Official Losswise library for Python
Project description
This is the official Losswise Python library. This library allows for server-side integration of Losswise.
Installation
The library can be installed using pip:
pip install losswise
Getting Started
First create an account on the Losswise website (https://losswise.com). This will automatically generate a unique API key.
Typical usage usually looks like this:
import random import losswise # replace with your own api key losswise.set_api_key('your_api_key') # replace with a string that identifies your model session = losswise.Session(tag='my_dilated_convnet', max_iter=10, data={'num_params': 10000000}) # create empty graph for loss, keep track of minima here hence kind='min' graph = session.graph(title='loss', kind='min') # track artificial loss over time for x in xrange(10): train_loss = 1. / (0.1 + x + 0.1 * random.random()) test_loss = 1.5 / (0.1 + x + 0.2 * random.random()) graph.append(x, {'train_loss': train_loss, 'test_loss': test_loss}) # mark session as complete session.done()
You can then view the visualization results on your dashboard.
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
losswise-3.4.tar.gz
(6.1 kB
view hashes)
Built Distribution
Close
Hashes for losswise-3.4-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 1ef5996ca49480c5dc25b8abc48eb605c0fc5fd43952105d3650ce74d81fc342 |
|
MD5 | e27dce735f5da97fe55c51daf12ae816 |
|
BLAKE2b-256 | 37d9edc14dd35b2d2fd2de727496b24db8f9b8599d84acbb4bc6fd4d045f4ba5 |