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- 14 Mar, 2024 2 commits
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Yih-Dar authored
* update --------- Co-authored-by:ydshieh <ydshieh@users.noreply.github.com>
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Yih-Dar authored
* add arg --------- Co-authored-by:
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- 13 Mar, 2024 8 commits
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Nate Cibik authored
* Added pytests for pvt-v2, all passed * Added pvt_v2 to docs/source/end/model_doc * Ran fix-copies and fixup. All checks passed * Added additional ReLU for linear attention mode * pvt_v2_b2_linear converted and working * copied models/pvt to adapt to pvt_v2 * First commit of pvt_v2 * PvT-v2 now works in AutoModel * Reverted batch eval changes for PR * Expanded type support for Pvt-v2 config * Fixed config docstring. Added channels property * Fixed model names in tests * Fixed config backbone compat. Added additional type support for image size in config * Fixed config backbone compat * Allowed for batching of eval metrics * copied models/pvt to adapt to pvt_v2 * First commit of pvt_v2 * Set key and value layers to use separate linear modules. Fixed pruning function * Set AvgPool to 7 * Fixed issue in init * PvT-v2 now works in AutoModel * Successful conversion of pretrained weights for PVT-v2 * Successful conversion of pretrained weights for PVT-v2 models * Added pytests for pvt-v2, all passed * Ran fix-copies and fixup. All checks passed * Added additional ReLU for linear attention mode * pvt_v2_b2_linear converted and working * Allowed for batching of eval metrics * copied models/pvt to adapt to pvt_v2 * First commit of pvt_v2 * Set key and value layers to use separate linear modules. Fixed pruning function * Set AvgPool to 7 * Fixed issue in init * PvT-v2 now works in AutoModel * Successful conversion of pretrained weights for PVT-v2 * Successful conversion of pretrained weights for PVT-v2 models * Added pytests for pvt-v2, all passed * Ran fix-copies and fixup. All checks passed * Added additional ReLU for linear attention mode * pvt_v2_b2_linear converted and working * Reverted batch eval changes for PR * Updated index.md * Expanded type support for Pvt-v2 config * Fixed config docstring. Added channels property * Fixed model names in tests * Fixed config backbone compat * Ran fix-copies * Fixed PvtV2Backbone tests * Added TFRegNet to OBJECTS_TO_IGNORE in check_docstrings.py * Fixed backbone stuff and fixed tests: all passing * Ran make fixup * Made modifications for code checks * Remove ONNX config from configuration_pvt_v2.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Use explicit image size dict in test_modeling_pvt_v2.py Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * Changed name of variable from 'attn_reduce' to 'sr_type' * Changed name of variable from 'attn_reduce' to 'sr_type' * Changed from using 'sr_type' to 'linear_attention' for clarity * Update src/transformers/models/pvt_v2/modeling_pvt_v2.py Removed old code * Changed from using 'sr_type' to 'linear_attention' for clarity * Fixed Class names to be more descriptive * Update src/transformers/models/pvt_v2/modeling_pvt_v2.py Removed outdated code * Moved paper abstract to single line in pvt_v2.md * Added usage tips to pvt_v2.md * Simplified module inits by passing layer_idx * Fixed typing for hidden_act in PvtV2Config * Removed unusued import * Add pvt_v2 to docs/source/en/_toctree.yml * Updated documentation in docs/source/en/model_doc/pvt_v2.md to be more comprehensive. * Updated documentation in docs/source/en/model_doc/pvt_v2.md to be more comprehensive. * Update src/transformers/models/pvt_v2/modeling_pvt_v2.py Move function parameters to single line Co-authored-by:
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Yih-Dar authored
update Co-authored-by: -
Raushan Turganbay authored
* fix batchinng tests for new models * Update tests/models/seggpt/test_modeling_seggpt.py Co-authored-by:
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Fanli Lin authored
[tests] make `test_trainer_log_level_replica` to run on accelerators with more than 2 devices (#29609) add new arg
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Sourab Mangrulkar authored
* fsdp+qlora related changes * fixes * Update quantization_config.py * support fsdp+qlora and dsz3+qlora * Update quantization_config.py * Update modeling_utils.py * Update modeling_utils.py * Update modeling_utils.py * Update modeling_utils.py * Update modeling_utils.py * Update modeling_utils.py * handle fsdp+qlora and dsz3+qlora correctly while model loading * fix param count * quality * fsdp related changes * fsdp changes only when using LoRA/QLoRA * add accelerate version check * refactor, update min accelerate version and add tests 1. Update minimum accelerate version to 0.26.0 2. Clean the trainer wrt accelerate version checks 3. FSDP refactor and test for fsdp config 4. use `itemsize` instead of `dtype2bytes` dict * fix test * Address comments Co-Authored-By:
Younes Belkada <49240599+younesbelkada@users.noreply.github.com> * fix the conditional flag * fix conditional flag * address comments Co-Authored-By:
Zach Mueller <7831895+muellerzr@users.noreply.github.com> --------- Co-authored-by:
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Joao Gante authored
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Lysandre Debut authored
* Adds pretrained IDs directly in the tests * Fix tests * Fix tests * Review!
