CNN

Operation classes

avgPooling2d

INDArray avgPooling2d(INDArray input, Pooling2DConfig pooling2DConfig)

SDVariable avgPooling2d(SDVariable input, Pooling2DConfig pooling2DConfig)
SDVariable avgPooling2d(String name, SDVariable input, Pooling2DConfig pooling2DConfig)

2D Convolution layer operation - average pooling 2d

• input (NUMERIC) - the input to average pooling 2d operation - 4d CNN (image) activations in NCHW format (shape [minibatch, channels, height, width]) or NHWC format (shape [minibatch, height, width, channels])

• Pooling2DConfig - see Pooling2DConfig

avgPooling3d

INDArray avgPooling3d(INDArray input, Pooling3DConfig pooling3DConfig)

SDVariable avgPooling3d(SDVariable input, Pooling3DConfig pooling3DConfig)
SDVariable avgPooling3d(String name, SDVariable input, Pooling3DConfig pooling3DConfig)

3D convolution layer operation - average pooling 3d

• input (NUMERIC) - the input to average pooling 3d operation - 5d activations in NCDHW format (shape [minibatch, channels, depth, height, width]) or NDHWC format (shape [minibatch, depth, height, width, channels])

• Pooling3DConfig - see Pooling3DConfig

batchToSpace

INDArray batchToSpace(INDArray x, int[] blocks, int[] croppingTop, int[] croppingBottom)

SDVariable batchToSpace(SDVariable x, int[] blocks, int[] croppingTop, int[] croppingBottom)
SDVariable batchToSpace(String name, SDVariable x, int[] blocks, int[] croppingTop, int[] croppingBottom)

Convolution 2d layer batch to space operation on 4d input.

Reduces input batch dimension by rearranging data into a larger spatial dimensions

• x (NUMERIC) - Input variable. 4d input

• blocks - Block size, in the height/width dimension (Size: Exactly(count=2))

• croppingTop - (Size: Exactly(count=2))

• croppingBottom - (Size: Exactly(count=2))

col2Im

INDArray col2Im(INDArray in, Conv2DConfig conv2DConfig)

SDVariable col2Im(SDVariable in, Conv2DConfig conv2DConfig)
SDVariable col2Im(String name, SDVariable in, Conv2DConfig conv2DConfig)

col2im operation for use in 2D convolution operations. Outputs a 4d array with shape

[minibatch, inputChannels, height, width]

• in (NUMERIC) - Input - rank 6 input with shape [minibatch, inputChannels, kernelHeight, kernelWidth, outputHeight, outputWidth]