* Work on tokenizer summary
* Finish tutorial
* Link to it
* Apply suggestions from code review
Co-authored-by: Anthony MOI <xn1t0x@gmail.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Add vocab definition
Co-authored-by: Anthony MOI <xn1t0x@gmail.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* remove references to old API in docstring - update data processors
* style
* fix tests - better type checking error messages
* better type checking
* include awesome fix by @LysandreJik for #5310
* updated doc and examples
* All done
* Link to the tutorial
* Typo fixes
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
* Add metnion of the return_xxx args
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
* Quicktour part 1
* Update
* All done
* Typos
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
* Address comments in quick tour
* Update docs/source/quicktour.rst
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Update from feedback
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* ElectraForQuestionAnswering
* udate __init__
* add test for electra qa model
* add ElectraForQuestionAnswering in auto models
* add ElectraForQuestionAnswering in all_model_classes
* fix outputs, input_ids defaults to None
* add ElectraForQuestionAnswering in docs
* remove commented line
* [hf_api] Attach all unknown attributes for future-proof compatibility
* [Pipeline] NerPipeline is really a TokenClassificationPipeline
* modelcard.py: I don't think we need to force the download
* Remove config, tokenizer from SUPPORTED_TASKS as we're moving to one model = one weight + one tokenizer
* FillMaskPipeline: also output token in string form
* TextClassificationPipeline: option to return all scores, not just the argmax
* Update docs/source/main_classes/pipelines.rst
* Kill model archive maps
* Fixup
* Also kill model_archive_map for MaskedBertPreTrainedModel
* Unhook config_archive_map
* Tokenizers: align with model id changes
* make style && make quality
* Fix CI
* better api
* improve automatic setting of global attention mask
* fix longformer bug
* fix global attention mask in test
* fix global attn mask flatten
* fix slow tests
* update docstring
* update docs and make more robust
* improve attention mask
* add multiple choice for longformer
* add models to docs
* adapt docstring
* add test to longformer
* add longformer for mc in init and modeling auto
* fix tests
* first commit
* bug fixes
* better examples
* undo padding
* remove wrong VOCAB_FILES_NAMES
* License
* make style
* make isort happy
* unit tests
* integration test
* make `black` happy by undoing `isort` changes!!
* lint
* no need for the padding value
* batch_size not bsz
* remove unused type casting
* seqlen not seq_len
* staticmethod
* `bert` selfattention instead of `n2`
* uint8 instead of bool + lints
* pad inputs_embeds using embeddings not a constant
* black
* unit test with padding
* fix unit tests
* remove redundant unit test
* upload model weights
* resolve todo
* simpler _mask_invalid_locations without lru_cache + backward compatible masked_fill_
* increase unittest coverage
"Migrating from pytorch-transformers to transformers" is missing in the main document. It is available in the main `readme` thought. Just move it to the document.
* Created using Colaboratory
* [examples] reorganize files
* remove run_tpu_glue.py as superseded by TPU support in Trainer
* Bugfix: int, not tuple
* move files around
* first copy & past commit from Bert and morgans LSH code
* add easy way to compare to trax original code
* translate most of function
* make trax lsh self attention deterministic with numpy seed + copy paste code
* add same config
* add same config
* make layer init work
* implemented hash_vectors function for lsh attention
* continue reformer translation
* hf LSHSelfAttentionLayer gives same output as trax layer
* refactor code
* refactor code
* refactor code
* refactor
* refactor + add reformer config
* delete bogus file
* split reformer attention layer into two layers
* save intermediate step
* save intermediate step
* make test work
* add complete reformer block layer
* finish reformer layer
* implement causal and self mask
* clean reformer test and refactor code
* fix merge conflicts
* fix merge conflicts
* update init
* fix device for GPU
* fix chunk length init for tests
* include morgans optimization
* improve memory a bit
* improve comment
* factorize num_buckets
* better testing parameters
* make whole model work
* make lm model work
* add t5 copy paste tokenizer
* add chunking feed forward
* clean config
