GitLab

* v1 tags

* remove unneeded conversion

* v2

* rm unneeded warning

* add more utility methods

* Update src/transformers/utils/hub.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/utils/hub.py
Co-authored-by: Lucain <lucainp@gmail.com>

* Update src/transformers/utils/hub.py
Co-authored-by: Lucain <lucainp@gmail.com>

* more enhancements

* oops

* merge tags

* clean up

* revert unneeded change

* add extensive docs

* more docs

* more kwargs

* add test

* oops

* fix test

* Update src/transformers/modeling_utils.py
Co-authored-by: Omar Sanseviero <osanseviero@gmail.com>

* Update src/transformers/utils/hub.py
Co-authored-by: Lucain <lucainp@gmail.com>

* Update src/transformers/modeling_utils.py

* Update src/transformers/trainer.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update src/transformers/modeling_utils.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* add more conditions

* more logic

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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Lucain <lucainp@gmail.com>
Co-authored-by: Omar Sanseviero <osanseviero@gmail.com>

* MVP

* fix ci

* more ci

* remove redundant kwarg

* added and wired up PromptLookupCandidateGenerator

* rebased with main, working

* removed print

* style fixes

* fix test

* fixed tests

* added test for prompt lookup decoding

* fixed circleci

* fixed test issue

* Update src/transformers/generation/candidate_generator.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update src/transformers/generation/candidate_generator.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update src/transformers/generation/candidate_generator.py

* Update src/transformers/generation/candidate_generator.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

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Co-authored-by: Joao Gante <joao@huggingface.co>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* add mixtral fused modules

* add changes from modeling utils

* add test

* fix test + rope theta issue

* Update src/transformers/modeling_utils.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* add tests

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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update meatdata loading for oneformer

* Enable loading from a model repo

* Update docstrings

* Fix tests

* Update tests

* Clarify repo_path behaviour

* Mark two logger tests as flaky

* Add description to is_flaky

* add llava + fused modules

* Update src/transformers/models/llava/modeling_llava.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* fix

* fix

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Correct the implementation of auxiliary loss of mixtrtal

* correct the implementation of auxiliary loss of mixtrtal

* Implement a simpler calculation method

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Co-authored-by: zhangliangxu3 <zhangliangxu3@jd.com>

* chore(phi): Updates configuration_phi with missing keys.

* chore(phi): Adds first draft of combined modeling_phi.

* fix(phi): Fixes according to latest review.

* fix(phi): Removes pad_vocab_size_multiple to prevent inconsistencies.

* fix(phi): Fixes unit and integration tests.

* fix(phi): Ensures that everything works with microsoft/phi-1 for first integration.

* fix(phi): Fixes output of docstring generation.

* fix(phi): Fixes according to latest review.

* fix(phi): Fixes according to latest review.

* fix(tests): Re-enables Phi-1.5 test.

* fix(phi): Fixes attention overflow on PhiAttention (for Phi-2).

* fix(phi): Improves how queries and keys are upcast.

* fix(phi): Small updates on latest changes.

* optionally preprocess segmentation maps for mobilevit

* changed pretrained model name to that of segmentation model

* removed voc-deeplabv3 from model archive list

* added preprocess_image and preprocess_mask methods for processing images and segmentation masks respectively

* added tests for segmentation masks based on segformer feature extractor

* use crop_size instead of size

* reverting to initial model

Enable multi-label image classification

* [Whisper] Fix slow test

* update

* update

* update

* update

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

Fixup test

* Fix test

* Skip

fix(generation/logits_process.py): BarkEosPrioritizerLogitsProcessor eos_token_id use list, tensor size mismatch
Co-authored-by: chenhanhui <chenhanhui@kanzhun.com>

Use mmap option to load_state_dict (#28331)

* fix `_merge_input_ids_with_image_features` for llava model

* Update src/transformers/models/llava/modeling_llava.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* adress comments

* style and tests

* ooops

* test the backward too

* Apply suggestions from code review
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update tests/models/vipllava/test_modeling_vipllava.py

* style and quality

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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Fix initialization for missing parameters in `from_pretrained` under ZeRO-3

* Test initialization for missing parameters under ZeRO-3

* Add more tests

* Only enable deepspeed context for per-module level parameters

* Enable deepspeed context only once

* Move class definition inside test case body

* fix auxiliary loss training in detrSegmentation

* add auxiliary_loss testing

* 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

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Co-authored-by: patil-suraj <surajp815@gmail.com>

