"docs/source/vscode:/vscode.git/clone" did not exist on "015f8e110d270a0ad42de4ae5b98198d69eb1964"
- 09 Dec, 2023 2 commits
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Justin Yu authored
* fix tune integration for ray 2.7+ Signed-off-by:
Justin Yu <justinvyu@anyscale.com> * add version check for ray tune backend availability Signed-off-by:
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Joshua Lochner authored
* [CLAP] Replace hard-coded batch size to enable dynamic ONNX export * Add back docstring
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- 08 Dec, 2023 14 commits
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fxmarty authored
* 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:
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Joao Gante authored
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zhc7 authored
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Zach Mueller authored
* Fuffill request * Add test * Better test * Apply suggestions from code review Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by:
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Arthur authored
* fix llava * nits * attention_mask was forgotten * nice * :) * fixup
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Pedro Cuenca authored
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Yoach Lacombe authored
* update converting script * make style
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Xin Qiu authored
* Fix issues in add and is_done for BeamHypotheses * make newly added arguments optional for better compatibility * Directly use cur_len as generated_len, add note for retrocompatibility * update test expectation * make cur_len represents the length of the entire sequence including the decoder prompt * remove redundant if/else in testing
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Xin Qiu authored
* Fix beam score calculation issue for tensorflow version * fix transition score computation error * make cur_len represent the entire sequence length including decoder prompt
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Jonathon Belotti authored
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Charbel Abi Daher authored
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Saibo-creator authored
Fix: Raise informative exception when `prefix_allowed_tokens_fn` return empty set of tokens (#27797) Co-authored-by: -
fxmarty authored
[
⚠ ️ removed a default argument] Make `AttentionMaskConverter` compatible with `torch.compile(..., fullgraph=True)` (#27868) * remove bugged torch.float32 default * add test * fix tests * fix test * fix doc -
Tom Aarsen authored
* Draft version of new KV Caching This should allow Attention Sinks (https://github.com/tomaarsen/attention_sinks) / StreamingLLM (https://arxiv.org/abs/2309.17453) to be easily implemented in a third-party or in transformers directly * Address numerous PR suggestions 1. Move layer_idx from cache to ...Attention. Removes confusing set_layer_idx magic. 2. Always convert past_key_values to Cache instance at the start of ...Attention, removes all other isinstance calls. 3. Remove __bool__ and __getitem__ magic as they're confusing. 4. past_key_values.update(key, value, idx) now returns key, value. 5. Add use_legacy_cache flag, defaults to None, i.e. Falsey. This breaks generate for now, until 1) the cache is used is generate() or 2) use_legacy_cache is defaulted to True in generate() until we change it in another PR. 6. Separate key_cache and value_cache. Some work is still needed to see if the SinkCache can conveniently be implemented with just one update method. * Implement the SinkCache through backward+forward rotations * Integrate (Sink)Cache with Llama FA2 * Set use_legacy_cache=True as default, allows for test passes * Move from/to_legacy_cache to ...Model class * Undo unnecessary newline change * Remove copy utility from deprecated OpenLlama * Match import style * manual rebase with main * Cache class working with generate (#1) * Draft version of new KV Caching This should allow Attention Sinks (https://github.com/tomaarsen/attention_sinks) / StreamingLLM (https://arxiv.org/abs/2309.17453 ) to be easily implemented in a third-party or in transformers directly * Address numerous PR suggestions 1. Move layer_idx from cache to ...Attention. Removes confusing set_layer_idx magic. 2. Always convert past_key_values to Cache instance at the start of ...Attention, removes all other isinstance calls. 3. Remove __bool__ and __getitem__ magic as they're confusing. 4. past_key_values.update(key, value, idx) now returns key, value. 5. Add use_legacy_cache flag, defaults to None, i.e. Falsey. This breaks generate for now, until 1) the cache is used is generate() or 2) use_legacy_cache is defaulted to True in generate() until we change it in another PR. 6. Separate key_cache and value_cache. Some work is still needed to see if the SinkCache can conveniently be implemented with just one update method. * Integrate (Sink)Cache with Llama FA2 * Move from/to_legacy_cache to ...Model class * Undo unnecessary newline change * Match import style * working generate * Add tests; Simplify code; Apply changes to Mistral and Persimmon * fix rebase mess * a few more manual fixes * last manual fix * propagate changes to phi * upgrade test * add use_legacy_cache docstring; beef up tests * reintroduce unwanted deletes --------- Co-authored-by:
