GitLab

* add support for MLFLOW_FLATTEN_PARAMS

* ensure key is str

* fix style and update warning msg

* Empty commit to trigger CI

* fix bug in check_inits.py

* add unittest for flatten_dict utils

* fix 'NoneType' object is not callable on __del__

* add generic flatten_dict unittest to SPECIAL_MODULE_TO_TEST_MAP

* fix style

* model zoo take 2

* add deberta

* new param for zero2

* doc update

* doc update

* add layoutlm

* bump deepspeed

* add deberta-v2, funnel, longformer

* new models

* style

* add t5_v1

* update TAPAS status

* reorg problematic models

* move doc to another PR

* style

* fix checkpoint check test

* making progress on more models running

* cleanup

* new version

* cleanup

* [trainer] sharded _load_best_model

probably needs a test?

* undo delete

Co-authored-by: Dom Miketa <dmiketa@exscientia.co.uk>

* LogSumExp trick `question_answering` pipeline.

* Adding a failing test.

* ensure mlflow.end_run() is executed at end of training when mlflow.start_run() was executed by the callback

* add debug msg

* add support for MLFLOW_TAGS, MLFLOW_RUN_ID, and MLFLOW_NESTED_RUN

* update to support python 3.6+

* Validate env variables using ENV_VARS_TRUE_VALUES

* Empty-Commit

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

- Adds auto_batch_size finder 
- Moves training loop to an inner training loop

* rebase and isort

* modify cookiecutter init

* fix cookiecutter auto imports

* fix clean_frameworks_in_init

* fix add_model_to_main_init

* blackify

* replace unnecessary f-strings

* update yolos imports

* fix roberta import bug

* fix yolos missing dependency

* fix add_model_like and cookiecutter bug

* fix repository consistency error

* modify cookiecutter, fix add_new_model_like

* remove stale line
Co-authored-by: Dom Miketa <dmiketa@exscientia.co.uk>

* PyTorch FSDP integration in Trainer

* reformatting

make style and make quality are now compliant.

* Updating dependency check

* Trigger CI
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>

* update docs of length_penalty

* Revert "update docs of length_penalty"

This reverts commit 466bf4800b75ec29bd2ff75bad8e8973bd98d01c.

* add mobilebert onnx config

* address suggestions

* Update auto.mdx

* Update __init__.py

* Update features.py

* Add type hints for remaining BigBirdPegasus models

Here I added type hints to the BigBirdPegasusForCausalLM class.

* Add missing type hints for Data2VecText models

Added type hints to the Data2VecTextForCausalLM, Data2VecTextForMaskedLM,
Data2VecTextForMultipleChoice, Data2VecTextForQuestionAnswering,
Data2VecTextForSequenceClassification, and
Data2VecTextForTokenClassification classes.

LayoutLMv2Processor: ensure 1-to-1 mapping between images and samples in case of overflowing tokens (#17092)

* add get_overflowing_images function to ensure 1-to-1 mapping between samples and images in LayoutLMv2Processor

* make style

* add test for overflowing_tokens, change assert to ValueError, avoiding unrelated formatting changes

* change line length by passing --preview into black

* Add onnx configuration for bigbird-pegasus

* Modify docs

* Fix use of mlflow.active_run() and add proper support for MLFLOW_EXPERIMENT_NAME

* Fix code style (make style)

Added type hints for the BERTGenerationEncoder and BERTGenerationDecoder
classes.

* type hints for pytorch models

* fixed import error

* fixed some errors

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

* CLIP Serving

* Add type hints per code review

* Use black, flake8, and isort

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

* Rollback serving_output and add TODO

* Remove irrelevant portions of failing tests

* Revert "Rollback serving_output and add TODO"

This reverts commit a4abfa6ba3b7875a13538dbc2ddc4eb17dfcca8d.

* Rollback to original test/serving_output

* Fix unused var

* Apply suggestions from code review

* Update formatting with black

* Fix style again from rebase

* Update tests/models/clip/test_modeling_tf_clip.py
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Sean Moriarity <sean.l.moriarity.mil@army.mil>
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

* Deprecate model templates

* Address review comments

* Type hint complete Albert model file.

* Update typing.

* Update src/transformers/models/albert/modeling_albert.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* add utilities till TFData2VecVisionLayer.

* chore: pass window_size to attention layer.

* feat: add TFData2VecVisionRelativePositionBias.

* feat: initial implementation ready for tf data2vec.

* fix: relative position bias index, table to be fixed.

* chore: implementation added, tests remaining.

