1. 30 Sep, 2022 1 commit
    • NielsRogge's avatar
      Add MarkupLM (#19198) · f3d2f7a6
      NielsRogge authored
      
      
      * First draft
      
      * Make basic test work
      
      * Fix most tokenizer tests
      
      * More improvements
      
      * Make more tests pass
      
      * Fix more tests
      
      * Fix some code quality
      
      * Improve truncation
      
      * Implement feature extractor
      
      * Improve feature extractor and add tests
      
      * Improve feature extractor tests
      
      * Fix pair_input test partly
      
      * Add fast tokenizer
      
      * Improve implementation
      
      * Fix rebase
      
      * Fix rebase
      
      * Fix most of the tokenizer tests.
      
      * propose solution for fast
      
      * add: integration test for fasttokenizer, warning for decode, fix template in slow tokenizer
      
      * add: modify markuplmconverter
      
      * add: some modify on converter and tokenizerfast
      
      * Fix style, copies
      
      * Make fixup
      
      * Update tokenization_markuplm.py
      
      * Update test_tokenization_markuplm.py
      
      * Update markuplm related
      
      * Improve processor, add integration test
      
      * Add processor test file
      
      * Improve processor
      
      * Improve processor tests
      
      * Fix more processor tests
      
      * Fix processor tests
      
      * Update docstrings
      
      * Add Copied from statements
      
      * Add more Copied from statements
      
      * Add code examples
      
      * Improve code examples
      
      * Add model to doc tests
      
      * Adding dependency check
      
      * Add dummy file
      
      * Add requires_backends
      
      * Add model to toctree
      
      * Fix more things, disable dependency check for now
      
      * Apply more suggestions
      
      * Add soft dependency
      
      * Add annotators to tests
      
      * Fix style
      
      * Remove from_slow=True
      
      * Remove print statements
      
      * Add sanity check
      
      * Fix processor test
      
      * Fix processor tests, add more docs
      
      * Add doc tests for mdx file
      
      * Add more tips
      
      * Apply suggestions
      Co-authored-by: default avatarNiels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
      Co-authored-by: default avatarlockon-n <45759388+lockon-n@users.noreply.github.com>
      Co-authored-by: default avatarSaulLu <lucilesaul.com@gmail.com>
      Co-authored-by: default avatarlockon-n <dd098309@126.com>
      f3d2f7a6
  2. 29 Sep, 2022 2 commits
    • Yih-Dar's avatar
      Update Past CI report script (#19228) · 1a1893e5
      Yih-Dar authored
      
      
      * Simplify the error report
      
      * Add status placeholder
      
      * Add job links
      Co-authored-by: default avatarydshieh <ydshieh@users.noreply.github.com>
      1a1893e5
    • Aritra Roy Gosthipaty's avatar
      [TensorFlow] Adding GroupViT (#18020) · 0dc7b3a7
      Aritra Roy Gosthipaty authored
      
      
      * chore: initial commit
      
      * chore: adding util methods
      
      yet to work on the nn.functional.interpolate port with align_corener=True
      
      * chore: refactor the utils
      
      * used tf.compat.v1.image.resize to align the F.interpolate function
      * added type hints to the method signatures
      * added references to the gists where one 2 one alignment of torch and tf has been shown
      
      * chore: adding the layers
      
      * chore: porting all the layers from torch to tf
      
      This is the initial draft, nothing is tested yet.
      
