The TokenizedDataPairsLayer loads and tokenizes data for a transformer model where data is loaded in the form: data, pos, target(optional) More...

Inheritance diagram for MyCaffe.layers.gpt.TokenizedDataPairsLayer< T >:

Public Member Functions
	TokenizedDataPairsLayer (CudaDnn< T > cuda, Log log, LayerParameter p, IXDatabaseBase db, CancelEvent evtCancel)
	The TokenizedDataPairsLayer constructor. 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 top based on the parameter batch and block size. More...

List< int >	Tokenize (string str, VOCABULARY vocab)
	Tokenize an input string using the internal vocabulary. More...

string	Detokenize (float[] rg, int nStartIdx, int nCount, VOCABULARY vocab)
	Detokenize a set of tokens from the data specified. More...

uint	GetVocabuarySize (VOCABULARY src)
	Get the vocabulary size for the specified vocabulary source. More...

override BlobCollection< T >	PreProcessInput (PropertySet customInput, out int nSeqLen, BlobCollection< T > colBottom=null)
	Preproces the input and return as a set of bottom blobs. More...

override bool	PreProcessInput (string str, int? nTokIdx, BlobCollection< T > colBottom=null)
	Preproces the input and return as a set of bottom blobs. More...

override List< Tuple< string, int, double > >	PostProcessLogitsOutput (int nCurIdx, Blob< T > blobLogits, Layer< T > softmax, int nAxis, int nK=1)
	Allows post processing the logits output data by converting the logits to and selecting from the probability distribution produced and detokenizing the results to the string character. More...

override 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...

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

virtual void	SetOnDebug (EventHandler< GetWorkBlobArgs< T > > fn)
	Set the OnDebug event. More...

virtual void	ResetOnDebug (EventHandler< GetWorkBlobArgs< T > > fn)
	Reset the OnDebug event, disabling it. 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...

virtual bool	AllowForceBackward (int nBottomIdx)
	Return whether to allow 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 ()
	Release all internal blobs. More...

override void	setup_internal_blobs (BlobCollection< T > col)
	Add all internal blobs. More...

override void	forward (BlobCollection< T > colBottom, BlobCollection< T > colTop)
	Run the Forward computation, which fills the data into the top (output) Blobs. More...

override void	backward (BlobCollection< T > colTop, List< bool > rgbPropagateDown, BlobCollection< T > colBottom)
	Not implemented - data Layers do not perform backward.. 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...

Properties
override int?	ExactNumBottomBlobs `[get]`
	Specifies the exact number of bottom blobs (TRAIN\|TEST: 0, RUN:2 encin, decin) More...

override int	ExactNumTopBlobs `[get]`
	Returns the minimum number of required top (output) Blobs: enc_in, dec_in, dec_out, e_mask, d_mask More...

override bool	SupportsPreProcessing `[get]`
	Specifies that this layer supports preprocessing. More...

override bool	SupportsPostProcessingLogits `[get]`
	Specifies that this layer supports post processing the logits. 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...

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...

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 TokenizedDataPairsLayer loads and tokenizes data for a transformer model where data is loaded in the form: data, pos, target(optional)

Template Parameters

T	Specifies the base type float or double. Using float is recommended to conserve GPU memory.

Definition at line 27 of file TokenizedDataPairsLayer.cs.

Constructor & Destructor Documentation

◆ TokenizedDataPairsLayer()

MyCaffe.layers.gpt.TokenizedDataPairsLayer< T >.TokenizedDataPairsLayer	(	CudaDnn< T >	cuda,
		Log	log,
		LayerParameter	p,
		IXDatabaseBase	db,
		CancelEvent	evtCancel
	)

The TokenizedDataPairsLayer constructor.

Parameters

cuda	Specifies the CudaDnn connection to Cuda.
log	Specifies the Log for output.
p	Provides TokenizedDataPairsParameter model_data_param with options: source. The encoder input data source. target. The decoder input/output data source. batch_size. The batch size time_steps. The maximum number of time steps. input_dim. The input dimension of the encoder input. sample_size. The number of samples to load for training. shuffle. Whether or not to shuffle the data.
db	Specifies the external database to use.
evtCancel	Specifies the CancelEvent used to cancel any pre-fetching operations.

Definition at line 82 of file TokenizedDataPairsLayer.cs.

Member Function Documentation

◆ backward()

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

protectedvirtual

Not implemented - data Layers do not perform backward..

Implements MyCaffe.layers.Layer< T >.

Definition at line 384 of file TokenizedDataPairsLayer.cs.

◆ Detokenize()

string MyCaffe.layers.gpt.TokenizedDataPairsLayer< T >.Detokenize	(	float[]	rg,
		int	nStartIdx,
		int	nCount,
		VOCABULARY	vocab
	)

Detokenize a set of tokens from the data specified.

Parameters

rg	Specifies an array of tokens.
nStartIdx	Specifies the start index.
nCount	Specifies the number of tokens to detokenize.
vocab	Specifies the vocabulary to use: ENCODER or DECODER.

Returns: The detokenized string is returned.

Definition at line 426 of file TokenizedDataPairsLayer.cs.

