The RecurrentLayer is an abstract class for implementing recurrent behavior inside of an unrolled newtork. This layer type cannot be instantiated – instead, you should use one of teh implementations which defines the recurrent architecture, such as RNNLayer or LSTMLayer. This layer is initialized with the MyCaffe.param.RecurrentParameter. More...

Inheritance diagram for MyCaffe.layers.RecurrentLayer< T >:

Public Member Functions
	RecurrentLayer (CudaDnn< T > cuda, Log log, LayerParameter p, CancelEvent evtCancel)
	The RecurrentLayer constructor. More...

override void	SetOnDebug (EventHandler< GetWorkBlobArgs< T > > fn)
	Set the OnDebug event on the unrolled net. More...

override void	ResetOnDebug (EventHandler< GetWorkBlobArgs< T > > fn)
	Reset the OnDebug event, disabling it on the unrolled net. More...

override void	LayerSetUp (BlobCollection< T > colBottom, BlobCollection< T > colTop)
	Setup the layer. More...

override void	Reshape (BlobCollection< T > colBottom, BlobCollection< T > colTop)
	Reshape the bottom (input) and top (output) blobs. More...

virtual void	Reset ()
	Reset the hidden state of the net by zeroing out all recurrent outputs. More...

override bool	AllowForceBackward (int nBottomIdx)
	Returns true for all but the bottom index = 1, for you can't propagate to the sequence continuation indicators. More...

Public Member Functions inherited from MyCaffe.layers.Layer< T >
	Layer (CudaDnn< T > cuda, Log log, LayerParameter p)
	The Layer constructor. More...

void	Dispose ()
	Releases all GPU and host resources used by the Layer. More...

virtual void	ConnectLoss (LossLayer< T > layer)
	Called to connect the loss OnLoss event to a specified layer (typically the data layer). More...

virtual BlobCollection< T >	PreProcessInput (PropertySet customInput, out int nSeqLen, BlobCollection< T > colBottom=null)
	The PreprocessInput allows derivative data layers to convert a property set of input data into the bottom blob collection used as intput. More...

virtual bool	PreProcessInput (string strEncInput, int? nDecInput, BlobCollection< T > colBottom)
	Preprocess the input data for the RUN phase. More...

virtual List< Tuple< string, int, double > >	PostProcessOutput (Blob< T > blobSofmtax, int nK=1)
	The PostProcessOutput allows derivative data layers to post-process the results, converting them back into text results (e.g., detokenizing). More...

virtual List< Tuple< string, int, double > >	PostProcessLogitsOutput (int nCurIdx, Blob< T > blobLogits, Layer< T > softmax, int nAxis, int nK=1)
	The PostProcessLogitsOutput allows derivative data layers to post-process the results, converting them back into text results (e.g., detokenizing). More...

virtual string	PostProcessFullOutput (Blob< T > blobSoftmax)
	The PostProcessFullOutput allows derivative data layers to post-process the results, usually be detokenizing the data in the blobSoftmax. More...

virtual string	PostProcessOutput (int nIdx)
	Convert the index to the word. More...

virtual bool	ReInitializeParameters (WEIGHT_TARGET target)
	Re-initialize the parameters of the layer. More...

void	SetNetReshapeRequest ()
	Called by the Net when requesting a reshape. More...

void	SetPhase (Phase phase)
	Changes the layer's Phase to the one specified. More...

void	Setup (BlobCollection< T > colBottom, BlobCollection< T > colTop)
	Implements common Layer setup functionality. More...

virtual void	SetNetParameterUsed (NetParameter np)
	This function allows other layers to gather needed information from the NetParameters if any, and is called when initialzing the Net. More...

void	ConvertToBase (BlobCollection< T > col)
	ConvertToBase converts any blobs in a collection that are in half size to the base size. More...

double	Forward (BlobCollection< T > colBottom, BlobCollection< T > colTop)
	Given the bottom (input) Blobs, this function computes the top (output) Blobs and the loss. More...

void	Backward (BlobCollection< T > colTop, List< bool > rgbPropagateDown, BlobCollection< T > colBottom)
	Given the top Blob error gradients, compute the bottom Blob error gradients. More...

