org.deeplearning4j.util

Class ConvolutionUtils

java.lang.Object

org.deeplearning4j.util.ConvolutionUtils

public class ConvolutionUtils
extends Object

Convolutional shape utilities

Author:

Adam Gibson

Field Summary

Fields

Modifier and Type	Field and Description
static String	NCHW_NHWC_ERROR_MSG

Method Summary

Modifier and Type	Method and Description
static INDArray	adapt2dMask(INDArray mask, INDArray output, @NonNull CNN2DFormat format, LayerWorkspaceMgr workspaceMgr, ArrayType type)
static INDArray	cnn1dMaskReduction(INDArray in, int kernel, int stride, int padding, int dilation, ConvolutionMode cm) Given a mask array for a 1D CNN layer of shape [minibatch, sequenceLength], reduce the mask according to the 1D CNN layer configuration.
static INDArray	cnn2dMaskReduction(INDArray inMask, int[] kernel, int[] stride, int[] padding, int[] dilation, ConvolutionMode convolutionMode) Reduce a 2d CNN layer mask array (of 0s and 1s) according to the layer configuration.
static int[]	effectiveKernelSize(int[] kernel, int[] dilation)
static long[]	getDeconvolution3DOutputSize(INDArray inputData, int[] kernel, int[] strides, int[] padding, int[] dilation, ConvolutionMode convolutionMode, Convolution3D.DataFormat dataFormat) Get the output size of a deconvolution operation for given input data.
static int[]	getDeconvolutionOutputSize(INDArray inputData, int[] kernel, int[] strides, int[] padding, ConvolutionMode convolutionMode, int[] dilation, CNN2DFormat format) Get the output size of a deconvolution operation for given input data.
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[]	getHWDFromInputType(InputType inputType) Get heigh/width/channels as length 3 int[] from the InputType
static int[]	getOutputSize(INDArray inputData, int[] kernel, int[] strides, int[] padding, ConvolutionMode convolutionMode) Deprecated.
static int[]	getOutputSize(INDArray inputData, int[] kernel, int[] strides, int[] padding, ConvolutionMode convolutionMode, int[] dilation) Deprecated. Use getOutputSize(INDArray, int[], int[], int[], ConvolutionMode, int[], CNN2DFormat)
static int[]	getOutputSize(INDArray inputData, int[] kernel, int[] strides, int[] padding, ConvolutionMode convolutionMode, int[] dilation, CNN2DFormat format) Get the output size (height/width) for the given input data and CNN configuration
static int[]	getSameModeBottomRightPadding(int[] outSize, int[] inSize, int[] kernel, int[] strides, int[] dilation) Get bottom and right padding for same mode only.
static int[]	getSameModeTopLeftPadding(int[] outSize, int[] inSize, int[] kernel, int[] strides, int[] dilation) 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 long	numFeatureMap(NeuralNetConfiguration conf)
static INDArray	reshape2dTo4d(INDArray in2d, long[] toShape, CNN2DFormat format, LayerWorkspaceMgr workspaceMgr, ArrayType type)
static INDArray	reshape2dTo5d(Convolution3D.DataFormat format, INDArray in2d, long n, long d, long h, long w, long ch, LayerWorkspaceMgr workspaceMgr, ArrayType type)
static INDArray	reshape3dMask(INDArray mask, LayerWorkspaceMgr workspaceMgr, ArrayType type)
static INDArray	reshape4dMask(INDArray mask, LayerWorkspaceMgr workspaceMgr, ArrayType arrayType)
static INDArray	reshape4dTo2d(INDArray in, CNN2DFormat format, LayerWorkspaceMgr workspaceMgr, ArrayType type)
static INDArray	reshape4dTo2d(INDArray in, LayerWorkspaceMgr workspaceMgr, ArrayType type)
static INDArray	reshape5dTo2d(Convolution3D.DataFormat format, INDArray in, LayerWorkspaceMgr workspaceMgr, ArrayType type)
static INDArray	reshapeCnn3dMask(Convolution3D.DataFormat format, INDArray mask, INDArray label, LayerWorkspaceMgr workspaceMgr, ArrayType type)
static INDArray	reshapeMaskIfRequired(INDArray mask, INDArray output, CNN2DFormat format, LayerWorkspaceMgr workspaceMgr, ArrayType type)
static INDArray	reshapeMaskIfRequired(INDArray mask, INDArray output, LayerWorkspaceMgr workspaceMgr, ArrayType type) Deprecated. Use reshapeMaskIfRequired(INDArray, INDArray, CNN2DFormat, LayerWorkspaceMgr, ArrayType)
static void	validateCnnKernelStridePadding(int[] kernelSize, int[] stride, int[] padding) Perform validation on the CNN layer kernel/stride/padding.
static void	validateConvolutionModePadding(ConvolutionMode mode, int[] padding) Check that the convolution mode is consistent with the padding specification
static void	validateShapes(INDArray inputData, int[] eKernel, int[] strides, int[] padding, ConvolutionMode convolutionMode, int[] dilation, int[] inShape, boolean atrous)