* add: tests, other PR files.

* fix: code quality.

* fix: import structure in init.

* chore: run make fix-copies.

* chore: address PR feedback (round I).

* chore: styling nit.

* fix: tests due to removal of to_2tuple().

* chore: rebase with upstream main and move the test.

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

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

* fix: layer call.

* chore: remove from_pt=True and rerun test.

* chore: remove cast and tf.divide.

* chore: minor edits to the test script.

* Update src/transformers/models/data2vec/modeling_tf_data2vec_vision.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* fix: expand() on TF tensors with broadcast_to().

* fix: test import.
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* Make sure telemetry arguments are not returned as unused kwargs

* Fix test

* Add masked image modelling to task mapping

* Refactor ONNX features to be listed alphabetically

* Add warning about BEiT masked image modeling
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Skip RoFormer ONNX test if rjieba not installed

* Update deps table

* Skip RoFormer serialization test

* Fix RoFormer vocab

* Add rjieba to CircleCI

* Fix RNG reload in resume training from epoch checkpoint

* Fix test

* Make Trainer compatible with sharded checkpoints

* Add doc

* move test model folders (TODO: fix imports and others)

* fix (potentially partially) imports (in model test modules)

* fix (potentially partially) imports (in tokenization test modules)

* fix (potentially partially) imports (in feature extraction test modules)

* fix import utils.test_modeling_tf_core

* fix path ../fixtures/

* fix imports about generation.test_generation_flax_utils

* fix more imports

* fix fixture path

* fix get_test_dir

* update module_to_test_file

* fix get_tests_dir from wrong transformers.utils

* update config.yml (CircleCI)

* fix style

* remove missing imports

* update new model script

* update check_repo

* update SPECIAL_MODULE_TO_TEST_MAP

* fix style

* add __init__

* update self-scheduled

* fix add_new_model scripts

* check one way to get location back

* python setup.py build install

* fix import in test auto

* update self-scheduled.yml

* update slack notification script

* Add comments about artifact names

* fix for yolos
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* [FlaxBert] Add ForCausalLM

* make style

* fix output attentions

* Add RobertaForCausalLM

* remove comment

* fix fx-to-pt model loading

* remove comment

* add modeling tests

* add enc-dec model tests

* add big_bird

* add electra

* make style

* make repo-consitency

* add to docs

* remove roberta test

* quality

* amend cookiecutter

* fix attention_mask bug in flax bert model tester

* tighten pt-fx thresholds to 1e-5

* add 'copied from' statements

* amend 'copied from' statements

* amend 'copied from' statements

* quality

* [T5 Tokenizer] Model has no fixed position ids - there is no hardcoded max length

* [T5 Tokenizer] Model has no fixed position ids - there is no hardcoded max length

* correct t5 tokenizer

* correct t5 tokenizer

* fix test

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

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

* Make sacremoses optional

* Pickle

* First draft

* Add YolosForObjectDetection

* Make forward pass work

* Add mid position embeddings

* Add interpolation of position encodings

* Add expected values

* Add YOLOS to tests

* Add integration test

* Support tiny model as well

* Support all models in conversion script

* Remove mid_pe_size attribute

* Make more tests pass

* Add model to README and fix config

* Add copied from statements

* Rename base_model_prefix to vit

* Add missing YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP

* Apply suggestions from code review

* Apply more suggestions from code review

* Convert remaining checkpoints

* Improve docstrings

* Add YolosFeatureExtractor

* Add feature extractor to docs

* Add corresponding tests

* Fix style

* Fix docs

* Apply suggestion from code review

* Fix bad rebase

* Fix some more bad rebase

* Fix missing character

* Improve docs and variable names
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

* [FlaxSpeechEncoderDecoder] Fix bug in `decoder_module`

* [FlaxEncoderDecoder] Fix bug in `decoder_module`

* Add meta proxy

* Uses meta data to trace data dependent control-flow

* Remove commented class

* Handles torch creating functions

* Added type annotation to fix tracing

* Tracing works for everything but T5 and GPT-J

* Almost all previously supported models pass

* All architectures can be traced except T5

* Intermediate commit to have a trace of the comparison operators for HFProxy

* Everything works, except loss computation

* Everything works

* Removed unused import

* Overriden methods do not use underlying ops (linear and torch.matmul), and model attributes are copied to the traced version

* Fix torch_matmul_override

* Change attributes reference to deepcopy

* Remove breakpoint and add torch_index_override

* Small fix

* Fix typo

* Replace asserts by explicit exceptions