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CNeuralConvolutionalLayer类 参考

详细描述

Main component in convolutional neural networks

This layer type of consists of multiple feature maps. Each feature map computes its activations using by convolving its filter with the inputs, adding a bias, and then applying a non-linearity. Activations of each feature map can be max-pooled, that is, the map is divided into regions of a certain size and then the maximum activation is taken from each region.

All layer that are connected to this layer as input must have the same size.

During convolution, the inputs are implicitly padded with zeros on the sides

The layer assumes that its input images are in column major format

在文件 NeuralConvolutionalLayer.h59 行定义.

类 CNeuralConvolutionalLayer 继承关系图:
Inheritance graph
[图例]

Public 成员函数

 CNeuralConvolutionalLayer ()
 
 CNeuralConvolutionalLayer (EConvMapActivationFunction function, int32_t num_maps, int32_t radius_x, int32_t radius_y, int32_t pooling_width=1, int32_t pooling_height=1, int32_t stride_x=1, int32_t stride_y=1)
 
virtual ~CNeuralConvolutionalLayer ()
 
virtual void set_batch_size (int32_t batch_size)
 
virtual void initialize (CDynamicObjectArray *layers, SGVector< int32_t > input_indices)
 
virtual void initialize_parameters (SGVector< float64_t > parameters, SGVector< bool > parameter_regularizable, float64_t sigma)
 
virtual void compute_activations (SGVector< float64_t > parameters, CDynamicObjectArray *layers)
 
virtual void compute_gradients (SGVector< float64_t > parameters, SGMatrix< float64_t > targets, CDynamicObjectArray *layers, SGVector< float64_t > parameter_gradients)
 
virtual float64_t compute_error (SGMatrix< float64_t > targets)
 
virtual void enforce_max_norm (SGVector< float64_t > parameters, float64_t max_norm)
 
virtual const char * get_name () const
 
virtual bool is_input ()
 
virtual void compute_activations (SGMatrix< float64_t > inputs)
 
virtual void dropout_activations ()
 
virtual float64_t compute_contraction_term (SGVector< float64_t > parameters)
 
virtual int32_t get_num_neurons ()
 
virtual int32_t get_width ()
 
virtual int32_t get_height ()
 
virtual int32_t get_num_parameters ()
 
virtual SGMatrix< float64_tget_activations ()
 
virtual SGMatrix< float64_tget_activation_gradients ()
 
virtual SGMatrix< float64_tget_local_gradients ()
 
virtual CSGObjectshallow_copy () const
 
virtual CSGObjectdeep_copy () const
 
virtual bool is_generic (EPrimitiveType *generic) const
 
template<class T >
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
void unset_generic ()
 
virtual void print_serializable (const char *prefix="")
 
virtual bool save_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_version_parameter())
 
virtual bool load_serializable (CSerializableFile *file, const char *prefix="", int32_t param_version=Version::get_version_parameter())
 
DynArray< TParameter * > * load_file_parameters (const SGParamInfo *param_info, int32_t file_version, CSerializableFile *file, const char *prefix="")
 
DynArray< TParameter * > * load_all_file_parameters (int32_t file_version, int32_t current_version, CSerializableFile *file, const char *prefix="")
 
void map_parameters (DynArray< TParameter * > *param_base, int32_t &base_version, DynArray< const SGParamInfo * > *target_param_infos)
 
void set_global_io (SGIO *io)
 
SGIOget_global_io ()
 
void set_global_parallel (Parallel *parallel)
 
Parallelget_global_parallel ()
 
void set_global_version (Version *version)
 
Versionget_global_version ()
 
SGStringList< char > get_modelsel_names ()
 
void print_modsel_params ()
 
char * get_modsel_param_descr (const char *param_name)
 
index_t get_modsel_param_index (const char *param_name)
 
void build_gradient_parameter_dictionary (CMap< TParameter *, CSGObject * > *dict)
 
virtual void update_parameter_hash ()
 
virtual bool parameter_hash_changed ()
 
virtual bool equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false)
 
virtual CSGObjectclone ()
 

