Mobile first web app to monitor PyTorch & TensorFlow model training

Relax while your models are training instead of sitting in front of a computer

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This is an open-source library to push updates of your ML/DL model training to mobile. [Here's a sample experiment](https://app.labml.ai/run/39b03a1e454011ebbaff2b26e3148b3d) You can host this on your own. We also have a small [AWS instance running](https://app.labml.ai). 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?](https://github.com/labmlai/labml) ### How to run app locally? Install the PIP package ```sh pip install labml-app ``` Start the server ```sh 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`](https://github.com/labmlai/labml/blob/master/guides/labml_yaml_file.md). ```python 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}) ```