Implementation of the Sequential class. More...
Public Member Functions | |
Sequential (const bool model=true) | |
Create the Sequential object using the specified parameters. More... | |
Sequential (const bool model, const bool ownsLayers) | |
Create the Sequential object using the specified parameters. More... | |
Sequential (const Sequential &layer) | |
Copy constructor. More... | |
~Sequential () | |
Destroy the Sequential object. More... | |
template | |
void | Add (Args... args) |
void | Add (LayerTypes< CustomLayers... > layer) |
template | |
void | Backward (const arma::Mat< eT > &, const arma::Mat< eT > &gy, arma::Mat< eT > &g) |
Ordinary feed backward pass of a neural network, using 3rd-order tensors as input, calculating the function f(x) by propagating x backwards through f. More... | |
arma::mat const & | Delta () const |
Get the delta. More... | |
arma::mat & | Delta () |
Modify the delta. More... | |
template | |
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... | |
template | |
void | Gradient (const arma::Mat< eT > &input, const arma::Mat< eT > &error, arma::Mat< eT > &) |
arma::mat const & | Gradient () const |
Get the gradient. More... | |
arma::mat & | Gradient () |
Modify the gradient. More... | |
arma::mat const & | InputParameter () const |
Get the input parameter. More... | |
arma::mat & | InputParameter () |
Modify the input parameter. More... | |
std::vector< LayerTypes< CustomLayers... > > & | Model () |
Return the model modules. More... | |
Sequential & | operator= (const Sequential &layer) |
Copy assignment operator. More... | |
arma::mat const & | OutputParameter () const |
Get the output parameter. More... | |
arma::mat & | OutputParameter () |
Modify the output parameter. More... | |
const arma::mat & | Parameters () const |
Return the initial point for the optimization. More... | |
arma::mat & | Parameters () |
Modify the initial point for the optimization. More... | |
template | |
void | serialize (Archive &, const unsigned int) |
Serialize the layer. More... | |
Implementation of the Sequential class.
The sequential class works as a feed-forward fully connected network container which plugs various layers together.
This class can also be used as a container for a residual block. In that case, the sizes of the input and output matrices of this class should be equal. A typedef has been added for use as a Residual<> class.
For more information, refer the following paper.
Note: If this class is used as the first layer of a network, it should be preceded by IdentityLayer<>.
Note: This class should at least have two layers for a call to its Gradient() function.
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). |
Residual | If true, use the object as a Residual block. |
Definition at line 138 of file layer_types.hpp.
Sequential | ( | const bool | model = true | ) |
Create the Sequential object using the specified parameters.
model | Expose the all network modules. |
Sequential | ( | const bool | model, |
const bool | ownsLayers | ||
) |
Create the Sequential object using the specified parameters.
model | Expose all the network modules. |
ownsLayers | If true, then this module will delete its layers when deallocated. |
Sequential | ( | const Sequential< InputDataType, OutputDataType, Residual, CustomLayers > & | layer | ) |
Copy constructor.
~Sequential | ( | ) |
Destroy the Sequential object.
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inline |
Definition at line 142 of file sequential.hpp.
Referenced by DuelingDQN< OutputLayerType, InitType, CompleteNetworkType, FeatureNetworkType, AdvantageNetworkType, ValueNetworkType >::DuelingDQN().
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inline |
Definition at line 149 of file sequential.hpp.
void Backward | ( | const arma::Mat< eT > & | , |
const arma::Mat< eT > & | gy, | ||
arma::Mat< eT > & | g | ||
) |
Ordinary feed backward pass of a neural network, using 3rd-order tensors as input, calculating the function f(x) by propagating x backwards through f.
Using the results from the feed forward pass.
* | (input) The propagated input activation. |
gy | The backpropagated error. |
g | The calculated gradient. |
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inline |
Get the delta.
Definition at line 178 of file sequential.hpp.
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inline |
Modify the delta.
Definition at line 180 of file sequential.hpp.
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.
input | Input data used for evaluating the specified function. |
output | Resulting output activation. |
void Gradient | ( | const arma::Mat< eT > & | input, |
const arma::Mat< eT > & | error, | ||
arma::Mat< eT > & | |||
) |
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inline |
Get the gradient.
Definition at line 183 of file sequential.hpp.
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inline |
Modify the gradient.
Definition at line 185 of file sequential.hpp.
References Sequential< InputDataType, OutputDataType, Residual, CustomLayers >::serialize().
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inline |
Get the input parameter.
Definition at line 168 of file sequential.hpp.
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inline |
Modify the input parameter.
Definition at line 170 of file sequential.hpp.
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inline |
Return the model modules.
Definition at line 152 of file sequential.hpp.
Sequential& operator= | ( | const Sequential< InputDataType, OutputDataType, Residual, CustomLayers > & | layer | ) |
Copy assignment operator.
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inline |
Get the output parameter.
Definition at line 173 of file sequential.hpp.
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inline |
Modify the output parameter.
Definition at line 175 of file sequential.hpp.
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inline |
Return the initial point for the optimization.
Definition at line 163 of file sequential.hpp.
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inline |
Modify the initial point for the optimization.
Definition at line 165 of file sequential.hpp.
void serialize | ( | Archive & | , |
const unsigned | int | ||
) |
Serialize the layer.
Referenced by Sequential< InputDataType, OutputDataType, Residual, CustomLayers >::Gradient().