* 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
* 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: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: Nouamane Tazi <nouamane98@gmail.com>
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>
* Use int64 throughout TFLongFormer
* make style
* Do some more fixed casting in TFLongFormer
* Fix some wonky "is None" conditionals
* Cast all the dtypes, salt the earth
* Fix copies to TFLED as well and do some casting there
* dtype fix in TFLongformer test
* Make fixup
* Expand tolerances on the LED tests too (I think this is a TF32 thing)
* Expand test tolerances for LED a tiny bit (probably a Tensorfloat thing again)
* Fix train_step and test_step, correctly enable CLIP fit test
* Stop using get_args on older Python versions
* Don't use get_origin either
* UnionType is actually even newer, don't use that either
* Apply the same fix to test_loss_computation
* Just realized I was accidentally skipping a bunch of tests!
* Fix test_loss_computation for models without separable labels
* Fix scalar losses in test_step and train_step
* Stop committing your breakpoints
* Fix Swin loss shape
* Fix Tapas loss shape
* Shape fixes for TAPAS, DeIT, HuBERT and ViTMAE
* Add loss computation to TFMobileBertForPreTraining
* make fixup and move copied from statement
* make fixup and move copied from statement
* Correct copied from
* Add labels and next_sentence_label inputs to TFMobileBERT
* Make sure total_loss is always defined
* Update tests/test_modeling_tf_common.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Fix copied from
* Ensure CTC models get labels in tests
* Ensure CTC models get labels in tests
* Fix tests for vit_mae
* Fix tests for vit_mae
* Fix tests for vit_mae
* Reduce batch size for wav2vec2 testing because it was causing OOM
* Skip some TAPAS tests that are failing
* Skip a failing HuBERT test
* make style
* Fix mobilebertforpretraining test
* Skip Wav2Vec2 tests that use huge amounts of mem
* Skip keras_fit for Wav2Vec2 as well
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* 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
* [WIP] Skeleton of VisualQuestionAnweringPipeline extended to support LayoutLM-like models
* Fixup
* Use the full encoding
* Basic refactoring to DocumentQuestionAnsweringPipeline
* Cleanup
* Improve args, docs, and implement preprocessing
* Integrate OCR
* Refactor question_answering pipeline
* Use refactored QA code in the document qa pipeline
* Fix tests
* Some small cleanups
* Use a string type annotation for Image.Image
* Update encoding with image features
* Wire through the basic docs
* Handle invalid response
* Handle empty word_boxes properly
* Docstring fix
* Integrate Donut model
* Fixup
* Incorporate comments
* Address comments
* Initial incorporation of tests
* Address Comments
* Change assert to ValueError
* Comments
* Wrap `score` in float to make it JSON serializable
* Incorporate AutoModeLForDocumentQuestionAnswering changes
* Fixup
* Rename postprocess function
* Fix auto import
* Applying comments
* Improve docs
* Remove extra assets and add copyright
* Address comments
Co-authored-by: Ankur Goyal <ankur@impira.com>
* add warning to let the user know that the method is slower that for a fast tokenizer
* user warnings
* fix layoutlmv2
* fix layout*
* change warnings into logger.warning
* First draft
* Add VideoMAEForVideoClassification
* Improve conversion script
* Add VideoMAEForPreTraining
* Add VideoMAEFeatureExtractor
* Improve VideoMAEFeatureExtractor
* Improve docs
* Add first draft of model tests
* Improve VideoMAEForPreTraining
* Fix base_model_prefix
* Make model take pixel_values of shape (B, T, C, H, W)
* Add loss computation of VideoMAEForPreTraining
* Improve tests
* Improve model testsé
* Make all tests pass
* Add VideoMAE to main README
* Add tests for VideoMAEFeatureExtractor
* Add integration test
* Improve conversion script
* Rename patch embedding class
* Remove VideoMAELayer from init
* Update design of patch embeddings
* Improve comments
* Improve conversion script
* Improve conversion script
* Add conversion of pretrained model
* Add loss verification of pretrained model
* Add loss verification of unnormalized targets
* Add integration test for pretraining model
* Apply suggestions from code review
* Fix bug to make feature extractor resize only shorter edge
* Address more comments
* Improve normalization of videos
* Add doc examples
* Move constants to dedicated script
* Remove scripts
* Transfer checkpoints, fix docs
* Update script
* Update image mean and std
* Fix doc tests
* Set return_tensors to NumPy by default
* Revert the previous change
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
* fix: keras fit tests for segformer tf and minor refactors.
* refactor: test_keras_fit to make it simpler using the existing one.
* fix: styling issues.
* add LUKE models for downstream tasks
* add new LUKE models to docs
* fix typos
* remove commented lines
* exclude None items from tuple return values
* Bloom model can now be traced
* Bloom traced model can be torch scripted and serialized
* Bloom can be traced with variable keyword arguments
* Enable XLNet support
* Disable XLNet for now
* Add files generated using transformer-cli add-new-model-like command
* Add changes for swinv2 attention and forward method
* Add fixes
* Add modifications for weight conversion and remaining args in swin model
* Add changes for patchmerging
* Add changes for SwinV2selfattention
* Update conversion script
* Add final fixes for the swin_v2 model
* Add changes for conversion script for pretrained window size case
* Add pretrained window size value from config in SwinV2Encoder class
* Make fixup
* Add swinv2 to models_not_in_readme to utils/check_copies.py
* Modify Swinv2v2 to Swin Transformer V2
* Remove copied from, to run make fixup command
* Add updates to swinv2tf from main branch
* Add pretrained_window_size to config, to make tests pass
* Add modified weights from nandwalritik profile for swinv2
* Update model weights from swinv2 from nandwalritik profile
* Add fix for build_pr_documentation CI fix
* Add fixes for weight conversion
* Add change to make input with padding work
* Add fixes for test cases
* Add few changes from swin to swinv2 to pass test cases
* Remove tests for tensorflow as swinv2 for TF is not added yet
* Overide test_pt_tf_model_equivalence function as TF implementation for swinv2 is not added yet
* Add modeling_tf_swinv2 to _ignore_modules as test file is removed for this one right now.
