What's Changed

• Speed up function _same_mask in DetConBLoss by 25% by @misrasaurabh1 in #1847
• Fix DINOv2 Bugs
• Add DINOv2 to Docs with Example
• Fix: vicregl_loss tensor RuntimeError by @RDR2Blackwater in #1850
• Add iBOTTransform
• Add iBOT Implementation
• Add iBOT to Docs with Example
• Fix KNN dtype for ResNet benchmark
• Fix CUDA Tests for Losses
• Fix OnlineClassifier Issues
• Support Tensor Input for GaussianBlur
• Use ToTensor Helper Function by @ajtritt in #1862
• Move Rotation After Flip for Transforms by @KylevdLangemheen in #1865
• Improve pre-commit hooks for Dev Env
• Add iBOT Benchmarks

New Contributors

• @misrasaurabh1 made their first contribution in #1847
• @RDR2Blackwater made their first contribution in #1850
• @ajtritt made their first contribution in #1862
• @KylevdLangemheen made their first contribution in #1865

Full Changelog: v1.15.21...v1.15.22

Many thanks to our contributors!

Models

• AIM: Scalable Pre-training of Large Autoregressive Image Models
• Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021
• Bootstrap your own latent: A new approach to self-supervised Learning, 2020
• DCL: Decoupled Contrastive Learning, 2021
• DenseCL: Dense Contrastive Learning for Self-Supervised Visual Pre-Training, 2021
• DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021
• DINOv2: Learning Robust Visual Features without Supervision, 2023
• FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022
• iBOT: Image BERT Pre-Training with Online Tokenizer, 2021
• I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023
• MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
• MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
• MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019
• NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021
• PMSN: Prior Matching for Siamese Networks, 2022
• SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020
• SimMIM: A Simple Framework for Masked Image Modeling, 2021
• SimSiam: Exploring Simple Siamese Representation Learning, 2020
• SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
• SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
• TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022
• VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
• VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022

What's Changed

• Add DINOv2 ViT benchmark Implementation
• Add Paper Joint-Embedding vs Reconstruction: Provable Benefits of Latent Space Prediction for Self-Supervised Learning, 2025 by Meta to "Lightly in Research". Thank them for the credit!
• Add seed_everything for reproducibility in benchmarks by @yvesyue in #1819
• Fix MyPy type-checking issues for newer versions of NumPy by @yvesyue in #1820
• Fix DCLLoss negative-term aggregation and add loop-based reference test by @yvesyue in #1827
• Fix bugs in KNN benchmark evaluation
• Fix bugs in cosine scheduler warmup epochs
• Fix MaskedCausalBlock.__init__() got an unexpected keyword argument 'proj_bias' due to interface change in the newer TIMM versions
• Fix AddGridTransform due to interface change in the newer Torchvision versions
• Fix format & format-check to only target python directories
• Remove video download functions
• Remove unused download functions & add typing

New Contributors

• @yvesyue made their first contribution in #1819

Full Changelog: v1.5.20...v1.15.21

Many thanks to our contributors!

Models

• AIM: Scalable Pre-training of Large Autoregressive Image Models
• Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021
• Bootstrap your own latent: A new approach to self-supervised Learning, 2020
• DCL: Decoupled Contrastive Learning, 2021
• DenseCL: Dense Contrastive Learning for Self-Supervised Visual Pre-Training, 2021
• DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021
• DINOv2: Learning Robust Visual Features without Supervision, 2023
• FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022
• I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023
• MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
• MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
• MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019
• NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021
• PMSN: Prior Matching for Siamese Networks, 2022
• SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020
• SimMIM: A Simple Framework for Masked Image Modeling, 2021
• SimSiam: Exploring Simple Siamese Representation Learning, 2020
• SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
• SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
• TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022
• VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
• VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022

Changes

• Added DINO ViT Benchmark
• Fixed BTLoss: ensure invariance to affine transformations by @adosar in #1806
• Tested BTLoss: use default values for torch.allclose by @adosar in #1810
• Added more detailed docstring to knn predict by @maxprogrammer007 in #1812
• Removed verbose in CosineWarmUpScheduler
• Add LightlyTrain Reference
• Renamed lightly-train command to lightly-ssl-train

Many thanks to our contributors!

