GitLab

* haha tokens go brrrr

* [deepspeed zero3] need generate(synced_gpus=True, ...)

* fix

* rework per Sylvain's suggestion

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* [deepspeed] offload + non-cpuadam optimizer exception doc

* deps

* [deepspeed docs] Activation Checkpointing

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update deepspeed.mdx

---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* added informer to gitignore

* added informer to gitignore

* WIP informer2020

* added checking that instantiate works

* added config using gluonTS by kashif

* WIP config

* adding informeConfig. need to remove FeatureEmbedder

* done InformerConfig, but need to change the names

* Done informer model init. working on enc-dec

* added things to address, after reading again enc-dec in the paper

* done modeling - checking initialization work

* added informer to gitignore

* WIP informer2020

* added checking that instantiate works

* added config using gluonTS by kashif

* WIP config

* adding informeConfig. need to remove FeatureEmbedder

* done InformerConfig, but need to change the names

* Done informer model init. working on enc-dec

* added things to address, after reading again enc-dec in the paper

* done modeling - checking initialization work

* moved enc-dec init to InformerEncoder/Decoder init

* added 'init_std' to config, now model init works!

* WIP conversion script, and added code sources

* WIP conversion script: loading original informer pth works

* WIP conversion script: change defaults in the config

* WIP conversion script: supporting Informer input embedding

* WIP conversion script: added parameters for the informer embed

* WIP conversion script: change dim_feedforward=2048

* WIP conversion script: remove unused args for loading checkpoint

* just cleaning up

* DataEmbedding removed, after thinking with Kashif

* working on forward pass

* WIP forward pass: trying to establish working batch for forward pass

* cleaning and finalizing

* adding HF names and docs

* init after cleaning works

* WIP in tests

* added docs for the informer specific args

* fix style

* undo change

* cleaning informer, now need to work only enc-dec

* initial enc-dec classes

* added encoder and decoder

* added todo

* add todos for conv_layers

* added decoder docs from vanilla

* added encoder docs from vanilla

* remove encoder decoder from the original informer

* removed AttentionLayer from the original paper

* removed TriangularCausalMask, same as decoder_attention_mask

* initial sparse attention

* use conv_layers

* fixed test_config test

* fix parenthesis when itearting zip(layers, conv_layers)

* error found in prob attention, added sizes as comments

* fix sizes

* added proposal for q_reduce indexing, and remove unused

* WIP ProbMask, and changed factor=2 for testing

* remove unused libs for this PR for creating the env

* fix checking the attn_weights.size() after bmm

* Q_reduce: changed from torch.gather to simple slicing

* WIP calculate final attn_output

* finish adding v_aggregated, attn_output ready

* changed tgt_len to u in attention_mask, need to fix the size error

* comment attention_mask for encoder, and fix if cond for v_agg

* added ProbMask support (wip), removed old original code

* finished ProbMask 😃



* Revert "remove unused libs for this PR for creating the env"

This reverts commit 11a081e09e92771e51a5d2758d53a9afb59547f0.

* fixes

* make style

* fix initial tests

* fix more tests

* dry

* make style

* remove unused files

* style

* added integration tests

* fix num_static_real_features

* fix header

* remove unused function

* fix example

* fix docs

* Update src/transformers/models/informer/configuration_informer.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/informer/modeling_informer.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/informer/configuration_informer.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/informer/configuration_informer.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/informer/configuration_informer.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/informer/configuration_informer.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* fixes for reviewer

* use prediction_length from model

* fix style

* fixed informer.mdx

* added to index

* updated readme

* undo

* make fix-copies

* typo

* fix copy

* added Informer to toctree

* in order

* fixed comments

* remove unneeded new lines in docs

* make static real and cat optional

* fix use of distil conv layers

* fixed integration test

* added checkpoint for convlayer

* make fix-copies

* updated from time series model

* make fix-copies

* copy decoder

* fix unit tests

* updated scaling config

* fix integration tests

* IGNORE_NON_TESTED

* IGNORE_NON_AUTO_CONFIGURED

* IGNORE_NON_AUTO_CONFIGURED

* updated check configs

* fix formatting

* undo change from time series

* prediction_length should not be None

* aliign with the blog: prettify ProbSparse and change attention_factor  to sampling_factor

