$1.$ Assume that a typical CNN has following input channels$(5$x$5$x$3),$ two$(3$x$3$x$3)$ filtervolumes and two$(1$x$1)$ bias. A convolutional layer cross$-$correlates the input and kernels andadds a scalar bias to produce an output. Assume that a zero padding$($P$=1),$ stride of $2$ is appliedto the input volume. ReLU activation function is used on the feature map and then a $2$x$2$ avg.pooling with a stride of $1$ is applied. Illustrate the convolution layer computation to poolingoutput. $[15$M$]$x$1$ x$2$ x$3101001100210002012201012010102010101211012122110220010011012012200222120220$w$00$ w$01$ w$020111-10-1-11-11-1111-10-10-100110-1-1$w$10$ w$11$ w$1211010-1-1-1-111-1-11-11101-1-10-1-1011$b$0$ b$110$