double	loss (int nTopIdx)
	Returns the scalar loss associated with the top Blob at a given index. More...

void	set_loss (int nTopIdx, double dfLoss)
	Sets the loss associated with a top Blob at a given index. More...

bool	param_propagate_down (int nParamIdx)
	Returns whether or not the Layer should compute gradients w.r.t. a parameter at a particular index given by a parameter index. More...

void	set_param_propagate_down (int nParamIdx, bool bPropagate)
	Sets whether or not the Layer should compute gradients w.r.t. a parameter at a particular index given by a parameter index. More...

void	SetEnablePassthrough (bool bEnable)
	Enables/disables the pass-through mode. More...

Protected Member Functions
override void	dispose ()
	Releases all GPU and host resources used by the Layer. More...

abstract void	FillUnrolledNet (NetParameter net_param)
	Fills net_param with the recurrent network architecture. Subclasses should define this – see RNNLayer and LSTMLayer for examples. More...

abstract void	RecurrentInputBlobNames (List< string > rgNames)
	Fills names with the names of the 0th timestep recurrent input Blob's. Subclasses should define this – see RNNlayer and LSTMLayer for examples. More...

abstract void	RecurrentInputShapes (List< BlobShape > rgShapes)
	Fills shapes with the shapes of the recurrent input Blob's. Subclassses should define this – see RNNLayer and LSTMLayer for examples. More...

abstract void	RecurrentOutputBlobNames (List< string > rgNames)
	Fills names with the names of the Tth timestep recurrent output Blob's. Subclassses should define this – see RNNLayer and LSTMLayer for examples. More...

abstract void	OutputBlobNames (List< string > rgNames)
	Fills names with the names of the output blobs, concatenated across all timesteps. Should return a name for each top Blob. Subclassses should define this – see RNNLayer and LSTMLayer for examples. More...

override void	setup_internal_blobs (BlobCollection< T > col)
	Derivative layers should add all internal blobws to the 'col' provided. More...

override void	forward (BlobCollection< T > colBottom, BlobCollection< T > colTop)
	Peforms the forward calculation. More...

override void	backward (BlobCollection< T > colTop, List< bool > rgbPropagateDown, BlobCollection< T > colBottom)
	Backward computation. More...

Protected Member Functions inherited from MyCaffe.layers.Layer< T >
void	dispose (ref Layer< T > l)
	Helper method used to dispose internal layers. More...

void	dispose (ref Blob< T > b)
	Helper method used to dispose internal blobs. More...

void	dispose (ref BlobCollection< T > rg, bool bSetToNull=true)
	Dispose the blob collection. More...

GetIterationArgs	getCurrentIteration ()
	Fires the OnGetIteration event to query the current iteration. More...

long	convert_to_full (int nCount, long hMem)
	Convert half memory to full memory. More...

void	convert (BlobCollection< T > col)
	Convert a collection of blobs from / to half size. More...

virtual bool	reshapeNeeded (BlobCollection< T > colBottom, BlobCollection< T > colTop, bool bReset=true)
	Tests the shapes of both the bottom and top blobs and if they are the same as the previous sizing, returns false indicating that no reshape is needed. More...

bool	compareShapes (BlobCollection< T > colBottom, BlobCollection< T > colTop)
	Compare the shapes of the top and bottom and if the same, return true, otherwise false. More...

void	setShapes (BlobCollection< T > colBottom, BlobCollection< T > colTop)
	Set the internal shape sizes - used when determining if a Reshape is necessary. More...

void	CheckBlobCounts (BlobCollection< T > colBottom, BlobCollection< T > colTop)
	Called by the Layer::Setup function to check the number of bottom (input) and top (output) Blobs provided match the expected number of blobs expected via the {EactNum,Min,Max}{Bottom,Top}Blobs functions. More...

void	SetLossWeights (BlobCollection< T > colTop)
	Called by Layer::Setup to initialize the weights associated with any top (output) Blobs in the loss function ans store non-zero loss weights in the diff Blob. More...

