Algorithm 2. Build a deep Learning model using CXRVN-proposed architecture.

Input $\leftarrow$ Image_COVID-19_Set imds, Generator Layers GeLayers, Discriminator Layers DiLayers

Output $\leftarrow$ Generator GEN, Discriminator DISC

Begin  // Setting up Training options  Options.set(ValidationFrequecy $\leftarrow$ 5)  Options.set(InitialLearnRate ←1e-4)  Options.set(LearnRateSchedule ← Piecewise)  Options.set(MiniBatchSize ←16)  Options.set(MaxEpochs ←50)  GAN $\leftarrow$ LGraph2Net(GeLayers)  DISC $\leftarrow$ LGraph2Net(DiLayers)  // Training GEN and DISC using imds  For i=1: MaxEpochs   batchImgs $\leftarrow$ read(imds,BatchSize)   Imgs $\leftarrow$ Shulfe(batchImgs)   latentIN $\leftarrow$gen(Imgs,GEN)   DPred $\leftarrow$ Forward(DISC, latentIN)   GPred $\leftarrow$ Forward(GEN, latentIN)   DProb $\leftarrow$ Sigmoid(DPred)   GProb $\leftarrow$ Mean(DProb)   Loss $\leftarrow$ CalcLoss(DProb, GProb)   GAN $\leftarrow$ CalcGradients(GAN.Learnables,Loss)   DISC $\leftarrow$ CalcGradients(DISC.Learnables,Loss)  End for End