1. 18 Nov, 2021 4 commits
    • 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
    • NielsRogge's avatar
      Fix code example (#14441) · 08816de1
      NielsRogge authored
      08816de1
    • William Held's avatar
      Recover Deleted XNLI Instructions (#14437) · 01f8e639
      William Held authored
      01f8e639
  2. 17 Nov, 2021 6 commits
  3. 16 Nov, 2021 5 commits
  4. 15 Nov, 2021 8 commits
  5. 14 Nov, 2021 1 commit
  6. 13 Nov, 2021 2 commits
  7. 12 Nov, 2021 4 commits
    • Li-Huai (Allan) Lin's avatar
      Use `AlbertConverter` for FNet instead of using FNet's own converter (#14365) · 280a811e
      Li-Huai (Allan) Lin authored
      * Add normalizer to FNetConverter
      
      * Style
      
      * Directly use AlbertConverter
      280a811e
    • Patrick von Platen's avatar
      [Wav2Vec2 Example] Improve fine-tuning script (#14373) · 55f49c5f
      Patrick von Platen authored
      * improve some stuff
      
      * finish
      
      * correct last
      55f49c5f
    • Suraj Patil's avatar
      fix docs (#14377) · 21546e59
      Suraj Patil authored
      21546e59
    • 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
  8. 11 Nov, 2021 7 commits
  9. 10 Nov, 2021 3 commits