Public 属性

bool is_training
 
float64_t dropout_prop
 
float64_t contraction_coefficient
 
ENLAutoencoderPosition autoencoder_position
 
SGIOio
 
Parallelparallel
 
Versionversion
 
Parameterm_parameters
 
Parameterm_model_selection_parameters
 
Parameterm_gradient_parameters
 
ParameterMapm_parameter_map
 
uint32_t m_hash
 

Protected 成员函数

virtual TParametermigrate (DynArray< TParameter * > *param_base, const SGParamInfo *target)
 
virtual void one_to_one_migration_prepare (DynArray< TParameter * > *param_base, const SGParamInfo *target, TParameter *&replacement, TParameter *&to_migrate, char *old_name=NULL)
 
virtual void load_serializable_pre () throw (ShogunException)
 
virtual void load_serializable_post () throw (ShogunException)
 
virtual void save_serializable_pre () throw (ShogunException)
 
virtual void save_serializable_post () throw (ShogunException)
 

Protected 属性

int32_t m_num_maps
 
int32_t m_input_width
 
int32_t m_input_height
 
int32_t m_input_num_channels
 
int32_t m_radius_x
 
int32_t m_radius_y
 
int32_t m_pooling_width
 
int32_t m_pooling_height
 
int32_t m_stride_x
 
int32_t m_stride_y
 
EConvMapActivationFunction m_activation_function
 
SGMatrix< float64_tm_convolution_output
 
SGMatrix< float64_tm_convolution_output_gradients
 
SGMatrix< float64_tm_max_indices
 
int32_t m_num_neurons
 
int32_t m_width
 
int32_t m_height
 
int32_t m_num_parameters
 
SGVector< int32_t > m_input_indices
 
SGVector< int32_t > m_input_sizes
 
int32_t m_batch_size
 
SGMatrix< float64_tm_activations
 
SGMatrix< float64_tm_activation_gradients
 
SGMatrix< float64_tm_local_gradients
 
SGMatrix< bool > m_dropout_mask
 

构造及析构函数说明

default constructor

在文件 NeuralConvolutionalLayer.cpp40 行定义.

CNeuralConvolutionalLayer ( EConvMapActivationFunction  function,
int32_t  num_maps,
int32_t  radius_x,
int32_t  radius_y,
int32_t  pooling_width = 1,
int32_t  pooling_height = 1,
int32_t  stride_x = 1,
int32_t  stride_y = 1 
)

Constuctor

参数
functionActivation function
num_mapsNumber of feature maps
radius_xRadius of the convolution filter on the x (width) axis. The filter size on the x-axis equals (2*radius_x+1)
radius_yRadius of the convolution filter on the y (height) axis. The filter size on the y-axis equals (2*radius_y+1)
pooling_widthWidth of the pooling region
pooling_heightHeight of the pooling region
stride_xStride in the x direction for convolution
stride_yStride in the y direction for convolution

在文件 NeuralConvolutionalLayer.cpp45 行定义.

virtual ~CNeuralConvolutionalLayer ( )
virtual

在文件 NeuralConvolutionalLayer.h91 行定义.

成员函数说明

void build_gradient_parameter_dictionary ( CMap< TParameter *, CSGObject * > *  dict)
inherited

Builds a dictionary of all parameters in SGObject as well of those of SGObjects that are parameters of this object. Dictionary maps parameters to the objects that own them.

参数
dictdictionary of parameters to be built.

在文件 SGObject.cpp1243 行定义.

CSGObject * clone ( )
virtualinherited

Creates a clone of the current object. This is done via recursively traversing all parameters, which corresponds to a deep copy. Calling equals on the cloned object always returns true although none of the memory of both objects overlaps.

返回
an identical copy of the given object, which is disjoint in memory. NULL if the clone fails. Note that the returned object is SG_REF'ed

在文件 SGObject.cpp1360 行定义.

void compute_activations ( SGVector< float64_t parameters,
CDynamicObjectArray layers 
)
virtual

Computes the activations of the neurons in this layer, results should be stored in m_activations. To be used only with non-input layers

参数
parametersVector of size get_num_parameters(), contains the parameters of the layer
layersArray of layers that form the network that this layer is being used with

重载 CNeuralLayer .

在文件 NeuralConvolutionalLayer.cpp146 行定义.

virtual void compute_activations ( SGMatrix< float64_t inputs)
virtualinherited

Computes the activations of the neurons in this layer, results should be stored in m_activations. To be used only with input layers

参数
inputsactivations of the neurons in the previous layer, matrix of size previous_layer_num_neurons * batch_size

CNeuralInputLayer 重载.

