AssertionDLApproach

Instance Constructors

new AssertionDLApproach()
new AssertionDLApproach(uid: String)

uid
a unique identifier for the instanced AssertionDLApproach

Type Members

type AnnotatorType = String

Definition Classes
HasOutputAnnotatorType

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def $[T](param: Param[T]): T

Attributes
protected
Definition Classes
Params
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def _fit(dataset: Dataset[_], recursiveStages: Option[PipelineModel]): AssertionDLModel

Attributes
protected
Definition Classes
AnnotatorApproach
final def asInstanceOf[T0]: T0

Definition Classes
Any
val batchSize: IntParam
def beforeTraining(spark: SparkSession): Unit

Definition Classes
AnnotatorApproach
final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean

Attributes
protected
Definition Classes
HasInputAnnotationCols
val chunkCol: Param[String]
final def clear(param: Param[_]): AssertionDLApproach.this.type

Definition Classes
Params
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
val configProtoBytes: IntArrayParam
final def copy(extra: ParamMap): Estimator[AssertionDLModel]

Definition Classes
AnnotatorApproach → Estimator → PipelineStage → Params
def copyValues[T <: Params](to: T, extra: ParamMap): T

Attributes
protected
Definition Classes
Params
final def defaultCopy[T <: Params](extra: ParamMap): T

Attributes
protected
Definition Classes
Params
val description: String

Definition Classes
AssertionDLApproach → AnnotatorApproach
val dropout: FloatParam
val enableOutputLogs: BooleanParam
val endCol: Param[String]
val epochs: IntParam
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def explainParam(param: Param[_]): String

Definition Classes
Params
def explainParams(): String

Definition Classes
Params
final def extractParamMap(): ParamMap

Definition Classes
Params
final def extractParamMap(extra: ParamMap): ParamMap

Definition Classes
Params
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def fit(dataset: Dataset[_]): AssertionDLModel

Definition Classes
AnnotatorApproach → Estimator
def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[AssertionDLModel]

Definition Classes
Estimator
Annotations
@Since( "2.0.0" )
def fit(dataset: Dataset[_], paramMap: ParamMap): AssertionDLModel

Definition Classes
Estimator
Annotations
@Since( "2.0.0" )
def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): AssertionDLModel

Definition Classes
Estimator
Annotations
@Since( "2.0.0" ) @varargs()
final def get[T](param: Param[T]): Option[T]

Definition Classes
Params
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
def getConfigProtoBytes: Option[Array[Byte]]
final def getDefault[T](param: Param[T]): Option[T]

Definition Classes
Params
def getEnableOutputLogs: Boolean
def getIncludeConfidence: Boolean

whether to include confidence scores in annotation metadata
def getInputCols: Array[String]

Definition Classes
HasInputAnnotationCols
def getLazyAnnotator: Boolean

Definition Classes
CanBeLazy
def getLogName: String

Definition Classes
Logging
final def getOrDefault[T](param: Param[T]): T

Definition Classes
Params
final def getOutputCol: String

Definition Classes
HasOutputAnnotationCol
def getOutputLogsPath: String
def getParam(paramName: String): Param[Any]

Definition Classes
Params
val graphFolder: Param[String]
final def hasDefault[T](param: Param[T]): Boolean

Definition Classes
Params
def hasParam(paramName: String): Boolean

Definition Classes
Params
def hashCode(): Int

Definition Classes
AnyRef → Any
val includeConfidence: BooleanParam
def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

Attributes
protected
Definition Classes
Logging
def initializeLogIfNecessary(isInterpreter: Boolean): Unit

Attributes
protected
Definition Classes
Logging
val inputAnnotatorTypes: Array[String]

Definition Classes
AssertionDLApproach → HasInputAnnotationCols
final val inputCols: StringArrayParam

Attributes
protected
Definition Classes
HasInputAnnotationCols
final def isDefined(param: Param[_]): Boolean

Definition Classes
Params
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
final def isSet(param: Param[_]): Boolean

Definition Classes
Params
def isTraceEnabled(): Boolean

Attributes
protected
Definition Classes
Logging
val labelCol: Param[String]
val lazyAnnotator: BooleanParam

Definition Classes
CanBeLazy
val learningRate: FloatParam
def log(value: ⇒ String, minLevel: Level): Unit

