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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.  def apply(schemas: Seq[RowTransformSchema], rowSize: Int = 0): RowTransformer
5.  final def asInstanceOf[T0]: T0

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6.  def atomic(indices: Seq[Int], rowSize: Int): RowTransformer

   A RowTransformer which transform each selected columns to a size(1) Tensor.

   A RowTransformer which transform each selected columns to a size(1) Tensor. The keys of output Table are indices of selected columns.

   indices

   indices of selected columns

   rowSize

   size of Row transformed by this transformer

7.  def atomic(fieldNames: Seq[String]): RowTransformer

   A RowTransformer which transform each selected columns to a size(1) Tensor.

   A RowTransformer which transform each selected columns to a size(1) Tensor. The keys of output Table are fieldNames of selected columns.

   fieldNames

   field names of selected columns

8.  def atomicWithNumeric[T](atomicFields: Seq[String], numericFields: Map[String, Seq[String]])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): RowTransformer

   A RowTransformer which contains both atomic schemas and numeric schemas.

   A RowTransformer which contains both atomic schemas and numeric schemas.

   atomicFields

   field names of selected columns

   numericFields

   Map<schemaKey, fieldNames of selected columns> of numeric fields

9.  def clone(): AnyRef

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10.  final def eq(arg0: AnyRef): Boolean

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11.  def equals(arg0: Any): Boolean

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12.  def finalize(): Unit

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13.  final def getClass(): Class[_]

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14.  def hashCode(): Int

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15.  final def isInstanceOf[T0]: Boolean

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16.  final def ne(arg0: AnyRef): Boolean

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17.  final def notify(): Unit

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18.  final def notifyAll(): Unit

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19.  def numeric[T](numericFields: Map[String, Seq[String]])(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): RowTransformer

    A RowTransformer which concat values of selected columns to one Tensor.

    A RowTransformer which concat values of selected columns to one Tensor. It means you will get a Table with keys of numericFields. Values of Table are Tensors concatenated by selected columns of the keys.

    numericFields

    Map<schemaKey, fieldNames of selected columns> of numeric fields

20.  def numeric[T](schemaKey: String = "all")(implicit arg0: ClassTag[T], ev: TensorNumeric[T]): RowTransformer

    A RowTransformer which concat values of all columns to one Tensor.

    A RowTransformer which concat values of all columns to one Tensor. It means you will get a Table with single key-value pair after transformation. The unique key is schemaKey. The unique value is a size(length of Row) Tensor.

    schemaKey

    key of the schema, default value is "all"

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

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22.  def toString(): String

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23.  final def wait(): Unit

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

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25.  final def wait(arg0: Long): Unit

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