- 16 May, 2024 6 commits
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Yih-Dar authored
* fix * [run-slow] gemma * add test * add `test_compile_static_cache` * fix * style * remove subprocess * use attribute * fix * style * update * [run-slow] dbrx,gemma,jetmoe,phi3,recurrent_gemma --------- Co-authored-by:ydshieh <ydshieh@users.noreply.github.com>
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Mohit Sharma authored
* disable fa * disable fa * update warning * update warning
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Joao Gante authored
* jamba cache * new flag * generate exception
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NielsRogge authored
* Add resources * Address comment * Address comments * Update docs/source/en/model_doc/idefics2.md Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update figure --------- Co-authored-by:
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hyenal authored
remove blank line (+1 squashed commit) Squashed commits: [24ccd2061] [run-slow]vit_msn,vision_encoder_decoder (+24 squashed commits) Squashed commits: [08bd27e7a] [run-slow]vit_msn,vision_encoder_decoder [ec96a8db3] [run-slow]vit_msn [ead817eca] fix vit msn multi gpu [d12cdc8fd] [run-slow]audio_spectrogram_transformer,deit,vision_encoder_decoder,vision_text_dual_encoder,vit,vit_hybrid,vit_mae,vit_msn,videomae,yolos [3fdbfa88f] doc [a3ff33e4a] finish implementation [e20b7b7fb] Update test_modeling_common.py [e290c5810] Update test_modeling_flax_common.py [d3af86f46] comment [ff7dd32d8] more comments [59b137889] suggestion [7e2ba6d67] attn_implementation as attribute of the class [fe66ab71f] minor [38642b568] Apply suggestions from code review Accept comments Co-authored-by:
Liubov Yaronskaya <luba.yaronskaya@gmail.com>
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NielsRogge authored
* First draft * Update docstring
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- 15 May, 2024 14 commits
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Edoardo Cetin authored
* Fix llama model forward function with attention=True, same-length encoded sequence. * Fix style * propagate fix to modeling_cohere, gemma, dbrx, and olmo (which copy the same sdpa masking logic from llama) * Fix style * ignore unnecessary sdpa mask converter when output_attentions=True * add tests checking sdpa and eager outputs match when output_attentions=True * Split if statements in two lines Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * Fix formatting * Add fix to new jetmoe model * Add missing output_attentions argument to jetmoe mask creation --------- Co-authored-by:
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Yih-Dar authored
2.3 Co-authored-by: -
Younes Belkada authored
* add method * change method name * more comments * Apply suggestions from code review Co-authored-by:
Marc Sun <57196510+SunMarc@users.noreply.github.com> Co-authored-by:
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amyeroberts authored
* Correctly set the moel name for the doc file * Fix up
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Xuan-Phi Nguyen authored
* Better llava next. - Batched forward with multiple image of different sizes (number of patches). - Support training, for cases without any image. - Support multi-image in same sequence. e.g: ["<image> <image> the first image is a dog while the second is a cat", "<image> <image> <image> <image> these 4 image are..."] Current limitation: - Haven't done testing - Only support right padding (for training) - left padding (batched generation) is not ready yet. - PR not ready. * fix bugs in batched generation * add tests * fix batch-gen bugs, left-padding positions and incorrect attention mask * remove better modeling llava * fix formatting * fix test * fix test * fix testing * fix test * fix formatting * Update src/transformers/models/llava_next/modeling_llava_next.py add clarity Co-authored-by:
NGUYEN, Xuan Phi <x.nguyen@alibaba-inc.com> Co-authored-by:
raushan <raushan@huggingface.co> Co-authored-by:
Raushan Turganbay <raushan.turganbay@alumni.nu.edu.kz>
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Sourab Mangrulkar authored
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xkszltl authored
The function checks for None in its first line.
