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* get default device through `PartialState().default_device` as is has been officially released * apply code review suggestion * apply code review suggestion Co-authored-by: Zach Mueller <muellerzr@gmail.com> --------- Co-authored-by: Zach Mueller <muellerzr@gmail.com>
…and AltCLIPConfig (#27128) * [docstring] Fix docstring for AltCLIPVisionConfig, AltCLIPTextConfig + cleaned some docstring * Removed entries from check_docstring.py * Removed entries from check_docstring.py * Removed entry from check_docstring.py * [docstring] Fix docstring for AltCLIPTextConfig, AltCLIPVisionConfig and AltCLIPConfig
Update configuration_blip.py edit docstrings
Disable runner check Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* added flash attention of gpt_bigcode * changed docs * Update src/transformers/models/gpt_bigcode/modeling_gpt_bigcode.py * add FA-2 docs * oops * Update docs/source/en/perf_infer_gpu_one.md Last Nit Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * fix * oops * remove padding_mask * change getattr->hasattr logic * changed .md file --------- Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by: younesbelkada <younesbelkada@gmail.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
A recent PR #26579 fixed an edge case out-of-bounds tensor indexing error in TypicalLogitsWarper, and a related behaviour change was made that we thought fixed a long-standing bug w.r.t. the token inclusion cutoff. However after looking more closely, I am pretty certain that the original logic was correct and that the OOB fix should have been made differently. Specifically the docs state that it should include the "smallest set of tokens that add up to P or higher" and so `last_ind` should actually be one more than the index of the last token satisfying (cumulative_probs < self.mass). We still need a max clamp in case that last token is the very last one in the tensor.
* Add support for loading GPTQ models on CPU Right now, we can only load the GPTQ Quantized model on the CUDA device. The attribute `gptq_supports_cpu` checks if the current auto_gptq version is the one which has the cpu support for the model or not. The larger variants of the model are hard to load/run/trace on the GPU and that's the rationale behind adding this attribute. Signed-Off By: Vivek Khandelwal <vivek@nod-labs.com> * Update quantization.md * Update quantization.md * Update quantization.md
fix Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
…26960) * Shorten the conversation tests for speed + fixing position overflows * Put max_new_tokens back to 5 * Remove test skips * Increase max_position_embeddings in blenderbot tests * Add skips for blenderbot_small * Correct TF test skip * make fixup * Reformat skips to use is_pipeline_test_to_skip * Update tests/models/blenderbot_small/test_modeling_blenderbot_small.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/models/blenderbot_small/test_modeling_flax_blenderbot_small.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update tests/models/blenderbot_small/test_modeling_tf_blenderbot_small.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* device agnostic pipelines testing * pass torch_device
* add v1 neftune * use `unwrap_model` instead * add test + docs * Apply suggestions from code review Co-authored-by: Zach Mueller <muellerzr@gmail.com> * more details * fixup * Update docs/source/en/main_classes/trainer.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * refactor a bit * more elaborated test * fix unwrap issue --------- Co-authored-by: Zach Mueller <muellerzr@gmail.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Backward compatibility fix for the Conversation class * Explain what's going on in the conditional
fix bnb mpt test
* translate traning.md * update _tocree.yml * update _tocree.yml * update _tocree.yml
* first draft * remove non-existent paths * edits * feedback * feedback and optimum * Apply suggestions from code review Co-authored-by: regisss <15324346+regisss@users.noreply.github.com> Co-authored-by: Ella Charlaix <80481427+echarlaix@users.noreply.github.com> * redirect to correct doc * _redirects.yml --------- Co-authored-by: regisss <15324346+regisss@users.noreply.github.com> Co-authored-by: Ella Charlaix <80481427+echarlaix@users.noreply.github.com>
* device agnostic models testing * add decorator `require_torch_fp16` * make style * apply review suggestion * Oops, the fp16 decorator was misused
