Generative Adversarial Network Action Set

Provides actions for training generative adversarial network models.

tabularGanTrain Action

Trains a tabular GAN model.

CASL Syntax
Summary: Input and Output Tables
Parameter Descriptions

CASL Syntax

generativeAdversarialNet.tabularGanTrain <result=results> <status=rc> /

casOut={

caslib="string",

compress=TRUE | FALSE,

indexVars={"variable-name-1" <, "variable-name-2", ...>},

label="string",

lifetime=64-bit-integer,

maxMemSize=64-bit-integer,

memoryFormat="DVR" | "INHERIT" | "STANDARD",

name="table-name",

promote=TRUE | FALSE,

replace=TRUE | FALSE,

replication=integer,

tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE",

threadBlockSize=64-bit-integer,

timeStamp="string",

where={"string-1" <, "string-2", ...>}

centroidsTable={

caslib="string",

computedOnDemand=TRUE | FALSE,

computedVars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

computedVarsProgram="string",

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>},

groupBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

groupByMode="NOSORT" | "REDISTRIBUTE",

importOptions={fileType="ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DELIMITED" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SOUND" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters},

name="table-name",

orderBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

singlePass=TRUE | FALSE,

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

where="where-expression",

whereTable={

casLib="string"

dataSourceOptions={adls_noreq-parameters | bigquery-parameters | cas_noreq-parameters | clouddex-parameters | db2-parameters | dnfs-parameters | esp-parameters | fedsvr-parameters | gcs_noreq-parameters | hadoop-parameters | hana-parameters | impala-parameters | informix-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sapiq-parameters | sforce-parameters | singlestore_standard-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | ss_noreq-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}

name="table-name"

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}}

where="where-expression"

}

checkpointFreq=integer,

checkpointIn={

caslib="string",

computedOnDemand=TRUE | FALSE,

computedVars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

computedVarsProgram="string",

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>},

groupBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

groupByMode="NOSORT" | "REDISTRIBUTE",

name="table-name",

orderBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

singlePass=TRUE | FALSE,

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

where="where-expression",

whereTable={

casLib="string"

name="table-name"

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}}

where="where-expression"

}

checkpointOut={

caslib="string",

compress=TRUE | FALSE,

indexVars={"variable-name-1" <, "variable-name-2", ...>},

label="string",

lifetime=64-bit-integer,

maxMemSize=64-bit-integer,

memoryFormat="DVR" | "INHERIT" | "STANDARD",

name="table-name",

promote=TRUE | FALSE,

replace=TRUE | FALSE,

replication=integer,

tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE",

threadBlockSize=64-bit-integer,

timeStamp="string",

where={"string-1" <, "string-2", ...>}

display={

caseSensitive=TRUE | FALSE,

exclude=TRUE | FALSE,

excludeAll=TRUE | FALSE,

keyIsPath=TRUE | FALSE,

names={"string-1" <, "string-2", ...>},

pathType="LABEL" | "NAME",

traceNames=TRUE | FALSE

embeddingDim=integer,

gmmOptions={

alpha=double,

inference={

covariance="DIAGONAL" | "FULL"

maxVbIter=integer

threshold=double

maxClusters=integer,

seed=double

gpu={

deterministic=TRUE | FALSE,

device=integer,

enable=TRUE | FALSE

miniBatchSize=integer,

nominals={"variable-name-1" <, "variable-name-2", ...>},

numSamples=integer,

optimizerAe={method="ADAM", method-specific-parameters},

optimizerGan={method="ADAM", method-specific-parameters},

outputTables={

groupByVarsRaw=TRUE | FALSE,

includeAll=TRUE | FALSE,

names={"string-1" <, "string-2", ...>} | {key-1={casouttable-1} <, key-2={casouttable-2}, ...>},

repeated=TRUE | FALSE,

replace=TRUE | FALSE

packSize=integer,

printFreq=integer,

regDWeight=integer,

saveState={

caslib="string",

label="string",

lifetime=64-bit-integer,

memoryFormat="DVR" | "INHERIT" | "STANDARD",

name="table-name",

promote=TRUE | FALSE,

replace=TRUE | FALSE,

tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE"

scoreSeed=64-bit-integer,

seed=64-bit-integer,

table={

caslib="string",

computedOnDemand=TRUE | FALSE,

computedVars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

computedVarsProgram="string",

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>},

name="table-name",

orderBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

singlePass=TRUE | FALSE,

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

where="where-expression",

whereTable={

casLib="string"

name="table-name"

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}}

where="where-expression"

}

useLogLevelFreq=TRUE | FALSE

;

indicates a required parameter

Summary: Input and Output Tables

If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.

Parameters for Reading Input Tables
Parameter	Subparameter	Description
centroidsTable	—	specifies the CAS table that contains Gaussian mixture model (GMM) centroid information for continuous variables.
checkpointIn	—	specifies the checkpoint CAS table to be loaded to restore your model. If you omit this parameter, the model is trained from scratch.
required parametertable	—	specifies the input CAS table that contains tabular data.

Parameters for Creating Output Tables
Parameter	Subparameter	Description
required parametercasOut	—	specifies the output CAS table in which to store the generated tabular data from the trained model.
checkpointOut	—	specifies the CAS table in which to save the current model as a checkpoint.
outputTables	names	lists the names of results tables to save as CAS tables on the server.
required parametersaveState	—	specifies the table in which to save the model state for model scoring.

Parameter Descriptions

* casOut={casouttable}

specifies the output CAS table in which to store the generated tabular data from the trained model.

For more information about specifying the casOut parameter, see the common casouttable (Form 1) parameter (Appendix A: Common Parameters).

centroidsTable={castable}

specifies the CAS table that contains Gaussian mixture model (GMM) centroid information for continuous variables.

For more information about specifying the centroidsTable parameter, see the common castable (Form 1) parameter (Appendix A: Common Parameters).

checkpointFreq=integer

specifies the frequency at which to save a checkpoint during the training.

Default	5000
Minimum value	1

checkpointIn={castable}

specifies the checkpoint CAS table to be loaded to restore your model. If you omit this parameter, the model is trained from scratch.

For more information about specifying the checkpointIn parameter, see the common castable (Form 1) parameter (Appendix A: Common Parameters).

checkpointOut={casouttable}

specifies the CAS table in which to save the current model as a checkpoint.

For more information about specifying the checkpointOut parameter, see the common casouttable (Form 1) parameter (Appendix A: Common Parameters).

display={displayTables}

specifies a list of results tables to send to the client for display.

For more information about specifying the display parameter, see the common displayTables parameter (Appendix A: Common Parameters).

embeddingDim=integer

specifies the dimensions of the input noise to the generator.

Default	128
Minimum value	1

gmmOptions={gmmOptions}

specifies the Gaussian mixture model (GMM) parameters to generate the centroid information for continuous variables.

The gmmOptions value can be one or more of the following:

alpha=double

specifies the concentration parameter for the Dirichlet process.

Default	1
Minimum value (exclusive)	0

inference={gmmInference}

specifies the GMM inference parameters.

The gmmInference value can be one or more of the following:

covariance="DIAGONAL" | "FULL"

specifies the covariance matrix type of the Gaussian mixtures.

Default	DIAGONAL

maxVbIter=integer

specifies the number of iterations for the variational Bayesian (VB) inference.

Default	100
Minimum value	1

threshold=double

specifies the threshold of the difference between the current and previous likelihoods.

Default	0.01
Minimum value	0

maxClusters=integer

specifies the GMM maximum number of clusters.

Default	100
Minimum value	1

seed=double

specifies a double to use to start the pseudorandom number generator for initialization.

Default	0
Minimum value	0

gpu={gpuOptions}

specifies options that are related to graphics processing unit (GPU) devices.

The gpuOptions value can be one or more of the following:

deterministic=TRUE | FALSE

when set to True, tells the NVIDIA CUDA Deep Neural Network library (CuDNN) that you want only the deterministic implementations. NOTE: Setting this parameter to True can significantly slow down the training process.

Default	FALSE

device=integer

specifies the ID of one GPU device that is to be used.

Alias	devices
Default	0
Minimum value	0
Requirement	The specified values must be unique.

enable=TRUE | FALSE

when set to True, specifies that a GPU device is to be used.

Alias	useGPU
Default	TRUE

miniBatchSize=integer

specifies the number of observations in one minibatch.

Default	500
Minimum value	2

nominals={"variable-name-1" <, "variable-name-2", ...>}

specifies the list of nominal variables that are included in the input CAS table's variable list.

Alias	nom

numSamples=integer

specifies the number of observations to generate.

