GitLab

* finalize convbert

* finalize convbert

* fix

* fix

* fix

* push

* fix

* tf image patches

* fix torch model

* tf tests

* conversion

* everything aligned

* remove print

* tf tests

* fix tf

* make tf tests pass

* everything works

* fix init

* fix

* special treatment for sepconv1d

* style

* 🙏🏽



* add doc and cleanup

* add electra test again

* fix doc

* fix doc again

* fix doc again

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

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

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

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

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

* conv_bert -> convbert

* more fixes from review

* add conversion script

* dont use pretrained embed

* unused config

* suggestions from julien

* some more fixes

* p -> param

* fix copyright

* fix doc

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

* comments from reviews

* fix-copies

* fix style

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

* We most likely don't want special tokens in this output.

* Adding `skip_special_tokens=True` to FillMaskPipeline

- It's backward incompatible.
- It makes for sense for pipelines to remove references to
special_tokens (all of the other pipelines do that).
- Keeping special tokens makes it hard for users to actually remove them
  because all models have different tokens (<s>, <cls>, [CLS], ....)

* Fixing `token_str` in the same vein, and actually fix the tests too !

* Add head_mask/decoder_head_mask for TF BART models

* Add head_mask and decoder_head_mask input arguments for TF BART-based
models as a TF counterpart to the PR #9569

* Add test_headmasking functionality to tests/test_modeling_tf_common.py

* TODO: Add a test to verify that we can get a gradient back for
importance score computation

* Remove redundant #TODO note

Remove redundant #TODO note from tests/test_modeling_tf_common.py

* Fix assertions

* Make style

* Fix ...Model input args and adjust one new test

* Add back head_mask and decoder_head_mask to BART-based ...Model
after the last commit

* Remove head_mask ande decoder_head_mask from input_dict
in TF test_train_pipeline_custom_model as these two have different
shape than other input args (Necessary for passing this test)

* Revert adding global_rng in test_modeling_tf_common.py

* fix ci

* fix ci

* renaming

* fix dup line

* onnx triu workaround

* style

* working this time

* add test

* more efficient version

* 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.

* Moved ProphetNetForCausalLM's parent initialization after config update

* Added unit tests for generation for ProphetNetForCausalLM

* Add DebertaForMaskedLM, DebertaForTokenClassification, DebertaForQuestionAnswering

* Add docs and fix quality

* Fix Deberta not having pooler

* 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>

* 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

* New run_seq2seq script

* Add tests

* Mark as slow

* Update examples/seq2seq/run_seq2seq.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/data/data_collator.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update src/transformers/data/data_collator.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Address review comments
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update past_key_values in gpt2 (#9391)

* Update generation_utils, and rename some items

* Update modeling_gpt2 to avoid an error in gradient_checkpointing

* Remove 'reorder_cache' from util and add variations to XLNet, TransfoXL, GPT-2

* Change the location of '_reorder_cache' in modeling files

* Add '_reorder_cache' in modeling_ctrl

* Fix a bug of my last commit in CTRL

* Add '_reorder_cache' to GPT2DoubleHeadsModel

* Manage 'use_cache' in config of test_modeling_gpt2

* Clean up the doc string

* Update src/transformers/models/gpt2/modeling_gpt2.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Fix the doc string (GPT-2, CTRL)

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

* Fix the attention_mask in DPRReaderTokenizer

* Add an integration test for DPRReader inference

* Run make style

* Add head_mask/decoder_head_mask for BART

This branch implement head_mask and decoder_head_mask
for BART-based models. Full list below:
- BART
- MBart
- Blenderbot
- BlenderbotSmall
- Marian
- Pegasus

Everything is accompanied with updated testing.

* Fix test_headmasking for BART models

* Fix text_headmasking for BART-like models
which has only 2 layers in each modules.
The condition
```
self.assertNotEqual(attentions[1][..., 0, :, :].flatten().sum().item(), 0.0)
```
is, therefore, invalid for encoder-decoder models considering
the `head_mask`
```
head_mask = torch.ones(
    self.model_tester.num_hidden_layers,
    self.model_tester.num_attention_heads,
    device=torch_device,
)
head_mask[0, 0] = 0
head_mask[-1, :-1] = 0
```
specified in the `test_headmasking` test/function.

