Class/Object

ml.dmlc.mxnet

NDArray

Related Docs: object NDArray | package mxnet

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class NDArray extends AnyRef

NDArray object in mxnet. NDArray is basic ndarray/Tensor like data structure in mxnet.
WARNING: it is your responsibility to clear this object through dispose(). NEVER rely on the GC strategy

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

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    Definition Classes
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  2. final def ##(): Int

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    Definition Classes
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  3. def %(other: Float): NDArray

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  4. def %(other: NDArray): NDArray

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  5. def %=(other: Float): NDArray

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  6. def %=(other: NDArray): NDArray

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  7. def *(other: Float): NDArray

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  8. def *(other: NDArray): NDArray

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  9. def **(other: Float): NDArray

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  10. def **(other: NDArray): NDArray

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  11. def **=(other: Float): NDArray

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  12. def **=(other: NDArray): NDArray

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  13. def *=(other: Float): NDArray

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  14. def *=(other: NDArray): NDArray

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  15. def +(other: Float): NDArray

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  16. def +(other: NDArray): NDArray

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  17. def +=(other: Float): NDArray

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  18. def +=(other: NDArray): NDArray

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  19. def -(other: Float): NDArray

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  20. def -(other: NDArray): NDArray

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  21. def -=(other: Float): NDArray

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  22. def -=(other: NDArray): NDArray

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  23. def /(other: Float): NDArray

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  24. def /(other: NDArray): NDArray

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  25. def /=(other: Float): NDArray

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  26. def /=(other: NDArray): NDArray

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  27. def <(other: Float): NDArray

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  28. def <(other: NDArray): NDArray

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  29. def <=(other: Float): NDArray

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  30. def <=(other: NDArray): NDArray

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

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    Definition Classes
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  32. def >(other: Float): NDArray

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  33. def >(other: NDArray): NDArray

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  34. def >=(other: Float): NDArray

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  35. def >=(other: NDArray): NDArray

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  36. def T: NDArray

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  37. def asInContext(context: Context): NDArray

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    Return an NDArray that lives in the target context.

    Return an NDArray that lives in the target context. If the array is already in that context, self is returned. Otherwise, a copy is made.

    context

    The target context we want the return value to live in.

    returns

    A copy or self as an NDArray that lives in the target context.

  38. final def asInstanceOf[T0]: T0

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    Definition Classes
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  39. def asType(dtype: DType): NDArray

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    Return a copied numpy array of current array with specified type.

    Return a copied numpy array of current array with specified type.

    dtype

    Desired type of result array.

    returns

    A copy of array content.

  40. def at(idx: Int): NDArray

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    Return a sub NDArray that shares memory with current one.

    Return a sub NDArray that shares memory with current one. the first axis will be rolled up, which causes its shape different from slice(i, i+1)

    idx

    index of sub array.

  41. def clone(): AnyRef

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    Attributes
    protected[java.lang]
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    @throws( ... )
  42. def context: Context

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    Get context of current NDArray.

    Get context of current NDArray.

    returns

    The context of current NDArray.

  43. def copy(): NDArray

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    Clone the current array

    Clone the current array

    returns

    the copied NDArray in the same context

  44. def copyTo(ctx: Context): NDArray

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    Copy the content of current array to a new NDArray in the context.

    Copy the content of current array to a new NDArray in the context.

    ctx

    Target context we want to copy data to.

    returns

    The copy target NDArray

  45. def copyTo(other: NDArray): NDArray

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    Copy the content of current array to other.

    Copy the content of current array to other.

    other

    Target NDArray or context we want to copy data to.

    returns

    The copy target NDArray

  46. def dispose(): Unit

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    Release the native memory.

    Release the native memory.
    The NDArrays it depends on will NOT be disposed.
    The object shall never be used after it is disposed.

  47. def disposeDeps(): NDArray

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    Dispose all NDArrays who help to construct this array.

