GitLab

* add cross attn to outputs

* add cross attn to outputs for TFLED

* add undo padding

* remove unused import

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

* Wav2Vec2 models must either throw or deal with add_apater
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

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

* Single-epoch run

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

* 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 <patrick.v.platen@gmail.com>

* Unused import

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

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

* 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 <35901082+sgugger@users.noreply.github.com>

* 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 <35901082+sgugger@users.noreply.github.com>

* [torch_int_div] Correct true division in generation

* up

* up

This reverts commit 854a0d52.

* [deepspeed docs] DeepSpeed ZeRO Inference

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

* tweak

* deal with black

* extra cleanup, better comments
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Standardize instance segmentation models outputs

* Rename output

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

* Add legacy argument to the config and model forward

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

* Copy fix in Segformer
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* fix

* fix test

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

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

* Remove return_loss from Flax models

* fix more

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

* Add preprocess_logits_for_metrics Trainer param

* Compute accuracy in LM examples

* Improve comments

* [deepspeed] fix a bug in a test

* consistency

* Add general docstrings

* Remove legacy docstrings

* Add BEiT

* Add DEiT

* Add SegFormer

* Fix beit output class

* Fix missing return_dict

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

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

* Correct eos_token_id set in generate

* Set eos_token_id in test

* Correct eos_token_id set in generate

* Set eos_token_id in test

* change truncation_side in init of `PreTrainedTokenizerBase`
Co-authored-by: LSinev <LSinev@users.noreply.github.com>

* add test

* Revert "replace assert with exception for `padding_side` arg in `PreTrainedTokenizerBase` `__init__`"

This reverts commit 7a98b87962d2635c7e4d4f00db3948b694624843.

* fix kwargs

* Revert "fix kwargs"

This reverts commit 67b0a5270e8cf1dbf70e6b0232e94c0452b6946f.

* Update tests/test_tokenization_common.py
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* delete truncation_side variable

* reorganize test

* format

* complete doc

* Revert "Revert "replace assert with exception for `padding_side` arg in `PreTrainedTokenizerBase` `__init__`""

This reverts commit d5a10a7e2680539e5d9e98ae5d896c893d224b80.

* fix typo

* fix typos to render documentation

* Revert "Revert "Revert "replace assert with exception for `padding_side` arg in `PreTrainedTokenizerBase` `__init__`"""

This reverts commit 16cf58811943a08f43409a7c83eaa330686591d0.

* format
Co-authored-by: LSinev <LSinev@users.noreply.github.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* Playing

* Properly set labels in model config for token classification example

* Port to run_ner_no_trainer

* Quality

# Add support for W&B hyperparameter sweep
This PR:
* allows using wandb for running hyperparameter search.
* The runs are visualized on W&B sweeps dashboard
* This supports runnning sweeps on parallel devices, all reporting to the same central dashboard.

### Usage
**To run new a hyperparameter search:**
```
trainer.hyperparameter_search(
    backend="wandb", 
    project="transformers_sweep", # name of the project
    n_trials=5,
    metric="eval/loss", # metric to be optimized, default 'eval/loss'. A warning is raised if the passed metric is not found
)
```
This outputs a sweep id. Eg. `my_project/sweep_id`

**To run sweeps on parallel devices:**
Just pass sweep id which you want to run parallel
```
trainer.hyperparameter_search(
    backend="wandb", 
    sweep_id = "my_project/sweep_id"
)
```

* fix error posted in issue #15448
Signed-off-by: bugface <alexgre@ufl.edu>

* clean up - remove commented line
Signed-off-by: bugface <alexgre@ufl.edu>

* Allow dynamic modules to use relative imports

* Work for configs

* Fix last merge conflict

* Save code of registered custom objects

* Map strings to strings

* Fix test

* Add tokenizer

* Rework tests

* Tests

* Ignore fixtures py files for tests

* Tokenizer test + fix collection

* With full path

* Rework integration

* Fix typo

* Remove changes in conftest

* Test for tokenizers

* Add documentation

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

* Add file structure and file content

* Add more doc

* Style

* Update docs/source/custom_models.mdx
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Address review comments
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Adding support for `microphone` streaming within pipeline.

