+ QV-jÔãó¼€^RIt^RIHtHt^RIHt^RIHt^RIH t ^RI H t ]P!] 4t]] !] P4!RR] 444tR#) éN)Ú dataclassÚfield)ÚPath)ÚGenerationConfig)ÚTrainingArguments)Úadd_start_docstringscóºaa€]tRt^toRt]!RRR/R7t]!RRR/R7t]!RRR/R7t]!RRR /R7t ]!RRR /R7t V3R lt V3R lt R t VtV;t#)ÚSeq2SeqTrainingArgumentsaœ 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. FÚhelpz%Whether to use SortishSampler or not.)ÚdefaultÚmetadatazFWhether to use generate to calculate generative metrics (ROUGE, BLEU).Nz•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.z“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.z^Model id, file path or url pointing to a GenerationConfig json file, to use during prediction.c óª<€\SV`4pVP4F/wr#\V\4'gKVP4W&K1 V#)zÀ 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. )ÚsuperÚto_dictÚitemsÚ isinstancer)ÚselfÚdÚkÚvÚ __class__s& €Ús/Volumes/fast/ai/experiments/ui-tars-smoke/.venv/lib/python3.14/site-packages/transformers/training_args_seq2seq.pyrÚ Seq2SeqTrainingArguments.to_dictTsEø€ô ‰G‰OÓ ˆØ—G‘G–I‰DˆAܘ!Ô-×.Ô.Ø—y‘y“{“ñðˆócó <€V^8„dQh/S[;R&S[;R&S[R,;R&S[R,;R&S[S[,S[,R,;R&#)éÚsortish_samplerÚpredict_with_generateNÚgeneration_max_lengthÚgeneration_num_beamsÚgeneration_config)ÚboolÚintÚstrrr)ÚformatÚ __classdict__s"€rÚ __annotate__Ú%Seq2SeqTrainingArguments.__annotate__skø‡‚ñ8Ñlñ9ñ: ññ;ñ@ :ññAñR *ññSñd™T•zÑ$4Õ4°tÕ;ñòer©)Ú__name__Ú __module__Ú __qualname__Ú__firstlineno__Ú__doc__rrrrr r!rÚ__annotate_func__Ú__static_attributes__Ú__classdictcell__Ú __classcell__)rr&s@@rr r s™ù‡€ññ2"¨%¸6ÐCjÐ:kÔl€OÙ"'Ø Ð)qÐ rô#Ðñ).Øà ðHð ô)Ðñ(-Øà ðGð ô(Ðñ?DØà Ðtð ô?Ðõ ÷s…rr )ÚloggingÚ dataclassesrrÚpathlibrÚgeneration.configuration_utilsrÚ training_argsrÚutilsrÚ getLoggerr*Úloggerr.r r)rrÚr;s^ðóß(Ýå<Ý,Ý'ð × Ò ˜8Ó $€ð ÙÐ'×/Ñ/Ó0ôAÐ0óAó1ó òAr