* make style

* make fix-copies

* niels CR: update contributed by

* niels CR: update configuration_informer.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* niels CR: update kashif -> huggingface
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* niels CR: `sampling_factor` only relevant when `attention_type`=prob

* make style

* fixed U_part: added multiplication by `L_Q`

* fixed bug: remove `is not None` from `if config.distil`

* fixed test: `decoder_seq_length` to `encoder_seq_length` in cross_attentions check

* fix integration tests

* updated model hub

* do not shift as in training

* undo

* fix make-copies

* make fix-copies

* added `if prediction_length is None`

* changed `ProbSparseAttention` to `InformerProbSparseAttention`

* changed `V_sum` -> `v_mean_dim_time`

* changed `ConvLayer` to `InformerConvLayer` and fixed `super()`

* TimeSeriesTansformer->Informer in decoder's Copied from

* more descriptive in ProbSparse

* make style

* fix coped from

* Revert "added `if prediction_length is None`"

This reverts commit b4cbddfa05e3bd739b79569cd3c3b89e316f2451.

* fixed indent

* use InformerSinusoidalPositionalEmbedding

* make fix-style

* fix from #21860

* fix name

* make fix-copies

* use time series utils

* fix dec num_heads

* docstring

* added time series util doc

* _import_structure

* formatting

* changes from review

* make style

* fix docs

* fix doc

* removed NegativeLogLikelihood

---------
Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* update FSDP and add XLA-FSDP documentation

* resolving comments

* minor update

* fix xla-fsdp docs

* add pipeline

* update init

* add zero shot to init

* update inits and correct checkpoints

* update base to support input features

* add tests

* Update src/transformers/pipelines/zero_shot_audio_classification.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Update src/transformers/pipelines/zero_shot_audio_classification.py
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* update pieline code

* use tiny checkpoint

* nits and expected value with tiny model

* style

* last nit on tests values

* fix styling

* fix collate fn that was casting t float

* update

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

* fix wrong url

* typos in english documentation

* v1 `BitsandbytesConfig`

- add v1
- add tests
- more user-friendly API
- add docs

* change to `BitsAndBytesConfig`

* replace logic

* changes

* make fixup

* quality

* make fixup

* fix doc

* fix test

* update toctree

* fix slow test

* add tips

* add warning

* change title

* oops

* Update docs/source/en/main_classes/quantization.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/utils/bitsandbytes.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* remove unused file

* adapt suggestion

- add also tests
- change logic

* update docs

* adapt suggestions

---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* [deepspeed] performance docs

* fix

* re-org

* update

* update

* a new NCCL Collectives section

* inference

* Update docs/source/en/main_classes/deepspeed.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* suggestion

* Update docs/source/en/main_classes/deepspeed.mdx

* suggestion

---------
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* adding note concerning use_node_local_storage

* overriding checkpoint.use_node_local_storage if save_on_each_node == True

* add more content

* add more content

* improve

* style

---------
Co-authored-by: Stas Bekman <stas@stason.org>

* added inverse sqrt lr scheduler

* Updated get_scheduler in src/transformers/optimization.py

* Updated src/transformers/__init__.py

* Added inverse sqrt lr scheduler test

* Updated docs/source/en/main_classes/optimizer_schedules.mdx

* Ran style and quality scripts

* Fix get_inverse_sqrt_schedule docstring

* Comment implementation URL

updated documentation

* make SpeechT5 model by copying Wav2Vec2

* add paper to docs

* whoops added docs in wrong file

* remove SpeechT5Tokenizer + put CTC back in the name

* remove deprecated class

* remove unused docstring

* delete SpeechT5FeatureExtractor, use Wav2Vec2FeatureExtractor instead

* remove classes we don't need right now

* initial stab at speech encoder prenet

* add more speech encoder prenet stuff

* improve SpeechEncoderPrenet

* add encoder (not finished yet)

