Packages

class LanguageDetectorDL extends AnnotatorModel[LanguageDetectorDL] with HasSimpleAnnotate[LanguageDetectorDL] with WriteTensorflowModel

Language Identification and Detection by using CNNs and RNNs architectures in TensowrFlow LanguageDetectorDL is an annotator that detects the language of documents or sentences depending on the inputCols

The models are trained on large datasets such as Wikipedia and Tatoeba The output is a language code in Wiki Code style: https://en.wikipedia.org/wiki/List_of_Wikipedias

Linear Supertypes
WriteTensorflowModel, HasSimpleAnnotate[LanguageDetectorDL], AnnotatorModel[LanguageDetectorDL], CanBeLazy, RawAnnotator[LanguageDetectorDL], HasOutputAnnotationCol, HasInputAnnotationCols, HasOutputAnnotatorType, ParamsAndFeaturesWritable, HasFeatures, DefaultParamsWritable, MLWritable, Model[LanguageDetectorDL], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
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Inherited
  1. LanguageDetectorDL
  2. WriteTensorflowModel
  3. HasSimpleAnnotate
  4. AnnotatorModel
  5. CanBeLazy
  6. RawAnnotator
  7. HasOutputAnnotationCol
  8. HasInputAnnotationCols
  9. HasOutputAnnotatorType
  10. ParamsAndFeaturesWritable
  11. HasFeatures
  12. DefaultParamsWritable
  13. MLWritable
  14. Model
  15. Transformer
  16. PipelineStage
  17. Logging
  18. Params
  19. Serializable
  20. Serializable
  21. Identifiable
  22. AnyRef
  23. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new LanguageDetectorDL()
  2. new LanguageDetectorDL(uid: String)

Type Members

  1. type AnnotationContent = Seq[Row]

    internal types to show Rows as a relevant StructType Should be deleted once Spark releases UserDefinedTypes to @developerAPI

    internal types to show Rows as a relevant StructType Should be deleted once Spark releases UserDefinedTypes to @developerAPI

    Attributes
    protected
    Definition Classes
    AnnotatorModel
  2. type AnnotatorType = String
    Definition Classes
    HasOutputAnnotatorType

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def $[T](param: Param[T]): T
    Attributes
    protected
    Definition Classes
    Params
  4. def $$[T](feature: StructFeature[T]): T
    Attributes
    protected
    Definition Classes
    HasFeatures
  5. def $$[K, V](feature: MapFeature[K, V]): Map[K, V]
    Attributes
    protected
    Definition Classes
    HasFeatures
  6. def $$[T](feature: SetFeature[T]): Set[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  7. def $$[T](feature: ArrayFeature[T]): Array[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  8. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  9. def _transform(dataset: Dataset[_], recursivePipeline: Option[PipelineModel]): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  10. def afterAnnotate(dataset: DataFrame): DataFrame
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  11. val alphabet: MapFeature[String, Int]

    alphabet

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

    takes a document and annotations and produces new annotations of this annotator's annotation type

    takes a document and annotations and produces new annotations of this annotator's annotation type

    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
    LanguageDetectorDLHasSimpleAnnotate
  13. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  14. def beforeAnnotate(dataset: Dataset[_]): Dataset[_]
    Attributes
    protected
    Definition Classes
    AnnotatorModel
  15. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  16. final def clear(param: Param[_]): LanguageDetectorDL.this.type
    Definition Classes
    Params
  17. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  18. val coalesceSentences: BooleanParam

    coalesceSentences

  19. val configProtoBytes: IntArrayParam

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString()

  20. def copy(extra: ParamMap): LanguageDetectorDL

    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  21. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  22. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  23. def dfAnnotate: UserDefinedFunction

    Wraps annotate to happen inside SparkSQL user defined functions in order to act with org.apache.spark.sql.Column

    Wraps annotate to happen inside SparkSQL user defined functions in order to act with org.apache.spark.sql.Column

    returns

    udf function to be applied to inputCols using this annotator's annotate function as part of ML transformation

