org.apache.mxnet.javaapi

UpSamplingParam

Related Doc: package javaapi

class UpSamplingParam extends AnyRef

This Param Object is specifically used for UpSampling

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Instance Constructors

  1. new UpSamplingParam(data: Array[NDArray], scale: Integer, sample_type: String, num_args: Integer)

    data

    Array of tensors to upsample. For bilinear upsampling, there should be 2 inputs - 1 data and 1 weight.

    scale

    Up sampling scale

    sample_type

    upsampling method

    num_args

    Number of inputs to be upsampled. For nearest neighbor upsampling, this can be 1-N; the size of output will be(scale*h_0,scale*w_0) and all other inputs will be upsampled to thesame size. For bilinear upsampling this must be 2; 1 input and 1 weight.

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

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  10. def getData(): Array[NDArray]

  11. def getMulti_input_mode(): String

  12. def getNum_args(): Integer

  13. def getNum_filter(): Integer

  14. def getOut(): mxnet.NDArray

  15. def getSample_type(): String

  16. def getScale(): Integer

  17. def getWorkspace(): Long

  18. def hashCode(): Int

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  21. final def notify(): Unit

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  22. final def notifyAll(): Unit

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  23. def setMulti_input_mode(multi_input_mode: String): UpSamplingParam

    multi_input_mode

    How to handle multiple input. concat means concatenate upsampled images along the channel dimension. sum means add all images together, only available for nearest neighbor upsampling.

  24. def setNum_filter(num_filter: Integer): UpSamplingParam

    num_filter

    Input filter. Only used by bilinear sample_type.Since bilinear upsampling uses deconvolution, num_filters is set to the number of channels.

  25. def setOut(out: NDArray): UpSamplingParam

  26. def setWorkspace(workspace: Long): UpSamplingParam

    workspace

    Tmp workspace for deconvolution (MB)

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

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  28. def toString(): String

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