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* Fix circular import in onnx.utils * Add comment for test fetcher * Here too * Style
* Add examples telemetry * Alternative approach * Add to all other examples * Add to templates as well * Put framework separately * Same for TensorFlow
* Support for deberta and deberta-v2 * Support for LXMert * Support for Hubert * Fix for pt1.11 * Trigger CI
* Quicktour Portuguese Translation Translated quicktour.mdx until line 161 * Finished translating quicktour.mdx Ready to upload and adjust eventual .mdx or translation mistakes. * Add _toctree.yml and fix nits * Fixed pt-br mdx syntax problem Closed <frameworkcontent> instance * Changed </frameworkcontent> line * Copied missing block from english version of quicktour.mdx * Reviwed the entire file once again. It should be working now. Co-authored-by: Omar U. Espejel <[email protected]>
* 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: Patrick von Platen <[email protected]> * relposemb fixes * conv1d name issue; expecting config fail with paraentheses * fix config issue * fix config issue * fix config issue * change everything to MCTCT * fixing naming change errors * archive list * copyrights and docs * copyrights and docs * copyrights and docs * merge resolution * move tests, fix to changed optionaldependency structure * test directories changed * fixing tests * how to avoid tf tests? * how to avoid tf tests? * tests passing locally * allow mctctprocessor imported any env * allow mctctprocessor imported any env * fixed second round of feedback, need to fix docs * doc changes not being applied * all fixed * style fix * feedback fixes * fix copies and feature extraction style fix * Update tests/models/visual_bert/test_modeling_visual_bert.py Co-authored-by: Sylvain Gugger <[email protected]> * copy paste huggingface:main visual bert * added eof newline to visual bert; all tests are passing otherwise * fix slow tests by adding attention mask * change model id to speechbrain * make fix-copies * fix readme unwanted deletes * fixing readmes, make fix-copies * consistent M-CTC-T naming * Update src/transformers/models/mctct/__init__.py Co-authored-by: Patrick von Platen <[email protected]> * all fixed but variable naming * adjust double quotes * fixed variable names * copyright and mr quilter * Apply suggestions from code review Co-authored-by: Sylvain Gugger <[email protected]> * correct slow tests * make fix-copies * Update src/transformers/models/mctct/configuration_mctct.py Co-authored-by: Sylvain Gugger <[email protected]> * Update src/transformers/models/mctct/configuration_mctct.py Co-authored-by: Sylvain Gugger <[email protected]> * m-ctc-t not mctct Co-authored-by: Patrick von Platen <[email protected]> Co-authored-by: Sylvain Gugger <[email protected]>
Co-authored-by: ydshieh <[email protected]>
* Stricter pt-to-tf checks; Update docker image for related tests * check all attributes in the output Co-authored-by: Sylvain Gugger <[email protected]>
* 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 <[email protected]>
* Update docker file Co-authored-by: ydshieh <[email protected]>
…el Extension for PyTorch (huggingface#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: Sylvain Gugger <[email protected]> * refine code * refine notes * Update src/transformers/trainer.py Co-authored-by: Sylvain Gugger <[email protected]> * Update src/transformers/trainer.py Co-authored-by: Sylvain Gugger <[email protected]> * code refine * add ipex ut * add performance cpu doc * link to the cpu doc from main perf doc * install ipex into CI's docker * Update perf_train_cpu.mdx * Update docs/source/en/perf_train_cpu.mdx Co-authored-by: Stas Bekman <[email protected]> * Update perf_train_cpu.mdx * Update perf_train_cpu.mdx Co-authored-by: Sylvain Gugger <[email protected]> Co-authored-by: Stas Bekman <[email protected]> Co-authored-by: Stas Bekman <[email protected]>
* Fix link for community notebooks This fixes the link for community notebooks due to reorganization. * Replace old link with fully link to the doc page Co-authored-by: Sylvain Gugger <[email protected]> Co-authored-by: Sylvain Gugger <[email protected]>
…assed (huggingface#17593) * Merge PT and TF behavior
