kmath-tensorflow/space.kscience.kmath.tensorflow/DoubleTensorFlowAlgebra

DoubleTensorFlowAlgebra

class DoubleTensorFlowAlgebra : TensorFlowAlgebra<Double, TFloat64, DoubleField> , PowerOperations<StructureND<Double>>

Functions

open override fun add(left: StructureND<Double>, right: StructureND<Double>): Tensor<Double>

open override fun StructureND<Double>.argMax(dim: Int, keepDim: Boolean): Tensor<Int>

binaryOperation

open fun binaryOperation(operation: String, left: StructureND<Double>, right: StructureND<Double>): StructureND<Double>

binaryOperationFunction

open override fun binaryOperationFunction(operation: String): (left: StructureND<Double>, right: StructureND<Double>) -> StructureND<Double>

open fun bindSymbol(value: String): StructureND<Double>

bindSymbolOrNull

open fun bindSymbolOrNull(value: String): StructureND<Double>?

diagonalEmbedding

open override fun diagonalEmbedding(diagonalEntries: Tensor<Double>, offset: Int, dim1: Int, dim2: Int): TensorFlowOutput<Double, TFloat64>

open operator fun StructureND<Double>.div(arg: StructureND<Double>): StructureND<Double>

open override fun divide(left: StructureND<Double>, right: StructureND<Double>): TensorFlowOutput<Double, TFloat64>

open infix override fun StructureND<Double>.dot(other: StructureND<Double>): TensorFlowOutput<Double, TFloat64>

open override fun export(arg: StructureND<Double>): StructureND<Double>

open operator override fun Tensor<Double>.get(i: Int): Tensor<Double>

open fun <F : StructureFeature> getFeature(structure: StructureND<Double>, type: KClass<out F>): F?

open operator fun (Double) -> Double.invoke(structure: StructureND<Double>): StructureND<Double>

open fun StructureND<Double>.map(transform: DoubleField.(Double) -> Double): StructureND<Double>

open fun StructureND<Double>.mapIndexed(transform: DoubleField.(index: IntArray, Double) -> Double): StructureND<Double>

open override fun StructureND<Double>.max(): Double

open override fun StructureND<Double>.max(dim: Int, keepDim: Boolean): Tensor<Double>

open override fun StructureND<Double>.min(): Double

open override fun StructureND<Double>.min(dim: Int, keepDim: Boolean): Tensor<Double>

open operator override fun Double.minus(arg: StructureND<Double>): Tensor<Double>

open operator override fun StructureND<Double>.minus(arg: Double): TensorFlowOutput<Double, TFloat64>

open operator override fun StructureND<Double>.minus(arg: StructureND<Double>): TensorFlowOutput<Double, TFloat64>

open operator override fun Tensor<Double>.minusAssign(value: Double)

open operator override fun Tensor<Double>.minusAssign(arg: StructureND<Double>)

open override fun multiply(left: StructureND<Double>, right: StructureND<Double>): Tensor<Double>

fun StructureND<Double>.operate(operation: (Operand<TFloat64>) -> Operand<TFloat64>): TensorFlowOutput<Double, TFloat64>

fun Double.operate(other: StructureND<Double>, operation: (left: Operand<TFloat64>, right: Operand<TFloat64>) -> Operand<TFloat64>): TensorFlowOutput<Double, TFloat64>

fun StructureND<Double>.operate(value: Double, operation: (left: Operand<TFloat64>, right: Operand<TFloat64>) -> Operand<TFloat64>): TensorFlowOutput<Double, TFloat64>

fun StructureND<Double>.operate(other: StructureND<Double>, operation: (left: Operand<TFloat64>, right: Operand<TFloat64>) -> Operand<TFloat64>): TensorFlowOutput<Double, TFloat64>

Perform binary lazy operation on tensor. Both arguments are implicitly converted

fun Tensor<Double>.operateInPlace(value: Double, operation: (left: Operand<TFloat64>, right: Operand<TFloat64>) -> Operand<TFloat64>)

fun Tensor<Double>.operateInPlace(other: StructureND<Double>, operation: (left: Operand<TFloat64>, right: Operand<TFloat64>) -> Operand<TFloat64>)

open operator override fun Double.plus(arg: StructureND<Double>): TensorFlowOutput<Double, TFloat64>

open operator override fun StructureND<Double>.plus(arg: Double): TensorFlowOutput<Double, TFloat64>

open operator override fun StructureND<Double>.plus(arg: StructureND<Double>): TensorFlowOutput<Double, TFloat64>

open operator override fun Tensor<Double>.plusAssign(value: Double)

open operator override fun Tensor<Double>.plusAssign(arg: StructureND<Double>)

open infix fun StructureND<Double>.pow(pow: Number): StructureND<Double>

open override fun power(arg: StructureND<Double>, pow: Number): TensorFlowOutput<Double, TFloat64>

open fun sqrt(arg: StructureND<Double>): StructureND<Double>

open override fun structureND(shape: Shape, initializer: DoubleField.(IntArray) -> Double): StructureND<Double>

open override fun StructureND<Double>.sum(): Double

open override fun StructureND<Double>.sum(dim: Int, keepDim: Boolean): TensorFlowOutput<Double, TFloat64>

open operator override fun Double.times(arg: StructureND<Double>): TensorFlowOutput<Double, TFloat64>

open operator override fun StructureND<Double>.times(arg: Double): TensorFlowOutput<Double, TFloat64>

open operator override fun StructureND<Double>.times(arg: StructureND<Double>): TensorFlowOutput<Double, TFloat64>

open operator override fun Tensor<Double>.timesAssign(value: Double)

open operator override fun Tensor<Double>.timesAssign(arg: StructureND<Double>)

open override fun Tensor<Double>.transpose(i: Int, j: Int): Tensor<Double>

open operator override fun StructureND<Double>.unaryMinus(): TensorFlowOutput<Double, TFloat64>

open fun unaryOperation(operation: String, arg: StructureND<Double>): StructureND<Double>

unaryOperationFunction

open override fun unaryOperationFunction(operation: String): (arg: StructureND<Double>) -> StructureND<Double>

open operator fun StructureND<Double>.unaryPlus(): StructureND<Double>

open fun StructureND<Double>.value(): Double

open override fun StructureND<Double>.valueOrNull(): Double?

open override fun Tensor<Double>.view(shape: IntArray): Tensor<Double>

open override fun Tensor<Double>.viewAs(other: StructureND<Double>): Tensor<Double>

open fun zip(left: StructureND<Double>, right: StructureND<Double>, transform: DoubleField.(Double, Double) -> Double): StructureND<Double>

Properties

open override val elementAlgebra: DoubleField

val ops: Ops

Sources