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KMP library for tensors #300

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grinisrit merged 215 commits from feature/tensor-algebra into dev 2021-05-08 09:48:04 +03:00
Conversation 1 Commits 215 Files Changed 40 +103 -109
11 changed files with 103 additions and 109 deletions
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25
kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/BufferedTensor.kt
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@ -8,7 +8,7 @@ import space.kscience.kmath.tensors.core.algebras.TensorLinearStructure
public open class BufferedTensor<T>(
override val shape: IntArray,
internal val buffer: MutableBuffer<T>,
internal val mutableBuffer: MutableBuffer<T>,
internal val bufferStart: Int
) : TensorStructure<T> {
public val linearStructure: TensorLinearStructure
@ -17,10 +17,10 @@ public open class BufferedTensor<T>(
public val numElements: Int
get() = linearStructure.size
override fun get(index: IntArray): T = buffer[bufferStart + linearStructure.offset(index)]
override fun get(index: IntArray): T = mutableBuffer[bufferStart + linearStructure.offset(index)]
override fun set(index: IntArray, value: T) {
buffer[bufferStart + linearStructure.offset(index)] = value
mutableBuffer[bufferStart + linearStructure.offset(index)] = value
}
override fun elements(): Sequence<Pair<IntArray, T>> = linearStructure.indices().map {
@ -37,33 +37,28 @@ public class IntTensor internal constructor(
shape: IntArray,
buffer: IntArray,
offset: Int = 0
) : BufferedTensor<Int>(shape, IntBuffer(buffer), offset) {
internal constructor(bufferedTensor: BufferedTensor<Int>) :
this(bufferedTensor.shape, bufferedTensor.buffer.array(), bufferedTensor.bufferStart)
}
) : BufferedTensor<Int>(shape, IntBuffer(buffer), offset)
public class DoubleTensor internal constructor(
shape: IntArray,
buffer: DoubleArray,
offset: Int = 0
) : BufferedTensor<Double>(shape, DoubleBuffer(buffer), offset) {
internal constructor(bufferedTensor: BufferedTensor<Double>) :
this(bufferedTensor.shape, bufferedTensor.buffer.array(), bufferedTensor.bufferStart)
override fun toString(): String = toPrettyString()
}
internal inline fun BufferedTensor<Int>.asTensor(): IntTensor = IntTensor(this)
internal inline fun BufferedTensor<Double>.asTensor(): DoubleTensor = DoubleTensor(this)
internal fun BufferedTensor<Int>.asTensor(): IntTensor =
IntTensor(this.shape, this.mutableBuffer.array(), this.bufferStart)
internal fun BufferedTensor<Double>.asTensor(): DoubleTensor =
DoubleTensor(this.shape, this.mutableBuffer.array(), this.bufferStart)
internal inline fun <T> TensorStructure<T>.copyToBufferedTensor(): BufferedTensor<T> =
internal fun <T> TensorStructure<T>.copyToBufferedTensor(): BufferedTensor<T> =
BufferedTensor(
this.shape,
TensorLinearStructure(this.shape).indices().map(this::get).toMutableList().asMutableBuffer(), 0
)
internal inline fun <T> TensorStructure<T>.toBufferedTensor(): BufferedTensor<T> = when (this) {
internal fun <T> TensorStructure<T>.toBufferedTensor(): BufferedTensor<T> = when (this) {
is BufferedTensor<T> -> this
is MutableBufferND<T> -> if (this.strides.strides.toIntArray() contentEquals TensorLinearStructure(this.shape).strides)
BufferedTensor(this.shape, this.mutableBuffer, 0) else this.copyToBufferedTensor()

28
kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/BroadcastDoubleTensorAlgebra.kt
View File

