Metadata-Version: 2.1
Name: fos
Version: 0.5.1
Summary: Deeplearning framework for PyTorch
Home-page: https://github.com/quanta/fos
Author: FOS Authors
Author-email: peter@jbaron.com
License: UNKNOWN
Description: Introduction
        ============
        **FOS** is a Python framework that makes it easier to develop neural network models 
        in PyTorch. Some of the 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 when you get stuck.
        
        
        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 steps. First create the model, optimizer and 
        loss function that you want to use using plain PyTorch objects::
        
           predictor = resnet18()
           optim     = Adam(predictor.parameters())
           loss      = F.binary_cross_entropy_with_logits
        
        Then create the FOS classes that will take care of the training and output::
        
           model   = Supervisor(predictor, loss)
           meter   = NotebookMeter()
           trainer = Trainer(model, optim, meter)
        
        And we are ready to start the training::
        
           trainer.run(train_data, valid_data, epochs=5)
        
        
        Examples
        ========
        You can find several example Jupyter notebooks `here <https://github.com/innerlogic/fos/examples>`_, 
        or even more convenient try them directly in a Google Colab environment:
        
            1) Basic Example
            2) MNIST example
        
        
        Contribution
        ============
        If you want to help out, we appreciate all contributions. 
        Please see the [contribution guidelines]() for more information.
        
        As always, PRs are welcome :)= 
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.5
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/x-rst
