- 13 Jun, 2022 8 commits
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Daniel Stancl authored
* Initial commit * Make some fixes * Make PT model full forward pass * Drop TF & Flax implementation, fix copies etc * Add Flax model and update some corresponding stuff * Drop some TF things * Update config and flax local attn * Add encoder_attention_type to config * . * Update docs * Do some cleansing * Fix some issues -> make style; add some docs * Fix position_bias + mask addition + Update tests * Fix repo consistency * Fix model consistency by removing flax operation over attn_mask * [WIP] Add PT TGlobal LongT5 * . * [WIP] Add flax tglobal model * [WIP] Update flax model to use the right attention type in the encoder * Fix flax tglobal model forward pass * Make the use of global_relative_attention_bias * Add test suites for TGlobal model * Fix minor bugs, clean code * Fix pt-flax equivalence though not convinced with correctness * Fix LocalAttn implementation to match the original impl. + update READMEs * Few updates * Update: [Flax] improve large model init and loading #16148 * Add ckpt conversion script accoring to #16853 + handle torch device placement * Minor updates to conversion script. * Typo: AutoModelForSeq2SeqLM -> FlaxAutoModelForSeq2SeqLM * gpu support + dtype fix * Apply some suggestions from code review Co-authored-by:
Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> * * Remove (de)parallelize stuff * Edit shape comments * Update README.md * make fix-copies * Remove caching logic for local & tglobal attention * Apply another batch of suggestions from code review * Add missing checkpoints * Format converting scripts * Drop (de)parallelize links from longT5 mdx * Fix converting script + revert config file change * Revert "Remove caching logic for local & tglobal attention" This reverts commit 2a619828f6ddc3e65bd9bb1725a12b77fa883a46. * Stash caching logic in Flax model * Make side relative bias used always * Drop caching logic in PT model * Return side bias as it was * Drop all remaining model parallel logic * Remove clamp statements * Move test files to the proper place * Update docs with new version of hf-doc-builder * Fix test imports * Make some minor improvements * Add missing checkpoints to docs * Make TGlobal model compatible with torch.onnx.export * Replace some np.ndarray with jnp.ndarray * Fix TGlobal for ONNX conversion + update docs * fix _make_global_fixed_block_ids and masked neg value * update flax model * style and quality * fix imports * remove load_tf_weights_in_longt5 from init and fix copies * add slow test for TGlobal model * typo fix * Drop obsolete is_parallelizable and one warning * Update __init__ files to fix repo-consistency * fix pipeline test * Fix some device placements * [wip]: Update tests -- need to generate summaries to update expected_summary * Fix quality * Update LongT5 model card * Update (slow) summarization tests * make style * rename checkpoitns * finish * fix flax tests Co-authored-by:
phungvanduy <pvduy23@gmail.com> Co-authored-by:
patil-suraj <surajp815@gmail.com>
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haohanchen-yagao authored
* Add FP16 supporot for sagemaker model parallel * minor fix * fix indentation * handle mix precision exception for smmp * minor fix * remove amp implementation on SMMP * remove redundant stuff * reformat trainer * restyling * reformat
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Wang, Yi authored
* enable cpu distribution training using mpirun *command like * mpirun -n 2 python3 run_qa.py --no_cuda --xpu_backend ccl xxxx *MASTER_ADDR and MASTER_PORT should be set as env *export MASTER_ADDR=127.0.0.1 *export MASTER_PORT=29500 Signed-off-by:
Wang, Yi A <yi.a.wang@intel.com> * fix according to the review comment Signed-off-by:
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Bram Vanroy authored
* allow scope from trainer arg * add ray_scope to training args * escape double quotes * make style && quality * attempt to solve doc style issues * splitting up URLs for style * make fixup * Update src/transformers/training_args.py Co-authored-by:
Antoni Baum <antoni.baum@protonmail.com> * make style Co-authored-by:
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Will Frey authored
I'm guessing that the intention was to have the `_no_split_modules` class attribute for `GPTNeoXPreTrainedModel` to be set to `["GPTNeoXLayer"]`, akin to how its set as `["GPTJBlock"]` for `GPTJPreTrainedModel`. If this is incorrect, please feel free to just close the PR. Thanks!
