Generic definition for NDArray
This commit is contained in:
parent
6c25042f0f
commit
ba63b2e373
@ -1,6 +1,8 @@
|
|||||||
description = "Platform-independent interfaces for kotlin maths"
|
plugins{
|
||||||
|
id "kotlin-platform-common"
|
||||||
|
}
|
||||||
|
|
||||||
apply plugin: 'kotlin-platform-common'
|
description = "Platform-independent interfaces for kotlin maths"
|
||||||
|
|
||||||
repositories {
|
repositories {
|
||||||
mavenCentral()
|
mavenCentral()
|
||||||
@ -12,3 +14,9 @@ dependencies {
|
|||||||
testCompile "org.jetbrains.kotlin:kotlin-test-common:$kotlin_version"
|
testCompile "org.jetbrains.kotlin:kotlin-test-common:$kotlin_version"
|
||||||
}
|
}
|
||||||
|
|
||||||
|
kotlin {
|
||||||
|
experimental {
|
||||||
|
coroutines "enable"
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
@ -0,0 +1,93 @@
|
|||||||
|
package scientifik.kmath.structures
|
||||||
|
|
||||||
|
import scientifik.kmath.operations.Field
|
||||||
|
import kotlin.coroutines.experimental.buildSequence
|
||||||
|
|
||||||
|
|
||||||
|
/**
|
||||||
|
* A generic buffer for both primitives and objects
|
||||||
|
*/
|
||||||
|
interface Buffer<T> {
|
||||||
|
operator fun get(index: Int): T
|
||||||
|
operator fun set(index: Int, value: T)
|
||||||
|
}
|
||||||
|
|
||||||
|
/**
|
||||||
|
* Generic implementation of NDField based on continuous buffer
|
||||||
|
*/
|
||||||
|
abstract class BufferNDField<T>(shape: List<Int>, field: Field<T>) : NDField<T>(shape, field) {
|
||||||
|
|
||||||
|
/**
|
||||||
|
* Strides for memory access
|
||||||
|
*/
|
||||||
|
private val strides: List<Int> by lazy {
|
||||||
|
ArrayList<Int>(shape.size).apply {
|
||||||
|
var current = 1
|
||||||
|
add(1)
|
||||||
|
shape.forEach {
|
||||||
|
current *= it
|
||||||
|
add(current)
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
protected fun offset(index: List<Int>): Int {
|
||||||
|
return index.mapIndexed { i, value ->
|
||||||
|
if (value < 0 || value >= shape[i]) {
|
||||||
|
throw RuntimeException("Index out of shape bounds: ($i,$value)")
|
||||||
|
}
|
||||||
|
value * strides[i]
|
||||||
|
}.sum()
|
||||||
|
}
|
||||||
|
|
||||||
|
protected fun index(offset: Int): List<Int>{
|
||||||
|
return buildSequence {
|
||||||
|
var current = offset
|
||||||
|
var strideIndex = strides.size-2
|
||||||
|
while (strideIndex>=0){
|
||||||
|
yield(current / strides[strideIndex])
|
||||||
|
current %= strides[strideIndex]
|
||||||
|
strideIndex--
|
||||||
|
}
|
||||||
|
}.toList().reversed()
|
||||||
|
}
|
||||||
|
|
||||||
|
private val capacity: Int
|
||||||
|
get() = strides[shape.size]
|
||||||
|
|
||||||
|
|
||||||
|
protected abstract fun createBuffer(capacity: Int, initializer: (Int) -> T): Buffer<T>
|
||||||
|
|
||||||
|
override fun produce(initializer: (List<Int>) -> T): NDArray<T> {
|
||||||
|
val buffer = createBuffer(capacity){initializer(index(it))}
|
||||||
|
return BufferNDArray(this, buffer)
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
class BufferNDArray<T>(override val context: BufferNDField<T>, val data: Buffer<T>) : NDArray<T> {
