GitLab

* refactor GPT Config to allow dyn. properties

* make attribute_map a class attribute

* remove old code

* update unit test to test config: Add test for common properties setter

* update unit test to test config: Add test for common properties passed as parameters to __init__

* update to black code format

* Allow that setters are not defined for certain config classes

* update config classes to implement attribute_map

* bugfix lxmert config - id2labels was not defined when num_labels was set

* update broken configs - add attribute_maps

* update bart config

* update black codestyle

* update documentation on common config attributes

* update GPTJ config to new attribute map

* update docs on common attributes

* gptj config: add max_position_embeddings

* gptj config: format with black

* update speech to text 2 config

* format doc file to max_len 119

* update config template

* [docs] Update perplexity.rst to use negative log likelihood

Model `forward` returns the negative log likelihood. The document correctly defines and calculates perplexity, but the description and variable names are inconsistent, which might cause confusion.

* [docs] restyle perplexity.rst

* Remove disclaimer

* First draft

* Fix rebase

* Improve docs some more

* Add inference section

* Improve example scripts section

* Improve code examples of modeling files

* Add docs regarding task prefix

* Address @craffel's comments

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

* Add suggestions from code review

* Apply @sgugger's suggestions

* Fix Flax code examples

* Fix index.rst
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* fix_torch_device_generate_test

* remove @

* up

* correct some bugs

* correct model

* finish speech2text extension

* up

* up

* up

* up

* Update utils/custom_init_isort.py

* up

* up

* update with tokenizer

* correct old tok

* correct old tok

* fix bug

* up

* up

* add more tests

* up

* fix docs

* up

* fix some more tests

* add better config

* correct some more things
"

* fix tests

* improve docs

* Apply suggestions from code review

* Apply suggestions from code review

* final fixes

* finalize

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

* apply suggestions Lysandre and Sylvain

* apply nicos suggestions

* upload everything

* finish
Co-authored-by: Patrick von Platen <patrick@huggingface.co>
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* Add the audio classification pipeline

* Remove autoconfig exception

* Mark ffmpeg test as slow

* Rearrange pipeline tests

* Add small test

* Replace asserts with ValueError

* Test GPTJ implementation

* Fixed conflicts

* Update __init__.py

* Update __init__.py

* change GPT_J to GPTJ

* fix missing imports and typos

* use einops for now
(need to change to torch ops later)

* Use torch ops instead of einsum

* remove einops deps

* Update configuration_auto.py

* Added GPT J

* Update gptj.rst

* Update __init__.py

* Update test_modeling_gptj.py

* Added GPT J

* Changed configs to match GPT2 instead of GPT Neo

* Removed non-existent sequence model

* Update configuration_auto.py

* Update configuration_auto.py

* Update configuration_auto.py

* Update modeling_gptj.py

* Update modeling_gptj.py

* Progress on updating configs to agree with GPT2

* Update modeling_gptj.py

* num_layers -> n_layer

* layer_norm_eps -> layer_norm_epsilon

* attention_layers -> num_hidden_layers

* Update modeling_gptj.py

* attention_pdrop -> attn_pdrop

* hidden_act -> activation_function

* Update configuration_gptj.py

* Update configuration_gptj.py

* Update configuration_gptj.py

* Update configuration_gptj.py

* Update configuration_gptj.py

* Update modeling_gptj.py

* Update modeling_gptj.py

* Update modeling_gptj.py

* Update modeling_gptj.py

* Update modeling_gptj.py

* Update modeling_gptj.py

* fix layernorm and lm_head size
delete attn_type

* Update docs/source/model_doc/gptj.rst
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* removed claim that GPT J uses local attention

* Removed GPTJForSequenceClassification

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

* Removed unsupported boilerplate

* Update tests/test_modeling_gptj.py
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* Update src/transformers/models/gptj/modeling_gptj.py
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* Update src/transformers/models/gptj/modeling_gptj.py
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* Update src/transformers/models/gptj/modeling_gptj.py
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* Update tests/test_modeling_gptj.py
Co-authored-by: Eric Hallahan <eric@hallahans.name>

* Update tests/test_modeling_gptj.py
Co-authored-by: Eric Hallahan <eric@hallahans.name>

