GitLab

add int8 support

* Remove unused decoder_layerdrop

* Update SPECIAL_CASES_TO_ALLOW for MT5Config

* Remove unused position_embedding_init_scale

* Remove unused decoder_max_relative_position

* Use unused decoder_max_relative_position

* Remove unused init_std

* Remove unused forgotten attributes

* Remove unused patch_norm

* Remove unused max_seq_len

* Update SPECIAL_CASES_TO_ALLOW for OneFormerConfig

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

* Added timesformer configuration
Co-authored-by: JuheonChu <chuj@dickinson.edu>

* Create documentation_tests.txt

* Update documentation_tests.txt
Co-authored-by: JuheonChu <chuj@dickinson.edu>

* Delete documentation_tests.txt

Updates, Deleting "src/transformers/utils/documentation_tests.txt" file.
Co-authored-by: JuheonChu <chuj@dickinson.edu>

* Create documentation_tests.txt
Co-authored-by: JuheonChu <chuj@dickinson.edu>

* Delete documentation_tests.txt
Co-authored-by: JuheonChu <chuj@dickinson.edu>

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Co-authored-by: JuheonChu <chuj@dickinson.edu>

* Replace input_values_prrocessing with unpack_inputs

* Skip test failing with OOM

* Update tests

* improving tests section

* documenting other  env variables

* [deepspeed] deal with models w/o config.hidden_size

* typo

* typo

Byebye Blip-2 doctest
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* add: task guide on image cpationing.

* Empty commit to trigger CI

* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* address additional comments from the PR.

* fix: wording.

* Update docs/source/en/tasks/image_captioning.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

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Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

[from_pretrained] extend `torch_dtype="auto"` to look up `config.torch_dtype` first, expand docs (#21524)

* [from_pretrained] expand on torch_dtype entry

* fold 4 into 1

* style

* support torch_dtype='config' plus tests

* style

* oops

* fold config into auto, fix bug

* fix check

* better log

* better log

* clean up

improving flax tests

Update run_mae.py

* [Variant] Make sure variant files are not incorrectly deleted

* Apply suggestions from code review

* fix

* fix rsqrt

* fix typo

* Add X-MOD to Readme

* Add documentation for X-MOD

* Implement X-MOD

* Fix formatting of X-MOD docs

* Change signature of X-MOD forward methods to use lang_ids

* Minor changes

* Rebase with main and run make fix-copies

* Make suggested changes to docstrings

* Improve code readability
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Fix code style

* Conversion script: Remove asserts and type annotations

* Remove _TOKENIZER_FOR_DOC

* XMOD -> Xmod

* Update copyright note

* Fix doctests

* Fix docstring

* Add integration test for FillMaskPipeline

* Revert "Add integration test for FillMaskPipeline"

This reverts commit 4381eb3b1d0f5d85785f89caba83928e6efa6d1f.

* Add end-to-end integration test for mask fill

* make style

* Rebase with main and make fix-copies

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Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>

* Fix stuff related to the causal_mask in CodeGen.

1. Line 613, `_keys_to_ignore_on_load_missing  =  [r"h\.\d+\.attn\.masked_bias", r"h\.\d+\.attn\.bias"]` => `_keys_to_ignore_on_load_missing  =  [r"h\.\d+\.attn\.causal_mask"]` to load correctly from CodeGen checkpoint without `causal_mask`.
2. Line 152, `causal_mask = self.causal_mask[:, :, key_length - query_length : key_length, :key_length]
` => `causal_mask = self.causal_mask[:, :, key_length - query_length : key_length, :key_length].bool()
` to alleviate potential user warning saying like `UserWarning: where received a uint8 condition tensor. This behavior is deprecated and will be removed in a future version of PyTorch. Use a boolean condition instead.`.

* Revert the .bool()

Revert the .bool() and leave it to the future PR.

* Remove CLI spams with Whisper FeatureExtractor

Whisper feature extractor representation includes the MEL filters, a list of list that is represented as ~16,000 lines. This needlessly spams the command line. I added a `__repr__` method that replaces this list with a string "<array of shape (80, 201)>"

* Remove mel_filters from to_dict output  

Credits to @ArthurZucker

* remove unused import

* update feature extraction tests for the changes in to_dict

* adding note concerning use_node_local_storage

* overriding checkpoint.use_node_local_storage if save_on_each_node == True

* add more content

* add more content

* improve

* style

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

add with torch.no_grad() to Camembert integration test
Co-authored-by: Bibi <Bibi@katies-mac.local>

* v1 fix

* adapt from suggestions

* make style

* fix tests

* add gpu tests

* update docs

* fix other tests

* Apply suggestions from code review
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* better fix

* make fixup

* better example

* revert changes

* proposal

* more elegant solution

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

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Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* added with torch.no_grad() to the integration tests and applied make style

* added with torch.no_grad() to xlm roberta forward pass

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Co-authored-by: Bibi <Bibi@katies-mac.local>

* Enforce single model initialization

* Add OneFormer example for problem 3

* Do it the Stas way

* Actually rename the uses...

* Rewrite test

* Try to change the test this way

* Fix all init slow/fast tests

* Break connection

* Fix more tests

* Fix test for initialization

* Remove custom test

* Quality

* Fix last failing tests

* The end?

* Fix inclusion of non py files in package

* No need for the **

* First draft

* More improvements

* More improvements

* Improve conversion script

* Convert all weights

* Make forward pass work

* Make logits match

* More improvements

* More improvements

* More improvements

* Use get_input_embeddings

* Improve some more

* Improve model tests

* Improve model tests

* More improvements

* Fix processor

* Update files

* Update prepare_inputs_for_generation

* More improvements

* Fix copies

* More fixes

* Make fixup

* More improvements

* Add support for seq2seq language model

* More improvements

* Fix test

* More improvements

* Improve conversion script

* Remove some todo's

* Fix README's

* Improve conversion script

* Fix generation

* Fix style and remove Blip2Model

* Fix model outputs

* More improvements

* Set eos_token_id in config

* Fix quality

* Small improvements

* Add processor tests

* More improvements

* Apply suggestions

* Apply suggestions

* Add integration test

* Update image URL

* Add integration test

* Fix model_type

* Update style

* Improve docs

* Add doc tests

* Fix copies

* Remove tests which are passing

* Improve some more

* Add tests for seq2seq language models

* Minor fix

* Convert more checkpoints

* finalize CI

* Fix blip and blip2 processors

* add `accelerate` support for `blip2`

* clean up

* make style

* Update conversion script

* Update conversion script some more

* Update organization

* revert toc file

* add blip-2 to toc file

* Some more improvements

* Fix docstring

* Improve docs

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

Update run_speech_recognition_ctc.py

There should be `# limitations under the License` line at the end of the documentation section.

begone slow tests

* Added clearml pipeline fix for when task is already initialized

* Correctly initialize

fix missing unfinished_sequences

Add `__len__` method to `_LazyAutoMapping`
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* add tests with multiple eos_token_ids

* make math.prod instead of sum

* make fixup

* fix long and also use np.prod since math.prod does not exist <python 3.8

* make fixup

* add prod util

* use prod util instead of np.prod

* make fixup

* previous .long location

* use tensor ops

* remove prod

* remove prod

* update device

* make fixup

* fix none

[tests] report_to none

docs: fix some references in PyTorch text classification readme