GitLab

* Start the work for TFViTModel

* Convert to TF code - need to check in the follow up commits

* Clean up model code

* Expose TFViTModel

* make style

* make quality

* Add test

* make style & quality

* Fix some imports

* fix wrong usage - *kwargs => ** kwargs

* Fix Conv2D weight loading (PT->TF) issue

* Add tests for images with different sizes + fix model

* Fix some common tests for TFViTModel

* Use inputs instead of input_ids in test_compile_tf_model

* Add a comment about transpose and Conv2D in convert_tf_weight_name_to_pt_weight_name

* Avoid transpose in TFViT call

* Fix Conv2D issue in load_tf2_weights_in_pytorch_model

* Use tf.keras.layers.Conv2D instead of tf.nn.conv2d

* Using simpler heuristic to detect Conv2D layer

* Change convert_tf_weight_name_to_pt_weight_name to return TransposeType

* Check tf_weight_shape is not None before using it

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

* fix missing comma

* fix input dtype
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Start the work on FlaxVisionEncoderDecoderModel

* Add FlaxVisionEncoderDecoderModel

* Add VisionEncoderDecoderConfig

* Make FlaxVisionEncoderDecoderModel visible to transformers

* Add test

* Fix wrong getattr usage

* Fix tests

* Add FlaxAutoModelForVision2Seq

* Expose FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING

* clean-up

* add integration test

* update expected logits

* update expected scores

* Add ViT2GPT2ModelIntegrationTest + some cleaning

* Add projection layer + PT/Flax equivalence tests

* Fix import

* minor changes

* make test slow again

* Apply suggestions

* Add modeling_flax_vision_encoder_decoder to _ignore_modules in get_model_modules()

* fix copies

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

* split long strings in multiple lines

* decoder_input_ids can't be None

* Add back test_configuration_tie

* Remove attention_mask parameter

* fix test - encoder_last_hidden_state should be encoder_outputs.last_hidden_state instead of the projected vector

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

* Remove more encoder_attention_mask

* remove encoder_attention_mask when calling self.decode (in FlaxVisionEncoderDecoderModule)

* Fix style + pass 1s instead of None as encoder_attention_mask

* fix init_weights

* pass None for encoder_attention_mask

* pass 1s instead of None as encoder_attention_mask

* Fix doc style
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Add LayoutXLMTokenizer and LayoutXLMTokenizerFast

* Fix styling issues

* Fix more styling issues

* Fix more styling issues

* Fix docstring

* Fix unit tests

* Fix docs

* Fix unit tests

* Fix typos and styling issues

* Fix styling issues

* Fix docstring

* Make all tests of test_tokenization_layoutxlm pass

* Add LayoutXLMProcessor

* Make fixup

* Make all LayoutXLMProcessor tests pass

* Minor fixes

* Leave LayoutLMv2Processor tests unchanged

* Fix code quality

* Move LayoutXLM tokenizers and processor to separate folder

* Fix code quality

* Apply suggestions from code review

* Replace assertions by value errors

* Remove methods from fast tokenizer
Co-authored-by: King Yiu Suen <kingyiusuen@gmail.com>

* Add first draft

* Make forward pass work

* Improve conversion script

* Add notebook that checks if it works

* Add BeitForSemanticSegmentation to the tests

* More improvements

* Make BeitForSemanticSegmentation consistent with Segformer

* Small bug fix

* Add BeitForSemanticSegmentation to docs

* Make sure model doesn't output hidden states when the user doesn't want to

* Make it possible to convert the large model

* Fix issue

* Fix conversion script for large model

* Add auxiliary_head option to semantic segmentation model

* Apply suggestions from @sgugger's review

* Apply suggestions from code review

* Fix failing test
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* Add the support for the fast (rust) implementation of BlenbderbotTokenizer

* Fix a converter and a typo in a doc

* Apply the patil-suraj's suggestion

* (Nitpick) Fast tokenization -> Fast Tokenization in doc

* Apply the SaulLu's suggestion

* Apply Narsil's suggestion to fix test pipelines

* Add encoder_no_repeat_ngram_size according to the Narsil's suggestion

* Revert the last (unnecessary) commit

* Override pipeline config for Blenderbot to allow for larger pos. emb.