LayerParameter	convertLayerParam (LayerParameter pChild, LayerParameter pParent)
	Called to convert a parent LayerParameterEx, used in blob sharing, with a child layer parameter. More...

bool	shareParameter (Blob< T > b, List< int > rgMinShape, bool bAllowEndsWithComparison=false)
	Attempts to share a parameter Blob if another parameter Blob with the same name and accpetable size is found. More...

bool	shareLayerBlob (Blob< T > b, List< int > rgMinShape)
	Attempts to share a Layer Blob if another parameter Blob with the same name and acceptable size is found. More...

bool	shareLayerBlobs (Layer< T > layer)
	Attempts to share the Layer blobs and internal_blobs with matching names and sizes with those in another matching layer. More...

virtual WorkspaceArgs	getWorkspace ()
	Returns the WorkspaceArgs used to share a workspace between Layers. More...

virtual bool	setWorkspace (ulong lSizeInBytes)
	Sets the workspace size (in items) and returns true if set, false otherwise. More...

void	check_nan (Blob< T > b)
	Checks a Blob for NaNs and throws an exception if found. More...

T	convert (double df)
	Converts a double to a generic. More...

T	convert (float f)
	Converts a float to a generic. More...

double	convertD (T df)
	Converts a generic to a double value. More...

float	convertF (T df)
	Converts a generic to a float value. More...

double[]	convertD (T[] rg)
	Converts an array of generic values into an array of double values. More...

T[]	convert (double[] rg)
	Converts an array of double values into an array of generic values. More...

float[]	convertF (T[] rg)
	Converts an array of float values into an array of generic values. More...

T[]	convert (float[] rg)
	Converts an array of float values into an array of generic values. More...

int	val_at (T[] rg, int nIdx)
	Returns the integer value at a given index in a generic array. More...

Size	size_at (Blob< T > b)
	Returns the Size of a given two element Blob, such as one that stores Blob size information. More...

Protected Attributes
int	m_nN
	The number of independent streams to process simultaneously. More...

int	m_nT
	The number of timesteps in the layer's input, and the number of timesteps over which to backpropagate through time. More...

bool	m_bStaticInput
	Whether the layer has a 'static' input copies across all timesteps. More...

Protected Attributes inherited from MyCaffe.layers.Layer< T >
LayerParameter.LayerType	m_type = LayerParameter.LayerType._MAX
	Specifies the Layer type. More...

CudaDnn< T >	m_cuda
	Specifies the CudaDnn connection to Cuda. More...

Log	m_log
	Specifies the Log for output. More...

LayerParameter	m_param
	Specifies the LayerParameter describing the Layer. More...

Phase	m_phase
	Specifies the Phase under which the Layer is run. More...

BlobCollection< T >	m_colBlobs
	Specifies the learnable parameter Blobs of the Layer. More...

BlobCollection< T >	m_colInternalBlobs = new BlobCollection<T>()
	Specifies internal blobs used by the layer. More...

DictionaryMap< bool >	m_rgbParamPropagateDown
	Specifies whether or not to compute the learnable diff of each parameter Blob. More...

DictionaryMap< double >	m_rgLoss
	Specifies the loss values that indeicate whether each top (output) Blob has a non-zero weight in the objective function.. More...

T	m_tOne
	Specifies a generic type equal to 1.0. More...

T	m_tZero
	Specifies a generic type equal to 0.0. More...

bool	m_bEnablePassthrough = false
	Enables/disables the pass-through mode for the layer. Default = false. More...

bool	m_bUseHalfSize = false
	Specifies that the half size of the top (if any) should be converted to the base size. More...

bool	m_bConvertTopOnFwd = false
	Specifies whether or not the layer should convert the top on the forward pass when using half sized memory (typically only done with input data). More...

bool	m_bConvertTopOnBwd = true
	Specifies whether or not to convert the top on the backward pass when using half sized memory (typically not done on loss layers). More...

bool	m_bConvertBottom = true
	Specifies whether or not the layer should convert the bottom when using half sized memory. More...

bool	m_bReshapeOnForwardNeeded = true
	Specifies whether or not the reshape on forward is needed or not. More...

bool	m_bNetReshapeRequest = false
	Specifies whether the reshape is requested from a Net.Reshape call or not. More...

