forecast_mask_patches to num_mask_patches. Remove forecast_mask_ratios.
* Bring PatchTSTClassificationHead on top of PatchTSTForClassification
* change encoder_ffn_dim to ffn_dim and edit the docstring.
* update variable names to match with the config
* add generation tests
* change num_mask_patches to num_forecast_mask_patches
* Add examples explaining the use of these models
* make style
* Revert "Revert "[time series] Add PatchTST (#25927)" (#27486)"
This reverts commit
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Juarez Bochi
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fdd86eed3b
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Add madlad-400 MT models (#27471)
* Add madlad-400 models * Add madlad-400 to the doc table * Update docs/source/en/model_doc/madlad-400.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Fill missing details in documentation * Update docs/source/en/model_doc/madlad-400.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Do not doctest madlad-400 Tests are timing out. --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> |
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dg845
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7f6a804d30
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Add UnivNet Vocoder Model for Tortoise TTS Diffusers Integration (#24799)
* initial commit * Add inital testing files and modify __init__ files to add UnivNet imports. * Fix some bugs * Add checkpoint conversion script and add references to transformers pre-trained model. * Add UnivNet entries for auto. * Add initial docs for UnivNet. * Handle input and output shapes in UnivNetGan.forward and add initial docstrings. * Write tests and make them pass. * Write docs. * Add UnivNet doc to _toctree.yml and improve docs. * fix typo * make fixup * make fix-copies * Add upsample_rates parameter to config and improve config documentation. * make fixup * make fix-copies * Remove unused upsample_rates config parameter. * apply suggestions from review * make style * Verify and add reason for skipped tests inherited from ModelTesterMixin. * Add initial UnivNetGan integration tests * make style * Remove noise_length input to UnivNetGan and improve integration tests. * Fix bug and make style * Make UnivNet integration tests pass * Add initial code for UnivNetFeatureExtractor. * make style * Add initial tests for UnivNetFeatureExtractor. * make style * Properly initialize weights for UnivNetGan * Get feature extractor fast tests passing * make style * Get feature extractor integration tests passing * Get UnivNet integration tests passing * make style * Add UnivNetGan usage example * make style and use feature extractor from hub in integration tests * Update tips in docs * apply suggestions from review * make style * Calculate padding directly instead of using get_padding methods. * Update UnivNetFeatureExtractor.to_dict to be UnivNet-specific. * Update feature extractor to support using model(**inputs) and add the ability to generate noise and pad the end of the spectrogram in __call__. * Perform padding before generating noise to ensure the shapes are correct. * Rename UnivNetGan.forward's noise_waveform argument to noise_sequence. * make style * Add tests to test generating noise and padding the end for UnivNetFeatureExtractor.__call__. * Add tests for checking batched vs unbatched inputs for UnivNet feature extractor and model. * Add expected mean and stddev checks to the integration tests and make them pass. * make style * Make it possible to use model(**inputs), where inputs is the output of the feature extractor. * fix typo in UnivNetGanConfig example * Calculate spectrogram_zero from other config values. * apply suggestions from review * make style * Refactor UnivNet conversion script to use load_state_dict (following persimmon). * Rename UnivNetFeatureExtractor to UnivNetGanFeatureExtractor. * make style * Switch to using torch.tensor and torch.testing.assert_close for testing expected values/slices. * make style * Use config in UnivNetGan modeling blocks. * make style * Rename the spectrogram argument of UnivNetGan.forward to input_features, following Whisper. * make style * Improving padding documentation. * Add UnivNet usage example to the docs. * apply suggestions from review * Move dynamic_range_compression computation into the mel_spectrogram method of the feature extractor. * Improve UnivNetGan.forward return docstring. * Update table in docs/source/en/index.md. * make fix-copies * Rename UnivNet components to have pattern UnivNet*. * make style * make fix-copies * Update docs * make style * Increase tolerance on flaky unbatched integration test. * Remove torch.no_grad decorators from UnivNet integration tests to try to avoid flax/Tensorflow test errors. * Add padding_mask argument to UnivNetModel.forward and add batch_decode feature extractor method to remove padding. * Update documentation and clean up padding code. * make style * make style * Remove torch dependency from UnivNetFeatureExtractor. * make style * Fix UnivNetModel usage example * Clean up feature extractor code/docstrings. * apply suggestions from review * make style * Add comments for tests skipped via ModelTesterMixin flags. * Add comment for model parallel tests skipped via the test_model_parallel ModelTesterMixin flag. * Add # Copied from statements to copied UnivNetFeatureExtractionTest tests. * Simplify UnivNetFeatureExtractorTest.test_batch_decode. * Add support for unbatched padding_masks in UnivNetModel.forward. * Refactor unbatched padding_mask support. * make style |
