const model = tf.sequential();

// Add layers to the model
model.add(tf.layers.dense({
    inputShape: [512],
    activation: 'sigmoid',
    units: 2,
}));

model.add(tf.layers.dense({
    inputShape: [2],
    activation: 'sigmoid',
    units: 2,
}));

model.add(tf.layers.dense({
    inputShape: [2],
    activation: 'sigmoid',
    units: 2,
}));

// Compile the model
model.compile({
    loss: 'meanSquaredError',
    optimizer: tf.train.adam(.06), // This is a standard compile config
});