Default	1000
Minimum value	1

optimizerAe={method="ADAM", method-specific-parameters}

specifies the optimization method to use in training the autoencoder model. Currently only the Adam method is supported.

Alias	optimizationAe

The value that you specify for the method parameter determines the other parameters that apply.

optimizerGan={method="ADAM", method-specific-parameters}

specifies the optimization method to use in training the GAN model. Currently only the Adam method is supported.

Alias	optimizationGan

The value that you specify for the method parameter determines the other parameters that apply.

outputTables={outputTables}

lists the names of results tables to save as CAS tables on the server.

For more information about specifying the outputTables parameter, see the common outputTables parameter (Appendix A: Common Parameters).

packSize=integer

specifies the number of samples to group together in applying the discriminator. This number must be a factor of the minibatch size.

Default	10
Minimum value	1

printFreq=integer

specifies the frequency at which to print losses to the log and the iteration history table.

Default	1
Minimum value	1

regDWeight=integer

specifies the weight to use in regularizing the discriminator.

Default	10
Minimum value	0

* saveState={casouttable}

specifies the table in which to save the model state for model scoring.

Long form	saveState={name="table-name"}
Shortcut form	saveState="table-name"

The casouttable value can be one or more of the following:

caslib="string"

specifies the name of the caslib for the output table.

label="string"

specifies the descriptive label to associate with the table.

lifetime=64-bit-integer

specifies the number of seconds to keep the table in memory after it is last accessed. The table is dropped if it is not accessed for the specified number of seconds.

Default	0
Minimum value	0

memoryFormat="DVR" | "INHERIT" | "STANDARD"

specifies the memory format for the output table.

Default	INHERIT

DVR

use the duplicate value reduction memory format. This memory format can reduce the memory consumption and file size when the input data contains duplicate values.

INHERIT

use the default memory format that is set for the server. By default, the server uses the standard memory format. If an administrator sets the CAS_DEFAULT_MEMORY_FORMAT environment variable to DVR, then the DVR memory format is set as the default for the server.

STANDARD

use the standard memory format.

name="table-name"

specifies the name for the output table.

promote=TRUE | FALSE

when set to True, adds the output table with a global scope. This enables other sessions to access the table, subject to access controls. The target caslib must also have a global scope.

Default	FALSE

replace=TRUE | FALSE

when set to True, overwrites an existing table that has the same name.

Default	FALSE

tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE"

Specifies the Table Redistribution Policy when the number of worker pods increases on a running CAS server.

DEFER

Defer redistribution policy selection to higher-level entity.

NOREDIST

Do not redistribute table data when the number of worker pods changes on a running CAS server.

REBALANCE

Rebalance table data when the number of worker pods changes on a running CAS server.

scoreSeed=64-bit-integer

specifies the seed to use for the random number generator for scoring. A value of 0 means use the time from the computer's clock as the seed.

Default	0
Minimum value	0

seed=64-bit-integer

specifies the seed to use for the random number generator for training. A value of 0 means use the time from the computer's clock as the seed.

Default	0
Minimum value	0

* table={castable}

specifies the input CAS table that contains tabular data.

Long form	table={name="table-name"}
Shortcut form	table="table-name"

The castable value can be one or more of the following:

caslib="string"

specifies the caslib for the input table that you want to use with the action. By default, the active caslib is used. Specify a value only if you need to access a table from a different caslib.

computedOnDemand=TRUE | FALSE

when set to True, creates the computed variables when the table is loaded instead of when the action begins.

Alias	compOnDemand
Default	FALSE

computedVars={{casinvardesc-1} <, {casinvardesc-2}, ...>}

specifies the names of the computed variables to create. Specify an expression for each variable in the computedVarsProgram parameter. If you do not specify this parameter, then all variables from computedVarsProgram are automatically included.

Alias	compVars

The casinvardesc value can be one or more of the following:

format="string"

specifies the format to apply to the variable.

formattedLength=integer

specifies the length of the format field plus the length of the format precision.

label="string"

specifies the descriptive label for the variable.

* name="variable-name"

specifies the name for the variable.

nfd=integer

specifies the length of the format precision.

nfl=integer

specifies the length of the format field.

computedVarsProgram="string"

specifies an expression for each computed variable that you include in the computedVars parameter.

Alias	compPgm

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>}

specifies data source options.

Aliases	options
Aliases	dataSource

importOptions={fileType="ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters}

specifies the settings for reading a table from a data source.

Alias	import

For more information about specifying the importOptions parameter, see the common importOptions parameter (Appendix A: Common Parameters).

* name="table-name"

specifies the name of the input table.

orderBy={{casinvardesc-1} <, {casinvardesc-2}, ...>}

specifies the variables to use for ordering observations within partitions. This parameter applies to partitioned tables, or it can be combined with variables that are specified in the groupBy parameter when the value of the groupByMode parameter is set to REDISTRIBUTE.

The casinvardesc value can be one or more of the following:

format="string"

specifies the format to apply to the variable.

formattedLength=integer

specifies the length of the format field plus the length of the format precision.

label="string"

specifies the descriptive label for the variable.

* name="variable-name"

specifies the name for the variable.

nfd=integer

specifies the length of the format precision.

nfl=integer

specifies the length of the format field.

singlePass=TRUE | FALSE

when set to True, does not create a transient table on the server. Setting this parameter to True can be efficient, but the data might not have stable ordering upon repeated runs.

Default	FALSE

vars={{casinvardesc-1} <, {casinvardesc-2}, ...>}

specifies the variables to use in the action.

The casinvardesc value can be one or more of the following:

format="string"

specifies the format to apply to the variable.

formattedLength=integer

specifies the length of the format field plus the length of the format precision.

label="string"

specifies the descriptive label for the variable.

* name="variable-name"

specifies the name for the variable.

nfd=integer

specifies the length of the format precision.

nfl=integer

specifies the length of the format field.

where="where-expression"

specifies an expression for subsetting the input data.

whereTable={groupbytable}

specifies an input table that contains rows to use as a WHERE filter. If the vars parameter is not specified, then all the variable names that are common to the input table and the filtering table are used to find matching rows. If the where parameter for the input table and this parameter are specified, then this filtering table is applied first.

The groupbytable value can be one or more of the following:

casLib="string"

specifies the caslib for the filter table. By default, the active caslib is used.

dataSourceOptions={adls_noreq-parameters | bigquery-parameters | cas_noreq-parameters | clouddex-parameters | db2-parameters | dnfs-parameters | esp-parameters | fedsvr-parameters | gcs_noreq-parameters | hadoop-parameters | hana-parameters | impala-parameters | informix-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sapiq-parameters | sforce-parameters | singlestore_standard-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | ss_noreq-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}

specifies data source options.

Aliases	options
Aliases	dataSource

For more information about specifying the dataSourceOptions parameter, see the common dataSourceOptions parameter (Appendix A: Common Parameters).

importOptions={fileType="ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters}

specifies the settings for reading a table from a data source.

Alias	import

For more information about specifying the importOptions parameter, see the common importOptions parameter (Appendix A: Common Parameters).

* name="table-name"

specifies the name of the filter table.

vars={{casinvardesc-1} <, {casinvardesc-2}, ...>}

specifies the variable names to use from the filter table.

The casinvardesc value can be one or more of the following:

format="string"

specifies the format to apply to the variable.

formattedLength=integer

specifies the length of the format field plus the length of the format precision.

label="string"

specifies the descriptive label for the variable.

* name="variable-name"

specifies the name for the variable.

nfd=integer

specifies the length of the format precision.

nfl=integer

specifies the length of the format field.

where="where-expression"

specifies an expression for subsetting the data from the filter table.

useLogLevelFreq=TRUE | FALSE

when set to True, uses the log frequency of categorical levels in the conditional sampling.

Default	TRUE

Parameters for method="ADAM"

beta1=double

specifies the exponential decay rate for the first-moment estimates.

Default	0.9
Range	[0–1)

beta2=double

specifies the exponential decay rate for the second-moment estimates.

Default	0.999
Range	[0–1)

learningRate=double

specifies the learning rate for the optimizer.

Default	0.001
Range	(0–1]

numEpochs=integer

specifies the number of epochs to use in training the model.

Default	150
Minimum value	0

weightDecay=double

specifies the weight decay for the autoencoder's optimizer.

Default	1E-08
Range	0–1

Parameters for method="ADAM"

beta1=double

specifies the exponential decay rate for the first-moment estimates.

Default	0.5
Range	[0–1)

beta2=double

specifies the exponential decay rate for the second-moment estimates.

Default	0.9
Range	[0–1)

learningRate=double

specifies the learning rate for the optimizer.