|
||||||
|
|
||||||
|
override fun get(vararg index: Int): T {
|
||||||
|
return data[context.offset(index.asList())]
|
||||||
|
}
|
||||||
|
|
||||||
|
override fun equals(other: Any?): Boolean {
|
||||||
|
if (this === other) return true
|
||||||
|
if (other !is BufferNDArray<*>) return false
|
||||||
|
|
||||||
|
if (context != other.context) return false
|
||||||
|
if (data != other.data) return false
|
||||||
|
|
||||||
|
return true
|
||||||
|
}
|
||||||
|
|
||||||
|
override fun hashCode(): Int {
|
||||||
|
var result = context.hashCode()
|
||||||
|
result = 31 * result + data.hashCode()
|
||||||
|
return result
|
||||||
|
}
|
||||||
|
|
||||||
|
override val self: NDArray<T> get() = this
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
|
@ -198,15 +198,3 @@ operator fun <T> T.div(arg: NDArray<T>): NDArray<T> = arg.transform { _, value -
|
|||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
/**
|
|
||||||
* Create a platform-specific NDArray of doubles
|
|
||||||
*/
|
|
||||||
expect fun realNDArray(shape: List<Int>, initializer: (List<Int>) -> Double = { 0.0 }): NDArray<Double>
|
|
||||||
|
|
||||||
fun real2DArray(dim1: Int, dim2: Int, initializer: (Int, Int) -> Double = { _, _ -> 0.0 }): NDArray<Double> {
|
|
||||||
return realNDArray(listOf(dim1, dim2)) { initializer(it[0], it[1]) }
|
|
||||||
}
|
|
||||||
|
|
||||||
fun real3DArray(dim1: Int, dim2: Int, dim3: Int, initializer: (Int, Int, Int) -> Double = { _, _, _ -> 0.0 }): NDArray<Double> {
|
|
||||||
return realNDArray(listOf(dim1, dim2, dim3)) { initializer(it[0], it[1], it[2]) }
|
|
||||||
}
|
|
@ -0,0 +1,38 @@
|
|||||||
|
package scientifik.kmath.structures
|
||||||
|
|
||||||
|
import scientifik.kmath.operations.Field
|
||||||
|
|
||||||
|
/**
|
||||||
|
* Create a platform-optimized NDArray of doubles
|
||||||
|
*/
|
||||||
|
expect fun realNDArray(shape: List<Int>, initializer: (List<Int>) -> Double = { 0.0 }): NDArray<Double>
|
||||||
|
|
||||||
|
fun real2DArray(dim1: Int, dim2: Int, initializer: (Int, Int) -> Double = { _, _ -> 0.0 }): NDArray<Double> {
|
||||||
|
return realNDArray(listOf(dim1, dim2)) { initializer(it[0], it[1]) }
|
||||||
|
}
|
||||||
|
|
||||||
|
fun real3DArray(dim1: Int, dim2: Int, dim3: Int, initializer: (Int, Int, Int) -> Double = { _, _, _ -> 0.0 }): NDArray<Double> {
|
||||||
|
return realNDArray(listOf(dim1, dim2, dim3)) { initializer(it[0], it[1], it[2]) }
|
||||||
|
}
|
||||||
|
|
||||||
|
|
||||||
|
class SimpleNDField<T: Any>(field: Field<T>, shape: List<Int>) : BufferNDField<T>(shape, field) {
|
||||||
|
override fun createBuffer(capacity: Int, initializer: (Int) -> T): Buffer<T> {
|
||||||
|
val array = ArrayList<T>(capacity)
|
||||||
|
(0 until capacity).forEach {
|
||||||
|
array.add(initializer(it))
|
||||||
|
}
|
||||||
|
|
||||||
|
return object : Buffer<T> {
|
||||||
|
override fun get(index: Int): T = array[index]
|
||||||
|
|
||||||
|
override fun set(index: Int, value: T) {
|
||||||
|
array[index] = initializer(index)