      * chore: aligning the layers with reference to tf clip
      
      * chore: aligning the modules
      
      * added demaraction comments
      * added copied and adapted from comments
      
      * chore: aligning with CLIP
      
      * chore: wrangling the layers to keep it tf compatible
      
      * chore: aligning the names of the layers for porting
      
      * chore: style changes
      
      * chore: adding docs and inits
      
      * chore: adding tfp dependencis
      
      the code is taken from TAPAS
      
      * chore: initial commit for testing
      
      * chore: aligning the vision embeddings with the vit implementatino
      
      * chore: changing model prefix
      
      * chore: fixing the name of the model and the layer normalization test case
      
      * chore: every test passes but the slow ones
      
      * chore: fix style and integration test
      
      * chore: moving comments below decorators
      
      * chore: make fixup and fix-copies changes
      
      * chore: adding the Vision and Text Model to check_repo
      
      * chore: modifying the prefix name to align it with the torch implementation
      
      * chore: fix typo in configuration
      
      * choer: changing the name of the model variable
      
      * chore: adding segmentation flag
      
      * chore: gante's review
      
      * chore: style refactor
      
      * chore: amy review
      
      * chore: adding shape_list to parts that have been copied from other snippets
      
      * chore: init batchnorm with torch defaults
      
      * chore: adding shape_list to pass the tests
      
      * test fix: adding seed as 0
      
      * set seed
      
      * chore: changing the straight through trick to fix -ve dimensinos
      
      * chore: adding a dimension to the loss
      
      * chore: adding reviewers and contributors names to the docs
      
      * chore: added changes after review
      
      * chore: code quality fixup
      
      * chore: fixing the segmentation snippet
      
      * chore: adding  to the layer calls
      
      * chore: changing int32 to int64 for inputs of serving
      
      * chore: review changes
      
      * chore: style changes
      
      * chore: remove from_pt=True
      
      * fix: repo consistency
      Co-authored-by: default avatarydshieh <ydshieh@users.noreply.github.com>
      0dc7b3a7
  3. 26 Sep, 2022 1 commit
  4. 23 Sep, 2022 2 commits
  5. 22 Sep, 2022 3 commits
  6. 21 Sep, 2022 2 commits
  7. 19 Sep, 2022 1 commit
  8. 16 Sep, 2022 1 commit
  9. 14 Sep, 2022 3 commits
    • Sylvain Gugger's avatar
      Automate check for new pipelines and metadata update (#19029) · 37740101
      Sylvain Gugger authored
      * Automate check for new pipelines and metadata update
      
      * Add Datasets to quality extra
      37740101
    • Sylvain Gugger's avatar
      0b567aa4
    • NielsRogge's avatar
      Add Deformable DETR (#17281) · 59407bbe
      NielsRogge authored
      
      
      * First draft
      
      * More improvements
      
      * Improve model, add custom CUDA code
      
      * Import torch before
      
      * Add script that imports custom layer
      
      * Add everything in new ops directory
      
      * Import custom layer in modeling file
      
      * Fix ARCHIVE_MAP typo
      
      * Creating the custom kernel on the fly.
      
