Specifies the parameters for the InnerProductLayer. More...

Inheritance diagram for MyCaffe.param.InnerProductParameter:

Public Member Functions
	InnerProductParameter ()
	Constructor for the parameter. More...

override object	Load (System.IO.BinaryReader br, bool bNewInstance=true)
	Load the parameter from a binary reader. More...

override void	Copy (LayerParameterBase src)
	Copy on parameter to another. More...

override LayerParameterBase	Clone ()
	Creates a new copy of this instance of the parameter. More...

override RawProto	ToProto (string strName)
	Convert the parameter into a RawProto. More...

Public Member Functions inherited from MyCaffe.param.LayerParameterBase
	LayerParameterBase ()
	Constructor for the parameter. More...

virtual string	PrepareRunModelInputs ()
	This method gives derivative classes a chance specify model inputs required by the run model. More...

virtual void	PrepareRunModel (LayerParameter p)
	This method gives derivative classes a chance to prepare the layer for a run-model. More...

void	Save (BinaryWriter bw)
	Save this parameter to a binary writer. More...

abstract object	Load (BinaryReader br, bool bNewInstance=true)
	Load the parameter from a binary reader. More...

Public Member Functions inherited from MyCaffe.basecode.BaseParameter
	BaseParameter ()
	Constructor for the parameter. More...

virtual bool	Compare (BaseParameter p)
	Compare this parameter to another parameter. More...

Static Public Member Functions
static InnerProductParameter	FromProto (RawProto rp)
	Parses the parameter from a RawProto. More...

Static Public Member Functions inherited from MyCaffe.basecode.BaseParameter
static double	ParseDouble (string strVal)
	Parse double values using the US culture if the decimal separator = '.', then using the native culture, and if then lastly trying the US culture to handle prototypes containing '.' as the separator, yet parsed in a culture that does not use '.' as a decimal. More...

static bool	TryParse (string strVal, out double df)
	Parse double values using the US culture if the decimal separator = '.', then using the native culture, and if then lastly trying the US culture to handle prototypes containing '.' as the separator, yet parsed in a culture that does not use '.' as a decimal. More...

static float	ParseFloat (string strVal)
	Parse float values using the US culture if the decimal separator = '.', then using the native culture, and if then lastly trying the US culture to handle prototypes containing '.' as the separator, yet parsed in a culture that does not use '.' as a decimal. More...

static bool	TryParse (string strVal, out float f)
	Parse doufloatble values using the US culture if the decimal separator = '.', then using the native culture, and if then lastly trying the US culture to handle prototypes containing '.' as the separator, yet parsed in a culture that does not use '.' as a decimal. More...

Properties
bool	output_contains_predictions `[getset]`
	Specifies that the output contains predictions and that the output blob is marked as BLOB_TYPE.PREDICTION. More...

double	bias_grad_scale `[getset]`
	Specifies a scaling value applied to the bias mutliplier and then unapplied after calculating the bias - used to help improve float accuracy (default = 1.0). A value of 1.0 is ignored. More...

bool	enable_noise `[getset]`
	Enable/disable noise in the inner-product layer (default = false). More...

double	sigma_init `[getset]`
	Specifies the initialization value for the sigma weight and sigma bias used when 'enable_noise' = true. More...

uint	num_output `[getset]`
	The number of outputs for the layer. More...

int	min_top_axes `[getset]`
	Optionally, specifies the minimum top axes (default = -1, which ignores this setting). More...

bool	bias_term `[getset]`
	Whether to have bias terms or not. More...

FillerParameter	weight_filler `[getset]`
	The filler for the weights. More...

FillerParameter	bias_filler `[getset]`
	The filler for the bias. More...

int	axis `[getset]`
	Specifies the first axis to be lumped into a single inner product computation; all preceding axes are retained in the output. May be negative to index from the end (e.g., -1 for the last axis) More...

bool	transpose `[getset]`
	Specifies whether to transpose the weight matrix or not. If transpose == true, any operations will be performed on the transpose of the weight matrix. The weight matrix itself is not going to be transposed but rather the transfer flag of operations will be toggled accordingly. More...

Additional Inherited Members
Public Types inherited from MyCaffe.param.LayerParameterBase
enum	LABEL_TYPE { NONE , SINGLE , MULTIPLE , ONLY_ONE }
	Defines the label type. More...

Detailed Description

Specifies the parameters for the InnerProductLayer.

See also: Product-based Neural Networks for User Response Prediction by Yanru Qu, Kan Cai, Weinan Zhang, Yong Yu, Ying Wen, and Jun Wang, 2016.

Definition at line 18 of file InnerProductParameter.cs.

Constructor & Destructor Documentation

◆ InnerProductParameter()

MyCaffe.param.InnerProductParameter.InnerProductParameter ( )

Constructor for the parameter.

Definition at line 33 of file InnerProductParameter.cs.

Member Function Documentation

◆ Clone()

override LayerParameterBase MyCaffe.param.InnerProductParameter.Clone ( )

virtual

Creates a new copy of this instance of the parameter.