- Uses `ffmpeg` to get microphone data.
- Makes sure alignment is made to `size_of_sample`.
- Works by sending `{"raw": ..data.., "stride": (n, left, right),
"partial": bool}`
directly to the pipeline enabling to stream partial results and still
get inference.
- Let's `partial` information flow through the pipeline to enable caller
  to get it back and choose to display text or not.

- The striding reconstitution is bound to have errors since CTC does not
keep previous state. Currently most of the errors are we don't know if
there's a space or not between two chunks.
Since we have some left striding info, we could use that during decoding
to choose what to do with those spaces and even extra letters maybe (if
the stride is long enough, it's bound to cover at least a few symbols)

Fixing tests.

Protecting with `require_torch`.

`raw_ctc` support for nicer demo.

Post rebase fixes.

Revamp to split raw_mic_data from it's live chunking.

- Requires a refactor to make everything a bit cleaner.

Automatic resampling.

Small fix.

Small fix.

* Post rebase fix (need to let super handle more logic, reorder args.)

* Update docstrings

* Docstring format.

* Remove print.

* Prevent flow of `input_values`.

* Fixing `stride` too.

* Fixing the PR by removing `raw_ctc`.

* Better docstrings.

* Fixing init.

* Update src/transformers/pipelines/audio_utils.py
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* Update tests/test_pipelines_automatic_speech_recognition.py
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* Quality.
Co-authored-by: Anton Lozhkov <aglozhkov@gmail.com>

* Add torchvision's resize

* Rename torch_resize to default_to_square

* Apply suggestions from code review

* Add support for default_to_square and tuple of length 1

* first draft of pipeline, autoclass, preprocess tutorials

* apply review feedback

* 🖍 apply feedback from patrick/niels

* 📝add output image to preprocessed image

* 🖍 apply feedback from patrick

* add fine-tune tutorial

* make edits, fix style

* 📝 make edits

* 🖍 fix code format links to external libraries

* 🔄revert code formatting

* 🖍 use DefaultDataCollator instead of DataCollatorWithPadding

* Harder check for IndexErrors in QA scripts

* Make test stronger

* refactor bart tokenizers

* doc

* replace assert with ValueError

* use mean instead of elementwise_mean

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

fix the `tokenizer_config.json` file for the slow tokenizer when a fast version is available (#15319)

* add new test

* update test

* remove `tokenizer_file` from `additional_files_names` in `tokenization_utils_base.py`

* add `tokenizer_file` for the fast only tokenizer

* change global variables layoutxml

* remove `"tokenizer_file"` from DPR tokenizer's Global variables

* remove `tokenizer_file` from herbert slow tokenizer init

* `"tokenizer_file"` from LED tokenizer's Global variables

* remove `tokenizer_file` from mbart slow tokenizer init

* remove `tokenizer_file` from slow tokenizer template

* adapt to versioning

* adapt the `test_tokenizer_mismatch_warning` test

* clean test

* clarify `VOCAB_FILES_NAMES` in tokenization_utils_fast.py

* Revert "remove `tokenizer_file` from mbart slow tokenizer init"

This reverts commit 0dbb723fa9c7599d4640fe30b3647a74eb4a64e1.

* Revert "`"tokenizer_file"` from LED tokenizer's Global variables"

This reverts commit 5a3f879bdd651233f3d74a3d1146c34cde82b0c2.

* Revert "remove `tokenizer_file` from herbert slow tokenizer init"

This reverts commit f5e10007b7b0ec5345e015b9de7ffec72c5407fd.

* Revert "remove `"tokenizer_file"` from DPR tokenizer's Global variables"

This reverts commit da0895330bedfafc81ae3073470a9348c669f032.

* set `tokenizer_file` in super `__init__` of mbart