Default	2E-05
Range	(0–1]

numEpochs=integer

specifies the number of epochs to use in training the model.

Default	150
Minimum value	0

weightDecayD=double

specifies the weight decay for the discriminator's optimizer.

Default	0.0001
Range	0–1

weightDecayG=double

specifies the weight decay for the generator's optimizer.

Default	1E-06
Range	0–1

tabularGanTrain Action

Trains a tabular GAN model.

Lua Syntax
Summary: Input and Output Tables
Parameter Descriptions

Lua Syntax

results, info = s:generativeAdversarialNet_tabularGanTrain{

casOut={

caslib="string",

compress=true | false,

indexVars={"variable-name-1" <, "variable-name-2", ...>},

label="string",

lifetime=64-bit-integer,

maxMemSize=64-bit-integer,

memoryFormat="DVR" | "INHERIT" | "STANDARD",

name="table-name",

promote=true | false,

replace=true | false,

replication=integer,

tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE",

threadBlockSize=64-bit-integer,

timeStamp="string",

where={"string-1" <, "string-2", ...>}

centroidsTable={

caslib="string",

computedOnDemand=true | false,

computedVars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

computedVarsProgram="string",

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>},

groupBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

groupByMode="NOSORT" | "REDISTRIBUTE",

name="table-name",

orderBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

singlePass=true | false,

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

where="where-expression",

whereTable={

casLib="string"

name="table-name"

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}}

where="where-expression"

}

checkpointFreq=integer,

checkpointIn={

caslib="string",

computedOnDemand=true | false,

computedVars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

computedVarsProgram="string",

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>},

groupBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

groupByMode="NOSORT" | "REDISTRIBUTE",

name="table-name",

orderBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

singlePass=true | false,

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

where="where-expression",

whereTable={

casLib="string"

name="table-name"

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}}

where="where-expression"

}

checkpointOut={

caslib="string",

compress=true | false,

indexVars={"variable-name-1" <, "variable-name-2", ...>},

label="string",

lifetime=64-bit-integer,

maxMemSize=64-bit-integer,

memoryFormat="DVR" | "INHERIT" | "STANDARD",

name="table-name",

promote=true | false,

replace=true | false,

replication=integer,

tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE",

threadBlockSize=64-bit-integer,

timeStamp="string",

where={"string-1" <, "string-2", ...>}

display={

caseSensitive=true | false,

exclude=true | false,

excludeAll=true | false,

keyIsPath=true | false,

names={"string-1" <, "string-2", ...>},

pathType="LABEL" | "NAME",

traceNames=true | false

embeddingDim=integer,

gmmOptions={

alpha=double,

inference={

covariance="DIAGONAL" | "FULL"

maxVbIter=integer

threshold=double

maxClusters=integer,

seed=double

gpu={

deterministic=true | false,

device=integer,

enable=true | false

miniBatchSize=integer,

nominals={"variable-name-1" <, "variable-name-2", ...>},

numSamples=integer,

optimizerAe={method="ADAM", method-specific-parameters},

optimizerGan={method="ADAM", method-specific-parameters},

outputTables={

groupByVarsRaw=true | false,

includeAll=true | false,

names={"string-1" <, "string-2", ...>} | {key-1={casouttable-1} <, key-2={casouttable-2}, ...>},

repeated=true | false,

replace=true | false

packSize=integer,

printFreq=integer,

regDWeight=integer,

saveState={

caslib="string",

label="string",

lifetime=64-bit-integer,

memoryFormat="DVR" | "INHERIT" | "STANDARD",

name="table-name",

promote=true | false,

replace=true | false,

tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE"

scoreSeed=64-bit-integer,

seed=64-bit-integer,

table={

caslib="string",

computedOnDemand=true | false,

computedVars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

computedVarsProgram="string",

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>},

name="table-name",

orderBy={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

singlePass=true | false,

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}},

where="where-expression",

whereTable={

casLib="string"

name="table-name"

vars={{

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

}, {...}}

where="where-expression"

}

useLogLevelFreq=true | false

}

indicates a required parameter

Summary: Input and Output Tables

If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.

Parameters for Reading Input Tables
Parameter	Subparameter	Description
centroidsTable	—	specifies the CAS table that contains Gaussian mixture model (GMM) centroid information for continuous variables.
checkpointIn	—	specifies the checkpoint CAS table to be loaded to restore your model. If you omit this parameter, the model is trained from scratch.
required parametertable	—	specifies the input CAS table that contains tabular data.

Parameters for Creating Output Tables
Parameter	Subparameter	Description
required parametercasOut	—	specifies the output CAS table in which to store the generated tabular data from the trained model.
checkpointOut	—	specifies the CAS table in which to save the current model as a checkpoint.
outputTables	names	lists the names of results tables to save as CAS tables on the server.
required parametersaveState	—	specifies the table in which to save the model state for model scoring.

Parameter Descriptions

* casOut={casouttable}

specifies the output CAS table in which to store the generated tabular data from the trained model.

For more information about specifying the casOut parameter, see the common casouttable (Form 1) parameter (Appendix A: Common Parameters).

centroidsTable={castable}

specifies the CAS table that contains Gaussian mixture model (GMM) centroid information for continuous variables.

For more information about specifying the centroidsTable parameter, see the common castable (Form 1) parameter (Appendix A: Common Parameters).

checkpointFreq=integer

specifies the frequency at which to save a checkpoint during the training.

Default	5000
Minimum value	1

checkpointIn={castable}

specifies the checkpoint CAS table to be loaded to restore your model. If you omit this parameter, the model is trained from scratch.

For more information about specifying the checkpointIn parameter, see the common castable (Form 1) parameter (Appendix A: Common Parameters).

checkpointOut={casouttable}

specifies the CAS table in which to save the current model as a checkpoint.

For more information about specifying the checkpointOut parameter, see the common casouttable (Form 1) parameter (Appendix A: Common Parameters).

display={displayTables}

specifies a list of results tables to send to the client for display.

For more information about specifying the display parameter, see the common displayTables parameter (Appendix A: Common Parameters).

embeddingDim=integer

specifies the dimensions of the input noise to the generator.

Default	128
Minimum value	1

gmmOptions={gmmOptions}

specifies the Gaussian mixture model (GMM) parameters to generate the centroid information for continuous variables.

The gmmOptions value can be one or more of the following:

alpha=double

specifies the concentration parameter for the Dirichlet process.

Default	1
Minimum value (exclusive)	0

inference={gmmInference}

specifies the GMM inference parameters.

The gmmInference value can be one or more of the following:

covariance="DIAGONAL" | "FULL"

specifies the covariance matrix type of the Gaussian mixtures.

Default	DIAGONAL

maxVbIter=integer

specifies the number of iterations for the variational Bayesian (VB) inference.

Default	100
Minimum value	1

threshold=double

specifies the threshold of the difference between the current and previous likelihoods.

Default	0.01
Minimum value	0

maxClusters=integer

specifies the GMM maximum number of clusters.

Default	100
Minimum value	1

seed=double

specifies a double to use to start the pseudorandom number generator for initialization.

Default	0
Minimum value	0

gpu={gpuOptions}

specifies options that are related to graphics processing unit (GPU) devices.

The gpuOptions value can be one or more of the following:

deterministic=true | false

Default	false

device=integer

specifies the ID of one GPU device that is to be used.

Alias	devices
Default	0
Minimum value	0
Requirement	The specified values must be unique.

enable=true | false

when set to True, specifies that a GPU device is to be used.

Alias	useGPU
Default	true

miniBatchSize=integer

specifies the number of observations in one minibatch.

Default	500
Minimum value	2

nominals={"variable-name-1" <, "variable-name-2", ...>}

specifies the list of nominal variables that are included in the input CAS table's variable list.

Alias	nom

numSamples=integer

specifies the number of observations to generate.

Default	1000
Minimum value	1

optimizerAe={method="ADAM", method-specific-parameters}

specifies the optimization method to use in training the autoencoder model. Currently only the Adam method is supported.

Alias	optimizationAe

The value that you specify for the method parameter determines the other parameters that apply.

optimizerGan={method="ADAM", method-specific-parameters}

specifies the optimization method to use in training the GAN model. Currently only the Adam method is supported.

Alias	optimizationGan

The value that you specify for the method parameter determines the other parameters that apply.

outputTables={outputTables}

lists the names of results tables to save as CAS tables on the server.

For more information about specifying the outputTables parameter, see the common outputTables parameter (Appendix A: Common Parameters).

packSize=integer

specifies the number of samples to group together in applying the discriminator. This number must be a factor of the minibatch size.

