object
Optimizer
Value Members
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final
def
!=(arg0: AnyRef): Boolean
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: AnyRef): Boolean
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final
def
==(arg0: Any): Boolean
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def
apply[T, D](model: Module[T], dataset: DataSet[D], criterion: Criterion[T])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Optimizer[T, D]
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def
apply[T](model: Module[T], sampleRDD: RDD[Sample[T]], criterion: Criterion[T], batchSize: Int, miniBatch: MiniBatch[T])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Optimizer[T, MiniBatch[T]]
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def
apply[T](model: Module[T], sampleRDD: RDD[Sample[T]], criterion: Criterion[T], batchSize: Int, featurePaddingParam: PaddingParam[T])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Optimizer[T, MiniBatch[T]]
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def
apply[T](model: Module[T], sampleRDD: RDD[Sample[T]], criterion: Criterion[T], batchSize: Int, featurePaddingParam: PaddingParam[T], labelPaddingParam: PaddingParam[T])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Optimizer[T, MiniBatch[T]]
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def
apply[T](model: Module[T], sampleRDD: RDD[Sample[T]], criterion: Criterion[T], batchSize: Int)(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): Optimizer[T, MiniBatch[T]]
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final
def
asInstanceOf[T0]: T0
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def
clone(): AnyRef
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final
def
eq(arg0: AnyRef): Boolean
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def
equals(arg0: Any): Boolean
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def
finalize(): Unit
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final
def
getClass(): Class[_]
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def
hashCode(): Int
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final
def
isInstanceOf[T0]: Boolean
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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final
def
notifyAll(): Unit
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final
def
synchronized[T0](arg0: ⇒ T0): T0
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def
toString(): String
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
Inherited from AnyRef
Inherited from Any