* make fix-copies

* Tentative enabling of `batch_size` for pipelines.

* Add systematic test for pipeline batching.

* Enabling batch_size on almost all pipelines

- Not `zero-shot` (it's already passing stuff as batched so trickier)
- Not `QA` (preprocess uses squad features, we need to switch to real
tensors at this boundary.

* Adding `min_length_for_response` for conversational.

* Making CTC, speech mappings avaiable regardless of framework.

* Attempt at fixing automatic tests (ffmpeg not enabled for fast tests)

* Removing ffmpeg dependency in tests.

* Small fixes.

* Slight cleanup.

* Adding docs

and adressing comments.

* Quality.

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

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

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

* Improving docs.

* Update docs/source/main_classes/pipelines.rst
Co-authored-by: Philipp Schmid <32632186+philschmid@users.noreply.github.com>

* N -> oberved_batch_size

softmax trick.

* Follow `padding_side`.

* Supporting image pipeline batching (and padding).

* Rename `unbatch` -> `loader_batch`.

* unbatch_size forgot.

* Custom padding for offset mappings.

* Attempt to remove librosa.

* Adding require_audio.

* torchaudio.

* Back to using datasets librosa.

* Adding help to set a pad_token on the tokenizer.

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

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

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

* Quality.
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Philipp Schmid <32632186+philschmid@users.noreply.github.com>

* First draft

* Make style & quality

* Improve conversion script

* Add print statement to see actual slice

* Make absolute tolerance smaller

* Fix image classification models

* Add post_process_semantic method

* Disable padding

* Improve conversion script

* Rename to ForSemanticSegmentation, add integration test, remove post_process methods

* Improve docs

* Fix code quality

* Fix feature extractor tests

* Fix tests for image classification model

* Delete file

* Add is_torch_available to feature extractor

* Improve documentation of feature extractor methods

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

* Apply some more suggestions of code review

* Rebase with master

* Fix rebase issues

* Make sure model only outputs hidden states when the user wants to

* Apply suggestions from code review

* Add pad method

* Support padding of 2d images

* Add print statement

* Add print statement

* Move padding method to SegformerFeatureExtractor

* Fix issue

* Add casting of segmentation maps

* Add test for padding

* Add small note about padding
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* unispeech

* add copy from

* remove hubert copy from

* finish for today

* add unispeech-sat

* adapt more

* up

* up

* up

* up

* add modeling

* add tests

* up

* up

* finish

* up

* Apply suggestions from code review

* up

* up

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

* up

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

* adapt_examples

* up

* up

* up

* up

* add auto models

* finish

* Add the pre-trained BARTpho model

* Add the pre-trained BARTpho model

* Add the pre-trained BARTpho model

* Fix incorrectly sorted and/or formatted imports

* Fix incorrectly sorted and/or formatted style

* Fix check_dummies

* Fix check_dummies

* Fix check_dummies

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

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

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

* Update tests/test_tokenization_bartpho.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

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

* Update tests/test_tokenization_bartpho.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>

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

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

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

* Add the pre-trained BARTpho model

* Add Tips section in doc and details of monolingual_vocab_file

* Fix conflicts

* Add another tip related to monolingual_vocab_file

* Readd dependency_versions_table.py

* Handle failing checks

* Remove test_list.txt

* Remove md5sum.saved

* Revise Readme.md
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Working encoder

* SEW-D and tests

* Further conv fixes

* Automodels and conv inits

* Update integration tests, add docs

* Docs cleanup, resolve todos

* Conf fix

* Fix docs

* Fix tests, apply suggestions

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

* Model conversion and updated no-mask tests

* Remove copy of feature_proj

* Style

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

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

* Move orgs
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Scatter dummies + skip pipeline tests

