A list of Tensor objects. a list of input tensors of size N + M;
Tout
A list of tf.DTypes that has length >= 1.
the type list for the input list.
f
A function decorated with @Defun.
The function we want to compute the gradient for.
The function 'f' must be a numerical function which takes N inputs and
produces M outputs. Its gradient function 'g', which is computed by
this SymbolicGradient op is a function taking N + M inputs and
produces N outputs.
I.e. if we have
(y1, y2, ..., y_M) = f(x1, x2, ..., x_N),
then, g is
(dL/dx1, dL/dx2, ..., dL/dx_N) = g(x1, x2, ..., x_N,
dL/dy1, dL/dy2, ..., dL/dy_M),
where L is a scalar-value function of (x1, x2, ..., xN) (e.g., the
loss function). dL/dx_i is the partial derivative of L with respect
to x_i.
(Needs some math expert to say the comment above better.)
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-01-23 UTC."],[],[]]