Skip to main content

This package is built on pytorch to avoid some standard steps

Project description


This repo aims to train neural networks with pytorch simple. The data are normalized insede the class. The validation is performed automatically. The output model gets the unscaled data and returns the output unscaled (The scaling is performed inside). This way the user do not interact the scaling,; however the user can select to not use the default scaling and scale the data before the training


Use the package manager pip to install foobar.

pip install simpleTorch


A more detailed example in example_of_usage.ipynb

# X array with inputs in np
# F labels in np
# model is the neural net written in pytorch
import simpleTorch.train_ann
train_ann(model, X, F,plot=True)


Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.



Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for simpleTorch, version 0.0.3
Filename, size File type Python version Upload date Hashes
Filename, size simpleTorch-0.0.3-py3-none-any.whl (8.5 kB) File type Wheel Python version py3 Upload date Hashes View
Filename, size simpleTorch-0.0.3.tar.gz (4.1 MB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page