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  1. 03 Dec, 2021 1 commit
    • Li-Huai (Allan) Lin's avatar
      Improve tokenizer tests (#13594) · 66ea7391
      Li-Huai (Allan) Lin authored
      * Use new method to acquire tokenizers
      
      * Resolve TODOs.
      
      * Style
      
      * Fix
      
      * Enable do_lower_case in test_tokenize_special_tokens
      
      * Apply suggestion from code review
      
      * Fix mask token handling
      
      * Revert "Fix mask token handling"
      
      This reverts commit daaa3f5291b1f71e5bc3604ca281c000000c4648.
      
      * Fix FNet mask token tokenization
      
      * Complete everything
      
      * Apply suggestions from code review
      66ea7391
  2. 02 Dec, 2021 2 commits
    • Nik's avatar
      fix #14524 (IndexError when mask prob is too low) (#14525) · 6645eb61
      Nik authored
      * fix #14524 (IndexError when mask prob is too low)
      
      * fix formatting
      
      * correct documentation, add option for setting min_num_masks
      
      * change the semantic meaning of `mask_prob` in _compute_mask_indices
      
      With this commit the meaing of `mask_prob` actually adhered to the probability for each
      vector to be the start of a masked span of length.
      
      * fix check_copies test
      
      * fix documentation to semantic meaning of `upper bound of overall masking percentage`, revert changes to _compute_mask_indices
      
      * fix typo
      6645eb61
    • Daniel Stancl's avatar
      [Flax] Add FlaxBlenderbotSmall (#14576) · 50d909be
      Daniel Stancl authored
      
      
      * [WIP] Add FlaxBlenderbotSmall
      
      * Revert some unintentionally changed files
      
      Revert some unintentionally files changed by improperly filled cookiecutter instructions.
      
      * Fix repo consistency
      
      * Fix Flax-PT equivalence
      
      * Apply suggestions from code review
      
      * Update index.mdx
      
      * Apply suggestions from code review
      Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>
      50d909be
  3. 01 Dec, 2021 2 commits
  4. 30 Nov, 2021 3 commits
    • Suraj Patil's avatar
      VisionTextDualEncoder (#13511) · fc1d97f2
      Suraj Patil authored
      
      
      * init vision_text_dual_encoder
      
      * fix merge
      
      * remove extra heads
      
      * fix tests
      
      * remove VISION_TEXT_DUAL_ENCODER_PRETRAINED_CONFIG_ARCHIVE_MAP
      
      * remove archive map
      
      * fix imports
      
      * fix more imports
      
      * fix init
      
      * delete tokenizers
      
      * fix imports
      
      * clean
      
      * support clip's vision model
      
      * handle None config
      
      * begin tests
      
      * more test and few fixes
      
      * warn about newly init weights
      
      * more tests
      
      * add loss to model
      
      * remove extra classes from doc
      
      * add processor
      
      * doc and small fixes
      
      * add start docstr
      
      * update flax model
      
      * flax tests
      
      * more flax tests
      
      * doc
      
      * quality
      
      * doc and quality
      
      * fix doc
      
      * doc
      
      * remove comments
      
      * update warning
      
      * quality
      
      * fix docs
      
      * Apply suggestions from code review
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      
      * replace asserts, fix imports
      
      * update imports
      
      * fix import
      
      * address some review comments
      
      * fix check
      
      * reduce tolerance
      
      * fix test
      
      * add flax integration test
      
      * Apply suggestions from code review
      Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>
      
      * address Sylvain's comments
      
      * fix style
      
      * add pt_flax_equivalence test in PT tests
      
      * add pt integration test
      
      * update test
      
      * use pre-trained checkpoint in examples
      Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>
      fc1d97f2
    • Daniel Stancl's avatar
      [Flax] Add FlaxBlenderbot (#13633) · faacd747
      Daniel Stancl authored
      
      
      * 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: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>
      faacd747
    • Kamal Raj's avatar
      Tapas tf (#13393) · c468a87a
      Kamal Raj authored
      * 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
      c468a87a
  5. 29 Nov, 2021 1 commit
  6. 25 Nov, 2021 1 commit
  7. 24 Nov, 2021 1 commit
  8. 23 Nov, 2021 1 commit
  9. 22 Nov, 2021 2 commits
  10. 19 Nov, 2021 4 commits
  11. 18 Nov, 2021 3 commits
    • Sylvain Gugger's avatar
    • NielsRogge's avatar
      Add ImageGPT (#14240) · da36c557
      NielsRogge authored
      * First draft
      