在文件 NeuralLayer.h153 行定义.

virtual float64_t compute_contraction_term ( SGVector< float64_t parameters)
virtualinherited

Computes

\[ \frac{\lambda}{N} \sum_{k=0}^{N-1} \left \| J(x_k) \right \|^2_F \]

where \( \left \| J(x_k)) \right \|^2_F \) is the Frobenius norm of the Jacobian of the activations of the hidden layer with respect to its inputs, \( N \) is the batch size, and \( \lambda \) is the contraction coefficient.

Should be implemented by layers that support being used as a hidden layer in a contractive autoencoder.

参数
parametersVector of size get_num_parameters(), contains the parameters of the layer

CNeuralLinearLayer, CNeuralLogisticLayer , 以及 CNeuralRectifiedLinearLayer 重载.

在文件 NeuralLayer.h242 行定义.

float64_t compute_error ( SGMatrix< float64_t targets)
virtual

Computes the error between the layer's current activations and the given target activations. Should only be used with output layers

参数
targetsdesired values for the layer's activations, matrix of size num_neurons*batch_size

重载 CNeuralLayer .

在文件 NeuralConvolutionalLayer.cpp224 行定义.

void compute_gradients ( SGVector< float64_t parameters,
SGMatrix< float64_t targets,
CDynamicObjectArray layers,
SGVector< float64_t parameter_gradients 
)
virtual

Computes the gradients that are relevent to this layer:

  • The gradients of the error with respect to the layer's parameters -The gradients of the error with respect to the layer's inputs

    Input gradients for layer i that connects into this layer as input are added to m_layers.element(i).get_activation_gradients()

    Deriving classes should make sure to account for dropout [Hinton, 2012] during gradient computations

    参数
    parametersVector of size get_num_parameters(), contains the parameters of the layer
    targetsa matrix of size num_neurons*batch_size. If the layer is being used as an output layer, targets is the desired values for the layer's activations, otherwise it's an empty matrix
    layersArray of layers that form the network that this layer is being used with
    parameter_gradientsVector of size get_num_parameters(). To be filled with gradients of the error with respect to each parameter of the layer

重载 CNeuralLayer .

在文件 NeuralConvolutionalLayer.cpp171 行定义.

CSGObject * deep_copy ( ) const
virtualinherited

A deep copy. All the instance variables will also be copied.

在文件 SGObject.cpp200 行定义.

void dropout_activations ( )
virtualinherited

Applies dropout [Hinton, 2012] to the activations of the layer

If is_training is true, fills m_dropout_mask with random values (according to dropout_prop) and multiplies it into the activations, otherwise, multiplies the activations by (1-dropout_prop) to compensate for using dropout during training

在文件 NeuralLayer.cpp90 行定义.

void enforce_max_norm ( SGVector< float64_t parameters,
float64_t  max_norm 
)
virtual

Constrains the weights of each neuron in the layer to have an L2 norm of at most max_norm

参数
parameterspointer to the layer's parameters, array of size get_num_parameters()
max_normmaximum allowable norm for a neuron's weights

重载 CNeuralLayer .

在文件 NeuralConvolutionalLayer.cpp235 行定义.

bool equals ( CSGObject other,
float64_t  accuracy = 0.0,
bool  tolerant = false 
)
virtualinherited

Recursively compares the current SGObject to another one. Compares all registered numerical parameters, recursion upon complex (SGObject) parameters. Does not compare pointers!

May be overwritten but please do with care! Should not be necessary in most cases.

参数
otherobject to compare with
accuracyaccuracy to use for comparison (optional)
tolerantallows linient check on float equality (within accuracy)
返回
true if all parameters were equal, false if not

在文件 SGObject.cpp1264 行定义.

virtual SGMatrix<float64_t> get_activation_gradients ( )
virtualinherited

Gets the layer's activation gradients, a matrix of size num_neurons * batch_size

返回
layer's activation gradients

在文件 NeuralLayer.h284 行定义.

virtual SGMatrix<float64_t> get_activations ( )
virtualinherited

Gets the layer's activations, a matrix of size num_neurons * batch_size

返回
layer's activations

在文件 NeuralLayer.h277 行定义.