Default	10
Minimum value	1

printFreq=integer

specifies the frequency at which to print losses to the log and the iteration history table.

Default	1
Minimum value	1

regDWeight=integer

specifies the weight to use in regularizing the discriminator.

Default	10
Minimum value	0

* saveState={casouttable}

specifies the table in which to save the model state for model scoring.

Long form	saveState={name="table-name"}
Shortcut form	saveState="table-name"

The casouttable value can be one or more of the following:

caslib="string"

specifies the name of the caslib for the output table.

label="string"

specifies the descriptive label to associate with the table.

lifetime=64-bit-integer

specifies the number of seconds to keep the table in memory after it is last accessed. The table is dropped if it is not accessed for the specified number of seconds.

Default	0
Minimum value	0

memoryFormat="DVR" | "INHERIT" | "STANDARD"

specifies the memory format for the output table.

Default	INHERIT

DVR

use the duplicate value reduction memory format. This memory format can reduce the memory consumption and file size when the input data contains duplicate values.

INHERIT

STANDARD

use the standard memory format.

name="table-name"

specifies the name for the output table.

promote=true | false

when set to True, adds the output table with a global scope. This enables other sessions to access the table, subject to access controls. The target caslib must also have a global scope.

Default	false

replace=true | false

when set to True, overwrites an existing table that has the same name.

Default	false

tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE"

Specifies the Table Redistribution Policy when the number of worker pods increases on a running CAS server.

DEFER

Defer redistribution policy selection to higher-level entity.

NOREDIST

Do not redistribute table data when the number of worker pods changes on a running CAS server.

REBALANCE

Rebalance table data when the number of worker pods changes on a running CAS server.

scoreSeed=64-bit-integer

specifies the seed to use for the random number generator for scoring. A value of 0 means use the time from the computer's clock as the seed.

Default	0
Minimum value	0

seed=64-bit-integer

specifies the seed to use for the random number generator for training. A value of 0 means use the time from the computer's clock as the seed.

Default	0
Minimum value	0

* table={castable}

specifies the input CAS table that contains tabular data.

Long form	table={name="table-name"}
Shortcut form	table="table-name"

The castable value can be one or more of the following:

caslib="string"

specifies the caslib for the input table that you want to use with the action. By default, the active caslib is used. Specify a value only if you need to access a table from a different caslib.

computedOnDemand=true | false

when set to True, creates the computed variables when the table is loaded instead of when the action begins.

Alias	compOnDemand
Default	false

computedVars={{casinvardesc-1} <, {casinvardesc-2}, ...>}

Alias	compVars

The casinvardesc value can be one or more of the following:

format="string"

specifies the format to apply to the variable.

formattedLength=integer

specifies the length of the format field plus the length of the format precision.

label="string"

specifies the descriptive label for the variable.

* name="variable-name"

specifies the name for the variable.

nfd=integer

specifies the length of the format precision.

nfl=integer

specifies the length of the format field.

computedVarsProgram="string"

specifies an expression for each computed variable that you include in the computedVars parameter.

Alias	compPgm

dataSourceOptions={key-1=any-list-or-data-type-1 <, key-2=any-list-or-data-type-2, ...>}

specifies data source options.

Aliases	options
Aliases	dataSource

importOptions={fileType="ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters}

specifies the settings for reading a table from a data source.

Alias	import

For more information about specifying the importOptions parameter, see the common importOptions parameter (Appendix A: Common Parameters).

* name="table-name"

specifies the name of the input table.

orderBy={{casinvardesc-1} <, {casinvardesc-2}, ...>}

The casinvardesc value can be one or more of the following:

format="string"

specifies the format to apply to the variable.

formattedLength=integer

specifies the length of the format field plus the length of the format precision.

label="string"

specifies the descriptive label for the variable.

* name="variable-name"

specifies the name for the variable.

nfd=integer

specifies the length of the format precision.

nfl=integer

specifies the length of the format field.

singlePass=true | false

when set to True, does not create a transient table on the server. Setting this parameter to True can be efficient, but the data might not have stable ordering upon repeated runs.

Default	false

vars={{casinvardesc-1} <, {casinvardesc-2}, ...>}

specifies the variables to use in the action.

The casinvardesc value can be one or more of the following:

format="string"

specifies the format to apply to the variable.

formattedLength=integer

specifies the length of the format field plus the length of the format precision.

label="string"

specifies the descriptive label for the variable.

* name="variable-name"

specifies the name for the variable.

nfd=integer

specifies the length of the format precision.

nfl=integer

specifies the length of the format field.

where="where-expression"

specifies an expression for subsetting the input data.

whereTable={groupbytable}

The groupbytable value can be one or more of the following:

casLib="string"

specifies the caslib for the filter table. By default, the active caslib is used.

dataSourceOptions={adls_noreq-parameters | bigquery-parameters | cas_noreq-parameters | clouddex-parameters | db2-parameters | dnfs-parameters | esp-parameters | fedsvr-parameters | gcs_noreq-parameters | hadoop-parameters | hana-parameters | impala-parameters | informix-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sapiq-parameters | sforce-parameters | singlestore_standard-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | ss_noreq-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}

specifies data source options.

Aliases	options
Aliases	dataSource

For more information about specifying the dataSourceOptions parameter, see the common dataSourceOptions parameter (Appendix A: Common Parameters).

importOptions={fileType="ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters}

specifies the settings for reading a table from a data source.

Alias	import

For more information about specifying the importOptions parameter, see the common importOptions parameter (Appendix A: Common Parameters).

* name="table-name"

specifies the name of the filter table.

vars={{casinvardesc-1} <, {casinvardesc-2}, ...>}

specifies the variable names to use from the filter table.

The casinvardesc value can be one or more of the following:

format="string"

specifies the format to apply to the variable.

formattedLength=integer

specifies the length of the format field plus the length of the format precision.

label="string"

specifies the descriptive label for the variable.

* name="variable-name"

specifies the name for the variable.

nfd=integer

specifies the length of the format precision.

nfl=integer

specifies the length of the format field.

where="where-expression"

specifies an expression for subsetting the data from the filter table.

useLogLevelFreq=true | false

when set to True, uses the log frequency of categorical levels in the conditional sampling.

Default	true

Parameters for method="ADAM"

beta1=double

specifies the exponential decay rate for the first-moment estimates.

Default	0.9
Range	[0–1)

beta2=double

specifies the exponential decay rate for the second-moment estimates.

Default	0.999
Range	[0–1)

learningRate=double

specifies the learning rate for the optimizer.

Default	0.001
Range	(0–1]

numEpochs=integer

specifies the number of epochs to use in training the model.

Default	150
Minimum value	0

weightDecay=double

specifies the weight decay for the autoencoder's optimizer.

Default	1E-08
Range	0–1

Parameters for method="ADAM"

beta1=double

specifies the exponential decay rate for the first-moment estimates.

Default	0.5
Range	[0–1)

beta2=double

specifies the exponential decay rate for the second-moment estimates.

Default	0.9
Range	[0–1)

learningRate=double

specifies the learning rate for the optimizer.

Default	2E-05
Range	(0–1]

numEpochs=integer

specifies the number of epochs to use in training the model.

Default	150
Minimum value	0

weightDecayD=double

specifies the weight decay for the discriminator's optimizer.

Default	0.0001
Range	0–1

weightDecayG=double

specifies the weight decay for the generator's optimizer.

Default	1E-06
Range	0–1

tabularGanTrain Action

Trains a tabular GAN model.

