Consider the neural network given below that is designed for a regression task. There is only one neuron in the output layer. The output of the network is denoted by the scalar variable

r

$.$ The loss function is defined as

L

$=$

$1$

$2$

$($

y

$$

r

$)$

$2$

$,$ where

y

is the true value $($a numeric scalar$)$ of the input data point

x

$.$

The activation function of the last layer is the pass$-$through function, i$.$e$.,$ it lets the input pass through it without any changes. Hence,

r

$=$

z

$3$

$.$

The neural network architecture we consider is as follows:

We pass a single data point and get the quantities shown above. Now, we have to implement backpropagation. Please note that there is a bias of the layer

$3$

:

b

$3$

$.$

Since the activation function is the pass$-$through function, we know that

r

$=$

z

$3$

Hence, we can conclude that

$$

L

$$

r

$=$

$$

L

$$

z

$3$

Please answer the below questions based on the above paragraph.