- 31 Jan, 2024 1 commit
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Kian Sierra McGettigan authored
* direct copy from llama work * mistral modules forward pass working * flax mistral forward pass with sliding window * added tests * added layer collection approach * Revert "added layer collection approach" This reverts commit 0e2905bf2236ec323163fc1a9f0c016b21aa8b8f. * Revert "Revert "added layer collection approach"" This reverts commit fb17b6187ac5d16da7c461e1130514dc3d137a43. * fixed attention outputs * added mistral to init and auto * fixed import name * fixed layernorm weight dtype * freeze initialized weights * make sure conversion consideres bfloat16 * added backend * added docstrings * added cache * fixed sliding window causal mask * passes cache tests * passed all tests * applied make style * removed commented out code * applied fix-copies ignored other model changes * applied make fix-copies * removed unused functions * passed generation integration test * slow tests pass * fixed slow tests * changed default dtype from jax.numpy.float32 to float32 for docstring check * skip cache test for FlaxMistralForSequenceClassification since if pad_token_id in input_ids it doesn't score previous input_ids * updated checkpoint since from_pt not included * applied black style * removed unused args * Applied styling and fixup * changed checkpoint for doc back * fixed rf after adding it to hf hub * Add dummy ckpt * applied styling * added tokenizer to new ckpt * fixed slice format * fix init and slice * changed ref for placeholder TODO * added copies from Llama * applied styling * applied fix-copies * fixed docs * update weight dtype reconversion for sharded weights * removed Nullable input ids * Removed unnecessary output attentions in Module * added embedding weight initialziation * removed unused past_key_values * fixed deterministic * Fixed RMS Norm and added copied from * removed input_embeds * applied make style * removed nullable input ids from sequence classification model * added copied from GPTJ * added copied from Llama on FlaxMistralDecoderLayer * added copied from to FlaxMistralPreTrainedModel methods * fix test deprecation warning * freeze gpt neox random_params and fix copies * applied make style * fixed doc issue * skipped docstring test to allign # copied from * applied make style * removed FlaxMistralForSequenceClassification * removed unused padding_idx * removed more sequence classification * removed sequence classification * applied styling and consistency * added copied from in tests * removed sequence classification test logic * applied styling * applied make style * removed freeze and fixed copies * undo test change * changed repeat_kv to tile * fixed to key value groups * updated copyright year * split casual_mask * empty to rerun failed pt_flax_equivalence test FlaxWav2Vec2ModelTest * went back to 2023 for tests_pr_documentation_tests * went back to 2024 * changed tile to repeat * applied make style * empty for retry on Wav2Vec2
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- 21 Dec, 2023 1 commit
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Arthur authored
* some nits * update test * add support d\sd[a * remove some dummy inputs * all good * style * nits * fixes * fix more copies * nits * styling * fix * Update src/transformers/models/mistral/modeling_mistral.py Co-authored-by:
Younes Belkada <49240599+younesbelkada@users.noreply.github.com> * add a slow test just to be sure * fixup --------- Co-authored-by:
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- 20 Dec, 2023 1 commit
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Joao Gante authored
Co-authored-by:Merve Noyan <merveenoyan@gmail.com>
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- 08 Dec, 2023 1 commit
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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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- 07 Dec, 2023 2 commits
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fxmarty authored
fix device of mask in tests
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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
馃 * 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馃敟 * 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馃敟 * 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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- 27 Nov, 2023 1 commit
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Yanan Xie authored
* Fix mistral generate for long prompt / response * Add unit test * fix linter * fix linter * fix test * add assisted generation test for mistral and load the model in 4 bit + fa2
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- 24 Nov, 2023 1 commit
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Yih-Dar authored
fix Co-authored-by:ydshieh <ydshieh@users.noreply.github.com>
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- 21 Nov, 2023 2 commits
- 16 Nov, 2023 1 commit
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Arthur authored
* try to stylify using ruff * might need to remove these changes? * use ruf format andruff check * use isinstance instead of type comparision * use # fmt: skip * use # fmt: skip * nits * soem styling changes * update ci job * nits isinstance * more files update * nits * more nits * small nits * check and format * revert wrong changes * actually use formatter instead of checker * nits * well docbuilder is overwriting this commit * revert notebook changes * try to nuke docbuilder * style * fix feature exrtaction test * remve `indent-width = 4` * fixup * more nits * update the ruff version that we use * style * nuke docbuilder styling * leve the print for detected changes * nits * Remove file I/O Co-authored-by:
charliermarsh <charlie.r.marsh@gmail.com> * style * nits * revert notebook changes * Add # fmt skip when possible * Add # fmt skip when possible * Fix * More ` # fmt: skip` usage * More ` # fmt: skip` usage * More ` # fmt: skip` usage * NIts * more fixes * fix tapas * Another way to skip * Recommended way * Fix two more fiels * Remove asynch Remove asynch --------- Co-authored-by:
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- 09 Nov, 2023 1 commit
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Yih-Dar authored
fix Co-authored-by:
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- 31 Oct, 2023 1 commit
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Hz, Ji authored
* device agnostic models testing * add decorator `require_torch_fp16` * make style * apply review suggestion * Oops, the fp16 decorator was misused
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- 16 Oct, 2023 1 commit
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Yih-Dar authored
fix Co-authored-by:
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- 12 Oct, 2023 1 commit
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Yih-Dar authored
* fix * fix * fix --------- Co-authored-by:
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- 11 Oct, 2023 1 commit
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Yih-Dar authored
* copied statement for test files --------- Co-authored-by:
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- 06 Oct, 2023 1 commit
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fxmarty authored
* remove unnecessary unsqueeze-squeeze in llama * correct other models * fix * revert gpt_neox_japanese * fix copie * fix test
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- 03 Oct, 2023 1 commit
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Younes Belkada authored
* add FA-2 support for mistral * fixup * add sliding windows * fixing few nits * v1 slicing cache - logits do not match * add comment * fix bugs * more mem efficient * add warning once * add warning once * oops * fixup * more comments * copy * add safety checker * fixup * Update src/transformers/models/mistral/modeling_mistral.py Co-authored-by:
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- 27 Sep, 2023 1 commit
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Chris Bamford authored
* [Mistral] Mistral-7B-v0.1 support * fixing names * slightly longer test * fixups * not_doctested * wrongly formatted references * make fixuped --------- Co-authored-by:
Timothee Lacroix <t@eugen.ai> Co-authored-by:
timlacroix <t@mistral.ai>
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