* Update tests/test_modeling_gptj.py
Co-authored-by: Eric Hallahan <eric@hallahans.name>

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

* Update __init__.py

* Update configuration_gptj.py

* Update modeling_gptj.py

* Corrected indentation

* Remove stray backslash

* Delete .DS_Store

* Delete .DS_Store

* Delete .DS_Store

* Delete .DS_Store

* Delete .DS_Store

* Update docs to match

* Remove tf loading

* Remove config.jax

* Remove stray `else:` statement

* Remove references to `load_tf_weights_in_gptj`

* Adapt tests to match output from GPT-J 6B

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

* Default `activation_function` to `gelu_new`

- Specify the approximate formulation of GELU to ensure parity with the default setting of `jax.nn.gelu()`

* Fix part of the config documentation

* Revert "Update configuration_auto.py"

This reverts commit e9860e9c043b6ebf57a0e705044e9ec9ba2263bb.

* Revert "Update configuration_auto.py"

This reverts commit cfaaae4c4dc70f1fbe9abd60fc8bd0b863b8c011.

* Revert "Update configuration_auto.py"

This reverts commit 687788954fd0cfbc567fa1202d56a4ff9271944f.

* Revert "Update configuration_auto.py"

This reverts commit 194d024ea87d4fcef0dcb08e57f52c47511a9fc6.

* Hyphenate GPT-J

* Undid sorting of the models alphabetically

* Reverting previous commit

* fix style and quality issues

* Update docs/source/model_doc/gptj.rst
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* Update src/transformers/__init__.py
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* Update tests/test_modeling_gptj.py
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* Update src/transformers/models/gptj/modeling_gptj.py
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* Update src/transformers/__init__.py
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* Update src/transformers/models/gptj/modeling_gptj.py
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* Update src/transformers/models/gptj/modeling_gptj.py
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* Update src/transformers/models/gptj/configuration_gptj.py
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* Update src/transformers/models/gptj/configuration_gptj.py
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* Update src/transformers/models/gptj/configuration_gptj.py
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* Update src/transformers/models/gptj/modeling_gptj.py
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* Update src/transformers/models/gptj/modeling_gptj.py
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* Update src/transformers/models/gptj/modeling_gptj.py
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* Update src/transformers/models/gptj/modeling_gptj.py
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* Update src/transformers/models/gptj/modeling_gptj.py
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* Replaced GPTJ-specific code with generic code

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

* Made the code always use rotary positional encodings

* Update index.rst

* Fix documentation

* Combine attention classes

- Condense all attention operations into `GPTJAttention`
- Replicate GPT-2 and improve code clarity by renaming `GPTJAttention.attn_pdrop` and `GPTJAttention.resid_pdrop` to `GPTJAttention.attn_dropout` and `GPTJAttention.resid_dropout`

* Removed `config.rotary_dim` from tests

* Update test_modeling_gptj.py

* Update test_modeling_gptj.py

* Fix formatting

* Removed depreciated argument `layer_id` to `GPTJAttention`

* Update modeling_gptj.py

* Update modeling_gptj.py

* Fix code quality

* Restore model functionality

* Save `lm_head.weight` in checkpoints

* Fix crashes when loading with reduced precision

* refactor self._attn(...)` and rename layer weights"

* make sure logits are in fp32 for sampling

* improve docs

* Add `GPTJForCausalLM` to `TextGenerationPipeline` whitelist

* Added GPT-J to the README

* Fix doc/readme consistency

* Add rough parallelization support

- Remove unused imports and variables
- Clean up docstrings
- Port experimental parallelization code from GPT-2 into GPT-J

* Clean up loose ends

* Fix index.rst
Co-authored-by: kurumuz <kurumuz1@gmail.com>
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Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Adding a TF variant of the DataCollatorForTokenClassification to get feedback

* Added a Numpy variant and a post_init check to fail early if a missing import is found

* Fixed call to Numpy variant

* Added a couple more of the collators

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

* Fixes, style pass, finished DataCollatorForSeqToSeq

* Added all the LanguageModeling DataCollators, except SOP and PermutationLanguageModeling

* Adding DataCollatorForPermutationLanguageModeling

* Style pass

* Add missing `__call__` for PLM

* Remove `post_init` checks for frameworks because the imports inside them were making us fail code quality checks

* Remove unused imports

* First attempt at some TF tests

* A second attempt to make any of those tests actually work

* TF tests, round three

* TF tests, round four

* TF tests, round five

* TF tests, all enabled!

