GitLab

`compute_objectie` => `compute_objective`

* Fix TFTrainer prediction output

* Update trainer_tf.py

* Fix TFTrainer prediction output

* Fix evaluation_loss update in TFTrainer

* Fix TFTrainer prediction output

* Fixes to run_seq2seq and instructions

* Add more defaults for summarization

* Fix saved model tests + fix a graph issue in longformer

* Apply style

* Fix memory regression in Seq2Seq example

* Fix test and properly deal with -100

* Easier condition with device safety

* Patch for MBartTokenzierFast

* Fix Seq2Seq models for serving

* Apply style

* Fix lonfgormer

* Fix mBart/Pegasus/Blenderbot

* Apply style

* Add a main intermediate layer

* Apply style

* Remove import

* Apply tf.function to Longformer

* Fix utils check_copy

* Update S2S template

* Fix BART + Blenderbot

* Fix BlenderbotSmall

* Fix BlenderbotSmall

* Fix BlenderbotSmall

* Fix MBart

* Fix Marian

* Fix Pegasus + template

* Apply style

* Fix common attributes test

* Forgot to fix the LED test

* Apply Patrick's comment on LED Decoder

* Changing model default for TableQuestionAnsweringPipeline.

- Discussion: https://discuss.huggingface.co/t/table-question-answering-is-not-an-available-task-under-pipeline/3284/6

* Updating slow tests that were out of sync.

* Fix Gelu precision

* Fix gelu_fast

* Naming

* Fix usage and apply style

* add TF gelu approximate version

* add TF gelu approximate version

* add TF gelu approximate version

* Apply style

* Fix albert

* Remove the usage of the Activation layer

* fix head mask in model_parallel

* pass correct head mask

* Moved ProphetNetForCausalLM's parent initialization after config update

* Added unit tests for generation for ProphetNetForCausalLM

* fix typo
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* no --deepspeed and --sharded_ddp together

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

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

* fix: Makes small typo corrections & standardises glossary

* feat: Adds introduction & links to transformer flashcards

* feat: Adds attribution & adjustments requested in #8949

* feat: Adds flashcards to community.md

* refactor: Removes flashcards from glossary

* Fix WAND_DISABLED test

* Remove duplicate import

* Make a test that actually works...

* Fix style

* Fix Trainer and Args to mention AdamW, not Adam.

* Update the docs for Training Arguments.

* Change arguments adamw_* to adam_*

* Fixed links to AdamW in TrainerArguments docs

* Fix line length in Training Args docs.

* Add DebertaForMaskedLM, DebertaForTokenClassification, DebertaForQuestionAnswering

* Add docs and fix quality

* Fix Deberta not having pooler

* Update run_mlm.py

* add t5 model to transformers-cli convert

* update rum_mlm.py same as master

* update converting model docs

* update converting model docs

* Update convert.py

* Trigger notification

* update import sorted

* fix typo t5

* Create new embeddings + add to BERT

* Add Albert

* Add DistilBert

* Add Albert + Electra + Funnel

* Add Longformer + Lxmert

* Add last models

* Apply style

* Update the template

* Remove unused imports

* Rename attribute

* Import embeddings in their own model file

* Replace word_embeddings per weight

* fix naming

* Fix Albert

* Fix Albert

* Fix Longformer

* Fix Lxmert Mobilebert and MPNet

* Fix copy

* Fix template

* Update the get weights function

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

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

* address Sylvain's comments
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Fix label datatype

* Apply style

* Restrain tokenizer.model_max_length default

* Fix indent

* Fix model templates and use less than 119 chars

* Missing new line

* Add decoder_head_mask for PyTorch T5 model

* Add decoder_head_mask args into T5Model and T5ForConditionalGeneration

* Slightly change the order of input args to be in accordance
with the convention from BART-based models introduced within the PR #9569.

* Make style for modeling_t5.py

* Add decoder_head_mask for TF T5 models

* Separate head_mask and decoder_head_mask args in TF T5 models

* Slightly change the order of input args to follow convention
of BART-based models updated in PR #9569

* Update test_forward_signature tests/test_modeling_tf_common.py
w.r.t. the changed order of input args

* Add FutureWarnings for T5 and TFT5 models

* Add FutureWarnings for T5 and TFT5 models warning a user that
input argument `head_mask` was split into two arguments -
`head_mask` and `decoder_head_mask`

* Add default behaviour - `decoder_head_mask` is set to copy
`head_mask`

* Fix T5 modeling and FutureWarning

* Make proper usage of head_mask and decoder_head_mask
in cross_attention

* Fix conditions for raising FutureWarning

* Reformat FutureWarning in T5 modeling

* Refactor the warning message