Rewind Reward
Project description
ReWiND Reward - Pytorch (wip)
Implementation of ReWiND, "Language-Guided Rewards Teach Robot Policies without New Demonstrations", from USC / Amazon Robotics
Install
$ pip install rewind-reward-pytorch
Usage
import torch
from rewind_reward_pytorch import RewardModel
reward_model = RewardModel(
reward_bins = 10
)
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)
logits = reward_model(commands, video) # (2, 16, 10)
assert logits.shape == (2, 16, 10)
Citations
@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}
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
rewind_reward_pytorch-0.0.8.tar.gz
(908.2 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file rewind_reward_pytorch-0.0.8.tar.gz.
File metadata
- Download URL: rewind_reward_pytorch-0.0.8.tar.gz
- Upload date:
- Size: 908.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.9.23
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
b09b668ce7db9fcdc443db611c3e7f3b41b01e619670c598c3a9872b0bafa5ae
|
|
| MD5 |
b1920b936095ba209242ba17502dcb71
|
|
| BLAKE2b-256 |
074678937b908e8a3d729b8426ebc9916160ecd276e40a8b015d94af3162d20e
|
File details
Details for the file rewind_reward_pytorch-0.0.8-py3-none-any.whl.
File metadata
- Download URL: rewind_reward_pytorch-0.0.8-py3-none-any.whl
- Upload date:
- Size: 5.5 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.9.23
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
be4f05b2f93a063708be2cdbe08e8eef98a61a235efbfe6d982967058c932c7b
|
|
| MD5 |
9af404781003573169f035dad15dd192
|
|
| BLAKE2b-256 |
1af8a0f92bf7bd1827f5589b600b7c72af0c9eb35273317a4788fc2ed4c6e717
|