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7 Commits
| Author | SHA1 | Message | Date | |
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Steven Liu
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c0f8d055ce
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[docs] Redesign (#31757)
* toctree * not-doctested.txt * collapse sections * feedback * update * rewrite get started sections * fixes * fix * loading models * fix * customize models * share * fix link * contribute part 1 * contribute pt 2 * fix toctree * tokenization pt 1 * Add new model (#32615) * v1 - working version * fix * fix * fix * fix * rename to correct name * fix title * fixup * rename files * fix * add copied from on tests * rename to `FalconMamba` everywhere and fix bugs * fix quantization + accelerate * fix copies * add `torch.compile` support * fix tests * fix tests and add slow tests * copies on config * merge the latest changes * fix tests * add few lines about instruct * Apply suggestions from code review Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * fix * fix tests --------- Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * "to be not" -> "not to be" (#32636) * "to be not" -> "not to be" * Update sam.md * Update trainer.py * Update modeling_utils.py * Update test_modeling_utils.py * Update test_modeling_utils.py * fix hfoption tag * tokenization pt. 2 * image processor * fix toctree * backbones * feature extractor * fix file name * processor * update not-doctested * update * make style * fix toctree * revision * make fixup * fix toctree * fix * make style * fix hfoption tag * pipeline * pipeline gradio * pipeline web server * add pipeline * fix toctree * not-doctested * prompting * llm optims * fix toctree * fixes * cache * text generation * fix * chat pipeline * chat stuff * xla * torch.compile * cpu inference * toctree * gpu inference * agents and tools * gguf/tiktoken * finetune * toctree * trainer * trainer pt 2 * optims * optimizers * accelerate * parallelism * fsdp * update * distributed cpu * hardware training * gpu training * gpu training 2 * peft * distrib debug * deepspeed 1 * deepspeed 2 * chat toctree * quant pt 1 * quant pt 2 * fix toctree * fix * fix * quant pt 3 * quant pt 4 * serialization * torchscript * scripts * tpu * review * model addition timeline * modular * more reviews * reviews * fix toctree * reviews reviews * continue reviews * more reviews * modular transformers * more review * zamba2 * fix * all frameworks * pytorch * supported model frameworks * flashattention * rm check_table * not-doctested.txt * rm check_support_list.py * feedback * updates/feedback * review * feedback * fix * update * feedback * updates * update --------- Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com> |
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fxmarty
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80377eb018
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F.scaled_dot_product_attention support (#26572)
* add sdpa * wip * cleaning * add ref * yet more cleaning * and more :) * wip llama * working llama * add output_attentions=True support * bigcode sdpa support * fixes * gpt-bigcode support, require torch>=2.1.1 * add falcon support * fix conflicts falcon * style * fix attention_mask definition * remove output_attentions from attnmaskconverter * support whisper without removing any Copied from statement * fix mbart default to eager renaming * fix typo in falcon * fix is_causal in SDPA * check is_flash_attn_2_available in the models init as well in case the model is not initialized through from_pretrained * add warnings when falling back on the manual implementation * precise doc * wip replace _flash_attn_enabled by config.attn_implementation * fix typo * add tests * style * add a copy.deepcopy on the config in from_pretrained, as we do not want to modify it inplace * obey to config.attn_implementation if a config is passed in from_pretrained * fix is_torch_sdpa_available when torch is not installed * remove dead code * Update src/transformers/modeling_attn_mask_utils.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/modeling_attn_mask_utils.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/modeling_attn_mask_utils.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/modeling_attn_mask_utils.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/modeling_attn_mask_utils.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/bart/modeling_bart.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * remove duplicate pretraining_tp code * add dropout in llama * precise comment on attn_mask * add fmt: off for _unmask_unattended docstring * precise num_masks comment * nuke pretraining_tp in LlamaSDPAAttention following Arthur's suggestion * cleanup modeling_utils * backward compatibility * fix style as requested * style * improve documentation * test pass * style * add _unmask_unattended tests * skip meaningless tests for idefics * hard_check SDPA requirements when specifically requested * standardize the use if XXX_ATTENTION_CLASSES * fix SDPA bug with mem-efficient backend on CUDA when using fp32 * fix test * rely on SDPA is_causal parameter to handle the causal mask in some cases * fix FALCON_ATTENTION_CLASSES * remove _flash_attn_2_enabled occurences * fix test * add OPT to the list of supported flash models * improve test * properly test on different SDPA backends, on different dtypes & properly handle separately the pad tokens in the test * remove remaining _flash_attn_2_enabled occurence * Update src/transformers/modeling_utils.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/modeling_utils.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/modeling_utils.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/modeling_attn_mask_utils.