GitLab

* Add onnx configuration for bigbird-pegasus

* Modify docs

* Skip RoFormer ONNX test if rjieba not installed

* Update deps table

* Skip RoFormer serialization test

* Fix RoFormer vocab

* Add rjieba to CircleCI

* add roformer onnx config

* added deit onnx config

Co-authored-by: ChainYo <t.chaigneau.tc@gmail.com>

* add OnnxConfig for ConvBert
Co-authored-by: ChainYo <t.chaigneau.tc@gmail.com>

* Add export of models with a multiple-choice classification head

* add Bigbird ONNX config

* Add beit onnx conversion support

* Updated docs

* Added cross reference to ViT ONNX config

* Add ONNX support for Blenderbot

* Add BlenderbotSmall ONNX configuration

* Update serialization table

* Split file_utils in several submodules

* Fixes

* Add back more objects

* More fixes

* Who exactly decided to import that from there?

* Second suggestion to code with code review

* Revert wront move

* Fix imports

* Adapt all imports

* Adapt all imports everywhere

* Revert this import, will fix in a separate commit

* Make Camembert great again!

* Add Camembert to TensorFlow ONNX tests

* Fix duplicate arguments passed to dummy inputs in ONNX export

* Fix M2M100 ONNX config

* Ensure we check PreTrained model only if torch is available

* Remove TensorFlow tests for models without PyTorch parity

* Add ONNX support for ViT

* Refactor to use generic preprocessor

* Add vision dep to tests

* Extend ONNX slow tests to ViT

* Add dummy image generator

* Use model_type to determine modality

* Add deprecation warnings for tokenizer argument

* Add warning when overwriting the preprocessor

* Add optional args to docstrings

* Add minimum PyTorch version to OnnxConfig

* Refactor OnnxConfig class variables from CONSTANT_NAME to snake_case

* Add reasonable value for default atol
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Add M2M100 support for ONNX export

* Delete useless imports

* Add M2M100 to tests

* Fix protobuf issue

* Per-folder tests reorganization
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Stas Bekman <stas@stason.org>

* Add TensorFlow support for ONNX export

* Change documentation to mention conversion with Tensorflow

* Refactor export into export_pytorch and export_tensorflow

* Check model's type instead of framework installation to choose between TF and Pytorch
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Alberto Bégué <alberto.begue@della.ai>
Co-authored-by: lewtun <lewis.c.tunstall@gmail.com>

* electra is added to onnx supported model

* add google/electra-base-generator for test onnx module
Co-authored-by: Lewis Tunstall <lewis.c.tunstall@gmail.com>

* Add IBertOnnxConfig and tests

* add all the supported features for IBERT and remove outputs in IbertOnnxConfig

* use OnnxConfig

* fix codestyle

* remove serialization.rst

* codestyle

* 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>

* 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

This reverts commit 0c70f145.

* Added support for other features for already supported models

* Partial support for causal and seq2seq models

* Partial support for causal and seq2seq models

* OnnxSeq2SeqConfigWithPast to support seq2seq models

* Parameterized the onnx tests

* Restored run_mlm.py

* Restored run_mlm.py

* [WIP] BART update

* BART and MBART

* Added comments

* Another sequence length of the past_key_values

* Add support for exporting PyTorch LayoutLM to ONNX

* Added tests for converting LayoutLM to ONNX

* Add support for exporting PyTorch LayoutLM to ONNX

* Added tests for converting LayoutLM to ONNX

* cleanup

* Removed regression/ folder

* Add support for exporting PyTorch LayoutLM to ONNX

* Added tests for converting LayoutLM to ONNX

* cleanup

* Fixed import error

* Remove unnecessary import statements

* Changed max_2d_positions from class variable to instance variable of the config class

* Add support for exporting PyTorch LayoutLM to ONNX

* Added tests for converting LayoutLM to ONNX

* cleanup

* Add support for exporting PyTorch LayoutLM to ONNX

* cleanup

* Fixed import error

* Changed max_2d_positions from class variable to instance variable of the config class

* Use super class generate_dummy_inputs method
Co-authored-by: Michael Benayoun <mickbenayoun@gmail.com>

