object Math extends Math
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- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- def abs[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def acos[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def acosh[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def add[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- def addN[T](inputs: Seq[Tensor[T]])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): Tensor[T]
- Definition Classes
- Math
- def all[I](input: Tensor[Boolean], axes: Tensor[I] = null, keepDims: Boolean = false)(implicit arg0: IntDefault[I], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Tensor[Boolean]
- Definition Classes
- Math
- def angleDouble[TL[A] <: TensorLike[A]](input: TL[core.types.ComplexDouble], name: String = "Angle")(implicit ev: Aux[TL, core.types.ComplexDouble]): TL[Double]
- Definition Classes
- Math
- def angleFloat[TL[A] <: TensorLike[A]](input: TL[core.types.ComplexFloat], name: String = "Angle")(implicit ev: Aux[TL, core.types.ComplexFloat]): TL[Float]
- Definition Classes
- Math
- def any[I](input: Tensor[Boolean], axes: Tensor[I] = null, keepDims: Boolean = false)(implicit arg0: IntDefault[I], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Tensor[Boolean]
- Definition Classes
- Math
- def approximatelyEqual[T](x: Tensor[T], y: Tensor[T], tolerance: Float = 0.00001f)(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): Tensor[Boolean]
- Definition Classes
- Math
- def argmax[T, I, IR](input: Tensor[T], axes: Tensor[I], outputDataType: core.types.DataType[IR])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I], arg4: core.types.TF[IR], arg5: core.types.IsIntOrLong[IR]): Tensor[IR]
- Definition Classes
- Math
- def argmax[T, I](input: Tensor[T], axes: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): Tensor[Long]
- Definition Classes
- Math
- def argmin[T, I, IR](input: Tensor[T], axes: Tensor[I], outputDataType: core.types.DataType[IR])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I], arg4: core.types.TF[IR], arg5: core.types.IsIntOrLong[IR]): Tensor[IR]
- Definition Classes
- Math
- def argmin[T, I](input: Tensor[T], axes: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): Tensor[Long]
- Definition Classes
- Math
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def asin[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def asinh[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def atan[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def atan2[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): Tensor[T]
- Definition Classes
- Math
- def atanh[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def binCount[T](input: Tensor[Int], dataType: core.types.DataType[T], weights: Tensor[T] = null, minLength: Tensor[Int] = null, maxLength: Tensor[Int] = null)(implicit arg0: core.types.TF[T], arg1: core.types.IsIntOrLongOrFloatOrDouble[T]): Tensor[T]
- Definition Classes
- Math
- def bucketize[T](input: Tensor[T], boundaries: Seq[Float])(implicit arg0: core.types.TF[T], arg1: core.types.IsIntOrLongOrFloatOrDouble[T]): Tensor[T]
- Definition Classes
- Math
- def ceil[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsHalfOrFloatOrDouble[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
- def complexDouble(real: Tensor[Double], imag: Tensor[Double]): Tensor[core.types.ComplexDouble]
- Definition Classes
- Math
- def complexFloat(real: Tensor[Float], imag: Tensor[Float]): Tensor[core.types.ComplexFloat]
- Definition Classes
- Math
- def conjugate[T, TL[A] <: TensorLike[A]](input: TL[T])(implicit arg0: core.types.TF[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def cos[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def cosh[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def countNonZero[T, I](input: Tensor[T], axes: Tensor[I] = null, keepDims: Boolean = false)(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T], arg2: IntDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): Tensor[Long]
- Definition Classes
- Math
- def cross[T](a: Tensor[T], b: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): Tensor[T]
- Definition Classes
- Math
- def cumprod[T, I](input: Tensor[T], axis: Tensor[I], exclusive: Boolean = false, reverse: Boolean = false)(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Math
- def cumsum[T, I](input: Tensor[T], axis: Tensor[I], exclusive: Boolean = false, reverse: Boolean = false)(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Math
- def diag[T](diagonal: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- def diagPart[T](input: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- def digamma[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def divide[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equal[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T]): Tensor[Boolean]
- Definition Classes
- Math
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- def erf[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def erfc[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def exp[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def expm1[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def floor[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsHalfOrFloatOrDouble[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def floorMod[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def greater[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): Tensor[Boolean]