* 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 <[email protected]> * final changes - attention mask change - generation works on BS176b Co-authored-by: thomasw21 <[email protected]> * changes - model + conversion * move to correct dir * put , * fex fixes * fix tokenizer autodoc * fix minor CI issues * fix minor CI issues * fix minor CI issues * fix style issue * fix minor import issues * fix few issues * remove def main on the test * add require torch * replace decorator with 'with' * fix style * change to bloom * add quick fix tokenizer * fix tokenizer file * fix tokenizer - merge tests - small fixes * fix import issue * add bloom to readme * fix consistency * Update docs/source/en/model_doc/bloom.mdx Co-authored-by: Sylvain Gugger <[email protected]> * Apply suggestions from code review fix comment issues on file headers Co-authored-by: Sylvain Gugger <[email protected]> * fix doc issue * small fix - modeling test * some changes - refactor some code - taking into account reviews - more tests should pass - removed pruning tests * remove useless division * more tests should pass * more tests should pass * more tests should pass * let's try this one -add alibi offset - remove all permutes to make the grad operations work - finger crossed * refactor - refactor code - style changes - add new threshold for test * major changes - change BLOOM to Bloom - add quick doc on bloom.mdx - move embeddings test on modeling test * modify readme * small fixes * small fix - better threshold for a test * remove old test file from fetcher * fix small typo * major change - change BloomLMHead to BloomForCausalLM * remove onnx config * major changes - refactor the code - remove asserts - change tol for test * make style * small change * adding a slow test + commenting old ones for now * make style * Apply suggestions from code review Co-authored-by: Sylvain Gugger <[email protected]> * make style * fix duplicates * cleaning comments on config * clean a bit conversion file * refacor a bit modeling file * refactor tokenizer file * fix tokenization test issue * fix tokenization issue #2 * fix tokenization issue second try * fix test issue * make style + add suggestions * change test fetcher * try this one - slow tests should pass - finger crossed * possible final changes * make style * try fix padding side issue * fix side * fix padding issue * fix ko-readme * fix config auto * cleaning modeling file * keep bloom in caps in ko * update config docs * remove pretraining_pp * remove model parallel * update config - add correct config files * fix duplicates * fix fetcher * fix refactor issue - remove divide function * try to remove alibi * small fixes - fix alibi - remove seq length - refactor a bit the code * put correct values - fix bos and eos token ids * fix attention mask loop Co-authored-by: thomasw21 <[email protected]> * small fixes: - remove skip bias add * small fixes - fix typo in readme - fix typos in config * small changes - remove a test - add reconstruction test - change config * small changes - change Scaled Softmax to BloomScaledSoftmax * small fixes - fix alibi dtype * major changes - removing explicit dtype when loading modules - fixing test args (torch_dtype=auto) - add dosctring * fix readmes * major changes - now bloom supports alibi shifting - refactor a bit the code - better test tolerance now * refactor a bit * refactor a bit * put correct name on test * change docstring * small changes - fix docstring modeling - fix test tolerance * fix small nit - take dtype from tensors in the conversion script * minor fix - fix mdx issue * minor fix - change config docstring * forward contrib credits from PR14084 * Apply suggestions from code review Co-authored-by: Stas Bekman <[email protected]> * apply modifications Co-authored-by: Stas Bekman <[email protected]> * resolve softmax upcast * Apply suggestions from code review Co-authored-by: Stas Bekman <[email protected]> * Update src/transformers/models/bloom/modeling_bloom.py Co-authored-by: Niklas Muennighoff <[email protected]> * final changes modeling Co-authored-by: Stas Bekman <[email protected]> * Merge commit 'd156898f3b9b2c990e5963f5030a7143d57921a2' * merge commit * Apply suggestions from code review Co-authored-by: Stas Bekman <[email protected]> * apply suggestions Apply suggestions from Stas comments Co-authored-by: Stas Bekman <[email protected]> * Fix gradient checkpointing Co-authored-by: Stas Bekman <[email protected]> * add slow but exact * add accelerate compatibility Co-authored-by: Nicolas Patry <[email protected]> * forward contrib credits Co-authored-by: thomasw21 <[email protected]> Co-authored-by: sgugger <[email protected]> Co-authored-by: patrickvonplaten <[email protected]> Co-authored-by: Niklas Muennighoff <[email protected]> Co-authored-by: LysandreJik <[email protected]> * Apply suggestions from code review Co-authored-by: Patrick von Platen <[email protected]> * fix torch device on tests * make style * Apply suggestions from code review Co-authored-by: Patrick von Platen <[email protected]> * fix nits Co-authored-by: patrickvonplaten<[email protected]> * remove final nits * fix doc - add more details on the doc - add links to checkpoints * Update src/transformers/__init__.py Co-authored-by: Sylvain Gugger <[email protected]> * Update src/transformers/models/bloom/modeling_bloom.py Co-authored-by: Sylvain Gugger <[email protected]> * apply suggestions Co-authored-by: sgugger <[email protected]> * put test torchscript to false * Update src/transformers/models/bloom/modeling_bloom.py Co-authored-by: justheuristic <[email protected]> * 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: Patrick von Platen <[email protected]> * minor change * slow tests pass * Apply suggestions from code review Co-authored-by: Sylvain Gugger <[email protected]> * Update docs/source/en/model_doc/bloom.mdx Co-authored-by: Sylvain Gugger <[email protected]> * minor changes: - change docstring - add link to paper Co-authored-by: Thomwolf <[email protected]> Co-authored-by: Thomas Wolf <[email protected]> Co-authored-by: thomasw21 <[email protected]> Co-authored-by: Sylvain Gugger <[email protected]> Co-authored-by: sIncerass <[email protected]> Co-authored-by: Stas Bekman <[email protected]> Co-authored-by: Niklas Muennighoff <[email protected]> Co-authored-by: Nicolas Patry <[email protected]> Co-authored-by: thomasw21 <[email protected]> Co-authored-by: sgugger <[email protected]> Co-authored-by: patrickvonplaten <[email protected]> Co-authored-by: LysandreJik <[email protected]> Co-authored-by: Patrick von Platen <[email protected]> Co-authored-by: justheuristic <[email protected]> Co-authored-by: Stas Bekman <[email protected]>
* Add ONNX support for ResNet * Add ONNX test * make fix-copies
* 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
…ce#17606) * 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.
* Fix very long job failure text in Slack report Co-authored-by: ydshieh <[email protected]>
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`.
…7614) * [modeling_utils] torch_dtype/auto fixes * add test * apply suggestions * add missing fallback * Renaming things * Use for else Co-authored-by: Sylvain Gugger <[email protected]>
* pre-build deepspeed Co-authored-by: ydshieh <[email protected]>
* Return scalar losses instead of per-sample means * Make loss shape (1,) instead of scalar * Allow scalar losses in test_loss_computation * Allow scalar losses in test_loss_computation * Allow scalar losses in test_loss_computation * Remove XLA loss function for RAG
Co-authored-by: Sreyan-G@NVIDIA <[email protected]>
…e#17969) * get the right slicing index for position_bias
…ggingface#18016) Co-authored-by: ydshieh <[email protected]>
Co-authored-by: ydshieh <[email protected]>
Co-authored-by: Niels Rogge <[email protected]>
…xample (huggingface#18002) * Add ALL_LAYERNORM_LAYERS for LayerNorm * fix bug of appending layer norm
* Link to the Datasets doc * Remove unwanted file
* Add script to sort doc ToC * Style and fixes * Add check to quality job
…ngface#18008) * Added command for windows VENV activation * changed linux and macos specification
…#17967) * Drop columns after loading samples, rather than before, to avoid breaking transforms * make fixup * Add workaround so this PR can work with current datasets version
* Fix slow CI by pinning resampy * Actually put it in the speech dependencies
* Fix type issue in using bucketing with Trainer - Fix type issues in LengthGrouperSampler, DistributedLengthGroupedSampler refs: huggingface#18003 * Change logging type in LengthGroupedSampler - Change `logger.warning` to `logger.info` Co-authored-by: Sylvain Gugger <[email protected]> * Change logging type in DistributedLengthGroupedSampler - Change `logger.warning` to `logger.info` Co-authored-by: Sylvain Gugger <[email protected]> * Remove adundant clause in LengthGroupedSampler - Use `elif` Co-authored-by: Sylvain Gugger <[email protected]> * Remove adundant clause in DistributedLengthGroupedSampler - Use `elif` Co-authored-by: Sylvain Gugger <[email protected]> * Apply black, isort to modified codes in the script Co-authored-by: Sylvain Gugger <[email protected]>
huggingface#18078) * Make Trainer.predict call on_evaluate (huggingface#17952) * Add on_predict * Small fix * Small and different fix * Add tests
kolia1985
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* update the contribution guide * apply review feedback * fix checkboxes * checkbox fix #2 * clarify force push
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