Class/Object

com.johnsnowlabs.nlp.embeddings

WordEmbeddings

Related Docs: object WordEmbeddings | package embeddings

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class WordEmbeddings extends AnnotatorApproach[WordEmbeddingsModel] with HasStorage with HasEmbeddingsProperties

Word Embeddings lookup annotator that maps tokens to vectors.

For instantiated/pretrained models, see WordEmbeddingsModel.

A custom token lookup dictionary for embeddings can be set with setStoragePath. Each line of the provided file needs to have a token, followed by their vector representation, delimited by a spaces.

...
are 0.39658191506190343 0.630968081620067 0.5393722253731201 0.8428180123359783
were 0.7535235923631415 0.9699218875629833 0.10397182122983872 0.11833962569383116
stress 0.0492683418305907 0.9415954572751959 0.47624463167525755 0.16790967216778263
induced 0.1535748762292387 0.33498936903209897 0.9235178224122094 0.1158772920395934
...

If a token is not found in the dictionary, then the result will be a zero vector of the same dimension. Statistics about the rate of converted tokens, can be retrieved with WordEmbeddingsModel.withCoverageColumn and WordEmbeddingsModel.overallCoverage.

For extended examples of usage, see the Spark NLP Workshop and the WordEmbeddingsTestSpec.

Example

In this example, the file random_embeddings_dim4.txt has the form of the content above.

import spark.implicits._
import com.johnsnowlabs.nlp.base.DocumentAssembler
import com.johnsnowlabs.nlp.annotators.Tokenizer
import com.johnsnowlabs.nlp.embeddings.WordEmbeddings
import com.johnsnowlabs.nlp.util.io.ReadAs
import com.johnsnowlabs.nlp.EmbeddingsFinisher
import org.apache.spark.ml.Pipeline

val documentAssembler = new DocumentAssembler()
  .setInputCol("text")
  .setOutputCol("document")

val tokenizer = new Tokenizer()
  .setInputCols(Array("document"))
  .setOutputCol("token")

val embeddings = new WordEmbeddings()
  .setStoragePath("src/test/resources/random_embeddings_dim4.txt", ReadAs.TEXT)
  .setStorageRef("glove_4d")
  .setDimension(4)
  .setInputCols("document", "token")
  .setOutputCol("embeddings")

val embeddingsFinisher = new EmbeddingsFinisher()
  .setInputCols("embeddings")
  .setOutputCols("finished_embeddings")
  .setOutputAsVector(true)
  .setCleanAnnotations(false)

val pipeline = new Pipeline()
  .setStages(Array(
    documentAssembler,
    tokenizer,
    embeddings,
    embeddingsFinisher
  ))

val data = Seq("The patient was diagnosed with diabetes.").toDF("text")
val result = pipeline.fit(data).transform(data)

result.selectExpr("explode(finished_embeddings) as result").show(false)
+----------------------------------------------------------------------------------+
|result                                                                            |
+----------------------------------------------------------------------------------+
|[0.9439099431037903,0.4707513153553009,0.806300163269043,0.16176554560661316]     |
|[0.7966810464859009,0.5551124811172485,0.8861005902290344,0.28284206986427307]    |
|[0.025029370561242104,0.35177749395370483,0.052506182342767715,0.1887107789516449]|
|[0.08617766946554184,0.8399239182472229,0.5395117998123169,0.7864698767662048]    |
|[0.6599600911140442,0.16109347343444824,0.6041093468666077,0.8913561105728149]    |
|[0.5955275893211365,0.01899011991918087,0.4397728443145752,0.8911281824111938]    |
|[0.9840458631515503,0.7599489092826843,0.9417727589607239,0.8624503016471863]     |
+----------------------------------------------------------------------------------+
See also

