Skip to main content

Torch Optimizer for constrained optimization problems

Project description

torch_constrained

Steps for development

  • Python >= 3.8

1) Clone the repository with the ssh link

git clone git@github.com:manuel-delverme/constrained_optimization.git

2) venv and requirement installation

install torch manually for your cuda driver https://pytorch.org/get-started/locally/

python -m venv venv
source venv/bin/activate
pip install -r requirements-dev.txt

3) Enable flake for good code checking

pre-commit install
git config --bool flake8.strict true

Style guides

https://google.github.io/styleguide/pyguide.html

https://www.python.org/dev/peps/pep-0008/

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

torch_constrained-0.0.27.tar.gz (5.9 kB view details)

Uploaded Source

Built Distribution

torch_constrained-0.0.27-py3-none-any.whl (6.4 kB view details)

Uploaded Python 3

File details

Details for the file torch_constrained-0.0.27.tar.gz.

File metadata

  • Download URL: torch_constrained-0.0.27.tar.gz
  • Upload date:
  • Size: 5.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.62.1 CPython/3.8.10

File hashes

Hashes for torch_constrained-0.0.27.tar.gz
Algorithm Hash digest
SHA256 79c2a1c74a3bb6036acae2f2dac97915ce9f952056dc7466f1df921e230e6092
MD5 c7bd31e6d259232d43df483048b5f9ea
BLAKE2b-256 c86169a753dfab62e73b71371cb755895b9070bd9fbf4c56a0ad2f3eb04c7905

See more details on using hashes here.

File details

Details for the file torch_constrained-0.0.27-py3-none-any.whl.

File metadata

  • Download URL: torch_constrained-0.0.27-py3-none-any.whl
  • Upload date:
  • Size: 6.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.5.0 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.62.1 CPython/3.8.10

File hashes

Hashes for torch_constrained-0.0.27-py3-none-any.whl
Algorithm Hash digest
SHA256 1e524a9a78f85bbe8f914ba19f47074202cb76950f3fa6efa01beec197ef459b
MD5 d5cf6ace28046410ca5c8beb417f4ce3
BLAKE2b-256 8e0cd95b9c0232e876da5782a7102dd8e898212277367d07bc834356d936f1c6

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