Question in computer scienceee

Question No: $02$

This is a subjective question, hence you have to write your answer in the Text$-$Fleld given below.

Consider a combined Lenet$-5$ and a single$-$layer RNN based visual captioning system that is trained to generate the sequence of small characters corresponding to ten digits, $0$ to $9.$ For example, an input image of $\text{'}7\text{'}$ will generate the output character sequences $s,e,v,e,$ n$.$ An input image that is not of a digit will generate the output n$,$ o$,$ n$,$ e$.$ Assume one hot representation is used for both input and output.

$($a$)$ What is the minimum number of input nodes and minimum number of output node required in RNN$?$

$($b$)$ Assuming linear combinations of the output of last convolution layer $($after subsampling and unrolling$)$ is used to initialize the RNN hidden layer, how many trainable parameters will be needed, excluding the CNN convolution parameters? Assume $50$ hidden nodes are used in RNN$.$ Show all steps clearly. No attention is used.

$($c$)$ Over how many time steps, does the loss function has to be evaluated during training? $[1]$