Tom Aarsen <Cubiegamedev@gmail.com> * move import * add default to model_kwargs.get('use_legacy_cache') * correct failing test * Apply suggestions from code review Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> * apply PR suggestions * fix failing test * Apply suggestions from code review Co-authored-by:
Tom Aarsen <37621491+tomaarsen@users.noreply.github.com> * PR comments * tmp commit * add docstrings * more tests, more docstrings, add to docs * derp * tmp commit * tmp dbg * more dbg * fix beam search bug * cache can be a list of tuples in some models * fix group beam search * all but sinkcache integration tests * fix sink cache and add hard integration test * now also compatible with input_embeds input * PR comments * add Cache support to Phi+FA2 * make fixup --------- Co-authored-by:
Joao Gante <joao@huggingface.co> Co-authored-by:
Joao Gante <joaofranciscocardosogante@gmail.com> Co-authored-by:
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- 07 Dec, 2023 9 commits
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Joao Gante authored
Co-authored-by: -
Matt authored
* Un-skip tests * Add aliasing support to tf_to_pt_weight_rename * Refactor tf-to-pt weight rename for simplicity * Patch mobilebert * Let us pray that the transfo-xl one works * Add XGLM rename * Expand the test to see if we can get more models to break * Expand the test to see if we can get more models to break * Fix MPNet (it was actually an unrelated bug) * Fix MPNet (it was actually an unrelated bug) * Add speech2text fix * Update src/transformers/modeling_tf_pytorch_utils.py Co-authored-by:
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Hz, Ji authored
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Sourab Mangrulkar authored
* update `create_model_card` to properly save peft details when using Trainer with PEFT * nit * Apply suggestions from code review Co-authored-by:
Benjamin Bossan <BenjaminBossan@users.noreply.github.com> --------- Co-authored-by:
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Younes Belkada authored
* add model like * logits match * minor fixes * fixes * up * up * add todo * llava processor * keep the processor simple * add conversion script * fixup * fix copies * up * add to index * fix config + logits * fix * refactor * more refactor * more refactor * fix copies * add authors * v1 tests * add `LlavaProcessor` in init * remove unneeded import * up * up * docs * up * fix CI * fix CI * add attention mask in test * make fixup * remove the vision model * that' s the dirty way to do it * nits * nits * updates * add more tests * add input tests * fixup * more styling * nits * updates amd cleanup * fixup the generation expected results * fix the testing script * some cleanup and simplification which does not work yet but almost there! * make correct dispatch operations * vectorize works for batch of images and text * last todos * nits * update test and modeling code * remove useless function for now * fix few issues * fix generation * some nits * add bakllava * nits * remove duplicated code * finis merge * cleanup * missed this line * fill the todos * add left padding offset * add left and rignt padding logic * bool to properly index * make sure * more cleanups * batch is fixed
😉 * add correct device for tensor creation * fix some dtype missmatch * ruff * update conversion script * Update src/transformers/__init__.py * fa 2 support + fix conversion script * more * correct reshaping * fix test dict * fix copies by ignoring * fix nit * skip clip vision model * fixup * fixup * LlavaForVisionText2Text -> LlavaForCausalLM * update * fix * raise correct errors * fix * docs * nuke for now * nits here and there * fixup * fix remaining tests * update LlavaForConditionalGeneration instead of CausalLM * fixups * pipeline support * slow and piepline tests * supports batch * nits * cleanup * fix first integration tests * add pad token where needed * correct etsts * fixups * update pipeline testr * fix quality * nits * revert unneeded change * nit * use BatchFeature * from ...feature_extraction_utils import BatchFeature * nits * nits * properly update * more f*** nits * fix copies * comment * keep slow test slow * Update src/transformers/models/llava/processing_llava.py Co-authored-by:Lysandre Debut <hi@lysand.re> * update docstring * nit * move to not doctested because of timeout issues * fixup * add description * more * fix-copies * fix docs * add beam search * add more comments * add typehints on processor * add speedup plot * update slow tests and docs * push test * push batched test * fix batched generation with different number of images * remove benchmark due to a bug * fix test * fix copies * add gcolab demo --------- Co-authored-by:
Arthur Zucker <arthur.zucker@gmail.com> Co-authored-by:
shauray8 <shauray8@users.noreply.github.com> Co-authored-by:
haotian-liu <haotian-liu@users.noreply.github.com> Co-authored-by:
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Susnato Dhar authored
* add FA and modify doc file * test_flash_attn_2_generate_padding_right test overwritten * comment * modify persimmon modeling file * added speedup graph * more changes
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jiqing-feng authored
* use _prepare_4d_attention_mask * fix comment
