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SHOGUN
4.1.0
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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.h 第 75 行定义.
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, EInitializationMode initialization_mode=NORMAL) | |
| virtual | ~CNeuralConvolutionalLayer () |
| virtual void | set_batch_size (int32_t batch_size) |
| virtual void | initialize_neural_layer (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 void | set_num_neurons (int32_t 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 SGVector< int32_t > | get_input_indices () |
| 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 () |
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| void | set_generic () |
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| 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="") |
| virtual bool | load_serializable (CSerializableFile *file, const char *prefix="") |
| 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 () |
Protected 成员函数 | |
| 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_t > | m_convolution_output |
| SGMatrix< float64_t > | m_convolution_output_gradients |
| SGMatrix< float64_t > | m_max_indices |
| EInitializationMode | m_initialization_mode |
| 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_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 NeuralConvolutionalLayer.cpp 第 40 行定义.
| CNeuralConvolutionalLayer | ( | EConvMapActivationFunction | function, |
| int32_t | num_maps, | ||
| int32_t | radius_x, | ||
| int32_t | radius_y, | ||
| int32_t | pooling_width = 1, |
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| int32_t | pooling_height = 1, |
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| int32_t | stride_x = 1, |
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| int32_t | stride_y = 1, |
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| EInitializationMode | initialization_mode = NORMAL |
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| ) |
Constuctor
| function | Activation function |
| num_maps | Number of feature maps |
| radius_x | Radius of the convolution filter on the x (width) axis. The filter size on the x-axis equals (2*radius_x+1) |
| radius_y | Radius of the convolution filter on the y (height) axis. The filter size on the y-axis equals (2*radius_y+1) |
| pooling_width | Width of the pooling region |
| pooling_height | Height of the pooling region |
| stride_x | Stride in the x direction for convolution |
| stride_y | Stride in the y direction for convolution |
在文件 NeuralConvolutionalLayer.cpp 第 45 行定义.
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virtual |
在文件 NeuralConvolutionalLayer.h 第 108 行定义.
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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 597 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 714 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 153 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 CNeuralLayer .
在文件 NeuralConvolutionalLayer.cpp 第 157 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 |
被 CNeuralLinearLayer, CNeuralLogisticLayer , 以及 CNeuralRectifiedLinearLayer 重载.
在文件 NeuralLayer.h 第 242 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 .
在文件 NeuralConvolutionalLayer.cpp 第 235 行定义.
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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
| 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 NeuralConvolutionalLayer.cpp 第 182 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 198 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 90 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 NeuralConvolutionalLayer.cpp 第 246 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 618 行定义.
Gets the layer's activation gradients, a matrix of size num_neurons * batch_size
在文件 NeuralLayer.h 第 294 行定义.
Gets the layer's activations, a matrix of size num_neurons * batch_size
在文件 NeuralLayer.h 第 287 行定义.
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Returns the height assuming that the layer's activations are interpreted as images (i.e for convolutional nets)
在文件 NeuralLayer.h 第 265 行定义.
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Gets the indices of the layers that are connected to this layer as input
在文件 NeuralLayer.h 第 313 行定义.
Gets the layer's local gradients, a matrix of size num_neurons * batch_size
在文件 NeuralLayer.h 第 304 行定义.
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在文件 SGObject.cpp 第 498 行定义.
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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 522 行定义.
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Returns index of model selection parameter with provided index
| param_name | name of model selection parameter |
在文件 SGObject.cpp 第 535 行定义.
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Returns the name of the SGSerializable instance. It MUST BE the CLASS NAME without the prefixed `C'.
重载 CNeuralLayer .
在文件 NeuralConvolutionalLayer.h 第 210 行定义.
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Gets the number of neurons in the layer
在文件 NeuralLayer.h 第 251 行定义.
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virtualinherited |
Gets the number of parameters used in this layer
在文件 NeuralLayer.h 第 281 行定义.
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Returns the width assuming that the layer's activations are interpreted as images (i.e for convolutional nets)
在文件 NeuralLayer.h 第 258 行定义.
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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 NeuralConvolutionalLayer.cpp 第 82 行定义.
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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 NeuralConvolutionalLayer.cpp 第 125 行定义.
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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 296 行定义.
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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 127 行定义.
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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 |
在文件 SGObject.cpp 第 369 行定义.
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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 occurs. |
被 CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel , 以及 CExponentialKernel 重载.
在文件 SGObject.cpp 第 426 行定义.
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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 occurs. |
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 421 行定义.
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在文件 SGObject.cpp 第 262 行定义.
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prints all parameter registered for model selection and their type
在文件 SGObject.cpp 第 474 行定义.