* Add torch scatter to build docs

* First draft

* Update self-attention of RoBERTa as proposition

* Improve conversion script

* Add TrOCR decoder-only model

* More improvements

* Make forward pass with pretrained weights work

* More improvements

* Some more improvements

* More improvements

* Make conversion work

* Clean up print statements

* Add documentation, processor

* Add test files

* Small improvements

* Some more improvements

* Make fix-copies, improve docs

* Make all vision encoder decoder model tests pass

* Make conversion script support other models

* Update URL for OCR image

* Update conversion script

* Fix style & quality

* Add support for the large-printed model

* Fix some issues

* Add print statement for debugging

* Add print statements for debugging

* Make possible fix for sinusoidal embedding

* Further debugging

* Potential fix v2

* Add more print statements for debugging

* Add more print statements for debugging

* Deubg more

* Comment out print statements

* Make conversion of large printed model possible, address review comments

* Make it possible to convert the stage1 checkpoints

* Clean up code, apply suggestions from code review

* Apply suggestions from code review, use Microsoft models in tests

* Rename encoder_hidden_size to cross_attention_hidden_size

* Improve docs

* Add cross attentions to TFGPT2Model

* Add TFEncoderDecoderModel

* Add TFBaseModelOutputWithPoolingAndCrossAttentions

* Add cross attentions to TFBertModel

* Fix past or past_key_values argument issue

* Fix generation

* Fix save and load

* Add some checks and comments

* Clean the code that deals with past keys/values

* Add kwargs to processing_inputs

* Add serving_output to TFEncoderDecoderModel

* Some cleaning + fix use_cache value issue

* Fix tests + add bert2bert/bert2gpt2 tests

* Fix more tests

* Ignore crossattention.bias when loading GPT2 weights into TFGPT2

* Fix return_dict_in_generate in tf generation

* Fix is_token_logit_eos_token bug in tf generation

* Finalize the tests after fixing some bugs

* Fix another is_token_logit_eos_token bug in tf generation

* Add/Update docs

* Add TFBertEncoderDecoderModelTest

* Clean test script

* Add TFEncoderDecoderModel to the library

* Add cross attentions to TFRobertaModel

* Add TFRobertaEncoderDecoderModelTest

* make style

* Change the way of position_ids computation

* bug fix

* Fix copies in tf_albert

* Remove some copied from and apply some fix-copies

* Remove some copied

* Add cross attentions to some other TF models

* Remove encoder_hidden_states from TFLayoutLMModel.call for now

* Make style

* Fix TFRemBertForCausalLM

* Revert the change to longformer + Remove copies

* Revert the change to albert and convbert + Remove copies

* make quality

* make style

* Add TFRembertEncoderDecoderModelTest

* make quality and fix-copies

* test TFRobertaForCausalLM

* Fixes for failed tests

* Fixes for failed tests

* fix more tests

* Fixes for failed tests

* Fix Auto mapping order

* Fix TFRemBertEncoder return value

* fix tf_rembert

* Check copies are OK

* Fix missing TFBaseModelOutputWithPastAndCrossAttentions is not defined

* Add TFEncoderDecoderModelSaveLoadTests

* fix tf weight loading

* check the change of use_cache

* Revert the change

* Add missing test_for_causal_lm for TFRobertaModelTest

* Try cleaning past

* fix _reorder_cache

* Revert some files to original versions

* Keep as many copies as possible

* Apply suggested changes - Use raise ValueError instead of assert

* Move import to top

* Fix wrong require_torch

* Replace more assert by raise ValueError

* Add test_pt_tf_model_equivalence (the test won't pass for now)