@ -21,7 +21,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
val newThis = broadcast[0]
val newOther = broadcast[1]
val resBuffer = DoubleArray(newThis.linearStructure.size) { i ->
newThis.buffer.array()[i] + newOther.buffer.array()[i]
newThis.mutableBuffer.array()[i] + newOther.mutableBuffer.array()[i]
}
return DoubleTensor(newThis.shape, resBuffer)
}
@ -29,8 +29,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
override fun TensorStructure<Double>.plusAssign(other: TensorStructure<Double>) {
val newOther = broadcastTo(other.tensor, tensor.shape)
for (i in 0 until tensor.linearStructure.size) {
tensor.buffer.array()[tensor.bufferStart + i] +=
newOther.buffer.array()[tensor.bufferStart + i]
tensor.mutableBuffer.array()[tensor.bufferStart + i] +=
newOther.mutableBuffer.array()[tensor.bufferStart + i]
}
}
@ -39,7 +39,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
val newThis = broadcast[0]
val newOther = broadcast[1]
val resBuffer = DoubleArray(newThis.linearStructure.size) { i ->
newThis.buffer.array()[i] - newOther.buffer.array()[i]
newThis.mutableBuffer.array()[i] - newOther.mutableBuffer.array()[i]
}
return DoubleTensor(newThis.shape, resBuffer)
}
@ -47,8 +47,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
override fun TensorStructure<Double>.minusAssign(other: TensorStructure<Double>) {
val newOther = broadcastTo(other.tensor, tensor.shape)
for (i in 0 until tensor.linearStructure.size) {
tensor.buffer.array()[tensor.bufferStart + i] -=
newOther.buffer.array()[tensor.bufferStart + i]
tensor.mutableBuffer.array()[tensor.bufferStart + i] -=
newOther.mutableBuffer.array()[tensor.bufferStart + i]
}
}
@ -57,8 +57,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
val newThis = broadcast[0]
val newOther = broadcast[1]
val resBuffer = DoubleArray(newThis.linearStructure.size) { i ->
newThis.buffer.array()[newThis.bufferStart + i] *
newOther.buffer.array()[newOther.bufferStart + i]
newThis.mutableBuffer.array()[newThis.bufferStart + i] *
newOther.mutableBuffer.array()[newOther.bufferStart + i]
}
return DoubleTensor(newThis.shape, resBuffer)
}
@ -66,8 +66,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
override fun TensorStructure<Double>.timesAssign(other: TensorStructure<Double>) {
val newOther = broadcastTo(other.tensor, tensor.shape)
for (i in 0 until tensor.linearStructure.size) {
tensor.buffer.array()[tensor.bufferStart + i] *=
newOther.buffer.array()[tensor.bufferStart + i]
tensor.mutableBuffer.array()[tensor.bufferStart + i] *=
newOther.mutableBuffer.array()[tensor.bufferStart + i]
}
}
@ -76,8 +76,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
val newThis = broadcast[0]
val newOther = broadcast[1]
val resBuffer = DoubleArray(newThis.linearStructure.size) { i ->
newThis.buffer.array()[newOther.bufferStart + i] /
newOther.buffer.array()[newOther.bufferStart + i]
newThis.mutableBuffer.array()[newOther.bufferStart + i] /
newOther.mutableBuffer.array()[newOther.bufferStart + i]
}
return DoubleTensor(newThis.shape, resBuffer)
}
@ -85,8 +85,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
override fun TensorStructure<Double>.divAssign(other: TensorStructure<Double>) {
val newOther = broadcastTo(other.tensor, tensor.shape)
for (i in 0 until tensor.linearStructure.size) {
tensor.buffer.array()[tensor.bufferStart + i] /=
newOther.buffer.array()[tensor.bufferStart + i]
tensor.mutableBuffer.array()[tensor.bufferStart + i] /=
newOther.mutableBuffer.array()[tensor.bufferStart + i]
}
}
}

2
kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleLinearOpsTensorAlgebra.kt
View File

@ -106,7 +106,7 @@ public object DoubleLinearOpsTensorAlgebra :
val matrixSize = matrix.shape.reduce { acc, i -> acc * i }
val curMatrix = DoubleTensor(
matrix.shape,
matrix.buffer.array().slice(matrix.bufferStart until matrix.bufferStart + matrixSize).toDoubleArray()
matrix.mutableBuffer.array().slice(matrix.bufferStart until matrix.bufferStart + matrixSize).toDoubleArray()
)
svdHelper(curMatrix, USV, m, n, epsilon)
}

68
kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/DoubleTensorAlgebra.kt
View File

