jSSKrSSKJrJr SSKJr SSKJr SSKJ r SSK J r \R"\ 5r\\ "\ R5"SS \ 555rg) N) dataclassfield)Path)GenerationConfig)TrainingArguments)add_start_docstringsc^\rSrSr%Sr\"SSS0S9r\\S'\"SSS0S9r \\S '\"S SS 0S9r \ S -\S '\"S SS 0S9r \ S -\S'\"S SS0S9r \\-\-S -\S'U4SjrSrU=r$)Seq2SeqTrainingArgumentsa sortish_sampler (`bool`, *optional*, defaults to `False`): Whether to use a *sortish sampler* or not. Only possible if the underlying datasets are *Seq2SeqDataset* for now but will become generally available in the near future. It sorts the inputs according to lengths in order to minimize the padding size, with a bit of randomness for the training set. predict_with_generate (`bool`, *optional*, defaults to `False`): Whether to use generate to calculate generative metrics (ROUGE, BLEU). generation_max_length (`int`, *optional*): The `max_length` to use on each evaluation loop when `predict_with_generate=True`. Will default to the `max_length` value of the model configuration. generation_num_beams (`int`, *optional*): The `num_beams` to use on each evaluation loop when `predict_with_generate=True`. Will default to the `num_beams` value of the model configuration. generation_config (`str` or `Path` or [`~generation.GenerationConfig`], *optional*): Allows to load a [`~generation.GenerationConfig`] from the `from_pretrained` method. This can be either: - a string, the *model id* of a pretrained model configuration hosted inside a model repo on huggingface.co. - a path to a *directory* containing a configuration file saved using the [`~GenerationConfig.save_pretrained`] method, e.g., `./my_model_directory/`. - a [`~generation.GenerationConfig`] object. Fhelpz%Whether to use SortishSampler or not.)defaultmetadatasortish_samplerzFWhether to use generate to calculate generative metrics (ROUGE, BLEU).predict_with_generateNzThe `max_length` to use on each evaluation loop when `predict_with_generate=True`. Will default to the `max_length` value of the model configuration.generation_max_lengthzThe `num_beams` to use on each evaluation loop when `predict_with_generate=True`. Will default to the `num_beams` value of the model configuration.generation_num_beamsz^Model id, file path or url pointing to a GenerationConfig json file, to use during prediction.generation_configc>[TU]5nUR5H.up#[U[5(dMUR5X'M0 U$)z Serializes this instance while replace `Enum` by their values and `GenerationConfig` by dictionaries (for JSON serialization support). It obfuscates the token values by removing their value. )superto_dictitems isinstancer)selfdkv __class__s ڰC:\Users\johnn\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.13_qbz5n2kfra8p0\LocalCache\local-packages\Python313\site-packages\transformers/training_args_seq2seq.pyr Seq2SeqTrainingArguments.to_dictTsE GO GGIDA!-..yy{)__name__ __module__ __qualname____firstlineno____doc__rrbool__annotations__rrintrrstrrrr__static_attributes__ __classcell__)rs@rr r s2"%6Cj:klOTl"')q r#4). H )3:(- G (#*?D t ?sTz$44t;  r!r )logging dataclassesrrpathlibrgeneration.configuration_utilsr training_argsrutilsr getLoggerr#loggerr'r r"r!rr6s^(<,'   8 $ '//0A0A1 Ar!