GitLab

* [deepspeed] zero inference

* only z3 makes sense for inference

* fix and style

* docs

* rework

* fix test

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

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

* Add AutoProcessor class

* Init and tests

* Add doc

* Fix init

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

* Reverts to tokenizer or feature extractor when available

* Adapt test
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* clean up branch for add-qdqbert-model

* README update for QAT example; update docstrings in modeling_qdqbert.py

* Update qdqbert.rst

* Update README.md

* Update README.md

* calibration data using traning set; QAT example runs in fp32

* re-use BERTtokenizer for qdqbert

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

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

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

* remove qdqbert tokenizer

* Update qdqbert.rst

* update evaluate-hf-trt-qa.py

* update configuration_qdqbert.py

* update modeling_qdqbert.py: add copied statement; replace assert with ValueError

* update copied from statement

* add is_quantization_available; run make fix-copies

* unittest add require_quantization

* add backend dependency to qdqbert model

* update README; update evaluate script; make style

* lint

* docs qdqbert update

* circleci build_doc add pytorch-quantization for qdqbert

* update README

* update example readme with instructions to upgrade TensorRT to 8.2

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

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

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

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

* change quantization to pytorch_quantization for backend requirement

* feed_forward_chunking not supported in QDQBert

* make style

* update model docstrings and comments in testing scripts

* rename example to quantization-qdqbert; rename example scripts from qat to quant

* Update src/transformers/models/qdqbert/modeling_qdqbert.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* rm experimental functions in quant_trainer

* qa cleanup

* make fix-copies for docs index.rst

* fix doctree; use post_init() for qdqbert

* fix early device assignment for qdqbert

* fix CI:Model templates runner
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Add integration test

* Fix typo

* First draft

* More improvements

* Improve conversion script

* Fix init weights for layer norm

* Fix correct model for conversion script

* Don't tie input and output embeddings

* Add print statements for debugging

* Add print statements for debugging

* Fix vocab size of model

* Improve documentation, remove fast tokenizer

* Add ImageGPTForImageClassification, improve docs

* Fix docs issue

* Set verbosity level back to info

* Improve tests

* Fix tests and add figure

* Delete tokenizer file

* Remove ImageGPTTokenizer from init files

* Remove ImageGPTLayer from init files

* Remove ImageGPT tokenizer from docs

* First draft of ImageGPTFeatureExtractor

* Fix typo

* Fix bug

* More improvements

* Apply suggestions from code review, add tests for feature extractor

* Fix layernorm

* Update save_pretrained method

* Fix issue

* Make all tests of ImageGPTFeatureExtractor pass

* Update code examples

* Rename model inputs to pixel_values

* Improve code examples

* Update init_weights to post_init

* Fix post_init

* Improve tests

* Improve documentation

* Add ignore_index attribute

* Add semantic_ignore_index to BEiT model

* Add segmentation maps argument to BEiTFeatureExtractor

* Simplify SegformerFeatureExtractor and corresponding tests

* Improve tests

* Apply suggestions from code review

* Minor docs improvements

* Streamline segmentation map tests of SegFormer and BEiT

* Improve reduce_labels docs and test

* Fix code quality

* Fix code quality again

* [Speech2Text2] Enable tokenizers

* minor fix

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

* [doc] performance and parallelism doc update

* improve

* improve

* Adding some quality of life for `pipeline` function.

