- 24 Sep, 2021 8 commits
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Gunjan Chhablani authored
* Update run_glue.py * Update run_glue.py * Add model creation snippet to other scripts * Fix style
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Yuta Hayashibe authored
* Warn for unexpected argument combinations * Updated the waning message for pad_to_max_length
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Patrick von Platen authored
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Nicolas Patry authored
Fixes #13697
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Tommy Chiang authored
We use `torch.unique` here only to check whether every elements have the same value. Therefore, we can use `torch.unique_consecutive` here. This function eliminates all but the first element from every consecutive group of equivalent elements. Like, if we apply this function to `[1, 2, 2, 1]`, it will result in `[1, 2, 1]`. As you could see, this is enough for checking whether every elements have the same value. Since `torch.unique_consecutive` do less thing, it is much more faster. On my computer, it is 25x faster on GPU and 15x faster on CPU.
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Patrick von Platen authored
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Josh Devins authored
This moves the assertion on checking input dimensions into a block that will only be called if the function is actually going to do chunking forward. This is often not the case at inference time and PyTorch tracing a model with this assertion in it leads to a tracing warning. TracerWarning: Converting a tensor to a Python boolean might cause the trace to be incorrect. We can't record the data flow of Python values, so this value will be treated as a constant in the future. This means that the trace might not generalize to other inputs! input_tensor.shape[chunk_dim] == tensor_shape for input_tensor in input_tensors
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Patrick von Platen authored
* up * rename * add asr example * add auto feature extractor * some more fixes * correct layerdrop * correct for multi-gpu dist * clean up * refactor * refactor * more fixes * more fixes * clean-up * finish * up * Apply suggestions from code review * fix isort * update * up * add note * apply surajs suggestions * Apply suggestions from code review Co-authored-by:
Suraj Patil <surajp815@gmail.com> * isort * small change * Apply suggestions from code review Co-authored-by:
Anton Lozhkov <aglozhkov@gmail.com> * Apply suggestions from code review Co-authored-by:
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- 23 Sep, 2021 6 commits
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Lysandre Debut authored
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Md Saiful Islam Sayef authored
* Add example use of few-shot named entity recognition model in research_projects folder. * Apply suggestions from code review Co-authored-by:
NielsRogge <48327001+NielsRogge@users.noreply.github.com> * Update fsner example README.md. - Change wrong import FSNERTokenizerWrapper to FSNERTokenizerUtils in the example code - Add a link to the model identifier * Update examples/research_projects/fsner/src/fsner/model.py Fix spelling mistake in the default parameter of pretrained model name. Co-authored-by:
Stefan Schweter <stefan@schweter.it> * Add example use of few-shot named entity recognition model in research_projects folder. * Apply suggestions from code review Co-authored-by:
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Li-Huai (Allan) Lin authored
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kding1 authored
* update trainer with cpu distributed fine-tuning support. Signed-off-by:
Ding, Ke <ke.ding@intel.com> * Style. * refinement on cpu dist training check. Signed-off-by:
Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by:
Morgan Funtowicz <funtowiczmo@gmail.com> Co-authored-by:
Funtowicz Morgan <mfuntowicz@users.noreply.github.com> Co-authored-by:
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kding1 authored
* add sigopt hpo to transformers. Signed-off-by:
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Stas Bekman authored
* one possible solution * low mem from_pretrained * edge cases * solve the persistent buffers * style * parametrize * for later * proper solution * cleanup * refactor; rework based on suggestions * revert splitting into 2 parts, move checks into main func
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- 22 Sep, 2021 11 commits
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Lysandre Debut authored
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Lysandre Debut authored
* Add BlenderBot small tokenizer to the init * Update src/transformers/__init__.py Co-authored-by:
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Gunjan Chhablani authored
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Suraj Patil authored
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Anton Lozhkov authored
* Use fp16 checkpoints * Style * Fix outputs and disable OOM tests * Correct another output * Use a random smaller model for generation tests * repo quickfix * fix gradient checkpointing