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amyeroberts authored
* Jamba - Skip 4d custom attention mask test * Skip assistant greedy test
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Lysandre Debut authored
* Adds support for loading GGUF files Co-authored-by:
Younes Belkada <younesbelkada@gmail.com> Co-authored-by:
99991 <99991@users.noreply.github.com> * add q2_k q3_k q5_k support from @99991 * fix tests * Update doc * Style * Docs * fix CI * Update docs/source/en/gguf.md * Update docs/source/en/gguf.md * Compute merges * change logic * add comment for clarity * add comment for clarity * Update src/transformers/models/auto/tokenization_auto.py Co-authored-by:
Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by:
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Raushan Turganbay authored
* add model draft * update docstring * add tests * support image and video as input * update for better handling of mixed input and clean-up a bit * bug when mixed inputs & add tests * Update README.md Co-authored-by:
NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Merge remote-tracking branch 'upstream/main' into video_llava * link to abstract of paper in README * fix test * fix-copies * make tests happy * skip docstest for now * do not run doctest for now * Update src/transformers/models/video_llava/processing_video_llava.py Co-authored-by:
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David authored
* removing heads for classification from DETR models. * quality fix
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Ond艡ej C铆fka authored
* Add support for mixing languages in a single batch * Update docstring * Enable different detected languages in batch * Do not require input_features * Test list of languages * Fix comment * Make init_tokens length-1 if possible, broadcast at the end * Test for ValueError with language list of incorrect length * Slow test for batched multilingual transcription * fixup * Apply suggestions from code review Co-authored-by:
Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * Address review, refactor * Second attempt to move this line where it was originally * Split test, fix a bug --------- Co-authored-by:
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Jacky Lee authored
fix: missing dependencies
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Jacky Lee authored
* feat: support custom checkpoint * update: revert changes and add TODO * update: docs and exception handling * fix: ah, extra space
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- 14 May, 2024 10 commits
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Pablo Montalvo authored
* add new model like * add state dict slicing + new model config * update palma config and weights, passes vision activations * fix * update * reorder loading/unpacking * clean up * add debug statements * change device * fix * debugging * fix noncausal mask * fixup sdpa + causal mask * fix activation function * remove debug before changing modeling file * add variants * debug attention mask in generate * revert to non-debug sdpa * revert gemma modifications * add custom language modeling * use Processor * add language modeling file to init * try thin wrapper around generate * Update * update mask * breakpoints galore * remove conflict * switch to left-padding * add incomplete model doc * add paligemma global files * batch rename paligemma * make generation match outputs and captioning * style * style * remove copied from + doc * remove more copied from * remove copy from projector * minor fix * update config and style * add readme - dummy * CORRECT image captioning * moving to args * add siglip proper + fix merging image + text features * take update_causal_mask from upstream * remove breakpoint * leverage AutoModel * fix input_ids slicing * make siglip head conditional * remove encoder_decoder value * remove unneeded modeling file * add commented 4d attention mask * FIXED generation with 4D mask * Update src/transformers/models/siglip/modeling_siglip.py Co-authored-by:
Merve Noyan <merveenoyan@gmail.com> * simplify conversion script * add copied from * add precision to conversion script * Update src/transformers/models/paligemma/modeling_paligemma.py Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> * clean up * Shift attention mask from `1:` After discussion with @molbap * add docs, fix quality * quality, tied weights inheritance, and logits/label alignment * fix more tests * pass attn_implementation to language model correctly * add SiglipVisionTransformer to no split modules * skip paligemma test for sdpa dispatch to flash * skip incompatible tests * quality * [broken archive maps] * Apply suggestions - remove archive lists - style - take shape of inputs_embeds for batch Co-authored-by:
ArthurZucker <arthur.zucker@gmail.com> Co-authored-by:
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Ankur Singh authored
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Yikang Shen authored
* init jetmoe code * update archive maps * remove flax import * fix import error * update README * ruff fix * update readme * fix * update config * fix issue * merge files * fix model bug * fix test * auto fix * model size * add comments * fix form * add flash attention support * fix attention head number * fix init * fix support list * sort auto mapping * fix test * fix docs * update test * fix test * fix test * change variable name * fix config * fix init * update format * clean code * fix config * fix config * change default config * update config * fix issues * update formate * update config argument * update format * Update src/transformers/models/jetmoe/modeling_jetmoe.py Co-authored-by:
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Masahiro Suzuki authored