* add relative position bias to self-attention

* add encoder CTC layers

* fix formatting

* add decoder from BART, doesn't work yet

* make it work with generate loop

* wrap the encoder into a speech encoder class

* wrap the decoder in a text decoder class

* changed my mind

* changed my mind again ;-)

* load decoder weights, make it work

* add weights for text decoder postnet

* add SpeechT5ForCTC model that uses only the encoder

* clean up EncoderLayer and DecoderLayer

* implement _init_weights in SpeechT5PreTrainedModel

* cleanup config + Encoder and Decoder

* add head + cross attention masks

* improve doc comments

* fixup

* more cleanup

* more fixup

* TextDecoderPrenet works now, thanks Kendall

* add CTC loss

* add placeholders for other pre/postnets

* add type annotation

* fix freeze_feature_encoder

* set padding tokens to 0 in decoder attention mask

* encoder attention mask downsampling

* remove features_pen calculation

* disable the padding tokens thing again

* fixup

* more fixup

* code review fixes

* rename encoder/decoder wrapper classes

* allow checkpoints to be loaded into SpeechT5Model

* put encoder into wrapper for CTC model

* clean up conversion script

* add encoder for TTS model

* add speech decoder prenet

* add speech decoder post-net

* attempt to reconstruct the generation loop

* add speech generation loop

* clean up generate_speech

* small tweaks

* fix forward pass

* enable always dropout on speech decoder prenet

* sort declaration

* rename models

* fixup

* fix copies

* more fixup

* make consistency checker happy

* add Seq2SeqSpectrogramOutput class

* doc comments

* quick note about loss and labels

* add HiFi-GAN implementation (from Speech2Speech PR)

* rename file

* add vocoder to TTS model

* improve vocoder

* working on tokenizer

* more better tokenizer

* add CTC tokenizer

* fix decode and batch_code in CTC tokenizer

* fix processor

* two processors and feature extractors

* use SpeechT5WaveformFeatureExtractor instead of Wav2Vec2

* cleanup

* more cleanup

* even more fixup

* notebooks

* fix log-mel spectrograms

* support reduction factor

* fixup

* shift spectrograms to right to create decoder inputs

* return correct labels

* add labels for stop token prediction

* fix doc comments

* fixup

* remove SpeechT5ForPreTraining

* more fixup

* update copyright headers

* add usage examples

* add SpeechT5ProcessorForCTC

* fixup

* push unofficial checkpoints to hub

* initial version of tokenizer unit tests

* add slow test

* fix failing tests

* tests for CTC tokenizer

* finish CTC tokenizer tests

* processor tests

* initial test for feature extractors

* tests for spectrogram feature extractor

* fixup

* more fixup

* add decorators

* require speech for tests

* modeling tests

* more tests for ASR model

* fix imports

* add fake tests for the other models

* fixup

* remove jupyter notebooks

* add missing SpeechT5Model tests

* add missing tests for SpeechT5ForCTC

* add missing tests for SpeechT5ForTextToSpeech

* sort tests by name

* fix Hi-Fi GAN tests

* fixup

* add speech-to-speech model

* refactor duplicate speech generation code

* add processor for SpeechToSpeech model

* add usage example

* add tests for speech-to-speech model

* fixup

* enable gradient checkpointing for SpeechT5FeatureEncoder

* code review

* push_to_hub now takes repo_id

* improve doc comments for HiFi-GAN config

* add missing test

* add integration tests

* make number of layers in speech decoder prenet configurable

* rename variable

* rename variables

* add auto classes for TTS and S2S

* REMOVE CTC!!!

