org.nd4j.autodiff.samediff.ops

Class SDRNN

java.lang.Object

org.nd4j.autodiff.samediff.ops.SDOps

org.nd4j.autodiff.samediff.ops.SDRNN

public class SDRNN
extends SDOps

Field Summary

Fields inherited from class org.nd4j.autodiff.samediff.ops.SDOps

sd

Constructor Summary

Constructors

Constructor and Description
SDRNN(SameDiff sameDiff)

Method Summary

Modifier and Type	Method and Description
SDVariable	gru(SDVariable x, SDVariable hLast, SDVariable Wx, SDVariable Wh, SDVariable biases) The GRU operation.
SDVariable	gru(String name, SDVariable x, SDVariable hLast, SDVariable Wx, SDVariable Wh, SDVariable biases) The GRU operation.
SDVariable[]	gruCell(SDVariable x, SDVariable hLast, GRUWeights GRUWeights) The GRU cell.
SDVariable[]	gruCell(String[] names, SDVariable x, SDVariable hLast, GRUWeights GRUWeights) The GRU cell.
SDVariable	lstmblock(SDVariable x, LSTMWeights LSTMWeights, LSTMConfiguration LSTMConfiguration) The LSTM block
SDVariable	lstmblock(SDVariable maxTSLength, SDVariable x, SDVariable cLast, SDVariable yLast, LSTMWeights LSTMWeights, LSTMConfiguration LSTMConfiguration) The LSTM block
SDVariable	lstmblock(String name, SDVariable x, LSTMWeights LSTMWeights, LSTMConfiguration LSTMConfiguration) The LSTM block
SDVariable	lstmblock(String name, SDVariable maxTSLength, SDVariable x, SDVariable cLast, SDVariable yLast, LSTMWeights LSTMWeights, LSTMConfiguration LSTMConfiguration) The LSTM block
SDVariable[]	lstmCell(SDVariable x, SDVariable cLast, SDVariable yLast, LSTMWeights LSTMWeights, LSTMConfiguration LSTMConfiguration) The LSTM cell.
SDVariable[]	lstmCell(String[] names, SDVariable x, SDVariable cLast, SDVariable yLast, LSTMWeights LSTMWeights, LSTMConfiguration LSTMConfiguration) The LSTM cell.
SDVariable[]	lstmLayer(SDVariable x, LSTMLayerWeights LSTMLayerWeights, LSTMLayerConfig LSTMLayerConfig) Long Short-Term Memory layer - Hochreiter 1997. SUPPORTS following data formats: for unidirectional: TNS: shapes [timeLength, numExamples, inOutSize] NST: shapes [numExamples, inOutSize, timeLength] NTS: shapes [numExamples, timeLength, inOutSize] for bidirectional: T2NS: shapes [timeLength, 2, numExamples, inOutSize] (for ONNX) SUPPORTS following direction modes: FWD: forward BWD: backward BIDIR_SUM: bidirectional sum BIDIR_CONCAT: bidirectional concat BIDIR_EXTRA_DIM: bidirectional extra output dim (in conjunction with format dataFormat - T2NS) You may use different gate configurations: specify gate/cell/out aplha/beta and numbers of activations for gate/cell/out described in activations enum ("RELU","SIGMOID","AFFINE","LEAKY_RELU","THRESHHOLD_RELU","SCALED_TAHN","HARD_SIGMOID","ELU","SOFTSIGN","SOFTPLUS") Also this layer supports MKLDNN (DNNL) and cuDNN acceleration
SDVariable[]	lstmLayer(SDVariable x, SDVariable cLast, SDVariable yLast, SDVariable maxTSLength, LSTMLayerWeights LSTMLayerWeights, LSTMLayerConfig LSTMLayerConfig) Long Short-Term Memory layer - Hochreiter 1997. SUPPORTS following data formats: for unidirectional: TNS: shapes [timeLength, numExamples, inOutSize] NST: shapes [numExamples, inOutSize, timeLength] NTS: shapes [numExamples, timeLength, inOutSize] for bidirectional: T2NS: shapes [timeLength, 2, numExamples, inOutSize] (for ONNX) SUPPORTS following direction modes: FWD: forward BWD: backward BIDIR_SUM: bidirectional sum BIDIR_CONCAT: bidirectional concat BIDIR_EXTRA_DIM: bidirectional extra output dim (in conjunction with format dataFormat - T2NS) You may use different gate configurations: specify gate/cell/out aplha/beta and numbers of activations for gate/cell/out described in activations enum ("RELU","SIGMOID","AFFINE","LEAKY_RELU","THRESHHOLD_RELU","SCALED_TAHN","HARD_SIGMOID","ELU","SOFTSIGN","SOFTPLUS") Also this layer supports MKLDNN (DNNL) and cuDNN acceleration