◆ dispose()

override void MyCaffe.layers.gpt.TokenizedDataPairsLayer< T >.dispose ( )

protectedvirtual

Release all internal blobs.

Reimplemented from MyCaffe.layers.Layer< T >.

Definition at line 95 of file TokenizedDataPairsLayer.cs.

◆ forward()

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

protectedvirtual

Run the Forward computation, which fills the data into the top (output) Blobs.

Parameters

colBottom Not used.

colTop

top output blob vector (length 2-5)

$(N \times C \times 1 \times 1)$ (TEXT input) the data outputs.
$(N \times C \times 1 \times 1)$ the position outputs.
$(N \times C \times 1 \times 1)$ (TEXT input, only on training and testing) the target outputs ENCODER mask
$(N \times C \times 1 \times 1)$ (1's on each input, otherwise 0's) the encoder mask. DECODER mask
$(N \times C \times C \times 1)$ (1's on each input, otherwise 0's. Duplicated across C channels, overlaid with triangle mask - see remarks.) the encoder mask.

The encoder and decoder masks use the following formats.

Encoder Mask: shape = (batch, seq_len, 1) The sequence length is filled with 1 where data exists in each sequence, and 0 otherwise. For example, when using a sequence length of 4 and batch = 3, the following input:

encoder input                encoder mask
shape = (3,4)                (3,4)
[33, 44, 22, 55]             [  1,  1,  1,  1]
[44, 33, 0,  0 ] has mask -> [  1,  1,  0,  0]
[88, 99, 22, 0 ]             [  1,  1,  1,  0]

Decoder Mask: shape (batch, seq_len, seq_len) The decoder mask is first filled with a mask similar to the encoder mask, whre each sequence for each entry is duplicated for the number of sequences high to create an initial mask like the following. Next a triangular mask is anded to avoid right side info.

decoder input                encoder like mask        triangular mask     final decoder mask
shape = (3,4)                (3,4,4)                  (3,4,4)             (3,4,4)
[33, 44, 22, 55]             [  1,  1,  1,  1]        [  1,  0,  0,  0]   [  1,  0,  0,  0]
                             [  1,  1,  1,  1]        [  1,  1,  0,  0]   [  1,  1,  0,  0]
                             [  1,  1,  1,  1] -and-> [  1,  1,  1,  0] = [  1,  1,  1,  0]
                             [  1,  1,  1,  1]        [  1,  1,  1,  1]   [  1,  1,  1,  1]
[44, 33, 0,  0 ] has mask -> [  1,  1,  0,  0]        [  1,  0,  0,  0]   [  1,  0,  0,  0]
                             [  1,  1,  0,  0]        [  1,  1,  0,  0]   [  1,  1,  0,  0]
                             [  1,  1,  0,  0] -and-> [  1,  1,  1,  0] = [  1,  1,  0,  0]
                             [  1,  1,  0,  0]        [  1,  1,  1,  1]   [  1,  1,  0,  0]
[88, 99, 22, 0 ]             [  1,  1,  1,  0]        [  1,  0,  0,  0]   [  1,  0,  0,  0]
                             [  1,  1,  1,  0]        [  1,  1,  0,  0]   [  1,  1,  0,  0]
                             [  1,  1,  1,  0] -and-> [  1,  1,  1,  0] = [  1,  1,  1,  0]
                             [  1,  1,  1,  0]        [  1,  1,  1,  1]   [  1,  1,  1,  0]

Implements MyCaffe.layers.Layer< T >.

Definition at line 355 of file TokenizedDataPairsLayer.cs.

◆ GetVocabuarySize()

uint MyCaffe.layers.gpt.TokenizedDataPairsLayer< T >.GetVocabuarySize ( VOCABULARY src )

Get the vocabulary size for the specified vocabulary source.

Parameters

src	Specifies the vocabulary source (ENCODER or DECODER).

Returns: The vocabulary size is returned.

Definition at line 437 of file TokenizedDataPairsLayer.cs.

◆ LayerSetUp()

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

virtual

Setup the layer.

Parameters

colBottom	Not used.
colTop	Specifies the collection of top (output) Blobs.

Implements MyCaffe.layers.Layer< T >.

Definition at line 138 of file TokenizedDataPairsLayer.cs.

◆ PostProcessFullOutput()

override string MyCaffe.layers.gpt.TokenizedDataPairsLayer< T >.PostProcessFullOutput ( Blob< T > blobSoftmax )

virtual

The PostProcessFullOutput allows derivative data layers to post-process the results, usually be detokenizing the data in the blobSoftmax.

Parameters

blobSoftmax Specifies the data to be post processed.

Returns: A string of the post processed data is returned.

Reimplemented from MyCaffe.layers.Layer< T >.

Definition at line 588 of file TokenizedDataPairsLayer.cs.

◆ PostProcessLogitsOutput()

override List< Tuple< string, int, double > > MyCaffe.layers.gpt.TokenizedDataPairsLayer< T >.PostProcessLogitsOutput	(	int	nCurIdx,
		Blob< T >	blobLogits,
		Layer< T >	softmax,
		int	nAxis,
		int	nK = `1`
	)

virtual

Allows post processing the logits output data by converting the logits to and selecting from the probability distribution produced and detokenizing the results to the string character.

