* Fix torch.jit.script and pickling issues
* Fix get_attr issues
* Fix import in function
* Fix GPT-J and T5 tracing for torch=1.11
* Gate graph surgery on torch version
* Modeling minor changes to enable TorchScripting
* Model serialization / deserialization test
* Remove _assert_is_none users
* add inference example to LayoutLMv2ForQuestionAnswering, passing doctest
* add loss example to LayoutLMv2ForQuestionAnswering, passing doctest
* Add correct doctest for LayoutLMv2ForTokenClassification, passing doctest
* add correct doctest for LayoutLMv2ForSequenceClassification, passing test
* add correct doctest for LayoutLMv2Model, passing test
* make fixup
* fix to address review comments
* make style
* fix doctest line break issue, add to documentaiton_tests.txt, address review comments
* move comment about layoutlmv2 dependencies to the doc page
* format doc page as suggested
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* delete extraneous backtick
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* average loss over batches and accumulated steps for tracking
* fix layernorm weight decay
* use AdamW from Pytorch instead of Transformers
* add shuffling of sequences inside the batches
* add shuffling of sequences inside the batches
* add logging dir and reformat code
* fix lr tracking
* remove Mistral scaling
* keep Mistral scaling
* reformat code
* fix error
* fix error
* use shuffling function from Pytorch
* remove argument for shuffling batch sequences as it isn't optional
* update package versions and install accelerate from source
* remove unused package
* Update loss average over accumulated steps
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
* Update loss average over accumulated steps
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
* use one shuffle buffer argument
* compute avg_loss in one line
Co-authored-by: Loubna ben allal <loubnabenallal@gmail.com>
Co-authored-by: Leandro von Werra <lvwerra@users.noreply.github.com>
* [BC] Fixing usage of text pairs
The BC is actually preventing users from misusing the pipeline since
users could have been willing to send text pairs and the pipeline would
instead understand the thing as a batch returning bogus results.
The correct usage of text pairs is preserved in this PR even when that
makes the code clunky.
Adds support for {"text":..,, "text_pair": ...} inputs for both dataset
iteration and more explicit usage to pairs.
* Updating the doc.
* Update src/transformers/pipelines/text_classification.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/pipelines/text_classification.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update tests/pipelines/test_pipelines_text_classification.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* quality.
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Fix length in no_trainer examples
* Add setup and teardown
* Use new accelerator config generator to automatically make tests able to run based on environment
* Add information gain filtration algorithm
* Complying with black requirements
* Added author
* Fixed import order
* flake8 corrections
Co-authored-by: Javier Turek <javier.turek@intel.com>
* added type hints to prophetnet
* reformatted with black
* fix bc black misformatted some parts
* fix imports
* fix imports
* Update src/transformers/models/prophetnet/configuration_prophetnet.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* update OPTIONAL type hint and docstring
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* [LED] fixed global_attention_mask not passed for generation + docs clarification for gradient checkpointing
* LED docs clarification
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* [LED] gradient_checkpointing=True should be passed to TrainingArguments
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* [LED] docs: remove wrong word
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* [LED] docs fix typo
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
- Add --ignore_mismatched_sizes argument to classification examples
- Expand the error message when loading a model whose head dimensions are different from expected dimensions
* Initial commit
* Better label renaming
* Remove breakpoint before pushing (this is your job)
* Test a lot more in the Keras fit() test
* make fixup
* Clarify the case where we flatten y dicts into tensors
* Clarify the case where we flatten y dicts into tensors
* Extract label name remapping to a method