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Sylvain Gugger authored
* Fix dtype getters * Proper fix for dtype getter * Style and commant * Always use last for consistency * Quality
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Saint authored
Co-authored-by:Saint <saint@st-mini.local>
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Sijun He authored
* wip * rebase * all tests pass * rebase * ready for PR * address comments * fix styles * add require_torch to pipeline test * remove remote image to improve CI consistency * address comments; fix tf/flax tests * address comments; fix tf/flax tests * fix tests; add alias * repo consistency tests * Update src/transformers/pipelines/visual_question_answering.py Co-authored-by:
NielsRogge <48327001+NielsRogge@users.noreply.github.com> * address comments * Update src/transformers/pipelines/visual_question_answering.py Co-authored-by:
Sijun He <sijunhe@Sijuns-MacBook-Pro.local> Co-authored-by:
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- 10 Jun, 2022 8 commits
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Domenic Rosati authored
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Simon Brandeis authored
* Raise RepoNotFoundError in case of 401 * Include changes from revert-17646-skip_repo_not_found * Add a comment *
馃拕 Code quality *馃挌 Update `get_from_cache` test *馃挌 Code quality & skip failing test -
Balaji authored
VisibleDeprecationWarning is addressed by specifying dtype=object when creating numpy array. Update code based on review feedback. Undo whitespace changes to tokenization_utils_base.py. Co-authored-by:I like data <ilikedata@nym.hush.com>
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Sylvain Gugger authored
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Lysandre authored
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Lysandre authored
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Alara Dirik authored
* enable crop_center method to handle (W, H, C) images * minor style and comment edits
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Alara Dirik authored
* move clip image utils to image_utils.py * dont default to square images * fix typo, revert change to test file * edit convert_rgb comments
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- 09 Jun, 2022 10 commits
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Stas Bekman authored
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mrbean authored
* convert assertion to raised exception in debertav2 * change assert to raise exception in deberta * fix messages
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Stas Bekman authored
* [modeling_utils] torch_dtype/auto fixes * add test * apply suggestions * add missing fallback * Renaming things * Use for else Co-authored-by:Sylvain Gugger <Sylvain.gugger@gmail.com>
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Nicolas Patry authored
When we're preparing the tensors for CPU for postprocessing, we need to upgrade the `float16` to `float32` since CPUs don't have instructions for `[b]float16`.
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Stas Bekman authored
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Nicolas Patry authored
* Adding `top_k` and `sort` arguments to `text-classification` pipeline. - Deprecate `return_all_scores` as `top_k` is more uniform with other pipelines, and a superset of what `return_all_scores` can do. BC is maintained though. `return_all_scores=True` -> `top_k=None` `return_all_scores=False` -> `top_k=1` - Using `top_k` will imply sorting the results, but using no argument will keep the results unsorted for backward compatibility. * Remove `sort`. * Fixing the test. * Remove bad doc.
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amyeroberts authored
* Use shape_list to safely get shapes * Add relevant test * Tidy and add metrics * Resolve dynamic shaping issues and move test * Tidy up and all samples in batch * Formatting
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regisss authored
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regisss authored
* Add ONNX support for ResNet * Add ONNX test * make fix-copies
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Younes Belkada authored
* adding template * update model * model update * update conf for debug model * update conversion * update conversion script * update conversion script * fix missing keys check * add tests to test the tokenizer in the local machine * Change variable name * add tests on xnli dataset * add more description * add descriptions + clearer code * clearer code * adding new tests + skipping few tests because of env problems * change comment * add dtype on the configuration * add test embeddings * add hardcoded test * fix dtype issue * adding torch.float16 to config * adding more metrics (min, max, mean) * add sum * now the test passes with almost equal * add files for conversion - test passes on cpu gpu * add final changes * cleaning code * add new args in the docstring * fix one liner function * remove macros * remove forward attention * clean up init funtion * add comments on the issue * rm scale mask softmax * do make style * fix dtype in init * fixing for loop on att probs * fix style with black * fix style + doc error * fix and debug CI errors (docs + style) * some updates - change new operations - finally add scaled softmax - added new args in the config * make use cache working * add changes - save sharded models - final changes on the modeling script * add changes - comment on alibi - add TODO on seq length * test commit - added a text to test the commit Co-authored-by:
thomasw21 <24695242+thomasw21@users.noreply.github.com> * final changes - attention mask change - generation works on BS176b Co-authored-by:
Stas Bekman <stas00@users.noreply.github.com> * apply modifications Co-authored-by:
Niklas Muennighoff <n.muennighoff@gmail.com> * final changes modeling Co-authored-by:
Nicolas Patry <Narsil@users.noreply.github.com> * forward contrib credits Co-authored-by:
thomasw21 <thomasw21@users.noreply.github.com> Co-authored-by:
sgugger <sgugger@users.noreply.github.com> Co-authored-by:
patrickvonplaten <patrickvonplaten@users.noreply.github.com> Co-authored-by:
LysandreJik <LysandreJik@users.noreply.github.com> * Apply suggestions from code review Co-authored-by:
justheuristic <justheuristic@gmail.com> * fix alibi - create alibi only once * add small doc * make quality * replace torch.nn * remove token type emb * fix fused op + output bias * add fused op - now can control fused operation from config * remove fused op * make quality * small changes - remove unsed args on config - removed bias gelu file - make the model torchscriptable - add torchscript slow tests * Update src/transformers/models/bloom/modeling_bloom.py * fix slow * make style * add accelerate support * add bloom to deepspeed tests * minor changes * Apply suggestions from code review Co-authored-by:
Thomwolf <thomwolf@gmail.com> Co-authored-by:
Thomas Wolf <thomas@huggingface.co> Co-authored-by:
sIncerass <sheng.s@berkeley.edu> Co-authored-by:
Stas Bekman <stas@stason.org>
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- 08 Jun, 2022 8 commits
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Joao Gante authored
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Joao Gante authored
* Merge PT and TF behavior
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Sylvain Gugger authored
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Joao Gante authored
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jianan-gu authored
Extend Transformers Trainer Class to Enable CPU AMP and Integrate Intel Extension for PyTorch (#17138) * init PR * fix import ipex * minor fix on bf16 * refine optimizer * refine args notes * refine code * refine ipex optimize args * refine half_precision_backend * black format * isort format * isort format files * flake8 format * doc builder format * refine codes * remove jit and optim bits * black preview format * Update src/transformers/trainer.py Co-authored-by:
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SaulLu authored
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Sayak Paul authored
* feat: initial implementation of data2vec segmentation model in TF. * chore: minor corrections to make the segmenter work. * chore: removed unncessary files. * chore: add tests and other modifications. * fix: loss computation for segmentation. * chore: remove unused variable. * chore: formatting. * added a dummy adaptive pooling layer. * removed unnecessary file. * potentially add identifiers to layer names. * fix: layer naming. * chore: removed unnecessary print. * Skipping unneeded test * chore: add logging to debug tolerance. * fix: segmentation tests for tfdata2vecvision * chore: make style. * fix: layer names, assertion to be resolved. * Bumping test tolerance a bit * chore: bump the tol in PT test. Co-authored-by:matt <rocketknight1@gmail.com>
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Joao Gante authored
* Stricter pt-to-tf checks; Update docker image for related tests * check all attributes in the output Co-authored-by:
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- 07 Jun, 2022 5 commits
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Yih-Dar authored
Co-authored-by:ydshieh <ydshieh@users.noreply.github.com>
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Chan Woo Kim authored
* added cbs to notebooks, made copy-paste error fix in generation_utils * initial push for mctc model * mctc feature extractor done * added processor, tokenizer and their tests for MCTC. Have added an MCTC modeling test, adjusting model code accordingly. * added processor, tokenizer and their tests for MCTC. Have added an MCTC modeling test, adjusting model code accordingly. * passing attention, now struggling to figure out how attention masks make sense here * works when excluding attention masks. ask later how one would integrate attention maskshere * bizarre configuration error (model prefix comes first in config dict json and messes up the order) * all passing but bizzarre config dict ordering issue when to_dict * passing all major tests * feature extraction, processor, tokenizer added & tests passing * style & consistency & other logistical fixes * copy paste fix * model after feature extraction working * commiting final feature extraction results; need to fix normalization * feature extraction passing tests; probably should add tests on the specific flashlight-copied functions? * delete print ; format code a bit * fixing tests * passing major tests * fixing styles * completed tokenization test with real example; not sure if these values are entirely correct. * last test fixes from local * reverting accidentally included custom setup configs * remove load tf weights; fix config error * testing couldnt import featureextractor * fix docs * fix docs * resolving comments * style fixes * style fixes * Update to MCTCConv1dSubSampler Co-authored-by:
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Michael Benayoun authored
* Support for deberta and deberta-v2 * Support for LXMert * Support for Hubert * Fix for pt1.11 * Trigger CI
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Sylvain Gugger authored
* Add examples telemetry * Alternative approach * Add to all other examples * Add to templates as well * Put framework separately * Same for TensorFlow
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Sylvain Gugger authored
* Fix circular import in onnx.utils * Add comment for test fetcher * Here too * Style
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- 06 Jun, 2022 1 commit
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regisss authored
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