* Style pass

* Merging tests into `test_data_collator.py`

* Merging tests into `test_data_collator.py`

* Fixing up test imports

* Fixing up test imports

* Trying shuffling the conditionals around

* Commenting out non-functional old tests

* Completed all tests for all three frameworks

* Style pass

* Fixed test typo

* Style pass

* Move standard `__call__` method to mixin

* Rearranged imports for `test_data_collator`

* Fix data collator typo "torch" -> "pt"

* Fixed the most embarrassingly obvious bug

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

* Renaming mixin

* Updating docs
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Dalton Walker <dalton_walker@icloud.com>
Co-authored-by: Andrew Romans <andrew.romans@hotmail.com>

`at` should be `a1`

fix a few implementation links

* Deberta_v2 tf

* added new line at the end of file, make style

* +V2, typo

* remove never executed branch of code

* rm cmnt and fixed typo in url filter

* cleanup according to review comments

* added #Copied from

* Add GPT2ForTokenClassification

* Fix dropout exception for GPT2 NER

* Remove sequence label in test

* Change TokenClassifierOutput to TokenClassifierOutputWithPast

* Fix for black formatter

* Remove dummy

* Update docs for GPT2ForTokenClassification

* Fix check_inits ci fail

* Update dummy_pt_objects after make fix-copies

* Remove TokenClassifierOutputWithPast

* Fix tuple input issue
Co-authored-by: danielsejong55@gmail.com <danielsejong55@gmail.com>

* Fix release utils

* Update docs/source/conf.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* albert flax