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

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

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

* rewrite guides for fine-tuning with datasets

* simple qa code example

* use anonymous rST links

* style

* Start the work for TFViTModel

* Convert to TF code - need to check in the follow up commits

* Clean up model code

* Expose TFViTModel

* make style

* make quality

* Add test

* make style & quality

* Fix some imports

* fix wrong usage - *kwargs => ** kwargs

* Fix Conv2D weight loading (PT->TF) issue

* Add tests for images with different sizes + fix model

* Fix some common tests for TFViTModel

* Use inputs instead of input_ids in test_compile_tf_model

* Add a comment about transpose and Conv2D in convert_tf_weight_name_to_pt_weight_name

* Avoid transpose in TFViT call

* Fix Conv2D issue in load_tf2_weights_in_pytorch_model

* Use tf.keras.layers.Conv2D instead of tf.nn.conv2d

* Using simpler heuristic to detect Conv2D layer

* Change convert_tf_weight_name_to_pt_weight_name to return TransposeType

* Check tf_weight_shape is not None before using it

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

* fix missing comma

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

* Start the work on FlaxVisionEncoderDecoderModel

* Add FlaxVisionEncoderDecoderModel

* Add VisionEncoderDecoderConfig

* Make FlaxVisionEncoderDecoderModel visible to transformers

* Add test

* Fix wrong getattr usage

* Fix tests

* Add FlaxAutoModelForVision2Seq

* Expose FLAX_MODEL_FOR_VISION_2_SEQ_MAPPING

* clean-up

* add integration test

* update expected logits

* update expected scores

* Add ViT2GPT2ModelIntegrationTest + some cleaning

* Add projection layer + PT/Flax equivalence tests

* Fix import

* minor changes

* make test slow again

* Apply suggestions

* Add modeling_flax_vision_encoder_decoder to _ignore_modules in get_model_modules()

* fix copies

* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* split long strings in multiple lines

* decoder_input_ids can't be None

* Add back test_configuration_tie

* Remove attention_mask parameter

* fix test - encoder_last_hidden_state should be encoder_outputs.last_hidden_state instead of the projected vector

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

* Remove more encoder_attention_mask

* remove encoder_attention_mask when calling self.decode (in FlaxVisionEncoderDecoderModule)

* Fix style + pass 1s instead of None as encoder_attention_mask

* fix init_weights

* pass None for encoder_attention_mask

* pass 1s instead of None as encoder_attention_mask

* Fix doc style
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Start PR doc

* Cleanup the quality checks and document them

* Add reference in the contributing guide

* Apply suggestions from code review
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Rename file as per review suggestion
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Add LayoutXLMTokenizer and LayoutXLMTokenizerFast

* Fix styling issues

* Fix more styling issues

* Fix more styling issues

* Fix docstring

* Fix unit tests

* Fix docs

* Fix unit tests

* Fix typos and styling issues

* Fix styling issues

* Fix docstring

* Make all tests of test_tokenization_layoutxlm pass

* Add LayoutXLMProcessor

* Make fixup

* Make all LayoutXLMProcessor tests pass

* Minor fixes

* Leave LayoutLMv2Processor tests unchanged

* Fix code quality

* Move LayoutXLM tokenizers and processor to separate folder

* Fix code quality

* Apply suggestions from code review

* Replace assertions by value errors

* Remove methods from fast tokenizer
Co-authored-by: King Yiu Suen <kingyiusuen@gmail.com>

* Update Transformers to huggingface_hub >= 0.1.0

* Forgot to save...

* Style

* Fix test

* add Beit model ouput class

* inherting from BaseModelOuputWithPooling

* updated docs if use_mean_pooling is False

* added beit specific outputs in model docs

* changed the import path

* Fix docs
Co-authored-by: Niels Rogge <niels.rogge1@gmail.com>

* Add first draft

* Make forward pass work

* Improve conversion script

* Add notebook that checks if it works

* Add BeitForSemanticSegmentation to the tests

* More improvements

* Make BeitForSemanticSegmentation consistent with Segformer

* Small bug fix

* Add BeitForSemanticSegmentation to docs

* Make sure model doesn't output hidden states when the user doesn't want to

* Make it possible to convert the large model

* Fix issue

* Fix conversion script for large model

* Add auxiliary_head option to semantic segmentation model

* Apply suggestions from @sgugger's review

* Apply suggestions from code review

* Fix failing test
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

* Add the support for the fast (rust) implementation of BlenbderbotTokenizer

* Fix a converter and a typo in a doc

* Apply the patil-suraj's suggestion

* (Nitpick) Fast tokenization -> Fast Tokenization in doc

* Apply the SaulLu's suggestion

* Apply Narsil's suggestion to fix test pipelines

* Add encoder_no_repeat_ngram_size according to the Narsil's suggestion

* Revert the last (unnecessary) commit

* Override pipeline config for Blenderbot to allow for larger pos. emb.

