Make PyTorch an optional dependency

Make torch optional (#85)

* Make torch optional

* fix tests

* Review fixes

Flexible trainers

In this release, we improve the trainers section to make them more easily changeable / extendable

First stable version

Merge pull request #46 from feedly/issue/change-dependencies

minimal dependencies

First stable version

add green tests

First stable version

Use find_packages in setup.py

First stable version

Fix bugs and enable first stable version

First stable version

This is a first stable version for Transfer NLP, allowing users to:

Keep track of experiments and enforce reproducible research
Combine custom and open-source code into controlled experiments
Here are a few features available in the release:

Configuring all objects from an experiment using a json file
Running sequential jobs for the same experiment using different sets of parameters (parameter tuning, ablation studies...)
Keep track of your experiments and make them reproducible / incrementally improvable
Allow dynamic re-creation of any instantiated object during training through object factories
Use several basic building blocks: Vocabulary class, PyTorch optimizer, Predictors...
Transfer Learning: use the BasicTrainer to fine-tune pre-trained models to your custom downstream tasks.

Initial Release

V0.0.2

version