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52 lines
1.8 KiB
52 lines
1.8 KiB
"""
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This file contains deprecated code that can only be used with the old `model.fit`-style Sentence Transformers v2.X training.
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It exists for backwards compatibility with the `model.old_fit` method, but will be removed in a future version.
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Nowadays, with Sentence Transformers v3+, it is recommended to use the `SentenceTransformerTrainer` class to train models.
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See https://www.sbert.net/docs/sentence_transformer/training_overview.html for more information.
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Instead, you should create a `datasets` `Dataset` for training: https://huggingface.co/docs/datasets/create_dataset
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"""
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from __future__ import annotations
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import os
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from . import InputExample
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class LabelSentenceReader:
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"""Reads in a file that has at least two columns: a label and a sentence.
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This reader can for example be used with the BatchHardTripletLoss.
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Maps labels automatically to integers
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"""
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def __init__(self, folder, label_col_idx=0, sentence_col_idx=1, separator="\t"):
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self.folder = folder
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self.label_map = {}
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self.label_col_idx = label_col_idx
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self.sentence_col_idx = sentence_col_idx
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self.separator = separator
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def get_examples(self, filename, max_examples=0):
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examples = []
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id = 0
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for line in open(os.path.join(self.folder, filename), encoding="utf-8"):
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splits = line.strip().split(self.separator)
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label = splits[self.label_col_idx]
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sentence = splits[self.sentence_col_idx]
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if label not in self.label_map:
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self.label_map[label] = len(self.label_map)
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label_id = self.label_map[label]
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guid = f"{filename}-{id}"
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id += 1
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examples.append(InputExample(guid=guid, texts=[sentence], label=label_id))
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if 0 < max_examples <= id:
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break
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return examples
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