let yActual = []
let yResults = []
// Looping over each batch in the array of all of the test batches
for (let i = 0; i < testDataXs.length - 1; i++) {
  // Build the input tensor
  const xs = tf.tensor2d(testDataXs[i])

  // Each prediction makes a series of tensors that build up over time and take up lots of memory.
  // tf.tidy cleans up all the extra tensors after each run to keep the predictions coming quickly!
  tf.tidy(() => {
    // This is where you use the model to predict the outputs on the previously unseen data.
    const preds = model.predict(xs)
    // Keeps the predictions in order due to asynchronisity
    const y_vals = preds.dataSync()
    // Build actual//expected output array
    testDataYs[i].forEach(elem => {
      yActual.push(elem[0])
    })
    // Build predicted results array
    y_vals.forEach(elem => {
      yResults.push(elem)
    })
  })
}
// Build a final results array to graph using whichever tool you prefer!
const fullResults = yActual.map((item, j) => {
  return [item, yResults[j]]
})