GitLab

* improve names and tests longformer

* more and better tests for longformer

* add first tf test

* finalize tf basic op functions

* fix merge

* tf shape test passes

* narrow down discrepancies

* make longformer local attn tf work

* correct tf longformer

* add first global attn function

* add more global longformer func

* advance tf longformer

* finish global attn

* upload big model

* finish all tests

* correct false any statement

* fix common tests

* make all tests pass except keras save load

* fix some tests

* fix torch test import

* finish tests

* fix test

* fix torch tf tests

* add docs

* finish docs

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

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

* apply Lysandres suggestions

* reverse to assert statement because function will fail otherwise

* applying sylvains recommendations

* Update src/transformers/modeling_longformer.py
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* Update src/transformers/modeling_tf_longformer.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* correct encoder decoder model

* Apply suggestions from code review

* apply sylvains suggestions

* TFAlbertFor{TokenClassification, MultipleChoice}

* Patch models

* BERT and TF BERT info


s

* Update check_repo

* refactor almost identical tests

* important to add a clear assert error message

* make the assert error even more descriptive than the original bt

* Fix the tests for Electra

* Apply style

* Add a script to check all models are tested and documented

* Apply suggestions from code review
Co-authored-by: Kevin Canwen Xu <canwenxu@126.com>

* Address comments
Co-authored-by: Kevin Canwen Xu <canwenxu@126.com>

* Add strip_accents to basic tokenizer

* Add tests for strip_accents.

* fix style with black

* Fix strip_accents test

* empty commit to trigger CI

* Improved strip_accents check

* Add code quality with is not False

* TF outputs and test on BERT

* Albert to DistilBert

* All remaining TF models except T5

* Documentation

* One file forgotten

* TF outputs and test on BERT

* Albert to DistilBert

* All remaining TF models except T5

* Documentation

* One file forgotten

* Add new models and fix issues

* Quality improvements

* Add T5

* A bit of cleanup

* Fix for slow tests

* Style

* Add SequenceClassification and MultipleChoice TF models to Electra

* Apply style

* Add summary_proj_to_labels to Electra config

* Finally mirroring the PT version of these models

* Apply style

* Fix Electra test

* improve unit tests

this is a sample of one test according to the request in https://github.com/huggingface/transformers/issues/5973
before I apply it to the rest

* batch 1

* batch 2

* batch 3

* batch 4

* batch 5

* style

* non-tf template

* last deletion of check_loss_output

* Fix TF Serving when output_hidden_states and output_attentions are True

* Add tests for saved model creation + bug fix for multiple choices models

* remove unused import

* Fix the input for several layers

* Fix test

* Fix conflict printing

* Apply style

* Fix XLM and Flaubert for TensorFlow

* Apply style

* Fix TF check version

* Apply style

* Trigger CI

* Use return_dict=True in all tests

* Formatting

* add parse_dict to parse arguments from dict

* add unit test for parse_dict

* enable easy checkout switch

allow having multiple repository checkouts and not needing to remember to rerun 'pip install -e .[dev]' when switching between checkouts and running tests.

* make isort happy

* examples needs one too

* 2 small typos

* more typos

* correct path

* initial commit for pipeline implementation

Addition of input processing and history concatenation

* Conversation pipeline tested and working for single & multiple conversation inputs

* Added docstrings for dialogue pipeline

* Addition of dialogue pipeline integration tests

* Delete test_t5.py

* Fixed max code length

* Updated styling

* Fixed test broken by formatting tools

* Removed unused import

* Added unit test for DialoguePipeline

* Fixed Tensorflow compatibility

* Fixed multi-framework support using framework flag

* - Fixed docstring
- Added `min_length_for_response` as an initialization parameter
- Renamed `*args` to `conversations`, `conversations` being a `Conversation` or a `List[Conversation]`
- Updated truncation to truncate entire segments of conversations, instead of cutting in the middle of a user/bot input

* - renamed pipeline name from dialogue to conversational
- removed hardcoded default value of 1000 and use config.max_length instead
- added `append_response` and `set_history` method to the Conversation class to avoid direct fields mutation
- fixed bug in history truncation method

* - Updated ConversationalPipeline to accept only active conversations (otherwise a ValueError is raised)

* - Simplified input tensor conversion

* - Updated attention_mask value for Tensorflow compatibility

* - Updated last dialogue reference to conversational & fixed integration tests

* Fixed conflict with master

* Updates following review comments

* Updated formatting

* Added Conversation and ConversationalPipeline to the library __init__, addition of docstrings for Conversation, added both to the docs

* Update src/transformers/pipelines.py

Updated docsting following review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Switch from return_tuple to return_dict

* Fix test

* [WIP] Test TF Flaubert + Add {XLM, Flaubert}{TokenClassification, MultipleC… (#5614)