@ -29,7 +29,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
check(tensor.shape contentEquals intArrayOf(1)) {
"Inconsistent value for tensor of shape ${shape.toList()}"
}
return tensor.buffer.array()[tensor.bufferStart]
return tensor.mutableBuffer.array()[tensor.bufferStart]
}
public fun fromArray(shape: IntArray, buffer: DoubleArray): DoubleTensor {
@ -43,7 +43,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
val lastShape = tensor.shape.drop(1).toIntArray()
val newShape = if (lastShape.isNotEmpty()) lastShape else intArrayOf(1)
val newStart = newShape.reduce(Int::times) * i + tensor.bufferStart
return DoubleTensor(newShape, tensor.buffer.array(), newStart)
return DoubleTensor(newShape, tensor.mutableBuffer.array(), newStart)
}
public fun full(value: Double, shape: IntArray): DoubleTensor {
@ -77,12 +77,12 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
}
public fun TensorStructure<Double>.copy(): DoubleTensor {
return DoubleTensor(tensor.shape, tensor.buffer.array().copyOf(), tensor.bufferStart)
return DoubleTensor(tensor.shape, tensor.mutableBuffer.array().copyOf(), tensor.bufferStart)
}
override fun Double.plus(other: TensorStructure<Double>): DoubleTensor {
val resBuffer = DoubleArray(other.tensor.numElements) { i ->
other.tensor.buffer.array()[other.tensor.bufferStart + i] + this
other.tensor.mutableBuffer.array()[other.tensor.bufferStart + i] + this
}
return DoubleTensor(other.shape, resBuffer)
}
@ -92,35 +92,35 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
override fun TensorStructure<Double>.plus(other: TensorStructure<Double>): DoubleTensor {
checkShapesCompatible(tensor, other.tensor)
val resBuffer = DoubleArray(tensor.numElements) { i ->
tensor.buffer.array()[i] + other.tensor.buffer.array()[i]
tensor.mutableBuffer.array()[i] + other.tensor.mutableBuffer.array()[i]
}
return DoubleTensor(tensor.shape, resBuffer)
}
override fun TensorStructure<Double>.plusAssign(value: Double) {
for (i in 0 until tensor.numElements) {
tensor.buffer.array()[tensor.bufferStart + i] += value
tensor.mutableBuffer.array()[tensor.bufferStart + i] += value
}
}
override fun TensorStructure<Double>.plusAssign(other: TensorStructure<Double>) {
checkShapesCompatible(tensor, other.tensor)
for (i in 0 until tensor.numElements) {
tensor.buffer.array()[tensor.bufferStart + i] +=
other.tensor.buffer.array()[tensor.bufferStart + i]
tensor.mutableBuffer.array()[tensor.bufferStart + i] +=
other.tensor.mutableBuffer.array()[tensor.bufferStart + i]
}
}
override fun Double.minus(other: TensorStructure<Double>): DoubleTensor {
val resBuffer = DoubleArray(other.tensor.numElements) { i ->
this - other.tensor.buffer.array()[other.tensor.bufferStart + i]
this - other.tensor.mutableBuffer.array()[other.tensor.bufferStart + i]
}
return DoubleTensor(other.shape, resBuffer)
}
override fun TensorStructure<Double>.minus(value: Double): DoubleTensor {
val resBuffer = DoubleArray(tensor.numElements) { i ->
tensor.buffer.array()[tensor.bufferStart + i] - value
tensor.mutableBuffer.array()[tensor.bufferStart + i] - value
}
return DoubleTensor(tensor.shape, resBuffer)
}
@ -128,28 +128,28 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
override fun TensorStructure<Double>.minus(other: TensorStructure<Double>): DoubleTensor {
checkShapesCompatible(tensor, other)
val resBuffer = DoubleArray(tensor.numElements) { i ->
tensor.buffer.array()[i] - other.tensor.buffer.array()[i]
tensor.mutableBuffer.array()[i] - other.tensor.mutableBuffer.array()[i]
}
return DoubleTensor(tensor.shape, resBuffer)
}
override fun TensorStructure<Double>.minusAssign(value: Double) {
for (i in 0 until tensor.numElements) {
tensor.buffer.array()[tensor.bufferStart + i] -= value
tensor.mutableBuffer.array()[tensor.bufferStart + i] -= value
}
}
override fun TensorStructure<Double>.minusAssign(other: TensorStructure<Double>) {
checkShapesCompatible(tensor, other)
for (i in 0 until tensor.numElements) {
tensor.buffer.array()[tensor.bufferStart + i] -=
other.tensor.buffer.array()[tensor.bufferStart + i]
tensor.mutableBuffer.array()[tensor.bufferStart + i] -=
other.tensor.mutableBuffer.array()[tensor.bufferStart + i]
}
}
override fun Double.times(other: TensorStructure<Double>): DoubleTensor {
val resBuffer = DoubleArray(other.tensor.numElements) { i ->
other.tensor.buffer.array()[other.tensor.bufferStart + i] * this
other.tensor.mutableBuffer.array()[other.tensor.bufferStart + i] * this
}
return DoubleTensor(other.shape, resBuffer)
}
@ -159,36 +159,36 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
override fun TensorStructure<Double>.times(other: TensorStructure<Double>): DoubleTensor {
checkShapesCompatible(tensor, other)
val resBuffer = DoubleArray(tensor.numElements) { i ->
tensor.buffer.array()[tensor.bufferStart + i] *
other.tensor.buffer.array()[other.tensor.bufferStart + i]