Python Syntax
Summary: Input and Output Tables
Parameter Descriptions

Python Syntax

results=s.generativeAdversarialNet.tabularGanTrain(

casOut={

"caslib":"string",

"compress":True | False,

"indexVars":["variable-name-1" <, "variable-name-2", ...>],

"label":"string",

"lifetime":64-bit-integer,

"maxMemSize":64-bit-integer,

"memoryFormat":"DVR" | "INHERIT" | "STANDARD",

"name":"table-name",

"promote":True | False,

"replace":True | False,

"replication":integer,

"tableRedistUpPolicy":"DEFER" | "NOREDIST" | "REBALANCE",

"threadBlockSize":64-bit-integer,

"timeStamp":"string",

"where":["string-1" <, "string-2", ...>]

centroidsTable={

"caslib":"string",

"computedOnDemand":True | False,

"computedVars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"computedVarsProgram":"string",

"dataSourceOptions":{"key-1":{any-list-or-data-type-1} <, "key-2":{any-list-or-data-type-2}, ...>},

"groupBy":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"groupByMode":"NOSORT" | "REDISTRIBUTE",

"importOptions":{"fileType":"ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DELIMITED" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SOUND" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters},

"name":"table-name",

"orderBy":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"singlePass":True | False,

"vars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"where":"where-expression",

"whereTable":{

"casLib":"string"

"dataSourceOptions":{adls_noreq-parameters | bigquery-parameters | cas_noreq-parameters | clouddex-parameters | db2-parameters | dnfs-parameters | esp-parameters | fedsvr-parameters | gcs_noreq-parameters | hadoop-parameters | hana-parameters | impala-parameters | informix-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sapiq-parameters | sforce-parameters | singlestore_standard-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | ss_noreq-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}

"name":"table-name"

"vars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>]

"where":"where-expression"

}

checkpointFreq=integer,

checkpointIn={

"caslib":"string",

"computedOnDemand":True | False,

"computedVars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"computedVarsProgram":"string",

"dataSourceOptions":{"key-1":{any-list-or-data-type-1} <, "key-2":{any-list-or-data-type-2}, ...>},

"groupBy":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"groupByMode":"NOSORT" | "REDISTRIBUTE",

"name":"table-name",

"orderBy":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"singlePass":True | False,

"vars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"where":"where-expression",

"whereTable":{

"casLib":"string"

"name":"table-name"

"vars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>]

"where":"where-expression"

}

checkpointOut={

"caslib":"string",

"compress":True | False,

"indexVars":["variable-name-1" <, "variable-name-2", ...>],

"label":"string",

"lifetime":64-bit-integer,

"maxMemSize":64-bit-integer,

"memoryFormat":"DVR" | "INHERIT" | "STANDARD",

"name":"table-name",

"promote":True | False,

"replace":True | False,

"replication":integer,

"tableRedistUpPolicy":"DEFER" | "NOREDIST" | "REBALANCE",

"threadBlockSize":64-bit-integer,

"timeStamp":"string",

"where":["string-1" <, "string-2", ...>]

display={

"caseSensitive":True | False,

"exclude":True | False,

"excludeAll":True | False,

"keyIsPath":True | False,

"names":["string-1" <, "string-2", ...>],

"pathType":"LABEL" | "NAME",

"traceNames":True | False

embeddingDim=integer,

gmmOptions={

"alpha":double,

"inference":{

"covariance":"DIAGONAL" | "FULL"

"maxVbIter":integer

"threshold":double

"maxClusters":integer,

"seed":double

gpu={

"deterministic":True | False,

"device":integer,

"enable":True | False

miniBatchSize=integer,

nominals=["variable-name-1" <, "variable-name-2", ...>],

numSamples=integer,

optimizerAe={"method":"ADAM", method-specific-parameters},

optimizerGan={"method":"ADAM", method-specific-parameters},

outputTables={

"groupByVarsRaw":True | False,

"includeAll":True | False,

"names":["string-1" <, "string-2", ...>] | {"key-1":{casouttable-1} <, "key-2":{casouttable-2}, ...>},

"repeated":True | False,

"replace":True | False

packSize=integer,

printFreq=integer,

regDWeight=integer,

saveState={

"caslib":"string",

"label":"string",

"lifetime":64-bit-integer,

"memoryFormat":"DVR" | "INHERIT" | "STANDARD",

"name":"table-name",

"promote":True | False,

"replace":True | False,

"tableRedistUpPolicy":"DEFER" | "NOREDIST" | "REBALANCE"

scoreSeed=64-bit-integer,

seed=64-bit-integer,

table={

"caslib":"string",

"computedOnDemand":True | False,

"computedVars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"computedVarsProgram":"string",

"dataSourceOptions":{"key-1":{any-list-or-data-type-1} <, "key-2":{any-list-or-data-type-2}, ...>},

"name":"table-name",

"orderBy":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"singlePass":True | False,

"vars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>],

"where":"where-expression",

"whereTable":{

"casLib":"string"

"name":"table-name"

"vars":[{

"format":"string",

"formattedLength":integer,

"label":"string",

"name":"variable-name",

"nfd":integer,

"nfl":integer

}<, {...}>]

"where":"where-expression"

}

useLogLevelFreq=True | False

)

indicates a required parameter

Summary: Input and Output Tables

If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.

Parameters for Reading Input Tables
Parameter	Subparameter	Description
centroidsTable	—	specifies the CAS table that contains Gaussian mixture model (GMM) centroid information for continuous variables.
checkpointIn	—	specifies the checkpoint CAS table to be loaded to restore your model. If you omit this parameter, the model is trained from scratch.
required parametertable	—	specifies the input CAS table that contains tabular data.

Parameters for Creating Output Tables
Parameter	Subparameter	Description
required parametercasOut	—	specifies the output CAS table in which to store the generated tabular data from the trained model.
checkpointOut	—	specifies the CAS table in which to save the current model as a checkpoint.
outputTables	names	lists the names of results tables to save as CAS tables on the server.
required parametersaveState	—	specifies the table in which to save the model state for model scoring.

Parameter Descriptions

* casOut={casouttable}

specifies the output CAS table in which to store the generated tabular data from the trained model.

For more information about specifying the casOut parameter, see the common casouttable (Form 1) parameter (Appendix A: Common Parameters).

centroidsTable={castable}

specifies the CAS table that contains Gaussian mixture model (GMM) centroid information for continuous variables.

For more information about specifying the centroidsTable parameter, see the common castable (Form 1) parameter (Appendix A: Common Parameters).

checkpointFreq=integer

specifies the frequency at which to save a checkpoint during the training.

Default	5000
Minimum value	1

checkpointIn={castable}

specifies the checkpoint CAS table to be loaded to restore your model. If you omit this parameter, the model is trained from scratch.

For more information about specifying the checkpointIn parameter, see the common castable (Form 1) parameter (Appendix A: Common Parameters).

checkpointOut={casouttable}

specifies the CAS table in which to save the current model as a checkpoint.

For more information about specifying the checkpointOut parameter, see the common casouttable (Form 1) parameter (Appendix A: Common Parameters).

display={displayTables}

specifies a list of results tables to send to the client for display.

For more information about specifying the display parameter, see the common displayTables parameter (Appendix A: Common Parameters).

embeddingDim=integer

specifies the dimensions of the input noise to the generator.

Default	128
Minimum value	1

gmmOptions={gmmOptions}

specifies the Gaussian mixture model (GMM) parameters to generate the centroid information for continuous variables.

The gmmOptions value can be one or more of the following:

"alpha":double

specifies the concentration parameter for the Dirichlet process.

Default	1
Minimum value (exclusive)	0

"inference":{gmmInference}

specifies the GMM inference parameters.

The gmmInference value can be one or more of the following:

"covariance":"DIAGONAL" | "FULL"

specifies the covariance matrix type of the Gaussian mixtures.

Default	DIAGONAL

"maxVbIter":integer

specifies the number of iterations for the variational Bayesian (VB) inference.

Default	100
Minimum value	1

"threshold":double

specifies the threshold of the difference between the current and previous likelihoods.

Default	0.01
Minimum value	0

"maxClusters":integer

specifies the GMM maximum number of clusters.

Default	100
Minimum value	1

"seed":double

specifies a double to use to start the pseudorandom number generator for initialization.

Default	0
Minimum value	0

gpu={gpuOptions}

specifies options that are related to graphics processing unit (GPU) devices.

The gpuOptions value can be one or more of the following:

"deterministic":True | False

Default	False

"device":integer

specifies the ID of one GPU device that is to be used.

Alias	devices
Default	0
Minimum value	0
Requirement	The specified values must be unique.

"enable":True | False

when set to True, specifies that a GPU device is to be used.

Alias	useGPU
Default	True

miniBatchSize=integer

specifies the number of observations in one minibatch.

Default	500
Minimum value	2

nominals=["variable-name-1" <, "variable-name-2", ...>]

specifies the list of nominal variables that are included in the input CAS table's variable list.

Alias	nom

numSamples=integer

specifies the number of observations to generate.

Default	1000
Minimum value	1

optimizerAe={"method":"ADAM", method-specific-parameters}

specifies the optimization method to use in training the autoencoder model. Currently only the Adam method is supported.

Alias	optimizationAe

The value that you specify for the method parameter determines the other parameters that apply.

optimizerGan={"method":"ADAM", method-specific-parameters}

specifies the optimization method to use in training the GAN model. Currently only the Adam method is supported.

Alias	optimizationGan

The value that you specify for the method parameter determines the other parameters that apply.

outputTables={outputTables}

lists the names of results tables to save as CAS tables on the server.