Annotators Main Page for a list of transformer based embeddings

SentenceEmbeddings to combine embeddings into a sentence-level representation

Linear Supertypes
Ordering
  1. Grouped
  2. Alphabetic
  3. By Inheritance
Inherited
  1. WordEmbeddings
  2. HasEmbeddingsProperties
  3. HasStorage
  4. HasCaseSensitiveProperties
  5. HasExcludableStorage
  6. HasStorageRef
  7. ParamsAndFeaturesWritable
  8. HasFeatures
  9. AnnotatorApproach
  10. CanBeLazy
  11. DefaultParamsWritable
  12. MLWritable
  13. HasOutputAnnotatorType
  14. HasOutputAnnotationCol
  15. HasInputAnnotationCols
  16. Estimator
  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 WordEmbeddings()

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    Annotator reference id.

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

  2. new WordEmbeddings(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
    HasOutputAnnotatorType

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: SetFeature[T]): Set[T]

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

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

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

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

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    Definition Classes
    Any
  11. def beforeTraining(spark: SparkSession): Unit

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    Definition Classes
    AnnotatorApproach
  12. val caseSensitive: BooleanParam

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    Whether to ignore case in index lookups (Default depends on model)

    Whether to ignore case in index lookups (Default depends on model)

    Definition Classes
    HasCaseSensitiveProperties
  13. final def checkSchema(schema: StructType, inputAnnotatorType: String): Boolean

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    Attributes
    protected
    Definition Classes
    HasInputAnnotationCols
  14. final def clear(param: Param[_]): WordEmbeddings.this.type

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    Definition Classes
    Params
  15. def clone(): AnyRef

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    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  16. final def copy(extra: ParamMap): Estimator[WordEmbeddingsModel]

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

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    Attributes
    protected
    Definition Classes
    Params
  18. def createDatabaseConnection(database: Name): RocksDBConnection

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    Definition Classes
    HasStorageRef
  19. def createWriter(database: Name, connection: RocksDBConnection): StorageWriter[_]

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    Attributes
    protected
    Definition Classes
    WordEmbeddingsHasStorage
  20. val databases: Array[Name]

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    Definition Classes
    WordEmbeddingsHasStorage
  21. final def defaultCopy[T <: Params](extra: ParamMap): T

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    Attributes
    protected
    Definition Classes
    Params
  22. val description: String

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    Word Embeddings lookup annotator that maps tokens to vectors

    Word Embeddings lookup annotator that maps tokens to vectors

    Definition Classes
    WordEmbeddingsAnnotatorApproach
  23. val dimension: IntParam

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    Number of embedding dimensions (Default depends on model)

    Number of embedding dimensions (Default depends on model)

    Definition Classes
    HasEmbeddingsProperties
  24. final def eq(arg0: AnyRef): Boolean

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

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

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    Definition Classes
    Params
  27. def explainParams(): String

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

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

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

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    Definition Classes
    HasFeatures
  31. def finalize(): Unit

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

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

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

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

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    Definition Classes
    Estimator
    Annotations
    @Since( "2.0.0" ) @varargs()
  36. def get[T](feature: StructFeature[T]): Option[T]

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

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    Attributes
    protected
    Definition Classes
    HasFeatures
  38. def get[T](feature: SetFeature[T]): Option[Set[T]]

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

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

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    Definition Classes
    Params
  41. def getCaseSensitive: Boolean

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    Definition Classes
    HasCaseSensitiveProperties
  42. final def getClass(): Class[_]

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    Definition Classes
    AnyRef → Any
  43. final def getDefault[T](param: Param[T]): Option[T]

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    Definition Classes
    Params
  44. def getDimension: Int

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    Definition Classes
    HasEmbeddingsProperties
  45. def getIncludeStorage: Boolean

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    Definition Classes
    HasExcludableStorage
  46. def getInputCols: Array[String]

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    returns

    input annotations columns currently used

    Definition Classes
    HasInputAnnotationCols
  47. def getLazyAnnotator: Boolean

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    Definition Classes
    CanBeLazy
  48. final def getOrDefault[T](param: Param[T]): T