LayerParameter.? LayerType	m_parentLayerType = null
	Specifies the layer type of the parent. More...

Properties
override int	MinBottomBlobs `[get]`
	Returns the minimum number of required bottom (input) Blobs. More...

override int	MaxBottomBlobs `[get]`
	Returns the maximum number of required bottom (input) Blobs: min+1 More...

override int	ExactNumTopBlobs `[get]`
	Returns the min number of required top (output) Blobs. More...

Properties inherited from MyCaffe.layers.Layer< T >
LayerParameter.? LayerType	parent_layer_type `[get]`
	Optionally, specifies the parent layer type (e.g. LOSS, etc.) More...

virtual bool	SupportsPreProcessing `[get]`
	Should return true when PreProcessing methods are overriden. More...

virtual bool	SupportsPostProcessing `[get]`
	Should return true when pre PostProcessing methods are overriden. More...

virtual bool	SupportsPostProcessingLogits `[get]`
	Should return true when pre PostProcessingLogits methods are overriden. More...

virtual bool	SupportsPostProcessingFullOutput `[get]`
	Should return true when PostProcessingFullOutput is supported. More...

BlobCollection< T >	blobs `[get]`
	Returns the collection of learnable parameter Blobs for the Layer. More...

BlobCollection< T >	internal_blobs `[get]`
	Returns the collection of internal Blobs used by the Layer. More...

LayerParameter	layer_param `[get]`
	Returns the LayerParameter for this Layer. More...

LayerParameter.LayerType	type `[get]`
	Returns the LayerType of this Layer. More...

virtual int	ExactNumBottomBlobs `[get]`
	Returns the exact number of bottom (input) Blobs required by the Layer, or -1 if no exact number is required. More...

virtual int	MinBottomBlobs `[get]`
	Returns the minimum number of bottom (input) Blobs required by the Layer, or -1 if no minimum number is required. More...

virtual int	MaxBottomBlobs `[get]`
	Returns the maximum number of bottom (input) Blobs required by the Layer, or -1 if no maximum number is required. More...

virtual int	ExactNumTopBlobs `[get]`
	Returns the exact number of top (output) Blobs required by the Layer, or -1 if no exact number is required. More...

virtual int	MinTopBlobs `[get]`
	Returns the minimum number of top (output) Blobs required by the Layer, or -1 if no minimum number is required. More...

virtual int	MaxTopBlobs `[get]`
	Returns the maximum number of top (output) Blobs required by the Layer, or -1 if no maximum number is required. More...

virtual bool	EqualNumBottomTopBlobs `[get]`
	Returns true if the Layer requires and equal number of bottom (input) and top (output) Blobs. More...

virtual bool	AutoTopBlobs `[get]`
	Return whether "anonymous" top (output) Blobs are created automatically by the Layer. More...

double	forward_timing `[get]`
	Returns the timing of the last forward pass in milliseconds. More...

double	forward_timing_average `[get]`
	Returns the average timing of the forward passes in milliseconds. More...

double	backward_timing `[get]`
	Returns the timing of the last backward pass in milliseconds. More...

double	backward_timing_average `[get]`
	Returns the average timing of the backward passes in milliseconds. More...

Additional Inherited Members
Static Public Member Functions inherited from MyCaffe.layers.Layer< T >
static Layer< T >	Create (CudaDnn< T > cuda, Log log, LayerParameter p, CancelEvent evtCancel, IXDatabaseBase db=null, TransferInput trxinput=null)
	Create a new Layer based on the LayerParameter. More...

Events inherited from MyCaffe.layers.Layer< T >
EventHandler< WorkspaceArgs >	OnGetWorkspace
	Specifies the OnGetWorkspace event that fires when the getWorkspace() function is called by a layer to get a shareable workspace to conserve GPU memory. More...

EventHandler< WorkspaceArgs >	OnSetWorkspace
	Specifies the OnSetWorkspace event that fires when the setWorkspace() function is called by a layer to get a shareable workspace to conserve GPU memory. More...