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
fun <T: Any> simpleNDArray(field: Field<T>, shape: List<Int>, initializer: (List<Int>) -> T): NDArray<T> {
|
||||||
|
return SimpleNDField(field, shape).produce { initializer(it) }
|
||||||
|
}
|
@ -0,0 +1,15 @@
|
|||||||
|
package scientifik.kmath.structures
|
||||||
|
|
||||||
|
import scientifik.kmath.operations.DoubleField
|
||||||
|
import kotlin.test.Test
|
||||||
|
import kotlin.test.assertEquals
|
||||||
|
|
||||||
|
|
||||||
|
class SimpleNDFieldTest{
|
||||||
|
@Test
|
||||||
|
fun testStrides(){
|
||||||
|
val ndArray = simpleNDArray(DoubleField, listOf(10,10)){(it[0]+it[1]).toDouble()}
|
||||||
|
assertEquals(ndArray[5,5], 10.0)
|
||||||
|
}
|
||||||
|
|
||||||
|
}
|
@ -1,4 +1,7 @@
|
|||||||
apply plugin: 'kotlin-platform-jvm'
|
plugins{
|
||||||
|
id "kotlin-platform-jvm"
|
||||||
|
id "me.champeau.gradle.jmh" version "0.4.5"
|
||||||
|
}
|
||||||
|
|
||||||
repositories {
|
repositories {
|
||||||
mavenCentral()
|
mavenCentral()
|
||||||
|
@ -0,0 +1,53 @@
|
|||||||
|
package scietifik.kmath.structures
|
||||||
|
|
||||||
|
import org.openjdk.jmh.annotations.*
|
||||||
|
import java.nio.IntBuffer
|
||||||
|
|
||||||
|
|
||||||
|
@Fork(1)
|
||||||
|
@Warmup(iterations = 2)
|
||||||
|
@Measurement(iterations = 50)
|
||||||
|
@State(Scope.Benchmark)
|
||||||
|
open class ArrayBenchmark {
|
||||||
|
|
||||||
|
lateinit var array: IntArray
|
||||||
|
lateinit var arrayBuffer: IntBuffer
|
||||||
|
lateinit var nativeBuffer: IntBuffer
|
||||||
|
|
||||||
|
@Setup
|
||||||
|
fun setup() {
|
||||||
|
array = IntArray(10000) { it }
|
||||||
|
arrayBuffer = IntBuffer.wrap(array)
|
||||||
|
nativeBuffer = IntBuffer.allocate(10000)
|
||||||
|
for (i in 0 until 10000) {
|
||||||
|
nativeBuffer.put(i,i)
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
@Benchmark
|
||||||
|
fun benchmarkArrayRead() {
|
||||||
|
var res = 0
|
||||||
|
for (i in 1..10000) {
|
||||||
|
res += array[10000 - i]
|
||||||
|
}
|
||||||
|
print(res)
|
||||||
|
}
|
||||||
|
|
||||||
|
@Benchmark
|
||||||
|
fun benchmarkBufferRead() {
|
||||||
|
var res = 0
|
||||||
|
for (i in 1..10000) {
|
||||||
|
res += arrayBuffer.get(10000 - i)
|
||||||
|
}
|
||||||
|
print(res)
|
||||||
|
}
|
||||||
|
|
||||||
|
@Benchmark
|
||||||
|
fun nativeBufferRead() {
|
||||||
|
var res = 0
|
||||||
|
for (i in 1..10000) {
|
||||||
|
res += nativeBuffer.get(10000 - i)
|
||||||
|
}
|
||||||
|
print(res)
|
||||||
|
}
|
||||||
|
}
|
@ -3,78 +3,22 @@ package scientifik.kmath.structures
|
|||||||
import scientifik.kmath.operations.DoubleField
|
import scientifik.kmath.operations.DoubleField
|
||||||
import java.nio.DoubleBuffer
|
import java.nio.DoubleBuffer
|
||||||
|
|
||||||
private class RealNDField(shape: List<Int>) : NDField<Double>(shape, DoubleField) {
|
private class RealNDField(shape: List<Int>) : BufferNDField<Double>(shape, DoubleField) {
|
||||||
|
override fun createBuffer(capacity: Int, initializer: (Int) -> Double): Buffer<Double> {
|
||||||
|