SGIO * get_global_io ( )
inherited

get the io object

返回
io object

在文件 SGObject.cpp237 行定义.

Parallel * get_global_parallel ( )
inherited

get the parallel object

返回
parallel object

在文件 SGObject.cpp278 行定义.

Version * get_global_version ( )
inherited

get the version object

返回
version object

在文件 SGObject.cpp291 行定义.

virtual int32_t get_height ( )
virtualinherited

Returns the height assuming that the layer's activations are interpreted as images (i.e for convolutional nets)

返回
Height

在文件 NeuralLayer.h265 行定义.

virtual SGMatrix<float64_t> get_local_gradients ( )
virtualinherited

Gets the layer's local gradients, a matrix of size num_neurons * batch_size

返回
layer's local gradients

在文件 NeuralLayer.h294 行定义.

SGStringList< char > get_modelsel_names ( )
inherited
返回
vector of names of all parameters which are registered for model selection

在文件 SGObject.cpp1135 行定义.

char * get_modsel_param_descr ( const char *  param_name)
inherited

Returns description of a given parameter string, if it exists. SG_ERROR otherwise

参数
param_namename of the parameter
返回
description of the parameter

在文件 SGObject.cpp1159 行定义.

index_t get_modsel_param_index ( const char *  param_name)
inherited

Returns index of model selection parameter with provided index

参数
param_namename of model selection parameter
返回
index of model selection parameter with provided name, -1 if there is no such

在文件 SGObject.cpp1172 行定义.

virtual const char* get_name ( ) const
virtual

Returns the name of the SGSerializable instance. It MUST BE the CLASS NAME without the prefixed `C'.

返回
name of the SGSerializable

重载 CNeuralLayer .

在文件 NeuralConvolutionalLayer.h193 行定义.

virtual int32_t get_num_neurons ( )
virtualinherited

Gets the number of neurons in the layer

返回
number of neurons in the layer

在文件 NeuralLayer.h251 行定义.

virtual int32_t get_num_parameters ( )
virtualinherited

Gets the number of parameters used in this layer

返回
number of parameters used in this layer

在文件 NeuralLayer.h271 行定义.

virtual int32_t get_width ( )
virtualinherited

Returns the width assuming that the layer's activations are interpreted as images (i.e for convolutional nets)

返回
Width

在文件 NeuralLayer.h258 行定义.

void initialize ( CDynamicObjectArray layers,
SGVector< int32_t >  input_indices 
)
virtual

Initializes the layer, computes the number of parameters needed for the layer

参数
layersArray of layers that form the network that this layer is being used with
input_indicesIndices of the layers that are connected to this layer as input

重载 CNeuralLayer .

在文件 NeuralConvolutionalLayer.cpp80 行定义.

void initialize_parameters ( SGVector< float64_t parameters,
SGVector< bool >  parameter_regularizable,
float64_t  sigma 
)
virtual

Initializes the layer's parameters. The layer should fill the given arrays with the initial value for its parameters

参数
parametersVector of size get_num_parameters()
parameter_regularizableVector of size get_num_parameters(). This controls which of the layer's parameter are subject to regularization, i.e to turn off regularization for parameter i, set parameter_regularizable[i] = false. This is usally used to turn off regularization for bias parameters.
sigmastandard deviation of the gaussian used to random the parameters

重载 CNeuralLayer .

在文件 NeuralConvolutionalLayer.cpp123 行定义.

bool is_generic ( EPrimitiveType *  generic) const
virtualinherited

If the SGSerializable is a class template then TRUE will be returned and GENERIC is set to the type of the generic.

参数
genericset to the type of the generic if returning TRUE
返回
TRUE if a class template.

在文件 SGObject.cpp297 行定义.

virtual bool is_input ( )
virtualinherited

returns true if the layer is an input layer. Input layers are the root layers of a network, that is, they don't receive signals from other layers, they receive signals from the inputs features to the network.

Local and activation gradients are not computed for input layers

CNeuralInputLayer 重载.

在文件 NeuralLayer.h127 行定义.

