Dropping creation methods from interface
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@ -1,29 +1,10 @@
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package space.kscience.kmath.tensors
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import space.kscience.kmath.tensors.core.DoubleTensor
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// https://proofwiki.org/wiki/Definition:Algebra_over_Ring
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public interface TensorAlgebra<T, TensorType : TensorStructure<T>> {
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public fun TensorType.value(): T
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//https://pytorch.org/docs/stable/generated/torch.full.html
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public fun full(value: T, shape: IntArray): TensorType
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public fun ones(shape: IntArray): TensorType
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public fun zeros(shape: IntArray): TensorType
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//https://pytorch.org/docs/stable/generated/torch.full_like.html#torch.full_like
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public fun TensorType.fullLike(value: T): TensorType
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public fun TensorType.zeroesLike(): TensorType
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public fun TensorType.onesLike(): TensorType
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//https://pytorch.org/docs/stable/generated/torch.eye.html
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public fun eye(n: Int): TensorType
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public fun TensorType.copy(): TensorType
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public operator fun T.plus(other: TensorType): TensorType
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public operator fun TensorType.plus(value: T): TensorType
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public operator fun TensorType.plus(other: TensorType): TensorType
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@ -53,8 +34,6 @@ public interface TensorAlgebra<T, TensorType : TensorStructure<T>> {
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public fun TensorType.view(shape: IntArray): TensorType
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public fun TensorType.viewAs(other: TensorType): TensorType
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public fun TensorType.eq(other: TensorType, delta: T): Boolean
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//https://pytorch.org/docs/stable/generated/torch.matmul.html
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public infix fun TensorType.dot(other: TensorType): TensorType
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@ -2,7 +2,7 @@ package space.kscience.kmath.tensors
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// https://proofwiki.org/wiki/Definition:Division_Algebra
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public interface TensorPartialDivisionAlgebra<T, TensorType : TensorStructure<T>> :
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TensorAlgebra<T, TensorType> {
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TensorAlgebra<T, TensorType> {
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public operator fun TensorType.div(value: T): TensorType
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public operator fun TensorType.div(other: TensorType): TensorType
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public operator fun TensorType.divAssign(value: T)
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@ -27,27 +27,27 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, Dou
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return DoubleTensor(newShape, this.buffer.array(), newStart)
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}
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override fun full(value: Double, shape: IntArray): DoubleTensor {
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public fun full(value: Double, shape: IntArray): DoubleTensor {
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checkEmptyShape(shape)
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val buffer = DoubleArray(shape.reduce(Int::times)) { value }
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return DoubleTensor(shape, buffer)
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}
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override fun DoubleTensor.fullLike(value: Double): DoubleTensor {
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public fun DoubleTensor.fullLike(value: Double): DoubleTensor {
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val shape = this.shape
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val buffer = DoubleArray(this.linearStructure.size) { value }
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return DoubleTensor(shape, buffer)
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}
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override fun zeros(shape: IntArray): DoubleTensor = full(0.0, shape)
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public fun zeros(shape: IntArray): DoubleTensor = full(0.0, shape)
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override fun DoubleTensor.zeroesLike(): DoubleTensor = this.fullLike(0.0)
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public fun DoubleTensor.zeroesLike(): DoubleTensor = this.fullLike(0.0)
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override fun ones(shape: IntArray): DoubleTensor = full(1.0, shape)
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public fun ones(shape: IntArray): DoubleTensor = full(1.0, shape)
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override fun DoubleTensor.onesLike(): DoubleTensor = this.fullLike(1.0)
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public fun DoubleTensor.onesLike(): DoubleTensor = this.fullLike(1.0)
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override fun eye(n: Int): DoubleTensor {
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public fun eye(n: Int): DoubleTensor {
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val shape = intArrayOf(n, n)
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val buffer = DoubleArray(n * n) { 0.0 }
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val res = DoubleTensor(shape, buffer)
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@ -57,7 +57,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, Dou
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return res
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}
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override fun DoubleTensor.copy(): DoubleTensor {
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public fun DoubleTensor.copy(): DoubleTensor {
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return DoubleTensor(this.shape, this.buffer.array().copyOf(), this.bufferStart)
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}
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@ -299,7 +299,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, Dou
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return this.contentEquals(other) { x, y -> abs(x - y) < delta }
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}
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override fun DoubleTensor.eq(other: DoubleTensor, delta: Double): Boolean {
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public fun DoubleTensor.eq(other: DoubleTensor, delta: Double): Boolean {
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return this.eq(other) { x, y -> abs(x - y) < delta }
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}
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@ -1,7 +1,8 @@
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package space.kscience.kmath.tensors.core
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import space.kscience.kmath.structures.*
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import kotlin.random.Random
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import kotlin.math.*
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/**
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* Returns a reference to [IntArray] containing all of the elements of this [Buffer].
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@ -34,3 +35,8 @@ internal fun Buffer<Double>.array(): DoubleArray = when (this) {
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is DoubleBuffer -> array
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else -> throw RuntimeException("Failed to cast Buffer to DoubleArray")
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}
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internal inline fun getRandomNormals(n: Int, seed: Long): DoubleArray {
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val u = Random(seed)
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return (0 until n).map { sqrt(-2.0 * u.nextDouble()) * cos(2.0 * PI * u.nextDouble()) }.toDoubleArray()
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}
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