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Project description
Mobile first web app to monitor PyTorch & TensorFlow model training
Relax while your models are training instead of sitting in front of a computer
This is an open-source library to push updates of your ML/DL model training to mobile. Here's a sample experiment
Notable Features
- Mobile first design: web version, that gives you a great mobile experience on a mobile browser.
- Model Gradients, Activations and Parameters: Track and compare these indicators independently. We provide a separate analysis for each of the indicator types.
- Summary and Detail Views: Summary views would help you to quickly scan and understand your model progress. You can use detail views for more in-depth analysis.
- Track only what you need: You can pick and save the indicators that you want to track in the detail view. This would give you a customised summary view where you can focus on specific model indicators.
- Standard ouptut: Check the terminal output from your mobile. No need to SSH.
📚 How to track experiments?
How to run app locally?
Install the PIP package
pip install labml-app
Start the server
labml app-server
Set the web api url to http://localhost:5005/api/v1/track? when you run experiments.
You can also set this on .labml.yaml.
from labml import tracker, experiment
with experiment.record(name='sample', token='http://localhost:5005/api/v1/track?'):
for i in range(50):
loss, accuracy = train()
tracker.save(i, {'loss': loss, 'accuracy': accuracy})
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