SDVariable[]	lstmLayer(String[] names, SDVariable x, LSTMLayerWeights LSTMLayerWeights, LSTMLayerConfig LSTMLayerConfig) Long Short-Term Memory layer - Hochreiter 1997. SUPPORTS following data formats: for unidirectional: TNS: shapes [timeLength, numExamples, inOutSize] NST: shapes [numExamples, inOutSize, timeLength] NTS: shapes [numExamples, timeLength, inOutSize] for bidirectional: T2NS: shapes [timeLength, 2, numExamples, inOutSize] (for ONNX) SUPPORTS following direction modes: FWD: forward BWD: backward BIDIR_SUM: bidirectional sum BIDIR_CONCAT: bidirectional concat BIDIR_EXTRA_DIM: bidirectional extra output dim (in conjunction with format dataFormat - T2NS) You may use different gate configurations: specify gate/cell/out aplha/beta and numbers of activations for gate/cell/out described in activations enum ("RELU","SIGMOID","AFFINE","LEAKY_RELU","THRESHHOLD_RELU","SCALED_TAHN","HARD_SIGMOID","ELU","SOFTSIGN","SOFTPLUS") Also this layer supports MKLDNN (DNNL) and cuDNN acceleration
SDVariable[]	lstmLayer(String[] names, SDVariable x, SDVariable cLast, SDVariable yLast, SDVariable maxTSLength, LSTMLayerWeights LSTMLayerWeights, LSTMLayerConfig LSTMLayerConfig) Long Short-Term Memory layer - Hochreiter 1997. SUPPORTS following data formats: for unidirectional: TNS: shapes [timeLength, numExamples, inOutSize] NST: shapes [numExamples, inOutSize, timeLength] NTS: shapes [numExamples, timeLength, inOutSize] for bidirectional: T2NS: shapes [timeLength, 2, numExamples, inOutSize] (for ONNX) SUPPORTS following direction modes: FWD: forward BWD: backward BIDIR_SUM: bidirectional sum BIDIR_CONCAT: bidirectional concat BIDIR_EXTRA_DIM: bidirectional extra output dim (in conjunction with format dataFormat - T2NS) You may use different gate configurations: specify gate/cell/out aplha/beta and numbers of activations for gate/cell/out described in activations enum ("RELU","SIGMOID","AFFINE","LEAKY_RELU","THRESHHOLD_RELU","SCALED_TAHN","HARD_SIGMOID","ELU","SOFTSIGN","SOFTPLUS") Also this layer supports MKLDNN (DNNL) and cuDNN acceleration
SDVariable	sru(SDVariable x, SDVariable initialC, SDVariable mask, SRUWeights SRUWeights) The SRU layer.
SDVariable	sru(SDVariable x, SDVariable initialC, SRUWeights SRUWeights) The SRU layer.
SDVariable	sru(String name, SDVariable x, SDVariable initialC, SDVariable mask, SRUWeights SRUWeights) The SRU layer.
SDVariable	sru(String name, SDVariable x, SDVariable initialC, SRUWeights SRUWeights) The SRU layer.
SDVariable	sruCell(SDVariable x, SDVariable cLast, SRUWeights SRUWeights) The SRU layer.
SDVariable	sruCell(String name, SDVariable x, SDVariable cLast, SRUWeights SRUWeights) The SRU layer.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

SDRNN

public SDRNN(SameDiff sameDiff)

Method Detail

gru

public SDVariable gru(SDVariable x,
                      SDVariable hLast,
                      SDVariable Wx,
                      SDVariable Wh,
                      SDVariable biases)

The GRU operation. Gated Recurrent Unit - Cho et al. 2014.