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

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    Definition Classes
    Params
  51. def getStoragePath: Option[ExternalResource]

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    Definition Classes
    HasStorage
  52. def getStorageRef: String

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    Definition Classes
    HasStorageRef
  53. final def hasDefault[T](param: Param[T]): Boolean

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

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    Definition Classes
    Params
  55. def hashCode(): Int

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    Definition Classes
    AnyRef → Any
  56. val includeStorage: BooleanParam

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    Definition Classes
    HasExcludableStorage
  57. def index(fitDataset: Dataset[_], storageSourcePath: Option[String], readAs: Option[util.io.ReadAs.Value], writers: Map[Name, StorageWriter[_]], readOptions: Option[Map[String, String]]): Unit

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    Attributes
    protected
    Definition Classes
    WordEmbeddingsHasStorage
  58. def indexStorage(fitDataset: Dataset[_], resource: Option[ExternalResource]): Unit

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    Definition Classes
    HasStorage
  59. def initializeLogIfNecessary(isInterpreter: Boolean, silent: Boolean): Boolean

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

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

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    Input annotation type : DOCUMENT, TOKEN

    Input annotation type : DOCUMENT, TOKEN

    Definition Classes
    WordEmbeddingsHasInputAnnotationCols
  62. 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
  63. final def isDefined(param: Param[_]): Boolean

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

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

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    Definition Classes
    Params
  66. def isTraceEnabled(): Boolean

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    Attributes
    protected
    Definition Classes
    Logging
  67. val lazyAnnotator: BooleanParam

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    Definition Classes
    CanBeLazy
  68. def log: Logger

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

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

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  75. def logName: String

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

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

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

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

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    Attributes
    protected
    Definition Classes
    Logging
  80. val missingRefMsg: String

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    Error message

    Error message

    Attributes
    protected
    Definition Classes
    WordEmbeddingsHasStorage
  81. def msgHelper(schema: StructType): String

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

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

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

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    Definition Classes
    AnyRef
  85. def onTrained(model: WordEmbeddingsModel, spark: SparkSession): Unit

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    Definition Classes
    AnnotatorApproach
  86. def onWrite(path: String, spark: SparkSession): Unit

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    Attributes
    protected
    Definition Classes
    ParamsAndFeaturesWritable
  87. val optionalInputAnnotatorTypes: Array[String]

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    Definition Classes
    HasInputAnnotationCols
  88. val outputAnnotatorType: AnnotatorType

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    Output annotation type : WORD_EMBEDDINGS

    Output annotation type : WORD_EMBEDDINGS

    Definition Classes
    WordEmbeddingsHasOutputAnnotatorType
  89. final val outputCol: Param[String]

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

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    Definition Classes
    Params
  91. val readCacheSize: IntParam

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    Cache size for items retrieved from storage.

    Cache size for items retrieved from storage. Increase for performance but higher memory consumption

  92. def save(path: String): Unit

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

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

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    Attributes
    protected
    Definition Classes
    HasFeatures
  95. def set[T](feature: SetFeature[T], value: Set[T]): WordEmbeddings.this.type

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

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

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

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

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    Definition Classes
    Params
  100. def setCaseSensitive(value: Boolean): WordEmbeddings.this.type

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    Definition Classes
    HasCaseSensitiveProperties
  101. def setDefault[T](feature: StructFeature[T], value: () ⇒ T): WordEmbeddings.this.type

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

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    Attributes
    protected
    Definition Classes
    HasFeatures
  103. def setDefault[T](feature: SetFeature[T], value: () ⇒ Set[T]): WordEmbeddings.this.type

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

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

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

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    Attributes
    protected
    Definition Classes
    Params
  107. def setDimension(value: Int): WordEmbeddings.this.type

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    Definition Classes
    HasEmbeddingsProperties
  108. def setIncludeStorage(value: Boolean): WordEmbeddings.this.type

