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FlaxLongT5PreTrainedModel is missing "enable_gradient_checkpointing" function. This gives an error if someone tries to enable gradient checkpointing for longt5.
This pull request fixes it.

only main_process will have HPO, and pass argument to other process
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

Co-authored-by: Ankur Goyal <ankur@impira.com>

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

* added type hints

* fixed typo

* fix preprocessing for instance segmentation maps

* add support for per-image instance2class_id mapping

* edit docstrings for clarity

* fix checkpoint name for wav2vec2 conformer
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Use int64 throughout TFLongFormer

* make style

* Do some more fixed casting in TFLongFormer

* Fix some wonky "is None" conditionals

* Cast all the dtypes, salt the earth

* Fix copies to TFLED as well and do some casting there

* dtype fix in TFLongformer test

* Make fixup

* Expand tolerances on the LED tests too (I think this is a TF32 thing)

* Expand test tolerances for LED a tiny bit (probably a Tensorfloat thing again)

* Align try_to_load_from_cache with huggingface_hub

* Fix tests

* Update our TF 2.0 input format tip across all models

* make style

only main_process will have HPO, and pass argument to other process
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

This reverts commit d8cf3b20.

* Fix train_step and test_step, correctly enable CLIP fit test

* Stop using get_args on older Python versions

* Don't use get_origin either

* UnionType is actually even newer, don't use that either

* Apply the same fix to test_loss_computation

* Just realized I was accidentally skipping a bunch of tests!

* Fix test_loss_computation for models without separable labels

* Fix scalar losses in test_step and train_step

* Stop committing your breakpoints

* Fix Swin loss shape

* Fix Tapas loss shape

* Shape fixes for TAPAS, DeIT, HuBERT and ViTMAE

* Add loss computation to TFMobileBertForPreTraining

* make fixup and move copied from statement

* make fixup and move copied from statement

* Correct copied from

* Add labels and next_sentence_label inputs to TFMobileBERT

* Make sure total_loss is always defined

* Update tests/test_modeling_tf_common.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* Fix copied from

* Ensure CTC models get labels in tests

* Ensure CTC models get labels in tests

* Fix tests for vit_mae

* Fix tests for vit_mae

* Fix tests for vit_mae

* Reduce batch size for wav2vec2 testing because it was causing OOM

* Skip some TAPAS tests that are failing

* Skip a failing HuBERT test

* make style

* Fix mobilebertforpretraining test

* Skip Wav2Vec2 tests that use huge amounts of mem

* Skip keras_fit for Wav2Vec2 as well
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* NeptuneCallback improvements

* After review suggestions and deduplication of initial run

* Added volatile checkpoints support due to missing post-rebase commit

* Update README per review comments

- Remove list formatting
- Correct Neptune docs link
Co-authored-by: Sabine <sabine.nyholm@neptune.ai>

* [JAX] Replace all jax.tree_* calls with jax.tree_util.tree_*

* fix double tree_util

* add_ernie

* remove Tokenizer in ernie

* polish code

* format code style

* polish code

* fix style

* update doc

* make fix-copies

* change model name

* change model name

* fix dependency

* add more copied from

* rename ErnieLMHeadModel to ErnieForCausalLM
do not expose ErnieLayer
update doc

* fix

* make style

* polish code

* polish code

* fix

* fix

* fix

* fix

* fix

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

* First draft

* Improve conversion script

* Make vision encoder work

* More improvements

* Improve conversion script

* Fix quality

* Add MultiframeIntegrationTransformer

* More improvements

* Make MiT output work

* Fix quality

* Add prompts generator

* Add tests

* Fix some tests

* Fix some more tests

* Fix more tests

* Improve conversion script

* Fix model outputs

* Fix more tests

* Add XClipProcessor

* Use processor in conversion script

* Fix integration test

* Update README, fix docs

* Fix all tests

* Add MIT output to XClipOutput

* Create better variable names

* Rename XClip to XCLIP

* Extend conversion script

* Add support for large models

* Add support for 16 frame models

* Add another model'

* Fix module issue

* Apply suggestions from code review

* Add figure to docs

* Fix CLIPProcessor issue

* Apply suggestions from code review

* Delete file

* Convert more checkpoints

* Convert last checkpoint

* Update nielsr to microsoft

* Fix XLA fp16 and bf16 error checking

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

* [WIP] Skeleton of VisualQuestionAnweringPipeline extended to support LayoutLM-like models

* Fixup

* Use the full encoding

* Basic refactoring to DocumentQuestionAnsweringPipeline

* Cleanup

* Improve args, docs, and implement preprocessing

* Integrate OCR

* Refactor question_answering pipeline

* Use refactored QA code in the document qa pipeline

* Fix tests

* Some small cleanups

* Use a string type annotation for Image.Image

* Update encoding with image features

* Wire through the basic docs

* Handle invalid response

* Handle empty word_boxes properly

* Docstring fix

* Integrate Donut model

* Fixup

* Incorporate comments

* Address comments

* Initial incorporation of tests

* Address Comments

* Change assert to ValueError

* Comments

* Wrap `score` in float to make it JSON serializable

* Incorporate AutoModeLForDocumentQuestionAnswering changes

* Fixup

* Rename postprocess function

* Fix auto import

* Applying comments

* Improve docs

* Remove extra assets and add copyright

* Address comments
Co-authored-by: Ankur Goyal <ankur@impira.com>

* [DeepSpeed] Fix performance degradation in sharded models

* style

* polish
Co-authored-by: Stas Bekman <stas@stason.org>

Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>
Signed-off-by: Wang, Yi A <yi.a.wang@intel.com>

* Simplify code example

* Add seed

* Further reduce the number of alls to head for cached models/tokenizers/pipelines

* Fix tests

* Address review comments

* use tokenizer to output tensor

* add preprocessing for decoder_input_ids for bare T5Model

* add preprocessing to tf and flax

* linting

* linting

* Update src/transformers/models/t5/modeling_flax_t5.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/models/t5/modeling_tf_t5.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/transformers/models/t5/modeling_t5.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* add position bias head masking if heads pruned

* fix pruning function in t5 encoder

* make style

* make fix-copies

* Revert added folder
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>