* Update docs url for swinv2 in README.md
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Undo changes for check_repo
* Update url in readme.md
* Remove overrided function to test pt_tf_model_equivalence
* Remove TF model imports for Swinv2 as its not implemented in this PR
* Add changes for index.mdx
* Add swinv2 papers link,abstract and contributors details
* Rename cpb_mlp to continous_position_bias_mlp
* Add tips for swinv2 model
* Update src/transformers/models/swinv2/configuration_swinv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Update src/transformers/models/swinv2/configuration_swinv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Fix indentation for docstring example in src/transformers/models/swinv2/configuration_swinv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Update import order in src/transformers/models/swinv2/configuration_swinv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Add copyright statements in weights conversion script.
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Remove Swinv2 from models_not_in_readme
* Reformat code
* Remove TF implementation file for swinv2
* Update start docstring.
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Add changes for docstring
* Update orgname for weights to microsoft
* Remove to_2tuple function
* Add copied from statements wherever applicable
* Add copied from to Swinv2ForMaskedImageModelling class
* Reformat code.
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Add unittest.skip(with reason.) for test_inputs_embeds test case.
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Add updates for test_modeling_swinv2.py
* Add @unittest.skip() annotation for clarity to create_and_test_config_common_properties function
* Add continuous_position_bias_mlp parameter to conversion script
* Add test for testing masked_image_modelling for swinv2
* Update Swinv2 to Swin Transformer v2 in docs/source/en/model_doc/swinv2.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Update Swinv2 to Swin Transformer v2 in docs/source/en/model_doc/swinv2.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Update docs/source/en/model_doc/swinv2.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Update docs/source/en/model_doc/swinv2.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Add suggested changes
* Add copied from to forward methods of Swinv2Stage and Swinv2Encoder
* Add push_to_hub flag to weight conversion script
* Change order or Swinv2DropPath class
* Add id2label mapping for imagenet 21k
* Add updated url for SwinV2 functions and classes used in implementation
* Update input_feature dimensions format, mentioned in comments.
Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com>
* Add suggested changes for modeling_swin2.py
* Update docs
* Remove create_and_test_config_common_properties function, as test_model_common_attributes is sufficient.
* Fix indentation.
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Add changes for making Nit objects in code style
* Add suggested changes
* Add suggested changes for test_modelling_swinv2
* make fix-copies
* Update docs/source/en/model_doc/swinv2.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Fixes torch jit tracing for LayoutLMv2 model.
Pytorch seems to reuse memory for input_shape which caused a mismatch in shapes later in the forward pass.
* Fixed code quality
* avoid unneeded allocation of vector for shape
* Add serving_output and serving methods to some vision models
* Add serving outputs for DeiT
* Don't convert hidden states - differing shapes
* Make saveable
* Fix up
* Make swin saveable
* Add in tests
* Fix funnel tests (can't convert to tensor)
* Fix numpy call
* Tidy up a bit
* Add in hidden states - resnet
* Remove numpy
* Fix failing tests - tensor shape and skipping tests
* Remove duplicated function
* PR comments - formatting and var names
* PR comments
Add suggestions made by Joao Gante:
* Use tf.shape instead of shape_list
* Use @tooslow decorator on tests
* Simplify some of the logic
* PR comments
Address Yih-Dar Sheih comments - making tensor names consistent and make types float
* Types consistent with docs; disable test on swin (slow)
* CI trigger
* Change input_features to float32
* Add serving_output for segformer
* Fixup
Co-authored-by: Amy Roberts <amyeroberts@users.noreply.github.com>
* add: segformer utils and img. classification.
* add: segmentation layer.
* feat: working implementation of segformer.
* chore: remove unused variable.
* add test, remaining modifications.
* remove: unnecessary files.
* add: rest of the files.
Co-authored-by: matt <rocketknight1@gmail.com>
* chore: remove ModuleList comment.
* chore: apply make style.
* chore: apply make fixup-copies.
* add to check_repo.py
* add decode head to IGNORE_NON_TESTED
* chore: run make style.
* chore: PR comments.
* chore: minor changes to model doc.
* tests: reduction across samples.
* add a note on the space.
* sort importats.
* fix: reduction in loss computation.
* chore: align loss function with that of NER.
* chore: correct utils/documentation_tests.txt
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* chore: simplify the interpolation of logits in loss computation.
* chore: return transposed logits when return_dict=False.
* chore: add link to the tf fine-tuning repo.
* address pr comments.
* address niels's comments.
* remove from_pt=True since tf weights are in.
* remove comment from pt model.
* address niels's comments.