Attributes
protected
Definition Classes
Logging
def log: Logger

Attributes
protected
Definition Classes
Logging
def logDebug(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logDebug(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logError(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logError(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logInfo(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logInfo(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logName: String

Attributes
protected
Definition Classes
Logging
def logTrace(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logTrace(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
def logWarning(msg: ⇒ String, throwable: Throwable): Unit

Attributes
protected
Definition Classes
Logging
def logWarning(msg: ⇒ String): Unit

Attributes
protected
Definition Classes
Logging
val logger: Logger

Attributes
protected
Definition Classes
Logging
val maxSentLen: IntParam
def msgHelper(schema: StructType): String

Attributes
protected
Definition Classes
HasInputAnnotationCols
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
def onTrained(model: AssertionDLModel, spark: SparkSession): Unit

Definition Classes
AnnotatorApproach
val outputAnnotatorType: AnnotatorType

Definition Classes
AssertionDLApproach → HasOutputAnnotatorType
final val outputCol: Param[String]

Attributes
protected
Definition Classes
HasOutputAnnotationCol
def outputLog(value: ⇒ String, uuid: String, shouldLog: Boolean, outputLogsPath: String): Unit

Attributes
protected
Definition Classes
Logging
val outputLogsPath: Param[String]
lazy val params: Array[Param[_]]

Definition Classes
Params
def save(path: String): Unit

Definition Classes
MLWritable
Annotations
@Since( "1.6.0" ) @throws( ... )
final def set(paramPair: ParamPair[_]): AssertionDLApproach.this.type

Attributes
protected
Definition Classes
Params
final def set(param: String, value: Any): AssertionDLApproach.this.type

Attributes
protected
Definition Classes
Params
final def set[T](param: Param[T], value: T): AssertionDLApproach.this.type

Definition Classes
Params
def setBatchSize(size: Int): AssertionDLApproach.this.type
def setChunkCol(c: String): AssertionDLApproach.this.type
def setConfigProtoBytes(bytes: Array[Int]): AssertionDLApproach
final def setDefault(paramPairs: ParamPair[_]*): AssertionDLApproach.this.type

Attributes
protected
Definition Classes
Params
final def setDefault[T](param: Param[T], value: T): AssertionDLApproach.this.type

Attributes
protected
Definition Classes
Params
def setDropout(factor: Float): AssertionDLApproach.this.type
def setEnableOutputLogs(v: Boolean): AssertionDLApproach.this.type

Whether to output to annotators log folder
def setEndCol(e: String): AssertionDLApproach.this.type
def setEpochs(number: Int): AssertionDLApproach.this.type
def setGraphFolder(path: String): AssertionDLApproach
def setIncludeConfidence(value: Boolean): AssertionDLApproach.this.type

Whether to include confidence scores in annotation metadata
final def setInputCols(value: String*): AssertionDLApproach.this.type

Definition Classes
HasInputAnnotationCols
final def setInputCols(value: Array[String]): AssertionDLApproach.this.type

Definition Classes
HasInputAnnotationCols
def setLabelCol(label: String): AssertionDLApproach.this.type
def setLazyAnnotator(value: Boolean): AssertionDLApproach.this.type

Definition Classes
CanBeLazy
def setLearningRate(rate: Float): AssertionDLApproach.this.type
def setMaxSentLen(len: Int): AssertionDLApproach.this.type
final def setOutputCol(value: String): AssertionDLApproach.this.type

Definition Classes
HasOutputAnnotationCol
def setOutputLogsPath(v: String): AssertionDLApproach.this.type
def setStartCol(s: String): AssertionDLApproach.this.type
def setValidationSplit(validationSplit: Float): AssertionDLApproach.this.type
def setVerbose(verbose: Level): AssertionDLApproach
val startCol: Param[String]
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
val testDataset: ExternalResourceParam

val testDataset = new ExternalResourceParam(this, "testDataset", "Path to test dataset.
val testDataset = new ExternalResourceParam(this, "testDataset", "Path to test dataset. If set used to calculate statistic on it during training.")
def toString(): String

Definition Classes
Identifiable → AnyRef → Any
def train(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): AssertionDLModel

This is a main point of interest of this class.
This is a main point of interest of this class. It trains the dataset with recursive pipeline and uses methods trainWithChunk() and trainwithStartEnd() The choice of training happens based on the startCol value of the DL Approach
dataset
a collection of inputs to train
recursivePipeline
an instance of PipelineModel
returns
an instance of trained AssertionDLModel

