com.intel.analytics.bigdl.optim

DistriOptimizer

class DistriOptimizer[T] extends Optimizer[T, MiniBatch[T]]

The optimizer run on a distributed cluster.

Linear Supertypes
Optimizer[T, MiniBatch[T]], AnyRef, Any
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  2. Optimizer
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Instance Constructors

  1. new DistriOptimizer(_model: Module[T], dataset: DistributedDataSet[MiniBatch[T]], criterion: Criterion[T])(implicit arg0: ClassTag[T], ev: TensorNumeric[T])

    _model

    train model

    dataset

    train dataset

    criterion

    loss function

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 ==(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  5. final def ==(arg0: Any): Boolean

    Definition Classes
    Any
  6. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  7. var checkSingleton: Boolean

    Attributes
    protected
    Definition Classes
    Optimizer
  8. var checkpointPath: Option[String]

    Attributes
    protected
    Definition Classes
    Optimizer
  9. var checkpointTrigger: Option[Trigger]

    Attributes
    protected
    Definition Classes
    Optimizer
  10. def clearState(): Unit

    Clean some internal states, so this or other optimizers can run optimize again

    Clean some internal states, so this or other optimizers can run optimize again

    This method will be called at the end of optimize. You need not call it if optimize succeed. If the optimize fails, you may call it before next optimize.

  11. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  12. var computeThresholdbatchSize: Int

    Attributes
    protected
    Definition Classes
    Optimizer
  13. var dropPercentage: Double

    Attributes
    protected
    Definition Classes
    Optimizer
  14. var endWhen: Trigger

    Attributes
    protected
    Definition Classes
    Optimizer
  15. final def eq(arg0: AnyRef): Boolean

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

    Definition Classes
    AnyRef → Any
  17. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  18. def getCheckpointPath(): Option[String]

    Get the directory of saving checkpoint

    Get the directory of saving checkpoint

    Definition Classes
    Optimizer
  19. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  20. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  21. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  22. var isOverWrite: Boolean

    Attributes
    protected
    Definition Classes
    Optimizer
  23. var maxDropPercentage: Double

    Attributes
    protected
    Definition Classes
    Optimizer
  24. val metrics: Metrics

  25. var model: Module[T]

    Attributes
    protected
    Definition Classes
    Optimizer
  26. final def ne(arg0: AnyRef): Boolean

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

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

    Definition Classes
    AnyRef
  29. var optimMethod: OptimMethod[T]

    Attributes
    protected
    Definition Classes
    Optimizer
  30. def optimize(): Module[T]

    Trigger the optimization process

    Trigger the optimization process

    returns

    the model to be trained

    Definition Classes
    DistriOptimizerOptimizer
  31. def overWriteCheckpoint(): DistriOptimizer.this.type

    Enable overwrite saving checkpoint

    Enable overwrite saving checkpoint

    Definition Classes
    Optimizer
  32. def prepareInput(): Unit

    Definition Classes
    DistriOptimizerOptimizer
  33. def setCheckpoint(path: String, trigger: Trigger): DistriOptimizer.this.type

    Set a check point saved at path triggered by trigger

    Set a check point saved at path triggered by trigger

    path

    the directory to save

    trigger

    how often to save the check point

    returns

    the optimizer

    Definition Classes
    Optimizer
  34. def setDropModuleProperty(dropPercentage: Double, maxDropPercentage: Double, batchsize: Int = 100, warmupIteration: Int = 200): DistriOptimizer.this.type

    Set dropping a certain percentage (dropPercentage) of models during distributed training to accelerate, because some cached model may take too long.

    Set dropping a certain percentage (dropPercentage) of models during distributed training to accelerate, because some cached model may take too long.

    dropPercentage

    drop percentage

    maxDropPercentage

    max drop percentage

    batchsize

    batch size

    warmupIteration

    how may iteration to warm up

    returns

    this optimizer

    Definition Classes
    Optimizer
  35. def setEndWhen(endWhen: Trigger): DistriOptimizer.this.type

    When to stop, passed in a Trigger

    When to stop, passed in a Trigger

    endWhen

    when to end

    returns

    the optimizer

    Definition Classes
    Optimizer
  36. def setModel(newModel: Module[T]): DistriOptimizer.this.type

    Set a model to the optimizer

    Set a model to the optimizer

    newModel

    new model

    Definition Classes
    Optimizer
  37. def setOptimMethod(method: OptimMethod[T]): DistriOptimizer.this.type

    Set an optimization method

    Set an optimization method

    method

    optimization method

    Definition Classes
    Optimizer
  38. def setState(state: Table): DistriOptimizer.this.type

    Set a state(learning rate, epochs.

