Observed since 20 Oct, 21:13 UTC
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Agent for Neural Network training supervision
AFS 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 beloved Social Media platforms.
AFS is built totally on Python & Node.JS.
Python 3.6+ required to use.
Get the package from PyPi
$ pip install AFS
Import the AFS and reach 'teller' function. Define the AFS.teller function inside the training loop, and pass the arguments.
$ import AFS as afs
$ afs.teller(arg1, arg2)
Then, reach uID function, and pass the 'yes' string, that will basically create unique id for you, by which you'll then verify your session with the chatbot.
$ afs.uID("yes")
After the execution of the training loop, this line will print unique ID for you that is generated super randomly to minimize the similarities.
It'll look like this:
$ Your unique ID is --- 231409296064663:68137457840134:27374860406350
Copy the unique ID, and text the AFS bot the plain text to verify your session. And, it's all done.
'teller' function takes maximum of 14 arguments. Default values are 0s.
$iteration argument is for counting iterations. type = number.
$distribution argument is basically a divider, for every how many iterations do you need to send the GET request. type = number.
$maxiter is a maximum of iterations, after which the model finishes training. type = number.
$epochdistribution is the same as 'distribution' argument, but for epochs. type = number.
$epoch counts epochs. type = number.
$testloss takes test loss as an information. type = number.
$valloss takes validation loss as an information. type = number.
The API sends the JSON array, that is basically stringified version of combination of dictionaries.
The Flask server is deployed on Heroku, and implemented only in Facebook Messenger for now. Next Social Media Platforms:
BSD 3-Clause Licence
Download counts and popularity will appear here as the collector receives them.
| Version | Published | Direct dependencies | Open version |
|---|---|---|---|
| 5.0 | 13 Jun 2019 | 0 |
This describes our collected data; it is not a security assessment.
Observed since 20 Oct, 21:13 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package:7b1b375530ccc72c4d85b7d16bb8b8849e2b77c74b34be5b2690381b9da4150c