org.deeplearning4j.util

Class ConvolutionUtils

java.lang.Object

org.deeplearning4j.util.ConvolutionUtils

public class ConvolutionUtils
extends java.lang.Object

Convolutional shape utilities

Method Summary

Modifier and Type	Method and Description
static int[]	getHeightAndWidth(int[] shape) Get the height and width for an image
static int[]	getHeightAndWidth(NeuralNetConfiguration conf) Get the height and width from the configuration
static int[]	getOutputSize(org.nd4j.linalg.api.ndarray.INDArray inputData, int[] kernel, int[] strides, int[] padding, ConvolutionMode convolutionMode) Get the output size (height/width) for the given inpud data and CNN configuration
static int[]	getSameModeTopLeftPadding(int[] outSize, int[] inSize, int[] kernel, int[] strides) Get top and left padding for same mode only.
static int	numChannels(int[] shape) Returns the number of feature maps for a given shape (must be at least 3 dimensions
static int	numFeatureMap(NeuralNetConfiguration conf)
static void	validateCnnKernelStridePadding(int[] kernelSize, int[] stride, int[] padding) Perform validation on the CNN layer kernel/stride/padding.

Methods inherited from class java.lang.Object

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

Method Detail

getOutputSize

public static int[] getOutputSize(org.nd4j.linalg.api.ndarray.INDArray inputData,
                                  int[] kernel,
                                  int[] strides,
                                  int[] padding,
                                  ConvolutionMode convolutionMode)

Get the output size (height/width) for the given inpud data and CNN configuration

Parameters:

inputData - Input data

kernel - Kernel size (height/width)

strides - Strides (height/width)

padding - Padding (height/width)

Returns:

Output size: int[2] with output height/width

getSameModeTopLeftPadding

public static int[] getSameModeTopLeftPadding(int[] outSize,
                                              int[] inSize,
                                              int[] kernel,
                                              int[] strides)

Get top and left padding for same mode only.

Parameters:

outSize -

inSize -

kernel -

strides -

Returns:

getHeightAndWidth

public static int[] getHeightAndWidth(NeuralNetConfiguration conf)

Get the height and width from the configuration

Parameters:

conf - the configuration to get height and width from

Returns:

the configuration to get height and width from

numFeatureMap

public static int numFeatureMap(NeuralNetConfiguration conf)

Parameters:

conf - the configuration to get the number of kernels from

Returns:

the number of kernels/filters to apply

getHeightAndWidth

public static int[] getHeightAndWidth(int[] shape)

Get the height and width for an image

Parameters:

shape - the shape of the image

Returns:

the height and width for the image

numChannels

public static int numChannels(int[] shape)

Returns the number of feature maps for a given shape (must be at least 3 dimensions

Parameters:

shape - the shape to get the number of feature maps for

Returns:

the number of feature maps for a particular shape

validateCnnKernelStridePadding

public static void validateCnnKernelStridePadding(int[] kernelSize,
                                                  int[] stride,
                                                  int[] padding)

Perform validation on the CNN layer kernel/stride/padding. Expect 2d int[], with values > 0 for kernel size and stride, and values >= 0 for padding.

Parameters:

kernelSize - Kernel size array to check

stride - Stride array to check

padding - Padding array to check