For more information about specifying the outputTables parameter, see the common outputTables parameter (Appendix A: Common Parameters).

packSize=integer

specifies the number of samples to group together in applying the discriminator. This number must be a factor of the minibatch size.

Default	10
Minimum value	1

printFreq=integer

specifies the frequency at which to print losses to the log and the iteration history table.

Default	1
Minimum value	1

regDWeight=integer

specifies the weight to use in regularizing the discriminator.

Default	10
Minimum value	0

* saveState={casouttable}

specifies the table in which to save the model state for model scoring.

Long form	saveState={"name":"table-name"}
Shortcut form	saveState="table-name"

The casouttable value can be one or more of the following:

"caslib":"string"

specifies the name of the caslib for the output table.

"label":"string"

specifies the descriptive label to associate with the table.

"lifetime":64-bit-integer

specifies the number of seconds to keep the table in memory after it is last accessed. The table is dropped if it is not accessed for the specified number of seconds.

Default	0
Minimum value	0

"memoryFormat":"DVR" | "INHERIT" | "STANDARD"

specifies the memory format for the output table.

Default	INHERIT

DVR

use the duplicate value reduction memory format. This memory format can reduce the memory consumption and file size when the input data contains duplicate values.

INHERIT

STANDARD

use the standard memory format.

"name":"table-name"

specifies the name for the output table.

"promote":True | False

when set to True, adds the output table with a global scope. This enables other sessions to access the table, subject to access controls. The target caslib must also have a global scope.

Default	False

"replace":True | False

when set to True, overwrites an existing table that has the same name.

Default	False

"tableRedistUpPolicy":"DEFER" | "NOREDIST" | "REBALANCE"

Specifies the Table Redistribution Policy when the number of worker pods increases on a running CAS server.

DEFER

Defer redistribution policy selection to higher-level entity.

NOREDIST

Do not redistribute table data when the number of worker pods changes on a running CAS server.

REBALANCE

Rebalance table data when the number of worker pods changes on a running CAS server.

scoreSeed=64-bit-integer

specifies the seed to use for the random number generator for scoring. A value of 0 means use the time from the computer's clock as the seed.

Default	0
Minimum value	0

seed=64-bit-integer

specifies the seed to use for the random number generator for training. A value of 0 means use the time from the computer's clock as the seed.

Default	0
Minimum value	0

* table={castable}

specifies the input CAS table that contains tabular data.

Long form	table={"name":"table-name"}
Shortcut form	table="table-name"

The castable value can be one or more of the following:

"caslib":"string"

specifies the caslib for the input table that you want to use with the action. By default, the active caslib is used. Specify a value only if you need to access a table from a different caslib.

"computedOnDemand":True | False

when set to True, creates the computed variables when the table is loaded instead of when the action begins.

Alias	compOnDemand
Default	False

"computedVars":[{casinvardesc-1} <, {casinvardesc-2}, ...>]

Alias	compVars

The casinvardesc value can be one or more of the following:

"format":"string"

specifies the format to apply to the variable.

"formattedLength":integer

specifies the length of the format field plus the length of the format precision.

"label":"string"

specifies the descriptive label for the variable.

* "name":"variable-name"

specifies the name for the variable.

"nfd":integer

specifies the length of the format precision.

"nfl":integer

specifies the length of the format field.

"computedVarsProgram":"string"

specifies an expression for each computed variable that you include in the computedVars parameter.

Alias	compPgm

"dataSourceOptions":{"key-1":{any-list-or-data-type-1} <, "key-2":{any-list-or-data-type-2}, ...>}

specifies data source options.

Aliases	options
Aliases	dataSource

"importOptions":{"fileType":"ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters}

specifies the settings for reading a table from a data source.

Alias	import_

For more information about specifying the importOptions parameter, see the common importOptions parameter (Appendix A: Common Parameters).

* "name":"table-name"

specifies the name of the input table.

"orderBy":[{casinvardesc-1} <, {casinvardesc-2}, ...>]

The casinvardesc value can be one or more of the following:

"format":"string"

specifies the format to apply to the variable.

"formattedLength":integer

specifies the length of the format field plus the length of the format precision.

"label":"string"

specifies the descriptive label for the variable.

* "name":"variable-name"

specifies the name for the variable.

"nfd":integer

specifies the length of the format precision.

"nfl":integer

specifies the length of the format field.

"singlePass":True | False

when set to True, does not create a transient table on the server. Setting this parameter to True can be efficient, but the data might not have stable ordering upon repeated runs.

Default	False

"vars":[{casinvardesc-1} <, {casinvardesc-2}, ...>]

specifies the variables to use in the action.

The casinvardesc value can be one or more of the following:

"format":"string"

specifies the format to apply to the variable.

"formattedLength":integer

specifies the length of the format field plus the length of the format precision.

"label":"string"

specifies the descriptive label for the variable.

* "name":"variable-name"

specifies the name for the variable.

"nfd":integer

specifies the length of the format precision.

"nfl":integer

specifies the length of the format field.

"where":"where-expression"

specifies an expression for subsetting the input data.

"whereTable":{groupbytable}

The groupbytable value can be one or more of the following:

"casLib":"string"

specifies the caslib for the filter table. By default, the active caslib is used.

"dataSourceOptions":{adls_noreq-parameters | bigquery-parameters | cas_noreq-parameters | clouddex-parameters | db2-parameters | dnfs-parameters | esp-parameters | fedsvr-parameters | gcs_noreq-parameters | hadoop-parameters | hana-parameters | impala-parameters | informix-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sapiq-parameters | sforce-parameters | singlestore_standard-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | ss_noreq-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters}

specifies data source options.

Aliases	options
Aliases	dataSource

For more information about specifying the dataSourceOptions parameter, see the common dataSourceOptions parameter (Appendix A: Common Parameters).

"importOptions":{"fileType":"ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters}

specifies the settings for reading a table from a data source.

Alias	import_

For more information about specifying the importOptions parameter, see the common importOptions parameter (Appendix A: Common Parameters).

* "name":"table-name"

specifies the name of the filter table.

"vars":[{casinvardesc-1} <, {casinvardesc-2}, ...>]

specifies the variable names to use from the filter table.

The casinvardesc value can be one or more of the following:

"format":"string"

specifies the format to apply to the variable.

"formattedLength":integer

specifies the length of the format field plus the length of the format precision.

"label":"string"

specifies the descriptive label for the variable.

* "name":"variable-name"

specifies the name for the variable.

"nfd":integer

specifies the length of the format precision.

"nfl":integer

specifies the length of the format field.

"where":"where-expression"

specifies an expression for subsetting the data from the filter table.

useLogLevelFreq=True | False

when set to True, uses the log frequency of categorical levels in the conditional sampling.

Default	True

Parameters for method="ADAM"

"beta1":double

specifies the exponential decay rate for the first-moment estimates.

Default	0.9
Range	[0–1)

"beta2":double

specifies the exponential decay rate for the second-moment estimates.

Default	0.999
Range	[0–1)

"learningRate":double

specifies the learning rate for the optimizer.

Default	0.001
Range	(0–1]

"numEpochs":integer

specifies the number of epochs to use in training the model.

Default	150
Minimum value	0

"weightDecay":double

specifies the weight decay for the autoencoder's optimizer.

Default	1E-08
Range	0–1

Parameters for method="ADAM"

"beta1":double

specifies the exponential decay rate for the first-moment estimates.

Default	0.5
Range	[0–1)

"beta2":double

specifies the exponential decay rate for the second-moment estimates.

Default	0.9
Range	[0–1)

"learningRate":double

specifies the learning rate for the optimizer.

Default	2E-05
Range	(0–1]

"numEpochs":integer

specifies the number of epochs to use in training the model.

Default	150
Minimum value	0

"weightDecayD":double

specifies the weight decay for the discriminator's optimizer.

Default	0.0001
Range	0–1

"weightDecayG":double

specifies the weight decay for the generator's optimizer.

Default	1E-06
Range	0–1

tabularGanTrain Action

Trains a tabular GAN model.

