Packages

class MarianTransformer extends AnnotatorModel[MarianTransformer] with HasSimpleAnnotate[MarianTransformer] with WriteTensorflowModel with WriteSentencePieceModel

MarianTransformer: Fast Neural Machine Translation

MarianTransformer uses models trained by MarianNMT.

Marian is an efficient, free Neural Machine Translation framework written in pure C++ with minimal dependencies. It is mainly being developed by the Microsoft Translator team. Many academic (most notably the University of Edinburgh and in the past the Adam Mickiewicz University in Poznań) and commercial contributors help with its development.

It is currently the engine behind the Microsoft Translator Neural Machine Translation services and being deployed by many companies, organizations and research projects (see below for an incomplete list).

Sources : MarianNMT https://marian-nmt.github.io/ Marian: Fast Neural Machine Translation in C++ https://www.aclweb.org/anthology/P18-4020/

Note : Note that this is a very computationally expensive module especially on larger sequence. The use of an accelerator such as GPU is recommended.

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

Instance Constructors

  1. new MarianTransformer()

    Annotator reference id.

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

  2. new MarianTransformer(uid: String)

    uid

    required internal uid for saving annotator

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

    ConfigProto from tensorflow, serialized into byte array.

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

  18. def copy(extra: ParamMap): MarianTransformer

    requirement for annotators copies

    requirement for annotators copies

    Definition Classes
    RawAnnotator → Model → Transformer → PipelineStage → Params
  19. def copyValues[T <: Params](to: T, extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  20. final def defaultCopy[T <: Params](extra: ParamMap): T
    Attributes
    protected
    Definition Classes
    Params
  21. 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
  22. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  23. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  24. def explainParam(param: Param[_]): String
    Definition Classes
    Params
  25. def explainParams(): String
    Definition Classes
    Params
  26. def extraValidate(structType: StructType): Boolean
    Attributes
    protected
    Definition Classes
    RawAnnotator
  27. def extraValidateMsg: String

    Override for additional custom schema checks

    Override for additional custom schema checks

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

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

    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  41. def getLangId: String

  42. def getLazyAnnotator: Boolean
    Definition Classes
    CanBeLazy
  43. def getMaxInputLength: Int

  44. def getMaxOutputLength: Int

  45. def getModelIfNotSet: TensorflowMarian

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

    Gets annotation column name going to generate

    Gets annotation column name going to generate

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

    Input Annotator Type : TOKEN DOCUMENT

    Input Annotator Type : TOKEN DOCUMENT

    Definition Classes
    MarianTransformerHasInputAnnotationCols
  56. 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
  57. final def isDefined(param: Param[_]): Boolean
    Definition Classes
    Params
  58. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  59. final def isSet(param: Param[_]): Boolean
    Definition Classes
    Params
  60. def isTraceEnabled(): Boolean
    Attributes
    protected
    Definition Classes
    Logging
  61. var langId: Param[String]

    A string representing the target language in the form of >>id<< (id = valid target language ID)

    A string representing the target language in the form of >>id<< (id = valid target language ID)

    langId is only needed if the model generates multi-lingual target language texts. For instance, for a 'en-fr' model this param is not required to be set.

  62. val lazyAnnotator: BooleanParam
    Definition Classes
    CanBeLazy
  63. def log: Logger
    Attributes
    protected
    Definition Classes
    Logging
  64. def logDebug(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  65. def logDebug(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  66. def logError(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  67. def logError(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  68. def logInfo(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  69. def logInfo(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  70. def logName: String
    Attributes
    protected
    Definition Classes
    Logging
  71. def logTrace(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  72. def logTrace(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  73. def logWarning(msg: ⇒ String, throwable: Throwable): Unit
    Attributes
    protected
    Definition Classes
    Logging
  74. def logWarning(msg: ⇒ String): Unit
    Attributes
    protected
    Definition Classes
    Logging
  75. val maxInputLength: IntParam

    Controls the maximum length for encoder inputs (source language texts) Default: 40

  76. val maxOutputLength: IntParam

    Controls the maximum length for decoder outputs (target language texts) Default: 40

  77. def msgHelper(schema: StructType): String
    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  78. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  79. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  80. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  81. def onWrite(path: String, spark: SparkSession): Unit
  82. val outputAnnotatorType: AnnotatorType

    Output Annotator Type : DOCUMENT

    Output Annotator Type : DOCUMENT

    Definition Classes
    MarianTransformerHasOutputAnnotatorType
  83. final val outputCol: Param[String]
    Attributes
    protected
    Definition Classes
    HasOutputAnnotationCol
  84. lazy val params: Array[Param[_]]
    Definition Classes
    Params
  85. var parent: Estimator[MarianTransformer]
    Definition Classes
    Model
  86. def save(path: String): Unit
    Definition Classes
    MLWritable
    Annotations
    @Since( "1.6.0" ) @throws( ... )
  87. def set[T](feature: StructFeature[T], value: T): MarianTransformer.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  88. def set[K, V](feature: MapFeature[K, V], value: Map[K, V]): MarianTransformer.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  89. def set[T](feature: SetFeature[T], value: Set[T]): MarianTransformer.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  90. def set[T](feature: ArrayFeature[T], value: Array[T]): MarianTransformer.this.type
    Attributes
    protected
    Definition Classes
    HasFeatures
  91. final def set(paramPair: ParamPair[_]): MarianTransformer.this.type
    Attributes
    protected
    Definition Classes
    Params
  92. final def set(param: String, value: Any): MarianTransformer.this.type
    Attributes
    protected
    Definition Classes
    Params
  93. final def set[T](param: Param[T], value: T): MarianTransformer.this.type
    Definition Classes
    Params
  94. def setConfigProtoBytes(bytes: Array[Int]): MarianTransformer.this.type

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

    Overrides required annotators column if different than default

    Overrides required annotators column if different than default

    Definition Classes
    HasInputAnnotationCols
  103. def setLangId(lang: String): MarianTransformer.this.type

  104. def setLazyAnnotator(value: Boolean): MarianTransformer.this.type
    Definition Classes
    CanBeLazy
  105. def setMaxInputLength(value: Int): MarianTransformer.this.type

  106. def setMaxOutputLength(value: Int): MarianTransformer.this.type

  107. def setModelIfNotSet(spark: SparkSession, tensorflow: TensorflowWrapper, sppSrc: SentencePieceWrapper, sppTrg: SentencePieceWrapper): MarianTransformer.this.type

  108. final def setOutputCol(value: String): MarianTransformer.this.type

    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  109. def setParent(parent: Estimator[MarianTransformer]): MarianTransformer
    Definition Classes
    Model
  110. def setVocabulary(value: Array[String]): MarianTransformer.this.type

  111. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  112. def toString(): String
    Definition Classes
    Identifiable → AnyRef → Any
  113. 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
  114. def transform(dataset: Dataset[_], paramMap: ParamMap): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" )
  115. def transform(dataset: Dataset[_], firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame
    Definition Classes
    Transformer
    Annotations
    @Since( "2.0.0" ) @varargs()
  116. 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
  117. def transformSchema(schema: StructType, logging: Boolean): StructType
    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()
  118. val uid: String
    Definition Classes
    MarianTransformer → Identifiable
  119. 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
  120. val vocabulary: StringArrayParam

    Vocabulary used to encode and decode piece tokens generated by SentencePiece This will be set once the model is created and cannot be changed afterwards

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

Inherited from WriteSentencePieceModel

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[MarianTransformer]

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

*

getParam *

getSaram *

setGaram *

setParam *

Parameters

Annotator types

Required input and expected output annotator types

Members

Parameter setters