Skip to main content

A loosely coupled lightweight framework for deep learning papers.

Project description

PaperCandy is a loosely coupled lightweight framework for deep learning papers. It provides a series of auxiliary tools for rapid rebuilding and writing papers, including universal data loader, and automatically generating network structure and training process diagram. So far support PyTorch as the only front-end framework.

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

paper-candy-1.0.1b7.tar.gz (15.3 kB view details)

Uploaded Source

File details

Details for the file paper-candy-1.0.1b7.tar.gz.

File metadata

  • Download URL: paper-candy-1.0.1b7.tar.gz
  • Upload date:
  • Size: 15.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.1

File hashes

Hashes for paper-candy-1.0.1b7.tar.gz
Algorithm Hash digest
SHA256 805d6df8763eb0df2a4a2acf488593924920e06138336905526f0deed5a64557
MD5 9515dc9e051a4a91b0a2c94e81945ab5
BLAKE2b-256 a7c442ceb85d5f3b575dc8cf032fbbb5f90cf3788af649dd20d8f6e1b5b271e3

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