GitLab

* device agnostic models testing

* add decorator `require_torch_fp16`

* make style

* apply review suggestion

* Oops, the fp16 decorator was misused

* stronger GC tests

* better tests and skip failing tests

* break down into 3 sub-tests

* break down into 3 sub-tests

* refactor a bit

* more refactor

* fix

* last nit

* credits contrib and suggestions

* credits contrib and suggestions

---------
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>

* CI with layers=2

---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Fix TypeError: Object of type int64 is not JSON serializable

* Convert numpy.float64 and numpy.int64 to float and int for json serialization

* Black reformatted examples/pytorch/token-classification/run_ner_no_trainer.py

* * make style

Revert "Fix gradient checkpointing + fp16 autocast for most models (#24247)"

This reverts commit 285a4801.

* fix gc bug

* continue PoC on OPT

* fixes

* :exploding_head:

* fix tests

* remove pytest.mark

* fixup

* forward contrib credits from discussions

* forward contrib credits from discussions

* reverting changes on untouched files.

---------
Co-authored-by: zhaoqf123 <zhaoqf123@users.noreply.github.com>
Co-authored-by: 7eu7d7 <7eu7d7@users.noreply.github.com>

* fix

* fix

---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* first draft - gives index error in question_answering.py

* maturing

* no labels

* pipeline should know about QA

* fixing checks

* formatting

* fixed docstring

* make sure legacy code executes

* comment

* like this

---------
Co-authored-by: Prof. Peter Schneider-Kamp <jps@ordbogen.com>

Revert "[GPT2] Propose fix for #21080 (#21853)" to avoid CI failure

This reverts commit a3fef89b.

* Make sure position ids are masked

* test that padded input produce the same results

* fix failing tests

* fixup

* fix batch test

* Add PipelineTesterMixin

* remove class PipelineTestCaseMeta

* move validate_test_components

* Add for ViT

* Add to SPECIAL_MODULE_TO_TEST_MAP

* style and quality

* Add feature-extraction

* update

* raise instead of skip

* add tiny_model_summary.json

* more explicit

* skip tasks not in mapping

* add availability check

* Add Copyright

* A way to diable irrelevant tests

* update with main

* remove disable_irrelevant_tests

* skip tests

* better skip message

* better skip message

* Add all pipeline task tests

* revert

* Import PipelineTesterMixin

* subclass test classes with PipelineTesterMixin

* Add pipieline_model_mapping

* Fix import after adding pipieline_model_mapping

* Fix style and quality after adding pipieline_model_mapping

* Fix one more import after adding pipieline_model_mapping

* Fix style and quality after adding pipieline_model_mapping

* Fix test issues

* Fix import requirements

* Fix mapping for MobileViTModelTest

* Update

* Better skip message

* pipieline_model_mapping could not be None

* Remove some PipelineTesterMixin

* Fix typo

* revert tests_fetcher.py

* update

* rename

* revert

* Remove PipelineTestCaseMeta from ZeroShotAudioClassificationPipelineTests

* style and quality

* test fetcher for all pipeline/model tests

---------
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Result of black 23.1

* Update target to Python 3.7

* Switch flake8 to ruff

* Configure isort

* Configure isort

* Apply isort with line limit

* Put the right black version

* adapt black in check copies

* Fix copies

* move generation_*.py src files into generation/*.py

* populate generation.__init__ with lazy loading

* move imports and references from generation.xxx.object to generation.object

* Use beam search functionality; Add extra outputs and test

* Add full tests for contrastive search

* Add error message on unconventional cache format

* move test model folders (TODO: fix imports and others)

* fix (potentially partially) imports (in model test modules)

* fix (potentially partially) imports (in tokenization test modules)

* fix (potentially partially) imports (in feature extraction test modules)

* fix import utils.test_modeling_tf_core

* fix path ../fixtures/

* fix imports about generation.test_generation_flax_utils

* fix more imports

* fix fixture path

* fix get_test_dir

* update module_to_test_file

* fix get_tests_dir from wrong transformers.utils

* update config.yml (CircleCI)

* fix style

* remove missing imports

* update new model script

* update check_repo

* update SPECIAL_MODULE_TO_TEST_MAP

* fix style

* add __init__

* update self-scheduled

* fix add_new_model scripts

* check one way to get location back

* python setup.py build install

* fix import in test auto

* update self-scheduled.yml

* update slack notification script

* Add comments about artifact names

* fix for yolos
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* First attempt at TF XLA generation