EventHandler< GetIterationArgs >	OnGetIteration
	Specifies the OnGetIteration event that fires when a layer needs to get the current iteration from the solver. More...

EventHandler< GetWorkBlobArgs< T > >	OnDebug
	Specifies the OnGetWorkBlob event that is only supported when debugging to get a work blob from the primary Net holding this layer. More...

Detailed Description

The RecurrentLayer is an abstract class for implementing recurrent behavior inside of an unrolled newtork. This layer type cannot be instantiated – instead, you should use one of teh implementations which defines the recurrent architecture, such as RNNLayer or LSTMLayer. This layer is initialized with the MyCaffe.param.RecurrentParameter.

Template Parameters

T

Definition at line 23 of file RecurrentLayer.cs.

Constructor & Destructor Documentation

◆ RecurrentLayer()

MyCaffe.layers.RecurrentLayer< T >.RecurrentLayer	(	CudaDnn< T >	cuda,
		Log	log,
		LayerParameter	p,
		CancelEvent	evtCancel
	)

The RecurrentLayer constructor.

Parameters

cuda	Specifies the CudaDnn connection to Cuda.
log	Specifies the Log for output.
p	Specifies the LayerParameter of type LSTM or RNN.
evtCancel	Specifies the CancelEvent used to cancel training operations.

Definition at line 124 of file RecurrentLayer.cs.

Member Function Documentation

◆ AllowForceBackward()

override bool MyCaffe.layers.RecurrentLayer< T >.AllowForceBackward ( int nBottomIdx )

virtual

Returns true for all but the bottom index = 1, for you can't propagate to the sequence continuation indicators.

Parameters

nBottomIdx Specifies the bottom index.

Returns: Returns whether or not to allow forced backward.

Reimplemented from MyCaffe.layers.Layer< T >.

Definition at line 1217 of file RecurrentLayer.cs.

◆ backward()

override void MyCaffe.layers.RecurrentLayer< T >.backward	(	BlobCollection< T >	colTop,
		List< bool >	rgbPropagateDown,
		BlobCollection< T >	colBottom
	)

protectedvirtual

Backward computation.

Parameters

colTop	See 'foward' documetation.
rgbPropagateDown	Specifies whether or not to propagate down.
colBottom	See 'forward' documentation.

Implements MyCaffe.layers.Layer< T >.

Definition at line 1505 of file RecurrentLayer.cs.

◆ dispose()

override void MyCaffe.layers.RecurrentLayer< T >.dispose ( )

protectedvirtual

Releases all GPU and host resources used by the Layer.

Reimplemented from MyCaffe.layers.Layer< T >.

Definition at line 145 of file RecurrentLayer.cs.

◆ FillUnrolledNet()

abstract void MyCaffe.layers.RecurrentLayer< T >.FillUnrolledNet ( NetParameter net_param )

protectedpure virtual

Fills net_param with the recurrent network architecture. Subclasses should define this – see RNNLayer and LSTMLayer for examples.

Parameters

net_param Specifies the net_param to be filled.

Implemented in MyCaffe.layers.LSTMLayer< T >, and MyCaffe.layers.RNNLayer< T >.

◆ forward()

override void MyCaffe.layers.RecurrentLayer< T >.forward	(	BlobCollection< T >	colBottom,
		BlobCollection< T >	colTop
	)

protectedvirtual

Peforms the forward calculation.

Parameters

colBottom

bottom input Blob vector (length 2-3)