* Adjust test_modeling_common.py to reflect T5 input args

* Update tests/test_modeling_common.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

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

* make style

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

* Upstream (and rename) sortish sampler

* Use proper sampler

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

* Fix Trainer with a parallel model

* More clean up

* Fix conversational pipeline test

* LayoutLM

* ProphetNet

* BART

* Blenderbot & small

* Marian

* mBART

* Pegasus

* Tapas tokenizer

* BERT2BERT test

* Style

* Example requirements

* TF BERT2BERT test

* Fix data parallelism in Trainer

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

* add model_input_names

* fix test

* Add target contextmanager and rework prepare_seq2seq_batch

* Fix tests, treat BART and Barthez

* Add last tokenizers

* Fix test

* Set src token before calling the superclass

* Remove special behavior for T5

* Remove needless imports

* Remove needless asserts

* Add LayoutLMForSequenceClassification and integration tests

Improve docs

Add LayoutLM notebook to list of community notebooks

* Make style & quality

* Address comments by @sgugger, @patrickvonplaten and @LysandreJik

* Fix rebase with master

* Reformat in one line

* Improve code examples as requested by @patrickvonplaten
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* make templates ready

* make add_new_model_command_ready

* finish tf bart

* prepare tf mbart

* finish tf bart

* add tf mbart

* add marian

* prep pegasus

* add tf pegasus

* push blenderbot tf

* add blenderbot

* add blenderbot small

* clean-up

* make fix copy

* define blend bot tok

* fix

* up

* make style

* add to docs

* add copy statements

* overwrite changes

* improve

* fix docs

* finish

* fix last slow test

* fix missing git conflict line

* fix blenderbot

* up

* fix blenderbot small

* load changes

* finish copied from

* upload fix

* Enable TruncationStrategy override for pipelines

* Update isort.

* Fixing test

* Fixing text_generation pipeline.

* Using same DummyTok as other PR  for easier merge later.

* Some more import guards.

* Remove bogus file.

* Do not pass `generate_kwargs` to `_parse_and_tokenize`.
@patrickvonplaten

* Removed DummyTok.

* Doc quality.

* Remove tolerance + drop_rows_to_fit by default

* remove drop_rows_to_fit

* Start rework resizing

* Rework bias/decoder resizing

* Full resizing rework

* Full resizing rework

* Start to update the models with the new approach

* Finish to update the models

* Update all the tests

* Update the template

* Fix tests

* Fix tests

* Test a new approach

* Refactoring

* Refactoring

* Refactoring

* New rework

* Rework BART

* Rework bert+blenderbot

* Rework CTRL

* Rework Distilbert

* Rework DPR

* Rework Electra

* Rework Flaubert

* Rework Funnel

* Rework GPT2

* Rework Longformer

* Rework Lxmert

* Rework marian+mbart

* Rework mobilebert

* Rework mpnet

* Rework openai

* Rework pegasus

* Rework Roberta

* Rework T5

* Rework xlm+xlnet

* Rework template

* Fix TFT5EncoderOnly + DPRs

* Restore previous methods

* Fix Funnel

* Fix CTRL and TransforXL

* Apply style

* Apply Sylvain's comments

* Restore a test in DPR

* Address the comments

* Fix bug

* Apply style

* remove unused import

* Fix test

* Forgot a method

* missing test

* Trigger CI

* naming update

* Rebase

* Trigger CI

Trying to keep warning tests for now. Should be discarded if it becomes
too hard to maintain.

* Cleaning up conversation tests.

* Adding tests that don't require downloading models + conversation can be

fully created from static state.

* Making tests non flaky (by fixing generation length)

* Bumping isort version.

* Doc cleanup.

* Remove unused test in this PR.

* Torch import guard for TF.

* Missing torch guard.

* Small mistake in doc.

* Actual uses `_history` and `_index` cache.

+ remove dead enumerate
+ improve warning message.

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

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

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

* Adding comments and cleaner code to address history copy.

* Improving pipeline name in tests.

* Change tokenizer to a real one (still created at runtime with no

external dependency)

* Simplify DummyTok, reverse changes on tokenization.

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

* Fix input for np.ndarray"

* add a test

* add a test

* Add a test

* Apply style

* Fix test

* fix tf flakey

* remove test files

* fix common inputs pt flakey led

* fix other tests correspondingly