tensor.mutableBuffer.array()[tensor.bufferStart + i] *
other.tensor.mutableBuffer.array()[other.tensor.bufferStart + i]
}
return DoubleTensor(tensor.shape, resBuffer)
}
override fun TensorStructure<Double>.timesAssign(value: Double) {
for (i in 0 until tensor.numElements) {
tensor.buffer.array()[tensor.bufferStart + i] *= value
tensor.mutableBuffer.array()[tensor.bufferStart + i] *= value
}
}
override fun TensorStructure<Double>.timesAssign(other: TensorStructure<Double>) {
checkShapesCompatible(tensor, other)
for (i in 0 until tensor.numElements) {
tensor.buffer.array()[tensor.bufferStart + i] *=
other.tensor.buffer.array()[tensor.bufferStart + i]
tensor.mutableBuffer.array()[tensor.bufferStart + i] *=
other.tensor.mutableBuffer.array()[tensor.bufferStart + i]
}
}
override fun Double.div(other: TensorStructure<Double>): DoubleTensor {
val resBuffer = DoubleArray(other.tensor.numElements) { i ->
this / other.tensor.buffer.array()[other.tensor.bufferStart + i]
this / other.tensor.mutableBuffer.array()[other.tensor.bufferStart + i]
}
return DoubleTensor(other.shape, resBuffer)
}
override fun TensorStructure<Double>.div(value: Double): DoubleTensor {
val resBuffer = DoubleArray(tensor.numElements) { i ->
tensor.buffer.array()[tensor.bufferStart + i] / value
tensor.mutableBuffer.array()[tensor.bufferStart + i] / value
}
return DoubleTensor(shape, resBuffer)
}
@ -196,29 +196,29 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
override fun TensorStructure<Double>.div(other: TensorStructure<Double>): DoubleTensor {
checkShapesCompatible(tensor, other)
val resBuffer = DoubleArray(tensor.numElements) { i ->
tensor.buffer.array()[other.tensor.bufferStart + i] /
other.tensor.buffer.array()[other.tensor.bufferStart + i]
tensor.mutableBuffer.array()[other.tensor.bufferStart + i] /
other.tensor.mutableBuffer.array()[other.tensor.bufferStart + i]
}
return DoubleTensor(tensor.shape, resBuffer)
}
override fun TensorStructure<Double>.divAssign(value: Double) {
for (i in 0 until tensor.numElements) {
tensor.buffer.array()[tensor.bufferStart + i] /= value
tensor.mutableBuffer.array()[tensor.bufferStart + i] /= value
}
}
override fun TensorStructure<Double>.divAssign(other: TensorStructure<Double>) {
checkShapesCompatible(tensor, other)
for (i in 0 until tensor.numElements) {
tensor.buffer.array()[tensor.bufferStart + i] /=
other.tensor.buffer.array()[tensor.bufferStart + i]
tensor.mutableBuffer.array()[tensor.bufferStart + i] /=
other.tensor.mutableBuffer.array()[tensor.bufferStart + i]
}
}
override fun TensorStructure<Double>.unaryMinus(): DoubleTensor {
val resBuffer = DoubleArray(tensor.numElements) { i ->
tensor.buffer.array()[tensor.bufferStart + i].unaryMinus()
tensor.mutableBuffer.array()[tensor.bufferStart + i].unaryMinus()
}
return DoubleTensor(tensor.shape, resBuffer)
}
@ -241,8 +241,8 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
newMultiIndex[ii] = newMultiIndex[jj].also { newMultiIndex[jj] = newMultiIndex[ii] }
val linearIndex = resTensor.linearStructure.offset(newMultiIndex)
resTensor.buffer.array()[linearIndex] =
tensor.buffer.array()[tensor.bufferStart + offset]
resTensor.mutableBuffer.array()[linearIndex] =
tensor.mutableBuffer.array()[tensor.bufferStart + offset]
}
return resTensor
}
@ -250,7 +250,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
override fun TensorStructure<Double>.view(shape: IntArray): DoubleTensor {
checkView(tensor, shape)
return DoubleTensor(shape, tensor.buffer.array(), tensor.bufferStart)
return DoubleTensor(shape, tensor.mutableBuffer.array(), tensor.bufferStart)
}
override fun TensorStructure<Double>.viewAs(other: TensorStructure<Double>): DoubleTensor {
@ -259,7 +259,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
override infix fun TensorStructure<Double>.dot(other: TensorStructure<Double>): DoubleTensor {
if (tensor.shape.size == 1 && other.shape.size == 1) {
return DoubleTensor(intArrayOf(1), doubleArrayOf(tensor.times(other).tensor.buffer.array().sum()))
return DoubleTensor(intArrayOf(1), doubleArrayOf(tensor.times(other).tensor.mutableBuffer.array().sum()))
}
var newThis = tensor.copy()
@ -361,7 +361,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
public fun TensorStructure<Double>.map(transform: (Double) -> Double): DoubleTensor {
return DoubleTensor(
tensor.shape,
tensor.buffer.array().map { transform(it) }.toDoubleArray(),
tensor.mutableBuffer.array().map { transform(it) }.toDoubleArray(),
tensor.bufferStart
)
}
@ -382,7 +382,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double> {
return false
}
for (i in 0 until n) {
if (!eqFunction(tensor.buffer[tensor.bufferStart + i], other.tensor.buffer[other.tensor.bufferStart + i])) {
if (!eqFunction(tensor.mutableBuffer[tensor.bufferStart + i], other.tensor.mutableBuffer[other.tensor.bufferStart + i])) {
return false
}
}

