Sync/v4.8.0 #194
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Sync/v4.8.0 #194
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* Improve docs of DeiT and ViT, add community notebook * Add gitignore for test_samples * Add notebook with Trainer Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* improve slow class tok usage at xlm rob * add subword regularization for barthez * improve barthez tok. test * fix tokenizer tests * add subword regularization for camembert * add subword regularization for deberta v2 tokenizer * add more doc to deberta v2 tokenizer * add subword regularization for speech to text tok. * fix sp_model_kwargs type in speech 2 text tok. * add subword regularization for M2M100 tok. * add more concrete type hints * fix tests for m2m100 and s2t tok. * add missing Any import * fix syntax error in m2m100 tok. * fix unpickle of m2m100 and s2t tok. * fix test of m2m100 and s2t tok. * improve unpickle of deberta v2 tok. * add test for pickle of barthez & camembert * fix pickle of barthez & camembert * add test for deberta v2 tok. pickle * fix m2m100 tok. pickle * fix s2t tok. pickle * add subword regularization to albert tok. * refactor subword reg. test into TokenizerTesterMixin improve albert tok. test remove sample argument form albert tok. check subword reg. using TokenizerTesterMixin improve tok. tests improve xlm roberta tok. tests improve xlm roberta tok. tests * add subword regularization for big bird t. * improve xlm roberta tok. test * add subword regularization for mbart50 tok. * add subword regularization for pegasus tok. * add subword regularization for reformer tok. * add subword regularization for T5 tok. * fix t5 tok. test formatting * add subword regularization for xlm_proph. tok. * add subword regularization for xlnet tok. * add subword regularization for gert_gen tok. * add typing to tokenizers * add typing to xlm rob. tok * add subword regularization for marian tok. * add reverse tok. test * fix marian tok test * fix marian tok test * fix casing in tok. tests * fix style of tok. common test * fix deberta v2 tok test * add type annotations to tok. tests * add type annotations to tok. __init__ * add typing to kokenizer * add type annotations to tok. __init__ * don't specify the default when it's None * fix barthez tok. doc * move sentencepiece tok. tests to TokenizerTesterMixin * fix unused imports * fix albert tok. test * add comment to sentencepiece test options * fix Any import at big bird tok. * fix Any import at xlm prophetnet tok. * empty commit to trigger CI
* fix some stuff * fix roberta & electra as well * del run bug Co-authored-by: Patrick von Platen <patrick@huggingface.co>
* Add 3D attention mask to T5 model (#9643) Added code for 3D attention mask in T5 model. Similar to BERT model. * Add test for 3D attention mask Added test for 3D attention mask: test_decoder_model_past_with_3d_attn_mask() 3D attention mask of the shape [Batch_size, Seq_length, Seq_length] both for attention mask and decoder attention mask. Test is passing.
* Add Cloud details to README * Flax script and readme updates
… and T5 (#11475) Symbolic tracing feature for BERT, ELECTRA and T5 Co-authored-by: Michael Benayoun <michael@huggingface.co> Co-authored-by: Stas Bekman <stas@stason.org> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Add Cloud details to README * Flax script and readme updates * Some simplifications of Flax script
* Update README.md * Update index.rst
Co-authored-by: Michael Benayoun <michael@huggingface.co>
* improve tests * remove bogus file * make style Co-authored-by: Patrick von Platen <patrick@huggingface.co>
* [TokenClassification] Label realignment for subword aggregation Tentative to replace https://github.com/huggingface/transformers/pull/11622/files - Added `AggregationStrategy` - `ignore_subwords` and `grouped_entities` arguments are now fused into `aggregation_strategy`. It makes more sense anyway because `ignore_subwords=True` with `grouped_entities=False` did not have a meaning anyway. - Added 2 new ways to aggregate which are MAX, and AVERAGE - AVERAGE requires a bit more information than the others, for now this case is slightly specific, we should keep that in mind for future changes. - Testing has been modified to reflect new argument, and to check the correct deprecation and the new aggregation_strategy. - Put the testing argument and testing results for aggregation_strategy, close together, so that readers can understand what is supposed to happen. - `aggregate` is now only tested on a small model as it does not mean anything to test it globally for all models. - Previous tests are unchanged in desired output. - Added a new test case that showcases better the difference between the FIRST, MAX and AVERAGE strategies. * Wrong framework. * Addressing three issues. 1- Tags might not follow B-, I- convention, so any tag should work now (assumed as B-TAG) 2- Fixed an issue with average that leads to a substantial code change. 3- The testing suite was not checking for the "index" key for "none" strategy. This is now fixed. The issue is that "O" could not be chosen by AVERAGE strategy because those tokens were filtered out beforehand, so their relative scores were not counted in the average. Now filtering on ignore_labels will happen at the very end of the pipeline fixing that issue. It's a bit hard to make sure this stays like that because we do not have a end-to-end test for that behavior * Formatting. * Adding formatting to code + cleaner handling of B-, I- tags. Co-authored-by: Francesco Rubbo <rubbo.francesco@gmail.com> Co-authored-by: elk-cloner <rezakakhki.rk@gmail.com> * Typo. Co-authored-by: Francesco Rubbo <rubbo.francesco@gmail.com> Co-authored-by: elk-cloner <rezakakhki.rk@gmail.com>