    Definition Classes
    HasSimpleAnnotate
  24. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  25. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  26. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  27. def explainParams(): String
    Definition Classes
    Params
  28. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  29. def extraValidateMsg: String

    Override for additional custom schema checks

    Override for additional custom schema checks

    Attributes
    protected
    Definition Classes
    RawAnnotator
  30. final def extractParamMap(): ParamMap
    Definition Classes
    Params
  31. final def extractParamMap(extra: ParamMap): ParamMap
    Definition Classes
    Params
  32. val features: ArrayBuffer[Feature[_, _, _]]
    Definition Classes
    HasFeatures
  33. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  34. def get[T](feature: StructFeature[T]): Option[T]
    Attributes
    protected
    Definition Classes
    HasFeatures
  35. def get[K, V](feature: MapFeature[K, V]): Option[Map[K, V]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  36. def get[T](feature: SetFeature[T]): Option[Set[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  37. def get[T](feature: ArrayFeature[T]): Option[Array[T]]
    Attributes
    protected
    Definition Classes
    HasFeatures
  38. final def get[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  39. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  40. def getCoalesceSentences: Boolean

  41. def getConfigProtoBytes: Option[Array[Byte]]

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString()

  42. final def getDefault[T](param: Param[T]): Option[T]
    Definition Classes
    Params
  43. def getInputCols: Array[String]

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  44. def getLanguage: Array[String]

    languages

  45. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  46. def getModelIfNotSet: TensorflowLD

  47. final def getOrDefault[T](param: Param[T]): T
    Definition Classes
    Params
  48. final def getOutputCol: String

    Gets annotation column name going to generate

    Gets annotation column name going to generate

    Definition Classes
    HasOutputAnnotationCol
  49. def getParam(paramName: String): Param[Any]
    Definition Classes
    Params
  50. def getThreshold: Float

    threshold

  51. def getThresholdLabel: String

  52. final def hasDefault[T](param: Param[T]): Boolean
    Definition Classes
    Params
  53. def hasParam(paramName: String): Boolean
    Definition Classes
    Params
  54. def hasParent: Boolean
    Definition Classes
    Model
  55. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  56. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  57. def initializeLogIfNecessary(isInterpreter: Boolean): Unit
    Attributes
    protected
    Definition Classes
    Logging
  58. val inputAnnotatorTypes: Array[String]

    Annotator reference id.

    Annotator reference id. Used to identify elements in metadata or to refer to this annotator type

    Definition Classes
    LanguageDetectorDLHasInputAnnotationCols
  59. final val inputCols: StringArrayParam

    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
  60. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  61. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  62. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  63. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  64. val language: MapFeature[String, Int]

    language

  65. val languages: StringArrayParam
  66. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  67. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  68. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  69. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  71. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  75. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  76. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  77. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  78. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  79. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  80. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  81. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  82. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  83. def onWrite(path: String, spark: SparkSession): Unit
  84. val outputAnnotatorType: AnnotatorType
  85. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  86. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  87. var parent: Estimator[LanguageDetectorDL]
    Definition Classes
    Model
  88. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  89. def set[T](feature: StructFeature[T], value: T): LanguageDetectorDL.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  90. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): LanguageDetectorDL.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  91. def set[T](feature: SetFeature[T], value: Set[T]): LanguageDetectorDL.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  92. def set[T](feature: ArrayFeature[T], value: Array[T]): LanguageDetectorDL.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  93. final def set(paramPair: ParamPair[_]): LanguageDetectorDL.this.type
    Attributes
    protected
    Definition Classes
    Params
  94. final def set(param: String, value: Any): LanguageDetectorDL.this.type
    Attributes
    protected
    Definition Classes
    Params
  95. final def set[T](param: Param[T], value: T): LanguageDetectorDL.this.type
    Definition Classes
    Params
  96. def setAlphabet(value: Map[String, Int]): LanguageDetectorDL.this.type

    alphabet used to feed the TensorFlow model for prediction

  97. def setCoalesceSentences(value: Boolean): LanguageDetectorDL.this.type

    If sets to true the output of all sentences will be averaged to one output instead of one output per sentence.

    If sets to true the output of all sentences will be averaged to one output instead of one output per sentence. Default to true.

  98. def setConfigProtoBytes(bytes: Array[Int]): LanguageDetectorDL.this.type

    ConfigProto from tensorflow, serialized into byte array.

    ConfigProto from tensorflow, serialized into byte array. Get with config_proto.SerializeToString()

  99. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): LanguageDetectorDL.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  100. def setDefault[K, V](feature: MapFeature[K, V], value: () ⇒ Map[K, V]): LanguageDetectorDL.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  101. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): LanguageDetectorDL.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  102. def setDefault[T](feature: ArrayFeature[T], value: () ⇒ Array[T]): LanguageDetectorDL.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  103. final def setDefault(paramPairs: ParamPair[_]*): LanguageDetectorDL.this.type
    Attributes
    protected
    Definition Classes
    Params
  104. final def setDefault[T](param: Param[T], value: T): LanguageDetectorDL.this.type
    Attributes
    protected
    Definition Classes
    Params
  105. final def setInputCols(value: String*): LanguageDetectorDL.this.type
    Definition Classes
    HasInputAnnotationCols
  106. final def setInputCols(value: Array[String]): LanguageDetectorDL.this.type

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  107. def setLanguage(value: Map[String, Int]): LanguageDetectorDL.this.type

    language used to map prediction to ISO 639-1 language codes

  108. def setLazyAnnotator(value: Boolean): LanguageDetectorDL.this.type
    Definition Classes
    CanBeLazy
  109. def setModelIfNotSet(spark: SparkSession, tensorflow: TensorflowWrapper): LanguageDetectorDL.this.type

  110. final def setOutputCol(value: String): LanguageDetectorDL.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  111. def setParent(parent: Estimator[LanguageDetectorDL]): LanguageDetectorDL
    Definition Classes
    Model
  112. def setThreshold(threshold: Float): LanguageDetectorDL.this.type

    The minimum threshold for the final result otheriwse it will be either Unknown or the value set in thresholdLabel.

    The minimum threshold for the final result otheriwse it will be either Unknown or the value set in thresholdLabel.

    Value is between 0.0 to 1.0 Try to set this lower if your text is hard to predict

  113. def setThresholdLabel(label: String): LanguageDetectorDL.this.type

    In case the score of prediction is less than threshold, what should be the label.

    In case the score of prediction is less than threshold, what should be the label. Default is Unknown.

  114. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  115. val threshold: FloatParam

    threshold

  116. val thresholdLabel: Param[String]

    thresholdLabel

  117. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  118. final def transform(dataset: Dataset[_]): DataFrame

    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
  119. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  120. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  121. final def transformSchema(schema: StructType): StructType

    requirement for pipeline transformation validation.

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

    Definition Classes
    RawAnnotator → PipelineStage
  122. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  123. val uid: String
    Definition Classes
    LanguageDetectorDL → Identifiable
  124. def validate(schema: StructType): Boolean

    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
    RawAnnotator
  125. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  126. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  127. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  128. def wrapColumnMetadata(col: Column): Column
    Attributes
    protected
    Definition Classes
    RawAnnotator
  129. def write: MLWriter
    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
  130. def writeTensorflowHub(path: String, tfPath: String, spark: SparkSession, suffix: String = "_use"): Unit
    Definition Classes
    WriteTensorflowModel
  131. def writeTensorflowModel(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]] = None): Unit
    Definition Classes
    WriteTensorflowModel
  132. def writeTensorflowModelV2(path: String, spark: SparkSession, tensorflow: TensorflowWrapper, suffix: String, filename: String, configProtoBytes: Option[Array[Byte]] = None): Unit
    Definition Classes
    WriteTensorflowModel

Inherited from WriteTensorflowModel

Inherited from CanBeLazy

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from HasOutputAnnotatorType

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from Model[LanguageDetectorDL]

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

thresholdLabel

Parameters

Members

Parameter setters

Parameter getters