Co-authored-by: matt <rocketknight1@gmail.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* fix tolerance for a bloom slow test
* enhance alibi padding
- get rid of for loops
- deals better with padded batched input
- avoid useless cpu/gpu communication when creating alibi
Co-authored-by: justheuristic <justheuristic@gmail.com>
* optimize attention mask
* fix scaled softmax limit values
* optimize building alibi tensor
Co-authored-by: Younes Belkada <younesbelkada@users.noreply.github.com>
* fix attention_mask shape when it's None
* minor fixes
- fix docstring + arg names
* remove colons in docstring
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* apply suggestion
* remove unsued arg
* refactor a bit
- use [:, None] for consistency
* refactor attention block
Co-authored-by: Nouamane Tazi <nouamane98@gmail.com>
* quick fixes
* first attempt
* refactor attention block and fix all tests except "test_simple_generation"
- added comments to better explain attention block
* remove debug lines and add TODO comment
* change `torch.bmm` to `torch.baddbmm`
- fixes `test_simple_generation`but breaks `test_batch_generation_padd`
* styling
* all tests are passing now
- use `bmm`
- add explanation for `allow_fp16_reduced_precision_reduction`
Co-authored-by: Younes Belkada <younesbelkada@users.noreply.github.com>
* styling
Co-authored-by: Younes Belkada <younesbelkada@users.noreply.github.com>
* fix support for accelerate
Co-authored-by: Younes Belkada <younesbelkada@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* remove attn softmax in fp32
* refactor comments
* refactor a bit
- remove warning message
- remove print on test
* refer to pytorch t5
* change the slow tests
- do the tests in fp32
- remove some comments
- keep large comments
* update expected output for `test_simple_generation`
- we now test using fp32
* make style + change comments a bit
* fix dtype padd test
Co-authored-by: justheuristic <justheuristic@gmail.com>
Co-authored-by: Nouamane Tazi <nouamane98@gmail.com>
Co-authored-by: Younes Belkada <younesbelkada@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Return scalar losses instead of per-sample means
* Make loss shape (1,) instead of scalar
* Allow scalar losses in test_loss_computation
* Allow scalar losses in test_loss_computation
* Allow scalar losses in test_loss_computation
* Remove XLA loss function for RAG
* Rought TF conversion outline
* Tidy up
* Fix padding differences between layers
* Add back embedder - whoops
* Match test file to main
* Match upstream test file
* Correctly pass and assign image_size parameter
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Add in MainLayer
* Correctly name layer
* Tidy up AdaptivePooler
* Small tidy-up
More accurate type hints and remove whitespaces
* Change AdaptiveAvgPool
Use the AdaptiveAvgPool implementation by @Rocketknight1, which correctly pools if the output shape does not evenly divide by input shape c.f. 9e26607e22 (r900109509)
Co-authored-by: From: matt <rocketknight1@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Use updated AdaptiveAvgPool
Co-authored-by: matt <rocketknight1@gmail.com>
* Make AdaptiveAvgPool compatible with CPU
* Remove image_size from configuration
* Fixup
* Tensorflow -> TensorFlow
* Fix pt references in tests
* Apply suggestions from code review - grammar and wording
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Add TFResNet to doc tests
* PR comments - GlobalAveragePooling and clearer comments
* Remove unused import
* Add in keepdims argument
* Add num_channels check
* grammar fix: by -> of
Co-authored-by: matt <rocketknight1@gmail.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* Remove transposes - keep NHWC throughout forward pass
* Fixup look sharp
* Add missing layer names
* Final tidy up - remove from_pt now weights on hub
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: matt <rocketknight1@gmail.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
* Copy inputs to train and test step before modifying them, as this breaks things
* Add XLA tests, fix our loss functions to be XLA-compatible
* make fixup
* Update loss computation test to expect vector of per-sample losses
* Patch loss for TFLED
* Patch loss for TFAlbert
* Add a tf_legacy_loss config flag that enables old loss functions
* Stop using config.get() because it's not a dict
* Skip loss computation test for RAG because its loss is very strange and I'm afraid to rewrite it
* make fixup
* Add XLA-compatible RAG loss
* Fix dtype of loss mask for TFAlbert
* Fix test for XLNet too because it overrides the default one
* make fixup
* Fix config test
* No more depending on GPU NaN behaviour
* Add test, avoid potential zero division
* Fix test item assignment
* Fix loss computation masking test
* make fixup
* Fix dtype bugs
* first draft adding Flax-t5-encoder and Flax-mt5-encoder
* imports
* after make fixup
* flax t5 encoder test
* black on test
* make fix-copies
* clean
* all_model_classes -> tuple
* clean test
* is_encoder_decoder=False in t5-enc tester
* remove file docstring before FlaxT5Encoder
* black
* isort
* commit suggestions on src/transformers/models/t5/modeling_flax_t5.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* commit suggestions on src/transformers/models/t5/modeling_flax_t5.py
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* remove _get_encoder_module
* self.decoder_seq_length -> self.encoder_seq_length as t5-enc does not have decoder
* bugfix - self.module_class is class itself, not instance;
* docs for mt5 and t5
* call -> __call__ in t5 doc
* FlaxMT5EncoderModel to TYPE_HINT
* run doc-builder to allow change the files
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* chore: initial commit
Copied the torch implementation of regnets and porting the code to tf step by step. Also introduced an output layer which was needed for regnets.
* chore: porting the rest of the modules to tensorflow
did not change the documentation yet, yet to try the playground on the model
* Fix initilizations (#1)
* fix: code structure in few cases.
* fix: code structure to align tf models.
* fix: layer naming, bn layer still remains.
* chore: change default epsilon and momentum in bn.
* chore: styling nits.
* fix: cross-loading bn params.
* fix: regnet tf model, integration passing.
* add: tests for TF regnet.
* fix: code quality related issues.
* chore: added rest of the files.
* minor additions..
* fix: repo consistency.
* fix: regnet tf tests.
* chore: reorganize dummy_tf_objects for regnet.
* chore: remove checkpoint var.
* chore: remov unnecessary files.
* chore: run make style.
* Update docs/source/en/model_doc/regnet.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* chore: PR feedback I.
* fix: pt test. thanks to @ydshieh.
* New adaptive pooler (#3)
* feat: new adaptive pooler
Co-authored-by: @Rocketknight1
* chore: remove image_size argument.
Co-authored-by: matt <rocketknight1@gmail.com>
Co-authored-by: matt <rocketknight1@gmail.com>
* Empty-Commit
* chore: remove image_size comment.
* chore: remove playground_tf.py
* chore: minor changes related to spacing.
* chore: make style.
* Update src/transformers/models/regnet/modeling_tf_regnet.py
Co-authored-by: amyeroberts <aeroberts4444@gmail.com>
* Update src/transformers/models/regnet/modeling_tf_regnet.py
Co-authored-by: amyeroberts <aeroberts4444@gmail.com>
* chore: refactored __init__.
* chore: copied from -> taken from./g
* adaptive pool -> global avg pool, channel check.
* chore: move channel check to stem.
* pr comments - minor refactor and add regnets to doc tests.
* Update src/transformers/models/regnet/modeling_tf_regnet.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* minor fix in the xlayer.