* Safetensors serialization by default * First pass on the tests * Second pass on the tests * Third pass on the tests * Fix TF weight loading from TF-format safetensors * Specific encoder-decoder fixes for weight crossloading * Add VisionEncoderDecoder fixes for TF too * Change filename test for pt-to-tf * One missing fix for TFVisionEncoderDecoder * Fix the other crossload test * Support for flax + updated tests * Apply suggestions from code review Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * Sanchit's comments * Sanchit's comments 2 * Nico's comments * Fix tests * cleanup * Apply suggestions from code review Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> --------- Co-authored-by: Matt <rocketknight1@gmail.com> Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* docs(zh): translate tflite.md * docs(zh): add space around links * Update docs/source/zh/tflite.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> --------- Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* make fsdp test cases device agnostic * make style
* working v1 * oops * Update src/transformers/modeling_utils.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * fixup * oops * push * more changes * add docs * some fixes * fix copies * add v1 doc * added installation guide * relax constraints * revert * attempt llm-awq * oops * oops * fixup * raise error when incorrect cuda compute capability * nit * add instructions for llm-awq * fixup * fix copies * fixup and docs * change * few changes + add demo * add v1 tests * add autoawq in dockerfile * finalize * Update tests/quantization/autoawq/test_awq.py * fix test * fix * fix issue * Update src/transformers/integrations/awq.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update docs/source/en/main_classes/quantization.md Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update docs/source/en/main_classes/quantization.md Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/integrations/awq.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Update src/transformers/integrations/awq.py Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * add link to example script * Update docs/source/en/main_classes/quantization.md Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * add more content * add more details * add link to quantization docs * camel case + change backend class name * change to string * fixup * raise errors if libs not installed * change to `bits` and `group_size` * nit * nit * Apply suggestions from code review Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * disable training * address some comments and fix nits * fix * final nits and fix tests * adapt to our new runners * make fix-copies * Update src/transformers/utils/quantization_config.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/utils/quantization_config.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/integrations/awq.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update src/transformers/integrations/awq.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * move to top * add conversion test * final nit * add more elaborated test --------- Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* fix docstring in get_maskformer_resize_output_image_size * fix functions docstring * fix 'copied from' functions docstring * fix docstring * fix return type * fix docstring resize
Fix the typos and grammar mistakes in CONTRIBUTING.md
* added unsqueeze_dim to apply_rotary_pos_emb * Added docstring * Modified docstring * Modified docstring * Modified docstring * Modified docstring * Modified docstring * ran make fix-copies and make fixup * Update src/transformers/models/llama/modeling_llama.py Accepting the proposed changes in formatting. Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * incorporating PR suggestions * incorporating PR suggestions * incorporating PR suggestions * incorporating PR suggestions * .. --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
#27032) * Added cache_block_outputs option to enable GPTQ for non-regular models * Update src/transformers/utils/quantization_config.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * Update src/transformers/utils/quantization_config.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * Fixed style * Update src/transformers/utils/quantization_config.py Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> --------- Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
…27195) * finish * add tests * fix all tests * [Assistant Decoding] Add test * fix more * better * finish * Apply suggestions from code review Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * finish --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Add type annotations to TFConvNextDropPath * Use tf.debugging.assert_equal for TFConvNextEmbeddings shape check * Add TensorFlow implementation of ConvNeXTV2 * check_docstrings: add TFConvNextV2Model to exclusions TFConvNextV2Model and TFConvNextV2ForImageClassification have docstrings which are equivalent to their PyTorch cousins, but a parsing issue prevents them from passing the test. Adding exclusions for these two classes as discussed in #25558.
