GitLab

* [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>

The model outputs a pooler_output whereas the doctype examples were using a pooled_output.

* 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>

* Replace outdated model tags with their now-canonical pipeline types

* spam the CI till it's green

* add test for glue

* add tests for clm

* fix clm test

* add summrization tests

* more tests

* fix few tests

* add test for t5 mlm

* fix t5 mlm test

* fix tests for multi device

* cleanup

* ci job

* fix metric file name

* make t5 more robust

* Make DefaultDataCollator importable from root

* Add documentation for DefaultDataCollator and add return_tensors argument to all class docstrings

* make style

* Add DefaultDataCollator to data_collator.rst

* Add DefaultDataCollator to data_collator.rst

* [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>

* 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

Co-authored-by: yis <yis@graphcore.ai>

* [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>

* Fix mask token handling

* Revert "Fix mask token handling"

This reverts commit daaa3f5291b1f71e5bc3604ca281c000000c4648.

* Fix FNet mask token tokenization

* Convert PretrainedConfig doc to Markdown

* Use syntax

* Add necessary doc files (#14496)

* Doc fixes (#14499)

* Fixes for the new front

* Convert DETR file for table

* Title is needed

* Simplify a bit

* Even simpler

* Remove imports

* Fix typo in toctree (#14516)

* Fix checkpoints badge

* Update versions.yml format (#14517)

* Doc new front github actions (#14512)

* Doc new front github actions

* Fix docstring

* Fix feature extraction utils import (#14515)

* Address Julien's comments

* Push to doc-builder

* Ready for merge

* Remove old build and deploy

* Doc misc fixes (#14583)

* Rm versions.yml from doc

* Fix converting.rst

* Rm pretrained_models from toctree

* Fix index links (#14567)

* Fix links in README

* Localized READMEs

* Fix copy script

* Fix find doc script

* Update README_ko.md
Co-authored-by: Julien Chaumond <julien@huggingface.co>
Co-authored-by: Julien Chaumond <julien@huggingface.co>

* Adapt build command to new CLI tools (#14578)

* Fix typo

* Fix doc interlinks (#14589)

* Convert PretrainedConfig doc to Markdown

* Use syntax

* Rm pattern <[a-z]+(.html).*>

* Rm huggingface.co/transformers/master

* Rm .html

* Rm .html from index.mdx

* Rm .html from model_summary.rst

* Update index.mdx rm html

* Update remove .html

* Fix inner doc links

* Fix interlink in preprocssing.rst

* Update pr_checks
Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Convert PretrainedConfig doc to Markdown

* Use syntax

* Add necessary doc files (#14496)

* Doc fixes (#14499)

* Fixes for the new front

* Convert DETR file for table

* Title is needed

* Simplify a bit

* Even simpler

* Remove imports

* Fix checkpoints badge

* Fix typo in toctree (#14516)

* Update versions.yml format (#14517)

* Doc new front github actions (#14512)

* Doc new front github actions

* Fix docstring

* Fix feature extraction utils import (#14515)

* Address Julien's comments

* Push to doc-builder

* Ready for merge

* Remove old build and deploy

* Doc misc fixes (#14583)

* Rm versions.yml from doc

* Fix converting.rst

* Rm pretrained_models from toctree

* Fix index links (#14567)

* Fix links in README

* Localized READMEs

* Fix copy script

* Fix find doc script

* Update README_ko.md
Co-authored-by: Julien Chaumond <julien@huggingface.co>
Co-authored-by: Julien Chaumond <julien@huggingface.co>

* Adapt build command to new CLI tools (#14578)

* Fix typo

* Fix doc interlinks (#14589)

* Convert PretrainedConfig doc to Markdown

* Use syntax

* Rm pattern <[a-z]+(.html).*>

* Rm huggingface.co/transformers/master

* Rm .html

* Rm .html from index.mdx

* Rm .html from model_summary.rst

* Update index.mdx rm html

* Update remove .html

* Fix inner doc links

* Fix interlink in preprocssing.rst

* Update pr_checks
Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Styling
Co-authored-by: Mishig Davaadorj <mishig.davaadorj@coloradocollege.edu>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Julien Chaumond <julien@huggingface.co>

* 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>

* use functional interface instead of instantiating module and immediately calling it

* fix torch.nn.functional to nn.functional. Thank you Stas!

* "update example docstring multilabel example

* update example docstring multilabel example

* 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

* Add checkpointing to push_to_hub and PushToHubCallback

* Add checkpoint loading

* Add missing default value

* Correct method name

* make style

* Moving everything to the right location

* make style

* Revert changes to file_utils.py

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

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

* Adding docstrings and comments to clarify code

* make style

* Fix organization positional arg

* Fix load_repo_checkpoint to no longer accidentally create empty repos

* make style

* Remove unnecessary 'organization' argument in load_repo_checkpoint

* Avoid private `_create_or_get_repo` method

* make style

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

* Rename

* Add MODEL_FOR_CAUSAL_IMAGE_MODELING_MAPPING

* Added the lang argument to apply_tesseract in feature_extraction_layoutlmv2.py, which is used in pytesseract.image_to_data.

* Added ocr_lang argument to LayoutLMv2FeatureExtractor.__init__, which is used when calling apply_tesseract

* Updated the documentation of the LayoutLMv2FeatureExtractor

* Specified in the documentation of the LayoutLMv2FeatureExtractor that the ocr_lang argument should be a language code.

* Update src/transformers/models/layoutlmv2/feature_extraction_layoutlmv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Split comment into two lines to adhere to the max line size limit.

* Update src/transformers/models/layoutlmv2/feature_extraction_layoutlmv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

When loading a pretrained tokenizer, a verification is done to ensure
that the actual tokenizer class matches the class it was called from.
If the tokenizer is absent, its config file is loaded from the repo.

However, the cache_dir for downloading is not provided, which leads to
ignoring of the user-specified cache_dir, storing files in several
places and and may result in incorrect warnings when the default
cache_dir is unreachsble.

This commit fixes that.

* [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>

* remove sum for list flattening

* change to chain(*)

* make chain object a list

* delete empty lines

per sgugger's suggestions
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Nicholas Broad <nicholas@nmbroad.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

in case of left padding_side there was a copy/paste error
assigning the bbox data to the labels

* 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>

* Fix dummy objects for quantization

* Add more models

* Update trainer_utils.py

* add Tuple type hints to all label_ids outputs

affects EvalLoopOutput and PredicctionOutput

* 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