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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 |
在文件 SGObject.cpp 第 314 行定义.
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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 occurs. |
被 CKernel 重载.
在文件 SGObject.cpp 第 436 行定义.
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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 occurs. |
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 431 行定义.
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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 |
重载 CNeuralLayer .
在文件 NeuralConvolutionalLayer.cpp 第 64 行定义.
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在文件 SGObject.cpp 第 41 行定义.
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在文件 SGObject.cpp 第 46 行定义.
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在文件 SGObject.cpp 第 51 行定义.
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在文件 SGObject.cpp 第 56 行定义.
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在文件 SGObject.cpp 第 61 行定义.
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在文件 SGObject.cpp 第 66 行定义.
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在文件 SGObject.cpp 第 71 行定义.
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在文件 SGObject.cpp 第 76 行定义.
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在文件 SGObject.cpp 第 81 行定义.
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在文件 SGObject.cpp 第 86 行定义.
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在文件 SGObject.cpp 第 91 行定义.
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在文件 SGObject.cpp 第 96 行定义.
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在文件 SGObject.cpp 第 101 行定义.
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在文件 SGObject.cpp 第 106 行定义.
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在文件 SGObject.cpp 第 111 行定义.
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set generic type to T
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Gets the number of neurons in the layer
| num_neurons | number of neurons in the layer |
在文件 NeuralLayer.h 第 271 行定义.
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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 192 行定义.
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unset generic type
this has to be called in classes specializing a template class
在文件 SGObject.cpp 第 303 行定义.
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Updates the hash of current parameter combination
在文件 SGObject.cpp 第 248 行定义.
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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.h 第 343 行定义.
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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 338 行定义.
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probabilty of dropping out a neuron in the layer
在文件 NeuralLayer.h 第 327 行定义.
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io
在文件 SGObject.h 第 369 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 324 行定义.
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The map's activation function
在文件 NeuralConvolutionalLayer.h 第 247 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 381 行定义.
activations of the neurons in this layer size num_neurons * batch_size
在文件 NeuralLayer.h 第 376 行定义.
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number of training/test cases the network is currently working with
在文件 NeuralLayer.h 第 371 行定义.
Holds the output of convolution
在文件 NeuralConvolutionalLayer.h 第 250 行定义.
Gradients of the error with respect to the convolution's output
在文件 NeuralConvolutionalLayer.h 第 253 行定义.
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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 393 行定义.
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parameters wrt which we can compute gradients
在文件 SGObject.h 第 384 行定义.
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Hash of parameter values
在文件 SGObject.h 第 387 行定义.
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Width of the image (if the layer's activations are to be interpreted as images. Default value is 1
在文件 NeuralLayer.h 第 357 行定义.
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Parameters initialization mode
在文件 NeuralConvolutionalLayer.h 第 259 行定义.
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Height of the input
在文件 NeuralConvolutionalLayer.h 第 223 行定义.
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Indices of the layers that are connected to this layer as input
在文件 NeuralLayer.h 第 363 行定义.
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Total number channels in the inputs
在文件 NeuralConvolutionalLayer.h 第 226 行定义.
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Number of neurons in the layers that are connected to this layer as input
在文件 NeuralLayer.h 第 368 行定义.
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Width of the input
在文件 NeuralConvolutionalLayer.h 第 220 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 387 行定义.
Row indices of the max elements for each pooling region
在文件 NeuralConvolutionalLayer.h 第 256 行定义.
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model selection parameters
在文件 SGObject.h 第 381 行定义.
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Number of feature maps
在文件 NeuralConvolutionalLayer.h 第 217 行定义.
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Number of neurons in this layer
在文件 NeuralLayer.h 第 347 行定义.
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Number of neurons in this layer
在文件 NeuralLayer.h 第 360 行定义.
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parameters
在文件 SGObject.h 第 378 行定义.
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Height of the pooling region
在文件 NeuralConvolutionalLayer.h 第 238 行定义.
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Width of the pooling region
在文件 NeuralConvolutionalLayer.h 第 235 行定义.
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Radius of the convolution filter on the x (width) axis
在文件 NeuralConvolutionalLayer.h 第 229 行定义.
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Radius of the convolution filter on the y (height) axis
在文件 NeuralConvolutionalLayer.h 第 232 行定义.
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Stride in the x direction
在文件 NeuralConvolutionalLayer.h 第 241 行定义.
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Stride in the y direcetion
在文件 NeuralConvolutionalLayer.h 第 244 行定义.
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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.h 第 352 行定义.
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parallel
在文件 SGObject.h 第 372 行定义.
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version
在文件 SGObject.h 第 375 行定义.
