Monitor deep learning model training and hardware usage from your mobile phone.
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Install the LabML App
# Install the app
pip install labml-app
# Start the server
labml app-server
Run an experiment
from labml import tracker, experiment
# set app url to the url of labml app-server
# i.e. http://localhost:5005/api/v1/track
with experiment.record(name='sample', exp_conf={}, app_url=''):
for i in range(50):
loss = train()
tracker.save(i, {'loss': loss})
Track experiment results, hardware usage, and performance metrics in real-time from any device, including mobile and laptops.
Add just two lines of code to start tracking metrics like loss and accuracy, with built-in support for distributed training across multiple machines.
Create custom charts and compare performance across multiple runs, offering detailed insights into your experiments' progress.
Track hyperparameters, Git commits, and other experiment details, ensuring full transparency and reproducibility for your projects.
