Package deepboof.forward
package deepboof.forward
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ClassDescriptionActivationReLU<T extends Tensor>Rectified Linear Unit (ReLU) activation function.ActivationSigmoid<T extends Tensor>The sigmoid is defined as:ActivationTanH<T extends Tensor>The hyperbolic tangent (tanh) is defined as:Batch Normalization [1] determines the mean and standard deviation (stdev) of each input element individually using the training data.ClippedPadding2D<T extends Tensor<T>>Interface for padding in which the region being sampled has been clipped so that it will be entirely contained inside the original image.Configuration for 2D convolution.Configuration for spatial padding.Common configuration for many spatial functionsConstantPadding2D<T extends Tensor<T>>Interface for padding which applies a constant padding to the output of the imageFunctionBatchNorm<T extends Tensor<T>>Implementation of a forward only Batch Normalization.FunctionElementWiseMult<T extends Tensor>Multiplies each element in a tensor by the same value.FunctionLinear<T extends Tensor>Applies a linear (or affine) equation to input array.SpatialAveragePooling<T extends Tensor>Max spatial pooling find the average value inside the pooling region.SpatialBatchNorm<T extends Tensor<T>>Spatial
Batch Normalizationseeks to maintain the convolutional property, "that different elements of the same feature map, at different locations, are normalized in the same way." [1] Thus the input tensor (N,C,H,W) is "reshaped" such that it is (N*H*W,C) and it's treated like a mini-batch with N*H*W elements.SpatialConvolve2D<T extends Tensor<T>>Performs convolutions across an input image with special kernels that have 'C' channels, one for each input image.SpatialMaxPooling<T extends Tensor>Max spatial pooling find the maximum value inside the pooling region.SpatialPadding2D<T extends Tensor<T>>Interface for all virtual 2D spatial padding implementation.Abstract class for F64 implementations ofBaseSpatialPadding2D.Abstract class for F64 implementations ofBaseSpatialPadding2D.SpatialPooling<T extends Tensor>Spatial pooling down samples the input spatial tensors by finding a representative value inside each pooling region.