org.apache.spark.ml

DLModel

class DLModel[T] extends DLTransformerBase[DLModel[T]] with DLParams with HasBatchSize

DLModel helps embed a BigDL model into a Spark Transformer, thus Spark users can conveniently merge BigDL into Spark ML pipeline. DLModel supports feature data in the format of Array[Double], Array[Float], org.apache.spark.mllib.linalg.{Vector, VectorUDT} for Spark 1.5, 1.6 and org.apache.spark.ml.linalg.{Vector, VectorUDT} for Spark 2.0+. Internally DLModel use features column as storage of the feature data, and create Tensors according to the constructor parameter featureSize.

DLModel is compatible with both spark 1.5-plus and 2.0 by extending ML Transformer.

Linear Supertypes
HasBatchSize, DLTransformerBase[DLModel[T]], DLParams, HasPredictionCol, HasFeaturesCol, Model[DLModel[T]], Transformer, PipelineStage, Logging, Params, Serializable, Serializable, Identifiable, AnyRef, Any
Known Subclasses
DLClassifierModel
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Inherited
  1. DLModel
  2. HasBatchSize
  3. DLTransformerBase
  4. DLParams
  5. HasPredictionCol
  6. HasFeaturesCol
  7. Model
  8. Transformer
  9. PipelineStage
  10. Logging
  11. Params
  12. Serializable
  13. Serializable
  14. Identifiable
  15. AnyRef
  16. Any
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  1. Public
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Instance Constructors

  1. new DLModel(model: Module[T], featureSize: Array[Int], uid: String = "DLModel")(implicit arg0: ClassTag[T], ev: TensorNumeric[T])

    model

    trainned BigDL models to use in prediction.

    featureSize

    The size (Tensor dimensions) of the feature data. (e.g. an image may be with featureSize = 28 * 28).

Value Members

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

    Definition Classes
    AnyRef

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

    Definition Classes
    Any

  3. final def ##(): Int

    Definition Classes
    AnyRef → Any

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

    Attributes
    protected
    Definition Classes
    Params

  5. final def ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  6. final def ==(arg0: Any): Boolean

    Definition Classes
    Any

  7. final def asInstanceOf[T0]: T0

    Definition Classes
    Any

  8. def batchOutputToPrediction(output: Tensor[T]): Iterable[_]

    Attributes
    protected

  9. final val batchSize: Param[Int]

    Definition Classes
    HasBatchSize

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

    Attributes
    protected
    Definition Classes
    Params

  11. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  12. def copy(extra: ParamMap): DLModel[T]

    Definition Classes
    DLModel → DLTransformerBase → Model → Transformer → PipelineStage → Params

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

    Attributes
    protected
    Definition Classes
    Params

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

    Attributes
    protected
    Definition Classes
    Params

  15. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  16. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any

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

    Definition Classes
    Params

  18. def explainParams(): String

    Definition Classes
    Params

  19. final def extractParamMap(): ParamMap

    Definition Classes
    Params

  20. final def extractParamMap(extra: ParamMap): ParamMap

    Definition Classes
    Params

  21. var featureSize: Array[Int]

    The size (Tensor dimensions) of the feature data.

    The size (Tensor dimensions) of the feature data. (e.g. an image may be with featureSize = 28 * 28).

  22. final val featuresCol: Param[String]

    Definition Classes
    HasFeaturesCol

  23. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )

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

    Definition Classes
    Params

  25. final def getBatchSize: Int

    Definition Classes
    HasBatchSize

  26. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any

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

    Definition Classes
    Params

  28. def getFeatureArrayCol: String

    Attributes
    protected
    Definition Classes
    DLParams

  29. def getFeatureSize: Array[Int]

  30. final def getFeaturesCol: String

    Definition Classes
    HasFeaturesCol

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

    Definition Classes
    Params

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

    Definition Classes
    Params

  33. final def getPredictionCol: String

    Definition Classes
    HasPredictionCol

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

    Definition Classes
    Params

  35. def hasParam(paramName: String): Boolean

    Definition Classes
    Params

  36. def hasParent: Boolean

    Definition Classes
    Model

  37. def hashCode(): Int

    Definition Classes
    AnyRef → Any

  38. def internalTransform(featureData: RDD[Seq[AnyVal]], dataset: DataFrame): DataFrame

    Perform a prediction on featureCol, and write result to the predictionCol.