      * More improvements
      
      * Improve conversion script
      
      * Fix init weights for layer norm
      
      * Fix correct model for conversion script
      
      * Don't tie input and output embeddings
      
      * Add print statements for debugging
      
      * Add print statements for debugging
      
      * Fix vocab size of model
      
      * Improve documentation, remove fast tokenizer
      
      * Add ImageGPTForImageClassification, improve docs
      
      * Fix docs issue
      
      * Set verbosity level back to info
      
      * Improve tests
      
      * Fix tests and add figure
      
      * Delete tokenizer file
      
      * Remove ImageGPTTokenizer from init files
      
      * Remove ImageGPTLayer from init files
      
      * Remove ImageGPT tokenizer from docs
      
      * First draft of ImageGPTFeatureExtractor
      
      * Fix typo
      
      * Fix bug
      
      * More improvements
      
      * Apply suggestions from code review, add tests for feature extractor
      
      * Fix layernorm
      
      * Update save_pretrained method
      
      * Fix issue
      
      * Make all tests of ImageGPTFeatureExtractor pass
      
      * Update code examples
      
      * Rename model inputs to pixel_values
      
      * Improve code examples
      
      * Update init_weights to post_init
      
      * Fix post_init
      da36c557
    • Sylvain Gugger's avatar
      Add a post init method to all models (#14431) · d83b0e0c
      Sylvain Gugger authored
      * Add a post init method to all models
      
      * Fix tests
      
      * Fix last tests
      
      * Fix templates
      
      * Add comment
      
      * Forgot to save
      d83b0e0c
  12. 17 Nov, 2021 3 commits
    • N's avatar
      [WIP] Ensure TF model configs can be converted to proper JSON (#14415) · 1991da07
      N authored
      
      
      * 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: default avatarniklas.fruehauf <niklas.fruehauf@sovanta.com>
      Co-authored-by: default avatarmatt <rocketknight1@gmail.com>
      1991da07
    • NielsRogge's avatar
      Improve semantic segmentation models (#14355) · a2864a50
      NielsRogge authored
      * Improve tests
      
      * Improve documentation
      
      * Add ignore_index attribute
      
      * Add semantic_ignore_index to BEiT model
      
      * Add segmentation maps argument to BEiTFeatureExtractor
      
      * Simplify SegformerFeatureExtractor and corresponding tests
      
      * Improve tests
      
      * Apply suggestions from code review
      
      * Minor docs improvements
      
      * Streamline segmentation map tests of SegFormer and BEiT
      
      * Improve reduce_labels docs and test
      
      * Fix code quality
      
      * Fix code quality again
      a2864a50
    • Patrick von Platen's avatar
      [Wav2Vec2] Add New Wav2Vec2 Translation (#14392) · 700a748f
      Patrick von Platen authored
      * add new wav2vec2 translation
      
      * correct
      
      * up
      
      * add tests
      
      * correct end copy
      
      * correct more
      
      * up
      
      * correct unispeech sat
      
      * finish
      
      * finalize
      
      * finish
      
      * up
      700a748f
  13. 16 Nov, 2021 2 commits
    • Valentin's avatar
      Avoid looping when data exhausted (#14413) · a33168aa
      Valentin authored
      * 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
      a33168aa
    • Sylvain Gugger's avatar
      Fix gradient_checkpointing backward compatibility (#14408) · 040fd471
      Sylvain Gugger authored
      
      
      * Fix gradient_checkpointing backward compatibility
      
      * Remove needless line
      
      * make sure mask prob is big enough and length small enough
      
      * Fix tests
      Co-authored-by: default avatarpatrickvonplaten <patrick.v.platen@gmail.com>
      040fd471
  14. 15 Nov, 2021 4 commits
  15. 13 Nov, 2021 1 commit
  16. 12 Nov, 2021 1 commit
    • Nicolas Patry's avatar
      Adding support for raw python `generator` in addition to `Dataset` for pipelines (#14352) · ed5d1551
      Nicolas Patry authored
      * Adding support for raw python `generator` in addition to `Dataset`
      
      The main goal is to ease the create of streaming data to the pipe.
      
      `Dataset` is more involved and pytorch specific.
      
      This PR, provides a way to use a python iterator too.
      This enabled #14250 but can be proposed as a standalone PR.
      
      ```python
      from transformers import pipeline
      
      def read_data(filename):
          with open(filename, 'r') as f:
              for line in f:
                  yield f
      
      pipe = pipeline("text-classification")
      for classified in pipe(read_data("large_file.txt")):
          print("Success ! ", classified)
      ```
      
      The main caveat of this, is the interaction with `DataLoader` with
      `num_workers>1`. When you have multiple workers, each receive a copy
      of the generator (like `IterableDataset`). That means the naive Iterator
      will fail since all workers iterate on all items of the generator.
      
      There are ways to do clever "skipping", but it could be bad still
      because all workers still do have to pass through all items of the
      generator (they just ignore items they don't handle), depending on
      the case it might be bad.
      
      Using `num_workers=1` is the simplest fix and if the cost of loading
      your data is small enough should be good enough. In the above example
      trying to do smart tricks to skip some lines is unlikely to be a net
      positive for instance.
      
      If there are better ways to do "jumps" on some data, then using
      `Dataset` is more advised (since then differents workers can just jump
      themselves).
      
      * Adding iterator support for `tf` too.
      ed5d1551
  17. 11 Nov, 2021 4 commits
  18. 10 Nov, 2021 2 commits
  19. 09 Nov, 2021 2 commits