* Standardize instance segmentation models outputs

* Rename output

* Update src/transformers/modeling_outputs.py

Co-authored-by: NielsRogge <[email protected]>

* Add legacy argument to the config and model forward

* Update src/transformers/models/beit/modeling_beit.py

Co-authored-by: Lysandre Debut <[email protected]>

* Copy fix in Segformer

Co-authored-by: NielsRogge <[email protected]>
Co-authored-by: Lysandre Debut <[email protected]>

* [deepspeed docs] DeepSpeed ZeRO Inference

* Apply suggestions from code review

Co-authored-by: Sylvain Gugger <[email protected]>

* tweak

* deal with black

* extra cleanup, better comments

Co-authored-by: Sylvain Gugger <[email protected]>

* [torch_int_div] Correct true division in generation

* up

* up

* First draft

* Add conversion script

* Improve conversion script

* Improve docs and implement tests

* Define model output class

* Fix tests

* Fix more tests

* Add model to README

* Apply suggestions from code review

Co-authored-by: Sylvain Gugger <[email protected]>

* Apply more suggestions from code review

* Apply suggestions from code review

* Rename dims to hidden_sizes

* Fix equivalence test

* Rename gamma to gamma_parameter

* Clean up conversion script

* Add ConvNextFeatureExtractor

* Add corresponding tests

* Implement feature extractor correctly

* Make implementation cleaner

* Add ConvNextStem class

* Improve design

* Update design to also include encoder

* Fix gamma parameter

* Use sample docstrings

* Finish conversion, add center cropping

* Replace nielsr by facebook, make feature extractor tests smaller

* Fix integration test

Co-authored-by: Sylvain Gugger <[email protected]>

* Unused import

* Make `has_length()` torch-independent to use in callbacks

* Update src/transformers/trainer_utils.py

Co-authored-by: Sylvain Gugger <[email protected]>

Co-authored-by: Sylvain Gugger <[email protected]>

* Single-epoch run

* Apply suggestions from code review

Co-authored-by: Patrick von Platen <[email protected]>

* Infinite dataset

* Trainer fix + distributed benchmark

* Benchmark fix

* unused import

* interleaved splits

* interleaved splits

* has_length util

* Move to research projects

* Leftover Sized checks

* Bump min version

* Unused import

* Revert trainer changes

Co-authored-by: Patrick von Platen <[email protected]>

* Wav2Vec2 models must either throw or deal with add_apater

Co-authored-by: Patrick von Platen <[email protected]>

* Add pre-add_adapter backwards compatibility

* Add pre-add_adapter backwards compatibility

* Fix issue in tests/test_modeling_wav2vec2.py

Co-authored-by: Patrick von Platen <[email protected]>

Co-authored-by: Patrick von Platen <[email protected]>

This reverts commit 48d8aef.

* add cross attn to outputs

* add cross attn to outputs for TFLED

* add undo padding

* remove unused import

* fix style

Co-authored-by: ydshieh <[email protected]>

* fix outputs

* fix for CTC

* fix doc

* make style

Co-authored-by: ydshieh <[email protected]>

Co-authored-by: Patrick von Platen <[email protected]>

Co-authored-by: Patrick von Platen <[email protected]>

Co-authored-by: Patrick von Platen <[email protected]>

* 📝 add config section

* 📝 finish first draft

* 📝 add feature extractor and processor

* 🖍 apply feedback from review

* 📝 minor edits

* last review

* Change the way tracing happens, enabling dynamic axes out of the box

* Update the tests and modeling xlnet

* Add the non recoding of leaf modules to avoid recording more values for the methods to record than what will be seen at tracing time (which would otherwise desynchronize the recorded values and the values that need to be given to the proxies during tracing, causing errors).

* Comments and making tracing work for gpt-j and xlnet

* Refactore things related to num_choices (and batch_size, sequence_length)

* Update fx to work on PyTorch 1.10

* Postpone autowrap_function feature usage for later

* Add copyrights

* Remove unnecessary file

* Fix issue with add_new_model_like

* Apply suggestions

* electra is added to onnx supported model

* add google/electra-base-generator for test onnx module

Co-authored-by: Lewis Tunstall <[email protected]>

* use_cache = False for PT models if labels is passed

* Fix for BigBirdPegasusForConditionalGeneration

* add warning if users specify use_cache=True

* Use logger.warning instead of warnings.warn

Co-authored-by: ydshieh <[email protected]>