DynArray< TParameter * > * load_all_file_parameters ( int32_t  file_version,
int32_t  current_version,
CSerializableFile file,
const char *  prefix = "" 
)
inherited

maps all parameters of this instance to the provided file version and loads all parameter data from the file into an array, which is sorted (basically calls load_file_parameter(...) for all parameters and puts all results into a sorted array)

参数
file_versionparameter version of the file
current_versionversion from which mapping begins (you want to use Version::get_version_parameter() for this in most cases)
filefile to load from
prefixprefix for members
返回
(sorted) array of created TParameter instances with file data

在文件 SGObject.cpp704 行定义.

DynArray< TParameter * > * load_file_parameters ( const SGParamInfo param_info,
int32_t  file_version,
CSerializableFile file,
const char *  prefix = "" 
)
inherited

loads some specified parameters from a file with a specified version The provided parameter info has a version which is recursively mapped until the file parameter version is reached. Note that there may be possibly multiple parameters in the mapping, therefore, a set of TParameter instances is returned

参数
param_infoinformation of parameter
file_versionparameter version of the file, must be <= provided parameter version
filefile to load from
prefixprefix for members
返回
new array with TParameter instances with the attached data

在文件 SGObject.cpp545 行定义.

bool load_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = Version::get_version_parameter() 
)
virtualinherited

Load this object from file. If it will fail (returning FALSE) then this object will contain inconsistent data and should not be used!

参数
filewhere to load from
prefixprefix for members
param_version(optional) a parameter version different to (this is mainly for testing, better do not use)
返回
TRUE if done, otherwise FALSE

在文件 SGObject.cpp374 行定义.

void load_serializable_post ( )
throw (ShogunException
)
protectedvirtualinherited

Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_POST is called.

异常
ShogunExceptionwill be thrown if an error occurs.

CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel , 以及 CExponentialKernel 重载.

在文件 SGObject.cpp1062 行定义.

void load_serializable_pre ( )
throw (ShogunException
)
protectedvirtualinherited

Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_PRE is called.

异常
ShogunExceptionwill be thrown if an error occurs.

CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool > , 以及 CDynamicObjectArray 重载.

在文件 SGObject.cpp1057 行定义.

void map_parameters ( DynArray< TParameter * > *  param_base,
int32_t &  base_version,
DynArray< const SGParamInfo * > *  target_param_infos 
)
inherited

Takes a set of TParameter instances (base) with a certain version and a set of target parameter infos and recursively maps the base level wise to the current version using CSGObject::migrate(...). The base is replaced. After this call, the base version containing parameters should be of same version/type as the initial target parameter infos. Note for this to work, the migrate methods and all the internal parameter mappings have to match

参数
param_baseset of TParameter instances that are mapped to the provided target parameter infos
base_versionversion of the parameter base
target_param_infosset of SGParamInfo instances that specify the target parameter base

在文件 SGObject.cpp742 行定义.

TParameter * migrate ( DynArray< TParameter * > *  param_base,
const SGParamInfo target 
)
protectedvirtualinherited

creates a new TParameter instance, which contains migrated data from the version that is provided. The provided parameter data base is used for migration, this base is a collection of all parameter data of the previous version. Migration is done FROM the data in param_base TO the provided param info Migration is always one version step. Method has to be implemented in subclasses, if no match is found, base method has to be called.

If there is an element in the param_base which equals the target, a copy of the element is returned. This represents the case when nothing has changed and therefore, the migrate method is not overloaded in a subclass

参数
param_baseset of TParameter instances to use for migration
targetparameter info for the resulting TParameter
返回
a new TParameter instance with migrated data from the base of the type which is specified by the target parameter

在文件 SGObject.cpp949 行定义.

void one_to_one_migration_prepare ( DynArray< TParameter * > *  param_base,
const SGParamInfo target,
TParameter *&  replacement,
TParameter *&  to_migrate,
char *  old_name = NULL 
)
protectedvirtualinherited

This method prepares everything for a one-to-one parameter migration. One to one here means that only ONE element of the parameter base is needed for the migration (the one with the same name as the target). Data is allocated for the target (in the type as provided in the target SGParamInfo), and a corresponding new TParameter instance is written to replacement. The to_migrate pointer points to the single needed TParameter instance needed for migration. If a name change happened, the old name may be specified by old_name. In addition, the m_delete_data flag of to_migrate is set to true. So if you want to migrate data, the only thing to do after this call is converting the data in the m_parameter fields. If unsure how to use - have a look into an example for this. (base_migration_type_conversion.cpp for example)

参数
param_baseset of TParameter instances to use for migration
targetparameter info for the resulting TParameter
replacement(used as output) here the TParameter instance which is returned by migration is created into
to_migratethe only source that is used for migration
old_namewith this parameter, a name change may be specified

在文件 SGObject.cpp889 行定义.

bool parameter_hash_changed ( )
virtualinherited
返回
whether parameter combination has changed since last update

在文件 SGObject.cpp263 行定义.

