A minimal and simple machine learning experiment module for PyTorch.
Project description
torchplate
: Minimal Experiment Workflows in PyTorch
An extremely minimal and simple experiment module for machine learning in PyTorch.
In addition to abstracting away the training loop, we provide several abstractions to improve the efficiency of machine learning workflows with PyTorch.
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
torchplate-0.0.1.tar.gz
(3.6 kB
view details)
Built Distribution
File details
Details for the file torchplate-0.0.1.tar.gz
.
File metadata
- Download URL: torchplate-0.0.1.tar.gz
- Upload date:
- Size: 3.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.8.5
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3b3a525b97a00ba0edafe9ac98413262f3edabccd351501424c36749961898c9 |
|
MD5 | 9810b2c0c60d17340123b6114d864078 |
|
BLAKE2b-256 | 1c0cc313497fb6ee217261af62c74c6f720265de1efdc28dbfaec22caa959233 |
File details
Details for the file torchplate-0.0.1-py3-none-any.whl
.
File metadata
- Download URL: torchplate-0.0.1-py3-none-any.whl
- Upload date:
- Size: 5.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.1 CPython/3.8.5
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8659ee21d9bef07b380560ffbbc1b894d92705e6f6b3a940871606cda931eb45 |
|
MD5 | 70d50a9d59a8dfb94c7ca76d9de6754e |
|
BLAKE2b-256 | dc2ec2c819cb413c077436d1c1e5c0ca1c8c012ae755ebbc65c55296b0b5b0b4 |