org.apache.mxnet.javaapi

EmbeddingParam

Related Doc: package javaapi

class EmbeddingParam extends AnyRef

This Param Object is specifically used for Embedding

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Instance Constructors

  1. new EmbeddingParam(data: NDArray, weight: NDArray, input_dim: Integer, output_dim: Integer)

    data

    The input array to the embedding operator.

    weight

    The embedding weight matrix.

    input_dim

    Vocabulary size of the input indices.

    output_dim

    Dimension of the embedding vectors.

Value Members

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

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  2. final def ##(): Int

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  3. final def ==(arg0: Any): Boolean

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  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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

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  7. def equals(arg0: Any): Boolean

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  8. def finalize(): Unit

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

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  10. def getData(): NDArray

  11. def getDtype(): String

  12. def getInput_dim(): Integer

  13. def getOut(): mxnet.NDArray

  14. def getOutput_dim(): Integer

  15. def getSparse_grad(): Boolean

  16. def getWeight(): NDArray

  17. def hashCode(): Int

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  18. final def isInstanceOf[T0]: Boolean

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

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  20. final def notify(): Unit

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  21. final def notifyAll(): Unit

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  22. def setDtype(dtype: String): EmbeddingParam

    dtype

    Data type of weight.

  23. def setOut(out: NDArray): EmbeddingParam

  24. def setSparse_grad(sparse_grad: Boolean): EmbeddingParam

    sparse_grad

    Compute row sparse gradient in the backward calculation. If set to True, the grad's storage type is row_sparse.

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

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  26. def toString(): String

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  27. final def wait(): Unit

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

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

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