* Add ResNetBackbone
* Define channels and strides as property
* Remove file
* Add test for backbone
* Update BackboneOutput class
* Remove strides property
* Fix docstring
* Add backbones to SHOULD_HAVE_THEIR_OWN_PAGE
* Fix auto mapping name
* Add sanity check for out_features
* Set stage names based on depths
* Update to tuple
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
Adds image-guided object detection method to OwlViTForObjectDetection class as described in the original paper. One-shot/ image-guided object detection enables users to use a query image to search for similar objects in the input image.
Co-Authored-By: Dhruv Karan k4r4n.dhruv@gmail.com
* Slightly alter Keras dummy loss
* Slightly alter Keras dummy loss
* Add sample weight to test_keras_fit
* Fix test_keras_fit for datasets
* Skip the sample_weight stuff for models where the model tester has no batch_size
* allow loading projection in text and vision model
* begin tests
* finish test for CLIPTextModelTest
* style
* add slow tests
* add new classes for projection heads
* remove with_projection
* add in init
* add in doc
* fix tests
* fix some more tests
* fix copies
* fix docs
* remove leftover from fix-copies
* add the head models in IGNORE_NON_AUTO_CONFIGURED
* fix docstr
* fix tests
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add docstr for models
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Try PT1.13 by removing torch scatter
* Skip failing tests
* Style
* Remvoe testing extras for repo utils
* Try with all decorators
* Try to wipe the cache
* Fix all tests?
* Try this way
* Fix comma
* Update to main
* Try with less deps
* Quality
* add `accelerate` support for `ViT` family
- add `_no_split_modules`
- manually cast to the right `dtype`: to change
* enable `float16` for `deit`
* fix `make fixup`
* add `slow` test for `fp16` inference
* another safety check
* Update src/transformers/models/deit/modeling_deit.py
* update relative positional embedding
* make fix copies
* add `use_cache` to list of arguments
* fixup
* 1line fucntion
* add `test_decoder_model_past_with_large_inputs_relative_pos_emb`
* add relative pos embedding test for more models
* style
* Fix ImageSegmentationPipelineTests
* Use 0.9
* no zip
* links to show images
* links to show images
* rebase
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* add model files etc for MobileNetV2
* rename files for MobileNetV1
* initial implementation of MobileNetV1
* fix conversion script
* cleanup
* write docs
* tweaks
* fix conversion script
* extract hidden states
* fix test cases
* make fixup
* fixup it all
* rename V1 to V2
* fix checkpoints
* fixup
* implement first block + weight conversion
* add remaining layers
* add output stride and dilation
* fixup
* add tests
* add deeplabv3+ head
* a bit of fixup
* finish deeplab conversion
* add link to doc
* fix issue with JIT trace
in_height and in_width would be Tensor objects during JIT trace, which caused Core ML conversion to fail on the remainder op. By making them ints, the result of the padding calculation becomes a constant value.
* cleanup
* fix order of models
* fix rebase error
* remove main from doc link
* add image processor
* remove old feature extractor
* fix converter + other issues
* fixup
* fix unit test
* add to onnx tests (but these appear broken now)
* add post_process_semantic_segmentation
* use google org
* remove unused imports
* move args
* replace weird assert
* Apply fix
* Fix test
* Remove another argument which is not used
* Fix pipeline test
* Add argument back, add deprecation warning
* Add warning add other location
* Use warnings instead
* Add num_channels to config
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain>
* Adding support for LayoutLMvX variants for `object-detection`.
* Revert bogs `layoutlm` feature extractor which does not exist (it was a
V2 model) .
* Updated condition.
* Handling the comments.
* move generation_*.py src files into generation/*.py
* populate generation.__init__ with lazy loading
* move imports and references from generation.xxx.object to generation.object
* Attempting to test automatically the `_keys_to_ignore`.
* Style.
* First fix pass.
* Moving test on its own.
* Another batch.
* Second round removing BatchNorm
* Fixing layoutlmv{2,3} + support older Python.
