Modifier and Type | Method and Description |
---|---|
static CNN2DFormat |
CNN2DFormat.valueOf(String name)
Returns the enum constant of this type with the specified name.
|
static CNN2DFormat[] |
CNN2DFormat.values()
Returns an array containing the constants of this enum type, in
the order they are declared.
|
Modifier and Type | Method and Description |
---|---|
static CNN2DFormat |
InputType.getDefaultCNN2DFormat() |
Modifier and Type | Method and Description |
---|---|
static InputType |
InputType.convolutional(long height,
long width,
long depth,
CNN2DFormat format) |
static void |
InputType.setDefaultCNN2DFormat(CNN2DFormat defaultCNN2DFormat) |
Constructor and Description |
---|
InputTypeConvolutional(long height,
long width,
long channels,
CNN2DFormat format) |
Modifier and Type | Field and Description |
---|---|
protected CNN2DFormat |
SubsamplingLayer.cnn2dDataFormat |
protected CNN2DFormat |
ConvolutionLayer.cnn2dDataFormat |
protected CNN2DFormat |
DepthwiseConvolution2D.Builder.cnn2DFormat |
protected CNN2DFormat |
SubsamplingLayer.BaseSubsamplingBuilder.cnn2DFormat
Configure the 2d data format
|
protected CNN2DFormat |
BatchNormalization.cnn2DFormat |
protected CNN2DFormat |
BatchNormalization.Builder.cnn2DFormat |
protected CNN2DFormat |
SpaceToDepthLayer.dataFormat |
protected CNN2DFormat |
SpaceToDepthLayer.Builder.dataFormat
Data format for input activations.
|
protected CNN2DFormat |
SeparableConvolution2D.Builder.dataFormat |
protected CNN2DFormat |
LocalResponseNormalization.dataFormat |
protected CNN2DFormat |
LocalResponseNormalization.Builder.dataFormat |
protected CNN2DFormat |
ConvolutionLayer.Builder.dataFormat |
static CNN2DFormat |
SubsamplingLayer.DEFAULT_FORMAT |
protected CNN2DFormat |
Upsampling2D.format |
protected CNN2DFormat |
Upsampling2D.Builder.format |
protected CNN2DFormat |
LocallyConnected2D.format |
protected CNN2DFormat |
LocallyConnected2D.Builder.format |
protected CNN2DFormat |
SpaceToBatchLayer.format |
protected CNN2DFormat |
SpaceToBatchLayer.Builder.format |
protected CNN2DFormat |
CnnLossLayer.format |
protected CNN2DFormat |
CnnLossLayer.Builder.format |
Modifier and Type | Method and Description |
---|---|
CNN2DFormat |
SpaceToDepthLayer.DataFormat.toFormat()
Deprecated.
|
Modifier and Type | Method and Description |
---|---|
T |
SpaceToDepthLayer.Builder.dataFormat(CNN2DFormat dataFormat)
Set the data format for the CNN activations - NCHW (channels first) or NHWC (channels last).
|
SeparableConvolution2D.Builder |
SeparableConvolution2D.Builder.dataFormat(CNN2DFormat format)
Set the data format for the CNN activations - NCHW (channels first) or NHWC (channels last).
|
DepthwiseConvolution2D.Builder |
DepthwiseConvolution2D.Builder.dataFormat(CNN2DFormat format)
Set the data format for the CNN activations - NCHW (channels first) or NHWC (channels last).
|
T |
SubsamplingLayer.BaseSubsamplingBuilder.dataFormat(CNN2DFormat cnn2DFormat)
Set the data format for the CNN activations - NCHW (channels first) or NHWC (channels last).
|
Upsampling2D.Builder |
Upsampling2D.Builder.dataFormat(CNN2DFormat format)
Set the data format for the CNN activations - NCHW (channels first) or NHWC (channels last).
|
LocallyConnected2D.Builder |
LocallyConnected2D.Builder.dataFormat(CNN2DFormat format)
Set the data format for the CNN activations - NCHW (channels first) or NHWC (channels last).
|
T |
SpaceToBatchLayer.Builder.dataFormat(CNN2DFormat format)
Set the data format for the CNN activations - NCHW (channels first) or NHWC (channels last).
|
BatchNormalization.Builder |
BatchNormalization.Builder.dataFormat(CNN2DFormat format)
Set the input and output array data format.
