Consider a two$-$layered neural network $y=(W^{(B)}(W^{(A)}x)).$ Let $h=(W^{(A)}x)$ denote

$1$ point

the hidden layer representation. $W^{(A)}$ and $W^{(B)}$ are arbitrary weights. Which of the following statement$($s$)$ is$/$are true? Note: $gra{d}_g(f)$ denotes the gradient of $f$ w$.$r$.$t $g.$

$gra{d}_h(y)$ depends on $W^{(A)}.$

$gra{d}_{W^{(A)}}(y)$ depends on $W^{(B)}.$

$gra{d}_{W^{(A)}}(h)$ depends on $W^{(B)}.$

$gra{d}_{W^{(B)}}(y)$ depends on $W^{(A)}.$