[T5] Adding `model_parallel = False` to `T5ForTokenClassification` and `MT5ForTokenClassification` (#30763) * Adding model_parallel = False * Revert "Adding model_parallel = False" This reverts commit ba1d99976acb598824ce3347dbe7d848daa21e79. * Trainer: circumvent error for model in which is_parallelizable is True but does not have model_parallel attribute
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Matt authored
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Joao Gante authored
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Raushan Turganbay authored
* add watermarking processor * remove the other hashing (context width=1 always) * make style * Update src/transformers/generation/logits_process.py Co-authored-by:
Joao Gante <joaofranciscocardosogante@gmail.com> * Update src/transformers/generation/logits_process.py Co-authored-by:
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Pashmina Cameron authored
Access active_adapters as a property
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Raushan Turganbay authored
standardize cache in idefics2
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Jacky Lee authored
fix: owlv2 doc
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- 13 May, 2024 10 commits
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fxmarty authored
* update to ROCm 6.0.2 and test MI300 * add callers for mi300 * update dockerfile * fix trainer tests * remove apex * style * Update tests/trainer/test_trainer_seq2seq.py * Update tests/trainer/test_trainer_seq2seq.py * Update tests/trainer/test_trainer_seq2seq.py * Update tests/trainer/test_trainer_seq2seq.py * update to torch 2.3 * add workflow dispatch target * we may need branches: mi300-ci after all * nit * fix docker build * nit * add check runner * remove docker-gpu * fix issues * fix --------- Co-authored-by:
Yih-Dar <2521628+ydshieh@users.noreply.github.com> Co-authored-by:
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Marc Sun authored
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amyeroberts authored
* Add utility for finding candidate models for deprecation * Update model init * Make into configurable script * Fix path * Add sorting of base object alphabetically * Tidy * Refactor __init__ alpha ordering * Update script with logging * fix import * Fix logger * Fix logger * Get config file before moving files * Take models from CLI * Split models into lines to make easier to feed to deprecate_models script * Update * Use posix path * Print instead * Add example in module docstring * Fix up * Add clarifying comments; add models to DEPRECATE_MODELS * Address PR comments * Don't update relative paths on the same level
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Yih-Dar authored
* update * update * update * update * update * update * update * update * Update utils/notification_service.py Co-authored-by:
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Joao Gante authored
* assistant should be greedy * better comment * Update src/transformers/generation/candidate_generator.py Co-authored-by:
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Alazar authored
* Initial commit * Just a copy of modeling_idefics.py that will be ported to TF * - Prepend TF to the name of all classes - Convert pytorch ops to TF (not all operations are converted yet) * Add TF imports * Add autotranslated files * Add TF classes to model_tf_auto.py * Add the TF classes in model_doc * include auto-translated code * Adopted from auto-translated version * Add a forgotten super().build * Add test code for TF version. * Fix indentation and load pytorch weights for now * Some fixes. Many tests are still failing but some are passing now. - I have added TODO's for some of the hacks I made to unblock me and I will address them soon - I have the processing_idefics.py hacked in my view to support TF temporarily * Add ALL_LAYERNORM_LAYERS to match pytorch * Revert "Add ALL_LAYERNORM_LAYERS to match pytorch" This reverts commit 7e0a35119b4d7a6284d04d8c543fba1b29e573c9 as it is not needed in the tf implementation. * Fix freeze_relevant_params() * Some more fixes * Fix test_attention_outputs * Add tf stuff to processing_idefics.py processing_idefics.py supports both pytorch and tf now. test_processor_idefics.py for pytorch is passing, so i didn't break anything but still some issues with tf. I also need to add tf tests in test_processor_idefics.py. * Pass return_tensors to image processing code and fix test * Pass return_tensors to the image processor __init__ * Fix several test cases - Make input to some of the forward pass of type `TFModelInputType` - Decorate main layer forward pass with `@unpack_inputs` - Decorate main layer with `@keras_serializable` - Pass `inputs` to TFIdeficsModel * Some more fixes forgotten in last commit * Fix processing code and vision_tf.py * Fix perceiver bug * Import from * Auto-add build() methods + style pass * Fix build() errors due to `None` being passed as shape to some layers * Change name in TFIdeficsForVisionText2Text to attribute in IdeficsForVisionText2Text * Fix pytorch weights load for tf2 There were a lot of `name=` missing in weight initialization code. * Attempt to fix CI * Add back accidently removed line * Remove torch-specific stuff from the TF test file * make fix-copies, make style, remove autotranslated files * Fixes to imports/docstrings * Let's try the from future import in desperation * Fix the core random_attention_mask fn to match the torch/flax behaviour * Clean random_attention_mask up correctly * Remove torch-only test * Fix loss shape, couple of nits * make style * Don't test for OOB embeddings because IDEFICS uses those deliberately * Fix loss computation to handle masking * Fix test failures when flattening * Fix some test failures - Add cross attention gate which was missing and wasn't being passed arround - Fix overwriting of image_attention_mask due to hack I had for dummy inputs * Add a proper stateless scaled_dot_product_attention * make style * Adding missing attribute from the PyTorch version * Small cleanups to decoupledlinearlayer in case