* S2S processor does not support save/load_pretrained

* fixup

* these models are now in an auto mapping

* fix doc links

* rename HiFiGAN to HifiGan, remove separate config file

* REMOVE auto classes

* there can be only one

* fixup

* replace assert

* reformat

* feature extractor can process input and target at same time

* update checkpoint names

* fix commit hash

fix broken link

Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* initial commit, refactoring the text generation api reference

* removed repetitive code examples

* Refactoring the text generation docs to reduce repetition

* make style

* generate from config mvp

* fix failing tests

* max_time test

* Load default gen config at model load time; Update docs

* further documentation; add tests

* adapt rag to the new structure

* handle models not instantiated with from_pretained (like in tests)

* better default generation config

* add can_generate fn

* handle legacy use case of ad hoc model config changes

* initialize gen config from config in individual methods, if gen config is none

* fix _get_decoder_start_token_id when called outside GenerationMixin

* correct model config load order (set attr > model config > decoder config)

* update rag to match latest changes

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* load gen config from model config in model.from_pretrained

* fix can_generate fn

* handle generate calls without a previous from_pretrained (e.g. tests)

* add legacy behavior (and a warning)

* lower logger severity
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* 🚧 wip video classification pipeline

* 🚧 wip - add is_decord_available check

* 🐛 add missing import

* ✅ add tests

* 🔧 add decord to setup extras

* 🚧 add is_decord_available

* ✨ add video-classification pipeline

* 📝 add video classification pipe to docs

* 🐛 add missing VideoClassificationPipeline import

* 📌 add decord install in test runner

* ✅ fix url inputs to video-classification pipeline

* ✨ updates from review

* 📝 add video cls pipeline to docs

* 📝 add docstring

* 🔥 remove unused import

* 🔥 remove some code

* 📝 docfix

* Update doc example feature extractor -> image processor

* Apply suggestions from code review

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Init Update

* ClearML Callbacks integration

* update corrections

* args reporting updated

* {'tensorboard': False, 'pytorch': False}

* ClearML Tests added

* add clearml

* output_uri=True in Task.init

* reformatted integrations.py

* reformatted and fixed

* IF-ELSE statement issue on "has_clearml" resolved

* Add clearml in main callback docs

* Add additional clearml documentation

* Update src/transformers/integrations.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Accept suggestion
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Accept suggestion
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Small change in comments

* Make style clearml

* Accept suggestion
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Victor Sonck <victor.sonck@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* move generation_*.py src files into generation/*.py

* populate generation.__init__ with lazy loading

* move imports and references from generation.xxx.object to generation.object

* AutoImageProcessor skeleton

* Update references

* Add mapping in init

* Add model image processors to __init__ for importing

* Add AutoImageProcessor tests

* Fix up

* Image Processor documentation

* Remove pdb

* Update docs/source/en/model_doc/mobilevit.mdx

* Update docs

* Don't add whitespace on json files

* Remove fixtures

* Move checking model config down

* Fix up

* Add check for image processor

* Remove FeatureExtractorMixin in docstrings

* Rename model_tmpfile to config_tmpfile

* Don't make None if not in image processor map

* docs: Fix typo in ONNX parser help: 'tolerence' => 'tolerance'

* docs: Resolve many typos in the English docs

Typos found via 'codespell ./docs/source/en'

Adding the state-of-the-art contrastive search decoding methods for the codebase of generation_utils.py (#19477)

* add: the contrastive search for generaton_utils

* add: testing scripts for contrastive search under examples/text-generation

* update the quality of codes

* revise the docstring; make the generation_contrastive_search.py scripts;

* revise the examples/pytorch/text-generation/run_generation_contrastive_search.py to the auto-APIs format

* revise the necessary documents

* fix: revise the docstring of generation_contrastive_search.py

* Fix the code indentation

* fix: revise the nits and examples in contrastive_search docstring.

