function buildMLPModel(inputShape, kernelRegularizer, dropoutRate) {
  const model = tf.sequential();
  model.add(tf.layers.flatten({inputShape}));
  model.add(
      tf.layers.dense({units: 32, kernelRegularizer, activation: 'relu'}));
  if (dropoutRate > 0) {
    model.add(tf.layers.dropout({rate: dropoutRate}));
  }
  model.add(tf.layers.dense({units: 1}));
  return model;
}
Build a GRU model for the temperature-prediction problem.

@param {tf.Shape} inputShape Input shape (without the batch dimenson).
@param {tf.regularizer.Regularizer} kernelRegularizer An optional
  regularizer for the kernel of the first (hdiden) dense layer of the MLP.
  If not specified, no weight regularization will be included in the MLP.
@param {number} dropoutRate Dropout rate of an optional dropout layer
  inserted between the two dense layers of the MLP. Optional. If not
  specified, no dropout layers will be included in the MLP.
@returns {tf.LayersModel} A TensorFlow.js tf.LayersModel instance.