* year -> 2021

* docstring updated for flax

* removed head_mask

* removed from_pt

* removed passing attention_mask to embedding layer

* distilbert-flax

* added missing self

* docs fix

* removed tied kernal extra init

* updated docs

* x -> hidden states

* removed head_mask

* removed from_pt, +FLAX

* updated year

* fix: typo spelling grammar

* fix: make fixup

* First commit

* Make style

* Fix dummy objects

* Add Detectron2 config

* Add LayoutLMv2 pooler

* More improvements, add documentation

* More improvements

* Add model tests

* Add clarification regarding image input

* Improve integration test

* Fix bug

* Fix another bug

* Fix another bug

* Fix another bug

* More improvements

* Make more tests pass

* Make more tests pass

* Improve integration test

* Remove gradient checkpointing and add head masking

* Add integration test

* Add LayoutLMv2ForSequenceClassification to the tests

* Add LayoutLMv2ForQuestionAnswering

* More improvements

* More improvements

* Small improvements

* Fix _LazyModule

* Fix fast tokenizer

* Move sync_batch_norm to a separate method

* Replace dummies by requires_backends

* Move calculation of visual bounding boxes to separate method + update README

* Add models to main init

* First draft

* More improvements

* More improvements

* More improvements

* More improvements

* More improvements

* Remove is_split_into_words

* More improvements

* Simply tesseract - no use of pandas anymore

* Add LayoutLMv2Processor

* Update is_pytesseract_available

* Fix bugs

* Improve feature extractor

* Fix bug

* Add print statement

* Add truncation of bounding boxes

* Add tests for LayoutLMv2FeatureExtractor and LayoutLMv2Tokenizer

* Improve tokenizer tests

* Make more tokenizer tests pass

* Make more tests pass, add integration tests

* Finish integration tests

* More improvements

* More improvements - update API of the tokenizer

* More improvements

* Remove support for VQA training

* Remove some files

* Improve feature extractor

* Improve documentation and one more tokenizer test

* Make quality and small docs improvements

* Add batched tests for LayoutLMv2Processor, remove fast tokenizer

* Add truncation of labels

* Apply suggestions from code review

* Improve processor tests

* Fix failing tests and add suggestion from code review

* Fix tokenizer test

* Add detectron2 CI job

* Simplify CI job

* Comment out non-detectron2 jobs and specify number of processes

* Add pip install torchvision

* Add durations to see which tests are slow

* Fix tokenizer test and make model tests smaller

* Frist draft

* Use setattr

* Possible fix

* Proposal with configuration

* First draft of fast tokenizer

* More improvements

* Enable fast tokenizer tests

* Make more tests pass

* Make more tests pass

* More improvements

* Addd padding to fast tokenizer

* Mkae more tests pass

* Make more tests pass

* Make all tests pass for fast tokenizer

* Make fast tokenizer support overflowing boxes and labels

* Add support for overflowing_labels to slow tokenizer

* Add support for fast tokenizer to the processor

* Update processor tests for both slow and fast tokenizers

* Add head models to model mappings

* Make style & quality

* Remove Detectron2 config file

* Add configurable option to label all subwords

* Fix test

* Skip visual segment embeddings in test

* Use ResNet-18 backbone in tests instead of ResNet-101

* Proposal

* Re-enable all jobs on CI

* Fix installation of tesseract

* Fix failing test

* Fix index table

* Add LayoutXLM doc page, first draft of code examples

* Improve documentation a lot

* Update expected boxes for Tesseract 4.0.0 beta

* Use offsets to create labels instead of checking if they start with ##

* Update expected boxes for Tesseract 4.1.1

* Fix conflict

* Make variable names cleaner, add docstring, add link to notebooks

* Revert "Fix conflict"

This reverts commit a9b46ce9afe47ebfcfe7b45e6a121d49e74ef2c5.

* Revert to make integration test pass

* Apply suggestions from @LysandreJik's review

* Address @patrickvonplaten's comments

* Remove fixtures DocVQA in favor of dataset on the hub
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* Add hubert classifier + tests

* Add hubert classifier + tests

* Dummies for all classification tests

* Wav2Vec2 classifier + ER test

* Fix hubert integration tests

* Add hubert IC

* Pass tests for all classification tasks on Hubert

* Pass all tests + copies

* Move models to the SUPERB org

* First commit

* Add interpolation of patch embeddings

* Comment out code

* Fix bug

* Fix another bug

* Fix bug

* Fix another bug

* Remove print statements

* Update conversion script

* Use the official vit implementation

* Add support for converting dino_vits8

* Add DINO to docs of ViT

* Remove assertion

* Add interpolation of position encodings

* Fix bug

* Add align_corners

* Add interpolate_pos_encoding option to forward pass of ViTModel

* Improve interpolate_pos_encoding method

* Add docstring

* make flax gpt2 working with cross attention

* Remove encoder->decoder projection layer

* A draft (incomplete) for FlaxEncoderDecoderModel

* Add the method from_encoder_decoder_pretrained + the docstrings

* Fix the mistakes of using EncoderDecoderModel

* Fix style

* Add FlaxEncoderDecoderModel to the library

* Fix cyclic imports

* Add FlaxEncoderDecoderModel to modeling_flax_auto.py

* Remove question comments

* add tests for FlaxEncoderDecoderModel

* add flax_encoder_decoder to the lists of ignored entries in check_repo.py

* fix missing required positional arguments

* Remove **kwargs when creating FlaxEncoderDecoderModel in from_encoder_decoder_pretrained()

Also fix generation eos/pad tokens issue

* Fix: Use sequences from the generated_output

* Change a check from assert to raise ValueError

* Fix examples and token ids issues

* Fix missing all_cross_attentions when outputting tuple in modeling_gpt2

* Remove the changes in configuration docstrings.

* allow for bert 2 gpt2

* make fix-copies

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

* Change remaining examples to bert2gpt2

* Change the test to Bert2GPT2

* Fix examples

* Fix import

* Fix unpack bug

* Rename to FlaxEncoderDecoderModelTest and change the test to bert2gpt2

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

* Fix: NotImplentedError -> NotImplementedError

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

* up

* finalize
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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
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* splinter template

* initialize splinter classes

* Splinter Tokenizer

* splinter.rst

* tokenization fixes

* Documentation & some minor variable name changes

* bug fix (added back question_token_id to config) + variable names

* Minor bug fixes + variable name changes

* Fix Splinter references after merge with new transformers

* changes after running make style & quality

* Fix documentation unindent

* Fix doc indentation in tokenization_splinter

* Fix also SplinterTokenizerFast

* Add Splinter to index.rst and README

* Fixdouble whitespace from index.rst

* Fixed index.rst with 'make fix-copies'

