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Andrew #220

Merged
AndreiKingsley merged 2 commits from andrew into feature/tensor-algebra 2021-03-10 00:14:02 +03:00
Conversation 0 Commits 2 Files Changed 4 +111 -67
4 changed files with 111 additions and 67 deletions
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137
kmath-core/src/commonMain/kotlin/space/kscience/kmath/tensors/RealTensorAlgebra.kt
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@ -3,6 +3,8 @@ package space.kscience.kmath.tensors
import space.kscience.kmath.nd.MutableNDBuffer
import space.kscience.kmath.structures.RealBuffer
import space.kscience.kmath.structures.array
import kotlin.js.JsName
import kotlin.math.abs
public class RealTensor(
@ -13,46 +15,80 @@ public class RealTensor(
MutableNDBuffer<Double>(
TensorStrides(shape),
RealBuffer(buffer)
) {
/*
* TODO: Andrei remove item()
*/
override fun item(): Double {
check(buffer.size > 0) { "The tensor is empty" }
return buffer[0]
}
}
)
public class RealTensorAlgebra : TensorPartialDivisionAlgebra<Double, RealTensor> {
//rename to item?
override fun RealTensor.value(): Double {
TODO("Andrei")
check(this.dimension == 0) {
// todo change message
"This tensor has shape ${shape.toList()}"
}
return this.buffer.array[0]
}
override fun eye(n: Int): RealTensor {
val shape = intArrayOf(n, n)
val buffer = DoubleArray(n * n) { 0.0 }
val res = RealTensor(shape, buffer)
for (i in 0 until n) {
res[intArrayOf(i, i)] = 1.0
}
return res
}
override fun zeros(shape: IntArray): RealTensor {
TODO("Not yet implemented")
}
override fun zeroesLike(other: RealTensor): RealTensor {
TODO("Not yet implemented")
}
override fun ones(shape: IntArray): RealTensor {
TODO("Not yet implemented")
}
override fun onesLike(shape: IntArray): RealTensor {
TODO("Not yet implemented")
}
override fun RealTensor.copy(): RealTensor {
TODO("Not yet implemented")
}
override fun Double.plus(other: RealTensor): RealTensor {
val n = other.buffer.size
val arr = other.buffer.array
val res = DoubleArray(n)
for (i in 1..n)
res[i - 1] = arr[i - 1] + this
return RealTensor(other.shape, res)
//todo should be change with broadcasting
val resBuffer = DoubleArray(other.buffer.size) { i ->
other.buffer.array[i] + this
}
return RealTensor(other.shape, resBuffer)
}
override fun RealTensor.plus(value: Double): RealTensor {
TODO("Andrei")
}
//todo should be change with broadcasting
override fun RealTensor.plus(value: Double): RealTensor = value + this
override fun RealTensor.plus(other: RealTensor): RealTensor {
TODO("Andrei")
//todo should be change with broadcasting
val resBuffer = DoubleArray(this.buffer.size) { i ->
this.buffer.array[i] + other.buffer.array[i]
}
return RealTensor(this.shape, resBuffer)
}
override fun RealTensor.plusAssign(value: Double) {
TODO("Andrei")
//todo should be change with broadcasting
for (i in this.buffer.array.indices) {
this.buffer.array[i] += value
}
}
override fun RealTensor.plusAssign(other: RealTensor) {
TODO("Andrei")
//todo should be change with broadcasting
for (i in this.buffer.array.indices) {
this.buffer.array[i] += other.buffer.array[i]
}
}
override fun Double.minus(other: RealTensor): RealTensor {
@ -76,27 +112,43 @@ public class RealTensorAlgebra : TensorPartialDivisionAlgebra<Double, RealTensor
}
override fun Double.times(other: RealTensor): RealTensor {
TODO("Andrei")
//todo should be change with broadcasting
val resBuffer = DoubleArray(other.buffer.size) { i ->
other.buffer.array[i] * this
}
return RealTensor(other.shape, resBuffer)
}
override fun RealTensor.times(value: Double): RealTensor {
TODO("Andrei")
}
//todo should be change with broadcasting
override fun RealTensor.times(value: Double): RealTensor = value * this
override fun RealTensor.times(other: RealTensor): RealTensor {
TODO("Andrei")
//todo should be change with broadcasting
val resBuffer = DoubleArray(this.buffer.size) { i ->
this.buffer.array[i] * other.buffer.array[i]
}
return RealTensor(this.shape, resBuffer)
}
override fun RealTensor.timesAssign(value: Double) {
TODO("Andrei")
//todo should be change with broadcasting
for (i in this.buffer.array.indices) {
this.buffer.array[i] *= value
}
}
override fun RealTensor.timesAssign(other: RealTensor) {
TODO("Andrei")
//todo should be change with broadcasting
for (i in this.buffer.array.indices) {
this.buffer.array[i] *= other.buffer.array[i]
}
}
override fun RealTensor.unaryMinus(): RealTensor {
TODO("Andrei")
val resBuffer = DoubleArray(this.buffer.size) { i ->
this.buffer.array[i].unaryMinus()
}
return RealTensor(this.shape, resBuffer)
}
override fun RealTensor.dot(other: RealTensor): RealTensor {
@ -124,11 +176,11 @@ public class RealTensorAlgebra : TensorPartialDivisionAlgebra<Double, RealTensor
}
override fun RealTensor.view(shape: IntArray): RealTensor {
TODO("Andrei")
return RealTensor(shape, this.buffer.array)
}
override fun RealTensor.view_as(other: RealTensor): RealTensor {
TODO("Andrei")
override fun RealTensor.viewAs(other: RealTensor): RealTensor {
return this.view(other.shape)
}
override fun RealTensor.abs(): RealTensor {
@ -147,10 +199,18 @@ public class RealTensorAlgebra : TensorPartialDivisionAlgebra<Double, RealTensor
TODO("Not yet implemented")
}
override fun RealTensor.div(value: Double): RealTensor {
TODO("Not yet implemented")
}
override fun RealTensor.div(other: RealTensor): RealTensor {
TODO("Not yet implemented")
}
override fun RealTensor.divAssign(value: Double) {
TODO("Not yet implemented")
}
override fun RealTensor.divAssign(other: RealTensor) {
TODO("Not yet implemented")
}
@ -172,15 +232,10 @@ public class RealTensorAlgebra : TensorPartialDivisionAlgebra<Double, RealTensor
}
override fun RealTensor.lu(): Pair<RealTensor, RealTensor> {
/**
* Main first task for @AndreiKingsley
* Compare with the implementation of [LupDecomposition]
* and provide a common API
*/
TODO("Not yet implemented")
TODO()
}
override fun lu_unpack(A_LU: RealTensor, pivots: RealTensor): Triple<RealTensor, RealTensor, RealTensor> {
override fun luUnpack(A_LU: RealTensor, pivots: RealTensor): Triple<RealTensor, RealTensor, RealTensor> {
TODO("Not yet implemented")
}

