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com.johnsnowlabs.nlp

ParamsAndFeaturesFallbackReadable

trait ParamsAndFeaturesFallbackReadable[T <: HasFeatures] extends ParamsAndFeaturesReadable[T]

Enables loading models with params and features with a fallback mechanism. The fallbackLoad function will be called in case there is an exception during Spark loading (i.e. missing parameters or features).

Usually, you might want to call loadSavedModel in the fallbackLoad method to load a model with default params.

T

The type of the model that extends HasFeatures

Linear Supertypes
ParamsAndFeaturesReadable[T], DefaultParamsReadable[T], MLReadable[T], AnyRef, Any
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Inherited
  1. ParamsAndFeaturesFallbackReadable
  2. ParamsAndFeaturesReadable
  3. DefaultParamsReadable
  4. MLReadable
  5. AnyRef
  6. Any
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Visibility
  1. Public
  2. All

Abstract Value Members

  1. abstract def fallbackLoad(folder: String, spark: SparkSession): T

    Fallback loader for when the main reader fails to load the model (e.g., missing params/features).

    Fallback loader for when the main reader fails to load the model (e.g., missing params/features).

    For example, we could use loadSavedModel to load a model with default parameters and features (if the model in the folder supports it).

    folder

    the folder where the model is stored

    spark

    the Spark session

    returns

    an instance of the model with default parameters and features loaded

Concrete Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. def addReader(reader: (T, String, SparkSession) ⇒ Unit): Unit
    Definition Classes
    ParamsAndFeaturesReadable
  5. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  6. def clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()
  7. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  8. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  9. def finalize(): Unit
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  10. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  11. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native()
  12. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  13. def load(path: String): T
    Definition Classes
    MLReadable
    Annotations
    @Since( "1.6.0" )
  14. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  15. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  16. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native()
  17. def onRead(instance: T, path: String, session: SparkSession): Unit
    Attributes
    protected
    Definition Classes
    ParamsAndFeaturesReadable
  18. def read: MLReader[T]
    Definition Classes
    ParamsAndFeaturesFallbackReadableParamsAndFeaturesReadable → DefaultParamsReadable → MLReadable
  19. val readers: ArrayBuffer[(T, String, SparkSession) ⇒ Unit]
    Attributes
    protected
    Definition Classes
    ParamsAndFeaturesReadable
  20. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  21. def toString(): String
    Definition Classes
    AnyRef → Any
  22. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  23. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  24. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... ) @native()

Inherited from ParamsAndFeaturesReadable[T]

Inherited from DefaultParamsReadable[T]

Inherited from MLReadable[T]

Inherited from AnyRef

Inherited from Any

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