contrastive-rl-pytorch 0.0.1

Contrastive RL

contrastive-rl (wip)

For following a new line of research that started in 2022 from Eysenbach et al.

install

$ pip install contrastive-rl-pytorch

usage

from contrastive_rl.contrastive_rl import ContrastiveRLTrainer
from x_mlps_pytorch import MLP

encoder = MLP(16, 256, 128)

trainer = ContrastiveRLTrainer(encoder)

trajectories = torch.randn(256, 512, 16)

trainer(trajectories, 100)

# train for 100 steps and save

torch.save(encoder.state_dict(), './trained.pt')

citations

@misc{eysenbach2023contrastivelearninggoalconditionedreinforcement,
    title   = {Contrastive Learning as Goal-Conditioned Reinforcement Learning}, 
    author  = {Benjamin Eysenbach and Tianjun Zhang and Ruslan Salakhutdinov and Sergey Levine},
    year    = {2023},
    eprint  = {2206.07568},
    archivePrefix = {arXiv},
    primaryClass = {cs.LG},
    url     = {https://arxiv.org/abs/2206.07568}, 
}

@misc{ziarko2025contrastiverepresentationstemporalreasoning,
    title   = {Contrastive Representations for Temporal Reasoning}, 
    author  = {Alicja Ziarko and Michal Bortkiewicz and Michal Zawalski and Benjamin Eysenbach and Piotr Milos},
    year    = {2025},
    eprint  = {2508.13113},
    archivePrefix = {arXiv},
    primaryClass = {cs.LG},
    url     = {https://arxiv.org/abs/2508.13113}, 
}