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

在文件 SGObject.cpp1111 行定义.

void print_serializable ( const char *  prefix = "")
virtualinherited

prints registered parameters out

参数
prefixprefix for members

在文件 SGObject.cpp309 行定义.

bool save_serializable ( CSerializableFile file,
const char *  prefix = "",
int32_t  param_version = Version::get_version_parameter() 
)
virtualinherited

Save this object to file.

参数
filewhere to save the object; will be closed during returning if PREFIX is an empty string.
prefixprefix for members
param_version(optional) a parameter version different to (this is mainly for testing, better do not use)
返回
TRUE if done, otherwise FALSE

在文件 SGObject.cpp315 行定义.

void save_serializable_post ( )
throw (ShogunException
)
protectedvirtualinherited

Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_POST is called.

异常
ShogunExceptionwill be thrown if an error occurs.

CKernel 重载.

在文件 SGObject.cpp1072 行定义.

void save_serializable_pre ( )
throw (ShogunException
)
protectedvirtualinherited

Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_PRE is called.

异常
ShogunExceptionwill be thrown if an error occurs.

CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool > , 以及 CDynamicObjectArray 重载.

在文件 SGObject.cpp1067 行定义.

void set_batch_size ( int32_t  batch_size)
virtual

Sets the batch_size and allocates memory for m_activations and m_input_gradients accordingly. Must be called before forward or backward propagation is performed

参数
batch_sizenumber of training/test cases the network is currently working with

重载 CNeuralLayer .

在文件 NeuralConvolutionalLayer.cpp62 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp42 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp47 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp52 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp57 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp62 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp67 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp72 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp77 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp82 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp87 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp92 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp97 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp102 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp107 行定义.

void set_generic ( )
inherited

在文件 SGObject.cpp112 行定义.

void set_generic ( )
inherited

set generic type to T

void set_global_io ( SGIO io)
inherited

set the io object

参数
ioio object to use

在文件 SGObject.cpp230 行定义.

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

参数
parallelparallel object to use

在文件 SGObject.cpp243 行定义.

void set_global_version ( Version version)
inherited

set the version object

参数
versionversion object to use

在文件 SGObject.cpp284 行定义.

CSGObject * shallow_copy ( ) const
virtualinherited

A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.

CGaussianKernel 重载.

在文件 SGObject.cpp194 行定义.

void unset_generic ( )
inherited

unset generic type

this has to be called in classes specializing a template class

在文件 SGObject.cpp304 行定义.

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

在文件 SGObject.cpp250 行定义.

类成员变量说明

ENLAutoencoderPosition autoencoder_position
inherited

For autoencoders, specifies the position of the layer in the autoencoder, i.e an encoding layer or a decoding layer. Default value is NLAP_NONE

在文件 NeuralLayer.h327 行定义.

float64_t contraction_coefficient
inherited

For hidden layers in a contractive autoencoders [Rifai, 2011] a term:

\[ \frac{\lambda}{N} \sum_{k=0}^{N-1} \left \| J(x_k) \right \|^2_F \]

is added to the error, where \( \left \| J(x_k)) \right \|^2_F \) is the Frobenius norm of the Jacobian of the activations of the hidden layer with respect to its inputs, \( N \) is the batch size, and \( \lambda \) is the contraction coefficient.

Default value is 0.0.

在文件 NeuralLayer.h322 行定义.

float64_t dropout_prop
inherited

probabilty of dropping out a neuron in the layer

在文件 NeuralLayer.h311 行定义.

SGIO* io
inherited

io

在文件 SGObject.h496 行定义.

bool is_training
inherited

Should be true if the layer is currently used during training initial value is false

在文件 NeuralLayer.h308 行定义.

EConvMapActivationFunction m_activation_function
protected

The map's activation function

在文件 NeuralConvolutionalLayer.h230 行定义.