$(T \times N \times ...)$ the time-varying input . After the first two axes, whose dimensions must correspond to the number of timesteps and the number of independent streams , respectively, its dimensions may be arbitrary. Note that the ordering of dimensions – $(T \times N \times ...)$ , rather than $(N \times T \times ...)$ – means that the independent input streams must be 'interleaved'.
$(T \times N)$ the sequence continuation indicators $\delta$ . These inputs should be binary (0 or 1) indicators, where $\delta{t,n} = 0$ means that timestep of stream is the beginning of a new sequence, and hence the previous hidden state $h_{t-1}$ is mulitplied by $\delta_t = 0$ and has no effect on the cell's output at timestep 't', and a value of $\delta_{t,n} = 1$ means that timestep of stream is a continuation from the previous timestep , and the previous hidden state $h_{t-1}$ affects the updated hidden state and output.
$(N \times ...)$ (optional) the static (non-time-varying) input $x_{static}$ . After the first axis, whose dimensions must be the number of independent streams, its dimensions must be the number of independent streams, its dimensions may be arbitrary. This is mathematically equivalent to using a time-varying input of $x'_t = [x_t; x_{static}]$ – i.e., tiling the static input across the 'T' timesteps and concatenating with the time-varying input. Note that if this input is used, all timesteps in a single batch within a particular one of the streams must share the same static input, even if the sequence continuation indicators suggest that difference sequences are ending and beginning within a single batch. This may require padding and/or truncation for uniform length.

colTop

top output Blob (length 1)

$(T \times N \times D)$ the time-varying output , where is
recurrent_param.num_output

. Refer to documentation for particular RecurrentLayer implementations (such as RNNLayer or LSTMLayer) for the definition of .

Implements MyCaffe.layers.Layer< T >.

Definition at line 1329 of file RecurrentLayer.cs.

◆ LayerSetUp()

override void MyCaffe.layers.RecurrentLayer< T >.LayerSetUp	(	BlobCollection< T >	colBottom,
		BlobCollection< T >	colTop
	)

virtual

Setup the layer.

Parameters

colBottom	Specifies the collection of bottom (input) Blobs.
colTop	Specifies the collection of top (output) Blobs.

Implements MyCaffe.layers.Layer< T >.

Definition at line 286 of file RecurrentLayer.cs.

◆ OutputBlobNames()

abstract void MyCaffe.layers.RecurrentLayer< T >.OutputBlobNames ( List< string > rgNames )

protectedpure virtual

Fills names with the names of the output blobs, concatenated across all timesteps. Should return a name for each top Blob. Subclassses should define this – see RNNLayer and LSTMLayer for examples.

Parameters

rgNames Specifies the output names.

Implemented in MyCaffe.layers.LSTMLayer< T >, and MyCaffe.layers.RNNLayer< T >.

◆ RecurrentInputBlobNames()

abstract void MyCaffe.layers.RecurrentLayer< T >.RecurrentInputBlobNames ( List< string > rgNames )

protectedpure virtual

Fills names with the names of the 0th timestep recurrent input Blob's. Subclasses should define this – see RNNlayer and LSTMLayer for examples.

Parameters

rgNames Specifies the input names.

Implemented in MyCaffe.layers.LSTMLayer< T >, and MyCaffe.layers.RNNLayer< T >.

◆ RecurrentInputShapes()

abstract void MyCaffe.layers.RecurrentLayer< T >.RecurrentInputShapes ( List< BlobShape > rgShapes )

protectedpure virtual

Fills shapes with the shapes of the recurrent input Blob's. Subclassses should define this – see RNNLayer and LSTMLayer for examples.

Parameters

rgShapes Specifies the shapes to be filled.

Implemented in MyCaffe.layers.LSTMLayer< T >, and MyCaffe.layers.RNNLayer< T >.

◆ RecurrentOutputBlobNames()

abstract void MyCaffe.layers.RecurrentLayer< T >.RecurrentOutputBlobNames ( List< string > rgNames )

protectedpure virtual

Fills names with the names of the Tth timestep recurrent output Blob's. Subclassses should define this – see RNNLayer and LSTMLayer for examples.

Parameters

rgNames Specifies the output names.

Implemented in MyCaffe.layers.LSTMLayer< T >, and MyCaffe.layers.RNNLayer< T >.

◆ Reset()

virtual void MyCaffe.layers.RecurrentLayer< T >.Reset ( )

virtual

Reset the hidden state of the net by zeroing out all recurrent outputs.

Definition at line 1147 of file RecurrentLayer.cs.

◆ ResetOnDebug()

override void MyCaffe.layers.RecurrentLayer< T >.ResetOnDebug ( EventHandler< GetWorkBlobArgs< T > > fn )

virtual

Reset the OnDebug event, disabling it on the unrolled net.