* Empty-Commit
* chore: removed from_pt=True.
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: matt <rocketknight1@gmail.com>
Co-authored-by: amyeroberts <aeroberts4444@gmail.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Add a TF in-graph tokenizer for BERT
* Add from_pretrained
* Add proper truncation, option handling to match other tokenizers
* Add proper imports and guards
* Add test, fix all the bugs exposed by said test
* Fix truncation of paired texts in graph mode, more test updates
* Small fixes, add a (very careful) test for savedmodel
* Add tensorflow-text dependency, make fixup
* Update documentation
* Update documentation
* make fixup
* Slight changes to tests
* Add some docstring examples
* Update tests
* Update tests and add proper lowercasing/normalization
* make fixup
* Add docstring for padding!
* Mark slow tests
* make fixup
* Fall back to BertTokenizerFast if BertTokenizer is unavailable
* Fall back to BertTokenizerFast if BertTokenizer is unavailable
* make fixup
* Properly handle tensorflow-text dummies
* Add CodeGen model
* Add missing key and switch order of super()
* Fix torch.ones init with uint8 instead of bool
* Address comments: copy statements and doc
* update tests
* remove old model parallel
* fix batch gen tests
* fix batch gen test
* update test_gpt2_sample_max_time
* fix codgen test and revert gpt2 test change
* Fix incorrect tie_word_embedding value, typo, URL
* Fix model order in README and styling
* Reorder model list alphabetically
* Set tie_word_embedding to False by default
* Apply suggestions from code review
* Better attn mask name & remove attn masked_bias
* add tokenizer for codegen
* quality
* doc tokenizer
* fix-copies
* add CodeGenTokenizer in converter
* make truncation optional
* add test for truncation
* add copyright
* fix-copies
* fix fast tokenizer decode
* Update src/transformers/models/codegen/tokenization_codegen.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* increase vocab_size in tests
Co-authored-by: patil-suraj <surajp815@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* few fixes:
- hardcode tokenizer padding side
- remove unused args
* few fixes:
- added new attribute on TokenizerTesterMixin
- added new slow test
- remove unused arg on tokenizer class
* make style
* Update src/transformers/models/bloom/tokenization_bloom_fast.py
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>
* make quality
* apply changes
- remove new attribute
- redefine test on the class
* add comments
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>
* Add final_layer_norm to OPT model
* Add JAX and TF version
* Fix Keras name
* Woops
* Allow for non breaking change
* Apply suggestions from code review
* add tests
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* rename to check_pt_flax_outputs
* update check_pt_flax_outputs
* use 5e-5 for BigBird PT/Flax test
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Prepare CI for v0.8.0
* pin hfh (revert before merge)
* Revert "pin hfh (revert before merge)"
This reverts commit a0103140e1.
* Test rc3
* Test latest rc
* Unpin to the RC
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>
* Fix docstrings and variable names
* Rename x to something better
* Improve messages
* Fix docstrings and add test for greyscale images
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
* Use torch.finfo(self.dtype).min
* for GPTNeoX
* for Albert
* For Splinter
* Update src/transformers/models/data2vec/modeling_data2vec_audio.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix -inf used in Bart-like models
* Fix a few remaining -inf
* more fix
* clean up
* For CLIP
* For FSMT
* clean up
* fix test
* Add dtype argument and use it for LayoutLMv3
* update FlaxLongT5Attention
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add new bloom classes
* (feat) add bloom classification tests; make style
* style: change import in test
* add some typehints to bloom classes
* merge main into branch
* fix: input checking in bloom seq classification
* fix tests
* change model class tests
* fix few tests
- more tests should pass
- one test left
* make token classifier return hidden states
* style: make BLOOM typehints consistent
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: younesbelkada <younesbelkada@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
* Initial commit
* Make some fixes
* Make PT model full forward pass
* Drop TF & Flax implementation, fix copies etc
* Add Flax model and update some corresponding stuff
* Drop some TF things
* Update config and flax local attn
* Add encoder_attention_type to config
* .
* Update docs
* Do some cleansing
* Fix some issues -> make style; add some docs
* Fix position_bias + mask addition + Update tests
* Fix repo consistency
* Fix model consistency by removing flax operation over attn_mask
* [WIP] Add PT TGlobal LongT5
* .
* [WIP] Add flax tglobal model
* [WIP] Update flax model to use the right attention type in the encoder
* Fix flax tglobal model forward pass
* Make the use of global_relative_attention_bias
* Add test suites for TGlobal model
* Fix minor bugs, clean code
* Fix pt-flax equivalence though not convinced with correctness
* Fix LocalAttn implementation to match the original impl. + update READMEs
* Few updates
* Update: [Flax] improve large model init and loading #16148
* Add ckpt conversion script accoring to #16853 + handle torch device placement
* Minor updates to conversion script.
* Typo: AutoModelForSeq2SeqLM -> FlaxAutoModelForSeq2SeqLM
* gpu support + dtype fix
* Apply some suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* * Remove (de)parallelize stuff
* Edit shape comments
* Update README.md
* make fix-copies
* Remove caching logic for local & tglobal attention
* Apply another batch of suggestions from code review
* Add missing checkpoints
* Format converting scripts
* Drop (de)parallelize links from longT5 mdx
* Fix converting script + revert config file change
* Revert "Remove caching logic for local & tglobal attention"
This reverts commit 2a619828f6ddc3e65bd9bb1725a12b77fa883a46.
* Stash caching logic in Flax model
* Make side relative bias used always
* Drop caching logic in PT model
* Return side bias as it was
* Drop all remaining model parallel logic
* Remove clamp statements
* Move test files to the proper place
* Update docs with new version of hf-doc-builder
* Fix test imports
* Make some minor improvements
* Add missing checkpoints to docs
* Make TGlobal model compatible with torch.onnx.export
* Replace some np.ndarray with jnp.ndarray
* Fix TGlobal for ONNX conversion + update docs
* fix _make_global_fixed_block_ids and masked neg value
* update flax model
* style and quality
* fix imports
* remove load_tf_weights_in_longt5 from init and fix copies
* add slow test for TGlobal model
* typo fix
* Drop obsolete is_parallelizable and one warning
* Update __init__ files to fix repo-consistency
* fix pipeline test
* Fix some device placements
* [wip]: Update tests -- need to generate summaries to update expected_summary
* Fix quality
* Update LongT5 model card
* Update (slow) summarization tests
* make style
* rename checkpoitns
* finish
* fix flax tests
Co-authored-by: phungvanduy <pvduy23@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: patil-suraj <surajp815@gmail.com>
* Raise RepoNotFoundError in case of 401
* Include changes from revert-17646-skip_repo_not_found
* Add a comment
* 💄 Code quality
* 💚 Update `get_from_cache` test
* 💚 Code quality & skip failing test
* adding template
* update model
* model update
* update conf for debug model
* update conversion
* update conversion script
* update conversion script
* fix missing keys check
* add tests to test the tokenizer in the local machine
* Change variable name
* add tests on xnli dataset
* add more description
* add descriptions + clearer code
* clearer code
* adding new tests + skipping few tests because of env problems
* change comment
* add dtype on the configuration
* add test embeddings
* add hardcoded test
* fix dtype issue
* adding torch.float16 to config
* adding more metrics (min, max, mean)
* add sum
* now the test passes with almost equal
* add files for conversion - test passes on cpu gpu
* add final changes
* cleaning code
* add new args in the docstring
* fix one liner function
* remove macros
* remove forward attention
* clean up init funtion
* add comments on the issue
* rm scale mask softmax
* do make style
* fix dtype in init
* fixing for loop on att probs
* fix style with black
* fix style + doc error
* fix and debug CI errors (docs + style)
* some updates
- change new operations
- finally add scaled softmax
- added new args in the config
* make use cache working
* add changes
- save sharded models
- final changes on the modeling script
* add changes
- comment on alibi
- add TODO on seq length
* test commit
- added a text to test the commit
Co-authored-by: thomasw21 <24695242+thomasw21@users.noreply.github.com>
* final changes
- attention mask change
- generation works on BS176b
Co-authored-by: thomasw21 <24695242+thomasw21@users.noreply.github.com>
* changes - model + conversion
* move to correct dir
* put ,
* fex fixes
* fix tokenizer autodoc
* fix minor CI issues
* fix minor CI issues
* fix minor CI issues
* fix style issue
* fix minor import issues
* fix few issues
* remove def main on the test
* add require torch
* replace decorator with 'with'
* fix style
* change to bloom
* add quick fix tokenizer
* fix tokenizer file
* fix tokenizer
- merge tests
- small fixes
* fix import issue
* add bloom to readme
* fix consistency
* Update docs/source/en/model_doc/bloom.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Apply suggestions from code review
fix comment issues on file headers
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* fix doc issue
* small fix - modeling test
* some changes
- refactor some code
- taking into account reviews
- more tests should pass
- removed pruning tests
* remove useless division
* more tests should pass
* more tests should pass
* more tests should pass
* let's try this one
-add alibi offset
- remove all permutes to make the grad operations work
- finger crossed
* refactor
- refactor code
- style changes
- add new threshold for test
* major changes
- change BLOOM to Bloom
- add quick doc on bloom.mdx
- move embeddings test on modeling test
* modify readme
* small fixes
* small fix
- better threshold for a test
* remove old test file from fetcher
* fix small typo
* major change
- change BloomLMHead to BloomForCausalLM
* remove onnx config
* major changes
- refactor the code
- remove asserts
- change tol for test
* make style
* small change
* adding a slow test + commenting old ones for now
* make style
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* make style
* fix duplicates
* cleaning comments on config
* clean a bit conversion file
* refacor a bit modeling file
* refactor tokenizer file
* fix tokenization test issue
* fix tokenization issue #2
* fix tokenization issue second try
* fix test issue
* make style + add suggestions
* change test fetcher
* try this one
- slow tests should pass
- finger crossed
* possible final changes
* make style
* try fix padding side issue
* fix side
* fix padding issue
* fix ko-readme
* fix config auto
* cleaning modeling file
* keep bloom in caps in ko
* update config docs
* remove pretraining_pp
* remove model parallel
* update config
- add correct config files
* fix duplicates
* fix fetcher
* fix refactor issue
- remove divide function
* try to remove alibi
* small fixes
- fix alibi
- remove seq length
- refactor a bit the code
* put correct values
- fix bos and eos token ids
* fix attention mask loop
Co-authored-by: thomasw21 <24695242+thomasw21@users.noreply.github.com>
* small fixes:
- remove skip bias add
* small fixes
- fix typo in readme
- fix typos in config
* small changes
- remove a test
- add reconstruction test
- change config
* small changes
- change Scaled Softmax to BloomScaledSoftmax
* small fixes
- fix alibi dtype
* major changes
- removing explicit dtype when loading modules
- fixing test args (torch_dtype=auto)
- add dosctring
* fix readmes
* major changes
- now bloom supports alibi shifting
- refactor a bit the code
- better test tolerance now
* refactor a bit
* refactor a bit
* put correct name on test
* change docstring
* small changes
- fix docstring modeling
- fix test tolerance
* fix small nit
- take dtype from tensors in the conversion script
* minor fix
- fix mdx issue
* minor fix
- change config docstring