* fix the copyright

* delete generation_contrastive_search.py

* revise the logic in contrastive_search

* update the intergration test and the docstring

* run the tests over

* add the slow decorate to the contrastive_search intergrate test

* add more test

* do the style, quality, consistency checks

* Add initial files for depth estimation pipelines

* Add test file for depth estimation pipeline

* Update model mapping names

* Add updates for depth estimation output

* Add generic test

* Hopefully fixing the tests.

* Check if test passes

* Add make fixup and make fix-copies changes after rebase with main

* Rebase with main

* Fixing up depth pipeline.

* This is not used anymore.

* Fixing the test. `Image` is a module `Image.Image` is the type.

* Update docs/source/en/main_classes/pipelines.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Add ZeroShotObjectDetectionPipeline (#18445)

* Add AutoModelForZeroShotObjectDetection task

This commit also adds the following

- Add explicit _processor method for ZeroShotObjectDetectionPipeline.
  This is necessary as pipelines don't auto infer processors yet and
  `OwlVitProcessor` wraps tokenizer and feature_extractor together, to
  process multiple images at once

- Add auto tests and other tests for ZeroShotObjectDetectionPipeline

* Add AutoModelForZeroShotObjectDetection task

This commit also adds the following

- Add explicit _processor method for ZeroShotObjectDetectionPipeline.
  This is necessary as pipelines don't auto infer processors yet and
  `OwlVitProcessor` wraps tokenizer and feature_extractor together, to
  process multiple images at once

- Add auto tests and other tests for ZeroShotObjectDetectionPipeline

* Add batching for ZeroShotObjectDetectionPipeline

* Fix doc-string ZeroShotObjectDetectionPipeline

* Fix output format: ZeroShotObjectDetectionPipeline

* Fix a broken link for deepspeed ZeRO inference

* fix link
Co-authored-by: Stas Bekman <stas@stason.org>

* NeptuneCallback improvements

* After review suggestions and deduplication of initial run

* Added volatile checkpoints support due to missing post-rebase commit

* Update README per review comments

- Remove list formatting
- Correct Neptune docs link
Co-authored-by: Sabine <sabine.nyholm@neptune.ai>

* [WIP] Skeleton of VisualQuestionAnweringPipeline extended to support LayoutLM-like models

* Fixup

* Use the full encoding

* Basic refactoring to DocumentQuestionAnsweringPipeline

* Cleanup

* Improve args, docs, and implement preprocessing

* Integrate OCR

* Refactor question_answering pipeline

* Use refactored QA code in the document qa pipeline

* Fix tests

* Some small cleanups

* Use a string type annotation for Image.Image

* Update encoding with image features

* Wire through the basic docs

* Handle invalid response

* Handle empty word_boxes properly

* Docstring fix

* Integrate Donut model

* Fixup

* Incorporate comments

* Address comments

* Initial incorporation of tests

* Address Comments

* Change assert to ValueError

* Comments

* Wrap `score` in float to make it JSON serializable

* Incorporate AutoModeLForDocumentQuestionAnswering changes

* Fixup

* Rename postprocess function

* Fix auto import

* Applying comments

* Improve docs

* Remove extra assets and add copyright

* Address comments
Co-authored-by: Ankur Goyal <ankur@impira.com>

Co-authored-by: Olivier Dehaene <olivier@huggingface.co>

* Add Image2TextGenerationPipeline to supported pipelines

* Add Flax and Tensorflow support

* Add Flax and Tensorflow small tests

* Add default model for Tensorflow

* Add docstring

* Fix doc style

* Add tiny models for pytorch and flax

* Remove flax from pipeline.
Fix tests

* Use ydshieh/vit-gpt2-coco-en as a default for both PyTorch and Tensorflow

* Fix Tensorflow support
Co-authored-by: Olivier Dehaene <olivier@huggingface.co>