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rewind-reward-pytorch

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Implementation of ReWiND, "Language-Guided Rewards Teach Robot Policies without New Demonstrations", from USC / Amazon Robotics

// repository documentation

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## ReWiND Reward - Pytorch (wip)

Implementation of [ReWiND, "Language-Guided Rewards Teach Robot Policies without New Demonstrations"](https://rewind-reward.github.io/), from USC / Amazon Robotics

## Install

```bash
$ pip install rewind-reward-pytorch
```

## Usage

```python
import torch

from rewind_reward_pytorch import (
    RewardModel,
    RewindTrainWrapper
)

reward_model = RewardModel()

wrapper = RewindTrainWrapper(
    reward_model,
    rewind_augmentation_prob = 0.25
)

commands = [
  'pick up the blue ball and put it in the red tray',
  'pick up the red cube and put it in the green bin',
]

video = torch.rand(2, 3, 16, 224, 224)

loss = wrapper(
    commands,
    video
)

loss.backward()

# after much training

pred_rewards = reward_model(
    commands,
    video
) # (2, 16) - per frame progress prediction

assert pred_rewards.shape == (2, 16)

```

## Citations

```bibtex
@article{Zhang2025ReWiNDLR,
    title   = {ReWiND: Language-Guided Rewards Teach Robot Policies without New Demonstrations},
    author  = {Jiahui Zhang and Yusen Luo and Abrar Anwar and Sumedh Anand Sontakke and Joseph J. Lim and Jesse Thomason and Erdem Biyik and Jesse Zhang},
    journal = {ArXiv},
    year    = {2025},
    volume  = {abs/2505.10911},
    url     = {https://api.semanticscholar.org/CorpusID:278714746}
}
```

rewind-reward-pytorch

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