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Lysandre Debut authored
* Patch training arguments issue * Update src/transformers/training_args.py Co-authored-by:
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Gunjan Chhablani authored
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Yih-Dar authored
Co-authored-by:ydshieh <ydshieh@users.noreply.github.com>
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MocktaiLEngineer authored
* Raise exceptions instead of using assertions for control flow #12789 * # coding=utf-8 * Raise exceptions instead of using assertions for control flow * Raise exceptions instead of using assertions for control flow * Update src/transformers/tokenization_utils.py Raise exceptions instead of using assertions for control flow Co-authored-by:
MocktaiLEngineer <kavinarasu22@gmail.com> Co-authored-by:
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Sylvain Gugger authored
* Make gradient_checkpointing a training argument * Update src/transformers/modeling_utils.py Co-authored-by:
Stas Bekman <stas00@users.noreply.github.com> * Update src/transformers/configuration_utils.py Co-authored-by:
Stas Bekman <stas@stason.org>
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Anton Lozhkov authored
* Force dtype, add tests * Local torch imports * Remove unused logic (always ndarray)
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- 21 Sep, 2021 12 commits
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Patrick von Platen authored
* up * up
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Patrick von Platen authored
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Kamal Raj authored
conv kernel_size to Tuple, Flax Version 0.3.5 breaking change, https://github.com/google/flax/releases/tag/v0.3.5
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Sylvain Gugger authored
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Nishant Prabhu authored
* Add support for exporting PyTorch LayoutLM to ONNX * Added tests for converting LayoutLM to ONNX * Add support for exporting PyTorch LayoutLM to ONNX * Added tests for converting LayoutLM to ONNX * cleanup * Removed regression/ folder * Add support for exporting PyTorch LayoutLM to ONNX * Added tests for converting LayoutLM to ONNX * cleanup * Fixed import error * Remove unnecessary import statements * Changed max_2d_positions from class variable to instance variable of the config class * Add support for exporting PyTorch LayoutLM to ONNX * Added tests for converting LayoutLM to ONNX * cleanup * Add support for exporting PyTorch LayoutLM to ONNX * cleanup * Fixed import error * Changed max_2d_positions from class variable to instance variable of the config class * Use super class generate_dummy_inputs method Co-authored-by:
Michael Benayoun <mickbenayoun@gmail.com> * Add support for Masked LM, sequence classification and token classification Co-authored-by:
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Sylvain Gugger authored
* Add push_to_hub to no_trainer examples * Quality * Document integration * Roll out to other examples
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Stas Bekman authored
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Anton Lozhkov authored
* Test np padding * Pass feature extraction tests * Update type hints * Fix flaky integration tests * Try a more stable waveform * Add to_numpy jax support * int32 attention masks * Refactor normalization tests
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Kamal Raj authored
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Kamal Raj authored
* flax qa example * Updated README: Added Large model * added utils_qa.py FULL_COPIES * Updates: 1. Copyright Year updated 2. added dtype arg 3. passing seed and dtype to load model 4. Check eval flag before running eval * updated README * updated code comment
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Kamal Raj authored
* beit-flax * updated FLAX_BEIT_MLM_DOCSTRING * removed bool_masked_pos from classification * updated Copyright * code refactoring: x -> embeddings * updated test: rm from_pt * Update docs/source/model_doc/beit.rst * model code dtype updates and other changes according to review * relative_position_bias revert back to pytorch design
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Patrick von Platen authored
* upload * correct * correct * correct * finish * up * up * up again
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- 20 Sep, 2021 3 commits
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flozi00 authored
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Lowin authored
the variables of run example is not correct
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Sylvain Gugger authored
* Dynamic model * Use defensive flag * Style * Doc and arg rename * Arg rename * Add tests * Apply suggestions from code review Co-authored-by:
Lysandre Debut <lysandre@huggingface.co> * Apply suggestions from code review Co-authored-by:
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