重磅开源！FAIR发布自监督训练库VISSL！-技术圈

点蓝色字关注“机器学习算法工程师”

设为星标，干货直达！

目前在CV领域最火的除了transformer的应用外，就属于自监督学习了（Self-Supervised Learning），日前Facebook AI开源了基于PyTorch的自监督学习库VISSL，目前该库实现了自监督学习的SOTA，并且给出了详细的使用教程

https://github.com/facebookresearch/vissl

VISSL助力推动CV领域自监督学习的发展，FAIR官方出品，特点突出：

Reproducible implementation of SOTA in Self-Supervision: All existing SOTA in Self-Supervision are implemented - SwAV, SimCLR, MoCo(v2), PIRL, NPID, NPID++, DeepClusterV2, ClusterFit, RotNet, Jigsaw. Also supports supervised trainings.
Benchmark suite: Variety of benchmarks tasks including linear image classification (places205, imagenet1k, voc07), full finetuning, semi-supervised benchmark, nearest neighbor benchmark, object detection (Pascal VOC and COCO).
Ease of Usability: easy to use using yaml configuration system based on Hydra.
Modular: Easy to design new tasks and reuse the existing components from other tasks (objective functions, model trunk and heads, data transforms, etc.). The modular components are simple drop-in replacements in yaml config files.
Scalability: Easy to train model on 1-gpu, multi-gpu and multi-node. Several components for large scale trainings provided as simple config file plugs: Activation checkpointing, ZeRO, FP16, LARC, Stateful data sampler, data class to handle invalid images, large model backbones like RegNets, etc.
Model Zoo: Over 60 pre-trained self-supervised model weights.