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    Definition Classes
    HasExcludableStorage
  109. final def setInputCols(value: String*): WordEmbeddings.this.type

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    Definition Classes
    HasInputAnnotationCols
  110. final def setInputCols(value: Array[String]): WordEmbeddings.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
  111. def setLazyAnnotator(value: Boolean): WordEmbeddings.this.type

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    Definition Classes
    CanBeLazy
  112. final def setOutputCol(value: String): WordEmbeddings.this.type

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    Overrides annotation column name when transforming

    Overrides annotation column name when transforming

    Definition Classes
    HasOutputAnnotationCol
  113. def setReadCacheSize(value: Int): WordEmbeddings.this.type

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    Cache size for items retrieved from storage.

    Cache size for items retrieved from storage. Increase for performance but higher memory consumption.

  114. def setStoragePath(path: String, readAs: util.io.ReadAs.Value): WordEmbeddings.this.type

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    Definition Classes
    HasStorage
  115. def setStoragePath(path: String, readAs: String): WordEmbeddings.this.type

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    Definition Classes
    HasStorage
  116. def setStorageRef(value: String): WordEmbeddings.this.type

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    Definition Classes
    HasStorageRef
  117. def setWriteBufferSize(value: Int): WordEmbeddings.this.type

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    Buffer size limit before dumping to disk storage while writing.

  118. val storagePath: ExternalResourceParam

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    Definition Classes
    HasStorage
  119. val storageRef: Param[String]

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    Unique identifier for storage (Default: this.uid)

    Unique identifier for storage (Default: this.uid)

    Definition Classes
    HasStorageRef
  120. final def synchronized[T0](arg0: ⇒ T0): T0

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    Definition Classes
    AnyRef
  121. def toString(): String

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

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    Definition Classes
    WordEmbeddingsAnnotatorApproach
  123. 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
    AnnotatorApproach → PipelineStage
  124. def transformSchema(schema: StructType, logging: Boolean): StructType

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

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    required uid for storing annotator to disk

    required uid for storing annotator to disk

    Definition Classes
    WordEmbeddings → Identifiable
  126. 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
    AnnotatorApproach
  127. def validateStorageRef(dataset: Dataset[_], inputCols: Array[String], annotatorType: String): Unit

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    Definition Classes
    HasStorageRef
  128. final def wait(): Unit

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

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

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    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  131. def wrapEmbeddingsMetadata(col: Column, embeddingsDim: Int, embeddingsRef: Option[String] = None): Column

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    Attributes
    protected
    Definition Classes
    HasEmbeddingsProperties
  132. def wrapSentenceEmbeddingsMetadata(col: Column, embeddingsDim: Int, embeddingsRef: Option[String] = None): Column

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    Attributes
    protected
    Definition Classes
    HasEmbeddingsProperties
  133. def write: MLWriter

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    Definition Classes
    ParamsAndFeaturesWritable → DefaultParamsWritable → MLWritable
  134. val writeBufferSize: IntParam

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    Buffer size limit before dumping to disk storage while writing

Inherited from HasEmbeddingsProperties

Inherited from HasStorage

Inherited from HasExcludableStorage

Inherited from HasStorageRef

Inherited from ParamsAndFeaturesWritable

Inherited from HasFeatures

Inherited from CanBeLazy

Inherited from DefaultParamsWritable

Inherited from MLWritable

Inherited from HasOutputAnnotatorType

Inherited from HasOutputAnnotationCol

Inherited from HasInputAnnotationCols

Inherited from Estimator[WordEmbeddingsModel]

Inherited from PipelineStage

Inherited from Logging

Inherited from Params

Inherited from Serializable

Inherited from Serializable

Inherited from Identifiable

Inherited from AnyRef

Inherited from Any

Parameters

A list of (hyper-)parameter keys this annotator can take. Users can set and get the parameter values through setters and getters, respectively.

Annotator types

Required input and expected output annotator types

Members

Parameter setters

Parameter getters