Parameters

fn	Specifies the event function to call when the OnDebug event fires.

Reimplemented from MyCaffe.layers.Layer< T >.

Definition at line 260 of file RecurrentLayer.cs.

◆ Reshape()

override void MyCaffe.layers.RecurrentLayer< T >.Reshape	(	BlobCollection< T >	colBottom,
		BlobCollection< T >	colTop
	)

virtual

Reshape the bottom (input) and top (output) blobs.

Parameters

colBottom	Specifies the collection of bottom (input) Blobs.
colTop	Specifies the collection of top (output) Blobs.

Implements MyCaffe.layers.Layer< T >.

Definition at line 934 of file RecurrentLayer.cs.

◆ SetOnDebug()

override void MyCaffe.layers.RecurrentLayer< T >.SetOnDebug ( EventHandler< GetWorkBlobArgs< T > > fn )

virtual

Set the OnDebug event on the unrolled net.

Parameters

fn	Specifies the event function to call when the OnDebug event fires.

Reimplemented from MyCaffe.layers.Layer< T >.

Definition at line 243 of file RecurrentLayer.cs.

◆ setup_internal_blobs()

override void MyCaffe.layers.RecurrentLayer< T >.setup_internal_blobs ( BlobCollection< T > col )

protectedvirtual

Derivative layers should add all internal blobws to the 'col' provided.

Parameters

col	Specifies the blob collection where internal blobs are added.

Reimplemented from MyCaffe.layers.Layer< T >.

Definition at line 1264 of file RecurrentLayer.cs.

Member Data Documentation

◆ m_bStaticInput

bool MyCaffe.layers.RecurrentLayer< T >.m_bStaticInput

protected

Whether the layer has a 'static' input copies across all timesteps.

Definition at line 52 of file RecurrentLayer.cs.

◆ m_nN

int MyCaffe.layers.RecurrentLayer< T >.m_nN

protected

The number of independent streams to process simultaneously.

Definition at line 41 of file RecurrentLayer.cs.

◆ m_nT

int MyCaffe.layers.RecurrentLayer< T >.m_nT

protected

The number of timesteps in the layer's input, and the number of timesteps over which to backpropagate through time.

Definition at line 47 of file RecurrentLayer.cs.

Property Documentation

◆ ExactNumTopBlobs

override int MyCaffe.layers.RecurrentLayer< T >.ExactNumTopBlobs

get

Returns the min number of required top (output) Blobs.

Returns the max number of required top (output) Blobs.

Definition at line 1195 of file RecurrentLayer.cs.

◆ MaxBottomBlobs

override int MyCaffe.layers.RecurrentLayer< T >.MaxBottomBlobs

get

Returns the maximum number of required bottom (input) Blobs: min+1

Definition at line 1179 of file RecurrentLayer.cs.

◆ MinBottomBlobs

override int MyCaffe.layers.RecurrentLayer< T >.MinBottomBlobs

get

Returns the minimum number of required bottom (input) Blobs.

Definition at line 1158 of file RecurrentLayer.cs.

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

C:/Data/Data/SS_Projects/Intelligence/GitHub/MyCaffe/MyCaffe/layers/RecurrentLayer.cs

Public Member Functions

Protected Member Functions

Protected Attributes

Properties

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ RecurrentLayer()

Member Function Documentation

◆ AllowForceBackward()

◆ backward()

◆ dispose()

◆ FillUnrolledNet()

◆ forward()

◆ LayerSetUp()

◆ OutputBlobNames()

◆ RecurrentInputBlobNames()

◆ RecurrentInputShapes()

◆ RecurrentOutputBlobNames()

◆ Reset()

◆ ResetOnDebug()

◆ Reshape()

◆ SetOnDebug()

◆ setup_internal_blobs()

Member Data Documentation

◆ m_bStaticInput

◆ m_nN

◆ m_nT

Property Documentation

◆ ExactNumTopBlobs

◆ MaxBottomBlobs

◆ MinBottomBlobs