richard:

“The gradient you pass to output.backward() is the “gradient of the output”.


sorry, I don’t quite understand the gradient of output?
the gradient of output w.r.t. model parameters = d(out)/d(param) = lim(Δout)/(Δparam).
the gradient of output = d(out)?  or   Δout ?   or  backward propagation errors?
@richard @jpeg729  can u explain it mathmatically?