* Add support for Masked LM, sequence classification and token classification
Co-authored-by: Michael Benayoun <mickbenayoun@gmail.com>

* Removed uncessary import and method

* Fixed code styling

* Raise error if PyTorch is not installed

* Remove unnecessary import statement
Co-authored-by: Michael Benayoun <mickbenayoun@gmail.com>

* Add MBART to models exportable with ONNX

* unittest mock

* Add tests

* Misc fixes

T5 with past ONNX export, and more explicit past_key_values inputs and outputs names for ONNX model
Authored-by: Michael Benayoun <michael@huggingface.co>

GPT-Neo ONNX export and task / feature refactoring
Authored-by: Michael Benayoun <michael@huggingface.co>

* Raise an issue if the pytorch version is < 1.8.0

* Attempt to add a test to ensure it correctly raises.

* Missing docstring.

* Second attempt, patch with string absolute import.

* Let's do the call before checking it was called ...

* use the correct function ... 🤦

* Raise ImportError and AssertionError respectively when unable to find torch and torch version is not sufficient.

* Correct path mock patching

* relax constraint for torch_onnx_dict_inputs to ge instead of eq.

* Style.

* Split each version requirements for torch.

* Let's compare version directly.

* Import torch_version after checking pytorch is installed.

* @require_torch

* Set model in eval mode when exporting to ONNX.

* Disable t5 for now.

* Disable T5 with past too.

* Style.

* Laying down building stone for more flexible ONNX export capabilities

* Ability to provide a map of config key to override before exporting.

* Makes it possible to export BART with/without past keys.

* Supports simple mathematical syntax for OnnxVariable.repeated

* Effectively apply value override from onnx config for model

* Supports export with additional features such as with-past for seq2seq

* Store the output path directly in the args for uniform usage across.

* Make BART_ONNX_CONFIG_* constants and fix imports.

* Support BERT model.

* Use tokenizer for more flexibility in defining the inputs of a model.

* Add TODO as remainder to provide the batch/sequence_length as CLI args

* Enable optimizations to be done on the model.

* Enable GPT2 + past

* Improve model validation with outputs containing nested structures

* Enable Roberta

* Enable Albert

* Albert requires opset >= 12

* BERT-like models requires opset >= 12

* Remove double printing.

* Enable XLM-Roberta

* Enable DistilBERT

* Disable optimization by default

* Fix missing setattr when applying optimizer_features

* Add value field to OnnxVariable to define constant input (not from tokenizers)

* Add T5 support.

* Simplify model type retrieval

* Example exporting token_classification pipeline for DistilBERT.

* Refactoring to package `transformers.onnx`

* Solve circular dependency & __main__

* Remove unnecessary imports in `__init__`

* Licences

* Use @Narsil's suggestion to forward the model's configuration to the ONNXConfig to avoid interpolation.

* Onnx export v2 fixes (#12388)

* Tiny fixes
Remove `convert_pytorch` from onnxruntime-less runtimes
Correct reference to model

* Style

* Fix Copied from

* LongFormer ONNX config.

* Removed optimizations

* Remvoe bad merge relicas.

* Remove unused constants.

* Remove some deleted constants from imports.

* Fix unittest to remove usage of PyTorch model for onnx.utils.

* Fix distilbert export

* Enable ONNX export test for supported model.

* Style.

* Fix lint.

* Enable all supported default models.

* GPT2 only has one output

* Fix bad property name when overriding config.

* Added unittests and docstrings.

* Disable with_past tests for now.

* Enable outputs validation for default export.

* Remove graph opt lvls.

* Last commit with on-going past commented.

* Style.

* Disabled `with_past` for now

* Remove unused imports.

* Remove framework argument

* Remove TFPreTrainedModel reference

* Add documentation

* Add onnxruntime tests to CircleCI

* Add test

* Rename `convert_pytorch` to `export`

* Use OrderedDict for dummy inputs

* WIP Wav2Vec2

* Revert "WIP Wav2Vec2"

This reverts commit f665efb04c92525c3530e589029f0ae7afdf603e.

* Style

* Use OrderedDict for I/O

* Style.

* Specify OrderedDict documentation.

* Style :)
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>