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jiqing-feng
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c770600fde
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TVP model (#25856)
* tvp model for video grounding add tokenizer auto fix param in TVPProcessor add docs clear comments and enable different torch dtype add image processor test and model test and fix code style * fix conflict * fix model doc * fix image processing tests * fix tvp tests * remove torch in processor * fix grammar error * add more details on tvp.md * fix model arch for loss, grammar, and processor * add docstring and do not regard TvpTransformer, TvpVisionModel as individual model * use pad_image * update copyright * control first downsample stride * reduce first only works for ResNetBottleNeckLayer * fix param name * fix style * add testing * fix style * rm init_weight * fix style * add post init * fix comments * do not test TvpTransformer * fix warning * fix style * fix example * fix config map * add link in config * fix comments * fix style * rm useless param * change attention * change test * add notes * fix comments * fix tvp * import checkpointing * fix gradient checkpointing * Use a more accurate example in readme * update * fix copy * fix style * update readme * delete print * remove tvp test_forward_signature * remove TvpTransformer * fix test init model * merge main and make style * fix tests and others * fix image processor * fix style and model_input_names * fix tests |
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amyeroberts
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78f6ed6c70
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Revert "[time series] Add PatchTST (#25927)" (#27486)
The model was merged before final review and approval.
This reverts commit
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Gift Sinthong
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2ac5b9325e
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[time series] Add PatchTST (#25927)
* Initial commit of PatchTST model classes Co-authored-by: Phanwadee Sinthong <phsinthong@gmail.com> Co-authored-by: Nam Nguyen <namctin@gmail.com> Co-authored-by: Vijay Ekambaram <vijaykr.e@gmail.com> Co-authored-by: Ngoc Diep Do <55230119+diepi@users.noreply.github.com> Co-authored-by: Wesley Gifford <79663411+wgifford@users.noreply.github.com> * Add PatchTSTForPretraining * update to include classification Co-authored-by: Phanwadee Sinthong <phsinthong@gmail.com> Co-authored-by: Nam Nguyen <namctin@gmail.com> Co-authored-by: Vijay Ekambaram <vijaykr.e@gmail.com> Co-authored-by: Ngoc Diep Do <55230119+diepi@users.noreply.github.com> Co-authored-by: Wesley Gifford <79663411+wgifford@users.noreply.github.com> * clean up auto files * Add PatchTSTForPrediction * Fix relative import * Replace original PatchTSTEncoder with ChannelAttentionPatchTSTEncoder * temporary adding absolute path + add PatchTSTForForecasting class * Update base PatchTSTModel + Unittest * Update ForecastHead to use the config class * edit cv_random_masking, add mask to model output * Update configuration_patchtst.py * add masked_loss to the pretraining * add PatchEmbeddings * Update configuration_patchtst.py * edit loss which considers mask in the pretraining * remove patch_last option * Add commits from internal repo * Update ForecastHead * Add model weight initilization + unittest * Update PatchTST unittest to use local import * PatchTST integration tests for pretraining and prediction * Added PatchTSTForRegression + update unittest to include label generation * Revert unrelated model test file * Combine similar output classes * update PredictionHead * Update configuration_patchtst.py * Add Revin * small edit to PatchTSTModelOutputWithNoAttention * Update modeling_patchtst.py * Updating integration test for forecasting * Fix unittest after class structure changed * docstring updates * change input_size to num_input_channels * more formatting * Remove some unused params * Add a comment for pretrained models * add channel_attention option add channel_attention option and remove unused positional encoders. * Update PatchTST models to use HF's MultiHeadAttention module * Update paper + github urls * Fix hidden_state return value * Update integration test to use PatchTSTForForecasting * Adding dataclass decorator for model output classes * Run fixup script * Rename model repos for integration