GitLab

* redo sans examples

* style

* [doc] consistent True/False/None default format

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

* New doc styler

* Fix issue with args at the start

* Code sample fixes

* Style code examples in MDX

* Fix more patterns

* Typo

* Typo

* More patterns

* Do without black for now

* Get more info in error

* Docstring style

* Re-enable check

* Quality

* Fix add_end_docstring decorator

* Fix docstring

* Fix duplicate call to save_checkpoint when using deepspeed / stage3_gather_fp16_weights_on_model_save

* Revert "Fix duplicate call to save_checkpoint when using deepspeed / stage3_gather_fp16_weights_on_model_save"

This reverts commit 6a3dec0397723a8417351dc38fdebf14ab17756c.

* Delete correct duplicate invocation of deepspeed save_checkpoint

* Add ElectraForCausalLM and cover some basic tests & need to fix a few tests

* Fix bugs

* make style

* make fix-copies

* Update doc

* Change docstring to markdown format

* Remove redundant update_keys_to_ignore

* Pipeline chunks.

* Batching for Chunking pipelines ?

* Batching for `question-answering` and `zero-shot-cls`.

* Fixing for FNet.

* Making ASR a chunk pipeline.

* Chunking ASR API.

* doc style.

* Fixing ASR test.

* Fixing QA eror (p_mask, padding is 1, not 0).

* Enable both vad and simple chunking.

* Max length for vad.

* remove inference mode, crashing on s2t.

* Revert ChunkPipeline for ASRpipeline.

Too many knobs for simple integration within the pipeline, better stick
to external convenience functions instead, more control to be had,
simpler pipeline and also easier to replace with other things later.

* Drop necessity for PT for these.

* Enabling generators.

* Add mic + cleanup.

* Typo.

* Typo2.

* Remove ASR work, it does not belong in this PR anymore.

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

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

* Adding many comments.

* Doc quality.

* `hidden_states` handling.

* Adding doc.

* Bad rebase.

* Autofixing docs.

* Fixing CRITICAL bug in the new Zerocls pipeline.
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

As `jax` cuda requires special instructions to be installed correctly add a link to jax installation instructions. 

Note: Flax install page only covers cpu jax installation info.

* Better logic for getting tokenizer config in AutoTokenizer

* Remove needless import

* Remove debug statement

* Address review comments

* Fix failing GPU trainer tests

* Remove print statements

* up

* save

* correct

* up

* correct more

* up

* up

* up

* up

* up

* correct

* fix tf

* fix

* remove tokenizer

found a few oddities:

1. https://huggingface.co/docs/transformers/main_classes/logging#transformers.utils.logging.enable_explicit_format
has a :: - this PR fixes it

2.  this looks borked too:
https://huggingface.co/docs/transformers/main_classes/logging#transformers.utils.logging.set_verbosity
 has a <

but I'm not sure where this one is coming from

* Start the work for TFCLIPModel

* Convert to TF code (TODO: loss + doc)

* Clean up

* Fix pooled_output for TFCLIPTextTransformer - using tf.gather_nd

* assert -> raise error

* Expose TFCLIPModel

* Deal with dummy_inputs

* Add tests

* Fix all tests. TODO: manual check weight loading + add more comments

* Fix pt tf equivalence test

* fixes

* update TFCLIPVisionEmbeddings's Conv2D

* Fix loss + overwrite test_pt_tf_model_equivalence from common

* Add a comment about the change about MainLayer in test_keras_save_load

* Set return_loss=True in TFCLIPModelTester + make tests pass

* overwrite test_pt_tf_model_equivalence from tf common

* fix base_model_prefix

* Fix examples

* remove unused

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

* apply review suggestions

* change self.pre_layrnorm to self.pre_layernorm

* apply more review suggestions

* return attention probs before dropout (to align with PT)

* fix weight init

* fix

* build doc

* fix missing doc

* fix for test
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Set run_name in MLflowCallback

* Update the docs for `run_name` argument

* First commit to add MarianMT to ONNX

* Now MarianModel.forward() automatically generates decoder_input_ids, like BartModel.forward()

* Adjusted MarianOnnxConfig.inputs and outputs to work with seq2seq-lm feature

* Style fix

* Added support for other features for already supported models

* Partial support for causal and seq2seq models

* Partial support for causal and seq2seq models

* Add default task for MarianMT ONNX

* Remove automatic creation of decoder_input_ids

* Extend inputs and outputs for MarianMT ONNX config

* Add MarianMT to ONNX unit tests

* Refactor

* OnnxSeq2SeqConfigWithPast to support seq2seq models

* Parameterized the onnx tests

* Restored run_mlm.py

* Restored run_mlm.py

* [WIP] BART update

* BART and MBART

* Add past_key_values and fix dummy decoder inputs

Using a sequence length of 1 in generate_dummy_outputs() produces large discrepancies, presumably due to some hidden optimisations.