* add improved assert statements
* make tokenizer work
* improve test
* correct typo
* extend config
* add complexer test
* add new axial position embeddings
* add local block attention layer
* clean tests
* refactor
* better testing
* save intermediate progress
* clean test file
* make shorter input length work for model
* allow variable input length
* refactor
* make forward pass for pretrained model work
* add generation possibility
* finish dropout and init
* make style
* refactor
* add first version of RevNet Layers
* make forward pass work and add convert file
* make uploaded model forward pass work
* make uploaded model forward pass work
* refactor code
* add namedtuples and cache buckets
* correct head masks
* refactor
* made reformer more flexible
* make style
* remove set max length
* add attention masks
* fix up tests
* fix lsh attention mask
* make random seed optional for the moment
* improve memory in reformer
* add tests
* make style
* make sure masks work correctly
* detach gradients
* save intermediate
* correct backprob through gather
* make style
* change back num hashes
* rename to labels
* fix rotation shape
* fix detach
* update
* fix trainer
* fix backward dropout
* make reformer more flexible
* fix conflict
* fix
* fix
* add tests for fixed seed in reformer layer
* fix trainer typo
* fix typo in activations
* add fp16 tests
* add fp16 training
* support fp16
* correct gradient bug in reformer
* add fast gelu
* re-add dropout for embedding dropout
* better naming
* better naming
* renaming
* finalize test branch
* finalize tests
* add more tests
* finish tests
* fix
* fix type trainer
* fix fp16 tests
* fix tests
* fix tests
* fix tests
* fix issue with dropout
* fix dropout seeds
* correct random seed on gpu
* finalize random seed for dropout
* finalize random seed for dropout
* remove duplicate line
* correct half precision bug
* make style
* refactor
* refactor
* docstring
* remove sinusoidal position encodings for reformer
* move chunking to modeling_utils
* make style
* clean config
* make style
* fix tests
* fix auto tests
* pretrained models
* fix docstring
* update conversion file
* Update pretrained_models.rst
* fix rst
* fix rst
* update copyright
* fix test path
* fix test path
* fix small issue in test
* include reformer in generation tests
* add docs for axial position encoding
* finish docs
* Update convert_reformer_trax_checkpoint_to_pytorch.py
* remove isort
* include sams comments
* remove wrong comment in utils
* correct typos
* fix typo
* Update reformer.rst
* applied morgans optimization
* make style
* make gpu compatible
* remove bogus file
* big test refactor
* add example for chunking
* fix typo
* add to README
* Add GenerationPipeline
* Fix parameter names
* Correct parameter __call__ parameters
* Add model type attribute and correct function calls for prepare_input
* Take out trailing commas from init attributes
* Remove unnecessary tokenization line
* Implement support for multiple text inputs
* Apply generation support for multiple input text prompts
* Take out tensor coersion
* Take out batch index
* Add text prompt to return sequence
* Squeeze token tensore before decoding
* Return only a single list of sequences if only one prompt was used
* Correct results variable name
* Add GenerationPipeline to SUPPORTED_TASKS with the alias , initalized w GPT2
* Registedred AutoModelWithLMHead for both pt and t
* Update docstring for GenerationPipeline
* Add kwargs parameter to mode.generate
* Take out kwargs parameter after all
* Add generation pipeline example in pipeline docstring
* Fix max length by squeezing tokens tensor
* Apply ensure_tensor_on_device to pytorch tensor
* Include generation step in torch.no_grad
* Take out input from prepare_xlm_input and set 'en' as default xlm_language
* Apply framework specific encoding during prepare_input
* Format w make style
* Move GenerationPipeline import to follow proper import sorting
* Take out training comma from generation dict
* Apply requested changes
* Change name to TextGenerationPipeline
* Apply TextGenerationPipeline rename to __init___
* Changing alias to
* Set input mapping as input to ensure_tensor_on_device
* Fix assertion placement
* Add test_text_generation
* Add TextGenerationPipeline to PipelineCommonTests
* Take out whitespace
* Format __init__ w black
* Fix __init__ style
* Forman __init___
* Add line to end of __init__
* Correct model tokenizer set for test_text_generation
* Ensure to return list of list, not list of string (to pass test)
