org.apache.mxnet.javaapi

Convolution_v1Param

Related Doc: package javaapi

class Convolution_v1Param extends AnyRef

This Param Object is specifically used for Convolution_v1

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Instance Constructors

  1. new Convolution_v1Param(data: NDArray, weight: NDArray, bias: NDArray, kernel: Shape, num_filter: Integer)

    data

    Input data to the ConvolutionV1Op.

    weight

    Weight matrix.

    bias

    Bias parameter.

    kernel

    convolution kernel size: (h, w) or (d, h, w)

    num_filter

    convolution filter(channel) number

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  9. def getBias(): NDArray

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

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  11. def getCudnn_off(): Boolean

  12. def getCudnn_tune(): String

  13. def getData(): NDArray

  14. def getDilate(): Shape

  15. def getKernel(): Shape

  16. def getLayout(): String

  17. def getNo_bias(): Boolean

  18. def getNum_filter(): Integer

  19. def getNum_group(): Integer

  20. def getOut(): mxnet.NDArray

  21. def getPad(): Shape

  22. def getStride(): Shape

  23. def getWeight(): NDArray

  24. def getWorkspace(): Long

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  28. final def notify(): Unit

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  29. final def notifyAll(): Unit

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  30. def setCudnn_off(cudnn_off: Boolean): Convolution_v1Param

    cudnn_off

    Turn off cudnn for this layer.

  31. def setCudnn_tune(cudnn_tune: String): Convolution_v1Param

    cudnn_tune

    Whether to pick convolution algo by running performance test. Leads to higher startup time but may give faster speed. Options are: 'off': no tuning 'limited_workspace': run test and pick the fastest algorithm that doesn't exceed workspace limit. 'fastest': pick the fastest algorithm and ignore workspace limit. If set to None (default), behavior is determined by environment variable MXNET_CUDNN_AUTOTUNE_DEFAULT: 0 for off, 1 for limited workspace (default), 2 for fastest.

  32. def setDilate(dilate: Shape): Convolution_v1Param

    dilate

    convolution dilate: (h, w) or (d, h, w)

  33. def setLayout(layout: String): Convolution_v1Param

    layout

    Set layout for input, output and weight. Empty for default layout: NCHW for 2d and NCDHW for 3d.

  34. def setNo_bias(no_bias: Boolean): Convolution_v1Param

    no_bias

    Whether to disable bias parameter.

  35. def setNum_group(num_group: Integer): Convolution_v1Param

    num_group

    Number of group partitions. Equivalent to slicing input into num_group partitions, apply convolution on each, then concatenate the results

  36. def setOut(out: NDArray): Convolution_v1Param

  37. def setPad(pad: Shape): Convolution_v1Param

    pad

    pad for convolution: (h, w) or (d, h, w)

  38. def setStride(stride: Shape): Convolution_v1Param

    stride

    convolution stride: (h, w) or (d, h, w)

  39. def setWorkspace(workspace: Long): Convolution_v1Param

    workspace

    Maximum temporary workspace allowed for convolution (MB).This parameter determines the effective batch size of the convolution kernel, which may be smaller than the given batch size. Also, the workspace will be automatically enlarged to make sure that we can run the kernel with batch_size=1

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