R Syntax
Summary: Input and Output Tables
Parameter Descriptions

R Syntax

results <– cas.generativeAdversarialNet.tabularGanTrain(s,

casOut=list(

caslib="string",

compress=TRUE | FALSE,

indexVars=list("variable-name-1" <, "variable-name-2", ...>),

label="string",

lifetime=64-bit-integer,

maxMemSize=64-bit-integer,

memoryFormat="DVR" | "INHERIT" | "STANDARD",

name="table-name",

promote=TRUE | FALSE,

replace=TRUE | FALSE,

replication=integer,

tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE",

threadBlockSize=64-bit-integer,

timeStamp="string",

where=list("string-1" <, "string-2", ...>)

centroidsTable=list(

caslib="string",

computedOnDemand=TRUE | FALSE,

computedVars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

computedVarsProgram="string",

dataSourceOptions=list(key-1=list(any-list-or-data-type-1) <, key-2=list(any-list-or-data-type-2), ...>),

groupBy=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

groupByMode="NOSORT" | "REDISTRIBUTE",

name="table-name",

orderBy=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

singlePass=TRUE | FALSE,

vars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

where="where-expression",

whereTable=list(

casLib="string"

name="table-name"

vars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>)

where="where-expression"

)

checkpointFreq=integer,

checkpointIn=list(

caslib="string",

computedOnDemand=TRUE | FALSE,

computedVars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

computedVarsProgram="string",

dataSourceOptions=list(key-1=list(any-list-or-data-type-1) <, key-2=list(any-list-or-data-type-2), ...>),

groupBy=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

groupByMode="NOSORT" | "REDISTRIBUTE",

name="table-name",

orderBy=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

singlePass=TRUE | FALSE,

vars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

where="where-expression",

whereTable=list(

casLib="string"

name="table-name"

vars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>)

where="where-expression"

)

checkpointOut=list(

caslib="string",

compress=TRUE | FALSE,

indexVars=list("variable-name-1" <, "variable-name-2", ...>),

label="string",

lifetime=64-bit-integer,

maxMemSize=64-bit-integer,

memoryFormat="DVR" | "INHERIT" | "STANDARD",

name="table-name",

promote=TRUE | FALSE,

replace=TRUE | FALSE,

replication=integer,

tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE",

threadBlockSize=64-bit-integer,

timeStamp="string",

where=list("string-1" <, "string-2", ...>)

display=list(

caseSensitive=TRUE | FALSE,

exclude=TRUE | FALSE,

excludeAll=TRUE | FALSE,

keyIsPath=TRUE | FALSE,

names=list("string-1" <, "string-2", ...>),

pathType="LABEL" | "NAME",

traceNames=TRUE | FALSE

embeddingDim=integer,

gmmOptions=list(

alpha=double,

inference=list(

covariance="DIAGONAL" | "FULL"

maxVbIter=integer

threshold=double

maxClusters=integer,

seed=double

gpu=list(

deterministic=TRUE | FALSE,

device=integer,

enable=TRUE | FALSE

miniBatchSize=integer,

nominals=list("variable-name-1" <, "variable-name-2", ...>),

numSamples=integer,

optimizerAe=list(method="ADAM", method-specific-parameters),

optimizerGan=list(method="ADAM", method-specific-parameters),

outputTables=list(

groupByVarsRaw=TRUE | FALSE,

includeAll=TRUE | FALSE,

names=list("string-1" <, "string-2", ...>) | list(key-1=list(casouttable-1) <, key-2=list(casouttable-2), ...>),

repeated=TRUE | FALSE,

replace=TRUE | FALSE

packSize=integer,

printFreq=integer,

regDWeight=integer,

saveState=list(

caslib="string",

label="string",

lifetime=64-bit-integer,

memoryFormat="DVR" | "INHERIT" | "STANDARD",

name="table-name",

promote=TRUE | FALSE,

replace=TRUE | FALSE,

tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE"

scoreSeed=64-bit-integer,

seed=64-bit-integer,

table=list(

caslib="string",

computedOnDemand=TRUE | FALSE,

computedVars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

computedVarsProgram="string",

dataSourceOptions=list(key-1=list(any-list-or-data-type-1) <, key-2=list(any-list-or-data-type-2), ...>),

name="table-name",

orderBy=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

singlePass=TRUE | FALSE,

vars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>),

where="where-expression",

whereTable=list(

casLib="string"

name="table-name"

vars=list( list(

format="string",

formattedLength=integer,

label="string",

name="variable-name",

nfd=integer,

nfl=integer

) <, list(...)>)

where="where-expression"

)

useLogLevelFreq=TRUE | FALSE

)

indicates a required parameter

Summary: Input and Output Tables

If a row includes a subparameter, you can specify the name, caslib, and so on in the subparameter. Otherwise, you can specify the name, caslib, and so on in the parameter.

Parameters for Reading Input Tables
Parameter	Subparameter	Description
centroidsTable	—	specifies the CAS table that contains Gaussian mixture model (GMM) centroid information for continuous variables.
checkpointIn	—	specifies the checkpoint CAS table to be loaded to restore your model. If you omit this parameter, the model is trained from scratch.
required parametertable	—	specifies the input CAS table that contains tabular data.

Parameters for Creating Output Tables
Parameter	Subparameter	Description
required parametercasOut	—	specifies the output CAS table in which to store the generated tabular data from the trained model.
checkpointOut	—	specifies the CAS table in which to save the current model as a checkpoint.
outputTables	names	lists the names of results tables to save as CAS tables on the server.
required parametersaveState	—	specifies the table in which to save the model state for model scoring.

Parameter Descriptions

* casOut=list(casouttable)

specifies the output CAS table in which to store the generated tabular data from the trained model.

For more information about specifying the casOut parameter, see the common casouttable (Form 1) parameter (Appendix A: Common Parameters).

centroidsTable=list(castable)

specifies the CAS table that contains Gaussian mixture model (GMM) centroid information for continuous variables.

For more information about specifying the centroidsTable parameter, see the common castable (Form 1) parameter (Appendix A: Common Parameters).

checkpointFreq=integer

specifies the frequency at which to save a checkpoint during the training.

Default	5000
Minimum value	1

checkpointIn=list(castable)

specifies the checkpoint CAS table to be loaded to restore your model. If you omit this parameter, the model is trained from scratch.

For more information about specifying the checkpointIn parameter, see the common castable (Form 1) parameter (Appendix A: Common Parameters).

checkpointOut=list(casouttable)

specifies the CAS table in which to save the current model as a checkpoint.

For more information about specifying the checkpointOut parameter, see the common casouttable (Form 1) parameter (Appendix A: Common Parameters).

display=list(displayTables)

specifies a list of results tables to send to the client for display.

For more information about specifying the display parameter, see the common displayTables parameter (Appendix A: Common Parameters).

embeddingDim=integer

specifies the dimensions of the input noise to the generator.

Default	128
Minimum value	1

gmmOptions=list(gmmOptions)

specifies the Gaussian mixture model (GMM) parameters to generate the centroid information for continuous variables.

The gmmOptions value can be one or more of the following:

alpha=double

specifies the concentration parameter for the Dirichlet process.

Default	1
Minimum value (exclusive)	0

inference=list(gmmInference)

specifies the GMM inference parameters.

The gmmInference value can be one or more of the following:

covariance="DIAGONAL" | "FULL"

specifies the covariance matrix type of the Gaussian mixtures.

Default	DIAGONAL

maxVbIter=integer

specifies the number of iterations for the variational Bayesian (VB) inference.

Default	100
Minimum value	1

threshold=double

specifies the threshold of the difference between the current and previous likelihoods.

Default	0.01
Minimum value	0

maxClusters=integer

specifies the GMM maximum number of clusters.

Default	100
Minimum value	1

seed=double

specifies a double to use to start the pseudorandom number generator for initialization.

Default	0
Minimum value	0

gpu=list(gpuOptions)

specifies options that are related to graphics processing unit (GPU) devices.

The gpuOptions value can be one or more of the following:

deterministic=TRUE | FALSE

Default	FALSE

device=integer

specifies the ID of one GPU device that is to be used.

Alias	devices
Default	0
Minimum value	0
Requirement	The specified values must be unique.

enable=TRUE | FALSE

when set to True, specifies that a GPU device is to be used.

Alias	useGPU
Default	TRUE

miniBatchSize=integer

specifies the number of observations in one minibatch.

Default	500
Minimum value	2

nominals=list("variable-name-1" <, "variable-name-2", ...>)

specifies the list of nominal variables that are included in the input CAS table's variable list.

Alias	nom

numSamples=integer

specifies the number of observations to generate.

Default	1000
Minimum value	1

optimizerAe=list(method="ADAM", method-specific-parameters)

specifies the optimization method to use in training the autoencoder model. Currently only the Adam method is supported.

Alias	optimizationAe

The value that you specify for the method parameter determines the other parameters that apply.

optimizerGan=list(method="ADAM", method-specific-parameters)

specifies the optimization method to use in training the GAN model. Currently only the Adam method is supported.

Alias	optimizationGan

The value that you specify for the method parameter determines the other parameters that apply.

outputTables=list(outputTables)

lists the names of results tables to save as CAS tables on the server.