Parameters:

x - input [time, bS, nIn] (NUMERIC type)

hLast - initial cell output (at time step = 0) [bS, nOut] (NUMERIC type)

Wx - input-to-hidden weights, [nIn, 3*nOut] (NUMERIC type)

Wh - hidden-to-hidden weights, [nOut, 3*nOut] (NUMERIC type)

biases - biases, [3*nOut] (NUMERIC type)

Returns:

h cell outputs [time, bS, nOut], that is per each time step (NUMERIC type)

gru

public SDVariable gru(String name,
                      SDVariable x,
                      SDVariable hLast,
                      SDVariable Wx,
                      SDVariable Wh,
                      SDVariable biases)

The GRU operation. Gated Recurrent Unit - Cho et al. 2014.

Parameters:

name - name May be null. Name for the output variable

x - input [time, bS, nIn] (NUMERIC type)

hLast - initial cell output (at time step = 0) [bS, nOut] (NUMERIC type)

Wx - input-to-hidden weights, [nIn, 3*nOut] (NUMERIC type)

Wh - hidden-to-hidden weights, [nOut, 3*nOut] (NUMERIC type)

biases - biases, [3*nOut] (NUMERIC type)

Returns:

h cell outputs [time, bS, nOut], that is per each time step (NUMERIC type)

gruCell

public SDVariable[] gruCell(SDVariable x,
                            SDVariable hLast,
                            GRUWeights GRUWeights)

The GRU cell. Does a single time step operation

Parameters:

x - Input, with shape [batchSize, inSize] (NUMERIC type)

hLast - Output of the previous cell/time step, with shape [batchSize, numUnits] (NUMERIC type)

GRUWeights - Configuration Object

gruCell

public SDVariable[] gruCell(String[] names,
                            SDVariable x,
                            SDVariable hLast,
                            GRUWeights GRUWeights)

The GRU cell. Does a single time step operation

Parameters:

names - names May be null. Arrays of names for the output variables.

x - Input, with shape [batchSize, inSize] (NUMERIC type)

hLast - Output of the previous cell/time step, with shape [batchSize, numUnits] (NUMERIC type)

GRUWeights - Configuration Object

lstmCell

public SDVariable[] lstmCell(SDVariable x,
                             SDVariable cLast,
                             SDVariable yLast,
                             LSTMWeights LSTMWeights,
                             LSTMConfiguration LSTMConfiguration)

The LSTM cell. Does a single time step operation.

Parameters:

x - Input, with shape [batchSize, inSize] (NUMERIC type)

cLast - Previous cell state, with shape [batchSize, numUnits] (NUMERIC type)

yLast - revious cell output, with shape [batchSize, numUnits] (NUMERIC type)

LSTMWeights - Configuration Object

LSTMConfiguration - Configuration Object

lstmCell

public SDVariable[] lstmCell(String[] names,
                             SDVariable x,
                             SDVariable cLast,
                             SDVariable yLast,
                             LSTMWeights LSTMWeights,
                             LSTMConfiguration LSTMConfiguration)

The LSTM cell. Does a single time step operation.