* add headers to main doc * Apply suggestions from code review * update * upload
…#11752) * Fixed: Better names for nlp variables in pipelines' tests and docs. * Fixed: Better variable names
* add `dataset_name` to data_args and added accuracy metric * added documentation for dataset_name * spelling correction
* Add Flax Examples README * Apply suggestions from code review * Update examples/flax/README.md * add nice table * fix * fix * apply suggestions * upload * finish flax readme.md Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* flax gpt2 * combine masks * handle shared embeds * add causal LM sample * style * add tests * style * fix imports, docs, quality * don't use cache * add cache * add cache 1st version * make use cache work * start adding test for generation * finish generation loop compilation * rewrite test * finish * update * update * apply sylvains suggestions * update * refactor * fix typo Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Optimizing away the `fill-mask` pipeline. - Don't send anything to the tokenizer unless needed. Vocab check is much faster - Keep BC by sending data to the tokenizer when needed. User handling warning messages will see performance benefits again - Make `targets` and `top_k` work together better `top_k` cannot be higher than `len(targets)` but can be smaller still. - Actually simplify the `target_ids` in case of duplicate (it can happen because we're parsing raw strings) - Removed useless code to fail on empty strings. It works only if empty string is in first position, moved to ignoring them instead. - Changed the related tests as only the tests would fail correctly (having incorrect value in first position) * Make tests compatible for 2 different vocabs... (at the price of a warning). Co-authored-by: @EtaoinWu * ValueError working globally * Update src/transformers/pipelines/fill_mask.py Co-authored-by: Lysandre Debut <lysandre@huggingface.co> * `tokenizer.vocab` -> `tokenizer.get_vocab()` for more compatiblity + fallback. Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Add output args to greedy search
* Fix critical typo + make style quality
* Handle generate_beam_search
* Add dict_specific tests and fix the placement of encoder outputs
* Add specific outputs
* Update doc
* Fix typo
* Adjust handling encoder_outputs + Fix generating for T5
* Fix generate for RAG
* Fix handling ouptut_attentions when target_mapping is not None
Take care of situations when target_mapping is provided
as there are 2-tuple of attentions
Change from:
if inputs["output_attentions"]:
attentions = tuple(tf.transpose(t, perm(2, 3, 0, 1)) for t in attentions)
to:
if inputs["output_attentions"]:
if inputs["target_mapping"] is not None:
# when target_mapping is provided, there are 2-tuple of attentions
attentions = tuple(
tuple(tf.transpose(attn_stream, perm=(2, 3, 0, 1)) for attn_stream in t) for t in attentions
)
else:
attentions = tuple(tf.transpose(t, perm=(2, 3, 0, 1)) for t in attentions)
* Rename kwargs to model_kwargs
* make style quality
* Move imports in test_modeling_tf_common.py
Move ModelOutput-related imports in test_modeling_tf_common.py
into the `is_tf_available():` statement.
* Rewrite nested if-statements
* Fix added tests
* add summrization script * fix arguments, preprocessing, metrics * add generation and metrics * auto model, prediction loop * prettify * label smoothing * adress Sylvain and Patricks suggestions * dynamically import shift_tokens_right * fix shift_tokens_right_fn call
* Rewrite * [ONNX] rewrite
* copy pytorch-t5 * init * boom boom * forward pass same * make generation work * add more tests * make test work * finish normal tests * make fix-copies * finish quality * correct slow example * correct slow test * version table * upload models * Update tests/test_modeling_flax_t5.py * correct incorrectly deleted line Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by: Patrick von Platen <patrick@huggingface.co>
* fix_torch_device_generate_test * remove @ * finish * make style
* fix error * make style check happy Co-authored-by: chenhaitao <chenhaitao@qiyi.com>
* Clean push to hub API * Create working dir if it does not exist * Different tweak * New API + all models + test Flax * Adds the Trainer clean up * Update src/transformers/file_utils.py Co-authored-by: Lysandre Debut <lysandre@huggingface.co> * Address review comments * (nit) output types * No need to set clone_from when folder exists * Update src/transformers/trainer.py Co-authored-by: Julien Chaumond <julien@huggingface.co> * Add generated_from_trainer tag * Update to new version * Fixes Co-authored-by: Lysandre Debut <lysandre@huggingface.co> Co-authored-by: Julien Chaumond <julien@huggingface.co> Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
* Add all XxxPreTrainedModel to the main init * Add to template * Add to template bis * Add FlaxT5
Co-authored-by: Michael Benayoun <michael@huggingface.co>
* finish t5 flax fixes * improve naming
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Signed-off-by: Richard Liaw <rliaw@berkeley.edu>
* Fix torchscript tests * Better test * Remove bogus print
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Upgrades the underlying transformers version: v4.6.1 -> v4.8.1.