* Fix comments

* Update XLA greedy generate with direct XLA calls

* Support attention mask, prepare_inputs_for_generation no longer hardcoded for greedy

* Handle position_ids correctly

* make xla generate work for non xla case

* force using xla generate

* refactor

* more fixes

* finish cleaning

* finish

* finish

* clean gpt2 tests

* add gpt2 tests

* correct more cases

* up

* finish

* finish

* more fixes

* flake 8 stuff

* final rag fix

* Update src/transformers/models/rag/modeling_tf_rag.py

* finish t5 as well

* finish

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

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

* Change the way tracing happens, enabling dynamic axes out of the box

* Update the tests and modeling xlnet

* Add the non recoding of leaf modules to avoid recording more values for the methods to record than what will be seen at tracing time (which would otherwise desynchronize the recorded values and the values that need to be given to the proxies during tracing, causing errors).

* Comments and making tracing work for gpt-j and xlnet

* Refactore things related to num_choices (and batch_size, sequence_length)

* Update fx to work on PyTorch 1.10

* Postpone autowrap_function feature usage for later

* Add copyrights

* Remove unnecessary file

* Fix issue with add_new_model_like

* Apply suggestions

* Remove n_ctx from configs

* Fix GPTJ and OpenAIGPT, both are acceptable breaking changes as there are no configs such that it breaks

* Remove unecessary n_positions from TFOpenAIGPT

* Add layer-wise scaling

* Add reorder & upcasting argument

* Add OpenAI GPT-2 weight initialization scheme

* start `layer_idx` count at zero for consistency

* disentangle attn and reordered and upscaled attn function

* rename `scale_attn_by_layer` to `scale_attn_by_layer_id`

* make autocast from amp compatible with pytorch<1.6

* fix docstring

* style fixes

* Add fixes from PR feedback, style tweaks

* Fix doc whitespace

* Reformat

* First pass scale_attn_by_layer_idx and reorder_and_upcast_attn tests

* Rename scale_attn_by_layer_idx, add tip

* Remove extra newline

* add test for weight initialization

* update code format

* add assert check weights are fp32

* remove assert

* Fix incorrect merge

* Fix shape mismatch in baddbmm

* Add generation test for Mistral flags
Co-authored-by: leandro <leandro.vonwerra@spoud.io>
Co-authored-by: Keshav Santhanam <keshav2@stanford.edu>
Co-authored-by: J38 <jebolton@stanford.edu>

* Make gradient_checkpointing a training argument

* Update src/transformers/modeling_utils.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Update src/transformers/configuration_utils.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Fix tests

* Style

* document Gradient Checkpointing as a performance feature

* Small rename

* PoC for not using the config

* Adapt BC to new PoC

* Forgot to save

* Rollout changes to all other models

* Fix typo
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Stas Bekman <stas@stason.org>

* Add GPT2ForTokenClassification

* Fix dropout exception for GPT2 NER

* Remove sequence label in test

* Change TokenClassifierOutput to TokenClassifierOutputWithPast

* Fix for black formatter

* Remove dummy

* Update docs for GPT2ForTokenClassification

* Fix check_inits ci fail

* Update dummy_pt_objects after make fix-copies

* Remove TokenClassifierOutputWithPast

* Fix tuple input issue
Co-authored-by: danielsejong55@gmail.com <danielsejong55@gmail.com>

* Expose get_config() on ModelTesters

* Typo

* seq classification changes

* fix tests

Cleaner and more scalable implementation of symbolic tracing with torch.fx, and provides support for new architectures:
- ALBERT
- DistilBERT
- MobileBERT
- MegatronBERT
- GPT2
- GPT Neo
Co-authored-by: Michael Benayoun <michael@huggingface.co>

* GPT2DoubleHeadsModel made parallelizeable

* GPT2DoubleHeadsModel added as parallelizeable onto the GPT2 test suite

* [WIP] Adding new parameter to `generate`:  `max_time`.

Generation by tokens number is sometimes a bit clunky because we don't
know how many tokens are good enough or even how many tokens are in
the payload (for pipelines users for instance). This leads to hard
to understand behavior.

This PR proposes a new argument `max_time` which is a float of seconds
for the allowed time for `generate` to run on.
Ideally combinations of `max_tokens=None`, `max_time=2` could be used to
generate as many tokens as possible within time budget.

