Dali Visualizer

Provides a visualization web frontend for the Dali automatic differentiation library. Allows you to see a model optimize in real time, see the predictions, and collect your results into one window.

Dependencies

• Python 3
• Redis
• Dali

Installation

To run this visualizer you need to build the javascript files, launch redis, and start a python server that uses tornado. To install the dependencies for Javascript and Python run these commands:

pip3 install -r requirements.txt
cd dali-visualizer
npm install
npm install -g gulp
npm install -g bower
bower install
gulp

Run visualizer

Start the server from top-level directory:

./run.sh

And now head to localhost:8000!

Running with supervisor on Fedora Server

DISCLAIMER: Setup described below is insecure. Anybody who is willing to write a nice write up on setting it up in a secure manner, please submit a pull requrest.

First install supervisor:

    sudo yum install supervisor

Example configuration might look like this:

[supervisord]
logfile=/home/mers/.supervisord/supervisord.log
logfile_maxbytes=50MB
logfile_backups=10
loglevel=info
pidfile=/home/mers/.supervisord/supervisord.pid

[rpcinterface:supervisor]
supervisor.rpcinterface_factory = supervisor.rpcinterface:make_main_rpcinterface

[unix_http_server]
file=/var/run/supervisor.sock

[supervisorctl]
serverurl=unix:///var/run/supervisor.sock

[program:redis]
command=redis-server
autostart=true
autorestart=true
redirect_stderr=true
stdout_logfile=/var/log/redis.log

[program:dali_visualizer]
command=python3 /home/mers/dali-visualizer/run_server.py
redirect_stderr=true
stdout_logfile=/var/log/dali_visualizer.log
directory=/home/mers/dali-visualizer

To now you can do the following

    # to run the supervisor
    sudo systemctl start supervisor
    # to run supervisor as start of system
    sudo systemctl enable supervisor
    # verify everything is running
    sudo supervisorctl status

Forward the ports:

    sudo firewall-cmd --zone=FedoraServer --add-forward-port=port=80:proto=tcp:toport=8000
    sudo firewall-cmd --zone=FedoraServer --add-forward-port=port=6379:proto=tcp:toport=6379

Usage examples

Named Entity Recognition

an LSTM predicting Named Entities in text

visualizer->throttled_feed(seconds(5), [&word_vocab, &label_vocab, &minibatch, &model]() {
    // choose an example
    auto example = std::get<0>(minibatch[utils::randint(0, minibatch.size()-1)]);
    // predict the result
    auto prediction = model.predict(example);
    // convert the input from indices back to text
    auto input_sentence = make_shared<visualizable::Sentence<float>>(word_vocab.decode(example));
    // convert the prediction from indices to labels
    auto decoded = label_vocab.decode(prediction);

    // visualize text and labels as a "parallel sentence"
    auto psentence = visualizable::ParallelSentence<REAL_t>(
        input_sentence,
        make_shared<visualizable::Sentence<REAL_t>>(decoded)
    );
    return psentence.to_json();
});