    Dispose all NDArrays who help to construct this array.
    e.g. (a * b + c).disposeDeps() will dispose a, b, c (including their deps) and a * b

    returns

    this array

  48. def disposeDepsExcept(arrs: NDArray*): NDArray

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    Dispose all NDArrays who help to construct this array, excepts those in the arguments.

    Dispose all NDArrays who help to construct this array, excepts those in the arguments.
    e.g. (a * b + c).disposeDepsExcept(a, b) will dispose c and a * b. Note that a, b's dependencies will not be disposed either.

    returns

    this array

  49. def dtype: DType

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    Get data type of current NDArray.

    Get data type of current NDArray.

    returns

    class representing type of current ndarray

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

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    Definition Classes
    AnyRef
  51. def equals(o: Any): Boolean

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    Definition Classes
    NDArray → AnyRef → Any
  52. def finalize(): Unit

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    Attributes
    protected
    Definition Classes
    NDArray → AnyRef
  53. final def getClass(): Class[_]

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    Definition Classes
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  54. def hashCode(): Int

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    Definition Classes
    NDArray → AnyRef → Any
  55. def internal: NDArrayInternal

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  56. def isDisposed: Boolean

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  57. final def isInstanceOf[T0]: Boolean

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    Definition Classes
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  58. final def ne(arg0: AnyRef): Boolean

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    Definition Classes
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  59. final def notify(): Unit

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    Definition Classes
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  60. final def notifyAll(): Unit

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  61. def reshape(dims: Shape): NDArray

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    Return a reshaped NDArray that shares memory with current one.

    Return a reshaped NDArray that shares memory with current one.

    dims

    New shape.

    returns

    a reshaped NDArray that shares memory with current one.

  62. def reshape(dims: Array[Int]): NDArray

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    Return a reshaped NDArray that shares memory with current one.

    Return a reshaped NDArray that shares memory with current one.

    dims

    New shape.

    returns

    a reshaped NDArray that shares memory with current one.

  63. def serialize(): Array[Byte]

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  64. def set(other: Array[Float]): NDArray

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  65. def set(other: NDArray): NDArray

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  66. def set(value: Float): NDArray

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    Set the values of the NDArray

    Set the values of the NDArray

    value

    Value to set

    returns

    Current NDArray

  67. def shape: Shape

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    Get shape of current NDArray.

    Get shape of current NDArray.

    returns

    an array representing shape of current ndarray

  68. def size: Int

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  69. def slice(i: Int): NDArray

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    Return a sliced NDArray at the ith position of axis0

    Return a sliced NDArray at the ith position of axis0

    returns

    a sliced NDArray that shares memory with current one.

  70. def slice(range: (Int, Int)): NDArray

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  71. def slice(start: Int, stop: Int): NDArray

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    Return a sliced NDArray that shares memory with current one.

    Return a sliced NDArray that shares memory with current one. NDArray only support continuous slicing on axis 0

    start

    Starting index of slice.

    stop

    Finishing index of slice.

    returns

    a sliced NDArray that shares memory with current one.

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

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    Definition Classes
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  73. def toArray: Array[Float]

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    Return a copied flat java array of current array (row-major).

    Return a copied flat java array of current array (row-major).

    returns

    A copy of array content.

  74. def toScalar: Float

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    Return a CPU scalar(float) of current ndarray.

    Return a CPU scalar(float) of current ndarray. This ndarray must have shape (1,)

    returns

    The scalar representation of the ndarray.

  75. def toString(): String

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    Definition Classes
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  76. def unary_-(): NDArray

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  77. final def wait(): Unit

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

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

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  80. def waitToRead(): Unit

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    Block until all pending writes operations on current NDArray are finished.

    Block until all pending writes operations on current NDArray are finished. This function will return when all the pending writes to the current NDArray finishes. There can still be pending read going on when the function returns.

  81. val writable: Boolean

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