Neural Network Supervision Platform
Project description
AFS
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.
PROS
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Easy to install and use
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Takes Steps, Epochs, Train & Test Loss, Acc as arguments so you can have all useful metrics in your app
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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.
Installation
Python 3.6+ required to use.
Get the package from PyPi
$ pip install nightwalker
Usage
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.
Arguments
$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.
Suggestions
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
License
BSD 3-Clause Licence
Project details
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