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| | AtrousConvolution () |
| | Create the AtrousConvolution object. More...
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| | AtrousConvolution (const size_t inSize, const size_t outSize, const size_t kW, const size_t kH, const size_t dW=1, const size_t dH=1, const size_t padW=0, const size_t padH=0, const size_t inputWidth=0, const size_t inputHeight=0, const size_t dilationW=1, const size_t dilationH=1) |
| | Create the AtrousConvolution object using the specified number of input maps, output maps, filter size, stride, dilation and padding parameter. More...
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| template<typename eT > |
| void | Backward (const arma::Mat< eT > &&, arma::Mat< eT > &&gy, arma::Mat< eT > &&g) |
| | Ordinary feed backward pass of a neural network, calculating the function f(x) by propagating x backwards through f. More...
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| OutputDataType const & | Delta () const |
| | Get the delta. More...
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| OutputDataType & | Delta () |
| | Modify the delta. More...
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| template<typename eT > |
| void | Forward (const arma::Mat< eT > &&input, arma::Mat< eT > &&output) |
| | Ordinary feed forward pass of a neural network, evaluating the function f(x) by propagating the activity forward through f. More...
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| template<typename eT > |
| void | Gradient (const arma::Mat< eT > &&, arma::Mat< eT > &&error, arma::Mat< eT > &&gradient) |
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| OutputDataType const & | Gradient () const |
| | Get the gradient. More...
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| OutputDataType & | Gradient () |
| | Modify the gradient. More...
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| size_t const & | InputHeight () const |
| | Get the input height. More...
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| size_t & | InputHeight () |
| | Modify the input height. More...
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| InputDataType const & | InputParameter () const |
| | Get the input parameter. More...
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| InputDataType & | InputParameter () |
| | Modify the input parameter. More...
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| size_t const & | InputWidth () const |
| | Get the input width. More...
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| size_t & | InputWidth () |
| | Modify input the width. More...
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| size_t const & | OutputHeight () const |
| | Get the output height. More...
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| size_t & | OutputHeight () |
| | Modify the output height. More...
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| OutputDataType const & | OutputParameter () const |
| | Get the output parameter. More...
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| OutputDataType & | OutputParameter () |
| | Modify the output parameter. More...
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| size_t const & | OutputWidth () const |
| | Get the output width. More...
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| size_t & | OutputWidth () |
| | Modify the output width. More...
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| OutputDataType const & | Parameters () const |
| | Get the parameters. More...
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| OutputDataType & | Parameters () |
| | Modify the parameters. More...
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| void | Reset () |
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| template<typename Archive > |
| void | serialize (Archive &ar, const unsigned int) |
| | Serialize the layer. More...
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template<typename ForwardConvolutionRule = NaiveConvolution<ValidConvolution>, typename BackwardConvolutionRule = NaiveConvolution<FullConvolution>, typename GradientConvolutionRule = NaiveConvolution<ValidConvolution>, typename InputDataType = arma::mat, typename OutputDataType = arma::mat>
class mlpack::ann::AtrousConvolution< ForwardConvolutionRule, BackwardConvolutionRule, GradientConvolutionRule, InputDataType, OutputDataType >
Implementation of the Atrous Convolution class.
The Atrous Convolution class represents a single layer of a neural network. Atrous (or Dilated) Convolutions are just simple convolutions applied to input with the defined, spaces included between the kernel cells, in order to capture a larger field of reception, without having to increase dicrete kernel sizes.
- Template Parameters
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| ForwardConvolutionRule | Atrous Convolution to perform forward process. |
| BackwardConvolutionRule | Atrous Convolution to perform backward process. |
| GradientConvolutionRule | Atrous Convolution to calculate gradient. |
| InputDataType | Type of the input data (arma::colvec, arma::mat, arma::sp_mat or arma::cube). |
| OutputDataType | Type of the output data (arma::colvec, arma::mat, arma::sp_mat or arma::cube). |
Definition at line 50 of file atrous_convolution.hpp.