NB: Another possible approach consists of passing a callback to `generate`
  putting the caller in charge of the actual decision of when to stop
  generating tokens. It opens the door to 'which args should we pass'
  to this callback. It's hard to imagine other use-cases for this
  early stopping behavior than time (that are not already covered by
  parameters of generate)

* Revamp with StoppingCriteria

* Removing deprecated mentions.

* Forgot arguments to stopping criteria.

* Readding max_length it's not just used as a stopping criteria.

* Default value for `stopping_criteria`.

* Address @patrickvonplaten comments.

- More docstrings
- Actual doc
- Include in global namespace
- Remove TF work.

* Put back `max_length` (deprecation different PR).

* Doc quality.

* Fixing old behavior without `stopping_criteria` but with `max_length`.

Making sure we don't break that in the future.

* Adding more tests for possible inconsistencies between

`max_length` and `stopping_criteria`.

* Fixing the torch imports.

* Update past_key_values in gpt2 (#9391)

* Update generation_utils, and rename some items

* Update modeling_gpt2 to avoid an error in gradient_checkpointing

* Remove 'reorder_cache' from util and add variations to XLNet, TransfoXL, GPT-2

* Change the location of '_reorder_cache' in modeling files

* Add '_reorder_cache' in modeling_ctrl

* Fix a bug of my last commit in CTRL

* Add '_reorder_cache' to GPT2DoubleHeadsModel

* Manage 'use_cache' in config of test_modeling_gpt2

* Clean up the doc string

* Update src/transformers/models/gpt2/modeling_gpt2.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Fix the doc string (GPT-2, CTRL)

* improve gradient_checkpointing_behavior
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* add tests

* make style and fix bart bug

* fix bart past key value edge case

* correct tf bart test

* fix gpt2 tf

* fix t5 test

* Add copyright everywhere missing

* Style

* gpt2 and t5 parallel modeling

* model_parallel utils update

* adding missing model_parallel_utils

Adds missing model_parallel_utils and reverses the changes to code in modeling_gpt2 and modeling_t5

* training_args reformat

Reformatted training_args

* style formatting

Style formatting doc string length on training_args and model_parallel_utils

* style changes

make style && make quality for training_args and model_parallel_utils.

* adding tests

* minor change in trainer

reverts loss calculation

* Update training_args.py

* Update training_args.py

added back docstring language for adam_beta1 and adam_beta2

* Update trainer.py

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

* Fix style & rebase
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>

* Remove old deprecated arguments
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>

* Remove needless imports

* Fix tests
Co-authored-by: LysandreJik <lysandre.debut@reseau.eseo.fr>

* Use the CI to identify failing tests

* Remove from all examples and tests

* More default switch

* Fixes

* More test fixes

* More fixes

* Last fixes hopefully

* Use the CI to identify failing tests

* Remove from all examples and tests

* More default switch

* Fixes

* More test fixes

* More fixes

* Last fixes hopefully

* Run on the real suite

* Fix slow tests

* Fix passing token_type_ids during GPT2DoubleHeadsModel.generate() if used

and for GPT2LMHeadModel too

* Update tests to check token_type_ids usage in GPT2 models

* add training tests

* correct longformer

* fix docs

* fix some tests

* fix some more train tests

* remove ipdb

* fix multiple edge case model training

* fix funnel and prophetnet

* clean gpt models

* undo renaming of albert

* first draft

* show design proposition for new generate method

* up

* make better readable

* make first version

* gpt2 tests pass

* make beam search for gpt2 work

* add first encoder-decoder code

* delete typo

* make t5 work

* save indermediate

* make bart work with beam search

* finish beam search bart / t5

* add default kwargs

* make more tests pass

* fix no bad words sampler

* some fixes and tests for all distribution processors

* fix test

* fix rag slow tests

* merge to master

* add nograd to generate

* make all slow tests pass

* speed up generate

* fix edge case bug

* small fix

* correct typo

* add type hints and docstrings

* fix typos in tests

* add beam search tests

* add tests for beam scorer

* fix test rag

* finish beam search tests

* move generation tests in seperate file

* fix generation tests

* more tests

* add aggressive generation tests

* fix tests

* add gpt2 sample test

* add more docstring

* add more docs

* finish doc strings

* apply some more of sylvains and sams comments

* fix some typos

* make fix copies

* apply lysandres and sylvains comments

* final corrections on examples

* small fix for reformer

* Add support for gpt2 batch inferencing

* add test

* remove typo
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>