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com.intel.analytics.zoo.pipeline.api.autograd

CustomLoss

Related Docs: class CustomLoss | package autograd

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object CustomLoss extends Serializable

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

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  4. def apply[T](lossFunc: (Variable[T], Variable[T]) ⇒ Variable[T], yPredShape: Shape, yTrueShape: Shape = null, sizeAverage: Boolean = true)(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): TensorLossFunction[T]

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    lossFunc

    function to calculate the loss (yTrue, yPred) => loss

    yPredShape

    the pred shape without batch

    yTrueShape

    the target shape without batch which is the same as yPredShape by default.

    sizeAverage

    average the batch result or not

  5. final def asInstanceOf[T0]: T0

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