* Test TF Flaubert + Add {XLM, Flaubert}{TokenClassification, MultipleChoice} models and tests

* AutoModels


Tiny tweaks

* Style

* Final changes before merge

* Re-order for simpler review

* Final fixes

* Addressing @sgugger's comments

* Test MultipleChoice

* Rework TF trainer (#6038)

* Fully rework training/prediction loops

* fix method name

* Fix variable name

* Fix property name

* Fix scope

* Fix method name

* Fix tuple index

* Fix tuple index

* Fix indentation

* Fix variable name

* fix eval before log

* Add drop remainder for test dataset

* Fix step number + fix logging datetime

* fix eval loss value

* use global step instead of step + fix logging at step 0

* Fix logging datetime

* Fix global_step usage

* Fix breaking loop + logging datetime

* Fix step in prediction loop

* Fix step breaking

* Fix train/test loops

* Force TF at least 2.2 for the trainer

* Use assert_cardinality to facilitate the dataset size computation

* Log steps per epoch

* Make tfds compliant with TPU

* Make tfds compliant with TPU

* Use TF dataset enumerate instead of the Python one

* revert previous commit

* Fix data_dir

* Apply style

* rebase on master

* Address Sylvain's comments

* Address Sylvain's and Lysandre comments

* Trigger CI

* Remove unused import

* Switch from return_tuple to return_dict

* Fix test

* Add recent model
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Julien Plu <plu.julien@gmail.com>

* Test TF Flaubert + Add {XLM, Flaubert}{TokenClassification, MultipleChoice} models and tests

* AutoModels


Tiny tweaks

* Style

* Final changes before merge

* Re-order for simpler review

* Final fixes

* Addressing @sgugger's comments

* Test MultipleChoice

* Added capability to quantize a model while exporting through ONNX.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

We do not support multiple extensions
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Reformat files
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* More quality
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Ensure test_generate_identified_name compares the same object types
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Added documentation everywhere on ONNX exporter
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Use pathlib.Path instead of plain-old string
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Use f-string everywhere
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Use the correct parameters for black formatting
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Use Python 3 super() style.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Use packaging.version to ensure installed onnxruntime version match requirements
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Fixing imports sorting order.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Missing raise(s)
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Added quantization documentation
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Fix some spelling.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Fix bad list header format
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* MBART: support summarization tasks

* fix test

* Style

* add tokenizer test

* add initial zero-shot pipeline

* change default args

* update default template

* add label string splitting

* add str labels support, remove nli from name

* style

* add input validation and working tf defaults

* tests

* quality check

* add docstring to __call__

* add slow tests

* Change truncation to only_first

also lower precision on tests for readibility

* style

* Avoid unnecessary warnings when loading pretrained model

* Fix test

* Add other keys to ignore

* keys_to_ignore_at_load -> authorized_missing_keys

* DataParallel fixes:

1. switched to a more precise check
-        if self.args.n_gpu > 1:
+        if isinstance(model, nn.DataParallel):

2. fix tests - require the same fixup under DataParallel as the training module

* another fix

* Don't pass sampler for iterable dataset

* Added check for test and eval dataloaders.

* Formatting

* Don't pass sampler for iterable dataset

* Added check for test and eval dataloaders.

* Formatting

* Cleaner if nesting.

* Added test for trainer and iterable dataset

* Formatting for test

* Fixed import when torch is available only.

* Added require torch decorator to helper class

* Moved dataset class inside unittest

* Removed nested if and changed model in test

* Checking torch availability for IterableDataset

Slightly breaking change, changes functionality for `use_cache` in XLNet: if use_cache is True and mem_len is 0 or None (which is the case in the base model config), the model behaves like GPT-2 and returns mems to be used as past in generation. At training time `use_cache` is overriden and always True.

This reverts commit 13be4872.

Slightly breaking change, changes functionality for `use_cache` in XLNet: if use_cache is True and mem_len is 0 or None (which is the case in the base model config), the model behaves like GPT-2 and returns mems to be used as past in generation. At training time `use_cache` is overriden and always True.

This reverts commit 0b2da0e5.

Slightly breaking change, changes functionality for `use_cache` in XLNet: if use_cache is True and mem_len is 0 or None (which is the case in the base model config), the model behaves like GPT-2 and returns mems to be used as past in generation. At training time `use_cache` is overriden and always True.

* fix merge rebase

* add intermediate reformer code

* save intermediate caching results

* save intermediate

* save intermediate results

* save intermediate

* upload next step

* fix generate tests

* make tests work

* add named tuple output

* Apply suggestions from code review

* fix use_cache for False case

* fix tensor to gpu

* fix tensor to gpu

* refactor

* refactor and make style

Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>