Skip to main content

Differentiable Fuzzy Logic operators for

Project description

torch-norms

t-norms in PyTorch

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

torchnorms-1.4.1.tar.gz (6.7 kB view details)

Uploaded Source

Built Distribution

torchnorms-1.4.1-py3-none-any.whl (17.4 kB view details)

Uploaded Python 3

File details

Details for the file torchnorms-1.4.1.tar.gz.

File metadata

  • Download URL: torchnorms-1.4.1.tar.gz
  • Upload date:
  • Size: 6.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.3 pkginfo/1.8.2 requests/2.13.0 requests-toolbelt/0.9.1 tqdm/4.23.3 CPython/3.6.9

File hashes

Hashes for torchnorms-1.4.1.tar.gz
Algorithm Hash digest
SHA256 5d043ae8e9f43e6ae930727b2aa4d2b6e8f0eb79dc9e30a5de098f8b5bfba342
MD5 cda900d4aa1af0439bbf9b0c76d8df29
BLAKE2b-256 f92e54a51c4c8b8f892d33344cbae130d7d433df26b6693b8505afab7a3c68a1

See more details on using hashes here.

File details

Details for the file torchnorms-1.4.1-py3-none-any.whl.

File metadata

  • Download URL: torchnorms-1.4.1-py3-none-any.whl
  • Upload date:
  • Size: 17.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.3 pkginfo/1.8.2 requests/2.13.0 requests-toolbelt/0.9.1 tqdm/4.23.3 CPython/3.6.9

File hashes

Hashes for torchnorms-1.4.1-py3-none-any.whl
Algorithm Hash digest
SHA256 84e6db62003ccfa7ca21d3f8069e006d84f60653c94d202c48633b52b4c2a75b
MD5 95ce772866de862da2882e47be5edf36
BLAKE2b-256 0ccd8bd5a28471271862d1b746648ac70d234dbf6940b8992573b96fb078469e

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page