Ë wfžhãót—ddlmZddlZddlmZddlmZeje«Z eGd„de««Z y)é)Ú annotationsN)Ú dataclass)ÚSentenceTransformerDataCollatorcó—eZdZdZy)ÚSparseEncoderDataCollatoraËCollator for a SparseEncoder model. Overridden from SentenceTransformerDataCollator with nothing added. This encodes the text columns to {column}_input_ids and {column}_attention_mask columns. This works with the two text dataset that is used as the example in the training overview: https://www.sbert.net/docs/sentence_transformer/training_overview.html It is important that the columns are in the expected order. For example, if your dataset has columns "answer", "question" in that order, then the MultipleNegativesRankingLoss will consider "answer" as the anchor and "question" as the positive, and it will (unexpectedly) optimize for "given the answer, what is the question?". N)Ú__name__Ú __module__Ú __qualname__Ú__doc__©óúp/home/chris/cleankitchens-env/lib/python3.12/site-packages/sentence_transformers/sparse_encoder/data_collator.pyrr s„ò r r) Ú __future__rÚloggingÚ dataclassesrÚ#sentence_transformers.data_collatorrÚ getLoggerrÚloggerrr r rúrs?ðÝ"ãÝ!åOà ˆ× Ñ ˜8Ó $€ð ô Ð ?ó ó ñ r