* started bf16 integration
* minor changes
* code now runs
* style
* lay foundation for bf16 testing
* lay foundation for bf16 testing
* start the tests
* better bf16 check
* style
* 2 separate checkers - one for bf16 support, another for bf16+autocast
* Update src/transformers/training_args.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* a couple of comment resolutions
* more comment resolutions
* resolved a small bug
* just some print statemtns
* added todo marking
* added a todo
* adjust for API change s/fast_dtype/dtype/
* fix style
* merge 2 bf16 util functions
* bf16 now does scaling too
* Add support for bfloat16
* Revert T5 layernorm to float32
This is based on the comment at https://github.com/huggingface/transformers/pull/14448/files#r752660929 and the PyTorch PR https://github.com/pytorch/pytorch/pull/66920 .
* Add comment about conversion to float32 before returning the numpy data
* Add comment about AMP-bfloat16 incompatibility
* Fix formatting
* typo
* reformer / bf16
* cleanup
* require at least pt-1.10
* fix
* will deal with deepspeed separately
* cleanup
* revert
* cleanup
* fp16_full_eval and bf16_full_eval are separate modes
* proper deprecation
* cleanup
* test and fixes
* spelling
* cleanup
* add a note that this API is experimental
Co-authored-by: jamie <jamie@cortx.com>
Co-authored-by: Stas Bekman <stas@stason.org>
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: suriya <suriya@cortx.com>
Co-authored-by: Manuel R. Ciosici <manuelrciosici@gmail.com>
* Init Flax implementation for Blenderbot
* Add a majority of stuff except for tests
* make style quality
* Add tests and fix some bugs
* Add tests
* Clean source code and fix some bugs
* Fix copies and docs
* Fix jax device condition for tests
* Fix layer norm in the encoder
* Fix a few typos in the test file
* make fix-copies
* make fix-copies
* fix layer norm
* Fix Flax params dtype (#13090)
* Fix PR reference (#13098)
* make fix-copies
* Update tests/test_modeling_flax_blenderbot.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* TF Tapas first commit
* updated docs
* updated logger message
* updated pytorch weight conversion
script to support scalar array
* added use_cache to tapas model config to
work properly with tf input_processing
* 1. rm embeddings_sum
2. added # Copied
3. + TFTapasMLMHead
4. and lot other small fixes
* updated docs
* + test for tapas
* updated testing_utils to check
is_tensorflow_probability_available
* converted model logits post processing using
numpy to work with both PT and TF models
* + TFAutoModelForTableQuestionAnswering
* added TF support
* added test for
TFAutoModelForTableQuestionAnswering
* added test for
TFAutoModelForTableQuestionAnswering pipeline
* updated auto model docs
* fixed typo in import
* added tensorflow_probability to run tests
* updated MLM head
* updated tapas.rst with TF model docs
* fixed optimizer import in docs
* updated convert to np
data from pt model is not
`transformers.tokenization_utils_base.BatchEncoding`
after pipeline upgrade
* updated pipeline:
1. with torch.no_gard removed, pipeline forward handles
2. token_type_ids converted to numpy
* updated docs.
* removed `use_cache` from config
* removed floats_tensor
* updated code comment
* updated Copyright Year and
logits_aggregation Optional
* updated docs and comments
* updated docstring
* fixed model weight loading
* make fixup
* fix indentation
* added tf slow pipeline test
* pip upgrade
* upgrade python to 3.7
* removed from_pt from tests
* revert commit f18cfa9
* Added the lang argument to apply_tesseract in feature_extraction_layoutlmv2.py, which is used in pytesseract.image_to_data.
* Added ocr_lang argument to LayoutLMv2FeatureExtractor.__init__, which is used when calling apply_tesseract
* Updated the documentation of the LayoutLMv2FeatureExtractor
* Specified in the documentation of the LayoutLMv2FeatureExtractor that the ocr_lang argument should be a language code.
* Update src/transformers/models/layoutlmv2/feature_extraction_layoutlmv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Split comment into two lines to adhere to the max line size limit.
* Update src/transformers/models/layoutlmv2/feature_extraction_layoutlmv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* added save_directories for _psave_pretrained_pt and _tf, changed model to tf_model and pt_model, enable the notebook to run cleanly from top to bottom without error
* Update quicktour.rst
* added >>>
* dependencies
* added space
When loading a pretrained tokenizer, a verification is done to ensure
that the actual tokenizer class matches the class it was called from.
If the tokenizer is absent, its config file is loaded from the repo.
However, the cache_dir for downloading is not provided, which leads to
ignoring of the user-specified cache_dir, storing files in several
places and and may result in incorrect warnings when the default
cache_dir is unreachsble.
This commit fixes that.
* [deepspeed] zero inference
* only z3 makes sense for inference
* fix and style
* docs
* rework
* fix test
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* responding to suggestions
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* remove sum for list flattening
* change to chain(*)
* make chain object a list
* delete empty lines
per sgugger's suggestions
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Nicholas Broad <nicholas@nmbroad.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
