All Classes
| Class | Description |
|---|---|
| BaseDBatchNorm_F64 |
Implements common functionality for all batch normalization implementations for
Tensor_F64. |
| BaseDFunction<T extends deepboof.Tensor<T>> |
Base class which implements common functionality between all
DFunction |
| DActivationReLU<T extends deepboof.Tensor<T>> |
Interface of
ActivationReLU which adds functionality for the backwards step. |
| DActivationReLU_F64 |
Implementation of
DActivationReLU for Tensor_F64 |
| DActivationSigmoid<T extends deepboof.Tensor<T>> |
Interface of
ActivationSigmoid which adds functionality for the backwards step. |
| DActivationSigmoid_F64 |
Implementation of
DActivationSigmoid for Tensor_F64. |
| DActivationTanH<T extends deepboof.Tensor<T>> |
Interface of
ActivationTanH which adds functionality for the backwards step. |
| DActivationTanH_F64 |
Implementation of
DActivationTanH for Tensor_F64. |
| DBatchNorm<T extends deepboof.Tensor<T>> |
Implementation of
batch normalization for training networks. |
| DClippedPadding2D_F64 |
Backwards implementation of
ClippedPadding2D_F64. |
| DConstantPadding2D_F64 |
Backwards implementation of
ConstantPadding2D_F64. |
| DFunctionBatchNorm<T extends deepboof.Tensor<T>> |
Implementation of
Batch Normalization for training networks. |
| DFunctionBatchNorm_F64 |
Implementation of
DFunctionBatchNorm for Tensor_F64. |
| DFunctionDropOut<T extends deepboof.Tensor<T>> |
Drop out is a technique introduced by [1] for regularizing a network and helps prevents over fitting.
|
| DFunctionDropOut_F64 |
Implementation of
DFunctionDropOut for Tensor_F64 |
| DFunctionLinear<T extends deepboof.Tensor<T>> |
Interface of
FunctionLinear which adds functionality for the backwards step. |
| DFunctionLinear_F64 |
Implementation of
DFunctionLinear for Tensor_F64 |
| DFunctionSequence | |
| DSpatialBatchNorm<T extends deepboof.Tensor<T>> |
Interface of
Spatial Batch Normalization for training networks. |
| DSpatialBatchNorm_F64 |
Implementation of
DSpatialBatchNorm for Tensor_F64. |
| DSpatialConvolve2D<T extends deepboof.Tensor<T>> |
Implementation of
Spatial Convolve 2D for training networks. |
| DSpatialConvolve2D_F64 |
Implementation of
DSpatialConvolve2D for Tensor_F64. |
| DSpatialMaxPooling<T extends deepboof.Tensor<T>> |
Interface of
SpatialMaxPooling which adds functionality for the backwards step. |
| DSpatialMaxPooling_F64 | |
| DSpatialPadding2D<T extends deepboof.Tensor<T>> |
Interface for computing the gradient of a padded spatial tensor.
|
| DSpatialPadding2D_F64 | |
| DSpatialWindowChannel<T extends deepboof.Tensor<T>,P extends DSpatialPadding2D<T>> |
Backwards functions for operations which convolve a window across the input spatial tensor and
process the image in a BCHW (batch, channel, (row, column)) order, e.g.
|
| DSpatialWindowImage<T extends deepboof.Tensor<T>,P extends DSpatialPadding2D<T>> |
Backwards functions for operations which convolve a window across the input spatial tensor.
|
| ElementWiseDFunction<T extends deepboof.Tensor<T>> |
Base class for element-wise derivative functions
|
| FactoryBackwards<T extends deepboof.Tensor<T>> | |
| NumericalGradient<T extends deepboof.Tensor<T>> |
Given a
Function implementations of this interface will compute the gradient of its
inputs and parameters. |
| NumericalGradient_F64 |
Implementation of
NumericalGradient for Tensor_F64 |
| VanilaGradientDescent |