Models

• AIM: Scalable Pre-training of Large Autoregressive Image Models
• Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021
• Bootstrap your own latent: A new approach to self-supervised Learning, 2020
• DCL: Decoupled Contrastive Learning, 2021
• DenseCL: Dense Contrastive Learning for Self-Supervised Visual Pre-Training, 2021
• DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021
• FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022
• I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023
• MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
• MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
• MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019
• NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021
• PMSN: Prior Matching for Siamese Networks, 2022
• SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020
• SimMIM: A Simple Framework for Masked Image Modeling, 2021
• SimSiam: Exploring Simple Siamese Representation Learning, 2020
• SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
• SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
• TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022
• VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
• VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022

Changes

• Docs: Fix mismatch between forward method and docstring of NTXentLoss by @adosar in #1789
• Update NNCLR model examples in docs
• Updated the BYOL model examples in docs
• Updated the DINO model examples in docs
• Update the SimSiam model examples in docs
• Additional tests added to pooling operation for DetCon
• Fix issues with the Lightning Trainer's strategy in the MAE examples and support new Lightning versions in the benchmarks
• Added loss function for MACL (Model-Aware Contrastive Learning)
• Updated CONTRIBUTING Guide and GitHub Actions
• Fix multiple issues with loss tests

Models

• AIM: Scalable Pre-training of Large Autoregressive Image Models
• Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021
• Bootstrap your own latent: A new approach to self-supervised Learning, 2020
• DCL: Decoupled Contrastive Learning, 2021
• DenseCL: Dense Contrastive Learning for Self-Supervised Visual Pre-Training, 2021
• DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021
• FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022
• I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023
• MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
• MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
• MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019
• NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021
• PMSN: Prior Matching for Siamese Networks, 2022
• SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020
• SimMIM: A Simple Framework for Masked Image Modeling, 2021
• SimSiam: Exploring Simple Siamese Representation Learning, 2020
• SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
• SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
• TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022
• VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
• VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022

Changes

• Update SimCLR model model example
• Update MAE model docs
• adjust pagination to be defensive at 2500 entries
• Fix typo: Dict() instead of dict() return class instanciation error by @gatienc in #1785

Many thanks to all of our contributors!

Models

• AIM: Scalable Pre-training of Large Autoregressive Image Models
• Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021
• Bootstrap your own latent: A new approach to self-supervised Learning, 2020
• DCL: Decoupled Contrastive Learning, 2021
• DenseCL: Dense Contrastive Learning for Self-Supervised Visual Pre-Training, 2021
• DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021
• FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022
• I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023
• MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
• MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
• MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019
• NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021
• PMSN: Prior Matching for Siamese Networks, 2022
• SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020
• SimMIM: A Simple Framework for Masked Image Modeling, 2021
• SimSiam: Exploring Simple Siamese Representation Learning, 2020
• SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
• SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
• TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022
• VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
• VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022

Changes

• fix detcon loss distributed issue
• remove heuristics in masked pooling
• fix torchvision dependency test

Many thanks to all of our contributors!

Models

• AIM: Scalable Pre-training of Large Autoregressive Image Models
• Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021
• Bootstrap your own latent: A new approach to self-supervised Learning, 2020
• DCL: Decoupled Contrastive Learning, 2021
• DenseCL: Dense Contrastive Learning for Self-Supervised Visual Pre-Training, 2021
• DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021
• FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022
• I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023
• MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
• MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
• MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019
• NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021
• PMSN: Prior Matching for Siamese Networks, 2022
• SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020
• SimMIM: A Simple Framework for Masked Image Modeling, 2021
• SimSiam: Exploring Simple Siamese Representation Learning, 2020
• SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
• SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
• TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022
• VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
• VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022

Changes

• Added DetConSLoss and DetConBLoss
• removed opencv dependencies partial thanks to @vectorvp
• fix: IJEPA example by thanks to @vectorvp

Typing and Docs

• Many files are now properly typed and type-checked thanks to @philippmwirth
• We removed old and outdated documentation regarding the LightlyOne Worker

Many thanks to all of our contributors!

Models

• AIM: Scalable Pre-training of Large Autoregressive Image Models
• Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021
• Bootstrap your own latent: A new approach to self-supervised Learning, 2020
• DCL: Decoupled Contrastive Learning, 2021
• DenseCL: Dense Contrastive Learning for Self-Supervised Visual Pre-Training, 2021
• DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021
• FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022
• I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023
• MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
• MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
• MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019
• NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021
• PMSN: Prior Matching for Siamese Networks, 2022
• SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020
• SimMIM: A Simple Framework for Masked Image Modeling, 2021
• SimSiam: Exploring Simple Siamese Representation Learning, 2020
• SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
• SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
• TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022
• VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
• VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022

Changes

New transforms

• Add PhaseShift Transform (#1714) by @pearguacamole
• Add FDATransform (#1734) by @vectorvp

Switch to version-independent torchvision transforms.