For more information about specifying the outputTables parameter, see the common outputTables parameter (Appendix A: Common Parameters).

packSize=integer

specifies the number of samples to group together in applying the discriminator. This number must be a factor of the minibatch size.

Default	10
Minimum value	1

printFreq=integer

specifies the frequency at which to print losses to the log and the iteration history table.

Default	1
Minimum value	1

regDWeight=integer

specifies the weight to use in regularizing the discriminator.

Default	10
Minimum value	0

* saveState=list(casouttable)

specifies the table in which to save the model state for model scoring.

Long form	saveState=list(name="table-name")
Shortcut form	saveState="table-name"

The casouttable value can be one or more of the following:

caslib="string"

specifies the name of the caslib for the output table.

label="string"

specifies the descriptive label to associate with the table.

lifetime=64-bit-integer

specifies the number of seconds to keep the table in memory after it is last accessed. The table is dropped if it is not accessed for the specified number of seconds.

Default	0
Minimum value	0

memoryFormat="DVR" | "INHERIT" | "STANDARD"

specifies the memory format for the output table.

Default	INHERIT

DVR

use the duplicate value reduction memory format. This memory format can reduce the memory consumption and file size when the input data contains duplicate values.

INHERIT

STANDARD

use the standard memory format.

name="table-name"

specifies the name for the output table.

promote=TRUE | FALSE

when set to True, adds the output table with a global scope. This enables other sessions to access the table, subject to access controls. The target caslib must also have a global scope.

Default	FALSE

replace=TRUE | FALSE

when set to True, overwrites an existing table that has the same name.

Default	FALSE

tableRedistUpPolicy="DEFER" | "NOREDIST" | "REBALANCE"

Specifies the Table Redistribution Policy when the number of worker pods increases on a running CAS server.

DEFER

Defer redistribution policy selection to higher-level entity.

NOREDIST

Do not redistribute table data when the number of worker pods changes on a running CAS server.

REBALANCE

Rebalance table data when the number of worker pods changes on a running CAS server.

scoreSeed=64-bit-integer

specifies the seed to use for the random number generator for scoring. A value of 0 means use the time from the computer's clock as the seed.

Default	0
Minimum value	0

seed=64-bit-integer

specifies the seed to use for the random number generator for training. A value of 0 means use the time from the computer's clock as the seed.

Default	0
Minimum value	0

* table=list(castable)

specifies the input CAS table that contains tabular data.

Long form	table=list(name="table-name")
Shortcut form	table="table-name"

The castable value can be one or more of the following:

caslib="string"

specifies the caslib for the input table that you want to use with the action. By default, the active caslib is used. Specify a value only if you need to access a table from a different caslib.

computedOnDemand=TRUE | FALSE

when set to True, creates the computed variables when the table is loaded instead of when the action begins.

Alias	compOnDemand
Default	FALSE

computedVars=list( list(casinvardesc-1) <, list(casinvardesc-2), ...>)

Alias	compVars

The casinvardesc value can be one or more of the following:

format="string"

specifies the format to apply to the variable.

formattedLength=integer

specifies the length of the format field plus the length of the format precision.

label="string"

specifies the descriptive label for the variable.

* name="variable-name"

specifies the name for the variable.

nfd=integer

specifies the length of the format precision.

nfl=integer

specifies the length of the format field.

computedVarsProgram="string"

specifies an expression for each computed variable that you include in the computedVars parameter.

Alias	compPgm

dataSourceOptions=list(key-1=list(any-list-or-data-type-1) <, key-2=list(any-list-or-data-type-2), ...>)

specifies data source options.

Aliases	options
Aliases	dataSource

importOptions=list(fileType="ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters)

specifies the settings for reading a table from a data source.

Alias	import

For more information about specifying the importOptions parameter, see the common importOptions parameter (Appendix A: Common Parameters).

* name="table-name"

specifies the name of the input table.

orderBy=list( list(casinvardesc-1) <, list(casinvardesc-2), ...>)

The casinvardesc value can be one or more of the following:

format="string"

specifies the format to apply to the variable.

formattedLength=integer

specifies the length of the format field plus the length of the format precision.

label="string"

specifies the descriptive label for the variable.

* name="variable-name"

specifies the name for the variable.

nfd=integer

specifies the length of the format precision.

nfl=integer

specifies the length of the format field.

singlePass=TRUE | FALSE

when set to True, does not create a transient table on the server. Setting this parameter to True can be efficient, but the data might not have stable ordering upon repeated runs.

Default	FALSE

vars=list( list(casinvardesc-1) <, list(casinvardesc-2), ...>)

specifies the variables to use in the action.

The casinvardesc value can be one or more of the following:

format="string"

specifies the format to apply to the variable.

formattedLength=integer

specifies the length of the format field plus the length of the format precision.

label="string"

specifies the descriptive label for the variable.

* name="variable-name"

specifies the name for the variable.

nfd=integer

specifies the length of the format precision.

nfl=integer

specifies the length of the format field.

where="where-expression"

specifies an expression for subsetting the input data.

whereTable=list(groupbytable)

The groupbytable value can be one or more of the following:

casLib="string"

specifies the caslib for the filter table. By default, the active caslib is used.

dataSourceOptions=list(adls_noreq-parameters | bigquery-parameters | cas_noreq-parameters | clouddex-parameters | db2-parameters | dnfs-parameters | esp-parameters | fedsvr-parameters | gcs_noreq-parameters | hadoop-parameters | hana-parameters | impala-parameters | informix-parameters | jdbc-parameters | mongodb-parameters | mysql-parameters | odbc-parameters | oracle-parameters | path-parameters | postgres-parameters | redshift-parameters | s3-parameters | sapiq-parameters | sforce-parameters | singlestore_standard-parameters | snowflake-parameters | spark-parameters | spde-parameters | sqlserver-parameters | ss_noreq-parameters | teradata-parameters | vertica-parameters | yellowbrick-parameters)

specifies data source options.

Aliases	options
Aliases	dataSource

For more information about specifying the dataSourceOptions parameter, see the common dataSourceOptions parameter (Appendix A: Common Parameters).

importOptions=list(fileType="ANY" | "AUDIO" | "AUTO" | "BASESAS" | "CSV" | "DOCUMENT" | "DTA" | "ESP" | "EXCEL" | "FMT" | "HDAT" | "IMAGE" | "JMP" | "LASR" | "PARQUET" | "SPSS" | "VIDEO" | "XLS", fileType-specific-parameters)

specifies the settings for reading a table from a data source.

Alias	import

For more information about specifying the importOptions parameter, see the common importOptions parameter (Appendix A: Common Parameters).

* name="table-name"

specifies the name of the filter table.

vars=list( list(casinvardesc-1) <, list(casinvardesc-2), ...>)

specifies the variable names to use from the filter table.

The casinvardesc value can be one or more of the following:

format="string"

specifies the format to apply to the variable.

formattedLength=integer

specifies the length of the format field plus the length of the format precision.

label="string"

specifies the descriptive label for the variable.

* name="variable-name"

specifies the name for the variable.

nfd=integer

specifies the length of the format precision.

nfl=integer

specifies the length of the format field.

where="where-expression"

specifies an expression for subsetting the data from the filter table.

useLogLevelFreq=TRUE | FALSE

when set to True, uses the log frequency of categorical levels in the conditional sampling.

Default	TRUE

Parameters for method="ADAM"

beta1=double

specifies the exponential decay rate for the first-moment estimates.

Default	0.9
Range	[0–1)

beta2=double

specifies the exponential decay rate for the second-moment estimates.

Default	0.999
Range	[0–1)

learningRate=double

specifies the learning rate for the optimizer.

Default	0.001
Range	(0–1]

numEpochs=integer

specifies the number of epochs to use in training the model.

Default	150
Minimum value	0

weightDecay=double

specifies the weight decay for the autoencoder's optimizer.

Default	1E-08
Range	0–1

Parameters for method="ADAM"

beta1=double

specifies the exponential decay rate for the first-moment estimates.

Default	0.5
Range	[0–1)

beta2=double

specifies the exponential decay rate for the second-moment estimates.

Default	0.9
Range	[0–1)

learningRate=double

specifies the learning rate for the optimizer.

Default	2E-05
Range	(0–1]

numEpochs=integer

specifies the number of epochs to use in training the model.

Default	150
Minimum value	0

weightDecayD=double

specifies the weight decay for the discriminator's optimizer.

Default	0.0001
Range	0–1

weightDecayG=double

specifies the weight decay for the generator's optimizer.

Default	1E-06
Range	0–1

Last updated: November 23, 2025