Skip to main content

Torchswarm

A fast implementation of Particle Swarm Optimization using PyTorch

We support

Variants of Particle Swarm Optimization

We support for all kinds of PSO

Bring your own particle

We allow for getting a custom particle with a different velocity update rule, The Class must have the following methods:

  • __init__
  • move
  • update_velocity

How to define your problem.

Create a class by inheriting torchswarm.functions.Function and an evaluate method.

class XSquare(Function):
    def evaluate(self, x):
        return x**2

Contributors:

Metadata

Release files for torchswarm 0.0.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for torchswarm 0.0.1
File Interpreter ABI Platform
torchswarm-0.0.1-py3-none-any.whl Python 3 none any Details

Release files / torchswarm-0.0.1-py3-none-any.whl

Download URL torchswarm-0.0.1-py3-none-any.whl
Size 6.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
006adb65d21cc3173123298e142fbccf613ae616200787b11ecda21cb63ce0a5
BLAKE2b-256 checksum
How to use checksums
0be0f9eeeb3c5806ed3c43a3a4f1cb5d8aa894cd50fed832ddecefca9915aefd
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.8.5

Release history Release notifications | RSS feed

This release

0.0.1 This release

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page