Remove ND4j
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656d874a65
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@ -60,13 +60,14 @@ kotlin {
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dependencies {
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implementation(projects.kmathCommons)
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implementation(projects.kmathEjml)
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implementation(projects.kmathNd4j)
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implementation(projects.kmathKotlingrad)
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implementation(projects.kmathViktor)
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implementation(projects.kmathOjalgo)
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implementation(projects.kmath.kmathTensorflow)
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implementation(projects.kmathMultik)
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implementation(libs.tensorflow.core.platform)
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// implementation(projects.kmathNd4j)
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// implementation(libs.nd4j.native.platform)
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// uncomment if your system supports AVX2
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// val os = System.getProperty("os.name")
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@ -15,7 +15,6 @@ import org.jetbrains.kotlinx.multik.ndarray.data.DN
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import org.jetbrains.kotlinx.multik.ndarray.data.DataType
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import space.kscience.kmath.UnsafeKMathAPI
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import space.kscience.kmath.nd.*
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import space.kscience.kmath.nd4j.nd4j
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import space.kscience.kmath.operations.Float64Field
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import space.kscience.kmath.structures.Float64
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import space.kscience.kmath.tensors.core.DoubleTensor
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@ -32,7 +31,6 @@ internal class NDFieldBenchmark {
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private val shape = ShapeND(dim, dim)
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private val specializedField = Float64Field.ndAlgebra
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private val genericField = BufferedFieldOpsND(Float64Field)
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private val nd4jField = Float64Field.nd4j
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private val viktorField = Float64Field.viktorAlgebra
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}
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@ -23,7 +23,6 @@ dependencies {
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implementation(project(":kmath-viktor"))
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implementation(project(":kmath-dimensions"))
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implementation(project(":kmath-ejml"))
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implementation(project(":kmath-nd4j"))
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implementation(project(":kmath-tensors"))
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implementation(project(":kmath-symja"))
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implementation(project(":kmath-for-real"))
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@ -32,9 +31,10 @@ dependencies {
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implementation(libs.multik.default)
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//datetime
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implementation("org.jetbrains.kotlinx:kotlinx-datetime:0.4.0")
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implementation(spclibs.kotlinx.datetime)
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implementation("org.nd4j:nd4j-native:1.0.0-beta7")
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// implementation(project(":kmath-nd4j"))
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// implementation("org.nd4j:nd4j-native:1.0.0-beta7")
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// uncomment if your system supports AVX2
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// val os = System.getProperty("os.name")
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@ -44,7 +44,7 @@ dependencies {
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// os == "Linux" -> implementation("org.nd4j:nd4j-native:1.0.0-beta7:linux-x86_64-avx2")
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// os == "Mac OS X" -> implementation("org.nd4j:nd4j-native:1.0.0-beta7:macosx-x86_64-avx2")
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// } else
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implementation("org.nd4j:nd4j-native-platform:1.0.0-beta7")
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// implementation("org.nd4j:nd4j-native-platform:1.0.0-beta7")
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implementation("org.slf4j:slf4j-simple:1.7.32")
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// plotting
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@ -7,9 +7,7 @@ package space.kscience.kmath.structures
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import kotlinx.coroutines.DelicateCoroutinesApi
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import kotlinx.coroutines.GlobalScope
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import org.nd4j.linalg.factory.Nd4j
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import space.kscience.kmath.nd.*
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import space.kscience.kmath.nd4j.nd4j
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import space.kscience.kmath.operations.Float64Field
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import space.kscience.kmath.operations.invoke
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import space.kscience.kmath.viktor.ViktorFieldND
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@ -26,7 +24,6 @@ internal inline fun measureAndPrint(title: String, block: () -> Unit) {
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@OptIn(DelicateCoroutinesApi::class)
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fun main() {
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// initializing Nd4j
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Nd4j.zeros(0)
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val dim = 1000
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val n = 1000
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val shape = ShapeND(dim, dim)
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@ -36,8 +33,6 @@ fun main() {
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val doubleField = Float64Field.ndAlgebra
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//A generic field. It should be used for objects, not primitives.
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val genericField = BufferedFieldOpsND(Float64Field)
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// Nd4j specialized field.
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val nd4jField = Float64Field.nd4j
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//viktor field
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val viktorField = ViktorFieldND(dim, dim)
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//parallel processing based on Java Streams
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@ -57,13 +52,6 @@ fun main() {
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}
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}
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measureAndPrint("Nd4j specialized addition") {
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nd4jField {
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var res: StructureND<Float64> = one(shape)
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repeat(n) { res += 1.0 }
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}
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}
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measureAndPrint("Viktor addition") {
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viktorField {
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var res: StructureND<Float64> = one
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@ -50,7 +50,7 @@ include(
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":kmath-tensorflow",
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":kmath-optimization",
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":kmath-stat",
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":kmath-nd4j",
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// ":kmath-nd4j",
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":kmath-dimensions",
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":kmath-for-real",
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":kmath-geometry",
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