* make fix-copies

* Tentative enabling of `batch_size` for pipelines.

* Add systematic test for pipeline batching.

* Enabling batch_size on almost all pipelines

- Not `zero-shot` (it's already passing stuff as batched so trickier)
- Not `QA` (preprocess uses squad features, we need to switch to real
tensors at this boundary.

* Adding `min_length_for_response` for conversational.

* Making CTC, speech mappings avaiable regardless of framework.

* Attempt at fixing automatic tests (ffmpeg not enabled for fast tests)

* Removing ffmpeg dependency in tests.

* Small fixes.

* Slight cleanup.

* Adding docs

and adressing comments.

* Quality.

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

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

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

* Improving docs.

* Update docs/source/main_classes/pipelines.rst
Co-authored-by: Philipp Schmid <32632186+philschmid@users.noreply.github.com>

* N -> oberved_batch_size

softmax trick.

* Follow `padding_side`.

* Supporting image pipeline batching (and padding).

* Rename `unbatch` -> `loader_batch`.

* unbatch_size forgot.

* Custom padding for offset mappings.

* Attempt to remove librosa.

* Adding require_audio.

* torchaudio.

* Back to using datasets librosa.

* Adding help to set a pad_token on the tokenizer.

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

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

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

* Quality.
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Philipp Schmid <32632186+philschmid@users.noreply.github.com>

* First draft

* Make style & quality

* Improve conversion script

* Add print statement to see actual slice

* Make absolute tolerance smaller

* Fix image classification models

* Add post_process_semantic method

* Disable padding

* Improve conversion script

* Rename to ForSemanticSegmentation, add integration test, remove post_process methods

* Improve docs

* Fix code quality

* Fix feature extractor tests

* Fix tests for image classification model

* Delete file

* Add is_torch_available to feature extractor

* Improve documentation of feature extractor methods

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

* Apply some more suggestions of code review

* Rebase with master

* Fix rebase issues

* Make sure model only outputs hidden states when the user wants to

* Apply suggestions from code review

* Add pad method

* Support padding of 2d images

* Add print statement

* Add print statement

* Move padding method to SegformerFeatureExtractor

* Fix issue

* Add casting of segmentation maps

* Add test for padding

* Add small note about padding
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* unispeech

* add copy from

* remove hubert copy from

* finish for today

* add unispeech-sat

* adapt more

* up

* up

* up

* up

* add modeling

* add tests

* up

* up

* finish

* up

* Apply suggestions from code review

* up

* up

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

* up

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

Add Camembert to models exportable with ONNX
Co-authored-by: Thomas.Chaigneau <thomas.chaigneau@arkea.com>
Co-authored-by: Michael Benayoun <mickbenayoun@gmail.com>

* Fix some writing issues in the docs

* Run code quality check

* Fix some typos in the docs

* Fix a styling issue

* Fix code quality check error

* Update TP parallel GEMM image

* Delete parallelism-tp-parallel_gemm.png

* Update parallelism-tp-parallel_gemm.png

* adapt_examples

* up

* up

* up

* up

* add auto models

* finish

* Add API to register a new object in auto classes

* Fix test

* Documentation

* Add to tokenizers and test

* Add cleanup after tests

* Be more careful

* Move import

* Move import

* Cleanup in TF test too

* Add consistency check

* Add documentation

* Style

* Update docs/source/model_doc/auto.rst
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

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