GitLab

* Adding support for multiple mask tokens.

- Original implem: https://github.com/huggingface/transformers/pull/10222

Co-authored-by: njafer <naveen.jafer@oracle.com>

* In order to accomodate optionally multimodal models like Perceiver

we add information to the tasks to specify tasks where we know for sure
if we need the tokenizer/feature_extractor or not.

* Adding info in the documentation about multi masks.

+ marked as experimental.

* Add a copy() to prevent overriding the same tensor over and over.

* Fixup.

* Adding small test for multi mask with real values..
Co-authored-by: njafer <naveen.jafer@oracle.com>

* Adding some slow test to check for perceiver at least from a high level.

* Re-enabling fast tests for Perceiver ImageClassification.

* Perceiver might try to run without Tokenizer (Fast doesn't exist) and
with FeatureExtractor some text only pipelines.

* Oops.

* Adding a comment for `update_config_with_model_class`.

* Remove `model_architecture` to get `tiny_config`.

* Finalize rebase.

* Smarter way to handle undefined FastTokenizer.

* Remove old code.

* Addressing some nits.

* Don't instantiate `None`.

* First draft

* Improve docstring + clean up tests

* Remove unused code

* Add check in case one doesn't provide a preprocessor

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

- Do not run image-classification pipeline (_CHECKPOINT_FOR_DOC uses the checkpoint for
langage, which cannot load a FeatureExtractor so current logic fails).
- Add a safeguard to not run tests when `tokenizer_class` or
`feature_extractor_class` **are** defined, but cannot be loaded
This happens for Perceiver for the "FastTokenizer" (which doesn't exist
so None) and FeatureExtractor (which does exist but cannot be loaded
because the checkpoint doesn't define one which is reasonable for the
said checkpoint)
- Added `get_vocab` function to `PerceiverTokenizer` since it is used by
`fill-mask` pipeline when the argument `targets` is used to narrow a
subset of possible values.
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* Fixing tests for perceiver (texts)

* For MaskedLM

This reverts commit 0c70f145.

* Added support for other features for already supported models

* Partial support for causal and seq2seq models

* Partial support for causal and seq2seq models

* OnnxSeq2SeqConfigWithPast to support seq2seq models

* Parameterized the onnx tests

* Restored run_mlm.py

* Restored run_mlm.py

* [WIP] BART update

* BART and MBART

* Added comments

* Another sequence length of the past_key_values

* [AutoProcessor] Add Wav2Vec2WithLM & small fix

* revert line removal

* Update src/transformers/__init__.py

* add test

* up

* up

* small fix

* First draft

* Style and remove mlm

* Make forward pass work

* More improvements

* More improvements

* Fix bug

* More improvements

* More improvements

* Add PerceiverTokenizer first draft

* Improve conversion script

* More improvements

* Make conversion script work for the encoder

* Make conversion script work with local pickle files

* Style & quality, fix-copies

* Add dummy input to conversion script

* Add absolute position embeddings to TextPreProcessor

* Make forward pass of encoder work

* More improvements

* Move text preprocessor to separate script

* More improvements

* More improvements

* Add post processor

* Make MLM model work

* Style

* Add PerceiverForMaskedLM

* Add PerceiverImagePreprocessor

* Make style

* Make PerceiverForImageClassification work

* More improvements

* More improvements

* Use tokenizer in conversion script

* Use PerceiverForMaskedLM in conversion script

* Define custom PerceiverModelOutput

* Improve PerceiverAttention to make it work for both MLM and image classification