• If torchvision transforms v2 are available, they are used. Otherwise torchvision transforms v1 are used. For details see this comment.
• Add Transform for DetCon + MultiViewTransformV2 for torchvision.transforms.v2 (#1737)

Typing, naming & docstring improvements

• Type data/_utils (#1740), data/_helpers (#1742) and tests/models (#1744) by @vectorvp
• Cleanup: docstrings in the lightly/data subpackage (#1741) by @ChiragAgg5k
• Refactor: Update naming and remove unused package from AmplitudeRescaleTransform (#1732) by @vectorvp

Other

• Fix DINOProjectionHead BatchNorm Handling (#1729)
• Add masked average pooling for pooling with segmentation masks (DetCon)(#1739)

Many thanks to all of our contributors!

Models

• AIM: Scalable Pre-training of Large Autoregressive Image Models
• Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021
• Bootstrap your own latent: A new approach to self-supervised Learning, 2020
• DCL: Decoupled Contrastive Learning, 2021
• DenseCL: Dense Contrastive Learning for Self-Supervised Visual Pre-Training, 2021
• DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021
• FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022
• I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023
• MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
• MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
• MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019
• NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021
• PMSN: Prior Matching for Siamese Networks, 2022
• SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020
• SimMIM: A Simple Framework for Masked Image Modeling, 2021
• SimSiam: Exploring Simple Siamese Representation Learning, 2020
• SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
• SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
• TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022
• VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
• VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022

Changes

New transforms

• Added RFFT2D and IRFFT2D transforms @snehilchatterjee
• Add RandomFrequencyMaskTransform @payo101
• Add GaussianMixtureMaskTransform @snehilchatterjee
• Add AmplitudeRescaleTransform @payo101
• Better support for both torchvision.transforms v1 and v2 without warnings/errors.

Added and updated docstrings

• Many improvements by @Prathamesh010, @ayush22iitbhu, @ChiragAgg5k @HarshitVashisht11

Docs improvements

• Improvements of the README.md @bhargavshirin and @kushal34712 @eltociear @Mefisto04 @ayush22iitbhu
• Improvements of other parts of the the docs and tutorials @jizhang02
• Fix examples on Windows @snehilchatterjee
• Improve CONTRIBUTING.md @Prathamesh010
• Added a back to top button for easier navigation @hackit-coder

More and better typing

• Testing typing for all python versions
• Typing of serve.py @ishaanagw
• Cleanup: _image.py and _utils.py file in data subpackage @ChiragAgg5k

Better formatting

• Move classes and public functions to top of file @fadkeabhi and @SauravMaheshkar

Other

• Print Aggregate Metrics at End of Benchmarks as Markdown Table @EricLiclair

Many thanks to all of our contributors!

Models

• AIM: Scalable Pre-training of Large Autoregressive Image Models
• Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021
• Bootstrap your own latent: A new approach to self-supervised Learning, 2020
• DCL: Decoupled Contrastive Learning, 2021
• DenseCL: Dense Contrastive Learning for Self-Supervised Visual Pre-Training, 2021
• DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021
• FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022
• I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023
• MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
• MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
• MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019
• NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021
• PMSN: Prior Matching for Siamese Networks, 2022
• SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020
• SimMIM: A Simple Framework for Masked Image Modeling, 2021
• SimSiam: Exploring Simple Siamese Representation Learning, 2020
• SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
• SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
• TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022
• VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
• VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022

• Support python 3.12, thanks @MalteEbner
• update cosine warmup scheduler, thanks @guarin

Models

• AIM: Scalable Pre-training of Large Autoregressive Image Models
• Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021
• Bootstrap your own latent: A new approach to self-supervised Learning, 2020
• DCL: Decoupled Contrastive Learning, 2021
• DenseCL: Dense Contrastive Learning for Self-Supervised Visual Pre-Training, 2021
• DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021
• FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022
• I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023
• MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
• MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
• MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019
• NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021
• PMSN: Prior Matching for Siamese Networks, 2022
• SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020
• SimMIM: A Simple Framework for Masked Image Modeling, 2021
• SimSiam: Exploring Simple Siamese Representation Learning, 2020
• SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
• SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
• TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022
• VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
• VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022