10
kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/broadcastUtils.kt
View File

@ -18,8 +18,8 @@ internal inline fun multiIndexBroadCasting(tensor: DoubleTensor, resTensor: Doub
}
val curLinearIndex = tensor.linearStructure.offset(curMultiIndex)
resTensor.buffer.array()[linearIndex] =
tensor.buffer.array()[tensor.bufferStart + curLinearIndex]
resTensor.mutableBuffer.array()[linearIndex] =
tensor.mutableBuffer.array()[tensor.bufferStart + curLinearIndex]
}
}
@ -113,7 +113,7 @@ internal inline fun broadcastOuterTensors(vararg tensors: DoubleTensor): List<Do
var curMultiIndex = tensor.shape.sliceArray(0..tensor.shape.size - 3).copyOf()
curMultiIndex = IntArray(totalMultiIndex.size - curMultiIndex.size) { 1 } + curMultiIndex
val newTensor = DoubleTensor(curMultiIndex + matrixShape, tensor.buffer.array())
val newTensor = DoubleTensor(curMultiIndex + matrixShape, tensor.mutableBuffer.array())
for (i in curMultiIndex.indices) {
if (curMultiIndex[i] != 1) {
@ -133,8 +133,8 @@ internal inline fun broadcastOuterTensors(vararg tensors: DoubleTensor): List<Do
matrix.linearStructure.index(i)
)
resTensor.buffer.array()[resTensor.bufferStart + newLinearIndex] =
newTensor.buffer.array()[newTensor.bufferStart + curLinearIndex]
resTensor.mutableBuffer.array()[resTensor.bufferStart + newLinearIndex] =
newTensor.mutableBuffer.array()[newTensor.bufferStart + curLinearIndex]
}
}
res += resTensor

14
kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/linUtils.kt
View File

@ -18,7 +18,7 @@ internal inline fun <T> BufferedTensor<T>.vectorSequence(): Sequence<BufferedTen
val vectorOffset = shape[n - 1]
val vectorShape = intArrayOf(shape.last())
for (offset in 0 until numElements step vectorOffset) {
val vector = BufferedTensor(vectorShape, buffer, offset)
val vector = BufferedTensor(vectorShape, mutableBuffer, offset)
yield(vector)
}
}
@ -29,7 +29,7 @@ internal inline fun <T> BufferedTensor<T>.matrixSequence(): Sequence<BufferedTen
val matrixOffset = shape[n - 1] * shape[n - 2]
val matrixShape = intArrayOf(shape[n - 2], shape[n - 1])
for (offset in 0 until numElements step matrixOffset) {
val matrix = BufferedTensor(matrixShape, buffer, offset)
val matrix = BufferedTensor(matrixShape, mutableBuffer, offset)
yield(matrix)
}
}
@ -322,16 +322,16 @@ internal inline fun DoubleLinearOpsTensorAlgebra.svdHelper(
}
val s = res.map { it.first }.toDoubleArray()
val uBuffer = res.map { it.second }.flatMap { it.buffer.array().toList() }.toDoubleArray()
val vBuffer = res.map { it.third }.flatMap { it.buffer.array().toList() }.toDoubleArray()
val uBuffer = res.map { it.second }.flatMap { it.mutableBuffer.array().toList() }.toDoubleArray()
val vBuffer = res.map { it.third }.flatMap { it.mutableBuffer.array().toList() }.toDoubleArray()
for (i in uBuffer.indices) {
matrixU.buffer.array()[matrixU.bufferStart + i] = uBuffer[i]
matrixU.mutableBuffer.array()[matrixU.bufferStart + i] = uBuffer[i]
}
for (i in s.indices) {
matrixS.buffer.array()[matrixS.bufferStart + i] = s[i]
matrixS.mutableBuffer.array()[matrixS.bufferStart + i] = s[i]
}
for (i in vBuffer.indices) {
matrixV.buffer.array()[matrixV.bufferStart + i] = vBuffer[i]
matrixV.mutableBuffer.array()[matrixV.bufferStart + i] = vBuffer[i]
}
}

