Module treez::autograd [] [src]

Structs

Context

implementation of reverse automatic differentiation

Link
OpAdd

y = a + b; dy/da = 1; dy/db = 1;

OpCos

y = cos(x); dy/dx = -sin(x)

OpExponential

y = ax; dy/dx = ln(a) * ax

OpLog

y = log_base(x); dy/dx = 1/(x*ln(base))

OpMul

y = a*b; dy/da = b; dy/db = a

OpSin

y = sin(x); dy/dx = cos(x)

OpTan

y = tan(x); dy/dx = 1/(cos(x))2

Enums

OpType

Traits

Op

forward Op and gradient interface

Functions

compute_grad

computes dy/dx and other variables as well back propagating from y

fwd_pass

checker for link validity, computes forward values, saves eval order for backward pass in context, and returns ids for input links

init
init_op
init_var