Parameters

nCurIdx	Specifies the current index being processed, or -1 for the last index.
blobLogits	Specifies the output of the last inner product layer.
softmax	Specifies the softmax layer.
nAxis	Specifies the axis of the softmax layer.
nK	Specifies the TopK max items of the logits to use, or 0 to ignore.

Returns: The detokenized data is returned.

Reimplemented from MyCaffe.layers.Layer< T >.

Definition at line 528 of file TokenizedDataPairsLayer.cs.

◆ PreProcessInput() [1/2]

override BlobCollection< T > MyCaffe.layers.gpt.TokenizedDataPairsLayer< T >.PreProcessInput	(	PropertySet	customInput,
		out int	nSeqLen,
		BlobCollection< T >	colBottom = `null`
	)

virtual

Preproces the input and return as a set of bottom blobs.

Parameters

customInput	Specifies the custom text input.
nSeqLen	Specifies the sequence length.
colBottom	The output is placed in the bottom blobs as: tokidx, pos

Returns: The bottom blob collection is returned.

Reimplemented from MyCaffe.layers.Layer< T >.

Definition at line 450 of file TokenizedDataPairsLayer.cs.

◆ PreProcessInput() [2/2]

override bool MyCaffe.layers.gpt.TokenizedDataPairsLayer< T >.PreProcessInput	(	string	str,
		int?	nTokIdx,
		BlobCollection< T >	colBottom = `null`
	)

virtual

Preproces the input and return as a set of bottom blobs.

Parameters

str	Specifies the string input, can be null.
nTokIdx	Specifies the token input.
colBottom	The output is placed in the bottom blobs as: tokidx, pos

Returns: The bottom blob collection is returned.

Reimplemented from MyCaffe.layers.Layer< T >.

Definition at line 494 of file TokenizedDataPairsLayer.cs.

◆ Reshape()

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

virtual

Reshape the top based on the parameter batch and block size.

Parameters

colBottom	Specifies the collection of bottom (input) Blobs - Used only during RUN phase.
colTop	Specifies the collection of top (output) Blobs.

Implements MyCaffe.layers.Layer< T >.

Definition at line 240 of file TokenizedDataPairsLayer.cs.

◆ setup_internal_blobs()

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

protectedvirtual

Add all internal blobs.

Parameters

col	Specifies the internal blob array.

Reimplemented from MyCaffe.layers.Layer< T >.

Definition at line 112 of file TokenizedDataPairsLayer.cs.

◆ Tokenize()

List< int > MyCaffe.layers.gpt.TokenizedDataPairsLayer< T >.Tokenize	(	string	str,
		VOCABULARY	vocab
	)

Tokenize an input string using the internal vocabulary.

Parameters

str	Specifies the string to tokenize.
vocab	Specifies the vocabulary to use, ENCODER or DECODER.

Returns: A list of tokens corresponding to the input is returned.

Definition at line 410 of file TokenizedDataPairsLayer.cs.

Property Documentation

◆ ExactNumBottomBlobs

override int? MyCaffe.layers.gpt.TokenizedDataPairsLayer< T >.ExactNumBottomBlobs

get

Specifies the exact number of bottom blobs (TRAIN|TEST: 0, RUN:2 encin, decin)

Definition at line 120 of file TokenizedDataPairsLayer.cs.

◆ ExactNumTopBlobs

override int MyCaffe.layers.gpt.TokenizedDataPairsLayer< T >.ExactNumTopBlobs

get

Returns the minimum number of required top (output) Blobs: enc_in, dec_in, dec_out, e_mask, d_mask

Definition at line 128 of file TokenizedDataPairsLayer.cs.

◆ SupportsPostProcessingLogits

override bool MyCaffe.layers.gpt.TokenizedDataPairsLayer< T >.SupportsPostProcessingLogits

get

Specifies that this layer supports post processing the logits.

Definition at line 399 of file TokenizedDataPairsLayer.cs.

◆ SupportsPreProcessing

override bool MyCaffe.layers.gpt.TokenizedDataPairsLayer< T >.SupportsPreProcessing

get

Specifies that this layer supports preprocessing.

Definition at line 391 of file TokenizedDataPairsLayer.cs.

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

C:/Data/Data/SS_Projects/Intelligence/GitHub/MyCaffe/MyCaffe.layers.gpt/layers.gpt/TokenizedDataPairsLayer.cs

Public Member Functions

Protected Member Functions

Properties

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ TokenizedDataPairsLayer()

Member Function Documentation

◆ backward()

◆ Detokenize()

◆ dispose()

◆ forward()

◆ GetVocabuarySize()

◆ LayerSetUp()

◆ PostProcessFullOutput()

◆ PostProcessLogitsOutput()

◆ PreProcessInput() [1/2]

◆ PreProcessInput() [2/2]

◆ Reshape()

◆ setup_internal_blobs()

◆ Tokenize()

Property Documentation

◆ ExactNumBottomBlobs

◆ ExactNumTopBlobs

◆ SupportsPostProcessingLogits

◆ SupportsPreProcessing