|
Deconvolution2D.Builder |
Deconvolution2D.Builder.dataFormat(CNN2DFormat format) |
LocalResponseNormalization.Builder |
LocalResponseNormalization.Builder.dataFormat(CNN2DFormat dataFormat)
Set the data format for the CNN activations - NCHW (channels first) or NHWC (channels last).
|
ConvolutionLayer.Builder |
ConvolutionLayer.Builder.dataFormat(CNN2DFormat format)
Set the data format for the CNN activations - NCHW (channels first) or NHWC (channels last).
|
ZeroPaddingLayer.Builder |
ZeroPaddingLayer.Builder.dataFormat(CNN2DFormat format)
Set the data format for the CNN activations - NCHW (channels first) or NHWC (channels last).
|
CnnLossLayer.Builder |
CnnLossLayer.Builder.format(CNN2DFormat format) |
static InputType |
InputTypeUtil.getOutputTypeCnnLayers(InputType inputType,
int[] kernelSize,
int[] stride,
int[] padding,
int[] dilation,
ConvolutionMode convolutionMode,
long outputDepth,
long layerIdx,
String layerName,
CNN2DFormat format,
Class<?> layerClass) |
void |
SubsamplingLayer.Builder.setDataFormat(CNN2DFormat format) |
void |
ConvolutionLayer.Builder.setDataFormat(CNN2DFormat dataFormat) |
Constructor and Description |
---|
Builder(int blockSize,
CNN2DFormat dataFormat) |
Modifier and Type | Method and Description |
---|---|
Cropping2D.Builder |
Cropping2D.Builder.dataFormat(CNN2DFormat format)
Set the data format for the CNN activations - NCHW (channels first) or NHWC (channels last).
|
Constructor and Description |
---|
Cropping2D(CNN2DFormat dataFormat,
int cropTopBottom,
int cropLeftRight) |
Cropping2D(CNN2DFormat format,
int cropTop,
int cropBottom,
int cropLeft,
int cropRight) |
Modifier and Type | Field and Description |
---|---|
protected CNN2DFormat |
CnnToFeedForwardPreProcessor.format |
Constructor and Description |
---|
CnnToFeedForwardPreProcessor(long inputHeight,
long inputWidth,
long numChannels,
CNN2DFormat format) |
Modifier and Type | Method and Description |
---|---|
Pair<Gradient,INDArray> |
ConvolutionHelper.backpropGradient(INDArray input,
INDArray weights,
INDArray bias,
INDArray delta,
int[] kernel,
int[] strides,
int[] pad,
INDArray biasGradView,
INDArray weightGradView,
IActivation afn,
ConvolutionLayer.AlgoMode mode,
ConvolutionLayer.BwdFilterAlgo bwdFilterAlgo,
ConvolutionLayer.BwdDataAlgo bwdDataAlgo,
ConvolutionMode convolutionMode,
int[] dilation,
CNN2DFormat format,
LayerWorkspaceMgr workspaceMgr) |
INDArray |
ConvolutionHelper.preOutput(INDArray input,
INDArray weights,
INDArray bias,
int[] kernel,
int[] strides,
int[] pad,
ConvolutionLayer.AlgoMode mode,
ConvolutionLayer.FwdAlgo fwdAlgo,
ConvolutionMode convolutionMode,
int[] dilation,
CNN2DFormat format,
LayerWorkspaceMgr workspaceMgr) |
Modifier and Type | Method and Description |
---|---|
INDArray |
SubsamplingHelper.activate(INDArray input,
boolean training,
int[] kernel,
int[] strides,
int[] pad,
PoolingType poolingType,
ConvolutionMode convolutionMode,
int[] dilation,
CNN2DFormat format,
LayerWorkspaceMgr workspaceMgr) |
Pair<Gradient,INDArray> |
SubsamplingHelper.backpropGradient(INDArray input,
INDArray epsilon,
int[] kernel,
int[] strides,
int[] pad,
PoolingType poolingType,
ConvolutionMode convolutionMode,
int[] dilation,
CNN2DFormat format,
LayerWorkspaceMgr workspaceMgr) |
Modifier and Type | Method and Description |
---|---|
protected CNN2DFormat |
Upsampling2D.getFormat() |
protected CNN2DFormat |