- Definition Classes
- Math
- def greaterEqual[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): Tensor[Boolean]
- Definition Classes
- Math
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def igamma[T](a: Tensor[T], x: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): Tensor[T]
- Definition Classes
- Math
- def igammac[T](a: Tensor[T], x: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): Tensor[T]
- Definition Classes
- Math
- def imagDouble[TL[A] <: TensorLike[A]](input: TL[core.types.ComplexDouble], name: String = "Imag")(implicit ev: Aux[TL, core.types.ComplexDouble]): TL[Double]
- Definition Classes
- Math
- def imagFloat[TL[A] <: TensorLike[A]](input: TL[core.types.ComplexFloat], name: String = "Imag")(implicit ev: Aux[TL, core.types.ComplexFloat]): TL[Float]
- Definition Classes
- Math
- def incompleteBeta[T](a: Tensor[T], b: Tensor[T], x: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): Tensor[T]
- Definition Classes
- Math
- def isFinite[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsHalfOrFloatOrDouble[T], ev: Aux[TL, T]): TL[Boolean]
- Definition Classes
- Math
- def isInf[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsHalfOrFloatOrDouble[T], ev: Aux[TL, T]): TL[Boolean]
- Definition Classes
- Math
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- def isNaN[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsHalfOrFloatOrDouble[T], ev: Aux[TL, T]): TL[Boolean]
- Definition Classes
- Math
- def less[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): Tensor[Boolean]
- Definition Classes
- Math
- def lessEqual[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): Tensor[Boolean]
- Definition Classes
- Math
- def linspace[T, I](start: Tensor[T], stop: Tensor[T], numberOfValues: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.IsTruncatedHalfOrFloatOrDouble[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Math
- def log[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def log1p[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def logGamma[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def logSigmoid[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def logSumExp[T](input: Tensor[T], axes: Seq[Int] = null, keepDims: Boolean = false)(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- def logicalAnd(x: Tensor[Boolean], y: Tensor[Boolean]): Tensor[Boolean]
- Definition Classes
- Math
- def logicalNot(x: Tensor[Boolean]): Tensor[Boolean]
- Definition Classes
- Math
- def logicalOr(x: Tensor[Boolean], y: Tensor[Boolean]): Tensor[Boolean]
- Definition Classes
- Math
- def logicalXOr(x: Tensor[Boolean], y: Tensor[Boolean]): Tensor[Boolean]
- Definition Classes
- Math
- def magnitudeDouble[TL[A] <: TensorLike[A]](input: TL[core.types.ComplexDouble], name: String = "Magnitude")(implicit ev: Aux[TL, core.types.ComplexDouble]): TL[Double]
- Definition Classes
- Math
- def magnitudeFloat[TL[A] <: TensorLike[A]](input: TL[core.types.ComplexFloat], name: String = "Magnitude")(implicit ev: Aux[TL, core.types.ComplexFloat]): TL[Float]
- Definition Classes
- Math
- def matmul[T](a: Tensor[T], b: Tensor[T], transposeA: Boolean = false, transposeB: Boolean = false, conjugateA: Boolean = false, conjugateB: Boolean = false, aIsSparse: Boolean = false, bIsSparse: Boolean = false)(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- def matrixBandPart[T, I](input: Tensor[T], numSubDiagonals: Tensor[I], numSuperDiagonals: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Math
- def matrixDiag[T](diagonal: Tensor[T])(implicit arg0: core.types.TF[T]): Tensor[T]
- Definition Classes
- Math
- def matrixDiagPart[T](input: Tensor[T])(implicit arg0: core.types.TF[T]): Tensor[T]
- Definition Classes
- Math
- def matrixSetDiag[T](input: Tensor[T], diagonal: Tensor[T])(implicit arg0: core.types.TF[T]): Tensor[T]
- Definition Classes
- Math
- def max[T, I](input: Tensor[T], axes: Tensor[I] = null, keepDims: Boolean = false)(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: IntDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Math
- def maximum[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- def mean[T, I](input: Tensor[T], axes: Tensor[I] = null, keepDims: Boolean = false)(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T], arg2: IntDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Math
- def min[T, I](input: Tensor[T], axes: Tensor[I] = null, keepDims: Boolean = false)(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: IntDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Math
- def minimum[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- def mod[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- def multiply[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def negate[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def notEqual[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T]): Tensor[Boolean]
- Definition Classes
- Math
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def polygamma[T](n: Tensor[T], x: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): Tensor[T]
- Definition Classes
- Math
- def pow[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- def prod[T, I](input: Tensor[T], axes: Tensor[I] = null, keepDims: Boolean = false)(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: IntDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Math