* Limit test models to only 3 to limit runtime to address circleCI timeout error
* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>
* Update tests/test_pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>
* Remove argument docstring, __init__, add additional __call__ arguments, and reformat results to list of dict
* Fix blank result list
* Add TextGenerationPipeline to pipelines.rst
* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>
* Fix typos from adding PADDING_TEXT_TOKEN_LENGTH
* Fix incorrectly moved result list
* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/pipelines.py
* Update src/transformers/pipelines.py
* Update src/transformers/pipelines.py
* Update src/transformers/pipelines.py
* Update src/transformers/pipelines.py
* Update src/transformers/pipelines.py
* Update src/transformers/pipelines.py
* Update src/transformers/pipelines.py
* Update src/transformers/pipelines.py
* Update src/transformers/pipelines.py
* Update src/transformers/pipelines.py
* Update src/transformers/pipelines.py
Co-Authored-By: Patrick von Platen <patrick.v.platen@gmail.com>
* Add back generation line and make style
* Take out blank whitespace
* Apply new alis, text-generation, to test_pipelines
* Fix text generation alias in test
* Update src/transformers/pipelines.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Julien Chaumond <chaumond@gmail.com>
* First pass on utility classes and python tokenizers
* finishing cleanup pass
* style and quality
* Fix tests
* Updating following @mfuntowicz comment
* style and quality
* Fix Roberta
* fix batch_size/seq_length inBatchEncoding
* add alignement methods + tests
* Fix OpenAI and Transfo-XL tokenizers
* adding trim_offsets=True default for GPT2 et RoBERTa
* style and quality
* fix tests
* add_prefix_space in roberta
* bump up tokenizers to rc7
* style
* unfortunately tensorfow does like these - removing shape/seq_len for now
* Update src/transformers/tokenization_utils.py
Co-Authored-By: Stefan Schweter <stefan@schweter.it>
* Adding doc and docstrings
* making flake8 happy
Co-authored-by: Stefan Schweter <stefan@schweter.it>
* Add clear description of how to train T5
* correct docstring in T5
* correct typo
* correct docstring format
* update t5 model docs
* implement collins feedback
* fix typo and add more explanation for sentinal tokens
* delete unnecessary todos
* passing
* Undo stupid chg
* docs
* undo rename
* delete-cruft
* only import if you have torch
* Dont rely on dict ordering
* Fix dict ordering upstream
* docstring link
* docstring link
* remove trailing comma for 3.5 compat
* new name
* delegate kwarging
* Update kwargs
* memory benchmark rss
* have both forward pass and line-by-line mem tracing
* cleaned up tracing
* refactored and cleaning up API
* no f-strings yet...
* add GPU mem logging
* fix GPU memory monitoring
* style and quality
* clean up and doc
* update with comments
* Switching to python 3.6+
* fix quality
* Pipeline doc initial commit
* pipeline abstraction
* Remove modelcard argument from pipeline
* Task-specific pipelines can be instantiated with no model or tokenizer
* All pipelines doc
* Usage: Sequence Classification & Question Answering
* Pipeline example
* Language modeling
* TensorFlow code for Sequence classification
* Custom TF/PT toggler in docs
* QA + LM for TensorFlow
* Finish Usage for both PyTorch and TensorFlow
* Addressing Julien's comments
* More assertive
* cleanup
* Favicon
- added favicon option in conf.py along with the favicon image
- udpated 🤗 logo. slightly smaller and should appear more consistent across editing programs (no more tongue on the outside of the mouth)
Co-authored-by: joshchagani <joshua@joshuachagani.com>
Use -e only in docs targeted at contributors.
If a user copy-pastes command line with [--editable], they will hit
an error. If they don't know the --editable option, we're giving them
a choice to make before they can move forwards, but this isn't a choice
they need to make right now.
* Switch to plain unittest for skipping slow tests.
Add a RUN_SLOW environment variable for running them.
* Switch to plain unittest for PyTorch dependency.
* Switch to plain unittest for TensorFlow dependency.
* Avoid leaking open files in the test suite.
This prevents spurious warnings when running tests.
* Fix unicode warning on Python 2 when running tests.
The warning was:
UnicodeWarning: Unicode equal comparison failed to convert both arguments to Unicode - interpreting them as being unequal
* Support running PyTorch tests on a GPU.
Reverts 27e015bd.
* Tests no longer require pytest.
* Make tests pass on cuda