* add test for loading/saving

* finish

* finish

* Remove test_pt_tf_model_equivalence

* Update tf modeling template

* Remove pooling, added in the prev. commit, from MainLayer

* Update tf modeling test template

* Move inputs["use_cache"] = False to modeling_tf_utils.py

* Fix torch.Tensor in the comment

* fix use_cache

* Fix missing use_cache in ElectraConfig

* Add a note to from_pretrained

* Fix style

* Change test_encoder_decoder_save_load_from_encoder_decoder_from_pt

* Fix TFMLP (in TFGPT2) activation issue

* Fix None past_key_values value in serving_output

* Don't call get_encoderdecoder_model in TFEncoderDecoderModelTest.test_configuration_tie until we have a TF checkpoint on Hub

* Apply review suggestions - style for cross_attns in serving_output

* Apply review suggestions - change assert + docstrings

* break the error message to respect the char limit

* deprecate the argument past

* fix docstring style

* Update the encoder-decoder rst file

* fix Unknown interpreted text role "method"

* fix typo
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Implement img seg pipeline

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

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

* Update output shape with individual masks

* Rm dev change

* Remove loops in test
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* update

* add to docs and init

* make fix-copies

* add sigopt hpo to transformers.
Signed-off-by: Ding, Ke <ke.ding@intel.com>

* extend sigopt changes to test code and others..
Signed-off-by: Ding, Ke <ke.ding@intel.com>

* Style.

* fix style for sigopt integration.
Signed-off-by: Ding, Ke <ke.ding@intel.com>

* Add necessary information to run unittests on SigOpt.
Co-authored-by: Morgan Funtowicz <funtowiczmo@gmail.com>