20
kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestBroadcasting.kt
View File

@ -30,7 +30,7 @@ internal class TestBroadcasting {
val res = broadcastTo(tensor2, tensor1.shape)
assertTrue(res.shape contentEquals intArrayOf(2, 3))
assertTrue(res.buffer.array() contentEquals doubleArrayOf(10.0, 20.0, 30.0, 10.0, 20.0, 30.0))
assertTrue(res.mutableBuffer.array() contentEquals doubleArrayOf(10.0, 20.0, 30.0, 10.0, 20.0, 30.0))
}
@Test
@ -45,9 +45,9 @@ internal class TestBroadcasting {
assertTrue(res[1].shape contentEquals intArrayOf(1, 2, 3))
assertTrue(res[2].shape contentEquals intArrayOf(1, 2, 3))
assertTrue(res[0].buffer.array() contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
assertTrue(res[1].buffer.array() contentEquals doubleArrayOf(10.0, 20.0, 30.0, 10.0, 20.0, 30.0))
assertTrue(res[2].buffer.array() contentEquals doubleArrayOf(500.0, 500.0, 500.0, 500.0, 500.0, 500.0))
assertTrue(res[0].mutableBuffer.array() contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
assertTrue(res[1].mutableBuffer.array() contentEquals doubleArrayOf(10.0, 20.0, 30.0, 10.0, 20.0, 30.0))
assertTrue(res[2].mutableBuffer.array() contentEquals doubleArrayOf(500.0, 500.0, 500.0, 500.0, 500.0, 500.0))
}
@Test
@ -62,9 +62,9 @@ internal class TestBroadcasting {
assertTrue(res[1].shape contentEquals intArrayOf(1, 1, 3))
assertTrue(res[2].shape contentEquals intArrayOf(1, 1, 1))
assertTrue(res[0].buffer.array() contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
assertTrue(res[1].buffer.array() contentEquals doubleArrayOf(10.0, 20.0, 30.0))
assertTrue(res[2].buffer.array() contentEquals doubleArrayOf(500.0))
assertTrue(res[0].mutableBuffer.array() contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
assertTrue(res[1].mutableBuffer.array() contentEquals doubleArrayOf(10.0, 20.0, 30.0))
assertTrue(res[2].mutableBuffer.array() contentEquals doubleArrayOf(500.0))
}
@Test
@ -91,16 +91,16 @@ internal class TestBroadcasting {
val tensor32 = tensor3 - tensor2
assertTrue(tensor21.shape contentEquals intArrayOf(2, 3))
assertTrue(tensor21.buffer.array() contentEquals doubleArrayOf(9.0, 18.0, 27.0, 6.0, 15.0, 24.0))
assertTrue(tensor21.mutableBuffer.array() contentEquals doubleArrayOf(9.0, 18.0, 27.0, 6.0, 15.0, 24.0))
assertTrue(tensor31.shape contentEquals intArrayOf(1, 2, 3))
assertTrue(
tensor31.buffer.array()
tensor31.mutableBuffer.array()
contentEquals doubleArrayOf(499.0, 498.0, 497.0, 496.0, 495.0, 494.0)
)
assertTrue(tensor32.shape contentEquals intArrayOf(1, 1, 3))
assertTrue(tensor32.buffer.array() contentEquals doubleArrayOf(490.0, 480.0, 470.0))
assertTrue(tensor32.mutableBuffer.array() contentEquals doubleArrayOf(490.0, 480.0, 470.0))
}
}

2
kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleAnalyticTensorAlgebra.kt
View File

@ -30,7 +30,7 @@ internal class TestDoubleAnalyticTensorAlgebra {
fun testExp() = DoubleAnalyticTensorAlgebra.invoke {
tensor.exp().let {
assertTrue { shape contentEquals it.shape }
assertTrue { buffer.fmap(::exp).epsEqual(it.buffer.array())}
assertTrue { buffer.fmap(::exp).epsEqual(it.mutableBuffer.array())}
}
}
}

4
kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleLinearOpsAlgebra.kt
View File