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bytebarde authored
* initial implementation of flash attention for gptj * modify flash attention and overwrite test_flash_attn_2_generate_padding_right * update flash attention support list * remove the copy line in the `CodeGenBlock` * address copy mechanism * Update src/transformers/models/gptj/modeling_gptj.py Co-authored-by:
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- 12 Mar, 2024 2 commits
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Raushan Turganbay authored
* add tests for batching support * Update src/transformers/models/fastspeech2_conformer/modeling_fastspeech2_conformer.py Co-authored-by:
Joao Gante <joaofranciscocardosogante@gmail.com> * Update src/transformers/models/fastspeech2_conformer/modeling_fastspeech2_conformer.py Co-authored-by:
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Yih-Dar authored
* update * update * update --------- Co-authored-by:
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- 11 Mar, 2024 2 commits
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Pedro Cuenca authored
* Experimental loading of MLX files * Update exception message * Add test * Style * Use model from hf-internal-testing
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Arthur authored
* post merge update * nit * oups
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- 08 Mar, 2024 6 commits
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Fanli Lin authored
[tests] use the correct `n_gpu` in `TrainerIntegrationTest::test_train_and_eval_dataloaders` for XPU (#29307) * fix n_gpu * fix style
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Jonatan Kłosko authored
* Make sliding window size inclusive in eager attention * Fix tests
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Fanli Lin authored
* use torch_device * skip for XPU * Update tests/generation/test_utils.py Co-authored-by:
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Wang, Yi authored
* fix image-to-text batch incorrect output issue Signed-off-by:
Wang, Yi A <yi.a.wang@intel.com> * add ci test Signed-off-by:
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Fanli Lin authored
* add sacremoses check * fix style * for FlaubertTokenizer * HerbertTokenizer fix * add typeHint * Update src/transformers/testing_utils.py Co-authored-by:
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Joao Gante authored
* left-padding test revisited * Apply suggestions from code review Co-authored-by:
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- 07 Mar, 2024 6 commits
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Nick DeGroot authored
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🐛 Fix vision encoder decoder positional arg *✅ Add test for VisionEncoderDecoder with LayoutLMv3 encoder --------- Co-authored-by:Nick DeGroot <1966472+nickthegroot@users.noreply.github.com>
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amyeroberts authored
* Fall back to pytorch model for now * Fix up
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Raushan Turganbay authored
* flava multimodal add attn mask * make style * check mask is not None
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Lysandre Debut authored
Revert "Automatic safetensors conversion when lacking these files (#29390)" This reverts commit a69cbf4e.
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Joao Gante authored
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regisss authored
* Enable BLIP for auto VQA * Make style * Add VQA to BLIP pipeline tests
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- 06 Mar, 2024 3 commits
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Joao Gante authored
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Joao Gante authored
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Fanli Lin authored
* use require_torch_gpu * enable on XPU * fix
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- 05 Mar, 2024 8 commits
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Lysandre Debut authored
* Automatic safetensors conversion when lacking these files * Remove debug * Thread name * Typo * Ensure that raises do not affect the main thread
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Arthur authored
* initial-commit * start cleaning * small nits * small nits * current updates * add kernels * small refactoring little step * add comments * styling * nit * nits * Style * Small changes * Push dummy mambda simple slow * nit * Use original names * Use original names and remove norm * Updates for inference params * Style nd updates * nits * Match logits * Add a test * Add expected generated text * nits doc, imports and styling * style * oups * dont install kernels, invite users to install the required kernels * let use use the original packages * styling * nits * fix some copieds * update doc * fix-copies * styling done * nits * fix import check * run but wrong cuda ress * mamba CUDA works :) * fix the fast path * config naming nits * conversion script is not required at this stage * finish fixing the fast path: generation make sense now! * nit * Let's start working on the CIs * style * better style * more nits * test nit * quick fix for now * nits * nit * nit * nit * nits * update test rest * fixup * update test * nit * some fixes * nits * update test values * fix styling * nit * support peft * integrations tests require torchg * also add slow markers * styling * chose forward wisely * nits * update tests * fix gradient checkpointing * fixup * nit * fix doc * check copies * fix the docstring * fix some more tests * style * fix beam search * add init schene * update * nit * fix * fixup the doc * fix the doc * fixup * tentative update but slow is no longer good * nit * should we always use float32? * nits * revert wrong changes * res in float32 * cleanup * skip fmt for now * update generation values * update test values running original model * fixup * update tests + rename inference_params to cache_params + make sure training does not use cache_params * small nits * more nits * fix final CIs * style * nit doc * I hope final doc nits * nit * 🫠 * final touch! * fix torch import * Apply suggestions from code review Co-authored-by:
Lysandre Debut <hi@lysand.re> * Apply suggestions from code review * fix fix and fix * fix base model prefix! * nit * Update src/transformers/models/mamba/__init__.py * Update docs/source/en/model_doc/mamba.md Co-authored-by:
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Arthur authored
* fix udop imports * sort imports
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Arthur authored
* style * revert with RP * nit * exact revert
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Arthur Zucker authored
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Arthur authored
* update * ... * nits * arf * 🧼 * beat the last guy * style everyone
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Fanli Lin authored
* use torch_device * Update tests/pipelines/test_pipelines_text_generation.py Co-authored-by:
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Ilyas Moutawwakil authored
* added exllama kernels support for awq models * doc * style * Update src/transformers/modeling_utils.py Co-authored-by:
Marc Sun <57196510+SunMarc@users.noreply.github.com> * refactor * moved exllama post init to after device dispatching * bump autoawq version * added exllama test * style * configurable exllama kernels * copy exllama_config from gptq * moved exllama version check to post init * moved to quantization dockerfile --------- Co-authored-by:
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- 04 Mar, 2024 3 commits
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NielsRogge authored
* First draft * More improvements * More improvements * More fixes * Fix copies * More improvements * More fixes * More improvements * Convert checkpoint * More improvements, set up tests * Fix more tests * Add UdopModel * More improvements * Fix equivalence test * More fixes * Redesign model * Extend conversion script * Use real inputs for conversion script * Add image processor * Improve conversion script * Add UdopTokenizer * Add fast tokenizer * Add converter * Update README's * Add processor * Add fully fledged tokenizer * Add fast tokenizer * Use processor in conversion script * Add tokenizer tests * Fix one more test * Fix more tests * Fix tokenizer tests * Enable fast tokenizer tests * Fix more tests * Fix additional_special_tokens of fast tokenizer * Fix tokenizer tests * Fix more tests * Fix equivalence test * Rename image to pixel_values * Rename seg_data to bbox * More renamings * Remove vis_special_token * More improvements * Add docs * Fix copied from * Update slow tokenizer * Update fast tokenizer design * Make text input optional * Add first draft of processor tests * Fix more processor tests * Fix decoder_start_token_id * Fix test_initialization * Add integration test * More improvements * Improve processor, add test * Add more copied from * Add more copied from * Add more copied from * Add more copied from * Remove print statement * Update README and auto mapping * Delete files * Delete another file * Remove code * Fix test * Fix docs * Remove asserts * Add doc tests * Include UDOP in exotic model tests * Add expected tesseract decodings * Add sentencepiece * Use same design as T5 * Add UdopEncoderModel * Add UdopEncoderModel to tests * More fixes * Fix fast tokenizer * Fix one more test * Remove parallelisable attribute * Fix copies * Remove legacy file * Copy from T5Tokenizer * Fix rebase * More fixes, copy from T5 * More fixes * Fix init * Use ArthurZ/udop for tests * Make all model tests pass * Remove UdopForConditionalGeneration from auto mapping * Fix more tests * fixups * more fixups * fix the tokenizers * remove un-necessary changes * nits * nits * replace truncate_sequences_boxes with truncate_sequences for fix-copies * nit current path * add a test for input ids * ids that we should get taken from c9f7a32f57440d90ff79890270d376a1cc0acb68 * nits converting * nits * apply ruff * nits * nits * style * fix slow order of addition * fix udop fast range as well * fixup * nits * Add docstrings * Fix gradient checkpointing * Update code examples * Skip tests * Update integration test * Address comment * Make fixup * Remove extra ids from tokenizer * Skip test * Apply suggestions from code review Co-authored-by:
ArthurZucker <arthur.zucker@gmail.com> Co-authored-by:
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Donggeun Yu authored
* Update ms_deform_attn_cuda.cu * Update ms_deform_attn_cuda.cuh * Update modeling_deformable_detr.py * Update src/transformers/models/deformable_detr/modeling_deformable_detr.py Co-authored-by:
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Zach Mueller authored
Fully revert atomic checkpointing
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