- def range[T](start: Tensor[T], limit: Tensor[T], delta: Tensor[T] = null)(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): Tensor[T]
- Definition Classes
- Math
- def realDivide[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- def realDouble[TL[A] <: TensorLike[A]](input: TL[core.types.ComplexDouble], name: String = "Real")(implicit ev: Aux[TL, core.types.ComplexDouble]): TL[Double]
- Definition Classes
- Math
- def realFloat[TL[A] <: TensorLike[A]](input: TL[core.types.ComplexFloat], name: String = "Real")(implicit ev: Aux[TL, core.types.ComplexFloat]): TL[Float]
- Definition Classes
- Math
- def reciprocal[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def round[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def roundInt[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsHalfOrFloatOrDouble[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def rsqrt[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def scalarMul[T, TL[A] <: TensorLike[A]](scalar: Tensor[T], tensor: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def segmentMax[T, I](data: Tensor[T], segmentIndices: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Math
- def segmentMean[T, I](data: Tensor[T], segmentIndices: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Math
- def segmentMin[T, I](data: Tensor[T], segmentIndices: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Math
- def segmentProd[T, I](data: Tensor[T], segmentIndices: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Math
- def segmentSum[T, I](data: Tensor[T], segmentIndices: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Math
- def select[T](condition: Tensor[Boolean], x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T]): Tensor[T]
- Definition Classes
- Math
- def sigmoid[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def sign[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def sin[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def sinh[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def sparseSegmentMean[T, I1, I2](data: Tensor[T], indices: Tensor[I1], segmentIndices: Tensor[Int], numSegments: Tensor[I2] = null)(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: IntDefault[I2], arg5: core.types.TF[I2], arg6: core.types.IsIntOrLong[I2]): Tensor[T]
- Definition Classes
- Math
- def sparseSegmentSum[T, I1, I2](data: Tensor[T], indices: Tensor[I1], segmentIndices: Tensor[Int], numSegments: Tensor[I2] = null)(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: IntDefault[I2], arg5: core.types.TF[I2], arg6: core.types.IsIntOrLong[I2]): Tensor[T]
- Definition Classes
- Math
- def sparseSegmentSumSqrtN[T, I1, I2](data: Tensor[T], indices: Tensor[I1], segmentIndices: Tensor[Int], numSegments: Tensor[I2] = null)(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: IntDefault[I2], arg5: core.types.TF[I2], arg6: core.types.IsIntOrLong[I2]): Tensor[T]
- Definition Classes
- Math
- def sqrt[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def square[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def squaredDifference[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- def subtract[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- def sum[T, I](input: Tensor[T], axes: Tensor[I] = null, keepDims: Boolean = false)(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T], arg2: IntDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Math
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def tan[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def tanh[T, TL[A] <: TensorLike[A]](x: TL[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[TL, T]): TL[T]
- Definition Classes
- Math
- def tensorDot[T](a: Tensor[T], b: Tensor[T], axesA: Tensor[Int], axesB: Tensor[Int])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidShapeException])
- def tensorDot[T](a: Tensor[T], b: Tensor[T], numAxes: Tensor[Int])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidShapeException])
- def toString(): String
- Definition Classes
- AnyRef → Any
- def trace[T](input: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): Tensor[T]
- Definition Classes
- Math
- def truncateDivide[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- def truncateMod[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- def unsortedSegmentMax[T, I1, I2](data: Tensor[T], segmentIndices: Tensor[I1], segmentsNumber: Tensor[I2])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: core.types.TF[I2], arg5: core.types.IsIntOrLong[I2]): Tensor[T]
- Definition Classes
- Math
- def unsortedSegmentSum[T, I1, I2](data: Tensor[T], segmentIndices: Tensor[I1], segmentsNumber: Tensor[I2])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: core.types.TF[I2], arg5: core.types.IsIntOrLong[I2]): Tensor[T]
- Definition Classes
- Math
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- def zerosFraction[T](input: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): Tensor[Float]
- Definition Classes
- Math
- def zeta[T](x: Tensor[T], q: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): Tensor[T]
- Definition Classes
- Math
Deprecated Value Members
- def finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.Throwable]) @Deprecated @deprecated
- Deprecated
(Since version ) see corresponding Javadoc for more information.
- def floorDivide[T](x: Tensor[T], y: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Tensor[T]
- Definition Classes
- Math
- Annotations
- @deprecated
- Deprecated
(Since version 0.1) Use
truncateDivideinstead.