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-0.0.4.tar.gz
(907.6 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-0.0.4.tar.gz.
File metadata
- Download URL: rewind_reward_pytorch-0.0.4.tar.gz
- Upload date:
- Size: 907.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.9.23
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
90cf971f4e722059dc32ca28d6ab7bd447807a218511c940b5be07d141821977
|
|
| MD5 |
f575dcf902c930dd31e439eda1d38046
|
|
| BLAKE2b-256 |
21bfb0ed3efb3d0fb01e8059839ce3a7852eea924c960351e730246cf23b9625
|
File details
Details for the file rewind_reward_pytorch-0.0.4-py3-none-any.whl.
File metadata
- Download URL: rewind_reward_pytorch-0.0.4-py3-none-any.whl
- Upload date:
- Size: 5.0 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 |
1a262c019da2f4d4a980182ec0dbd72080fd14295bc293e930be42ae8a24281f
|
|
| MD5 |
337df02f915acdf60f2fa28c71a48ba1
|
|
| BLAKE2b-256 |
4c3e4a4e43efe1b2226e8ab9835d8cd726a1c89e54c047dc0fbde2307006cab6
|