Q$2$ Which of the following is true about Layer normalization $($Layer$-$Norm$)?$

a$)$ In LayerNorm the mean is computed over highly important features

b$)$ LayerNorm is suitable for sequence models

c$)$ LayerNorm is normalization of adjacent neural network layers for fast training

d$)$ LayerNorm is a non$-$linear transformation to center the dataset around the origin

e$)$ LayerNorm is averaging of values in same mini$-$batch