* add segmentation map processing to sam image processor

* fixup

* add tests

* reshaped_input_size is shape before padding

* update tests for size/shape outputs

* fixup

* add code snippet to docs

* Update docs/source/en/model_doc/sam.md
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Add missing backticks

* add `segmentation_maps` as arg for SamProcessor.__call__()

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Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Fix building alibi tensor when num_heads is not a power of 2

* Remove print function

* modified script and added test for phi2

* changes

* [DETA] fix freeze/unfreeze function

* Update src/transformers/models/deta/modeling_deta.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/deta/modeling_deta.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* add freeze/unfreeze test case in DETA

* fix type

* fix typo 2

* fix : enable aux and enc loss in training pipeline

* Add unsynced variables from original DETA for training

* modification for passing CI test

* make style

* make fix

* manual make fix

* change deta_modeling_test of configuration 'two_stage' default to TRUE and minor change of dist checking

* remove print

* divide configuration in DetaModel and DetaForObjectDetection

* image smaller size than 224 will give topk error

* pred_boxes and logits should be equivalent to two_stage_num_proposals

* add missing part in DetaConfig

* Update src/transformers/models/deta/modeling_deta.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* add docstring in configure and prettify TO DO part

* change distribute related code to accelerate

* Update src/transformers/models/deta/configuration_deta.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Update tests/models/deta/test_modeling_deta.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* protect importing accelerate

* change variable name to specific value

* wrong import

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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Fix pos_mask application and update tests accordingly

* Fix style

* Adding comments

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Co-authored-by: Fernando Rodriguez <fernando.rodriguez@nielseniq.com>

When running the case on multi-cards server with devcie_map-auto, It will not always be allocated to device 0,
Because other processes may be using these cards. It will select the devices that can accommodate this model.
Signed-off-by: yuanwu <yuan.wu@intel.com>

* fix M4T FE error when no attention mask

* modify logic

* add test

* go back to initial test situation + add other tests

* fix get_num_masks output as [int] to int

* fix loss size from torch.Size([1]) to torch.Size([])

* remove token_type_ids from model_input_names (like #24788)

* removed test that assumed token_type_ids should be present and updated a model reference so that it points to an available model)

* 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

* v1

* add docstring

* add tests

* add awq 0.1.8

* oops

* fix test

* fix llava index errors

* forward contrib credits from original implementation and fix

* better fix

* final fixes and fix all tests

* fix

* fix nit

* fix tests

* add regression tests

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Co-authored-by: gullalc <gullalc@users.noreply.github.com>

* fix frames

* use smaller chunk length

* correct beam search + tentative stride

* fix whisper word timestamp in batch

* add test batch generation with return token timestamps

* Apply suggestions from code review
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* clean a test

* make style + correct typo

* write clearer comments

* explain test in comment

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Co-authored-by: sanchit-gandhi <sanchit@huggingface.co>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* add check_support_list.py

* fix

* fix

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* First draft

* More improvements

* More improvements

* Make all tests pass

* Remove script

* Update image processor

* Address comments

* Use new gradient checkpointing method

* Convert checkpoints, add integration test

* Do not keep aspect ratio for now

* Set keep_aspect_ratio=False for beit, add integration test

* Remove print statement

Fix: [SeamlessM4T - S2TT] Bug in batch loading of audio in torch.Tensor format in the SeamlessM4TFeatureExtractor class (#27914)

* fixes: code fixes on is_batched condition to also check for batched audio data in torch.Tensor format instead of only just checking for batched audio data in np.ndarray format

* Update src/transformers/models/seamless_m4t/feature_extraction_seamless_m4t.py
Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com>

* refactor: code refactoring to remove torch framework dependency

* docs: updated docstring to add torch tensor compatibility

* test: add test cases to incorporate torch tensor inputs

* test: ran make fix-copies for code conformity

* test: refactor test to separate the test_call into test_call_numpy and test_call_torch

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Co-authored-by: Yoach Lacombe <52246514+ylacombe@users.noreply.github.com>

Update test values

Indices must match stage name ordering

* Fix vision text dual encoder

* Small cleanup for wav2vec2 (not fixed yet)

* Small fix for vision_encoder_decoder

* Fix SAM builds

* Update TFBertTokenizer test with modern exporting + tokenizer

* Fix DeBERTa

* Fix DeBERTav2

* Try RAG fix but it's impossible to test locally

* Actually fix RAG now that I got FAISS working somehow

* Fix Wav2Vec2, add sermon

* Fix Hubert