Class/Object

com.johnsnowlabs.nlp.annotators

Tokenizer

Related Docs: object Tokenizer | package annotators

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class Tokenizer extends AnnotatorModel[Tokenizer]

Tokenizes raw text into word pieces, tokens.

Linear Supertypes
AnnotatorModel[Tokenizer], TransformModelSchema, HasOutputAnnotationCol, HasInputAnnotationCols, HasAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[Tokenizer], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. Tokenizer
  2. AnnotatorModel
  3. TransformModelSchema
  4. HasOutputAnnotationCol
  5. HasInputAnnotationCols
  6. HasAnnotatorType
  7. ParamsAndFeaturesWritable
  8. HasFeatures
  9. DefaultParamsWritable
  10. MLWritable
  11. Model
  12. Transformer
  13. PipelineStage
  14. Logging
  15. Params
  16. Serializable
  17. Serializable
  18. Identifiable
  19. AnyRef
  20. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new Tokenizer()

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  2. new Tokenizer(uid: String)

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    uid

    required uid for storing annotator to disk

Type Members

  1. type AnnotatorType = String

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    Definition Classes
    HasAnnotatorType

Value Members

  1. final def !=(arg0: Any): Boolean

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

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

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    Attributes
    protected
    Definition Classes
    Params
  4. def $$[T](feature: StructFeature[T]): T

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    Attributes
    protected
    Definition Classes
    HasFeatures
  5. def $$[K, V](feature: MapFeature[K, V]): Map[K, V]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  6. def $$[T](feature: ArrayFeature[T]): Array[T]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  7. final def ==(arg0: Any): Boolean

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    Definition Classes
    AnyRef → Any
  8. def addInfixPattern(value: String): Tokenizer.this.type

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  9. def annotate(annotations: Seq[Annotation]): Seq[Annotation]

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    one to many annotation

    one to many annotation

    annotations

    Annotations that correspond to inputAnnotationCols generated by previous annotators if any

    returns

    any number of annotations processed for every input annotation. Not necessary one to one relationship

    Definition Classes
    TokenizerAnnotatorModel
  10. val annotatorType: AnnotatorType

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    Definition Classes
    TokenizerHasAnnotatorType
  11. final def asInstanceOf[T0]: T0

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    Definition Classes
    Any
  12. final def clear(param: Param[_]): Tokenizer.this.type

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    Definition Classes
    Params
  13. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  14. val compositeTokens: StringArrayParam

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  15. def copy(extra: ParamMap): Tokenizer

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    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    AnnotatorModel → Model → Transformer → PipelineStage → Params
  16. def copyValues[T <: Params](to: T, extra: ParamMap): T

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

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    Attributes
    protected
    Definition Classes
    Params
  18. final def eq(arg0: AnyRef): Boolean

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

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

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    Definition Classes
    Params
  21. def explainParams(): String

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    Definition Classes
    Params
  22. final def extractParamMap(): ParamMap

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

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    Definition Classes
    Params
  24. val features: ArrayBuffer[Feature[_, _, _]]

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    Definition Classes
    HasFeatures
  25. def finalize(): Unit

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  26. def get[T](feature: StructFeature[T]): Option[T]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  27. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  28. def get[T](feature: ArrayFeature[T]): Option[Array[T]]

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    Attributes
    protected
    Definition Classes
    HasFeatures
  29. final def get[T](param: Param[T]): Option[T]

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

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    Definition Classes
    AnyRef → Any
  31. def getCompositeTokens: Array[String]

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

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    Definition Classes
    Params
  33. def getInfixPatterns: Array[String]

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  34. final def getInputCols: Array[String]

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    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  35. final def getOrDefault[T](param: Param[T]): T

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    Definition Classes
    Params
  36. final def getOutputCol: String

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    Gets annotation column name going to generate

    Gets annotation column name going to generate

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

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    Definition Classes
    Params
  38. def getPrefixPattern: String

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  39. def getSuffixPattern: String

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  40. def getTargetPattern: String

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

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

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    Definition Classes
    Params
  43. def hasParent: Boolean

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    Definition Classes
    Model
  44. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  45. val infixPatterns: StringArrayParam

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  46. def initializeLogIfNecessary(isInterpreter: Boolean): Unit