* Refactor MarianOnnxConfig to remove custom past_key_values logic

* Fix quality

* Revert "Revert "Added support for other features for already supported models (#14358)" (#14679)"

This reverts commit 0f4e39c5.

* is_torch_available test to avoid failing imports

* sorting parameterize parameters to solve ERROR gw0 gw1

* tests fix

* tests fix

* GPT2 with past fix

* Fixed stateful class attribute change that was breaking things when converting multiple models sequentially

* Removed onnx file

* Refactor Marian export to account for base changes

* Fix copies

* Implemented suggestions

* Extend support for causal LM

* Revert "Revert "Added support for other features for already supported models (#14358)" (#14679)"

This reverts commit 0f4e39c5.

* is_torch_available test to avoid failing imports

* sorting parameterize parameters to solve ERROR gw0 gw1

* tests fix

* tests fix

* GPT2 with past fix

* Fixed stateful class attribute change that was breaking things when converting multiple models sequentially

* Removed onnx file

* Implemented suggestions

* Fixed __init__ to resolve conflict with master

* Revert "Revert "Added support for other features for already supported models (#14358)" (#14679)"

This reverts commit 0f4e39c5

.

* is_torch_available test to avoid failing imports

* sorting parameterize parameters to solve ERROR gw0 gw1

* tests fix

* tests fix

* GPT2 with past fix

* Fixed stateful class attribute change that was breaking things when converting multiple models sequentially

* Removed onnx file

* Implemented suggestions

* Fixed __init__ to resolve conflict with master

* Remove commented import

* Remove ONNX model

* Remove redundant class method

* Tidy up imports

* Fix quality

* Refactor dummy input function

* Add copied from statements to Marian config functions

* Remove false copied from comments

* Fix copy from comment
Co-authored-by: Massimiliano Bruni <massimiliano.bruni@hcl.com>
Co-authored-by: Michael Benayoun <mickbenayoun@gmail.com>

* Fix doc examples: ... takes no keyword arguments

* fix copies
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Convert all tutorials and guides

* Convert all remaining rst to mdx

* Track and fix bad links

* Working on splitting out labels

* First working version

* Fixed concatenation of outputs and labels

* val_dataset -> eval_dataset

* Only pass input arrays in tokenizer.model_input_names

* Only pass input arrays in tokenizer.model_input_names

* Only remove unexpected keys when predict_with_generate is True

* Adding proper docstring

* Adding example to docstring

* Add a proper ROUGE metric example

* Add a proper ROUGE metric example

* Add version checking

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

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

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

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

* Remove requirement for tokenizer with predict_with_generate
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Revert "Revert "Added support for other features for already supported models (#14358)" (#14679)"

This reverts commit 0f4e39c5.

* is_torch_available test to avoid failing imports

* sorting parameterize parameters to solve ERROR gw0 gw1

* tests fix

* tests fix

* GPT2 with past fix

* Fixed stateful class attribute change that was breaking things when converting multiple models sequentially

* Removed onnx file

* Implemented suggestions

* Fixed __init__ to resolve conflict with master

* Remove commented import

* Update example

* Remove skip in tests

* Removed unused p2p attention handling

* Updated DeBERTa configuration

* Updated TF DeBERTa attention

* Rolled back accidental comment deletion
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* make MLukeTokenizerTest fast

* make LukeTokenizerTest fast

* add entry to _toctree.yaml

update the arguments `add_prefix_space` and `trim_offsets` in `backend_tokenizer.post_processor` of `RobertaTokenizerFast` (#14752)

* add tests

* change post-processor, pre-tokenizer and decoder (can't update decoder)

* update test (remove decoder which doesn't depend on trim and add_prefix)

* just update the post_processor

* fix change

* `trim_offsets` has no influence on `pre_tokenizer`

* remove a test that need some input from the `tokenizers` lib maintainers

* format

* add new test offsets roberta

* polish comments

* First pass

* Apply suggestions from code review

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

* Remove double returns

* Last fixes

* Quality

* Last fix for Lxmert