deepboof.impl.forward.standard

Class BaseFunction<T extends Tensor>

java.lang.Object

deepboof.impl.forward.standard.BaseFunction<T>

All Implemented Interfaces:

Function<T>

Direct Known Subclasses:

BaseSpatialWindow, ElementWiseFunction, FunctionBatchNorm_F32, FunctionBatchNorm_F64, FunctionLinear_F32, FunctionLinear_F64

public abstract class BaseFunction<T extends Tensor>
extends java.lang.Object
implements Function<T>

Base class which implements common functionality between all functions

Field Summary

Fields

Modifier and Type	Field and Description
protected int	miniBatchSize Number of inputs in the mini-batch
protected java.util.List<T>	parameters
protected int[]	shapeInput
protected int[]	shapeOutput
protected java.util.List<int[]>	shapeParameters

Constructor Summary

Constructors

Constructor and Description
BaseFunction()

Method Summary

Modifier and Type	Method and Description
abstract void	_forward(T input, T output)
abstract void	_initialize()
abstract void	_setParameters(java.util.List<T> parameters)
void	forward(T input, T output) Performs forward pass of the function on the provided inputs.
int[]	getOutputShape() Returns the output tensor's shape, without the mini-batch dimension.
java.util.List<T>	getParameters() If the parameters have been set, then this returns the list of parameters.
java.util.List<int[]>	getParameterShapes() Returns the shape of input tensors, without the mini-batch dimension.
void	initialize(int... shapeInput) Initializes internal data structures given the shape of the input tensor, minus the stacked input dimension.
void	setParameters(java.util.List<T> parameters) Specifies learnable function parameters, e.g.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface deepboof.Function

getTensorType

Field Detail

shapeInput

protected int[] shapeInput

shapeParameters

protected java.util.List<int[]> shapeParameters

shapeOutput

protected int[] shapeOutput

parameters

protected java.util.List<T extends Tensor> parameters

miniBatchSize

protected int miniBatchSize

Number of inputs in the mini-batch

Constructor Detail

BaseFunction

public BaseFunction()

Method Detail

initialize

public void initialize(int... shapeInput)

Description copied from interface: Function

Initializes internal data structures given the shape of the input tensor, minus the stacked input dimension. For example, an input tensor of shape (B,C,D) might be passed into initialize, while the actual input is (N,B,C,D). N is the number of stacked inputs and is allowed to vary after initialization.

Specified by:

initialize in interface Function<T extends Tensor>

Parameters:

shapeInput - Shape of the input tensor

_initialize

public abstract void _initialize()

setParameters

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

Description copied from interface: Function

Specifies learnable function parameters, e.g. weights for linear functions. This function only needs to be called once each time a parameter has been modified. Must be called before Function.forward(T, T).

NOTE: Reference to the parameters may be saved internally and the tensors should not be modified externally.

Specified by:

setParameters in interface Function<T extends Tensor>

Parameters:

parameters - Tensors containing parameters which are optimized. Not modified.

_setParameters

public abstract void _setParameters(java.util.List<T> parameters)

getParameters

public java.util.List<T> getParameters()

Description copied from interface: Function

If the parameters have been set, then this returns the list of parameters. Otherwise null is returned.

Specified by:

getParameters in interface Function<T extends Tensor>

Returns:

List of parameters or null if they have not been set yet

forward

public void forward(T input,
                    T output)

Description copied from interface: Function

Performs forward pass of the function on the provided inputs.

 Input tensor shape = (N,variable ... )
 - N is the mini-batch size
 - Other dimensions are implementation specific.
 

Specified by:

forward in interface Function<T extends Tensor>

Parameters:

input - Input to the function.

output - Output tensor. Modified.

_forward

public abstract void _forward(T input,
                              T output)

getParameterShapes

public java.util.List<int[]> getParameterShapes()

Description copied from interface: Function

Returns the shape of input tensors, without the mini-batch dimension. Only valid after Function.initialize(int...) has been called.

Specified by:

getParameterShapes in interface Function<T extends Tensor>

Returns:

Expected shapes of input tensors. This data structure may be recycled and is modified on the next call to Function.initialize(int...).

getOutputShape

public int[] getOutputShape()

Description copied from interface: Function

Returns the output tensor's shape, without the mini-batch dimension. Only valid after Function.initialize(int...) has been called.

Specified by:

getOutputShape in interface Function<T extends Tensor>

Returns:

Expected shape of output tensor. This data structure may be recycled and is modified on the next call to Function.initialize(int...).