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Dali Visualizer

Babi visual

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

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

NER visual 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();
});