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Alex McKinney authored
* Copies `modeling_flax_gpt_neo.py` to start * MLP Block. WIP Attention and Block * Adds Flax implementation of `LlamaMLP` Validated with in-file test. Some slight numeric differences, but assuming it isn't an issue * Adds `FlaxLlamaRMSNorm` layer `flax.linen` includes `RMSNorm` layer but not necessarily in all versions. Hence, we add in-file. * Adds FlaxLlamaAttention Copied from GPT-J as it has efficient caching implementation as well as rotary embeddings. Notice numerically different, but not by a huge amount. Needs investigating * Adds `FlaxLlamaDecoderLayer` numerically inaccurate, debugging.. * debugging rotary mismatch gptj uses interleaved whilst llama uses contiguous i think they match now but still final result is wrong. maybe drop back to just debugging attention layer? * fixes bug with decoder layer still somewhat numerically inaccurate, but close enough for now * adds markers for what to implement next the structure here diverges a lot from the PT version. not a big fan of it, but just get something working for now * implements `FlaxLlamaBlockCollection`] tolerance must be higher than expected, kinda disconcerting * Adds `FlaxLlamaModule` equivalent PyTorch model is `LlamaModel` yay! a language model
🤗 * adds `FlaxLlamaForCausalLMModule` equivalent to `LlamaForCausalLM` still missing returning dict or tuple, will add later * start porting pretrained wrappers realised it probably needs return dict as a prereq * cleanup, quality, style * readds `return_dict` and model output named tuples * (tentatively) pretrained wrappers work🔥 * fixes numerical mismatch in `FlaxLlamaRMSNorm` seems `jax.lax.rsqrt` does not match `torch.sqrt`. manually computing `1 / jax.numpy.sqrt` results in matching values. * [WIP] debugging numerics * numerical match I think issue was accidental change of backend. forcing CPU fixes test. We expect some mismatch on GPU. * adds in model and integration tests for Flax Llama summary of failing: - mul invalid combination of dimensions - one numerical mismatch - bf16 conversion (maybe my local backend issue) - params are not FrozenDict * adds missing TYPE_CHECKING import and `make fixup` * adds back missing docstrings needs review on quality of docstrings, not sure what is required. Furthermore, need to check if `CHECKPOINT_FOR_DOC` is valid. See TODO * commenting out equivalence test as can just use common * debugging * Fixes bug where mask and pos_ids were swapped in pretrained models This results in all tests passing now🔥 * cleanup of modeling file * cleanup of test file * Resolving simpler review comments * addresses more minor review comments * fixing introduced pytest errors from review * wip additional slow tests * wip tests need to grab a GPU machine to get real logits for comparison otherwise, slow tests should be okay * `make quality`, `make style` * adds slow integration tests - checking logits - checking hidden states - checking generation outputs * `make fix-copies` * fix mangled function following `make fix-copies` * adds missing type checking imports * fixes missing parameter checkpoint warning * more finegrained 'Copied from' tags avoids issue of overwriting `LLAMA_INPUTS_DOCSTRING` * swaps import guards ??? how did these get swapped initially? * removing `inv_freq` again as pytorch version has now removed * attempting to get CI to pass * adds doc entries for llama flax models * fixes typo in __init__.py imports * adds back special equivalence tests these come from the gpt neo flax tests. there is special behaviour for these models that needs to override the common version * overrides tests with dummy to see if CI passes need to fill in these tests later * adds my contribution to docs * `make style; make quality` * replaces random masking with fixed to work with flax version * `make quality; make style` * Update src/transformers/models/llama/modeling_flax_llama.py Co-authored-by:Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * Update src/transformers/models/llama/modeling_flax_llama.py Co-authored-by:
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Xin Qiu authored
* Fix beam score calculation issue for JAX * Fix abstract tracer value errors
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- 06 Dec, 2023 2 commits
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Younes Belkada authored
* add flash-attn-2 support for GPT-neo-x * fixup * add comment * revert * fixes * update docs * comment * again * fix copies * add plot + fix copies * Update docs/source/en/model_doc/gpt_neox.md
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Yih-Dar authored
* fix --------- Co-authored-by:ydshieh <ydshieh@users.noreply.github.com>
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- 05 Dec, 2023 8 commits
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Vedat Baday authored
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NielsRogge authored
Address test
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Arindam Jati authored