test * edit argument explanation * change individual option to shared_projection * style * Rename integration test + import cleanup * Fix outpu_hidden_states return value * removed unused mode * added std, mean and nops scaler * add initial distributional loss for predition * fix typo in docs * add generate function * formatting * add num_parallel_samples * Fix a typo * copy weighted_average function, edit PredictionHead * edit PredictionHead * add distribution head to forecasting * formatting * Add generate function for forecasting * Add generate function to prediction task * formatting * use argsort * add past_observed_mask ordering * fix arguments * docs * add back test_model_outputs_equivalence test * formatting * cleanup * formatting * use ACT2CLS * formatting * fix add_start_docstrings decorator * add distribution head and generate function to regression task add distribution head and generate function to regression task. Also made add PatchTSTForForecastingOutput, PatchTSTForRegressionOutput. * add distribution head and generate function to regression task add distribution head and generate function to regression task. Also made add PatchTSTForForecastingOutput, PatchTSTForRegressionOutput. * fix typos * add forecast_masking * fixed tests * use set_seed * fix doc test * formatting * Update docs/source/en/model_doc/patchtst.md Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * better var names * rename PatchTSTTranspose * fix argument names and docs string * remove compute_num_patches and unused class * remove assert * renamed to PatchTSTMasking * use num_labels for classification * use num_labels * use default num_labels from super class * move model_type after docstring * renamed PatchTSTForMaskPretraining * bs -> batch_size * more review fixes * use hidden_state * rename encoder layer and block class * remove commented seed_number * edit docstring * Add docstring * formatting * use past_observed_mask * doc suggestion * make fix-copies * use Args: * add docstring * add docstring * change some variable names and add PatchTST before some class names * formatting * fix argument types * fix tests * change x variable to patch_input * format * formatting * fix-copies * Update tests/models/patchtst/test_modeling_patchtst.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * move loss to forward * Update src/transformers/models/patchtst/modeling_patchtst.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/models/patchtst/modeling_patchtst.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/models/patchtst/modeling_patchtst.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/models/patchtst/modeling_patchtst.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * Update src/transformers/models/patchtst/modeling_patchtst.py Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * formatting * fix a bug when pre_norm is set to True * output_hidden_states is set to False as default * set pre_norm=True as default * format docstring * format * output_hidden_states is None by default * add missing docs * better var names * docstring: remove default to False in output_hidden_states * change labels name to target_values in regression task * format * fix tests * change to forecast_mask_ratios and random_mask_ratio * change mask names * change future_values to target_values param in the prediction class * remove nn.Sequential and make PatchTSTBatchNorm class * black * fix argument name for prediction * add output_attentions option * add output_attentions to PatchTSTEncoder * formatting * Add attention output option to all classes * Remove PatchTSTEncoderBlock * create PatchTSTEmbedding class * use config in PatchTSTPatchify * Use config in PatchTSTMasking class * add channel_attn_weights * Add PatchTSTScaler class * add output_attentions arg to test function * format * Update doc with image patchtst.md * fix-copies * rename Forecast <-> Prediction * change name of a few parameters to match with PatchTSMixer. * Remove *ForForecasting class to match with other time series models. * make style * Remove PatchTSTForForecasting in the test * remove PatchTSTForForecastingOutput class * change test_forecast_head to test_prediction_head * style * fix docs * fix tests * change num_labels to num_targets * Remove PatchTSTTranspose * remove arguments in PatchTSTMeanScaler * remove arguments in PatchTSTStdScaler * add config as an argument to all the scaler classes * reformat * Add norm_eps for batchnorm and layernorm * reformat. * reformat * edit docstring * update docstring * change variable name pooling to pooling_type * fix output_hidden_states as tuple * fix bug when calling PatchTSTBatchNorm * change stride to patch_stride * create PatchTSTPositionalEncoding class and restructure the PatchTSTEncoder * formatting * initialize scalers with configs * edit output_hidden_states * style * fix forecast_mask_patches doc string --------- Co-authored-by: Gift Sinthong <gift.sinthong@ibm.com> Co-authored-by: Nam Nguyen <namctin@gmail.com> Co-authored-by: Vijay Ekambaram <vijaykr.e@gmail.com> Co-authored-by: Ngoc Diep Do <55230119+diepi@users.noreply.github.com> Co-authored-by: Wesley Gifford <79663411+wgifford@users.noreply.github.com> Co-authored-by: Wesley M. Gifford <wmgifford@us.ibm.com> Co-authored-by: nnguyen <nnguyen@us.ibm.com> Co-authored-by: Ngoc Diep Do <diiepy@gmail.com> Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com> Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> |
