Deep Learning Action Set: Syntax

deepLearn.buildModel <result=results> <status=rc> /

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", ...>}

nThreads=integer,

;

indicates a required parameter

Summary: 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 Creating Output Tables
Parameter	Subparameter	Description
required parametermodelTable	—	specifies the name of an in-memory table that is used to store the model.

Parameter Descriptions

* modelTable={casouttable}

specifies the name of an in-memory table that is used to store the model.

For more information about specifying the modelTable parameter, see the common casouttable parameter.

Alias	model

nThreads=integer

Minimum value	0

type="CNN" | "DNN" | "RNN"

specifies the model type.

Default	DNN

CNN

creates an empty model for building a convolutional neural network.

DNN

creates an empty model for building a deep, fully connected neural network.

RNN

creates an empty model for building a recurrent neural network.

buildModel Action

Creates an empty Deep Learning model.

See:	About the buildModel Action
Example:	Build a Deep Learning Model

Lua Syntax

results, info = s:deepLearn_buildModel{

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", ...>}

nThreads=integer,

}

indicates a required parameter

Summary: 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 Creating Output Tables
Parameter	Subparameter	Description
required parametermodelTable	—	specifies the name of an in-memory table that is used to store the model.

Parameter Descriptions

* modelTable={casouttable}

specifies the name of an in-memory table that is used to store the model.

For more information about specifying the modelTable parameter, see the common casouttable parameter.

Alias	model

nThreads=integer

Minimum value	0

type="CNN" | "DNN" | "RNN"

specifies the model type.

Default	DNN

CNN

creates an empty model for building a convolutional neural network.

DNN

creates an empty model for building a deep, fully connected neural network.

RNN

creates an empty model for building a recurrent neural network.

buildModel Action

Creates an empty Deep Learning model.

See:	About the buildModel Action
Example:	Build a Deep Learning Model

Python Syntax

results=s.deepLearn.buildModel(

"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", ...>]

nThreads=integer,

)

indicates a required parameter

Summary: 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 Creating Output Tables
Parameter	Subparameter	Description
required parametermodelTable	—	specifies the name of an in-memory table that is used to store the model.

Parameter Descriptions

* modelTable={casouttable}

specifies the name of an in-memory table that is used to store the model.

For more information about specifying the modelTable parameter, see the common casouttable parameter.

Alias	model

nThreads=integer

Minimum value	0

type="CNN" | "DNN" | "RNN"

specifies the model type.

Default	DNN

CNN

creates an empty model for building a convolutional neural network.

DNN

creates an empty model for building a deep, fully connected neural network.

RNN

creates an empty model for building a recurrent neural network.

buildModel Action

Creates an empty Deep Learning model.

See:	About the buildModel Action
Example:	Build a Deep Learning Model

R Syntax

results <– cas.deepLearn.buildModel(s,

=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", ...>)

nThreads=integer,