* Disable miss missing warning.
* Removing dodgy additions.
* Big pass.
* mbart.
* More corrections.
* Fixup.
* Updating test_correct_missing_keys
* Add escape hatch for when the head has no extra params so doesn't need
the missing keys check.
* Fixing test.
* Greener.
* Green ! (except for weird splinter bug).
* Adding a test about `named_parameters` usage.
* Shorten message.
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* After rebase modifications.
* More explicit condition checking.
* Fixing slow tests issues.
* Remove extra pdb.
* Remove print.
* Attempt to make failure consistent + fixing roc_bert.
* Removing the seed (all tests passing with it).
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Add first draft
* Update conversion script
* Improve conversion script
* Improve conversion script some more
* Add conditional embeddings
* Add initial decoder
* Fix activation function of decoder
* Make decoder outputs match original implementation
* Make decoder outputs match original implementation
* Add more copied from statements
* Improve model outputs
* Fix auto tokenizer file
* Fix more tests
* Add test
* Improve README and docs, improve conditional embeddings
* Fix more tests
* Remove print statements
* Remove initial embeddings
* Improve conversion script
* Add interpolation of position embeddings
* Finish addition of interpolation of position embeddings
* Add support for refined checkpoint
* Fix refined checkpoint
* Remove unused parameter
* Improve conversion script
* Add support for training
* Fix conversion script
* Add CLIPSegFeatureExtractor
* Fix processor
* Fix CLIPSegProcessor
* Fix conversion script
* Fix most tests
* Fix equivalence test
* Fix README
* Add model to doc tests
* Use better variable name
* Convert other checkpoint as well
* Update config, add link to paper
* Add docs
* Update organization
* Replace base_model_prefix with clip
* Fix base_model_prefix
* Fix checkpoint of config
* Fix config checkpoint
* Remove file
* Use logits for output
* Fix tests
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
* Add test for SentencePiece not adding special tokens to strings
* Add SentencePieceStringConversionMixin to fix issue 15003
* Fix conversion from tokens to string for most SentencePiece tokenizers
Tokenizers fixed:
- AlbertTokenizer
- BarthezTokenizer
- CamembertTokenizer
- FNetTokenizer
- M2M100Tokenizer
- MBart50Tokenizer
- PegasusTokenizer
- Speech2TextTokenizer
* Fix MarianTokenizer, adjust SentencePiece test to accomodate vocab
* Fix DebertaV2Tokenizer
* Ignore LayoutXLMTokenizer in SentencePiece string conversion test
* Run 'make style' and 'make quality'
* Clean convert_tokens_to_string test
Instead of explicitly ignoring LayoutXLMTokenizer in the test,
override the test in LayoutLMTokenizationTest and do nothing in it.
* Remove commented out code
* Improve robustness of convert_tokens_to_string test
Instead of comparing lengths of re-tokenized text and input_ids,
check that converting all special tokens to string yields a string
with all special tokens.
* Inline and remove SentencePieceStringConversionMixin
The convert_tokens_to_string method is now implemented
in each relevant SentencePiece tokenizer.
* Run 'make style' and 'make quality'
* Revert removal of space in convert_tokens_to_string
* Remove redundant import
* Revert test text to original
* Uncomment the lowercasing of the reverse_text variable
* Mimic Rust tokenizer behavior for tokenizers
- Albert
- Barthez
- Camembert
- MBart50
- T5
* Fix accidentally skipping test in wrong tokenizer
* Add test for equivalent Rust and slow tokenizer behavior
* Override _decode in BigBirdTokenizer to mimic Rust behavior
* Override _decode in FNetTokenizer to mimic Rust behavior
* Override _decode in XLNetTokenizer to mimic Rust behavior
* Remove unused 're' import
* Update DebertaV2Tokenizer to mimic Rust tokenizer
* Deberta tokenizer now behaves like Albert and its `convert_tokens_to_string` is not tested.
* Ignore problematic tests in Deberta V2
* Add comment on why the Deberta V2 tests are skipped
