Function getModel

intent-classifier/training/intent_model.js:32–50

* Returns a new ready-to-train tf.Model that classifies 512 dimensional vectors * into one of labels.length categories. * * The intended use is for the inputs to be embeddings from the universal * sentence encoder and labels to be the categories we want to classify those * sentence into. * *

(labels)

 * @return {tf.Model} the model instance
 */
function getModel(labels) {
  const NUM_CLASSES = labels.length;
  const EMBEDDING_DIMS = 512;

  const model = tf.sequential();
  model.add(tf.layers.dense({
    inputShape: [EMBEDDING_DIMS],
    units: NUM_CLASSES,
    activation: 'softmax',
  }));

  model.compile({
    optimizer: 'adam',
    loss: 'categoricalCrossentropy',
    metrics: ['accuracy'],
  });

  return model;
}

module.exports = {
  getModel,