Thank you for repeating yourself three times. It seems like you think that the dual number algebra involves "magic woo numbers." It seems like you haven't really worked through this stuff too much. I would suggest reading some of the resources above, such as the MIT lecture series. The rest of your points I think I have already addressed, though you ignored in your reply - I've said Pytorch does reverse mode diff several times at this point.
fpgamlirfanboy|1 year ago
yup not at all - i just wandered in off the street and knew accidentally that you were talking about non-standard analysis.
> The rest of your points I think I have already addressed
please show me the source line number in pytorch or tensorflow that defines this number
> we add one called "h" with h² = 0!
MikeBattaglia|1 year ago
Here's the documentation: https://pytorch.org/tutorials/intermediate/forward_ad_usage....
> When an input, which we call “primal”, is associated with a “direction” tensor, which we call “tangent”, the resultant new tensor object is called a “dual tensor” for its connection to dual numbers[0].
samatman|1 year ago
What's up with that?
Anyway, here's a forward differentiation package with a file that might interest you
https://github.com/JuliaDiff/ForwardDiff.jl/blob/master/src/...