Class GradientDef

java.lang.Object
com.google.protobuf.AbstractMessageLite
com.google.protobuf.AbstractMessage
com.google.protobuf.GeneratedMessageV3
org.tensorflow.proto.GradientDef
All Implemented Interfaces:
Message, MessageLite, MessageLiteOrBuilder, MessageOrBuilder, Serializable, GradientDefOrBuilder
public final class GradientDef extends GeneratedMessageV3 implements GradientDefOrBuilder
GradientDef defines the gradient function of a function defined in
a function library.
A gradient function g (specified by gradient_func) for a function f
(specified by function_name) must follow the following:
The function 'f' must be a numerical function which takes N inputs
and produces M outputs. Its gradient function 'g', which 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.
Protobuf type tensorflow.GradientDef
See Also: