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.
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-0.0.1b17.tar.gz
(14.0 kB
view details)
File details
Details for the file paper-candy-0.0.1b17.tar.gz.
File metadata
- Download URL: paper-candy-0.0.1b17.tar.gz
- Upload date:
- Size: 14.0 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.9.1
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 07380778646ce55299720f8406d70765b36577de308341e675b230d096be190f |
|
| MD5 | fdc29e19707d334ff25040f3addb124e |
|
| BLAKE2b-256 | eee856654d5402f1e9bdd8479508bd1a45c473406ec3d00f0969bacaa333c3bb |