* Update docs/source/model_doc/splinter.rst
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update docs/source/model_doc/splinter.rst
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update docs/source/model_doc/splinter.rst
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Update docs/source/model_doc/splinter.rst
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* Update src/transformers/models/splinter/__init__.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Added "copied from BERT" comments

* Removing unnexessary code from modeling_splinter

* Update README.md
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* Update src/transformers/models/splinter/configuration_splinter.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Remove references to TF modeling from splinter

* Update src/transformers/models/splinter/modeling_splinter.py
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* Remove unnecessary check

* Update src/transformers/models/splinter/modeling_splinter.py
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* Add differences between Splinter and Bert tokenizers

* Update src/transformers/models/splinter/modeling_splinter.py
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* Update src/transformers/models/splinter/tokenization_splinter_fast.py
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* Remove unnecessary check

* Doc formatting

* Update src/transformers/models/splinter/tokenization_splinter.py
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* Update src/transformers/models/splinter/tokenization_splinter.py
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* bug fix: remove load_tf_weights attribute

* Some minor quality changes

* Update docs/source/model_doc/splinter.rst
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* Update src/transformers/models/splinter/configuration_splinter.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Change FullyConnectedLayer to SplinterFullyConnectedLayer

* Variable naming

* Reove gather_positions function

* Remove ClassificationHead as it's outdated

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

* Remove hardcoded 102 token id

* Minor style change

* Added "tau" organization to all model identifiers & URLS

* Added tau to the tests as well

* Copy-from comments

* Removed all unnecessary classes (e.g. SplinterForMaskedLM)

* Running make fix-copies

* Bug fix: Further removed unnecessary classes

* Add Splinter to AutoTokenization

* Add an integration test for Splinter

* Removed initialize_new_qass from config - It will be done through different checkpoints

* Removed `initialize_new_qass` from documentation as well

* Added new checkpoint names (`tau/splinter-base-qass` and same for large) in the code

* Minor change to test

* SplinterTokenizer now doesn't abstract from BertTokenizer

* SplinterTokenizerFast also dosn't abstract from Bert

* style and quality

* bug fix: import ing torch in tests only if it's available

* Auto mappings

* Changed copyrights in Splinter's files

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

* Fix frameworks table so it's alphabetical

* Update index.rst

* Don't differentiate when sorting between upper and lower case

* Fix VisualBERT docs

* Show example notebooks as lists

* Fix style

* Remove hf_api module and use hugginface_hub

* Style

* Fix to test_fetcher

* Quality

* TFDeberta

moved weights to build and fixed name scope

added missing ,

bug fixes to enable graph mode execution

updated setup.py

fixing typo

fix imports

embedding mask fix

added layer names avoid autmatic incremental names

+XSoftmax

cleanup

added names to layer

disable keras_serializable
Distangled attention output shape hidden_size==None
using symbolic inputs

test for Deberta tf

make style

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

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

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

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

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

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

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

removed tensorflow-probability

removed blank line

* removed tf experimental api
+torch_gather tf implementation from @Rocketknight1

* layername DeBERTa --> deberta

* copyright fix

* added docs for TFDeberta & make style

* layer_name change to fix load from pt model

* layer_name change as pt model

* SequenceClassification layername change,
to same as pt model

* switched to keras built-in LayerNormalization

* added `TFDeberta` prefix most layer classes

* updated to tf.Tensor in the docstring

* Doctests

* Limit to 4 decimals

* Try with separate PT/TF tests

* Remove test for TF

* Ellips the predictions

* Doctest continue on failure
Co-authored-by: Sylvain Gugger <sylvain.gugger@gmail.com>

* Fix doctests for quicktour

* Adapt causal LM exemple

* Remove space

* Fix until summarization

* End of task summary

* Style

* With last changes in quicktour

* Adding HuggingArtists to Community Notebooks

* Adding HuggingArtists to Community Notebooks

* Adding HuggingArtists to Community Notebooks

* docs: add HuggingArtists to community notebooks
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Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Add to ONNX docs

* Add MBART example

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

Updating the import for load_dataset