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-0.0.10.tar.gz
(908.6 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-0.0.10.tar.gz.
File metadata
- Download URL: rewind_reward_pytorch-0.0.10.tar.gz
- Upload date:
- Size: 908.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.9.23
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f8bc7cfb5bf1841664cf029f73e76436c082485aefc98020ccedaaa657e38f3a
|
|
| MD5 |
f0c9a01976ecdff1d66ed46adc82ea5b
|
|
| BLAKE2b-256 |
05a345ae35d589c4b6c92f6dd8cb3cceaca8c802cb923e1adabffd8c410a5467
|
File details
Details for the file rewind_reward_pytorch-0.0.10-py3-none-any.whl.
File metadata
- Download URL: rewind_reward_pytorch-0.0.10-py3-none-any.whl
- Upload date:
- Size: 5.9 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 |
749eb0a0bb15f80a8ddfc40e07dde09d1fc632ad57032cb7fde52c4d4ab9c111
|
|
| MD5 |
8f7c561c752c8c321d0c50527b72f816
|
|
| BLAKE2b-256 |
8639d24aa76d566b7874073530c90de5cf2c6de03e7a8b3517d959fe7d779056
|