* More improvements

* More improvements

* More improvements to the conversion script

* Make conversion script work for both MLM and image classification

* Add PerceiverFeatureExtractor

* More improvements

* Style and quality

* Add center cropping

* Fix bug

* Small fix

* Add print statement

* Fix bug in image preprocessor

* Fix bug with conversion script

* Make output position embeddings an nn.Parameter layer instead of nn.Embedding

* Comment out print statements

* Add position encoding classes

* More improvements

* Use position_encoding_kwargs

* Add PerceiverForImageClassificationFourier

* Make style & quality

* Add PerceiverForImageClassificationConvProcessing

* Style & quality

* Add flow model

* Move processors to modeling file

* Make position encodings modular

* Make basic decoder use modular position encodings

* Add PerceiverForOpticalFlow to conversion script

* Add AudioPreprocessor

* Make it possible for the basic decoder to use Fourier position embeddings

* Add PerceiverForMultimodalAutoencoding

* Improve model for optical flow

* Improve _build_network_inputs method

* Add print statement

* Fix device issue

* Fix device of Fourier embeddings

* Add print statements for debugging

* Add another print statement

* Add another print statement

* Add another print statement

* Add another print statement

* Improve PerceiverAudioPreprocessor

* Improve conversion script for multimodal modal

* More improvements

* More improvements

* Improve multimodal model

* Make forward pass multimodal model work

* More improvements

* Improve tests

* Fix some more tests

* Add output dataclasses

* Make more tests pass

* Add print statements for debuggin

* Add tests for image classification

* Add PerceiverClassifierOutput

* More improvements

* Make more tests pass for the optical flow model

* Make style & quality

* Small improvements

* Don't support training for optical flow model for now

* Fix _prepare_for_class for tests

* Make more tests pass, add some docs

* Add multimodal model to tests

* Minor fixes

* Fix tests

* Improve conversion script

* Make fixup

* Remove pos_dim argument

* Fix device issue

* Potential fix for OOM

* Revert previous commit

* Fix test_initialization

* Add print statements for debugging

* Fix print statement

* Add print statement

* Add print statement

* Add print statement

* Add print statement

* Add print statement

* Add print statement

* Remove need for output_shape

* Comment out output_shape

* Remove unnecessary code

* Improve docs

* Fix make fixup

* Remove PerceiverTextProcessor from init

* Improve docs

* Small improvement

* Apply first batch of suggestions from code review

* Apply more suggestions from code review

* Update docstrings

* Define dicts beforehand for readability

* Rename task to architecture in conversion script, include PerceiverModel in tests

* Add print statements for debugging

* Fix tests on GPU

* Remove preprocessors, postprocessors and decoders from main init

* Add integration test

* Fix docs

* Replace einops by torch

* Update for new docs frontend

* Rename PerceiverForImageClassification

* Improve docs

* Improve docs

* Improve docs of PerceiverModel

* Fix some more tests

* Improve center_crop

* Add PerceiverForSequenceClassification

* Small improvements

* Fix tests

* Add integration test for optical flow model

* Clean up

* Add tests for tokenizer

* Fix tokenizer by adding special tokens properly

* Fix CI

* up

* up

* up

* make it cleaner

* correct

* make styhahalal

* add more tests

* finish

* small fix

* make style

* up

* tryout to solve cicrle ci

* up

* fix more tests

* fix more tests

* apply sylvains suggestions

* fix import

* correct docs

* add pyctcdecode only to speech tests

* fix more tests

* add tf, flax and pt tests

* add pt

* fix last tests

* fix more tests

* Apply suggestions from code review

* change lines

* Apply suggestions from code review
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* correct tests

* correct tests

* add doc string
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* Fixing Dataset for TQA + token-classification.

* Fixing the tests.

* Making sure `offset_mappings` is a valid argument.

* [deepspeed] fix load_best_model_at_end

* try with pull_request_target

* revert: try with pull_request_target

* style

* add test

* cleanup

* implement MLukeTokenizer and LukeForMaskedLM

* update tests

* update docs

* add LukeForMaskedLM to check_repo.py

* update README

* fix test and specify the entity pad id in tokenization_(m)luke

* fix EntityPredictionHeadTransform

* add cross_attention_hidden_size to text-2-text encoder-decoder models (PT/Flax)

* for TFEncoderDecoderModel

* add equivalence test for TFEncoderDecoderModel

* fix

* fix failed equivalence tests

* remove unused import

* add detailed comment

* Fix check_equivalence_tf_to_pt by using encoder/decoder

* cleaning

* Use cross_attention_hidden_size in speech-to-text

* clean fast init logging msg in encoder decoder models

* increase tol from 1e-5 to 1e-3 for tf test

* style

* style

* make sure projection layer can run

* remove type conversion + add check

* fix conflict (config.output_hidden_size)

* Remove TF -> PT in check_pt_tf_equivalence for TFEncoderDecoderModel
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Add AutoProcessor class
Init and tests
Add doc
Fix init
Update src/transformers/models/auto/processing_auto.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Reverts to tokenizer or feature extractor when available
Adapt test

* Revert "Adapt test"

This reverts commit bbdde5fab02465f24b54b227390073082cb32093.

* Revert "Reverts to tokenizer or feature extractor when available"

This reverts commit 77659ff5d21b6cc0baf6f443017e35e056a525bb.

* Don't revert everything Lysandre!
Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>

* Add GPTJForQuestionAnswering

* Reformat for GPTJForQuestionAnswering

* Fix isort error

* make style for GPTJForQA

* Add _keys_to_ignore_on_load_missing

* Change the sequence of qa and classification
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* [trainer] add --tf32 support

* it's pt>=.17

* it's pt>=.17

* flip the default to True

* add experimental note

* simplify logic

* style

* switch to 3-state logic

* doc

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

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

* Use new method to acquire tokenizers

* Resolve TODOs.