      * Import custom layer in modeling file
      
      * More improvements
      
      * Fix CUDA loading
      
      * More improvements
      
      * Improve conversion script
      
      * Improve conversion script
      
      * Make it work until encoder_outputs
      
      * Make forward pass work
      
      * More improvements
      
      * Make logits match original implementation
      
      * Make implementation also support single_scale model
      
      * Add support for single_scale and dilation checkpoint
      
      * Add support for with_box_refine model
      
      * Support also two stage model
      
      * Improve tests
      
      * Fix more tests
      
      * Make more tests pass
      
      * Upload all models to the hub
      
      * Clean up some code
      
      * Improve decoder outputs
      
      * Rename intermediate hidden states and reference points
      
      * Improve model outputs
      
      * Move tests to dedicated folder
      
      * Improve model outputs
      
      * Fix retain_grad test
      
      * Improve docs
      
      * Clean up and make test_initialization pass
      
      * Improve variable names
      
      * Add copied from statements
      
      * Improve docs
      
      * Fix style
      
      * Improve docs
      
      * Improve docs, move tests to model folder
      
      * Fix rebase
      
      * Remove DetrForSegmentation from auto mapping
      
      * Apply suggestions from code review
      
      * Improve variable names and docstrings
      
      * Apply some more suggestions from code review
      
      * Apply suggestion from code review
      
      * better docs and variables names
      
      * hint to num_queries and two_stage confusion
      
      * remove asserts and code refactor
      
      * add exception if two_stage is True and with_box_refine is False
      
      * use f-strings
      
      * Improve docs and variable names
      
      * Fix code quality
      
      * Fix rebase
      
      * Add require_torch_gpu decorator
      
      * Add pip install ninja to CI jobs
      
      * Apply suggestion of @sgugger
      
      * Remove DeformableDetrForObjectDetection from auto mapping
      
      * Remove DeformableDetrModel from auto mapping
      
      * Add model to toctree
      
      * Add model back to mappings, skip model in pipeline tests
      
      * Apply @sgugger's suggestion
      
      * Fix imports in the init
      
      * Fix copies
      
      * Add CPU implementation
      
      * Comment out GPU function
      
      * Undo previous change
      
      * Apply more suggestions
      
      * Remove require_torch_gpu annotator
      
      * Fix quality
      
      * Add logger.info
      
      * Fix logger
      
      * Fix variable names
      
      * Fix initializaztion
      
      * Add missing initialization
      
      * Update checkpoint name
      
      * Add model to doc tests
      
      * Add CPU/GPU equivalence test
      
      * Add Deformable DETR to pipeline tests
      
      * Skip model for object detection pipeline
      Co-authored-by: default avatarNicolas Patry <patry.nicolas@protonmail.com>
      Co-authored-by: default avatarNouamane Tazi <nouamane98@gmail.com>
      Co-authored-by: default avatarSylvain Gugger <Sylvain.gugger@gmail.com>
      59407bbe
  10. 12 Sep, 2022 1 commit
  11. 08 Sep, 2022 1 commit
    • NielsRogge's avatar
      Add X-CLIP (#18852) · bb6f6d53
      NielsRogge authored
      * First draft
      
      * Improve conversion script
      
      * Make vision encoder work
      
      * More improvements
      
      * Improve conversion script
      
      * Fix quality
      
      * Add MultiframeIntegrationTransformer
      
      * More improvements
      
      * Make MiT output work
      
      * Fix quality
      
      * Add prompts generator
      
      * Add tests
      
      * Fix some tests
      
      * Fix some more tests
      
      * Fix more tests
      
      * Improve conversion script
      
      * Fix model outputs
      
      * Fix more tests
      
      * Add XClipProcessor
      
      * Use processor in conversion script
      
      * Fix integration test
      
      * Update README, fix docs
      
      * Fix all tests
      
      * Add MIT output to XClipOutput
      
      * Create better variable names
      
      * Rename XClip to XCLIP
      
      * Extend conversion script
      
      * Add support for large models
      
      * Add support for 16 frame models
      
      * Add another model'
      
      * Fix module issue
      
      * Apply suggestions from code review
      
      * Add figure to docs
      
      * Fix CLIPProcessor issue
      
      * Apply suggestions from code review
      
      * Delete file
      
      * Convert more checkpoints
      
      * Convert last checkpoint
      
      * Update nielsr to microsoft
      bb6f6d53
  12. 02 Sep, 2022 2 commits
  13. 01 Sep, 2022 2 commits
  14. 31 Aug, 2022 1 commit
    • Ankur Goyal's avatar
      Add LayoutLMForQuestionAnswering model (#18407) · 5c4c8690
      Ankur Goyal authored
      
