deepboof.forward

Interface FunctionLinear<T extends Tensor>

All Superinterfaces:

Function<T>

All Known Implementing Classes:

FunctionLinear_F32, FunctionLinear_F64

public interface FunctionLinear<T extends Tensor>
extends Function<T>

Applies a linear (or affine) equation to input array. This is a matrix multiplication operation that is performed between the input vector and their respective weights plus bias.

 y = W*x + b
 

where y is the output, W are the weights, x is the input, and b is the bias.

Method Summary

Modifier and Type	Method and Description
void	forward(T input, T output) Input tensor shape =(N, d[i], ...
int	getNumberOfOutputs() Returns the number of output elements.
void	setParameters(java.util.List<T> parameters) See forward(T, T) for a description of parameters.

Methods inherited from interface deepboof.Function

getOutputShape, getParameters, getParameterShapes, getTensorType, initialize

Method Detail

forward

void forward(T input,
             T output)

Input tensor shape =(N, d[i], ... , d[K])
where N is the number of stacked inputs, d[i] is the number of inputs along dimension i, and K is the dimension of the input space.

Tensor Parameters:
Weight matrix shape=(M,D)
bias shape=(M)
where D is the total number of inputs (Product d[i]) and M is the number of outputs.

NOTE: The tensor parameters' shape has been selected to minimize cache misses during matrix multiplication.

Specified by:

forward in interface Function<T extends Tensor>

Parameters:

input - Tensor with a shape of (N, d[i], ... , d[k])

output - Output tensor with shape (N,M). Modified.

setParameters

void setParameters(java.util.List<T> parameters)

See forward(T, T) for a description of parameters.

Specified by:

setParameters in interface Function<T extends Tensor>

Parameters:

parameters - Weight and bias tensors with shapes (M, D), and (M,), respectively.

getNumberOfOutputs

int getNumberOfOutputs()

Returns the number of output elements. This is the variable M.

Returns:

Number of output elements.