Upsampling1D.getFormat() |
Modifier and Type | Method and Description |
---|---|
INDArray |
MKLDNNSubsamplingHelper.activate(INDArray input,
boolean training,
int[] kernel,
int[] strides,
int[] pad,
PoolingType poolingType,
ConvolutionMode convolutionMode,
int[] dilation,
CNN2DFormat format,
LayerWorkspaceMgr workspaceMgr) |
Pair<Gradient,INDArray> |
MKLDNNConvHelper.backpropGradient(INDArray input,
INDArray weights,
INDArray bias,
INDArray delta,
int[] kernel,
int[] strides,
int[] pad,
INDArray biasGradView,
INDArray weightGradView,
IActivation afn,
ConvolutionLayer.AlgoMode mode,
ConvolutionLayer.BwdFilterAlgo bwdFilterAlgo,
ConvolutionLayer.BwdDataAlgo bwdDataAlgo,
ConvolutionMode convolutionMode,
int[] dilation,
CNN2DFormat format,
LayerWorkspaceMgr workspaceMgr) |
Pair<Gradient,INDArray> |
MKLDNNSubsamplingHelper.backpropGradient(INDArray input,
INDArray epsilon,
int[] kernel,
int[] strides,
int[] pad,
PoolingType poolingType,
ConvolutionMode convolutionMode,
int[] dilation,
CNN2DFormat format,
LayerWorkspaceMgr workspaceMgr) |
Pair<Gradient,INDArray> |
MKLDNNBatchNormHelper.backpropGradient(INDArray input,
INDArray epsilon,
long[] shape,
INDArray gamma,
INDArray beta,
INDArray dGammaView,
INDArray dBetaView,
double eps,
CNN2DFormat format,
LayerWorkspaceMgr workspaceMgr) |
INDArray |
MKLDNNBatchNormHelper.preOutput(INDArray x,
boolean training,
long[] shape,
INDArray gamma,
INDArray beta,
INDArray mean,
INDArray var,
double decay,
double eps,
CNN2DFormat format,
LayerWorkspaceMgr workspaceMgr) |
INDArray |
MKLDNNConvHelper.preOutput(INDArray input,
INDArray weights,
INDArray bias,
int[] kernel,
int[] strides,
int[] pad,
ConvolutionLayer.AlgoMode mode,
ConvolutionLayer.FwdAlgo fwdAlgo,
ConvolutionMode convolutionMode,
int[] dilation,
CNN2DFormat format,
LayerWorkspaceMgr workspaceMgr) |
Modifier and Type | Method and Description |
---|---|
Pair<Gradient,INDArray> |
BatchNormalizationHelper.backpropGradient(INDArray input,
INDArray epsilon,
long[] shape,
INDArray gamma,
INDArray beta,
INDArray dGammaView,
INDArray dBetaView,
double eps,
CNN2DFormat format,
LayerWorkspaceMgr workspaceMgr) |
INDArray |
BatchNormalizationHelper.preOutput(INDArray x,
boolean training,
long[] shape,
INDArray gamma,
INDArray beta,
INDArray mean,
INDArray var,
double decay,
double eps,
CNN2DFormat format,
LayerWorkspaceMgr workspaceMgr) |
Modifier and Type | Method and Description |
---|---|
static CNN2DFormat |
ConvolutionUtils.getFormatForLayer(Layer layer)
Get the format for a given layer.
|
Modifier and Type | Method and Description |
---|---|
static INDArray |
ConvolutionUtils.adapt2dMask(INDArray mask,
INDArray output,
@NonNull CNN2DFormat format,
LayerWorkspaceMgr workspaceMgr,
ArrayType type) |
static int[] |
ConvolutionUtils.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[] |
ConvolutionUtils.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 INDArray |
ConvolutionUtils.reshape2dTo4d(INDArray in2d,
long[] toShape,
CNN2DFormat format,
LayerWorkspaceMgr workspaceMgr,
ArrayType type) |
static INDArray |
ConvolutionUtils.reshape4dTo2d(INDArray in,
CNN2DFormat format,
LayerWorkspaceMgr workspaceMgr,
ArrayType type) |
static INDArray |
ConvolutionUtils.reshapeMaskIfRequired(INDArray mask,
INDArray output,
CNN2DFormat format,
LayerWorkspaceMgr workspaceMgr,
ArrayType type) |
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