      
      * Add LayoutLMForQuestionAnswering model
      
      * Fix output
      
      * Remove TF TODOs
      
      * Add test cases
      
      * Add docs
      
      * TF implementation
      
      * Fix PT/TF equivalence
      
      * Fix loss
      
      * make fixup
      
      * Fix up documentation code examples
      
      * Fix up documentation examples + test them
      
      * Remove LayoutLMForQuestionAnswering from the auto mapping
      
      * Docstrings
      
      * Add better docstrings
      
      * Undo whitespace changes
      
      * Update tokenizers in comments
      
      * Fixup code and remove `from_pt=True`
      
      * Fix tests
      
      * Revert some unexpected docstring changes
      
      * Fix tests by overriding _prepare_for_class
      Co-authored-by: default avatarAnkur Goyal <ankur@impira.com>
      5c4c8690
  15. 30 Aug, 2022 3 commits
  16. 29 Aug, 2022 1 commit
  17. 25 Aug, 2022 1 commit
    • Craig Chan's avatar
      Determine framework automatically before ONNX export (#18615) · fbf382c8
      Craig Chan authored
      
      
      * Automatic detection for framework to use when exporting to ONNX
      
      * Log message change
      
      * Incorporating PR comments, adding unit test
      
      * Adding tf for pip install for run_tests_onnxruntime CI
      
      * Restoring past changes to circleci yaml and test_onnx_v2.py, tests moved to tests/onnx/test_features.py
      
      * Fixup
      
      * Adding test to fetcher
      
      * Updating circleci config to log more
      
      * Changing test class name
      
      * Comment typo fix in tests/onnx/test_features.py
      Co-authored-by: default avatarlewtun <lewis.c.tunstall@gmail.com>
      
      * Moving torch_str/tf_str to self.framework_pt/tf
      
      * Remove -rA flag in circleci config
      Co-authored-by: default avatarlewtun <lewis.c.tunstall@gmail.com>
      fbf382c8
  18. 16 Aug, 2022 1 commit
  19. 12 Aug, 2022 1 commit
    • NielsRogge's avatar
      Add Donut (#18488) · 2ab790e8
      NielsRogge authored
      
      
      * First draft
      
      * Improve script
      
      * Update script
      
      * Make conversion work
      
      * Add final_layer_norm attribute to Swin's config
      
      * Add DonutProcessor
      
      * Convert more models
      
      * Improve feature extractor and convert base models
      
      * Fix bug
      
      * Improve integration tests
      
      * Improve integration tests and add model to README
      
      * Add doc test
      
      * Add feature extractor to docs
      
      * Fix integration tests
      
      * Remove register_buffer
      
      * Fix toctree and add missing attribute
      
      * Add DonutSwin
      
      * Make conversion script work
      
      * Improve conversion script
      
      * Address comment
      
      * Fix bug
      
      * Fix another bug
      
      * Remove deprecated method from docs
      
      * Make Swin and Swinv2 untouched
      
      * Fix code examples
      
      * Fix processor
      
      * Update model_type to donut-swin
      
      * Add feature extractor tests, add token2json method, improve feature extractor
      
      * Fix failing tests, remove integration test
      
      * Add do_thumbnail for consistency
      
      * Improve code examples
      
      * Add code example for document parsing
      
      * Add DonutSwin to MODEL_NAMES_MAPPING
      
      * Add model to appropriate place in toctree
      
      * Update namespace to appropriate organization
      Co-authored-by: default avatarNiels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
      2ab790e8
  20. 10 Aug, 2022 1 commit
    • Younes Belkada's avatar
      `bitsandbytes` - `Linear8bitLt` integration into `transformers` models (#17901) · 4a51075a
      Younes Belkada authored
      
      
      * first commit
      
      * correct replace function
      
      * add final changes
      
      - works like charm!
      - cannot implement tests yet
      - tested
      
      * clean up a bit
      
      * add bitsandbytes dependencies
      
      * working version
      
      - added import function
      - added bitsandbytes utils file
      
      * small fix
      
      * small fix
      
      - fix import issue
      
      * fix import issues
      
      * Apply suggestions from code review
      Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>
      
      * refactor a bit
      
      - move bitsandbytes utils to utils
      - change comments on functions
      
      * reformat docstring
      
      - reformat docstring on init_empty_weights_8bit
      
      * Update src/transformers/__init__.py
      Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>
      