14
kmath-core/src/commonMain/kotlin/space/kscience/kmath/tensors/TensorAlgebra.kt
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@ -5,6 +5,14 @@ public interface TensorAlgebra<T, TensorType : TensorStructure<T>> {
public fun TensorType.value(): T
public fun eye(n: Int): TensorType
public fun zeros(shape: IntArray): TensorType
public fun zeroesLike(other: TensorType): TensorType
public fun ones(shape: IntArray): TensorType
public fun onesLike(shape: IntArray): TensorType
public fun TensorType.copy(): TensorType
public operator fun T.plus(other: TensorType): TensorType
public operator fun TensorType.plus(value: T): TensorType
public operator fun TensorType.plus(other: TensorType): TensorType
@ -42,7 +50,7 @@ public interface TensorAlgebra<T, TensorType : TensorStructure<T>> {
//https://pytorch.org/docs/stable/tensor_view.html
public fun TensorType.view(shape: IntArray): TensorType
public fun TensorType.view_as(other: TensorType): TensorType
public fun TensorType.viewAs(other: TensorType): TensorType
//https://pytorch.org/docs/stable/generated/torch.abs.html
public fun TensorType.abs(): TensorType
@ -57,7 +65,9 @@ public interface TensorAlgebra<T, TensorType : TensorStructure<T>> {
public interface TensorPartialDivisionAlgebra<T, TensorType : TensorStructure<T>> :
TensorAlgebra<T, TensorType> {
public operator fun TensorType.div(value: T): TensorType
public operator fun TensorType.div(other: TensorType): TensorType
public operator fun TensorType.divAssign(value: T)
public operator fun TensorType.divAssign(other: TensorType)
//https://pytorch.org/docs/stable/generated/torch.exp.html
@ -72,7 +82,7 @@ public interface TensorPartialDivisionAlgebra<T, TensorType : TensorStructure<T>
public fun TensorType.lu(): Pair<TensorType, TensorType>
//https://pytorch.org/docs/stable/generated/torch.lu_unpack.html
public fun lu_unpack(A_LU: TensorType, pivots: TensorType): Triple<TensorType, TensorType, TensorType>
public fun luUnpack(A_LU: TensorType, pivots: TensorType): Triple<TensorType, TensorType, TensorType>
//https://pytorch.org/docs/stable/generated/torch.svd.html
public fun TensorType.svd(): Triple<TensorType, TensorType, TensorType>

4
kmath-core/src/commonMain/kotlin/space/kscience/kmath/tensors/TensorStrides.kt
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@ -5,7 +5,7 @@ import space.kscience.kmath.nd.offsetFromIndex
import kotlin.math.max
inline public fun stridesFromShape(shape: IntArray): IntArray {
public inline fun stridesFromShape(shape: IntArray): IntArray {
val nDim = shape.size
val res = IntArray(nDim)
if (nDim == 0)
@ -22,7 +22,7 @@ inline public fun stridesFromShape(shape: IntArray): IntArray {
}
inline public fun indexFromOffset(offset: Int, strides: IntArray, nDim: Int): IntArray {
public inline fun indexFromOffset(offset: Int, strides: IntArray, nDim: Int): IntArray {
val res = IntArray(nDim)
var current = offset
var strideIndex = 0

23
kmath-core/src/commonMain/kotlin/space/kscience/kmath/tensors/TensorStructure.kt
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@ -2,26 +2,5 @@ package space.kscience.kmath.tensors
import space.kscience.kmath.nd.MutableNDStructure
public interface TensorStructure<T> : MutableNDStructure<T> {
public typealias TensorStructure<T> = MutableNDStructure<T>
/*
* TODO: Andrei remove item() and value()
*/
public fun item(): T
// A tensor can have empty shape, in which case it represents just a value
public fun value(): T {
checkIsValue()
return item()
}
}
public inline fun <T> TensorStructure<T>.isValue(): Boolean {
return (dimension == 0)
}
public inline fun <T> TensorStructure<T>.isNotValue(): Boolean = !this.isValue()
public inline fun <T> TensorStructure<T>.checkIsValue(): Unit = check(this.isValue()) {
"This tensor has shape ${shape.toList()}"
}