Dynamic-K Activation

Introduction

This repository contains the demo code for the ICCV'19 paper "Adaptive Activation Thresholding: Dynamic Routing Type Behavior for Interpretability in Convolutional Neural Networks".

Download

• Clone the code of DKA from github

    git clone https://github.com/sunyiyou/dynamic-k-activation
    cd dynamic-k-activation

• If you want to train and test a new model instead of just running a demo. Then you may need to include the netdissect module with command below

    git clone --recursive https://github.com/sunyiyou/dynamic-k-activation

Requirements

• Python3.6 Environments

    pip3 install numpy sklearn scipy scikit-image matplotlib easydict torch torchvision

• Places365 dataset. Put it in $PLACES_ROOT and create a soft link by

    mkdir data
    ln -s $PLACES_ROOT data/places365_standard

Note: The repo was written by pytorch-1.0.1. (PyTorch, Torchvision)

Test Network with Dynamic-K Activation

• Test Resnet-d5a

    python3 demo.py

DKA Result

• At the end of the dissection script, a HTML-formatted report will be generated inside result folder that summarizes the interpretable units of the tested network.

Train Network with Dynamic-K Activation

• Run the train script.

    python3 train.py --mark t[K]

The models are stored in 'snapshot' folder. Set $MODELFILE to any snapshotted model.

• Generate Netdissection results.

Specifically, you have to change the folder to "netdissect" and change the "MODEL_FILE" in settings.py. Then you have to download Broaden dataset by the given script and simply run python3 main.py. When finished, set the $ND_RESULT to the path of 'tally.csv' in results folder.

Please see instructions of Netdissect-Lite for more details.

• Then generate DKA results.

    python3 demo.py --mark t[K] --nd_result $ND_RESULT --modelfile $MODELFILE

Reference

If you find the codes useful, please cite this paper

@inproceedings{DKA2019,
  title={Adaptive Activation Thresholding: Dynamic Routing Type Behavior for Interpretability in Convolutional Neural Networks},
  author={Sun, Yiyou and Ravi, Sathya and Singh, Vikas},
  booktitle={International Conference on Computer Vision},
  year={2019}
}