Python Deep learning Natural language processing
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momohuang

Description

An example for applying FusionNet to Natural Language Inference

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FusionNet for Natural Language Inference

This is an example for applying FusionNet to natural language inference task.
For more details on FusionNet, please refer to our paper:
FusionNet: Fusing via Fully-Aware Attention with Application to Machine Comprehension

Requirements

  • Python (version 3.5.2)
  • PyTorch (0.2.0)
  • spaCy (1.x)
  • NumPy
  • JSON Lines
  • MessagePack

Since package update sometimes break backward compatibility, it is recommended to use Docker, which can be downloaded from here. To enable GPU, nvidia-docker may also needs to be installed.

After setting up Docker, simply perform

docker pull momohuang/fusionnet-docker
to pull the docker file. Note that this may take some time to download. Then we can run the docker image through
docker run -it momohuang/fusionnet-docker
(Only CPU)
or
nvidia-docker run -it momohuang/fusionnet-docker
(GPU-enabled).

Quick Start

pip install -r requirements.txt

bash download.sh

python prepro.py

python train.py

train.py
supports an option
--full_att_type
, where
--full_att_type 0
: standard attention
--full_att_type 1
: fully-aware attention
--full_att_type 2
: fully-aware multi-level attention

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