var model = keras.Sequential(new List<ILayer>()
            {
                keras.layers.InputLayer(5),
                keras.layers.Dense(1)
            });
var x = tf.ones((3, 5));
var y = tf.zeros(3);
using (var tape = tf.GradientTape())
{
    var y_pred = model.Apply(x);
    var loss = keras.losses.MeanSquaredError().Call(y, y_pred);
    var gradient = tape.gradient(loss, model.TrainableWeights);
    foreach (var g in gradient)
    {
        Console.WriteLine(g);
    }
}