Sync/v4.9.2 #232
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Sync/v4.9.2 #232
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mention in `save_strategy` param description that `load_best_model_at_end` can override
* document sub_group_size * style * install + issues reporting * style * style * Update docs/source/main_classes/deepspeed.rst Co-authored-by: Sylvain Gugger <[email protected]> * indent 4 * restore * style Co-authored-by: Sylvain Gugger <[email protected]>
Signed-off-by: Richard Liaw <[email protected]>
* Fix torchscript tests * Better test * Remove bogus print
…12350) * fix distributed_concat for scalar outputs * Update README.md * fixed typo (#12356) * simplify fix with terser syntax Co-authored-by: Sylvain Gugger <[email protected]> * Trigger CI Co-authored-by: Patrick von Platen <[email protected]> Co-authored-by: michal pitr <[email protected]> Co-authored-by: Sylvain Gugger <[email protected]>
* port bigbird script * adapt script a bit * change location * adapt more * save progress * init commit * style * dataset script tested * readme add
…(#12357) * Replace NotebookProgressReporter by ProgressReporter in Ray Tune run * Move to local import
* fixed multiplechoice tokenization The model would have seen two sequences: 1. [CLS]prompt[SEP]prompt[SEP] 2. [CLS]choice0[SEP]choice1[SEP] that is not correct as we want a contextualized embedding of prompt and choice * removed outer brackets for proper sequence generation
* main_process_first context manager * handle multi-node, add context description * sync desc
…d pytorch (#12359) * added log_level * fix comment * fixed log_level * Trigger CI * Unfied logging * simplified args for log_level
…BertTokenizer-like tokenizers (#12371) * Notify users that DataCollatorForWholeWordMask is limited to BertTokenier-like tokenizers * Fix code formatting
Before the code could not be used for validation only because of this line:
extension = data_args.train_file.split(".")[-1]
was assuming that extension must be extracted from the training dataset. This line would run regardless of the training or validation options of the user. This would lead to an error if the user only wants to run an evaluation only and does not want to do train (because the training file does not exist). I modified it to extract extension from the training file if the user wants to do train and extract it from the validation file if the user wants to run eval. This way the code can be used for both training and validation separately.
* add dependency table sync verification * improve the message * improve the message * revert * ready to merge
* added cotext manager to datasets map * fixed style and spaces * fixed warning of deprecation * changed desc
* fix_torch_device_generate_test * remove @ * boom boom * correct typos * Apply suggestions from code review Co-authored-by: Suraj Patil <[email protected]> * Apply suggestions from code review Co-authored-by: Suzana Ilić <[email protected]> * Apply suggestions from code review Co-authored-by: Suraj Patil <[email protected]> Co-authored-by: Suzana Ilić <[email protected]>
* Add _CHECKPOINT_FOR_DOC * Update src/transformers/models/funnel/modeling_funnel.py Co-authored-by: Sylvain Gugger <[email protected]> Co-authored-by: Sylvain Gugger <[email protected]>
* [Deepspeed] warmup_ratio docs * Update docs/source/main_classes/deepspeed.rst Co-authored-by: Sylvain Gugger <[email protected]> * style * Update docs/source/main_classes/deepspeed.rst Co-authored-by: Sylvain Gugger <[email protected]> * style Co-authored-by: Sylvain Gugger <[email protected]>
…12836) * document Deepspeed-Inference and parallelformers * Apply suggestions from code review Co-authored-by: Sylvain Gugger <[email protected]> Co-authored-by: Sylvain Gugger <[email protected]>
* Raise an issue if the pytorch version is < 1.8.0 * Attempt to add a test to ensure it correctly raises. * Missing docstring. * Second attempt, patch with string absolute import. * Let's do the call before checking it was called ... * use the correct function ... 🤦 * Raise ImportError and AssertionError respectively when unable to find torch and torch version is not sufficient. * Correct path mock patching * relax constraint for torch_onnx_dict_inputs to ge instead of eq. * Style. * Split each version requirements for torch. * Let's compare version directly. * Import torch_version after checking pytorch is installed. * @require_torch
GPT-Neo ONNX export and task / feature refactoring Authored-by: Michael Benayoun <[email protected]>
T5 with past ONNX export, and more explicit past_key_values inputs and outputs names for ONNX model Authored-by: Michael Benayoun <[email protected]>
* Add MBART to models exportable with ONNX * unittest mock * Add tests * Misc fixes
* Add to ONNX docs * Add MBART example * Update docs/source/serialization.rst Co-authored-by: Sylvain Gugger <[email protected]> Co-authored-by: Sylvain Gugger <[email protected]>
* Fix tied weights on TPU * Manually tie weights in no trainer examples * Fix for test * One last missing * Gettning owned by my scripts * Address review comments * Fix test * Fix tests * Fix reformer tests
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