      * revert bad formatting
      
      * change to bitsandbytes
      
      * refactor a bit
      
      - remove init8bit since it is useless
      
      * more refactoring
      
      - fixed init empty weights issue
      - added threshold param
      
      * small hack to make it work
      
      * Update src/transformers/modeling_utils.py
      
      * Update src/transformers/modeling_utils.py
      
      * revmoe the small hack
      
      * modify utils file
      
      * make style + refactor a bit
      
      * create correctly device map
      
      * add correct dtype for device map creation
      
      * Apply suggestions from code review
      Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>
      
      * apply suggestions
      
      - remove with torch.grad
      - do not rely on Python bool magic!
      
      * add docstring
      
       - add docstring for new kwargs
      
      * add docstring
      
      - comment `replace_8bit_linear` function
      - fix weird formatting
      
      * - added more documentation
      - added new utility function for memory footprint tracking
      - colab demo to add
      
      * few modifs
      
      - typo doc
      - force cast into float16 when load_in_8bit is enabled
      
      * added colab link
      
      * add test architecture + docstring a bit
      
      * refactor a bit testing class
      
      * make style + refactor a bit
      
      * enhance checks
      
      - add more checks
      - start writing saving test
      
      * clean up a bit
      
      * male style
      
      * add more details on doc
      
      * add more tests
      
      - still needs to fix 2 tests
      
      * replace by "or"
      
      - could not fix it from GitHub GUI
      Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>
      
      * refactor a bit testing code + add readme
      
      * make style
      
      * fix import issue
      
      * Update src/transformers/modeling_utils.py
      Co-authored-by: default avatarMichael Benayoun <mickbenayoun@gmail.com>
      
      * add few comments
      
      * add more doctring + make style
      
      * more docstring
      
      * raise error when loaded in 8bit
      
      * make style
      
      * add warning if loaded on CPU
      
      * add small sanity check
      
      * fix small comment
      
      * add bitsandbytes on dockerfile
      
      * Improve documentation
      
      - improve documentation from comments
      
      * add few comments
      
      * slow tests pass on the VM but not on the CI VM
      
      * Fix merge conflict
      
      * make style
      
      * another test should pass on a multi gpu setup
      
      * fix bad import in testing file
      
      * Fix slow tests
      
      - remove dummy batches
      - no more CUDA illegal memory errors
      
      * odify dockerfile
      
      * Update docs/source/en/main_classes/model.mdx
      
      * Update Dockerfile
      
      * Update model.mdx
      
      * Update Dockerfile
      
      * Apply suggestions from code review
      
      * few modifications
      
      - lm head can stay on disk/cpu
      - change model name so that test pass
      
      * change test value
      
      - change test value to the correct output
      - torch bmm changed to baddmm in bloom modeling when merging
      
      * modify installation guidelines
      
      * Apply suggestions from code review
      Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>
      
      * Apply suggestions from code review
      Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>
      
      * Apply suggestions from code review
      Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>
      
      * replace `n`by `name`
      
      * merge `load_in_8bit` and `low_cpu_mem_usage`
      
      * first try - keep the lm head in full precision
      
      * better check
      
      - check the attribute `base_model_prefix` instead of computing the number of parameters
      
      * added more tests
      
      * Update src/transformers/utils/bitsandbytes.py
      Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>
      
      * Merge branch 'integration-8bit' of https://github.com/younesbelkada/transformers
      
       into integration-8bit
      
      * improve documentation
      
      - fix typos for installation
      - change title in the documentation
      Co-authored-by: default avatarSylvain Gugger <35901082+sgugger@users.noreply.github.com>
      Co-authored-by: default avatarMichael Benayoun <mickbenayoun@gmail.com>
      4a51075a
  21. 08 Aug, 2022 2 commits
  22. 05 Aug, 2022 1 commit
  23. 04 Aug, 2022 1 commit
  24. 01 Aug, 2022 2 commits
  25. 28 Jul, 2022 1 commit
  26. 26 Jul, 2022 2 commits