val array = DoubleArray(capacity, initializer)
|
||||||
|
val buffer = DoubleBuffer.wrap(array)
|
||||||
|
return object : Buffer<Double> {
|
||||||
|
override fun get(index: Int): Double = buffer.get(index)
|
||||||
|
|
||||||
/**
|
override fun set(index: Int, value: Double) {
|
||||||
* Strides for memory access
|
buffer.put(index, value)
|
||||||
*/
|
|
||||||
private val strides: List<Int> by lazy {
|
|
||||||
ArrayList<Int>(shape.size).apply {
|
|
||||||
var current = 1
|
|
||||||
add(1)
|
|
||||||
shape.forEach {
|
|
||||||
current *= it
|
|
||||||
add(current)
|
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
fun offset(index: List<Int>): Int {
|
|
||||||
return index.mapIndexed { i, value ->
|
|
||||||
if (value < 0 || value >= shape[i]) {
|
|
||||||
throw RuntimeException("Index out of shape bounds: ($i,$value)")
|
|
||||||
}
|
|
||||||
value * strides[i]
|
|
||||||
}.sum()
|
|
||||||
}
|
|
||||||
|
|
||||||
val capacity: Int
|
|
||||||
get() = strides[shape.size]
|
|
||||||
|
|
||||||
|
|
||||||
override fun produce(initializer: (List<Int>) -> Double): NDArray<Double> {
|
|
||||||
//TODO use sparse arrays for large capacities
|
|
||||||
val buffer = DoubleBuffer.allocate(capacity)
|
|
||||||
//FIXME there could be performance degradation due to iteration procedure. Replace by straight iteration
|
|
||||||
NDArray.iterateIndexes(shape).forEach {
|
|
||||||
buffer.put(offset(it), initializer(it))
|
|
||||||
}
|
|
||||||
return RealNDArray(this, buffer)
|
|
||||||
}
|
|
||||||
|
|
||||||
class RealNDArray(override val context: RealNDField, val data: DoubleBuffer) : NDArray<Double> {
|
|
||||||
|
|
||||||
override fun get(vararg index: Int): Double {
|
|
||||||
return data.get(context.offset(index.asList()))
|
|
||||||
}
|
|
||||||
|
|
||||||
override fun equals(other: Any?): Boolean {
|
|
||||||
if (this === other) return true
|
|
||||||
if (javaClass != other?.javaClass) return false
|
|
||||||
|
|
||||||
other as RealNDArray
|
|
||||||
|
|
||||||
if (context.shape != other.context.shape) return false
|
|
||||||
if (data != other.data) return false
|
|
||||||
|
|
||||||
return true
|
|
||||||
}
|
|
||||||
|
|
||||||
override fun hashCode(): Int {
|
|
||||||
var result = context.shape.hashCode()
|
|
||||||
result = 31 * result + data.hashCode()
|
|
||||||
return result
|
|
||||||
}
|
|
||||||
|
|
||||||
//TODO generate fixed hash code for quick comparison?
|
|
||||||
|
|
||||||
|
|
||||||
override val self: NDArray<Double> get() = this
|
|
||||||
}
|
|
||||||
}
|
}
|
||||||
|
|
||||||
|
|
||||||
actual fun realNDArray(shape: List<Int>, initializer: (List<Int>) -> Double): NDArray<Double> {
|
actual fun realNDArray(shape: List<Int>, initializer: (List<Int>) -> Double): NDArray<Double> {
|
||||||
//TODO cache fields?
|
//TODO create a cache for fields to save time generating strides?
|
||||||
|
|
||||||
return RealNDField(shape).produce { initializer(it) }
|
return RealNDField(shape).produce { initializer(it) }
|
||||||
}
|
}
|
Loading…
Reference in New Issue
Block a user