Skip to main content

Deeplearning framework for PyTorch

Project description

https://travis-ci.com/neurallayer/fos.svg?branch=master

Introduction

FOS is a Python framework that makes it easy to develop neural network models in PyTorch. Some of its main features include:

  • Less boilerplate code required, see also the example below.
  • Lightweight and no magic under the hood that might get in the way.
  • You can extend Fos using common OO patterns.
  • Get the insights you need into the performance of the model.

Installation

You can install FOS using pip:

pip install fos

Or alternatively from the source:

python setup.py install

Fos requires Python 3.6 or higher.

Usage

Training a model, requires just a few lines of code. First create the model, optimizer and loss function that you want to use, using normal PyTorch code:

model = resnet18()
optim = Adam(model.parameters())
loss = F.binary_cross_entropy_with_logits

Then create the FOS workout that will take care of the training and output:

workout = Workout(net, loss, optim)

And we are ready to start the training:

workout.fit(train_data, valid_data, epochs=5)

Examples

You can find several example Jupyter notebooks here

You can also run them on Google Colab directly:

  • Basic https://colab.research.google.com/github/neurallayer/fos/blob/master/examples/basic_fos.ipynb
  • MINST https://colab.research.google.com/github/neurallayer/fos/blob/master/examples/mnist_fos.ipynb
  • Inputs https://colab.research.google.com/github/neurallayer/fos/blob/master/examples/inputs_fos.ipynb
  • Tensorboard https://colab.research.google.com/github/neurallayer/fos/blob/master/examples/tensorboard_fos.ipynb

Contribution

If you want to help out, we appreciate all contributions. Please see the contribution guidelines for more information.

As always, PRs are welcome :)=

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 fos, version 1.0.0
Filename, size File type Python version Upload date Hashes
Filename, size fos-1.0.0-py3-none-any.whl (18.3 kB) File type Wheel Python version py3 Upload date Hashes View
Filename, size fos-1.0.0.tar.gz (17.5 kB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring DigiCert DigiCert EV certificate Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page