Domain Attention Mixing Network: tool for domain adaptation
Project description
Domain Attention Mixing Network(DAMN)
Method
Citation
@article{tilk2021damn,
title={Domain Attention Mixing Network},
author={Bence Tilk},
journal={GitHub: https://github.com/tilkb/damn},
year={2021}
}
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pytorch_damn-0.5.4.tar.gz
(4.2 kB
view details)
Built Distribution
File details
Details for the file pytorch_damn-0.5.4.tar.gz
.
File metadata
- Download URL: pytorch_damn-0.5.4.tar.gz
- Upload date:
- Size: 4.2 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.22.0 setuptools/51.1.1 requests-toolbelt/0.9.1 tqdm/4.55.0 CPython/3.8.5
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | b912e34a6f3aeea19d29ece346819488bd993adab57bc9f601f0caca42986cd4 |
|
MD5 | ef5c7958874be17bdf3e80cd0c064539 |
|
BLAKE2b-256 | a775cbd8027d254c1e40a6761c53faef12657eb387186d32cb030351fc64ee03 |
File details
Details for the file pytorch_damn-0.5.4-py3-none-any.whl
.
File metadata
- Download URL: pytorch_damn-0.5.4-py3-none-any.whl
- Upload date:
- Size: 5.2 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.3.0 pkginfo/1.6.1 requests/2.22.0 setuptools/51.1.1 requests-toolbelt/0.9.1 tqdm/4.55.0 CPython/3.8.5
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | c628830a7060f0f179acccad6afa820508e42900be239056f9b48380d5dd9da2 |
|
MD5 | 23e753ffeeac0f103dc4ff74a7c4239b |
|
BLAKE2b-256 | ef5d314a2c2279d87fec01268144098ea0d6152692841434cd7c89a0c9c8e8be |