A library for providing a simple interface to create new metrics and an easy-to-use toolkit for metric computations and checkpointing.
Project description
TorchEval
a library that contains a rich collection of predefined PyTorch model metrics, a simple interface to create new metrics, and a toolkit to facilitate metric computation in distributed training and capabilities for snapshotting metric states.
Installing TorchEval
Requires Python >= 3.7.
From pip:
pip install torcheval
Contributing
We welcome PRs! See the CONTRIBUTING file.
License
TorchEval is BSD licensed, as found in the LICENSE file.
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
torcheval-nightly-2022.8.8.tar.gz
(38.3 kB
view hashes)
Built Distribution
Close
Hashes for torcheval-nightly-2022.8.8.tar.gz
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | dd246f637806673cd8187ed384d2eff39a7f253df8c4bbf513b3e0257f3bf08b |
|
| MD5 | ce3e99f174e6b6b60b70f26d96ea3105 |
|
| BLAKE2b-256 | 117e7f7fd3367815c65cc046bf8e4f2e22ebd95314eb6072cfca071a51c78e1d |
Close
Hashes for torcheval_nightly-2022.8.8-py3-none-any.whl
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 88048ac58c94f5effd25d83a89394a22938af9282572a3bc1a3705b7c3942210 |
|
| MD5 | 868c5d5f4223977931a8534d93886f83 |
|
| BLAKE2b-256 | 636c5c0c65ce91f9f96d6dee5a8867fccd5401d7dd81843ad011fb8508c48c7d |