Parameters:

names - names May be null. Arrays of names for the output variables.

x - Input, with shape [batchSize, inSize] (NUMERIC type)

cLast - Previous cell state, with shape [batchSize, numUnits] (NUMERIC type)

yLast - revious cell output, with shape [batchSize, numUnits] (NUMERIC type)

LSTMWeights - Configuration Object

LSTMConfiguration - Configuration Object

lstmLayer

public SDVariable[] lstmLayer(SDVariable x,
                              SDVariable cLast,
                              SDVariable yLast,
                              SDVariable maxTSLength,
                              LSTMLayerWeights LSTMLayerWeights,
                              LSTMLayerConfig LSTMLayerConfig)

Long Short-Term Memory layer - Hochreiter 1997.
SUPPORTS following data formats:
for unidirectional:
TNS: shapes [timeLength, numExamples, inOutSize]
NST: shapes [numExamples, inOutSize, timeLength]
NTS: shapes [numExamples, timeLength, inOutSize]
for bidirectional:
T2NS: shapes [timeLength, 2, numExamples, inOutSize] (for ONNX)
SUPPORTS following direction modes:
FWD: forward
BWD: backward
BIDIR_SUM: bidirectional sum
BIDIR_CONCAT: bidirectional concat
BIDIR_EXTRA_DIM: bidirectional extra output dim (in conjunction with format dataFormat - T2NS)
You may use different gate configurations:
specify gate/cell/out aplha/beta and numbers of activations for gate/cell/out described in activations enum
("RELU","SIGMOID","AFFINE","LEAKY_RELU","THRESHHOLD_RELU","SCALED_TAHN","HARD_SIGMOID","ELU","SOFTSIGN","SOFTPLUS")
Also this layer supports MKLDNN (DNNL) and cuDNN acceleration

Parameters:

x - Input, with shape dependent on the data format (in config). (NUMERIC type)

cLast - Previous/initial cell state, with shape [batchSize, numUnits] (NUMERIC type)

yLast - Previous/initial cell output, with shape [batchSize, numUnits] (NUMERIC type)

maxTSLength - maxTSLength with shape [batchSize] (NUMERIC type)

LSTMLayerWeights - Configuration Object

LSTMLayerConfig - Configuration Object

lstmLayer

public SDVariable[] lstmLayer(String[] names,
                              SDVariable x,
                              SDVariable cLast,
                              SDVariable yLast,
                              SDVariable maxTSLength,
                              LSTMLayerWeights LSTMLayerWeights,
                              LSTMLayerConfig LSTMLayerConfig)

Long Short-Term Memory layer - Hochreiter 1997.
SUPPORTS following data formats:
for unidirectional:
TNS: shapes [timeLength, numExamples, inOutSize]
NST: shapes [numExamples, inOutSize, timeLength]
NTS: shapes [numExamples, timeLength, inOutSize]
for bidirectional:
T2NS: shapes [timeLength, 2, numExamples, inOutSize] (for ONNX)
SUPPORTS following direction modes:
FWD: forward
BWD: backward
BIDIR_SUM: bidirectional sum
BIDIR_CONCAT: bidirectional concat
BIDIR_EXTRA_DIM: bidirectional extra output dim (in conjunction with format dataFormat - T2NS)
You may use different gate configurations:
specify gate/cell/out aplha/beta and numbers of activations for gate/cell/out described in activations enum
("RELU","SIGMOID","AFFINE","LEAKY_RELU","THRESHHOLD_RELU","SCALED_TAHN","HARD_SIGMOID","ELU","SOFTSIGN","SOFTPLUS")
Also this layer supports MKLDNN (DNNL) and cuDNN acceleration

Parameters:

names - names May be null. Arrays of names for the output variables.

x - Input, with shape dependent on the data format (in config). (NUMERIC type)

cLast - Previous/initial cell state, with shape [batchSize, numUnits] (NUMERIC type)

yLast - Previous/initial cell output, with shape [batchSize, numUnits] (NUMERIC type)

maxTSLength - maxTSLength with shape [batchSize] (NUMERIC type)

LSTMLayerWeights - Configuration Object

LSTMLayerConfig - Configuration Object

lstmLayer

public SDVariable[] lstmLayer(SDVariable x,
                              LSTMLayerWeights LSTMLayerWeights,
                              LSTMLayerConfig LSTMLayerConfig)

