value R6 class

value R6 class

value R6 class

Details

Represents a node in the computational graph with automatic differentiation. Each value object holds data as a matrix, gradient as a matrix of the same dimensions, a backward function, previous nodes, and an optional label.

All data in femtograd uses matrix representation:

• Scalars are 1x1 matrices

• Column vectors are n x 1 matrices

• Row vectors are 1 x n matrices

• Matrices are m x n matrices

This ensures consistent behavior for get_data(), grad(), and hessian().

Public fields

data

Numeric matrix containing the value

grad

Gradient matrix (same dimensions as data), initially zeros

backward_fn

A function that performs the backward pass (gradient computation)

prev

A list of previous nodes in the computational graph

label

Optional character label for debugging (default: "")

Methods

Public methods

• value$new()

• value$clone()

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Method new()

Initializes a new value object with the given data, list of children, and optional label.

Usage

value$new(data, children = list(), label = "")

Arguments

data

Numeric value (scalar, vector, or matrix) - will be converted to matrix

children

List of previous nodes in the computational graph (default: empty list)

label

Optional character label for debugging

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Method clone()

The objects of this class are cloneable with this method.

Usage

value$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.