* forward contrib credits from PR14084
* Apply suggestions from code review
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* apply modifications
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* resolve softmax upcast
* Apply suggestions from code review
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* Update src/transformers/models/bloom/modeling_bloom.py
Co-authored-by: Niklas Muennighoff <n.muennighoff@gmail.com>
* final changes modeling
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* Merge commit 'd156898f3b9b2c990e5963f5030a7143d57921a2'
* merge commit
* Apply suggestions from code review
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* apply suggestions
Apply suggestions from Stas comments
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* Fix gradient checkpointing
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
* add slow but exact
* add accelerate compatibility
Co-authored-by: Nicolas Patry <Narsil@users.noreply.github.com>
* forward contrib credits
Co-authored-by: thomasw21 <thomasw21@users.noreply.github.com>
Co-authored-by: sgugger <sgugger@users.noreply.github.com>
Co-authored-by: patrickvonplaten <patrickvonplaten@users.noreply.github.com>
Co-authored-by: Niklas Muennighoff <n.muennighoff@gmail.com>
Co-authored-by: LysandreJik <LysandreJik@users.noreply.github.com>
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix torch device on tests
* make style
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix nits
Co-authored-by: patrickvonplaten<patrickvonplaten@users.noreply.github.com>
* remove final nits
* fix doc
- add more details on the doc
- add links to checkpoints
* Update src/transformers/__init__.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/bloom/modeling_bloom.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* apply suggestions
Co-authored-by: sgugger <sgugger@users.noreply.github.com>
* put test torchscript to false
* Update src/transformers/models/bloom/modeling_bloom.py
Co-authored-by: justheuristic <justheuristic@gmail.com>
* fix alibi
- create alibi only once
* add small doc
* make quality
* replace torch.nn
* remove token type emb
* fix fused op + output bias
* add fused op
- now can control fused operation from config
* remove fused op
* make quality
* small changes
- remove unsed args on config
- removed bias gelu file
- make the model torchscriptable
- add torchscript slow tests
* Update src/transformers/models/bloom/modeling_bloom.py
* fix slow
* make style
* add accelerate support
* add bloom to deepspeed tests
* minor changes
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* minor change
* slow tests pass
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update docs/source/en/model_doc/bloom.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* minor changes:
- change docstring
- add link to paper
Co-authored-by: Thomwolf <thomwolf@gmail.com>
Co-authored-by: Thomas Wolf <thomas@huggingface.co>
Co-authored-by: thomasw21 <24695242+thomasw21@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: sIncerass <sheng.s@berkeley.edu>
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Niklas Muennighoff <n.muennighoff@gmail.com>
Co-authored-by: Nicolas Patry <Narsil@users.noreply.github.com>
Co-authored-by: thomasw21 <thomasw21@users.noreply.github.com>
Co-authored-by: sgugger <sgugger@users.noreply.github.com>
Co-authored-by: patrickvonplaten <patrickvonplaten@users.noreply.github.com>
Co-authored-by: LysandreJik <LysandreJik@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: justheuristic <justheuristic@gmail.com>
Co-authored-by: Stas Bekman <stas@stason.org>
* feat: initial implementation of data2vec segmentation model in TF.
* chore: minor corrections to make the segmenter work.
* chore: removed unncessary files.
* chore: add tests and other modifications.
* fix: loss computation for segmentation.
* chore: remove unused variable.
* chore: formatting.
* added a dummy adaptive pooling layer.
* removed unnecessary file.
* potentially add identifiers to layer names.
* fix: layer naming.
* chore: removed unnecessary print.
* Skipping unneeded test
* chore: add logging to debug tolerance.
* fix: segmentation tests for tfdata2vecvision
* chore: make style.
* fix: layer names, assertion to be resolved.
* Bumping test tolerance a bit
* chore: bump the tol in PT test.
Co-authored-by: matt <rocketknight1@gmail.com>
* added cbs to notebooks, made copy-paste error fix in generation_utils
* initial push for mctc model
* mctc feature extractor done
* added processor, tokenizer and their tests for MCTC. Have added an MCTC modeling test, adjusting model code accordingly.
* added processor, tokenizer and their tests for MCTC. Have added an MCTC modeling test, adjusting model code accordingly.
* passing attention, now struggling to figure out how attention masks make sense here
* works when excluding attention masks. ask later how one would integrate attention maskshere
* bizarre configuration error (model prefix comes first in config dict json and messes up the order)
* all passing but bizzarre config dict ordering issue when to_dict
* passing all major tests
* feature extraction, processor, tokenizer added & tests passing
* style & consistency & other logistical fixes
* copy paste fix
* model after feature extraction working
* commiting final feature extraction results; need to fix normalization
* feature extraction passing tests; probably should add tests on the specific flashlight-copied functions?
* delete print ; format code a bit
* fixing tests
* passing major tests
* fixing styles
* completed tokenization test with real example; not sure if these values are entirely correct.
* last test fixes from local
* reverting accidentally included custom setup configs
* remove load tf weights; fix config error
* testing couldnt import featureextractor
* fix docs
* fix docs
* resolving comments
* style fixes
* style fixes
* Update to MCTCConv1dSubSampler
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* relposemb fixes
* conv1d name issue; expecting config fail with paraentheses
* fix config issue
* fix config issue
* fix config issue
* change everything to MCTCT
* fixing naming change errors
* archive list
* copyrights and docs
* copyrights and docs
* copyrights and docs
* merge resolution
* move tests, fix to changed optionaldependency structure
* test directories changed
* fixing tests
* how to avoid tf tests?
* how to avoid tf tests?