Long Short-Term Memory layer - Hochreiter 1997.
SUPPORTS following data formats:
for unidirectional:
TNS: shapes [timeLength, numExamples, inOutSize]
NST: shapes [numExamples, inOutSize, timeLength]
NTS: shapes [numExamples, timeLength, inOutSize]
for bidirectional:
T2NS: shapes [timeLength, 2, numExamples, inOutSize] (for ONNX)
SUPPORTS following direction modes:
FWD: forward
BWD: backward
BIDIR_SUM: bidirectional sum
BIDIR_CONCAT: bidirectional concat
BIDIR_EXTRA_DIM: bidirectional extra output dim (in conjunction with format dataFormat - T2NS)
You may use different gate configurations:
specify gate/cell/out aplha/beta and numbers of activations for gate/cell/out described in activations enum
("RELU","SIGMOID","AFFINE","LEAKY_RELU","THRESHHOLD_RELU","SCALED_TAHN","HARD_SIGMOID","ELU","SOFTSIGN","SOFTPLUS")
Also this layer supports MKLDNN (DNNL) and cuDNN acceleration

Parameters:

x - Input, with shape dependent on the data format (in config). (NUMERIC type)

LSTMLayerWeights - Configuration Object

LSTMLayerConfig - Configuration Object

lstmLayer

public SDVariable[] lstmLayer(String[] names,
                              SDVariable x,
                              LSTMLayerWeights LSTMLayerWeights,
                              LSTMLayerConfig LSTMLayerConfig)

Long Short-Term Memory layer - Hochreiter 1997.
SUPPORTS following data formats:
for unidirectional:
TNS: shapes [timeLength, numExamples, inOutSize]
NST: shapes [numExamples, inOutSize, timeLength]
NTS: shapes [numExamples, timeLength, inOutSize]
for bidirectional:
T2NS: shapes [timeLength, 2, numExamples, inOutSize] (for ONNX)
SUPPORTS following direction modes:
FWD: forward
BWD: backward
BIDIR_SUM: bidirectional sum
BIDIR_CONCAT: bidirectional concat
BIDIR_EXTRA_DIM: bidirectional extra output dim (in conjunction with format dataFormat - T2NS)
You may use different gate configurations:
specify gate/cell/out aplha/beta and numbers of activations for gate/cell/out described in activations enum
("RELU","SIGMOID","AFFINE","LEAKY_RELU","THRESHHOLD_RELU","SCALED_TAHN","HARD_SIGMOID","ELU","SOFTSIGN","SOFTPLUS")
Also this layer supports MKLDNN (DNNL) and cuDNN acceleration

Parameters:

names - names May be null. Arrays of names for the output variables.

x - Input, with shape dependent on the data format (in config). (NUMERIC type)

LSTMLayerWeights - Configuration Object

LSTMLayerConfig - Configuration Object

lstmblock

public SDVariable lstmblock(SDVariable maxTSLength,
                            SDVariable x,
                            SDVariable cLast,
                            SDVariable yLast,
                            LSTMWeights LSTMWeights,
                            LSTMConfiguration LSTMConfiguration)

The LSTM block

Parameters:

maxTSLength - (NUMERIC type)

x - Input, with shape dependent on the data format (in config). (NUMERIC type)

cLast - Previous/initial cell state, with shape [batchSize, numUnits] (NUMERIC type)

yLast - Previous/initial cell output, with shape [batchSize, numUnits] (NUMERIC type)

LSTMWeights - Configuration Object

LSTMConfiguration - Configuration Object

Returns:

output The layer's outputs. (NUMERIC type)

lstmblock

public SDVariable lstmblock(String name,
                            SDVariable maxTSLength,
                            SDVariable x,
                            SDVariable cLast,
                            SDVariable yLast,
                            LSTMWeights LSTMWeights,
                            LSTMConfiguration LSTMConfiguration)

The LSTM block

Parameters:

name - name May be null. Name for the output variable

maxTSLength - (NUMERIC type)

x - Input, with shape dependent on the data format (in config). (NUMERIC type)

cLast - Previous/initial cell state, with shape [batchSize, numUnits] (NUMERIC type)

yLast - Previous/initial cell output, with shape [batchSize, numUnits] (NUMERIC type)

