1. 29 Sep, 2022 2 commits
    • 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
    • Gabriele Sarti's avatar
      XGLM - Fix Softmax NaNs when using FP16 (#18057) · 9d732fd2
      Gabriele Sarti authored
      
      
      * fix fp16 for xglm
      
      * Removed misleading comment
      
      * Fix undefined variable
      Co-authored-by: default avatarGabriele Sarti <gsarti@amazon.com>
      Co-authored-by: default avatarydshieh <ydshieh@users.noreply.github.com>
      Co-authored-by: default avatarYounes Belkada <49240599+younesbelkada@users.noreply.github.com>
      9d732fd2
  2. 27 Sep, 2022 2 commits
  3. 26 Sep, 2022 3 commits
  4. 23 Sep, 2022 1 commit
  5. 22 Sep, 2022 5 commits
  6. 21 Sep, 2022 3 commits
  7. 20 Sep, 2022 3 commits
  8. 16 Sep, 2022 4 commits
  9. 15 Sep, 2022 8 commits
  10. 14 Sep, 2022 9 commits
    • SaulLu's avatar
    • Sylvain Gugger's avatar
      4eb36f29
    • Shinya Otani's avatar
      Add support for Japanese GPT-NeoX-based model by ABEJA, Inc. (#18814) · f5f430e5
      Shinya Otani authored
      * add gpt-neox-japanese model and tokenizer as new model
      
      * Correction to PR's comment for GPT NeoX Japanese
      - Fix to be able to use gpu
      - Add comment # Copied... at the top of RotaryEmbedding
      - Implement nn.Linear instead of original linear class
      - Add generation test under @slow
      
      * fix bias treatment for gpt-neox-japanese
      
      * Modidy gpt-neox-japanese following PR
      - add doc for bias_dropout_add
      - style change following a PR comment
      
      * add document for gpt-neox-japanese
      
      * remove unused import from gpt-neox-japanese
      
      * fix README for gpt-neox-japanese
      f5f430e5
    • Yih-Dar's avatar
      Fix `DocumentQuestionAnsweringPipelineTests` (#19023) · 6a9726ec
      Yih-Dar authored
      
      
      * Fix DocumentQuestionAnsweringPipelineTests
      Co-authored-by: default avatarydshieh <ydshieh@users.noreply.github.com>
      6a9726ec
    • Sylvain Gugger's avatar
      Typo fix · 1207deb8
      Sylvain Gugger authored
      1207deb8
    • Sylvain Gugger's avatar
      e1224a2a
    • Yih-Dar's avatar
      Fix CI for `PegasusX` (#19025) · 77b18783
      Yih-Dar authored
      
      
      * Skip test_torchscript_output_attentions for PegasusXModelTest
      
      * fix test_inference_no_head
      
      * fix test_inference_head
      
      * fix test_seq_to_seq_generation
      Co-authored-by: default avatarydshieh <ydshieh@users.noreply.github.com>
      77b18783
    • Sylvain Gugger's avatar
      Make AutoProcessor a magic loading class for all modalities (#18963) · 6f8f2f6a
      Sylvain Gugger authored
      * Make AutoProcessor a magic loading class for all modalities
      
      * Quality
      6f8f2f6a
    • 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