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update docs/source/en/perf_infer_gpu_one.md Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * remove use_attn_implementation * fix docstring & slight bug * make attn_implementation internal (_attn_implementation) * typos * fix tests * deprecate use_flash_attention_2=True * fix test * add back llama that was removed by mistake * fix tests * remove _flash_attn_2_enabled occurences bis * add check & test that passed attn_implementation is valid * fix falcon torchscript export * fix device of mask in tests * add tip about torch.jit.trace and move bt doc below sdpa * fix parameterized.expand order * move tests from test_modeling_attn_mask_utils to test_modeling_utils as a relevant test class is already there * update sdpaattention class with the new cache * Update src/transformers/configuration_utils.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/models/bark/modeling_bark.py * address review comments * WIP torch.jit.trace fix. left: test both eager & sdpa * add test for torch.jit.trace for both eager/sdpa * fix falcon with torch==2.0 that needs to use sdpa * fix doc * hopefully last fix * fix key_value_length that has no default now in mask converter * is it flacky? * fix speculative decoding bug * tests do pass * fix following #27907 --------- Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> |
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Yoach Lacombe
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9dd58c53dd
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update Bark FA2 docs (#27400)
* update Bark FA2 docs * update benchmark section * Update bark.md * Apply suggestions from code review Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * rephrase --------- Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> |
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Maria Khalusova
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5964f820db
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[Docs] Model_doc structure/clarity improvements (#26876)
* first batch of structure improvements for model_docs * second batch of structure improvements for model_docs * more structure improvements for model_docs * more structure improvements for model_docs * structure improvements for cv model_docs * more structural refactoring * addressed feedback about image processors |
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Susheel Thapa
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b3961f7291
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Chore: Typo fixed in multiple files of docs/source/en/model_doc (#26833)
* Chore: Typo fixed in multiple files of docs/source/en/model_doc * Update docs/source/en/model_doc/nllb-moe.md Co-authored-by: Aryan V S <avs050602@gmail.com> --------- Co-authored-by: Aryan V S <avs050602@gmail.com> |
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Yoach Lacombe
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8455346c5c
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Update bark doc (#25234)
* add mention to optimization in Bark docs * add offload mention in docs * Apply suggestions from code review Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * Update bark docs. * Update bark.md --------- Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> |
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Yoach Lacombe
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f42a35e611
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Add bark (#24086)
* first raw version of the bark integration * working code on small models with single run * add converting script from suno weights 2 hf * many changes * correct past_kv output * working implementation for inference * update the converting script according to the architecture changes * add a working end-to-end inference code * remove some comments and make small changes * remove unecessary comment * add docstrings and ensure no unecessary intermediary output during audio generation * remove done TODOs * make style + add config docstrings * modification for batch inference support on the whole model * add details to .generation_audio method * add copyright * convert EncodecModel from original library to transformers implementation * add two class in order to facilitate model and sub-models loading from the hub * add support of loading the whole model * add BarkProcessor * correct modeling according to processor output * Add proper __init__ and auto support * Add up-to-date copyright/license message * add relative import instead of absolute * cleaner head_dim computation * small comment removal or changes * more verbose LayerNorm init method * specify eps for clearer comprehension * more verbose variable naming in the MLP module * remove unecessary BarkBlock parameter * clearer code in the forward pass of the BarkBlock * remove _initialize_modules method for cleaner code * Remove unnecessary methods from sub-models * move code to remove unnecessary function * rename a variable for clarity and change an assert * move code and change variable name for clarity * remove unnecessary asserts * correct small bug * correct a comment * change variable names for clarity * remove asserts * change import from absolute to relative * correct small error due to comma missing + correct import * Add attribute Bark config * add first version of tests * update attention_map * add tie_weights and resize_token_embeddings for fineModel * correct getting attention_mask in generate_text_semantic * remove Bark inference trick * leave more choices in barkProcessor * remove _no_split_modules * fixe error in forward of block and introduce clearer notations * correct converting script with last changes * make style + add draft bark.mdx * correct BarkModelTest::test_generate_text_semantic * add Bark in main README * add dummy_pt_objects for Bark * add missing models in the main init * correct test_decoder_model_past_with_large_inputs * disable torchscript test * change docstring of BarkProcessor * Add test_processor_bark * make style * correct copyrights * add bark.mdx + make style, quality and consistency * Apply suggestions from code review Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * Remove unnecessary test method * simply logic of a test * Only check first ids for slow audio generation * split full end-to-end generation tests * remove unneccessary comment * change submodel names for clearer naming * remove ModuleDict from modeling_bark * combine two if statements * ensure that an edge misued won't happen * modify variable name * move code snippet to the right place (coarse instead of semantic) * change BarkSemanticModule -> BarkSemanticModel * align BarkProcessor with transformers paradigm * correct BarkProcessor tests with last commit changes * change _validate_voice_preset to an instance method instead of a class method * tie_weights already called with post_init * add codec_model config to configuration * update bark modeling tests with recent BarkProcessor changes * remove SubModelPretrainedModel + change speakers embeddings prompt type in BarkModel * change absolute imports to relative * remove TODO * change docstrings * add examples to docs and docstrings * make style * uses BatchFeature in BarkProcessor insteads of dict * continue improving docstrings and docs + make style * correct docstrings examples * more comprehensible speaker_embeddings load/Save * rename speaker_embeddings_dict -> speaker_embeddings * correct bark.mdx + add bark to documentation_tests * correct docstrings configuration_bark * integrate last nit suggestions * integrate BarkGeneration configs * make style * remove bark tests from documentation_tests.txt because timeout - tested manually * add proper generation config initialization * small bark.mdx documentation changes * rename bark.mdx -> bark.md * add torch.no_grad behind BarkModel.generate_audio() * replace assert by ValueError in convert_suno_to_hf.py * integrate a series of short comments from reviewer * move SemanticLogitsProcessors and remove .detach() from Bark docs and docstrings * actually remove SemanticLogitsProcessor from modeling_bark.oy * BarkProcessor returns a single output instead of tuple + correct docstrings * make style + correct bug * add initializer_range to BarkConfig + correct slow modeling tests * add .clone() to history_prompt.coarse_prompt to avoid modifying input array * Making sure no extra "`" are present * remove extra characters in modeling_bark.py * Correct output if history_prompt is None * remove TODOs * remove ravel comment * completing generation_configuration_bark.py docstrings * change docstrings - number of audio codebooks instead of Encodec codebooks * change 'bias' docstrings in configuration_bark.py * format code * rename BarkModel.generate_audio -> BarkModel.generate_speech * modify AutoConfig instead of EncodecConfig in BarkConfig * correct AutoConfig wrong init * refactor BarkModel and sub-models generate_coarse, generate_fine, generate_text_semantic * remove SemanticLogitsProcessor and replace it with SuppressTokensLogitsProcessor * move nb_codebook related config arguments to BarkFineConfig * rename bark.mdx -> bark.md * correcting BarkModelConfig from_pretrained + remove keys_to_ignore * correct bark.md with correct hub path * correct code bug in bark.md * correct list tokens_to_suppress * modify Processor to load nested speaker embeddings in a safer way * correct batch sampling in BarkFineModel.generate_fine * Apply suggestions from code review Small docstrings correction and code improvements Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * give more details about num_layers in docstrings * correct indentation mistake * correct submodelconfig order of docstring variables * put audio models in alphabetical order in utils/check_repo.my * remove useless line from test_modeling_bark.py * makes BarkCoarseModelTest inherits from (ModelTesterMixin, GenerationTesterMixin, unittest.TestCase) instead of BarkSemanticModelTest * make a Tester class for each sub-model instead of inheriting * add test_resize_embeddings=True for Bark sub-models * add Copied from transformers.models.gpt_neo.modeling_gpt_neo.GPTNeoSelfAttention._split_heads * remove 'Copied fom Bark' comment * remove unneccessary comment * change np.min -> min in modeling_bark.py * refactored all custom layers to have Bark prefix * add attention_mask as an argument of generate_text_semantic * refactor sub-models start docstrings to have more precise config class definition * move _tied_weights_keys overriding * add docstrings to generate_xxx in modeling_bark.py * add loading whole BarkModel to convert_suno_to_hf * refactor attribute and variable names * make style convert_suno * update bark checkpoints * remove never entered if statement * move bark_modeling docstrings after BarkPretrainedModel class definition * refactor modeling_bark.py: kv -> key_values * small nits - code refactoring and removing unecessary lines from _init_weights * nits - replace inplace method by variable assigning * remove *optional* when necessary * remove some lines in generate_speech * add default value for optional parameter * Refactor preprocess_histories_before_coarse -> preprocess_histories Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * correct usage after refactoring * refactor Bark's generate_xxx -> generate and modify docstrings and tests accordingly * update docstrings python in configuration_bark.py * add bark files in utils/documentation_test.txt * correct docstrings python snippet * add the ability to use parameters in the form of e.g coarse_temperature * add semantic_max_new_tokens in python snippet in docstrings for quicker generation * Reformate sub-models kwargs in BakModel.generate Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * correct kwargs in BarkModel.generate * correct attention_mask kwarg in BarkModel.generate * add tests for sub-models args in BarkModel.generate and correct BarkFineModel.test_generate_fp16 * enrich BarkModel.generate docstrings with a description of how to use the kwargs --------- Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> |