Returns: A new instance of this parameter is returned.

Implements MyCaffe.param.LayerParameterBase.

Definition at line 196 of file InnerProductParameter.cs.

◆ Copy()

override void MyCaffe.param.InnerProductParameter.Copy ( LayerParameterBase src )

virtual

Copy on parameter to another.

Parameters

src	Specifies the parameter to copy.

Implements MyCaffe.param.LayerParameterBase.

Definition at line 173 of file InnerProductParameter.cs.

◆ FromProto()

static InnerProductParameter MyCaffe.param.InnerProductParameter.FromProto ( RawProto rp )

static

Parses the parameter from a RawProto.

Parameters

rp	Specifies the RawProto to parse.

Returns: A new instance of the parameter is returned.

Definition at line 249 of file InnerProductParameter.cs.

◆ Load()

override object MyCaffe.param.InnerProductParameter.Load	(	System.IO.BinaryReader	br,
		bool	bNewInstance = `true`
	)

Load the parameter from a binary reader.

Parameters

br	Specifies the binary reader.
bNewInstance	When true a new instance is created (the default), otherwise the existing instance is loaded from the binary reader.

Returns: Returns an instance of the parameter.

Definition at line 161 of file InnerProductParameter.cs.

◆ ToProto()

override RawProto MyCaffe.param.InnerProductParameter.ToProto ( string strName )

virtual

Convert the parameter into a RawProto.

Parameters

strName Specifies the name to associate with the RawProto.

Returns: The new RawProto is returned.

Implements MyCaffe.basecode.BaseParameter.

Definition at line 208 of file InnerProductParameter.cs.

Property Documentation

◆ axis

int MyCaffe.param.InnerProductParameter.axis

getset

Specifies the first axis to be lumped into a single inner product computation; all preceding axes are retained in the output. May be negative to index from the end (e.g., -1 for the last axis)

Definition at line 141 of file InnerProductParameter.cs.

◆ bias_filler

FillerParameter MyCaffe.param.InnerProductParameter.bias_filler

getset

The filler for the bias.

Definition at line 129 of file InnerProductParameter.cs.

◆ bias_grad_scale

double MyCaffe.param.InnerProductParameter.bias_grad_scale

getset

Specifies a scaling value applied to the bias mutliplier and then unapplied after calculating the bias - used to help improve float accuracy (default = 1.0). A value of 1.0 is ignored.

Definition at line 51 of file InnerProductParameter.cs.

◆ bias_term

bool MyCaffe.param.InnerProductParameter.bias_term

getset

Whether to have bias terms or not.

Definition at line 107 of file InnerProductParameter.cs.

◆ enable_noise

bool MyCaffe.param.InnerProductParameter.enable_noise

getset

Enable/disable noise in the inner-product layer (default = false).

When enabled, noise is only used during the training phase.

Definition at line 64 of file InnerProductParameter.cs.

◆ min_top_axes

int MyCaffe.param.InnerProductParameter.min_top_axes

getset

Optionally, specifies the minimum top axes (default = -1, which ignores this setting).

NOTE: The Deconvolution Layer requires 'min_top_axes' = 4.

Definition at line 97 of file InnerProductParameter.cs.

◆ num_output

uint MyCaffe.param.InnerProductParameter.num_output

getset

The number of outputs for the layer.

Definition at line 84 of file InnerProductParameter.cs.

◆ output_contains_predictions

bool MyCaffe.param.InnerProductParameter.output_contains_predictions

getset

Specifies that the output contains predictions and that the output blob is marked as BLOB_TYPE.PREDICTION.

Definition at line 41 of file InnerProductParameter.cs.

◆ sigma_init

double MyCaffe.param.InnerProductParameter.sigma_init

getset

Specifies the initialization value for the sigma weight and sigma bias used when 'enable_noise' = true.

Definition at line 74 of file InnerProductParameter.cs.

◆ transpose

bool MyCaffe.param.InnerProductParameter.transpose

getset

Specifies whether to transpose the weight matrix or not. If transpose == true, any operations will be performed on the transpose of the weight matrix. The weight matrix itself is not going to be transposed but rather the transfer flag of operations will be toggled accordingly.

Definition at line 154 of file InnerProductParameter.cs.

◆ weight_filler

FillerParameter MyCaffe.param.InnerProductParameter.weight_filler

getset

The filler for the weights.

Definition at line 118 of file InnerProductParameter.cs.

The documentation for this class was generated from the following file:

C:/Data/Data/SS_Projects/Intelligence/GitHub/MyCaffe/MyCaffe/param/InnerProductParameter.cs

Public Member Functions

Static Public Member Functions

Properties

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ InnerProductParameter()

Member Function Documentation

◆ Clone()

◆ Copy()

◆ FromProto()

◆ Load()

◆ ToProto()

Property Documentation

◆ axis

◆ bias_filler

◆ bias_grad_scale

◆ bias_term

◆ enable_noise

◆ min_top_axes

◆ num_output

◆ output_contains_predictions

◆ sigma_init

◆ transpose

◆ weight_filler