Skip to content
Memory, Attention and Composition (MAC) Network for CLEVR implemented via KnetLayers
Jupyter Notebook Julia
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
configs
data
models
plots
src
.gitignore
LICENSE
Manifest.toml
Project.toml
README.md
benchmark.jl
demoprepare.jl
demosetup.jl
extract_features.jl
job.sh
preprocess.jl
train.jl
trainsetup.jl
visualize.ipynb

README.md

Compositional Attention Networks for Machine Reasoning

Knet implementation of the paper "Compositional attention networks for machine reasoning." Hudson, Drew A., and Christopher D. Manning.

Running Demo

Open visualize.ipynb notebook with jupyter to see the demo.

Getting Data

You have two options for the data setup.

a) Raw Data

1-Download CLEVR dataset to data/ folder.

2-Process the CLEVR data:

julia trainsetup.jl data/CLEVR_v1.0

b) Processed Data

1-Download preprocessed data:

julia trainsetup.jl

Training

Below configuration can achieve %98.27 accuracy on CLEVR dataset

julia train.jl src/main.jl configs/config2.jl
You can’t perform that action at this time.