Neural Network Supervision Platform
nightwalker is a Python based library, that helps Deep / Machine Learning specialists to track their models during training without accessing server, and getting notifications full of their desired information via nightwalker App.
Easy to install and use
Takes Steps, Epochs, Train & Test Loss, Acc as arguments so you can have all useful metrics in your app
No registration required, just take the unique code after walker.UID generates it for you, and share it with any number of co-workers to add the model to their apps
Used Frameworks & Libraries
AFS is built totally on Python & Node.JS.
Python 3.6+ required to use.
Get the package from PyPi
$ pip install nightwalker
Import the nightwalker and reach 'walker' function.
Define the walker function inside the training loop, and pass the arguments.
$ from nightwalker import walker $ walker(arg1, arg2)
After executing the training loop, the library will generate and print unique id for you, by which you'll then verify your session within the app.
It'll look like this:
$ Your unique ID is --- 1sy45kd9
Add new model to your app using the generated unique id.
$iteration argument is for counting iterations. type = number. $itercount argument is basically a divider, for every how many iterations do you need to send the metric update. type = number. $maxiter is a maximum of iterations, after which the model finishes training. type = number. $epoch counts epochs. type = number. $maxepoch is a maximum number of epochs, after which nightwalker will decide the model had finished training. $testloss takes test loss as a metric. type = number. $trainloss takes validation loss as a metric. type = number. $acc takes accuracy as a metric. type = number.
In case you have any suggestions how to improve the app and library functionalities for you, please feel free to open new Issue, or contact us at CONTACT@SYSTEMCORP.AI
BSD 3-Clause Licence
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