George3d6/agjn5.jl

## agjn5.jl
global const 𝜀=Float32(1e-8) #  a small number prevent from getting NaN  in logs
𝑱d(𝗪d,x,Gz) = -mean(log.(D(𝗪d,x)+𝜀)+log.(1-D(𝗪d,Gz)+𝜀))/2 # Discriminator Loss
𝑱g(𝗪g, 𝗪d, z) = -mean(log.(D(𝗪d,G(𝗪g,z))+𝜀))             # Generator Loss

∇d  = grad(𝑱d) # Discriminator gradient
∇g  = grad(𝑱g) # Generator gradient
	global const 𝜀=Float32(1e-8) # a small number prevent from getting NaN in logs
	𝑱d(𝗪d,x,Gz) = -mean(log.(D(𝗪d,x)+𝜀)+log.(1-D(𝗪d,Gz)+𝜀))/2 # Discriminator Loss
	𝑱g(𝗪g, 𝗪d, z) = -mean(log.(D(𝗪d,G(𝗪g,z))+𝜀)) # Generator Loss

	∇d = grad(𝑱d) # Discriminator gradient
	∇g = grad(𝑱g) # Generator gradient