* 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>
* test: make sure model configs are jsonifiable
* fix: return python dict instead of config object
* fix: accept pretrained config and use correct class
* Re-enabling slow tests and applying them to core models only
* Re-enabling slow tests and applying them to core models only
* Add new test file to fetcher
* Remove tooslow tests from test_modeling_tf_common.py
* make style
* Style fixes
* Style fixes
* Style fixes
* Style fixes
* Adding core tests to GPT2 and BART
* Removing unused imports
Co-authored-by: niklas.fruehauf <niklas.fruehauf@sovanta.com>
Co-authored-by: matt <rocketknight1@gmail.com>
* add new wav2vec2 translation
* correct
* up
* add tests
* correct end copy
* correct more
* up
* correct unispeech sat
* finish
* finalize
* finish
* up
* stop training when a finite IterableDataset is exhausted
when using an iterable dataset num_epochs is set to
sys.maxsize to make sure all data is consumed
likewise we want to set max_steps high enough
but still stop when all data is consumed
(cherry picked from commit 6f0e1d6363153da9051e93acffe1cbab3a3f3b12)
* fix typo flase -> false
* add test for stopping training on exhausted finite iterable dataset
* remove redundant gradient_accumulation_steps
* run make style
reformat training_args docstring
* Fix gradient_checkpointing backward compatibility
* Remove needless line
* make sure mask prob is big enough and length small enough
* Fix tests
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>
