Example backpropogation calculation for intuition
# f(x, y) = (x + sigma(y)) / (sigma(x) + (x + y)^2)
x = 3 # example values
y = - 4
# forward pass
sigy = 1.0 / (1 + math .exp (- y )) # sigmoid in numerator #(1)
num = x + sigy # numerator #(2)
sigx = 1.0 / (1 + math .exp (- x )) # sigmoid in denominator #(3)
xpy = x + y #(4)
xpysqr = xpy ** 2 #(5)
den = sigx + xpysqr # denominator #(6)
invden = 1.0 / den #(7)
f = num * invden # done! #(8)
# backprop f = num * invden
dnum = invden # gradient on numerator #(8)
dinvden = num #(8)
# backprop invden = 1.0 / den
dden = (- 1.0 / (den ** 2 )) * dinvden #(7)
# backprop den = sigx + xpysqr
dsigx = (1 ) * dden #(6)
dxpysqr = (1 ) * dden #(6)
# backprop xpysqr = xpy**2
dxpy = (2 * xpy ) * dxpysqr #(5)
# backprop xpy = x + y
dx = (1 ) * dxpy #(4)
dy = (1 ) * dxpy #(4)
# backprop sigx = 1.0 / (1 + math.exp(-x))
dx += ((1 - sigx ) * sigx ) * dsigx # Notice += !! See notes below #(3)
# backprop num = x + sigy
dx += (1 ) * dnum #(2)
dsigy = (1 ) * dnum #(2)
# backprop sigy = 1.0 / (1 + math.exp(-y))
dy += ((1 - sigy ) * sigy ) * dsigy #(1)
# done! phew