Definition Classes
AssertionDLApproach → AnnotatorApproach
final def transformSchema(schema: StructType): StructType

Definition Classes
AnnotatorApproach → PipelineStage
def transformSchema(schema: StructType, logging: Boolean): StructType

Attributes
protected
Definition Classes
PipelineStage
Annotations
@DeveloperApi()
val uid: String

a unique identifier for the instanced AssertionDLApproach
a unique identifier for the instanced AssertionDLApproach

Definition Classes
AssertionDLApproach → Identifiable
def validate(schema: StructType): Boolean

Attributes
protected
Definition Classes
AnnotatorApproach
val validationSplit: FloatParam

Choose the proportion of training dataset to be validated against the model on each Epoch.
Choose the proportion of training dataset to be validated against the model on each Epoch. The value should be between 0.0 and 1.0 and by default it is 0.0 and off.
val verbose: IntParam
val verboseLevel: Level

Definition Classes
AssertionDLApproach → Logging
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
def write: MLWriter

Definition Classes
DefaultParamsWritable → MLWritable

Related Docs: object AssertionDLApproach | package dl

class AssertionDLApproach extends AnnotatorApproach[AssertionDLModel] with Logging with Licensed

Instance Constructors

new AssertionDLApproach()

new AssertionDLApproach(uid: String)

Type Members

type AnnotatorType = String

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def $[T](param: Param[T]): T

final def ==(arg0: Any): Boolean

def _fit(dataset: Dataset[_], recursiveStages: Option[PipelineModel]): AssertionDLModel

final def asInstanceOf[T0]: T0

val batchSize: IntParam

def beforeTraining(spark: SparkSession): Unit

final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean

val chunkCol: Param[String]

final def clear(param: Param[_]): AssertionDLApproach.this.type

def clone(): AnyRef

val configProtoBytes: IntArrayParam

final def copy(extra: ParamMap): Estimator[AssertionDLModel]

def copyValues[T <: Params](to: T, extra: ParamMap): T

final def defaultCopy[T <: Params](extra: ParamMap): T

val description: String

val dropout: FloatParam

val enableOutputLogs: BooleanParam

val endCol: Param[String]

val epochs: IntParam

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def explainParam(param: Param[_]): String

def explainParams(): String

final def extractParamMap(): ParamMap

final def extractParamMap(extra: ParamMap): ParamMap

def finalize(): Unit

final def fit(dataset: Dataset[_]): AssertionDLModel

def fit(dataset: Dataset[_], paramMaps: Array[ParamMap]): Seq[AssertionDLModel]

def fit(dataset: Dataset[_], paramMap: ParamMap): AssertionDLModel

def fit(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): AssertionDLModel

final def get[T](param: Param[T]): Option[T]

final def getClass(): Class[_]

def getConfigProtoBytes: Option[Array[Byte]]

final def getDefault[T](param: Param[T]): Option[T]

def getEnableOutputLogs: Boolean

def getIncludeConfidence: Boolean

def getInputCols: Array[String]

def getLazyAnnotator: Boolean

def getLogName: String

final def getOrDefault[T](param: Param[T]): T

final def getOutputCol: String

def getOutputLogsPath: String

def getParam(paramName: String): Param[Any]

val graphFolder: Param[String]

final def hasDefault[T](param: Param[T]): Boolean

def hasParam(paramName: String): Boolean

def hashCode(): Int

val includeConfidence: BooleanParam

def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

def initializeLogIfNecessary(isInterpreter: Boolean): Unit

val inputAnnotatorTypes: Array[String]

final val inputCols: StringArrayParam

final def isDefined(param: Param[_]): Boolean

final def isInstanceOf[T0]: Boolean

final def isSet(param: Param[_]): Boolean

def isTraceEnabled(): Boolean

val labelCol: Param[String]

val lazyAnnotator: BooleanParam

val learningRate: FloatParam

def log(value: ⇒ String, minLevel: Level): Unit

def log: Logger

def logDebug(msg: ⇒ String, throwable: Throwable): Unit

def logDebug(msg: ⇒ String): Unit

def logError(msg: ⇒ String, throwable: Throwable): Unit

def logError(msg: ⇒ String): Unit

def logInfo(msg: ⇒ String, throwable: Throwable): Unit

def logInfo(msg: ⇒ String): Unit

def logName: String

def logTrace(msg: ⇒ String, throwable: Throwable): Unit