    Set a state(learning rate, epochs...) to the optimizer

    state

    the state to be saved

    Definition Classes
    Optimizer
  39. def setTrainSummary(trainSummary: TrainSummary): DistriOptimizer.this.type

    Enable train summary.

    Enable train summary.

    Definition Classes
    Optimizer
  40. def setValidation(trigger: Trigger, sampleRDD: RDD[Sample[T]], vMethods: Array[ValidationMethod[T]], batchSize: Int, miniBatch: MiniBatch[T]): DistriOptimizer.this.type

    Set validate evaluation

    Set validate evaluation

    trigger

    how often to evaluation validation set

    sampleRDD

    validate data set in type of RDD of Sample

    vMethods

    a set of validation method ValidationMethod

    batchSize

    batch size

    miniBatch

    construct MiniBatch with a specified miniBatch type

    returns

    Definition Classes
    Optimizer
  41. def setValidation(trigger: Trigger, sampleRDD: RDD[Sample[T]], vMethods: Array[ValidationMethod[T]], batchSize: Int): DistriOptimizer.this.type

    Set a validate evaluation

    Set a validate evaluation

    trigger

    how often to evaluation validation set

    sampleRDD

    validate data set in type of RDD of Sample

    vMethods

    a set of validation method ValidationMethod

    batchSize

    batch size

    returns

    this optimizer

    Definition Classes
    Optimizer
  42. def setValidation(trigger: Trigger, sampleRDD: RDD[Sample[T]], vMethods: Array[ValidationMethod[T]], batchSize: Int, featurePaddingParam: PaddingParam[T], labelPaddingParam: PaddingParam[T]): DistriOptimizer.this.type

    Set a validate evaluation

    Set a validate evaluation

    trigger

    how often to evaluation validation set

    sampleRDD

    validate data set in type of RDD of Sample

    vMethods

    a set of validation method ValidationMethod

    batchSize

    batch size

    featurePaddingParam

    feature padding strategy, see com.intel.analytics.bigdl.dataset.PaddingParam for details.

    labelPaddingParam

    label padding strategy, see com.intel.analytics.bigdl.dataset.PaddingParam for details.

    returns

    this optimizer

    Definition Classes
    Optimizer
  43. def setValidation(trigger: Trigger, dataset: DataSet[MiniBatch[T]], vMethods: Array[ValidationMethod[T]]): DistriOptimizer.this.type

    Set a validate evaluation

    Set a validate evaluation

    trigger

    how often to evaluation validation set

    dataset

    validate data set in type of DataSet of MiniBatch

    vMethods

    a set of validation method ValidationMethod

    returns

    this optimizer

    Definition Classes
    Optimizer
  44. def setValidationSummary(validationSummary: ValidationSummary): DistriOptimizer.this.type

    Enable validation summary.

    Enable validation summary.

    Definition Classes
    Optimizer
  45. var state: Table

    Attributes
    protected
    Definition Classes
    Optimizer
  46. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  47. def toString(): String

    Definition Classes
    AnyRef → Any
  48. var trainSummary: Option[TrainSummary]

    Attributes
    protected
    Definition Classes
    Optimizer
  49. var validationDataSet: Option[DataSet[MiniBatch[T]]]

    Attributes
    protected
    Definition Classes
    Optimizer
  50. var validationMethods: Option[Array[ValidationMethod[T]]]

    Attributes
    protected
    Definition Classes
    Optimizer
  51. var validationSummary: Option[ValidationSummary]

    Attributes
    protected
    Definition Classes
    Optimizer
  52. var validationTrigger: Option[Trigger]

    Attributes
    protected
    Definition Classes
    Optimizer
  53. final def wait(): Unit

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

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

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  56. var warmupIterationNum: Int

    Attributes
    protected
    Definition Classes
    Optimizer

Deprecated Value Members

  1. def disableCheckSingleton(): DistriOptimizer.this.type

    make optimizer not check the singleton model on a node

    make optimizer not check the singleton model on a node

    returns

    Definition Classes
    Optimizer
    Annotations
    @deprecated
    Deprecated

    (Since version 0.1.0) Use bigdl.check.singleton instead

Inherited from Optimizer[T, MiniBatch[T]]

Inherited from AnyRef

Inherited from Any

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