diff --git a/examples/build.gradle.kts b/examples/build.gradle.kts index 33018976d..99828c621 100644 --- a/examples/build.gradle.kts +++ b/examples/build.gradle.kts @@ -20,6 +20,20 @@ dependencies { implementation(project(":kmath-viktor")) implementation(project(":kmath-dimensions")) implementation(project(":kmath-ejml")) + implementation(project(":kmath-nd4j")) + implementation("org.deeplearning4j:deeplearning4j-core:1.0.0-beta7") + implementation("org.nd4j:nd4j-native:1.0.0-beta7") + +// uncomment if your system supports AVX2 +// val os = System.getProperty("os.name") +// +// if (System.getProperty("os.arch") in arrayOf("x86_64", "amd64")) when { +// os.startsWith("Windows") -> implementation("org.nd4j:nd4j-native:1.0.0-beta7:windows-x86_64-avx2") +// os == "Linux" -> implementation("org.nd4j:nd4j-native:1.0.0-beta7:linux-x86_64-avx2") +// os == "Mac OS X" -> implementation("org.nd4j:nd4j-native:1.0.0-beta7:macosx-x86_64-avx2") +// } else + implementation("org.nd4j:nd4j-native-platform:1.0.0-beta7") + implementation("org.jetbrains.kotlinx:kotlinx-io:0.2.0-npm-dev-11") implementation("org.jetbrains.kotlinx:kotlinx.benchmark.runtime:0.2.0-dev-20") implementation("org.slf4j:slf4j-simple:1.7.30") @@ -48,4 +62,6 @@ kotlin.sourceSets.all { } } -tasks.withType { kotlinOptions.jvmTarget = "11" } +tasks.withType { + kotlinOptions.jvmTarget = "11" +} diff --git a/examples/src/main/kotlin/kscience/kmath/structures/NDField.kt b/examples/src/main/kotlin/kscience/kmath/structures/NDField.kt index 28bfab779..e53af0dee 100644 --- a/examples/src/main/kotlin/kscience/kmath/structures/NDField.kt +++ b/examples/src/main/kotlin/kscience/kmath/structures/NDField.kt @@ -1,8 +1,10 @@ package kscience.kmath.structures import kotlinx.coroutines.GlobalScope +import kscience.kmath.nd4j.Nd4jArrayField import kscience.kmath.operations.RealField import kscience.kmath.operations.invoke +import org.nd4j.linalg.factory.Nd4j import kotlin.contracts.InvocationKind import kotlin.contracts.contract import kotlin.system.measureTimeMillis @@ -14,6 +16,8 @@ internal inline fun measureAndPrint(title: String, block: () -> Unit) { } fun main() { + // initializing Nd4j + Nd4j.zeros(0) val dim = 1000 val n = 1000 @@ -23,6 +27,8 @@ fun main() { val specializedField = NDField.real(dim, dim) //A generic boxing field. It should be used for objects, not primitives. val genericField = NDField.boxing(RealField, dim, dim) + // Nd4j specialized field. + val nd4jField = Nd4jArrayField.real(dim, dim) measureAndPrint("Automatic field addition") { autoField { @@ -43,6 +49,13 @@ fun main() { } } + measureAndPrint("Nd4j specialized addition") { + nd4jField { + var res = one + repeat(n) { res += 1.0 as Number } + } + } + measureAndPrint("Lazy addition") { val res = specializedField.one.mapAsync(GlobalScope) { var c = 0.0 diff --git a/kmath-nd4j/src/main/kotlin/kscience.kmath.nd4j/Nd4jArrayAlgebra.kt b/kmath-nd4j/src/main/kotlin/kscience.kmath.nd4j/Nd4jArrayAlgebra.kt index 2093a3cb3..a8c874fc3 100644 --- a/kmath-nd4j/src/main/kotlin/kscience.kmath.nd4j/Nd4jArrayAlgebra.kt +++ b/kmath-nd4j/src/main/kotlin/kscience.kmath.nd4j/Nd4jArrayAlgebra.kt @@ -126,6 +126,36 @@ public interface Nd4jArrayRing : NDRing>, Nd4j check(b) return b.ndArray.rsub(this).wrap() } + + public companion object { + private val intNd4jArrayRingCache: ThreadLocal> = + ThreadLocal.withInitial { hashMapOf() } + + private val longNd4jArrayRingCache: ThreadLocal> = + ThreadLocal.withInitial { hashMapOf() } + + /** + * Creates an [NDRing] for [Int] values or pull it from cache if it was created previously. + */ + public fun int(vararg shape: Int): Nd4jArrayRing = + intNd4jArrayRingCache.get().getOrPut(shape) { IntNd4jArrayRing(shape) } + + /** + * Creates an [NDRing] for [Long] values or pull it from cache if it was created previously. + */ + public fun long(vararg shape: Int): Nd4jArrayRing = + longNd4jArrayRingCache.get().getOrPut(shape) { LongNd4jArrayRing(shape) } + + /** + * Creates a most suitable implementation of [NDRing] using reified class. + */ + @Suppress("UNCHECKED_CAST") + public inline fun auto(vararg shape: Int): Nd4jArrayRing> = when { + T::class == Int::class -> int(*shape) as Nd4jArrayRing> + T::class == Long::class -> long(*shape) as Nd4jArrayRing> + else -> throw UnsupportedOperationException("This factory method only supports Int and Long types.") + } + } } /** @@ -145,6 +175,37 @@ public interface Nd4jArrayField : NDField>, Nd check(b) return b.ndArray.rdiv(this).wrap() } + + + public companion object { + private val floatNd4jArrayFieldCache: ThreadLocal> = + ThreadLocal.withInitial { hashMapOf() } + + private val realNd4jArrayFieldCache: ThreadLocal> = + ThreadLocal.withInitial { hashMapOf() } + + /** + * Creates an [NDField] for [Float] values or pull it from cache if it was created previously. + */ + public fun float(vararg shape: Int): Nd4jArrayRing = + floatNd4jArrayFieldCache.get().getOrPut(shape) { FloatNd4jArrayField(shape) } + + /** + * Creates an [NDField] for [Double] values or pull it from cache if it was created previously. + */ + public fun real(vararg shape: Int): Nd4jArrayRing = + realNd4jArrayFieldCache.get().getOrPut(shape) { RealNd4jArrayField(shape) } + + /** + * Creates a most suitable implementation of [NDRing] using reified class. + */ + @Suppress("UNCHECKED_CAST") + public inline fun auto(vararg shape: Int): Nd4jArrayField> = when { + T::class == Float::class -> float(*shape) as Nd4jArrayField> + T::class == Double::class -> real(*shape) as Nd4jArrayField> + else -> throw UnsupportedOperationException("This factory method only supports Float and Double types.") + } + } } /**