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    Attributes
    protected
    Definition Classes
    Logging
  47. final val inputCols: StringArrayParam

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    columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified

    columns that contain annotations necessary to run this annotator AnnotatorType is used both as input and output columns if not specified

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

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    Definition Classes
    Params
  49. final def isInstanceOf[T0]: Boolean

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

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    Definition Classes
    Params
  51. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  52. def log: Logger

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

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  59. def logName: String

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  64. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
    AnyRef
  65. final def notify(): Unit

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    Definition Classes
    AnyRef
  66. final def notifyAll(): Unit

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    Definition Classes
    AnyRef
  67. def onWrite(path: String, spark: SparkSession): Unit

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    Definition Classes
    ParamsAndFeaturesWritable
  68. final val outputCol: Param[String]

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    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  69. lazy val params: Array[Param[_]]

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    Definition Classes
    Params
  70. var parent: Estimator[Tokenizer]

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    Definition Classes
    Model
  71. val prefixPattern: Param[String]

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  72. val requiredAnnotatorTypes: Array[AnnotatorType]

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    A Tokenizer could require only for now a SentenceDetector annotator

    A Tokenizer could require only for now a SentenceDetector annotator

    Definition Classes
    TokenizerHasInputAnnotationCols
  73. def save(path: String): Unit

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    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  74. def set[T](feature: StructFeature[T], value: T): Tokenizer.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  75. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): Tokenizer.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  76. def set[T](feature: ArrayFeature[T], value: Array[T]): Tokenizer.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  77. final def set(paramPair: ParamPair[_]): Tokenizer.this.type

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

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

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    Definition Classes
    Params
  80. def setCompositeTokens(value: Array[String]): Tokenizer.this.type

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  81. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): Tokenizer.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  82. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): Tokenizer.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  83. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): Tokenizer.this.type

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    Attributes
    protected
    Definition Classes
    HasFeatures
  84. final def setDefault(paramPairs: ParamPair[_]*): Tokenizer.this.type

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

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    Attributes
    protected
    Definition Classes
    Params
  86. def setInfixPatterns(value: Array[String]): Tokenizer.this.type

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  87. final def setInputCols(value: String*): Tokenizer.this.type

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

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    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  89. final def setOutputCol(value: String): Tokenizer.this.type

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    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  90. def setParent(parent: Estimator[Tokenizer]): Tokenizer

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    Definition Classes
    Model
  91. def setPrefixPattern(value: String): Tokenizer.this.type

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  92. def setSuffixPattern(value: String): Tokenizer.this.type

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  93. def setTargetPattern(value: String): Tokenizer.this.type

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  94. val suffixPattern: Param[String]

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  95. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  96. def tag(sentences: Seq[Sentence]): Seq[TokenizedSentence]

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  97. val targetPattern: Param[String]

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  98. def toString(): String

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    Definition Classes
    Identifiable → AnyRef → Any
  99. final def transform(dataset: Dataset[_]): DataFrame

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    Given requirements are met, this applies ML transformation within a Pipeline or stand-alone Output annotation will be generated as a new column, previous annotations are still available separately metadata is built at schema level to record annotations structural information outside its content

    Given requirements are met, this applies ML transformation within a Pipeline or stand-alone Output annotation will be generated as a new column, previous annotations are still available separately metadata is built at schema level to record annotations structural information outside its content

    dataset

    Dataset[Row]

    Definition Classes
    AnnotatorModel → Transformer
  100. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  101. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

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    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  102. final def transformSchema(schema: StructType): StructType

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    requirement for pipeline transformation validation.

    requirement for pipeline transformation validation. It is called on fit()

    Definition Classes
    TransformModelSchema
  103. def transformSchema(schema: StructType, logging: Boolean): StructType

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

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    required uid for storing annotator to disk

    required uid for storing annotator to disk

    Definition Classes
    Tokenizer → Identifiable
  105. def validate(schema: StructType): Boolean

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    takes a Dataset and checks to see if all the required annotation types are present.

    takes a Dataset and checks to see if all the required annotation types are present.

    schema

    to be validated

    returns

    True if all the required types are present, else false

    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  106. final def wait(): Unit

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

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

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

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    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable

Inherited from AnnotatorModel[Tokenizer]

Inherited from TransformModelSchema

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[Tokenizer]

Inherited from Transformer

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Ungrouped