com.intel.analytics.bigdl.nn

BilinearFiller

object BilinearFiller extends InitializationMethod with Product with Serializable

Initialize the weight with coefficients for bilinear interpolation.

A common use case is with the DeconvolutionLayer acting as upsampling. The variable tensor passed in the init function should have 5 dimensions of format [nGroup, nInput, nOutput, kH, kW], and kH should be equal to kW

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Type Members

  1. type Shape = Array[Int]

    Definition Classes
    InitializationMethod

Value Members

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

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

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  3. final def ##(): Int

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

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  10. def finalize(): Unit

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

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  12. def init[T](variable: Tensor[T], dataFormat: VariableFormat = Default)(implicit ev: TensorNumeric[T]): Unit

    Initialize the given weight and bias.

    Initialize the given weight and bias.

    variable

    the weight to initialize

    dataFormat

    the data format of weight indicating the dimension order of the weight. "output_first" means output is in the lower dimension "input_first" means input is in the lower dimension.

    Definition Classes
    BilinearFiller → InitializationMethod

  13. final def isInstanceOf[T0]: Boolean

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

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  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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

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  18. final def wait(): Unit

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

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

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