Uses of Class
org.deeplearning4j.nn.conf.layers.Convolution3D.DataFormat

Packages that use Convolution3D.DataFormat

Package	Description
org.deeplearning4j.nn.conf.inputs
org.deeplearning4j.nn.conf.layers
org.deeplearning4j.nn.conf.preprocessor
org.deeplearning4j.util

Uses of Convolution3D.DataFormat in org.deeplearning4j.nn.conf.inputs

Methods in org.deeplearning4j.nn.conf.inputs with parameters of type Convolution3D.DataFormat

Modifier and Type	Method and Description
static InputType	InputType.convolutional3D(Convolution3D.DataFormat dataFormat, long depth, long height, long width, long channels) Input type for 3D convolutional (CNN3D) 5d data: If NDHWC format [miniBatchSize, depth, height, width, channels] If NDCWH

Constructors in org.deeplearning4j.nn.conf.inputs with parameters of type Convolution3D.DataFormat

Constructor and Description
InputTypeConvolutional3D(Convolution3D.DataFormat dataFormat, long depth, long height, long width, long channels)

Uses of Convolution3D.DataFormat in org.deeplearning4j.nn.conf.layers

Fields in org.deeplearning4j.nn.conf.layers declared as Convolution3D.DataFormat

Modifier and Type	Field and Description
protected Convolution3D.DataFormat	Cnn3DLossLayer.dataFormat
protected Convolution3D.DataFormat	Cnn3DLossLayer.Builder.dataFormat Format of the input/output data.
protected Convolution3D.DataFormat	Subsampling3DLayer.dataFormat
protected Convolution3D.DataFormat	Subsampling3DLayer.Builder.dataFormat The data format for input and output activations. NCDHW: activations (in/out) should have shape [minibatch, channels, depth, height, width] NDHWC: activations (in/out) should have shape [minibatch, depth, height, width, channels]
protected Convolution3D.DataFormat	Upsampling3D.dataFormat
protected Convolution3D.DataFormat	Upsampling3D.Builder.dataFormat

Methods in org.deeplearning4j.nn.conf.layers that return Convolution3D.DataFormat

Modifier and Type	Method and Description
static Convolution3D.DataFormat	Convolution3D.DataFormat.valueOf(String name) Returns the enum constant of this type with the specified name.
static Convolution3D.DataFormat[]	Convolution3D.DataFormat.values() Returns an array containing the constants of this enum type, in the order they are declared.

Methods in org.deeplearning4j.nn.conf.layers with parameters of type Convolution3D.DataFormat

Modifier and Type	Method and Description
Convolution3D.Builder	Convolution3D.Builder.dataFormat(Convolution3D.DataFormat dataFormat) The data format for input and output activations. NCDHW: activations (in/out) should have shape [minibatch, channels, depth, height, width] NDHWC: activations (in/out) should have shape [minibatch, depth, height, width, channels]
Deconvolution3D.Builder	Deconvolution3D.Builder.dataFormat(Convolution3D.DataFormat dataFormat)
Subsampling3DLayer.Builder	Subsampling3DLayer.Builder.dataFormat(Convolution3D.DataFormat dataFormat) The data format for input and output activations. NCDHW: activations (in/out) should have shape [minibatch, channels, depth, height, width] NDHWC: activations (in/out) should have shape [minibatch, depth, height, width, channels]
Upsampling3D.Builder	Upsampling3D.Builder.dataFormat(Convolution3D.DataFormat dataFormat) Sets the DataFormat.
static InputType	InputTypeUtil.getOutputTypeCnn3DLayers(InputType inputType, Convolution3D.DataFormat dataFormat, int[] kernelSize, int[] stride, int[] padding, int[] dilation, ConvolutionMode convolutionMode, long outputChannels, long layerIdx, String layerName, Class<?> layerClass)
static InputType	InputTypeUtil.getOutputTypeDeconv3dLayer(InputType inputType, int[] kernelSize, int[] stride, int[] padding, int[] dilation, ConvolutionMode convolutionMode, Convolution3D.DataFormat dataFormat, long outputDepth, long layerIdx, String layerName, Class<?> layerClass)

Constructors in org.deeplearning4j.nn.conf.layers with parameters of type Convolution3D.DataFormat

Constructor and Description
Builder(Convolution3D.DataFormat format)
Builder(Convolution3D.DataFormat dataFormat, int size)

Uses of Convolution3D.DataFormat in org.deeplearning4j.nn.conf.preprocessor

Constructors in org.deeplearning4j.nn.conf.preprocessor with parameters of type Convolution3D.DataFormat

Constructor and Description
Cnn3DToFeedForwardPreProcessor(int inputDepth, int inputHeight, int inputWidth, int numChannels, Convolution3D.DataFormat dataFormat)

Uses of Convolution3D.DataFormat in org.deeplearning4j.util

Methods in org.deeplearning4j.util with parameters of type Convolution3D.DataFormat

Modifier and Type	Method and Description
static long[]	ConvolutionUtils.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 INDArray	ConvolutionUtils.reshape2dTo5d(Convolution3D.DataFormat format, INDArray in2d, long n, long d, long h, long w, long ch, LayerWorkspaceMgr workspaceMgr, ArrayType type)
static INDArray	ConvolutionUtils.reshape5dTo2d(Convolution3D.DataFormat format, INDArray in, LayerWorkspaceMgr workspaceMgr, ArrayType type)
static INDArray	ConvolutionUtils.reshapeCnn3dMask(Convolution3D.DataFormat format, INDArray mask, INDArray label, LayerWorkspaceMgr workspaceMgr, ArrayType type)