fos 0.8.0

Deeplearning framework for PyTorch

Introduction

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

• 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 3.5 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, creating plain PyTorch objects:

net   = resnet18()
optim = Adam(predictor.parameters())
loss  = F.binary_cross_entropy_with_logits

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

workout   = Workout(predictor, 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

Contribution

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

As always, PRs are welcome :)=