Neural layer with rectified linear neurons.
Activations are computed according to max(0,W*x+b) where W is the weight matrix, b is the bias vector, and x is the input vector.
When used as an output layer, a squared error measure is used
在文件 NeuralRectifiedLinearLayer.h 第 49 行定义.
Public 成员函数 | |
CNeuralRectifiedLinearLayer () | |
CNeuralRectifiedLinearLayer (int32_t num_neurons) | |
virtual | ~CNeuralRectifiedLinearLayer () |
virtual void | compute_activations (SGVector< float64_t > parameters, CDynamicObjectArray *layers) |
virtual float64_t | compute_contraction_term (SGVector< float64_t > parameters) |
virtual void | compute_contraction_term_gradients (SGVector< float64_t > parameters, SGVector< float64_t > gradients) |
virtual void | compute_local_gradients (SGMatrix< float64_t > targets) |
virtual const char * | get_name () const |
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 (SGMatrix< float64_t > inputs) |
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 void | set_batch_size (int32_t batch_size) |
virtual bool | is_input () |
virtual void | dropout_activations () |
virtual int32_t | get_num_neurons () |
virtual int32_t | get_num_parameters () |
virtual SGMatrix< float64_t > | get_activations () |
virtual SGMatrix< float64_t > | get_activation_gradients () |
virtual SGMatrix< float64_t > | get_local_gradients () |
virtual CSGObject * | shallow_copy () const |
virtual CSGObject * | deep_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) |
SGIO * | get_global_io () |
void | set_global_parallel (Parallel *parallel) |
Parallel * | get_global_parallel () |
void | set_global_version (Version *version) |
Version * | get_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 CSGObject * | clone () |
Public 属性 | |
bool | is_training |
float64_t | dropout_prop |
float64_t | contraction_coefficient |
SGIO * | io |
Parallel * | parallel |
Version * | version |
Parameter * | m_parameters |
Parameter * | m_model_selection_parameters |
Parameter * | m_gradient_parameters |
ParameterMap * | m_parameter_map |
uint32_t | m_hash |
Protected 成员函数 | |
virtual TParameter * | migrate (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_neurons |
int32_t | m_num_parameters |
SGVector< int32_t > | m_input_indices |
SGVector< int32_t > | m_input_sizes |
int32_t | m_batch_size |
SGMatrix< float64_t > | m_activations |
SGMatrix< float64_t > | m_activation_gradients |
SGMatrix< float64_t > | m_local_gradients |
SGMatrix< bool > | m_dropout_mask |
default constructor
在文件 NeuralRectifiedLinearLayer.cpp 第 40 行定义.
CNeuralRectifiedLinearLayer | ( | int32_t | num_neurons | ) |
Constuctor
num_neurons | Number of neurons in this layer |
在文件 NeuralRectifiedLinearLayer.cpp 第 44 行定义.
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virtual |
在文件 NeuralRectifiedLinearLayer.h 第 61 行定义.
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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.
dict | dictionary of parameters to be built. |
在文件 SGObject.cpp 第 1185 行定义.
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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.
在文件 SGObject.cpp 第 1302 行定义.
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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
parameters | Vector of size get_num_parameters(), contains the parameters of the layer |
layers | Array of layers that form the network that this layer is being used with |
重载 CNeuralLinearLayer .
在文件 NeuralRectifiedLinearLayer.cpp 第 49 行定义.
Computes the activations of the neurons in this layer, results should be stored in m_activations. To be used only with input layers
inputs | activations of the neurons in the previous layer, matrix of size previous_layer_num_neurons * batch_size |
被 CNeuralInputLayer 重载.
在文件 NeuralLayer.h 第 139 行定义.
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.
parameters | Vector of size get_num_parameters(), contains the parameters of the layer |
重载 CNeuralLinearLayer .
在文件 NeuralRectifiedLinearLayer.cpp 第 62 行定义.
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virtual |
Adds the gradients of
\[ \frac{\lambda}{N} \sum_{k=0}^{N-1} \left \| J(x_k) \right \|^2_F \]
to the gradients vector, 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.
parameters | Vector of size get_num_parameters(), contains the parameters of the layer |
gradients | Vector of size get_num_parameters(). Gradients of the contraction term will be added to it |
重载 CNeuralLinearLayer .
在文件 NeuralRectifiedLinearLayer.cpp 第 87 行定义.
Computes the error between the layer's current activations and the given target activations. Should only be used with output layers
targets | desired values for the layer's activations, matrix of size num_neurons*batch_size |
重载 CNeuralLayer .
被 CNeuralSoftmaxLayer 重载.
在文件 NeuralLinearLayer.cpp 第 260 行定义.