Methods inherited from class java.lang.Object

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

Field Detail

NCHW_NHWC_ERROR_MSG

public static final String NCHW_NHWC_ERROR_MSG

See Also:

Constant Field Values

Method Detail

getOutputSize

@Deprecated
public static int[] getOutputSize(INDArray inputData,
                                              int[] kernel,
                                              int[] strides,
                                              int[] padding,
                                              ConvolutionMode convolutionMode)

Deprecated.

Use getOutputSize(INDArray, int[], int[], int[], ConvolutionMode, int[], CNN2DFormat)

getDeconvolutionOutputSize

public static int[] getDeconvolutionOutputSize(INDArray inputData,
                                               int[] kernel,
                                               int[] strides,
                                               int[] padding,
                                               ConvolutionMode convolutionMode,
                                               int[] dilation,
                                               CNN2DFormat format)

Get the output size of a deconvolution operation for given input data. In deconvolution, we compute the inverse of the shape computation of a convolution.

Parameters:

inputData - Input data

kernel - Kernel size (height/width)

strides - Strides (height/width)

padding - Padding (height/width)

convolutionMode - Convolution mode (Same, Strict, Truncate)

dilation - Kernel dilation (height/width)

Returns:

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

getDeconvolution3DOutputSize

public static long[] getDeconvolution3DOutputSize(INDArray inputData,
                                                  int[] kernel,
                                                  int[] strides,
                                                  int[] padding,
                                                  int[] dilation,
                                                  ConvolutionMode convolutionMode,
                                                  Convolution3D.DataFormat dataFormat)

Get the output size of a deconvolution operation for given input data. In deconvolution, we compute the inverse of the shape computation of a convolution.

Parameters:

inputData - Input data

kernel - Kernel size (height/width)

strides - Strides (height/width)

padding - Padding (height/width)

convolutionMode - Convolution mode (Same, Strict, Truncate)

dilation - Kernel dilation (height/width)

Returns:

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

getOutputSize

@Deprecated
public static int[] getOutputSize(INDArray inputData,
                                              int[] kernel,
                                              int[] strides,
                                              int[] padding,
                                              ConvolutionMode convolutionMode,
                                              int[] dilation)

Deprecated. Use getOutputSize(INDArray, int[], int[], int[], ConvolutionMode, int[], CNN2DFormat)

getOutputSize

public static int[] getOutputSize(INDArray inputData,
                                  int[] kernel,
                                  int[] strides,
                                  int[] padding,
                                  ConvolutionMode convolutionMode,
                                  int[] dilation,
                                  CNN2DFormat format)

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

Parameters:

inputData - Input data

kernel - Kernel size (height/width)

strides - Strides (height/width)

padding - Padding (height/width)

convolutionMode - Convolution mode (Same, Strict, Truncate)

dilation - Kernel dilation (height/width)

format - Format for input activations

Returns:

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

validateShapes

public static void validateShapes(INDArray inputData,
                                  int[] eKernel,
                                  int[] strides,
                                  int[] padding,
                                  ConvolutionMode convolutionMode,
                                  int[] dilation,
                                  int[] inShape,
                                  boolean atrous)

effectiveKernelSize

public static int[] effectiveKernelSize(int[] kernel,
                                        int[] dilation)

getSameModeTopLeftPadding

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

Get top and left padding for same mode only.

Parameters:

outSize - Output size (length 2 array, height dimension first)

inSize - Input size (length 2 array, height dimension first)

kernel - Kernel size (length 2 array, height dimension first)

strides - Strides (length 2 array, height dimension first)

dilation - Dilation (length 2 array, height dimension first)

Returns:

Top left padding (length 2 array, height dimension first)

getSameModeBottomRightPadding

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

Get bottom and right padding for same mode only.