    Perform a prediction on featureCol, and write result to the predictionCol.

    featureData

    featureData in the format of Seq

    returns

    output DataFrame

    Attributes
    protected
    Definition Classes
    DLModel → DLTransformerBase

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

    Definition Classes
    Params

  40. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any

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

    Definition Classes
    Params

  42. def isTraceEnabled(): Boolean

    Attributes
    protected
    Definition Classes
    Logging

  43. def log: Logger

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  45. def logDebug(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  47. def logError(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  49. def logInfo(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

  50. def logName: String

    Attributes
    protected
    Definition Classes
    Logging

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

    Attributes
    protected
    Definition Classes
    Logging

  52. def logTrace(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

  53. def logWarning(msg: ⇒ String, throwable: Throwable): Unit

    Attributes
    protected
    Definition Classes
    Logging

  54. def logWarning(msg: ⇒ String): Unit

    Attributes
    protected
    Definition Classes
    Logging

  55. val model: Module[T]

    trainned BigDL models to use in prediction.

  56. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef

  57. final def notify(): Unit

    Definition Classes
    AnyRef

  58. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  59. lazy val params: Array[Param[_]]

    Definition Classes
    Params

  60. var parent: Estimator[DLModel[T]]

    Definition Classes
    Model

  61. final val predictionCol: Param[String]

    Definition Classes
    HasPredictionCol

  62. final def set(paramPair: ParamPair[_]): DLModel.this.type

    Attributes
    protected
    Definition Classes
    Params

  63. final def set(param: String, value: Any): DLModel.this.type

    Attributes
    protected
    Definition Classes
    Params

  64. final def set[T](param: Param[T], value: T): DLModel.this.type

    Attributes
    protected
    Definition Classes
    Params

  65. def setBatchSize(value: Int): DLModel.this.type

  66. final def setDefault(paramPairs: ParamPair[_]*): DLModel.this.type

    Attributes
    protected
    Definition Classes
    Params

  67. final def setDefault[T](param: Param[T], value: T): DLModel.this.type

    Attributes
    protected
    Definition Classes
    Params

  68. def setFeatureSize(value: Array[Int]): DLModel.this.type

  69. def setFeaturesCol(featuresColName: String): DLModel.this.type

  70. def setParent(parent: Estimator[DLModel[T]]): DLModel[T]

    Definition Classes
    Model

  71. def setPredictionCol(value: String): DLModel.this.type

  72. def supportedTypesToSeq(row: Row, colType: DataType, index: Int): Seq[AnyVal]

    Definition Classes
    DLParams

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

    Definition Classes
    AnyRef

  74. def toArrayType(dataset: DataFrame): RDD[Seq[AnyVal]]

    Attributes
    protected
    Definition Classes
    DLTransformerBase

  75. def toString(): String

    Definition Classes
    Identifiable → AnyRef → Any

  76. def transform(dataset: DataFrame): DataFrame

    Definition Classes
    DLTransformerBase → Transformer

  77. def transform(dataset: DataFrame, paramMap: ParamMap): DataFrame

    Definition Classes
    Transformer

  78. def transform(dataset: DataFrame, firstParamPair: ParamPair[_], otherParamPairs: ParamPair[_]*): DataFrame

    Definition Classes
    Transformer
    Annotations
    @varargs()

  79. def transformSchema(schema: StructType): StructType

    Definition Classes
    DLModel → PipelineStage

  80. def transformSchema(schema: StructType, logging: Boolean): StructType

    Attributes
    protected
    Definition Classes
    PipelineStage
    Annotations
    @DeveloperApi()

  81. val uid: String

    Definition Classes
    DLModel → Identifiable

  82. def validateParams(): Unit

    Definition Classes
    Params

  83. def validateSchema(schema: StructType): Unit

    Attributes
    protected
    Definition Classes
    DLParams

  84. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  85. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

  86. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from HasBatchSize

Inherited from DLTransformerBase[DLModel[T]]

Inherited from DLParams

Inherited from HasPredictionCol

Inherited from HasFeaturesCol

Inherited from Model[DLModel[T]]

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