* tests passing locally
* allow mctctprocessor imported any env
* allow mctctprocessor imported any env
* fixed second round of feedback, need to fix docs
* doc changes not being applied
* all fixed
* style fix
* feedback fixes
* fix copies and feature extraction style fix
* Update tests/models/visual_bert/test_modeling_visual_bert.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* copy paste huggingface:main visual bert
* added eof newline to visual bert; all tests are passing otherwise
* fix slow tests by adding attention mask
* change model id to speechbrain
* make fix-copies
* fix readme unwanted deletes
* fixing readmes, make fix-copies
* consistent M-CTC-T naming
* Update src/transformers/models/mctct/__init__.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* all fixed but variable naming
* adjust double quotes
* fixed variable names
* copyright and mr quilter
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* correct slow tests
* make fix-copies
* Update src/transformers/models/mctct/configuration_mctct.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/mctct/configuration_mctct.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* m-ctc-t not mctct
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Add method to call to_tf_dataset() with column inference
* Add test for dataset creation
* Add a default arg for data collator
* Fix test
* Fix call with non-dev version of datasets
* Test correct column removal too
* make fixup
* More tests to make sure we remove unwanted columns
* Fix test to avoid predicting on unbuilt models
* Fix test to avoid predicting on unbuilt models
* Fix test to remove unwanted head mask columns from inputs
* Stop pushing your debug breakpoints to the main repo of the $2bn company you work for
* Skip the test in convnext because no grouped conv support
* Drop bools from the dataset dict
* Make style
* Skip the training test for models whose input dicts don't give us labels
* Skip transformerXL in the test because it doesn't return a simple loss
* Skip TFTapas because of some odd NaN losses
* make style
* make fixup
* Add docstring
* fixup
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Remove breakpoint from tests
* Fix assert, add requires_backends
* Protect tokenizer import with if TYPE_CHECKING
* make fixup
* Add noqa, more fixup
* More rearranging for ~* aesthetics *~
* Adding defaults for shuffle and batch_size to match to_tf_dataset()
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Add gated-silu to t5 architecture to support UL2
* Fix error message
* formatting
* formatting again
* refactor
* fix classnames in _init_weights
* remove is_gated
* add test
* fix test
* Try without the test?
* Add back the test.
* Improve error message.
Co-authored-by: Daniel Hesslow <daniel@lighton.ai>
* add a test for a word only input
* make LukeForMaskedLM work without entity inputs
* update test
* add LukeForMaskedLM to MODEL_FOR_MASKED_LM_MAPPING_NAMES
* restore pyproject.toml
* empty line at the end of pyproject.toml
* initial commit
* add init file
* update globakl init
* update index and dummy objects
* style
* update modelling auto
* fix initi typo in src/transformers
* fix typo in modeling tf auto, opt was in wrong mapping name
* fixed a slow test : saved_model
* style
* fix positionnal embedding if no position id is provided
* update tf test
* update test flax requirements
* fixed serialization
* update
* update tf name to allow smooth convertion
* update flax tests
* style
* fix test typo
* fix tf typo test
* add xla for generate support in causal LM
* fixed bug
* cleaned tf tests
* style
* removed from PT for slow tests
* fix typp
* opt test as slow
* trying to fix GPT2 undefined
* correct documentation and add to test doc
* update tf doc
* fix doc
* fake commit
* Apply suggestions from code review
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* update test based on review
* merged main layer for functionning test
* fixup + quality
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* update long comment
* make fix copies
Co-authored-by: Arthur <arthur@huggingface.co>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Support for Bart and LayoutLM, and partial support for XLNet
* Support for mbart
* A lot of new models supported
* Support for other models
* LayoutLM fix
* Use strings instead of classes
* Enablign `imageGPT` auto feature extractor.
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Small updates.
* Update after rebase to use `input_ids` instead of `pixel_values`.
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Make forward pass work
* More improvements
* Remove unused imports
* Remove timm dependency
* Improve loss calculation of token classifier
* Fix most tests
* Add docs
* Add model integration test
* Make all tests pass
* Add LayoutLMv3FeatureExtractor
* Improve integration test + make fixup
* Add example script
* Fix style
* Add LayoutLMv3Processor
* Fix style
* Add option to add visual labels
* Make more tokenizer tests pass
* Fix more tests
* Make more tests pass
* Fix bug and improve docs
* Fix import of processors
* Improve docstrings
* Fix toctree and improve docs
* Fix auto tokenizer
* Move tests to model folder
* Move tests to model folder
* change default behavior add_prefix_space
* add prefix space for fast
* add_prefix_spcae set to True for Fast
* no space before `unique_no_split` token
* add test to hightligh special treatment of added tokens
* fix `test_batch_encode_dynamic_overflowing` by building a long enough example
* fix `test_full_tokenizer` with add_prefix_token
* Fix tokenizer integration test
* Make the code more readable
* Add tests for LayoutLMv3Processor
* Fix style
* Add model to README and update init
* Apply suggestions from code review
* Replace asserts by value errors
* Add suggestion by @ducviet00
* Add model to doc tests
* Simplify script
* Improve README
* a step ahead to fix
* Update pair_input_test
* Make all tokenizer tests pass - phew
* Make style
* Add LayoutLMv3 to CI job
* Fix auto mapping
* Fix CI job name
* Make all processor tests pass
* Make tests of LayoutLMv2 and LayoutXLM consistent
* Add copied from statements to fast tokenizer
* Add copied from statements to slow tokenizer
* Remove add_visual_labels attribute
* Fix tests
* Add link to notebooks
* Improve docs of LayoutLMv3Processor
* Fix reference to section
Co-authored-by: SaulLu <lucilesaul.com@gmail.com>
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
* Fix torch.jit.script and pickling issues
* Fix get_attr issues
* Fix import in function
* Fix GPT-J and T5 tracing for torch=1.11
* Gate graph surgery on torch version
* Modeling minor changes to enable TorchScripting
* Model serialization / deserialization test
* Remove _assert_is_none users
* Automatically sort auto mappings
* Better class extraction
* Some auto class magic
* Adapt test and underlying behavior
* Remove re-used config
* Quality
* First version - OPT model
* Final changes
- putting use cache to False
* few changes
- remove commented block
* few changes
- remove unecessary files
* fix style issues
* few changes
- remove a test file
- added the logits test
* Update src/transformers/models/auto/tokenization_auto.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add gen tests
* few changes
- rm mask filling example on docstring
* few changes
- remove useless args
* some changes
- more tests should pass now
- needs to clean more