) * initial commit * Add inital testing files and modify __init__ files to add UnivNet imports. * Fix some bugs * Add checkpoint conversion script and add references to transformers pre-trained model. * Add UnivNet entries for auto. * Add initial docs for UnivNet. * Handle input and output shapes in UnivNetGan.forward and add initial docstrings. * Write tests and make them pass. * Write docs. * Add UnivNet doc to _toctree.yml and improve docs. * fix typo * make fixup * make fix-copies * Add upsample_rates parameter to config and improve config documentation. * make fixup * make fix-copies * Remove unused upsample_rates config parameter. * apply suggestions from review * make style * Verify and add reason for skipped tests inherited from ModelTesterMixin. * Add initial UnivNetGan integration tests * make style * Remove noise_length input to UnivNetGan and improve integration tests. * Fix bug and make style * Make UnivNet integration tests pass * Add initial code for UnivNetFeatureExtractor. * make style * Add initial tests for UnivNetFeatureExtractor. * make style * Properly initialize weights for UnivNetGan * Get feature extractor fast tests passing * make style * Get feature extractor integration tests passing * Get UnivNet integration tests passing * make style * Add UnivNetGan usage example * make style and use feature extractor from hub in integration tests * Update tips in docs * apply suggestions from review * make style * Calculate padding directly instead of using get_padding methods. * Update UnivNetFeatureExtractor.to_dict to be UnivNet-specific. * Update feature extractor to support using model(**inputs) and add the ability to generate noise and pad the end of the spectrogram in __call__. * Perform padding before generating noise to ensure the shapes are correct. * Rename UnivNetGan.forward's noise_waveform argument to noise_sequence. * make style * Add tests to test generating noise and padding the end for UnivNetFeatureExtractor.__call__. * Add tests for checking batched vs unbatched inputs for UnivNet feature extractor and model. * Add expected mean and stddev checks to the integration tests and make them pass. * make style * Make it possible to use model(**inputs), where inputs is the output of the feature extractor. * fix typo in UnivNetGanConfig example * Calculate spectrogram_zero from other config values. * apply suggestions from review * make style * Refactor UnivNet conversion script to use load_state_dict (following persimmon). * Rename UnivNetFeatureExtractor to UnivNetGanFeatureExtractor. * make style * Switch to using torch.tensor and torch.testing.assert_close for testing expected values/slices. * make style * Use config in UnivNetGan modeling blocks. * make style * Rename the spectrogram argument of UnivNetGan.forward to input_features, following Whisper. * make style * Improving padding documentation. * Add UnivNet usage example to the docs. * apply suggestions from review * Move dynamic_range_compression computation into the mel_spectrogram method of the feature extractor. * Improve UnivNetGan.forward return docstring. * Update table in docs/source/en/index.md. * make fix-copies * Rename UnivNet components to have pattern UnivNet*. * make style * make fix-copies * Update docs * make style * Increase tolerance on flaky unbatched integration test. * Remove torch.no_grad decorators from UnivNet integration tests to try to avoid flax/Tensorflow test errors. * Add padding_mask argument to UnivNetModel.forward and add batch_decode feature extractor method to remove padding. * Update documentation and clean up padding code. * make style * make style * Remove torch dependency from UnivNetFeatureExtractor. * make style * Fix UnivNetModel usage example * Clean up feature extractor code/docstrings. * apply suggestions from review * make style * Add comments for tests skipped via ModelTesterMixin flags. * Add comment for model parallel tests skipped via the test_model_parallel ModelTesterMixin flag. * Add # Copied from statements to copied UnivNetFeatureExtractionTest tests. * Simplify UnivNetFeatureExtractorTest.test_batch_decode. * Add support for unbatched padding_masks in UnivNetModel.forward. * Refactor unbatched padding_mask support. * make style
Co-authored-by: 张兴言 <SENSETIME\zhangxingyan1@cn0214006377l.domain.sensetime.com>
* update d_kv'annotation in mt5'configuration * update d_kv'annotation in mt5'configuration * update d_kv'annotation in mt5'configuration
* added flash attention for opt * added to list * fix use cache (#3) * style fix * fix text * test fix2 * reverted until 689f599 * torch fx tests are working now! * small fix * added TODO docstring * changes * comments and .md file modification --------- Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