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Susnato Dhar
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e1c3ac2551
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Add Phi-1 and Phi-1_5 (#26170)
* only dir not even init * init * tokenizer removed and reference of codegen added * modeling file updated a lot remaining app_rotary_emb * conversion script done * conversion script fixed, a lot of factoring done and most tests pass * added token_clf and extractive_QA_head * integration tests pass * flash attn tests pass! * config done * more docs in modeling file * some style fix * style and others * doc test error fix * more doc fix * some attention fixes * most fixes * style and other fixes * docs fix and config * doc fix * some comments * conversion script updated * conversion script updated * Revert "conversion script updated" This reverts commit e92378c54084ec0747041b113083d1746ecb6c7f. * final comments * add Phi to language_modeling.md * edit phi.md file * rebase and fix * removed phi-1.5 example * changed model_type from 'phi'->'mixformer-sequential' * small change * small change * revert \small change * changed mixformer-sequential->phi * small change * added phi-1.5 example instead of phi-1 * doc test might pass now * rebase and small change * added the dropout layer * more fixes * modified .md file * very very small doc change |
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Susnato Dhar
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7e9f10ac94
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Add CLVP (#24745)
* init commit * attention arch done except rotary emb * rotary emb done * text encoder working * outputs matching * arch first pass done * make commands done, tests and docs remaining * all tests passed, only docs remaining * docs done * doc-builder fix * convert script removed(not relevant) * minor comments done * added ckpt conversion script * tokenizer done * very minor fix of index.md 2 * mostly make fixup related * all done except fe and rotary emb * very small change * removed unidecode dependency * style changes * tokenizer removed require_backends * added require_inflect to tokenizer tests * removed VOCAB_FILES in tokenizer test * inflect dependency removed * added rotary pos emb cache and simplified the apply method * style * little doc change * more comments * feature extractor added * added processor * auto-regressive config added * added CLVPConditioningEncoder * comments done except the test one * weights added successfull(NOT tested) * tokenizer fix with numbers * generate outputs matching * almost tests passing Integ tests not written * Integ tests added * major CUDA error fixed * docs done * rebase and multiple fixes * fixed rebase overwrites * generate code simplified and tests for AutoRegressive model added * minor changes * refectored gpt2 code in clvp file * weights done and all code refactored * mostly done except the fast_tokenizer * doc test fix * config file's doc fixes * more config fix * more comments * tokenizer comments mostly done * modeling file mostly refactored and can load modules * ClvpEncoder tested * ClvpDecoder, ClvpModel and ClvpForCausalLM tested * integration and all tests passed * more fixes * docs almost done * ckpt conversion refectored * style and some failing tests fix * comments * temporary output fix but test_assisted_decoding_matches_greedy_search test fails * majority changes done * use_cache outputs same now! Along with the asisted_greedy_decoding test fix * more comments * more comments * prepare_inputs_for_generation fixed and _prepare_model_inputs added * style fix * clvp.md change * moved clvpconditionalencoder norms * add model to new index * added tokenizer input_ids_with_special_tokens * small fix * config mostly done * added config-tester and changed conversion script * more comments * comments * style fix * some comments * tokenizer changed back to prev state * small commnets * added output hidden states for the main model * style fix * comments * small change * revert small change * . * Update clvp.md * Update test_modeling_clvp.py * :) * some minor change * new fixes * remove to_dict from FE |
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Lysandre
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bc78fd1274 | Dev version | ||
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Clifford Ressel
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b5c8e23f0f
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Remove broken links to s-JoL/Open-Llama (#27164) |