LSTMWeights - Configuration Object

LSTMConfiguration - Configuration Object

Returns:

output The layer's outputs. (NUMERIC type)

lstmblock

public SDVariable lstmblock(SDVariable x,
                            LSTMWeights LSTMWeights,
                            LSTMConfiguration LSTMConfiguration)

The LSTM block

Parameters:

x - Input, with shape dependent on the data format (in config). (NUMERIC type)

LSTMWeights - Configuration Object

LSTMConfiguration - Configuration Object

Returns:

output The layer's outputs. (NUMERIC type)

lstmblock

public SDVariable lstmblock(String name,
                            SDVariable x,
                            LSTMWeights LSTMWeights,
                            LSTMConfiguration LSTMConfiguration)

The LSTM block

Parameters:

name - name May be null. Name for the output variable

x - Input, with shape dependent on the data format (in config). (NUMERIC type)

LSTMWeights - Configuration Object

LSTMConfiguration - Configuration Object

Returns:

output The layer's outputs. (NUMERIC type)

sru

public SDVariable sru(SDVariable x,
                      SDVariable initialC,
                      SDVariable mask,
                      SRUWeights SRUWeights)

The SRU layer. Does a single time step operation.

Parameters:

x - Input, with shape [batchSize, inSize] (NUMERIC type)

initialC - Initial cell state, with shape [batchSize, inSize] (NUMERIC type)

mask - An optional dropout mask, with shape [batchSize, inSize] (NUMERIC type)

SRUWeights - Configuration Object

Returns:

output The cell's outputs.. (NUMERIC type)

sru

public SDVariable sru(String name,
                      SDVariable x,
                      SDVariable initialC,
                      SDVariable mask,
                      SRUWeights SRUWeights)

The SRU layer. Does a single time step operation.

Parameters:

name - name May be null. Name for the output variable

x - Input, with shape [batchSize, inSize] (NUMERIC type)

initialC - Initial cell state, with shape [batchSize, inSize] (NUMERIC type)

mask - An optional dropout mask, with shape [batchSize, inSize] (NUMERIC type)

SRUWeights - Configuration Object

Returns:

output The cell's outputs.. (NUMERIC type)

sru

public SDVariable sru(SDVariable x,
                      SDVariable initialC,
                      SRUWeights SRUWeights)

The SRU layer. Does a single time step operation.

Parameters:

x - Input, with shape [batchSize, inSize] (NUMERIC type)

initialC - Initial cell state, with shape [batchSize, inSize] (NUMERIC type)

SRUWeights - Configuration Object

Returns:

output The cell's outputs.. (NUMERIC type)

sru

public SDVariable sru(String name,
                      SDVariable x,
                      SDVariable initialC,
                      SRUWeights SRUWeights)

The SRU layer. Does a single time step operation.

Parameters:

name - name May be null. Name for the output variable

x - Input, with shape [batchSize, inSize] (NUMERIC type)

initialC - Initial cell state, with shape [batchSize, inSize] (NUMERIC type)

SRUWeights - Configuration Object

Returns:

output The cell's outputs.. (NUMERIC type)

sruCell

public SDVariable sruCell(SDVariable x,
                          SDVariable cLast,
                          SRUWeights SRUWeights)

The SRU layer. Does a single time step operation.

Parameters:

x - Input, with shape [batchSize, inSize] (NUMERIC type)

cLast - Previous cell state, with shape [batchSize, inSize] (NUMERIC type)

SRUWeights - Configuration Object

Returns:

output The cell's outputs. (NUMERIC type)

sruCell

public SDVariable sruCell(String name,
                          SDVariable x,
                          SDVariable cLast,
                          SRUWeights SRUWeights)

The SRU layer. Does a single time step operation.

Parameters:

name - name May be null. Name for the output variable

x - Input, with shape [batchSize, inSize] (NUMERIC type)

cLast - Previous cell state, with shape [batchSize, inSize] (NUMERIC type)

SRUWeights - Configuration Object

Returns:

output The cell's outputs. (NUMERIC type)