* patchtsmixer initial commit * x,y->context_values,target_values, unittest addded * cleanup code * minor * return hidden states * model tests, partial integration tests * ettm notebook temporary * minor * config mask bug fix, tests updated * final ETT notebooks * add selfattn * init * added docstrings * PatchTSMixerForPretraining -> PatchTSMixerForMaskPretraining * functionality tests added * add start and input docstrings * docstring edits * testcase edits * minor changes * docstring error fixed * ran make fixup * finalize integration tests and docs * minor * cleaned gitignore * added dataclass decorator, ran black formatter * ran ruff * formatting * add slow decorator * renamed in_Channel to input_size and default to 1 * shorten dataclass names * use smaller model for testing * moved the 3 heads to the modeling file * use scalers instead of revin * support forecast_channel_indices * fix regression scaling * undo reg. scaling * removed unneeded classes * forgot missing * add more layers * add copied positional_encoding * use patchmask from patchtst * removed dependency on layers directory * formatting * set seed * removed unused imports * fixed forward signature test * adding distributional head for PatchTSMixerForecasting * add generate to forecast * testcases for generate * add generate and distributional head for regression * raise Exception for negative values for neg binominal distribution * formatting changes * remove copied from patchtst and add TODO for test passing * make copies * doc edits * minor changes * format issues * minor changes * minor changes * format docstring * change some class names to PatchTSMixer + class name Transpose to PatchTSMixerTranspose GatedAttention to PatchTSMixerGatedAttention * change NormLayer to PatchTSMixerNormLayer * change MLP to PatchTSMixerMLP * change PatchMixer to PatchMixerBlock, FeatureMixer to FeatureMixerBlock * change ChannelFeatureMixer to ChannelFeatureMixerBlock * change PatchMasking to PatchTSMixerMasking * change Patchify to PatchTSMixerPatchify * list to `list` * fix docstrings * formatting * change bs to batch_size, edit forecast_masking * edit random_masking * change variable name and update docstring in PatchTSMixerMasking * change variable name and update docstring in InjectScalerStatistics4D * update forward call in PatchTSMixerTranspose * change variable name and update docstring in PatchTSMixerNormLayer * change variable name and update docstring in PatchTSMixerMLP * change variable name and update docstring in ChannelFeatureMixerBlock * formatting * formatting issues * docstring issue * fixed observed_mask type in docstrings * use FloatTensor type * formatting * fix rescaling issue in forecasting, fixed integration tests * add docstring from decorator * fix docstring * Update README.md Co-authored-by:
NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/patchtsmixer/configuration_patchtsmixer.py Co-authored-by:
Arindam Jati <arindam.jati@ibm.com> Co-authored-by:
vijaye12 <vijaye12@in.ibm.com> Co-authored-by:
Kashif Rasul <kashif.rasul@gmail.com> Co-authored-by:
nnguyen <nnguyen@us.ibm.com> Co-authored-by:
vijaye12 <vijaykr.e@gmail.com> Co-authored-by:
Nam Nguyen <namctin@gmail.com> Co-authored-by:
Wesley Gifford <79663411+wgifford@users.noreply.github.com> Co-authored-by:
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Bram Willemsen authored
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Younes Belkada authored
support accelerate for clip-vision
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Younes Belkada authored
* v1 fusing modules * add fused mlp support * up * fix CI * block save_pretrained * fixup * small fix * add new condition * add v1 docs * add some comments * style * fix nit * adapt from suggestion * add check * change arg names * change variables name * Update src/transformers/integrations/awq.py Co-authored-by:
Marc Sun <57196510+SunMarc@users.noreply.github.com> * Update src/transformers/utils/quantization_config.py Co-authored-by:
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NielsRogge authored
* Make image processors more general * Add backwards compatibility for KOSMOS-2 * Remove use_square_size everywhere * Remove script
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Yih-Dar authored
fix Co-authored-by:
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- 04 Dec, 2023 5 commits
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Sanchit Gandhi authored
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Yih-Dar authored
* fix * fix * Use TRUST_REMOTE_CODE * fix doc * fix --------- Co-authored-by: -
Arthur authored
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Yeounoh Chung authored
* [XLA] Re-enable broken _tpu_save for XLATensors, by explicitly moving to cpu * linter-fix
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fxmarty authored
* support FA2 * fix typo * fix broken tests * fix more test errors * left/right * fix bug * more test * typo * fix layout flash attention falcon * do not support this case * use allclose instead of equal * fix various bugs with flash attention * bump * fix test * fix mistral * use skiptest instead of return that may be misleading * add fix causal arg flash attention * fix copies * more explicit comment * still use self.is_causal * fix causal argument * comment * fixes * update documentation * add link * wrong test * simplify FA2 RoCm requirements * update opt * make flash_attn_uses_top_left_mask attribute private and precise comment * better error handling * fix copy & mistral * Update src/transformers/modeling_utils.py Co-authored-by:
Felix Marty <felix@hf.co> Co-authored-by:
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