Parameters:

outSize - Output size (length 2 array, height dimension first)

inSize - Input size (length 2 array, height dimension first)

kernel - Kernel size (length 2 array, height dimension first)

strides - Strides (length 2 array, height dimension first)

dilation - Dilation (length 2 array, height dimension first)

Returns:

Bottom right padding (length 2 array, height dimension first)

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 long 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

validateConvolutionModePadding

public static void validateConvolutionModePadding(ConvolutionMode mode,
                                                  int[] padding)

Check that the convolution mode is consistent with the padding specification

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

reshape4dTo2d

public static INDArray reshape4dTo2d(INDArray in,
                                     LayerWorkspaceMgr workspaceMgr,
                                     ArrayType type)

reshape4dTo2d

public static INDArray reshape4dTo2d(INDArray in,
                                     CNN2DFormat format,
                                     LayerWorkspaceMgr workspaceMgr,
                                     ArrayType type)

reshape5dTo2d

public static INDArray reshape5dTo2d(@NonNull
                                     Convolution3D.DataFormat format,
                                     INDArray in,
                                     LayerWorkspaceMgr workspaceMgr,
                                     ArrayType type)

reshapeCnn3dMask

public static INDArray reshapeCnn3dMask(@NonNull
                                        Convolution3D.DataFormat format,
                                        INDArray mask,
                                        INDArray label,
                                        LayerWorkspaceMgr workspaceMgr,
                                        ArrayType type)

reshape2dTo4d

public static INDArray reshape2dTo4d(INDArray in2d,
                                     long[] toShape,
                                     CNN2DFormat format,
                                     LayerWorkspaceMgr workspaceMgr,
                                     ArrayType type)

reshape2dTo5d

public static INDArray reshape2dTo5d(Convolution3D.DataFormat format,
                                     INDArray in2d,
                                     long n,
                                     long d,
                                     long h,
                                     long w,
                                     long ch,
                                     LayerWorkspaceMgr workspaceMgr,
                                     ArrayType type)

reshapeMaskIfRequired

@Deprecated
public static INDArray reshapeMaskIfRequired(INDArray mask,
                                                         INDArray output,
                                                         LayerWorkspaceMgr workspaceMgr,
                                                         ArrayType type)

Deprecated. Use reshapeMaskIfRequired(INDArray, INDArray, CNN2DFormat, LayerWorkspaceMgr, ArrayType)

reshapeMaskIfRequired

public static INDArray reshapeMaskIfRequired(INDArray mask,
                                             INDArray output,
                                             CNN2DFormat format,
                                             LayerWorkspaceMgr workspaceMgr,
                                             ArrayType type)

adapt2dMask

public static INDArray adapt2dMask(INDArray mask,
                                   INDArray output,
                                   @NonNull
                                   @NonNull CNN2DFormat format,
                                   LayerWorkspaceMgr workspaceMgr,
                                   ArrayType type)

reshape3dMask

public static INDArray reshape3dMask(INDArray mask,
                                     LayerWorkspaceMgr workspaceMgr,
                                     ArrayType type)

reshape4dMask

public static INDArray reshape4dMask(INDArray mask,
                                     LayerWorkspaceMgr workspaceMgr,
                                     ArrayType arrayType)

getHWDFromInputType

public static int[] getHWDFromInputType(InputType inputType)

Get heigh/width/channels as length 3 int[] from the InputType

Parameters:

inputType - Input type to get

Returns:

Length

cnn1dMaskReduction

public static INDArray cnn1dMaskReduction(INDArray in,
                                          int kernel,
                                          int stride,
                                          int padding,
                                          int dilation,
                                          ConvolutionMode cm)

Given a mask array for a 1D CNN layer of shape [minibatch, sequenceLength], reduce the mask according to the 1D CNN layer configuration. Unlike RNN layers, 1D CNN layers may down-sample the data; consequently, we need to down-sample the mask array in the same way, to maintain the correspondence between the masks and the output activations

Parameters:

in - Input size

kernel - Kernel size

stride - Stride

padding - Padding

dilation - Dilation

cm - Convolution mode

Returns:

Reduced mask

cnn2dMaskReduction

public static INDArray cnn2dMaskReduction(INDArray inMask,
                                          int[] kernel,
                                          int[] stride,
                                          int[] padding,
                                          int[] dilation,
                                          ConvolutionMode convolutionMode)

Reduce a 2d CNN layer mask array (of 0s and 1s) according to the layer configuration. Note that when a CNN layer changes the shape of the activations (for example, stride > 1) the corresponding mask array needs to change shape also (as there is a correspondence between the two). This method performs the forward pass for the mask.

Parameters:

inMask - Input mask array - rank 4, shape [mb,c,h,1] or [mb,c,w,1] or [mb,c,h,w]

kernel - Kernel configuration for the layer

stride - Stride

padding - Padding

dilation - Dilation

convolutionMode - Convolution mode

Returns:

The mask array corresponding to the network output