* Style

* Fix

* Enable do_lower_case in test_tokenize_special_tokens

* Apply suggestion from code review

* Fix mask token handling

* Revert "Fix mask token handling"

This reverts commit daaa3f5291b1f71e5bc3604ca281c000000c4648.

* Fix FNet mask token tokenization

* Complete everything

* Apply suggestions from code review

* fix #14524 (IndexError when mask prob is too low)

* fix formatting

* correct documentation, add option for setting min_num_masks

* change the semantic meaning of `mask_prob` in _compute_mask_indices

With this commit the meaing of `mask_prob` actually adhered to the probability for each
vector to be the start of a masked span of length.

* fix check_copies test

* fix documentation to semantic meaning of `upper bound of overall masking percentage`, revert changes to _compute_mask_indices

* fix typo

* [WIP] Add FlaxBlenderbotSmall

* Revert some unintentionally changed files

Revert some unintentionally files changed by improperly filled cookiecutter instructions.

* Fix repo consistency

* Fix Flax-PT equivalence

* Apply suggestions from code review

* Update index.mdx

* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* add flax gptj

* no bias in attention dense

* no wpe

* fix rotary embeddings

* fix rotary embeds

* fix rotray embeds

* quality

* doc and quality

* fix equivalence tests

* started bf16 integration

* minor changes

* code now runs

* style

* lay foundation for bf16 testing

* lay foundation for bf16 testing

* start the tests

* better bf16 check

* style

* 2 separate checkers - one for bf16 support, another for bf16+autocast

* Update src/transformers/training_args.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* a couple of comment resolutions

* more comment resolutions

* resolved a small bug

* just some print statemtns

* added todo marking

* added a todo

* adjust for API change s/fast_dtype/dtype/

* fix style

* merge 2 bf16 util functions

* bf16 now does scaling too

* Add support for bfloat16

* Revert T5 layernorm to float32

This is based on the comment at https://github.com/huggingface/transformers/pull/14448/files#r752660929 and the PyTorch PR https://github.com/pytorch/pytorch/pull/66920

 .

* Add comment about conversion to float32 before returning the numpy data

* Add comment about AMP-bfloat16 incompatibility

* Fix formatting

* typo

* reformer / bf16

* cleanup

* require at least pt-1.10

* fix

* will deal with deepspeed separately

* cleanup

* revert

* cleanup

* fp16_full_eval and bf16_full_eval are separate modes

* proper deprecation

* cleanup

* test and fixes

* spelling

* cleanup

* add a note that this API is experimental
Co-authored-by: jamie <jamie@cortx.com>
Co-authored-by: Stas Bekman <stas@stason.org>
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: suriya <suriya@cortx.com>
Co-authored-by: Manuel R. Ciosici <manuelrciosici@gmail.com>

* init vision_text_dual_encoder

* fix merge

* remove extra heads

* fix tests

* remove VISION_TEXT_DUAL_ENCODER_PRETRAINED_CONFIG_ARCHIVE_MAP

* remove archive map

* fix imports

* fix more imports

* fix init

* delete tokenizers

* fix imports

* clean

* support clip's vision model

* handle None config

* begin tests

* more test and few fixes

* warn about newly init weights

* more tests

* add loss to model

* remove extra classes from doc

* add processor

* doc and small fixes

* add start docstr

* update flax model

* flax tests

* more flax tests

* doc

* quality

* doc and quality

* fix doc

* doc

* remove comments

* update warning

* quality

* fix docs

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* replace asserts, fix imports

* update imports

* fix import

* address some review comments

* fix check

* reduce tolerance

* fix test

* add flax integration test

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

* address Sylvain's comments

* fix style

* add pt_flax_equivalence test in PT tests

* add pt integration test

* update test

* use pre-trained checkpoint in examples
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Init Flax implementation for Blenderbot

* Add a majority of stuff except for tests

* make style quality

* Add tests and fix some bugs

* Add tests

* Clean source code and fix some bugs

* Fix copies and docs

* Fix jax device condition for tests

* Fix layer norm in the encoder

* Fix a few typos in the test file

* make fix-copies

* make fix-copies

* fix layer norm

* Fix Flax params dtype (#13090)

* Fix PR reference (#13098)

* make fix-copies

* Update tests/test_modeling_flax_blenderbot.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* TF Tapas first commit

* updated docs

* updated logger message

* updated pytorch weight conversion
script to support scalar array

* added use_cache to tapas model config to
work properly with tf input_processing

