As a self-supervised learning paradigm. contrastive learning has been widely used to pre-train a powerful encoder as an effective feature extractor for various downstream tasks. This process requires numerous unlabeled training data and computational resources. which makes the pre-trained encoder become the valuable intellectual property of the owner. https://bbmbatteryes.shop/product-category/108/