org.apache.mxnet.javaapi

ctc_lossParam

Related Doc: package javaapi

class ctc_lossParam extends AnyRef

This Param Object is specifically used for ctc_loss

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Instance Constructors

  1. new ctc_lossParam(data: NDArray, label: NDArray, data_lengths: NDArray, label_lengths: NDArray)

    data

    Input ndarray

    label

    Ground-truth labels for the loss.

    data_lengths

    Lengths of data for each of the samples. Only required when use_data_lengths is true.

    label_lengths

    Lengths of labels for each of the samples. Only required when use_label_lengths is true.

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  9. def getBlank_label(): String

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  11. def getData(): NDArray

  12. def getData_lengths(): NDArray

  13. def getLabel(): NDArray

  14. def getLabel_lengths(): NDArray

  15. def getOut(): mxnet.NDArray

  16. def getUse_data_lengths(): Boolean

  17. def getUse_label_lengths(): Boolean

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  23. def setBlank_label(blank_label: String): ctc_lossParam

    blank_label

    Set the label that is reserved for blank label.If "first", 0-th label is reserved, and label values for tokens in the vocabulary are between 1 and alphabet_size-1, and the padding mask is -1. If "last", last label value alphabet_size-1 is reserved for blank label instead, and label values for tokens in the vocabulary are between 0 and alphabet_size-2, and the padding mask is 0.

  24. def setOut(out: NDArray): ctc_lossParam

  25. def setUse_data_lengths(use_data_lengths: Boolean): ctc_lossParam

    use_data_lengths

    Whether the data lenghts are decided by data_lengths. If false, the lengths are equal to the max sequence length.

  26. def setUse_label_lengths(use_label_lengths: Boolean): ctc_lossParam

    use_label_lengths

    Whether the label lenghts are decided by label_lengths, or derived from padding_mask. If false, the lengths are derived from the first occurrence of the value of padding_mask. The value of padding_mask is 0 when first CTC label is reserved for blank, and -1 when last label is reserved for blank. See blank_label.

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