* Extended semantic segmentation * Update image_segmentation.md * Changed title * Update docs/source/en/tasks/semantic_segmentation.md Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update docs/source/en/tasks/semantic_segmentation.md Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update docs/source/en/tasks/semantic_segmentation.md Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update docs/source/en/tasks/semantic_segmentation.md Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update docs/source/en/tasks/semantic_segmentation.md Co-authored-by: Pedro Cuenca <pedro@huggingface.co> * Update semantic_segmentation.md * Update docs/source/en/tasks/semantic_segmentation.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Update docs/source/en/tasks/semantic_segmentation.md Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Addressed Niels' and Maria's comments * Added detail on panoptic segmentation * Added redirection and renamed the file * Update _toctree.yml * Update _redirects.yml * Rename image_segmentation.md to semantic_segmentation.md --------- Co-authored-by: Pedro Cuenca <pedro@huggingface.co> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Update arxiv link
* Add resources * Remove script * Update docs/source/en/model_doc/dinov2.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* update * fix --------- Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
…integration (#27652) * add code changes 1. Refactor FSDP 2. Add `--save_only_model` option: When checkpointing, whether to only save the model, or also the optimizer, scheduler & rng state. 3. Bump up the minimum `accelerate` version to `0.21.0` * quality * fix quality? * Revert "fix quality?" This reverts commit 149330a. * fix fsdp doc strings * fix quality * Update src/transformers/training_args.py Co-authored-by: Zach Mueller <muellerzr@gmail.com> * please fix the quality issue 😅 * Apply suggestions from code review Co-authored-by: Benjamin Bossan <BenjaminBossan@users.noreply.github.com> * address comment * simplify conditional check as per the comment * update documentation --------- Co-authored-by: Zach Mueller <muellerzr@gmail.com> Co-authored-by: Benjamin Bossan <BenjaminBossan@users.noreply.github.com>
fix Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Fix typo in warning message The path of `default_cache_path` is hf_cache_home/hub. There is no directory named transformers under hf_cache_home * Fix a typo in comment * Update the version number v4.22.0 is the earlist version that contains those changes in PR #18492
* Update musicgen.md please make it less hidden * Add cleaner formatting
Change "convert predictions to logits" to "convert logits to predictions" to fix semantic error in the evaluation section. Logits need to be converted to predictions to evaluate the accuracy, not the other way round
…cstrings` to facilitate integrations (#27645) * initial commit * dummy changes * style * Update src/transformers/utils/doc.py Co-authored-by: Alex McKinney <44398246+vvvm23@users.noreply.github.com> * nits * nit use ` if re.match(r'^refs/pr/\d*', revision):` * restrict * nit * test the doc vuilder * wow * oke the order was wrong --------- Co-authored-by: Alex McKinney <44398246+vvvm23@users.noreply.github.com>
* reflect RoCm support in the documentation * Update docs/source/en/main_classes/trainer.md Co-authored-by: Lysandre Debut <hi@lysand.re> * fix review comments * use ROCm instead of RoCm --------- Co-authored-by: Lysandre Debut <hi@lysand.re>
* Successfully resolved the ZeroDivisionError exception in the utils.notebook.y file. * Now I update little code mentioned by Peter * Using Black package to reformat my file * Now I using ruff libary to reformated my file
* Fix sliding_window hasattr in Mistral * hasattr -> getattr for sliding_window in Mistral --------- Co-authored-by: Ilya Gusev <ilya.gusev@booking.com>
fix Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
… a requirement (#27691) Reorder
* 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
* fix assisted decoding attention_cat * fix attention_mask for assisted decoding * fix attention_mask len * fix attn len * Use a more clean way to prepare assistant models inputs * fix param meaning * fix param name * fix assistant model inputs * update token type ids * fix assistant kwargs copy * add encoder-decoder tests of assisted decoding * check if assistant kwargs contains updated keys * revert test * fix whisper tests * fix assistant kwargs * revert whisper test * delete _extend funcs
* Update forward signature * Empty-Commit
…label with "-" (#27325) * fix group_sub_entities bug * add space
* Fix code snippet * Improve code snippet
* docs: replace torch.distributed.run by torchrun `transformers` now officially support pytorch >= 1.10. The entrypoint `torchrun`` is present from 1.10 onwards. Signed-off-by: Peter Pan <Peter.Pan@daocloud.io> * Update src/transformers/trainer.py with @ArthurZucker's suggestion Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> --------- Signed-off-by: Peter Pan <Peter.Pan@daocloud.io> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
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