* 1. rm embeddings_sum
2. added # Copied
3. + TFTapasMLMHead
4. and lot other small fixes

* updated docs

* + test for tapas

* updated testing_utils to check
is_tensorflow_probability_available

* converted model logits post processing using
numpy to work with both PT and TF models

* + TFAutoModelForTableQuestionAnswering

* added TF support

* added test for
TFAutoModelForTableQuestionAnswering

* added test for
TFAutoModelForTableQuestionAnswering pipeline

* updated auto model docs

* fixed typo in import

* added tensorflow_probability to run tests

* updated MLM head

* updated tapas.rst with TF  model docs

* fixed optimizer import in docs

* updated convert to np
data from pt model is not
`transformers.tokenization_utils_base.BatchEncoding`
after pipeline upgrade

* updated pipeline:
1. with torch.no_gard removed, pipeline forward handles
2. token_type_ids converted to numpy

* updated docs.

* removed `use_cache` from config

* removed floats_tensor

* updated code comment

* updated Copyright Year and
logits_aggregation Optional

* updated docs and comments

* updated docstring

* fixed model weight loading

* make fixup

* fix indentation

* added tf slow pipeline test

* pip upgrade

* upgrade python to 3.7

* removed from_pt from tests

* revert commit f18cfa9

* Rename

* Add MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING

* Improve tests

* Install vision for tf tests

* [deepspeed] zero inference

* only z3 makes sense for inference

* fix and style

* docs

* rework

* fix test

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

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

* Add AutoProcessor class

* Init and tests

* Add doc

* Fix init

* Update src/transformers/models/auto/processing_auto.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Reverts to tokenizer or feature extractor when available

* Adapt test
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Moving everything to `hf-internal-testing`.

* Fixing test values.

* Moving to other repo.

* Last touch?

* clean up branch for add-qdqbert-model

* README update for QAT example; update docstrings in modeling_qdqbert.py

* Update qdqbert.rst

* Update README.md

* Update README.md

* calibration data using traning set; QAT example runs in fp32

* re-use BERTtokenizer for qdqbert

* Update docs/source/model_doc/qdqbert.rst
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update docs/source/model_doc/qdqbert.rst
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update docs/source/model_doc/qdqbert.rst
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* remove qdqbert tokenizer

* Update qdqbert.rst

* update evaluate-hf-trt-qa.py

* update configuration_qdqbert.py

* update modeling_qdqbert.py: add copied statement; replace assert with ValueError

* update copied from statement

* add is_quantization_available; run make fix-copies

* unittest add require_quantization

* add backend dependency to qdqbert model

* update README; update evaluate script; make style

* lint

* docs qdqbert update

* circleci build_doc add pytorch-quantization for qdqbert

* update README

* update example readme with instructions to upgrade TensorRT to 8.2

* Update src/transformers/models/qdqbert/configuration_qdqbert.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/models/qdqbert/configuration_qdqbert.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/models/qdqbert/configuration_qdqbert.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/models/qdqbert/configuration_qdqbert.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* change quantization to pytorch_quantization for backend requirement

* feed_forward_chunking not supported in QDQBert

* make style

* update model docstrings and comments in testing scripts

* rename example to quantization-qdqbert; rename example scripts from qat to quant

* Update src/transformers/models/qdqbert/modeling_qdqbert.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* rm experimental functions in quant_trainer

* qa cleanup

* make fix-copies for docs index.rst

* fix doctree; use post_init() for qdqbert

* fix early device assignment for qdqbert

* fix CI:Model templates runner
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

support.

* up

* finalize

* finalize

* finish

* Update src/transformers/generation_utils.py

* apply feedback

* Add integration test

* Fix typo

* First draft

* More improvements

* Improve conversion script

* Fix init weights for layer norm

* Fix correct model for conversion script

* Don't tie input and output embeddings

* Add print statements for debugging

* Add print statements for debugging

* Fix vocab size of model

* Improve documentation, remove fast tokenizer

* Add ImageGPTForImageClassification, improve docs

* Fix docs issue

* Set verbosity level back to info

* Improve tests

* Fix tests and add figure

* Delete tokenizer file

* Remove ImageGPTTokenizer from init files

* Remove ImageGPTLayer from init files

* Remove ImageGPT tokenizer from docs

* First draft of ImageGPTFeatureExtractor

* Fix typo

* Fix bug

* More improvements

* Apply suggestions from code review, add tests for feature extractor

* Fix layernorm

* Update save_pretrained method

* Fix issue

* Make all tests of ImageGPTFeatureExtractor pass

* Update code examples

* Rename model inputs to pixel_values

* Improve code examples

* Update init_weights to post_init

* Fix post_init