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- 30 May, 2023 9 commits
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Cl茅mentine Fourrier authored
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peridotml authored
* initial flyte callback * lint * logs should still be saved to Flyte even if pandas isn't install (unlikely) * cr - flyte team * add docs for Flytecallback * fix doc string - cr sgugger * Apply suggestions from code review cr - sgugger fix doc strings Co-authored-by:
Sylvain Gugger <35901082+sgugger@users.noreply.github.com> --------- Co-authored-by:
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Hyeonseo Yun authored
* docs: ko: troubleshooting.mdx * revised: fix _toctree.yml #23112 * feat: nmt draft `troubleshooting.mdx` * fix: manual edits `troubleshooting.mdx` * revised: resolve suggestions troubleshooting.mdx Co-authored-by:
Sohyun Sim <96299403+sim-so@users.noreply.github.com> --------- Co-authored-by:
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Kihoon Son authored
* task/video_classification translated Co-Authored-By:
Hyeonseo Yun <0525_hhgus@naver.com> Co-Authored-By:
Gabriel Yang <gabrielwithhappy@gmail.com> Co-Authored-By:
Nayeon Han <nayeon2.han@gmail.com> Co-Authored-By:
Wonhyeong Seo <wonhseo@kakao.com> Co-Authored-By:
Jungnerd <46880056+jungnerd@users.noreply.github.com> * Update docs/source/ko/tasks/video_classification.mdx Co-authored-by:
Hyeonseo Yun <0525yhs@gmail.com> Co-authored-by:
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Kihoon Son authored
* docs: ko: fast_tokenizer.mdx content - translated Co-Authored-By:
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Matthijs Hollemans authored
* move input features to GPU * skip these tests because undefined behavior * unskip tests
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Matt authored
SAM shape flexibility fixes for compilation
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Samin Yasar authored
* add type hint in pipeline model argument * add pretrainedmodel and tfpretainedmodel type hint * make type hints string
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Eli Simhayev authored
* ran `transformers-cli add-new-model-like` * added `AutoformerLayernorm` and `AutoformerSeriesDecomposition` * added `decomposition_layer` in `init` and `moving_avg` to config * added `AutoformerAutoCorrelation` to encoder & decoder * removed caninical self attention `AutoformerAttention` * added arguments in config and model tester. Init works!
馃榿 * WIP autoformer attention with autocorrlation * fixed `attn_weights` size * wip time_delay_agg_training * fixing sizes and debug time_delay_agg_training * aggregation in training works!馃榿 * `top_k_delays` -> `top_k_delays_index` and added `contiguous()` * wip time_delay_agg_inference * finish time_delay_agg_inference馃槑 * added resize to autocorrelation * bug fix: added the length of the output signal to `irfft` * `attention_mask = None` in the decoder * fixed test: changed attention expected size, `test_attention_outputs` works! * removed unnecessary code * apply AutoformerLayernorm in final norm in enc & dec * added series decomposition to the encoder * added series decomp to decoder, with inputs * added trend todos * added autoformer to README * added to index * added autoformer.mdx * remove scaling and init attention_mask in the decoder * make style * fix copies * make fix-copies * inital fix-copies * fix from https://github.com/huggingface/transformers/pull/22076 * make style * fix class names * added trend * added d_model and projection layers * added `trend_projection` source, and decomp layer init * added trend & seasonal init for decoder input * AutoformerModel cannot be copied as it has the decomp layer too * encoder can be copied from time series transformer * fixed generation and made distrb. out more robust * use context window to calculate decomposition * use the context_window for decomposition * use output_params helper * clean up AutoformerAttention * subsequences_length off by 1 * make fix copies * fix test * added init for nn.Conv1d * fix IGNORE_NON_TESTED * added model_doc * fix ruff * ignore tests * remove dup * fix SPECIAL_CASES_TO_ALLOW * do not copy due to conv1d weight init * remove unused imports * added short summary * added label_length and made the model non-autoregressive * added params docs * better doc for `factor` * fix tests * renamed `moving_avg` to `moving_average` * renamed `factor` to `autocorrelation_factor` * make style * Update src/transformers/models/autoformer/configuration_autoformer.py Co-authored-by:NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update src/transformers/models/autoformer/configuration_autoformer.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * fixing `lags_sequence` doc * Revert "fixing `lags_sequence` doc" This reverts commit 21e34911e36a6f8f45f25cbf43584a49e5316c55. * Update src/transformers/models/autoformer/modeling_autoformer.py Co-authored-by:
Kashif Rasul <kashif.rasul@gmail.com> Co-authored-by:
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- 26 May, 2023 7 commits
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Sylvain Gugger authored
* Enable code-specific revision for code on the Hub * invalidate old revision
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Zachary Mueller authored
Log the right train_batch_size if using auto_find_batch_size and also log the adjusted value seperately. (#23800) * Log right bs * Log * Diff message
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Ran Ran authored
* Fix no such file or directory error * Address comment * Fix formatting issue
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Wang, Yi authored
Signed-off-by:Wang, Yi <yi.a.wang@intel.com>
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amitportnoy authored
class_weights tensor should follow model's device
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Sylvain Gugger authored
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Arthur authored
small doc nit
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- 25 May, 2023 9 commits
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Younes Belkada authored
fix nllb moe accelerate issue
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dependabot[bot] authored
Bump tornado in /examples/research_projects/visual_bert Bumps [tornado](https://github.com/tornadoweb/tornado) from 6.0.4 to 6.3.2. - [Changelog](https://github.com/tornadoweb/tornado/blob/master/docs/releases.rst) - [Commits](https://github.com/tornadoweb/tornado/compare/v6.0.4...v6.3.2 ) --- updated-dependencies: - dependency-name: tornado dependency-type: direct:production ... Signed-off-by:
dependabot[bot] <support@github.com> Co-authored-by:
dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
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dependabot[bot] authored
Bumps [tornado](https://github.com/tornadoweb/tornado) from 6.0.4 to 6.3.2. - [Changelog](https://github.com/tornadoweb/tornado/blob/master/docs/releases.rst) - [Commits](https://github.com/tornadoweb/tornado/compare/v6.0.4...v6.3.2 ) --- updated-dependencies: - dependency-name: tornado dependency-type: direct:production ... Signed-off-by:
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鐜╃伀 authored
* Fix is_ninja_available() search ninja using subprocess instead of importlib. * Fix style * Fix doc * Fix style
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Arthur authored
* remove unused parameters * remove unused parameters in config
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Sylvain Gugger authored
* Revamp test selection for the example tests * Rename old XLA test and fake modif in run_glue * Fixes * Fake Trainer modif * Remove fake modifs
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Sylvain Gugger authored
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Ravi Theja authored
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Eric J. Wang authored
Fix command in modeling_utils.py
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- 24 May, 2023 15 commits
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Matt authored
Remove some more serving methods that (I think?) turned up while this PR was open
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Sylvain Gugger authored
* Enable prompts on the Hub * Update src/transformers/tools/prompts.py Co-authored-by:
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Zachary Mueller authored
* Check for use_sagemaker_dp * Add a check for is_sagemaker_mp when setting _n_gpu again. Should be last broken thing * Try explicit check? * Quality
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Daniel King authored
Fix the regex in `get_imports` to support multiline try blocks and excepts with specific exception types (#23725) * fix and test get_imports for multiline try blocks, and excepts with specific errors * fixup * add some more tests * add license
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Sanchit Gandhi authored
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Matt authored
* Let's try autodetecting serving sigs * Don't clobber existing sigs * Change shapes for multiplechoice models * Make default dummy inputs smarter too * Fix missing f-string * Let's YOLO a serving output too * Read __class__.__name__ properly * Don't just pass naked lists in there and expect it to be okay * Code cleanup * Update default serving sig * Clearer error messages * Further updates to the default serving output * make fixup * Update the serving output a bit more * Cleanups and renames, raise errors appropriately when we can't infer inputs * More renames * we're building in a functional context again, yolo * import DUMMY_INPUTS from the right place * import DUMMY_INPUTS from the right place * Support cross-attention in the dummies * Support cross-attention in the dummies * Complete removal of dummy/serving overrides in BERT * Complete removal of dummy/serving overrides in RoBERTa * Obliterate lots and lots of serving sig and dummy overrides * merge type hint changes * Fix for token_type_ids with vocab_size 1 * Add missing property decorator * Fix T5 and hopefully some models that take conv inputs * More signature pruning * Fix T5's signature * Fix Wav2Vec2 signature * Fix LongformerForMultipleChoice input signature * Fix BLIP and LED * Better default serving output error handling * Fix BART dummies * Fix dummies for cross-attention, esp encoder-decoder models * Fix visionencoderdecoder signature * Fix BLIP serving output * Small tweak to BART dummies * Cleanup the ugly parameter inspection line that I used in a few places * committed a breakpoint again * Move the text_dims check * Remove blip_text serving_output * Add decoder_input_ids to the default input sig * Remove all the manual overrides for encoder-decoder model signatures * Tweak longformer/led input sigs * Tweak default serving output * output.keys() -> output * make fixup
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Connor Henderson authored
move text_prompt_ids trimming to top
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Jungnerd authored
fix: delete duplicate sentence
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Matt authored
* Extremely small change to TF SAM dummies to reduce memory usage on build * remove debug breakpoint * Debug print statement to track array sizes * More debug shape printing * More debug shape printing * Now remove the debug shape printing * make fixup * make fixup
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pagarsky authored
Minor docs fixes
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Matt authored
* Rework TF type hints to use | None instead of Optional[] for tf.Tensor * Rework TF type hints to use | None instead of Optional[] for tf.Tensor * Don't forget the imports * Add the imports to tests too * make fixup * Refactor tests that depended on get_type_hints * Better test refactor * Fix an old hidden bug in the test_keras_fit input creation code * Fix for the Deit tests
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Wang, Yi authored
Signed-off-by: -
uchuhimo authored
fix: use bool instead of uint8/byte in Deberta/DebertaV2/SEW-D to make it compatible with TensorRT (#23683) * Use bool instead of uint8/byte in DebertaV2 to make it compatible with TensorRT TensorRT cannot accept onnx graph with uint8/byte intermediate tensors. This PR uses bool tensors instead of unit8/byte tensors to make the exported onnx file can work with TensorRT. * fix: use bool instead of uint8/byte in Deberta and SEW-D --------- Co-authored-by:Yuxian Qiu <yuxianq@nvidia.com>
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Maria Khalusova authored
* doc refocused on using optimum, tflite * minor updates to fix checks * Apply suggestions from code review Co-authored-by:
regisss <15324346+regisss@users.noreply.github.com> * TFLite to separate page, added links * Removed the onnx list builder * make style * Update docs/source/en/serialization.mdx Co-authored-by:
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Tim Dettmers authored
* Added lion and paged optimizers and made original tests pass. * Added tests for paged and lion optimizers. * Added and fixed optimizer tests. * Style and quality checks. --------- Co-authored-by:younesbelkada <younesbelkada@gmail.com>
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