SGMatrix<float64_t> m_activation_gradients
protectedinherited

gradients of the error with respect to the layer's inputs size previous_layer_num_neurons * batch_size

在文件 NeuralLayer.h365 行定义.

SGMatrix<float64_t> m_activations
protectedinherited

activations of the neurons in this layer size num_neurons * batch_size

在文件 NeuralLayer.h360 行定义.

int32_t m_batch_size
protectedinherited

number of training/test cases the network is currently working with

在文件 NeuralLayer.h355 行定义.

SGMatrix<float64_t> m_convolution_output
protected

Holds the output of convolution

在文件 NeuralConvolutionalLayer.h233 行定义.

SGMatrix<float64_t> m_convolution_output_gradients
protected

Gradients of the error with respect to the convolution's output

在文件 NeuralConvolutionalLayer.h236 行定义.

SGMatrix<bool> m_dropout_mask
protectedinherited

binary mask that determines whether a neuron will be kept or dropped out during the current iteration of training size num_neurons * batch_size

在文件 NeuralLayer.h377 行定义.

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

在文件 SGObject.h511 行定义.

uint32_t m_hash
inherited

Hash of parameter values

在文件 SGObject.h517 行定义.

int32_t m_height
protectedinherited

Width of the image (if the layer's activations are to be interpreted as images. Default value is 1

在文件 NeuralLayer.h341 行定义.

int32_t m_input_height
protected

Height of the input

在文件 NeuralConvolutionalLayer.h206 行定义.

SGVector<int32_t> m_input_indices
protectedinherited

Indices of the layers that are connected to this layer as input

在文件 NeuralLayer.h347 行定义.

int32_t m_input_num_channels
protected

Total number channels in the inputs

在文件 NeuralConvolutionalLayer.h209 行定义.

SGVector<int32_t> m_input_sizes
protectedinherited

Number of neurons in the layers that are connected to this layer as input

在文件 NeuralLayer.h352 行定义.

int32_t m_input_width
protected

Width of the input

在文件 NeuralConvolutionalLayer.h203 行定义.

SGMatrix<float64_t> m_local_gradients
protectedinherited

gradients of the error with respect to the layer's pre-activations, this is usually used as a buffer when computing the input gradients size num_neurons * batch_size

在文件 NeuralLayer.h371 行定义.

SGMatrix<float64_t> m_max_indices
protected

Row indices of the max elements for each pooling region

在文件 NeuralConvolutionalLayer.h239 行定义.

Parameter* m_model_selection_parameters
inherited

model selection parameters

在文件 SGObject.h508 行定义.

int32_t m_num_maps
protected

Number of feature maps

在文件 NeuralConvolutionalLayer.h200 行定义.

int32_t m_num_neurons
protectedinherited

Number of neurons in this layer

在文件 NeuralLayer.h331 行定义.

int32_t m_num_parameters
protectedinherited

Number of neurons in this layer

在文件 NeuralLayer.h344 行定义.

ParameterMap* m_parameter_map
inherited

map for different parameter versions

在文件 SGObject.h514 行定义.

Parameter* m_parameters
inherited

parameters

在文件 SGObject.h505 行定义.

int32_t m_pooling_height
protected

Height of the pooling region

在文件 NeuralConvolutionalLayer.h221 行定义.

int32_t m_pooling_width
protected

Width of the pooling region

在文件 NeuralConvolutionalLayer.h218 行定义.

int32_t m_radius_x
protected

Radius of the convolution filter on the x (width) axis

在文件 NeuralConvolutionalLayer.h212 行定义.

int32_t m_radius_y
protected

Radius of the convolution filter on the y (height) axis

在文件 NeuralConvolutionalLayer.h215 行定义.

int32_t m_stride_x
protected

Stride in the x direction

在文件 NeuralConvolutionalLayer.h224 行定义.

int32_t m_stride_y
protected

Stride in the y direcetion

在文件 NeuralConvolutionalLayer.h227 行定义.

int32_t m_width
protectedinherited

Width of the image (if the layer's activations are to be interpreted as images. Default value is m_num_neurons

在文件 NeuralLayer.h336 行定义.

Parallel* parallel
inherited

parallel

在文件 SGObject.h499 行定义.

Version* version
inherited

version

在文件 SGObject.h502 行定义.


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