Class

com.salesforce.op

OpWorkflowModelReader

Related Doc: package op

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class OpWorkflowModelReader extends AnyRef

Reads OpWorkflowModelWriter serialized OpWorkflowModel objects by path and JValue. This will only work if the features were serialized in topological order. NOTE: The FeatureGeneratorStages will not be recovered into the Model object, because they are part of each feature.

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Instance Constructors

  1. new OpWorkflowModelReader(workflowOpt: Option[OpWorkflow], asSpark: Boolean = true)

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    workflowOpt

    optional workflow that produced the trained model

    asSpark

    if true will load as spark models if false will load as Mleap stages for spark wrapped stages

Value Members

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

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  2. final def ##(): Int

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

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  4. final def asInstanceOf[T0]: T0

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  5. val asSpark: Boolean

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    if true will load as spark models if false will load as Mleap stages for spark wrapped stages

  6. def clone(): AnyRef

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

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  8. def equals(arg0: Any): Boolean

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  9. def finalize(): Unit

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

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  11. def hashCode(): Int

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  12. final def isInstanceOf[T0]: Boolean

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  13. final def load(path: String, modelStagingDir: String = WorkflowFileReader.modelStagingDir): OpWorkflowModel

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    Load a previously trained workflow model from path

    Load a previously trained workflow model from path

    path

    to the trained workflow model

    modelStagingDir

    local folder to copy and unpack stored model to for loading

    returns

    workflow model

  14. def loadJson(json: JValue, path: String): Try[OpWorkflowModel]

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    Load Workflow instance from json

    Load Workflow instance from json

    json

    json value

    path

    to the trained workflow model

    returns

    workflow model instance

  15. def loadJson(json: String, path: String): Try[OpWorkflowModel]

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    Load a previously trained workflow model from json

    Load a previously trained workflow model from json

    json

    json of the trained workflow model

    path

    to the trained workflow model

    returns

    workflow model

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

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  17. final def notify(): Unit

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  18. final def notifyAll(): Unit

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

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  20. def toString(): String

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  21. final def wait(): Unit

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

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

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  24. val workflowOpt: Option[OpWorkflow]

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    optional workflow that produced the trained model

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