* Replace mecab-python3 with fugashi
This replaces mecab-python3 with fugashi for Japanese tokenization. I am
the maintainer of both projects.
Both projects are MeCab wrappers, so the underlying C++ code is the
same. fugashi is the newer wrapper and doesn't use SWIG, so for basic
use of the MeCab API it's easier to use.
This code insures the use of a version of ipadic installed via pip,
which should make versioning and tracking down issues easier.
fugashi has wheels for Windows, OSX, and Linux, which will help with
issues with installing old versions of mecab-python3 on Windows.
Compared to mecab-python3, because fugashi doesn't use SWIG, it doesn't
require a C++ runtime to be installed on Windows.
In adding this change I removed some code dealing with `cursor`,
`token_start`, and `token_end` variables. These variables didn't seem to
be used for anything, it is unclear to me why they were there.
I ran the tests and they passed, though I couldn't figure out how to run
the slow tests (`--runslow` gave an error) and didn't try testing with
Tensorflow.
* Style fix
* Remove unused variable
Forgot to delete this...
* Adapt doc with install instructions
* Fix typo
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Add onnxruntime transformers optimization support
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Added Optimization section in ONNX/ONNXRuntime documentation.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Improve note reference
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Fixing imports order.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Add warning about different level of optimization between torch and tf export.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Address @LysandreJik wording suggestion
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Address @LysandreJik wording suggestion
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Always optimize model before quantization for maximum performances.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Address comments on the documentation.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Improve TensorFlow optimization message as suggested by @yufenglee
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Removed --optimize parameter
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Warn the user about current quantization limitation when model is larger than 2GB.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Trigger CI for last check
* Small change in print for the optimization section.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* 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>
* 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>
* Move torchscript and add ONNX documentation under modle_export
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Let's follow guidelines by the gurus: Renamed torchscript.rst to serialization.rst
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* Remove previously introduced tree element
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* WIP doc
Signed-off-by: Morgan Funtowicz <funtowiczmo@gmail.com>
* ONNX documentation
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Fix invalid link
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Improve spelling
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* Final wording pass
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>
* 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
