human
Solve the following python programming problem given the following code:
# Let's reuse the Linear class
# with a `build` method that we defined above.

class MLP(keras.layers.Layer):
    """Simple stack of Linear layers."""

    def __init__(self):
        super(MLP, self).__init__()
        self.linear_1 = Linear(32)
        self.linear_2 = Linear(32)
        self.linear_3 = Linear(10)

    def call(self, inputs):
        x = self.linear_1(inputs)
        x = tf.nn.relu(x)
        x = self.linear_2(x)
        x = tf.nn.relu(x)
        return self.linear_3(x)

mlp = MLP()

# The first call to the `mlp` object will create the weights.
y = mlp(tf.ones(shape=(3, 64)))

# Weights are recursively tracked.
assert len(mlp.weights) == 6
Given the above code, generate some markdown instructions for it.
assistant
#Here is the Python program you requested.

Layers that own layers
Layers can be recursively nested to create bigger computation blocks.
Each layer will track the weights of its sublayers
(both trainable and non-trainable).