@ -151,8 +151,8 @@ internal class TestDoubleLinearOpsTensorAlgebra {
val res = svd1d(tensor2)
assertTrue(res.shape contentEquals intArrayOf(2))
assertTrue { abs(abs(res.buffer.array()[res.bufferStart]) - 0.386) < 0.01 }
assertTrue { abs(abs(res.buffer.array()[res.bufferStart + 1]) - 0.922) < 0.01 }
assertTrue { abs(abs(res.mutableBuffer.array()[res.bufferStart]) - 0.386) < 0.01 }
assertTrue { abs(abs(res.mutableBuffer.array()[res.bufferStart + 1]) - 0.922) < 0.01 }
}
@Test

5
kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensor.kt
View File

@ -6,7 +6,6 @@ import space.kscience.kmath.nd.as1D
import space.kscience.kmath.nd.as2D
import space.kscience.kmath.operations.invoke
import space.kscience.kmath.structures.DoubleBuffer
import space.kscience.kmath.structures.asMutableBuffer
import space.kscience.kmath.structures.toDoubleArray
import space.kscience.kmath.tensors.core.algebras.DoubleTensorAlgebra
import kotlin.test.Test
@ -27,7 +26,7 @@ internal class TestDoubleTensor {
val tensor = fromArray(intArrayOf(2, 2), doubleArrayOf(3.5, 5.8, 58.4, 2.4))
assertEquals(tensor[intArrayOf(0, 1)], 5.8)
assertTrue(
tensor.elements().map { it.second }.toList().toDoubleArray() contentEquals tensor.buffer.toDoubleArray()
tensor.elements().map { it.second }.toList().toDoubleArray() contentEquals tensor.mutableBuffer.toDoubleArray()
)
}
@ -71,7 +70,7 @@ internal class TestDoubleTensor {
val tensorArrayPublic = ndArray.toTypedTensor() // public API, data copied twice
val sharedTensorArray = tensorArrayPublic.toTypedTensor() // no data copied by matching type
assertTrue(tensorArray.buffer.array() contentEquals sharedTensorArray.buffer.array())
assertTrue(tensorArray.mutableBuffer.array() contentEquals sharedTensorArray.mutableBuffer.array())
tensorArray[intArrayOf(0)] = 55.9
assertEquals(tensorArrayPublic[intArrayOf(0)], 1.0)

34
kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensorAlgebra.kt
View File

