cg_opr

symbol, operation performed by the node.

call

list of symbols, gradients functions of the input nodes that are consumed by the operation in argument <code>call</code>.

grads

list of cg_node objects, the nodes that are consumed by the operation in argument <code>call</code>.

args

character scalar, name of the node (optional). In case argument <code>name</code> is missing, the node is tried to be added to the graph under an auto-generated name.

name

Add an operation node to the graph.

Allows to create, evaluate, and differentiate computational graphs in R. A computational graph is a graph representation of a multivariate function decomposed by its (elementary) operations. Nodes in the graph represent arrays while edges represent dependencies among the arrays. An advantage of expressing a function as a computational graph is that this enables to differentiate the function by automatic differentiation. The 'cgraph' package supports various operations including basic arithmetic, trigonometry operations, and linear algebra operations. It differentiates computational graphs by reverse automatic differentiation. The flexible architecture of the package makes it applicable to solve a variety of problems including local sensitivity analysis, gradient-based optimization, and machine learning.

cg_opr: Add Operation

Description

Arguments

Value

Details