labml-app 0.0.6

No project description provided

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

You can host this on your own. We also have a small AWS instance running. and you are welcome to use it. Please consider using your own installation if you are running lots of experiments.

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:5000/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:5000/api/v1/track?'):
    for i in range(50):
        loss, accuracy = train()
        tracker.save(i, {'loss': loss, 'accuracy': accuracy})