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-1.1.tar.gz
(4.3 kB
view hashes)
Built Distribution
Close
Hashes for losswise-1.1-py2.py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 836892ed3708de5aa4656fd15f2bf4bde82455125d6e20cb8f41891fa63c3e07 |
|
MD5 | 065d5b6b0906f0b1dcc985b0750f769a |
|
BLAKE2b-256 | 8fa2800d34074126d41a4da0a23eeffbd15bbbd4a78cb6cd55ae4f82b9be8225 |