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virtualinherited |
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
parameters | Vector of size get_num_parameters(), contains the parameters of the layer |
targets | a 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 |
layers | Array of layers that form the network that this layer is being used with |
parameter_gradients | Vector 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 NeuralLinearLayer.cpp 第 135 行定义.
Computes the gradients of the error with respect to this layer's pre-activations. Results are stored in m_local_gradients.
This is used by compute_gradients() and can be overriden to implement layers with different activation functions
targets | a 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 |
重载 CNeuralLinearLayer .
在文件 NeuralRectifiedLinearLayer.cpp 第 111 行定义.
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virtualinherited |
A deep copy. All the instance variables will also be copied.
在文件 SGObject.cpp 第 146 行定义.
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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.cpp 第 88 行定义.
Constrains the weights of each neuron in the layer to have an L2 norm of at most max_norm
parameters | pointer to the layer's parameters, array of size get_num_parameters() |
max_norm | maximum allowable norm for a neuron's weights |
重载 CNeuralLayer .
在文件 NeuralLinearLayer.cpp 第 271 行定义.
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.
other | object to compare with |
accuracy | accuracy to use for comparison (optional) |
tolerant | allows linient check on float equality (within accuracy) |
在文件 SGObject.cpp 第 1206 行定义.
Gets the layer's activation gradients, a matrix of size num_neurons * batch_size
在文件 NeuralLayer.h 第 256 行定义.
Gets the layer's activations, a matrix of size num_neurons * batch_size
在文件 NeuralLayer.h 第 249 行定义.
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inherited |
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inherited |
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inherited |
Gets the layer's local gradients, a matrix of size num_neurons * batch_size
在文件 NeuralLayer.h 第 266 行定义.
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inherited |
在文件 SGObject.cpp 第 1077 行定义.
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inherited |
Returns description of a given parameter string, if it exists. SG_ERROR otherwise
param_name | name of the parameter |
在文件 SGObject.cpp 第 1101 行定义.
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inherited |
Returns index of model selection parameter with provided index
param_name | name of model selection parameter |
在文件 SGObject.cpp 第 1114 行定义.
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virtual |
Returns the name of the SGSerializable instance. It MUST BE the CLASS NAME without the prefixed `C'.
重载 CNeuralLinearLayer .
在文件 NeuralRectifiedLinearLayer.h 第 120 行定义.
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virtualinherited |
Gets the number of neurons in the layer
在文件 NeuralLayer.h 第 237 行定义.
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virtualinherited |
Gets the number of parameters used in this layer
在文件 NeuralLayer.h 第 243 行定义.
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virtualinherited |
Initializes the layer, computes the number of parameters needed for the layer
layers | Array of layers that form the network that this layer is being used with |
input_indices | Indices of the layers that are connected to this layer as input |
重载 CNeuralLayer .
在文件 NeuralLinearLayer.cpp 第 53 行定义.
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virtualinherited |
Initializes the layer's parameters. The layer should fill the given arrays with the initial value for its parameters
parameters | Vector of size get_num_parameters() |
parameter_regularizable | Vector 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. |
sigma | standard deviation of the gaussian used to random the parameters |
重载 CNeuralLayer .
在文件 NeuralLinearLayer.cpp 第 63 行定义.
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virtualinherited |
If the SGSerializable is a class template then TRUE will be returned and GENERIC is set to the type of the generic.
generic | set to the type of the generic if returning TRUE |
在文件 SGObject.cpp 第 243 行定义.
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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
被 CNeuralInputLayer 重载.
在文件 NeuralLayer.h 第 113 行定义.
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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)
file_version | parameter version of the file |
current_version | version from which mapping begins (you want to use Version::get_version_parameter() for this in most cases) |
file | file to load from |
prefix | prefix for members |
在文件 SGObject.cpp 第 648 行定义.
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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
param_info | information of parameter |
file_version | parameter version of the file, must be <= provided parameter version |
file | file to load from |
prefix | prefix for members |
在文件 SGObject.cpp 第 489 行定义.
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virtualinherited |
Load this object from file. If it will fail (returning FALSE) then this object will contain inconsistent data and should not be used!
file | where to load from |
prefix | prefix for members |
param_version | (optional) a parameter version different to (this is mainly for testing, better do not use) |
在文件 SGObject.cpp 第 320 行定义.
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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.
ShogunException | Will be thrown if an error occurres. |
被 CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel , 以及 CExponentialKernel 重载.
在文件 SGObject.cpp 第 1004 行定义.
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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.
ShogunException | Will be thrown if an error occurres. |
被 CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool > , 以及 CDynamicObjectArray 重载.
在文件 SGObject.cpp 第 999 行定义.
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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
param_base | set of TParameter instances that are mapped to the provided target parameter infos |
base_version | version of the parameter base |
target_param_infos | set of SGParamInfo instances that specify the target parameter base |
在文件 SGObject.cpp 第 686 行定义.