@ -13,21 +13,21 @@ internal class TestDoubleTensorAlgebra {
fun doublePlus() = DoubleTensorAlgebra.invoke {
val tensor = fromArray(intArrayOf(2), doubleArrayOf(1.0, 2.0))
val res = 10.0 + tensor
assertTrue(res.buffer.array() contentEquals doubleArrayOf(11.0, 12.0))
assertTrue(res.mutableBuffer.array() contentEquals doubleArrayOf(11.0, 12.0))
}
@Test
fun doubleDiv() = DoubleTensorAlgebra.invoke {
val tensor = fromArray(intArrayOf(2), doubleArrayOf(2.0, 4.0))
val res = 2.0/tensor
assertTrue(res.buffer.array() contentEquals doubleArrayOf(1.0, 0.5))
assertTrue(res.mutableBuffer.array() contentEquals doubleArrayOf(1.0, 0.5))
}
@Test
fun divDouble() = DoubleTensorAlgebra.invoke {
val tensor = fromArray(intArrayOf(2), doubleArrayOf(10.0, 5.0))
val res = tensor / 2.5
assertTrue(res.buffer.array() contentEquals doubleArrayOf(4.0, 2.0))
assertTrue(res.mutableBuffer.array() contentEquals doubleArrayOf(4.0, 2.0))
}
@Test
@ -35,7 +35,7 @@ internal class TestDoubleTensorAlgebra {
val tensor = fromArray(intArrayOf(1), doubleArrayOf(0.0))
val res = tensor.transpose(0, 0)
assertTrue(res.buffer.array() contentEquals doubleArrayOf(0.0))
assertTrue(res.mutableBuffer.array() contentEquals doubleArrayOf(0.0))
assertTrue(res.shape contentEquals intArrayOf(1))
}
@ -44,7 +44,7 @@ internal class TestDoubleTensorAlgebra {
val tensor = fromArray(intArrayOf(3, 2), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
val res = tensor.transpose(1, 0)
assertTrue(res.buffer.array() contentEquals doubleArrayOf(1.0, 3.0, 5.0, 2.0, 4.0, 6.0))
assertTrue(res.mutableBuffer.array() contentEquals doubleArrayOf(1.0, 3.0, 5.0, 2.0, 4.0, 6.0))
assertTrue(res.shape contentEquals intArrayOf(2, 3))
}
@ -59,9 +59,9 @@ internal class TestDoubleTensorAlgebra {
assertTrue(res02.shape contentEquals intArrayOf(3, 2, 1))
assertTrue(res12.shape contentEquals intArrayOf(1, 3, 2))
assertTrue(res01.buffer.array() contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
assertTrue(res02.buffer.array() contentEquals doubleArrayOf(1.0, 4.0, 2.0, 5.0, 3.0, 6.0))
assertTrue(res12.buffer.array() contentEquals doubleArrayOf(1.0, 4.0, 2.0, 5.0, 3.0, 6.0))
assertTrue(res01.mutableBuffer.array() contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
assertTrue(res02.mutableBuffer.array() contentEquals doubleArrayOf(1.0, 4.0, 2.0, 5.0, 3.0, 6.0))
assertTrue(res12.mutableBuffer.array() contentEquals doubleArrayOf(1.0, 4.0, 2.0, 5.0, 3.0, 6.0))
}
@Test
@ -92,8 +92,8 @@ internal class TestDoubleTensorAlgebra {
assignResult += tensorC
assignResult += -39.4
assertTrue(expected.buffer.array() contentEquals result.buffer.array())
assertTrue(expected.buffer.array() contentEquals assignResult.buffer.array())
assertTrue(expected.mutableBuffer.array() contentEquals result.mutableBuffer.array())
assertTrue(expected.mutableBuffer.array() contentEquals assignResult.mutableBuffer.array())
}
@Test
@ -104,19 +104,19 @@ internal class TestDoubleTensorAlgebra {
val tensor3 = fromArray(intArrayOf(1, 1, 3), doubleArrayOf(-1.0, -2.0, -3.0))
val res12 = tensor1.dot(tensor2)
assertTrue(res12.buffer.array() contentEquals doubleArrayOf(140.0, 320.0))
assertTrue(res12.mutableBuffer.array() contentEquals doubleArrayOf(140.0, 320.0))
assertTrue(res12.shape contentEquals intArrayOf(2))
val res32 = tensor3.dot(tensor2)
assertTrue(res32.buffer.array() contentEquals doubleArrayOf(-140.0))
assertTrue(res32.mutableBuffer.array() contentEquals doubleArrayOf(-140.0))
assertTrue(res32.shape contentEquals intArrayOf(1, 1))
val res22 = tensor2.dot(tensor2)
assertTrue(res22.buffer.array() contentEquals doubleArrayOf(1400.0))
assertTrue(res22.mutableBuffer.array() contentEquals doubleArrayOf(1400.0))
assertTrue(res22.shape contentEquals intArrayOf(1))
val res11 = tensor1.dot(tensor11)
assertTrue(res11.buffer.array() contentEquals doubleArrayOf(22.0, 28.0, 49.0, 64.0))
assertTrue(res11.mutableBuffer.array() contentEquals doubleArrayOf(22.0, 28.0, 49.0, 64.0))
assertTrue(res11.shape contentEquals intArrayOf(2, 2))
var tensor4 = fromArray(intArrayOf(10, 3, 4), DoubleArray(10 * 3 * 4) {0.0})
@ -147,17 +147,17 @@ internal class TestDoubleTensorAlgebra {
val diagonal1 = diagonalEmbedding(tensor1, 0, 1, 0)
assertTrue(diagonal1.shape contentEquals intArrayOf(3, 3))
assertTrue(diagonal1.buffer.array() contentEquals
assertTrue(diagonal1.mutableBuffer.array() contentEquals
doubleArrayOf(10.0, 0.0, 0.0, 0.0, 20.0, 0.0, 0.0, 0.0, 30.0))
val diagonal1Offset = diagonalEmbedding(tensor1, 1, 1, 0)
assertTrue(diagonal1Offset.shape contentEquals intArrayOf(4, 4))
assertTrue(diagonal1Offset.buffer.array() contentEquals
assertTrue(diagonal1Offset.mutableBuffer.array() contentEquals
doubleArrayOf(0.0, 0.0, 0.0, 0.0, 10.0, 0.0, 0.0, 0.0, 0.0, 20.0, 0.0, 0.0, 0.0, 0.0, 30.0, 0.0))
val diagonal2 = diagonalEmbedding(tensor2, 1, 0, 2)
assertTrue(diagonal2.shape contentEquals intArrayOf(4, 2, 4))
assertTrue(diagonal2.buffer.array() contentEquals
assertTrue(diagonal2.mutableBuffer.array() contentEquals
doubleArrayOf(
0.0, 1.0, 0.0, 0.0, 0.0, 4.0, 0.0, 0.0,
0.0, 0.0, 2.0, 0.0, 0.0, 0.0, 5.0, 0.0,