GitLab

* fix docs for decoder_input_ids

* revert the changes for bart and mbart

* finish quicktour

* fix import

* fix print

* explain config default better

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

* update docs to reflect model output object

* run make style`

* removed max_len

* removed max_length from BeamSearchScorer

* correct max length

* finish

* del vim

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

* adding Z-inf

* revamp config process

* up version requirement

* wip

* massive rewrite

* cleanup

* cleanup

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

* consistent json commas

* act on suggestions

* leave this feature for 0.3.16

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

As the error comes from the inconsistency of variable meaning number of gpus in parser and its actual usage in the train.py script, 'gpus' and 'n_gpu' respectively,  the correction makes the example work

* added changes for uniformity

* modified files

* corrected typo

* fixed qa scripts

* fix typos

* fixed predict typo in qa no trainer

* fixed test file

* reverted trainer changes

* reverted trainer changes in custom exmaples

* updated readme

* added changes in deepspeed test

* added changes for predict and eval

* fix invalid class name

* proper ref

* proper ref

* Improve documentation for is_split_into_words argument

* Change description wording

* Pass along seed to DistributedSampler

* Add seed to DistributedLengthGroupedSampler

* Add FP16 support for SageMaker MP

* Add print debugs

* Squeeze

* Remove debug statements

* Add defensive check

* Typo

TF BART models - Add `cross_attentions` to model output and fix cross-attention head masking (#10699)

* Add cross_attn_head_mask to BART

* Fix cross_attentions in TFBart-like models

* This commit enables returning of `cross_attentions`
for TFBart-like models

* It also fixes attention head masking in cross-attenion module

* Update TF model templates

* Fix missing , in TF model templates

* Fix typo: congig -> config

* removes the creation of separate config objects and uses the existing ones instead+overwrite resize_token_embeddings from parent class because it is not working for the EncoderDecoderModel

* rollback to current version of the huggingface master branch

* reworked version that ties the encoder and decoder config of the parent encoderdecoder instance

* overwrite of resize_token_embeddings throws an error now

* review comment suggestion
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* implemented warning in case encoderdecoder is created with differing configs of encoderdecoderconfig and decoderconfig or encoderconfig

* added test to avoid diverging configs of wrapper class and wrapped classes

* Update src/transformers/models/encoder_decoder/modeling_encoder_decoder.py

* make style
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Add head_mask & decoder_head_mask + some corrections

* Fix head masking for N-grams

* Enable test_headmasking for encoder and decod

* Fix one typo regarding in modeling_propgetnet.py

* Enable test_headmasking for ProphetNetStandaloneDecoderModelTest
and ProphetNetStandaloneEncoderModelTest in test_modeling_prophetnet.py

* make style

* Fix cross_head_mask

* Fix attention head mask naming

* `cross_head_mask` -> `cross_attn_head_mask`

* `cross_layer_head_mask` -> `cross_attn_layer_head_mask`

* Still need to merge #10605 to master to pass the tests

documentation linked to the parent class PreTrainedTokenizerFast but it should be the slow tokenizer (#11410)

* enable subword regularization.

* fix tokenizer storage

* fix docstring formatting

* Update src/transformers/models/xlm_roberta/tokenization_xlm_roberta.py
Co-authored-by: Stefan Schweter <stefan@schweter.it>

* fix docstring formatting

* add test for subword regularization tokenizer

* improve comments of test

* add sp_model_kwargs

* reformat docstring to match the style

* add some more documentation

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

* improve docstring

* empty commit to trigger CI

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

* fix docstring formatting for sphinx
Co-authored-by: Stefan Schweter <stefan@schweter.it>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Fix cross-attention head mask for Torch BART models

* Fix head masking for cross-attention module for the following
models: BART, Blenderbot, Blenderbot_small, M2M_100, Marian, MBart,
Pegasus

* Enable test_headmasking for M2M_100 model

* Fix cross_head_mask for FSMT, LED and T5

* This commit fixes `head_mask` for cross-attention modules
in the following models: FSMT, LED, T5

* It also contains some smaller changes in doc so that
it is be perfectly clear the shape of `cross_head_mask`
is the same as of `decoder_head_mask`

* Update template

* Fix template for BartForCausalLM

* Fix cross_head_mask for Speech2Text models

* Fix cross_head_mask in templates

* Fix args order in BartForCausalLM template

* Fix doc in BART templates

* Make more explicit naming

* `cross_head_mask` -> `cross_attn_head_mask`

* `cross_layer_head_mask` -> `cross_attn_layer_head_mask`

* Fix doc

* make style quality

* Fix speech2text docstring

When passing `inputs_embeds` and not `input_ids=None` the generation function fails because `input_ids` is created but the function but it should not.

* Initial support for upload to hub

* push -> upload

* Fixes + examples

* Fix torchhub test

* Torchhub test I hate you

* push_model_to_hub -> push_to_hub

* Apply mixin to other pretrained models

* Remove ABC inheritance

* Add tests

* Typo

* Run tests

* Install git-lfs

* Change approach

* Add push_to_hub to all

* Staging test suite

* Typo

* Maybe like this?

* More deps

* Cache

* Adapt name

* Quality

* MOAR tests

* Put it in testing_utils

* Docs + torchhub last hope

* Styling

* Wrong method

* Typos

* Update src/transformers/file_utils.py
Co-authored-by: Julien Chaumond <julien@huggingface.co>

* Address review comments

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

* Fixed trainer total_flos relaoding in distributed mode

* logging flos at the end of training