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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
param_base | set of TParameter instances to use for migration |
target | parameter info for the resulting TParameter |
在文件 SGObject.cpp 第 893 行定义.
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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)
param_base | set of TParameter instances to use for migration |
target | parameter info for the resulting TParameter |
replacement | (used as output) here the TParameter instance which is returned by migration is created into |
to_migrate | the only source that is used for migration |
old_name | with this parameter, a name change may be specified |
在文件 SGObject.cpp 第 833 行定义.
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virtualinherited |
在文件 SGObject.cpp 第 209 行定义.
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inherited |
prints all parameter registered for model selection and their type
在文件 SGObject.cpp 第 1053 行定义.
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virtualinherited |
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virtualinherited |
Save this object to file.
file | where to save the object; will be closed during returning if PREFIX is an empty string. |
prefix | prefix for members |
param_version | (optional) a parameter version different to (this is mainly for testing, better do not use) |
在文件 SGObject.cpp 第 261 行定义.
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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.
ShogunException | Will be thrown if an error occurres. |
被 CKernel 重载.
在文件 SGObject.cpp 第 1014 行定义.
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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.
ShogunException | Will be thrown if an error occurres. |
被 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.cpp 第 1009 行定义.
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virtualinherited |
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
batch_size | number of training/test cases the network is currently working with |
被 CNeuralConvolutionalLayer 重载.
在文件 NeuralLayer.cpp 第 73 行定义.
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inherited |
在文件 SGObject.cpp 第 38 行定义.
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inherited |
在文件 SGObject.cpp 第 43 行定义.
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inherited |
在文件 SGObject.cpp 第 48 行定义.
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inherited |
在文件 SGObject.cpp 第 53 行定义.
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inherited |
在文件 SGObject.cpp 第 58 行定义.
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inherited |
在文件 SGObject.cpp 第 63 行定义.
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inherited |
在文件 SGObject.cpp 第 68 行定义.
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inherited |
在文件 SGObject.cpp 第 73 行定义.
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inherited |
在文件 SGObject.cpp 第 78 行定义.
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inherited |
在文件 SGObject.cpp 第 83 行定义.
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inherited |
在文件 SGObject.cpp 第 88 行定义.
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inherited |
在文件 SGObject.cpp 第 93 行定义.
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inherited |
在文件 SGObject.cpp 第 98 行定义.
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inherited |
在文件 SGObject.cpp 第 103 行定义.
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inherited |
在文件 SGObject.cpp 第 108 行定义.
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inherited |
set generic type to T
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inherited |
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inherited |
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inherited |
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virtualinherited |
A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.
被 CGaussianKernel 重载.
在文件 SGObject.cpp 第 140 行定义.
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inherited |
unset generic type
this has to be called in classes specializing a template class
在文件 SGObject.cpp 第 250 行定义.
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virtualinherited |
Updates the hash of current parameter combination
在文件 SGObject.cpp 第 196 行定义.
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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.h 第 294 行定义.
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inherited |
probabilty of dropping out a neuron in the layer
在文件 NeuralLayer.h 第 283 行定义.
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inherited |
io
在文件 SGObject.h 第 461 行定义.
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Should be true if the layer is currently used during training initial value is false
在文件 NeuralLayer.h 第 280 行定义.
gradients of the error with respect to the layer's inputs size previous_layer_num_neurons * batch_size
在文件 NeuralLayer.h 第 322 行定义.
activations of the neurons in this layer size num_neurons * batch_size
在文件 NeuralLayer.h 第 317 行定义.
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protectedinherited |
number of training/test cases the network is currently working with
在文件 NeuralLayer.h 第 312 行定义.
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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.h 第 334 行定义.
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inherited |
parameters wrt which we can compute gradients
在文件 SGObject.h 第 476 行定义.
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inherited |
Hash of parameter values
在文件 SGObject.h 第 482 行定义.
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protectedinherited |
Indices of the layers that are connected to this layer as input
在文件 NeuralLayer.h 第 304 行定义.
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protectedinherited |
Number of neurons in the layers that are connected to this layer as input
在文件 NeuralLayer.h 第 309 行定义.
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.h 第 328 行定义.
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inherited |
model selection parameters
在文件 SGObject.h 第 473 行定义.
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protectedinherited |
Number of neurons in this layer
在文件 NeuralLayer.h 第 298 行定义.
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protectedinherited |
Number of neurons in this layer
在文件 NeuralLayer.h 第 301 行定义.
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inherited |
map for different parameter versions
在文件 SGObject.h 第 479 行定义.
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parameters
在文件 SGObject.h 第 470 行定义.
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parallel
在文件 SGObject.h 第 464 行定义.
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version
在文件 SGObject.h 第 467 行定义.