PyTorch implementation of custom DNC variants

Please see our ICLR 2019 paper on https://openreview.net/forum?id=HyGEM3C9KQ for more details.

Tasks

Supported tasks:

• bAbI
• copy
• repeated copy
• associative recall
• key-value recall
• 2 way key-value recall

Visualization and debugging

Many interesting internal states of the DNC are visualized inside Visdom. Check console output for the port.

Usage

Everything is done by main.py. Use -name to give some path (it will be created if doesn't exists), where the state of the training will be saved. Check out main.py for more information about the flags available.

Most of the trainings can be run by profiles:

./main.py -name <train dir> -profile babi

Supported profiles: babi, repeat_copy, repeat_copy_simple, keyvalue, keyvalue2way, associative_recall.

If you want to train a pure DNC, use add "dnc" to the profile:

./main.py -name <train dir> -profile babi,dnc

For other options, see main.py.

DNC variants

The variant of DNC can be specified as a profile. Supported variants: dnc, dnc-msd, dnc-m, dnc-s, dnc-d, dnc-md, dnc-ms, dnc-sd.

Reusing the code

The DNC is implemented as a single file (Models/DNC.py) depending only on torch. You should be able to reuse it very easily. Please check main.py for details on its interface.

Dependencies

PyTroch (1.0), Python 3. Others can be installed by running pip3 -r requirements.txt.

License

The software is under Apache 2.0 license. See http://www.apache.org/licenses/LICENSE-2.0 for further details.