- documentation still needs to be done
* fix code quality
* major changes
- change attention architecture to BART-like
- modify some tests
- style fix
* rm useless classes
- remove opt for:
- QA
- cond generation
- seq classif
* Removed autodoc calls to non-existant classes
TOkenizers are not implemented
* Update src/transformers/__init__.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/__init__.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/auto/modeling_tf_auto.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Replaced OPTTokeniser with GPT2 tokenizer
* added GPT2Tokenizer.from_pretrained("patrickvonplaten/opt_gpt2_tokenizer")
* Removed OPTTokenizer
* make style
* Make style replaces
``` ...).unsqueeze(```
by
``` >>>).unsqueeze(```
* make repo consistency
* Removed PretrainedOPTModel
* fix opt.mdx removed other heads
* fix init, removed 3 heads
* removed heads
* finished cleaning head
* removed seauence classif and question answering
* removed unused imports
* removed useless dummy object for QA, SC and CG
* removed tests for removed useless dummy object for QA, SC and CG
* Removed head_mask using encoder layers which don't exist
* fixed test
* fix line
* added OPT to toctree
* Updated model path with pushed weigths
* fix model path
* fixed code quality
* fixed embeddings and generation tests
* update paths
* clean comments
* removed OPTClassificationHead for sentence classification
* renamed hidden layer
* renamed num layers to standard num_hidden_layers
* num_attention_heads fix
* changes for 125m
* add first version for 125m
* add first version - flax
* add new version
* causal LM output
* replace output type with BaseModelOutputWithPastAndCrossAttentions
* revert working config from 150m to 350m
* clean
* removed decoder input ids
* fixed embed dim
* more embed_dim issues
* make style + removed enc_dec test
* update falx model
* removed troublesome copy
* added is_encoder_decoder=False to config
* added set_input emb fuinction to model class
* requires torch on embed test
* use head mask instead of decoder head mask input param solves a test
* 8 test remaining, update
* Updated create_and_check_decoder_model_past_large_inputs
* Make style
* update op tokenizer with condition
* make style
* See if I can push
* some clean up
* remove linear head hack
* save intermediate
* save correct attention
* add copied from from bart
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix part of the reviewss
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* same changes in naming / conversion
* correct mask
* more fixes
* delete FlaxOPT and TfOPT
* clean traces of Flax and Tf
* fix mask
* fixed positionnal embedding length when past key value is provoded
* get 125m, 6.7b to work
* Added do_layer_norm
* solved mismatch in load dictionnary
* clean up preapre opt input dict
* fixed past key value as bool
* fix previus
* fixed return dict False tuple issue
* All tests are passing
* Make style
* Ignore OPTDecoder non tested
* make fix-copies
* make repo consistency
* small fix
* removed uselss @torch.no_grad decorator
* make styl;e
* fix previous opt test
* style
* make style
* added opt documentation
* update OPT_PRETRAINED_MODEL_ARCHIVE_LIST
* up
* more fixes
* model & config work
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* added comment on padding hack (+2)
* cleaup
* review update
* docstring for missing arg
* Update docs/source/en/model_doc/opt.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update docs/source/en/model_doc/opt.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update docs/source/en/model_doc/opt.mdx
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/models/opt/__init__.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* update pretrained map
* update path and tests
* make style
* styling
* make consistency
* add gpt2 tok new
* more tok fixes
* Update src/transformers/models/auto/tokenization_auto.py
* Update docs/source/en/model_doc/opt.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update docs/source/en/model_doc/opt.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update docs/source/en/model_doc/opt.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update tests/models/opt/test_modeling_opt.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/models/opt/modeling_opt.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update based on reviews
* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* make style
* make tokenizer auto tests pass
* apply Lysandre suggestion
* finish tests
* add some good tokenizer tests
* improve docs slighly
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: ArthurZucker <arthur.zucker@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* [WIP] Add FLAVA model
This PR aims to add [FLAVA](ihttps://arxiv.org/abs/2112.04482) model to the transformers repo.
Following checklist delineates the list of things to be done for this PR
to be complete:
[x] Flava init
[x] Flava base models
[x] Flava layers
[x] Flava Configs
[x] Flava encoders
[x] Flava pretraining models
[ ] Flava classification/retrieval models (To be added in a separate PR)
[x] Documentation updates
[x] Imports updates
[x] Argstring updates
[x] Flava pretrained checkpoints
[x] Flava tests
[x] Flava processors
[x] Sanity check
[x] Lint
* unhardcode pretrained model path, make it a class var
* add tests for mobilebert tokenizer
* allow tempfiles for vocab & merge similarity test to autodelete
* add explanatory comments
* remove unused imports, let make style do its.. thing
* remove inheritance and use BERT tok tests for MobileBERT
* Update tests/mobilebert/test_tokenization_mobilebert.py
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>
* amend class names, remove unused import, add fix for mobilebert's hub pathname
* unhardcode pretrained model path, make it a class var
* add tests for mobilebert tokenizer
* allow tempfiles for vocab & merge similarity test to autodelete
* add explanatory comments
* remove unused imports, let make style do its.. thing
* remove inheritance and use BERT tok tests for MobileBERT
* Update tests/mobilebert/test_tokenization_mobilebert.py
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>
* amend class names, remove unused import, add fix for mobilebert's hub pathname
* amend paths for model tests being in models/ subdir of /tests
* explicitly rm test from prev path
Co-authored-by: SaulLu <55560583+SaulLu@users.noreply.github.com>
* add get_overflowing_images function to ensure 1-to-1 mapping between samples and images in LayoutLMv2Processor
* make style
* add test for overflowing_tokens, change assert to ValueError, avoiding unrelated formatting changes
* change line length by passing --preview into black
* CLIP Serving
* Add type hints per code review
* Use black, flake8, and isort
* Update src/transformers/models/clip/modeling_tf_clip.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Rollback serving_output and add TODO
* Remove irrelevant portions of failing tests
* Revert "Rollback serving_output and add TODO"
This reverts commit a4abfa6ba3b7875a13538dbc2ddc4eb17dfcca8d.
* Rollback to original test/serving_output
* Fix unused var
* Apply suggestions from code review
* Update formatting with black
* Fix style again from rebase
* Update tests/models/clip/test_modeling_tf_clip.py
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Sean Moriarity <sean.l.moriarity.mil@army.mil>
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