* Add BlenderBot small tokenizer to the init

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

* Style

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

* beit-flax

* updated FLAX_BEIT_MLM_DOCSTRING

* removed bool_masked_pos from classification

* updated Copyright

* code refactoring: x -> embeddings

* updated test: rm from_pt

* Update docs/source/model_doc/beit.rst

* model code dtype updates and
other changes according to review

* relative_position_bias
revert back to pytorch design

* upload

* correct

* correct

* correct

* finish

* up

* up

* up again

* Init FNet

* Update config

* Fix config

* Update model classes

* Update tokenizers to use sentencepiece

* Fix errors in model

* Fix defaults in config

* Remove position embedding type completely

* Fix typo and take only real numbers

* Fix type vocab size in configuration

* Add projection layer to embeddings

* Fix position ids bug in embeddings

* Add minor changes

* Add conversion script and remove CausalLM vestiges

* Fix conversion script

* Fix conversion script

* Remove CausalLM Test

* Update checkpoint names to dummy checkpoints

* Add tokenizer mapping

* Fix modeling file and corresponding tests

* Add tokenization test file

* Add PreTraining model test

* Make style and quality

* Make tokenization base tests work

* Update docs

* Add FastTokenizer tests

* Fix fast tokenizer special tokens

* Fix style and quality

* Remove load_tf_weights vestiges

* Add FNet to  main README

* Fix configuration example indentation

* Comment tokenization slow test

* Fix style

* Add changes from review

* Fix style

* Remove bos and eos tokens from tokenizers

* Add tokenizer slow test, TPU transforms, NSP

* Add scipy check

* Add scipy availabilty check to test

* Fix tokenizer and use correct inputs

* Remove remaining TODOs

* Fix tests

* Fix tests

* Comment Fourier Test

* Uncomment Fourier Test

* Change to google checkpoint

* Add changes from review

* Fix activation function

* Fix model integration test

* Add more integration tests

* Add comparison steps to MLM integration test

* Fix style

* Add masked tokenization fix

* Improve mask tokenization fix

* Fix index docs

* Add changes from review

* Fix issue

* Fix failing import in test

* some more fixes

* correct fast tokenizer

* finalize

* make style

* Remove additional tokenization logic

* Set do_lower_case to False

* Allow keeping accents

* Fix tokenization test

* Fix FNet Tokenizer Fast

* fix tests

* make style

* Add tips to FNet docs
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>

* added initial files

* fixes pipeline

* fixes style and quality

* fixes doc issue and positional encoding

* fixes layer norm and test

* fixes quality issue

* fixes code quality

* removed extra layer norm

* added layer norm back in encoder and decoder

* added more code copy quality checks

* update tests

* Apply suggestions from code review

* fix import

* fix test
Co-authored-by: patil-suraj <surajp815@gmail.com>

* Implement object-detection pipeline

* Define threshold const

* Add `threshold` argument

* Refactor

* Uncomment test inputs

* `rm
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Fix typo
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Fix typo
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Chore better doc
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Rm unnecessary lines
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Chore better naming
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

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

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

* Fix typo

* Add `detr-tiny` for tests

* Add `ObjectDetectionPipeline` to `trnsfrmrs/init`

* Implement new bbox format

* Update detr post_process

* Update `load_img` method obj det pipeline

* make style

* Implement new testing format for obj det pipeln

* Add guard pytorch specific code in pipeline

* Add doc

* Make pipeline_obj_tet tests deterministic

* Revert some changes to `post_process` COCO api

* Chore

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

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

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

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

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

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

* Rm timm requirement

* make fixup

* Add timm requirement to test

* Make fixup

* Guard torch.Tensor

* Chore

* Delete unnecessary comment
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Add conversion of TapasForMaskedLM

* Add copied from statements

* 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>
Co-authored-by: your_github_username <your_github_email>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Add the audio classification pipeline

* Remove autoconfig exception

* Mark ffmpeg test as slow

* Rearrange pipeline tests

* Add small test

* Replace asserts with ValueError

* Add option to add flax

* Add flax template for __init__.py

* Add flax template for .rst

* Copy TF modeling template

* Add a missing line in modeling_tf_... template

* Update first half of modeling_flax_..

* Update encoder flax template

* Copy test_modeling_tf... as test_modeling_flax...

* Replace some TF to Flax in test_modeling_flax_...

* Replace tf to np

some function might not work, like _assert_tensors_equal

* Replace remaining tf to np (might not work)

* Fix cookiecutter

* Add Flax in to_replace_... template

* Update transformers-cli add-new-model

* Save generate_flax in configuration.json

This will be read by transformers-cli

* Fix to_replace_... and cli

* Fix replace cli

* Fix cookiecutter name

* Move docstring earlier to avoid not defined error

* Fix a missing Module

* Add encoder-decoder flax template from bart

* Fix flax test

* Make style

* Fix endif

* Fix replace all "utf-8 -> unp-8"

* Update comment

* Fix flax template (add missing ..._DOCSTRING)

* Use flax_bart imports in template (was t5)

* Fix unp

* Update templates/adding_a_new_model/tests

* Revert "Fix unp"

This reverts commit dc9002a41d902c4f9b07343eab1cb350c8b7fd57.

* Remove one line of copied from to suppress CI error

* Use generate_tensorflow_pytorch_and_flax

* Add a missing part

* fix typo

* fix flax config

* add examples for flax

* small rename

* correct modeling imports

* correct auto loading

* corrects some flax tests

* correct small typo

* correct as type

* finish modif

* correct more templates

* final fixes

* add file testers

* up

* make sure tests match template regex

* correct pytorch

* correct tf

* correct more tf

* correct imports

* minor error

* minor error

* correct init

* more fixes

* correct more flax tests

* correct flax test

* more fixes

* correct docs

* update

* fix
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* 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
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* removed claim that GPT J uses local attention

* Removed GPTJForSequenceClassification

* Update src/transformers/models/gptj/configuration_gptj.py
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* Removed unsupported boilerplate

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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
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* Update tests/test_modeling_gptj.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 __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
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* 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
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* 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
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* 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
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* 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
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* Renaming mixin

* Updating docs
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Co-authored-by: Dalton Walker <dalton_walker@icloud.com>
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