that helps * Pass epsilon to LayerNormalization * Attemp to fix pytorch weight cross-loading for TFIdeficsEmbedding * Fix a bug in TFIdeficsGatedCrossAttentionLayer * Patching up build() methods * Constant self.inv_freq * Constant self.inv_freq * First working version The TF implementation works now, there was a bug in the TFIdeficsDecoupledLinear where the weights were mis-intialized (in_features,out_features) when it should be: (out_features, in_features) I have tested this so far with tiny-random and idefics-9b-instruct and gives correct output. I also dumped the final outputs for both pytorch and TF and they are identical. * Fix some test failures * remove print statement * Fix return_tensors * Fix CI test failure check_code_quality * Attempt to fix CI failures by running `make fixup` The hardcoded IDs in test_modeling_tf_idefics.py are for the integration test and makes that file unreadable and should probably be moved to a seperate file. * Attempt to fix tests_pr_documentation_tests * Fix a test failure in test_image_processing_idefics.py * Fix test test_pt_tf_model_equivalence * Fix a few failures * Tiny fix * Some minor fixes * Remove a duplicate test * Override a few test failures for IDEFICS - `test_keras_save_load` is passing now - `test_compile_tf_model` is still failing * Fix processing_idefics.py after rebase * Guard import keras with is_tf_available * fix check code quality * fix check code quality * Minor fixes * Skip test_save_load temporarily This test passed on my local box but fails on the CI, skipping for now to see if there are other remaining failures on the CI. * Run `ruff format tests src utils` * Fix last failing test, `test_compile_tf_model` * Add fixes for vision_tf.py I forgot to add this file in last commit. * Minor fixes * Replace "<<<" with "<<" for doc tests IDEFICS-9B is too big for doctest runner, so don't run it there * Make code more readable * Fix bug after code review I added a layer_norm_eps to IdeficsConfig but I don't even need it since the vision config has a layer_norm_eps. * Fix after code review Use original code tokenizer.convert_tokens_to_ids * Keep PyTorch as the default return_tensors * Fixes to modeling_tf after code review * Fixes from code review - Remove all references of `TF_IDEFICS_PRETRAINED_MODEL_ARCHIVE_LIST` - Pass 1e-5 to LayerNormalization in perceiver * Run ruff * Undo a change * Refactor processing code after Matt's suggestion * Remove TODO's that aren't needed anymore * For pytorch, Use original pytorch processing code from main Since this PR is a TF port it shouldn't make any modifications to pytorch IDEFICS code. This changes undo's the pytorch processing modifications I made and uses original code from main. * Update tests/models/idefics/test_modeling_idefics.py * Update tests/models/idefics/test_modeling_tf_idefics.py * Add missing imports for is_pt_tf_cross_test * [DO NOT MERGE]: This is a commit for debugging and will be reverted The cross test `test_pt_tf_model_equivalence` passes locally but fails when running on the CI. This commit is to help debug that and will be reverted. * Revert "[DO NOT MERGE]: This is a commit for debugging and will be reverted" This reverts commit 8f0d709ec5bd46685fb0b4259d914ffee794875b. * [DO NOT MERGE]: This commit is for debugging a CI failure and will be reverted * [DO NOT MERGE]: This commit is for debugging a CI failure and will be reverted * Revert "[DO NOT MERGE]: This commit is for debugging a CI failure and will be reverted" This reverts commit 998cc38b8c3d313bf5e5eb55a7f5b7b881897b89. * Revert "[DO NOT MERGE]: This commit is for debugging a CI failure and will be reverted" This reverts commit 1c695ac4219c4ae4d39b330b01744dc27deb7dd4. * Don't skip test_save_load IIRC test_save_load was also failing on the CI but not on my local box, it might be easier to debug that on the CI first than the cross tests * Debugging commit, will be reverted * Revert "Debugging commit, will be reverted" This reverts commit 8eafc8e41e20c4e95a3a90834f06a6e9f445e2d5. * Override `test_save_load` and push model to save Maybe this will help me repro this weird bug * pass my repo_id * add endpoint * Pass a temp (write) token just for this CI * Undo last few commits, still pushing to hub for model debugging The issue seems to be with save_pretrained(), when I looked at the model saved from the CI test failure it is basically empty and has no weights. `self.save_weights(..)` seems to be failing in save_pretrained but needs more debugging * Add logging to modeling tf utils, will be reverted just for debugging * Debugging, will revert * Revert "Debugging, will revert" This reverts commit 9d0d3075fb7c82d8cde3a5c76bc8f3876c5c55d3. * Revert "Add logging to modeling tf utils, will be reverted just for debugging" This reverts commit 774b6b7b1c17b3ce5d7634ade768f2f686cee617. * Remove `test_save_load` The CI failures are gone after my latest rebase, no idea why but I was still saving the model to my hub on HF and the tf_model.h5 file now has everything. * Run make fix-copies * Run ruff format tests src utils * Debugging commit, will be reverted * Run ruff, also trigger CI run * Run ruff again * Undo debugging commit --------- Co-authored-by:
Matt <rocketknight1@gmail.com> Co-authored-by:
Matt <Rocketknight1@users.noreply.github.com>
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Joao Gante authored
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NielsRogge authored
* Lower threshold * Address comment
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Fanli Lin authored
* check model.device * fix * style fix * move model device * remove print * add comment * fix * add unit test * optimize * change test names and add more cases * Update tests/pipelines/test_pipelines_common.py Co-authored-by:
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Joao Gante authored
qwen does not support the new cache classes
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