forked from kscience/kmath
Add example of new AST API
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@ -19,7 +19,8 @@ repositories {
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sourceSets.register("benchmarks")
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dependencies {
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// implementation(project(":kmath-ast"))
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implementation(project(":kmath-ast"))
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implementation(project(":kmath-ast-kotlingrad"))
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implementation(project(":kmath-core"))
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implementation(project(":kmath-coroutines"))
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implementation(project(":kmath-commons"))
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@ -1,70 +1,80 @@
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package kscience.kmath.ast
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//
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//import kscience.kmath.asm.compile
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//import kscience.kmath.expressions.Expression
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//import kscience.kmath.expressions.expressionInField
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//import kscience.kmath.expressions.invoke
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//import kscience.kmath.operations.Field
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//import kscience.kmath.operations.RealField
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//import kotlin.random.Random
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//import kotlin.system.measureTimeMillis
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//
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//class ExpressionsInterpretersBenchmark {
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// private val algebra: Field<Double> = RealField
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// fun functionalExpression() {
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// val expr = algebra.expressionInField {
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// variable("x") * const(2.0) + const(2.0) / variable("x") - const(16.0)
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// }
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//
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// invokeAndSum(expr)
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// }
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//
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// fun mstExpression() {
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// val expr = algebra.mstInField {
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// symbol("x") * number(2.0) + number(2.0) / symbol("x") - number(16.0)
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// }
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//
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// invokeAndSum(expr)
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// }
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//
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// fun asmExpression() {
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// val expr = algebra.mstInField {
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// symbol("x") * number(2.0) + number(2.0) / symbol("x") - number(16.0)
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// }.compile()
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//
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// invokeAndSum(expr)
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// }
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//
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// private fun invokeAndSum(expr: Expression<Double>) {
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// val random = Random(0)
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// var sum = 0.0
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//
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// repeat(1000000) {
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// sum += expr("x" to random.nextDouble())
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// }
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//
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// println(sum)
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// }
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//}
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//
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//fun main() {
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// val benchmark = ExpressionsInterpretersBenchmark()
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//
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// val fe = measureTimeMillis {
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// benchmark.functionalExpression()
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// }
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//
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// println("fe=$fe")
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//
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// val mst = measureTimeMillis {
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// benchmark.mstExpression()
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// }
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//
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// println("mst=$mst")
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//
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// val asm = measureTimeMillis {
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// benchmark.asmExpression()
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// }
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//
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// println("asm=$asm")
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//}
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import kscience.kmath.asm.compile
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import kscience.kmath.expressions.Expression
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import kscience.kmath.expressions.expressionInField
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import kscience.kmath.expressions.invoke
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import kscience.kmath.operations.Field
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import kscience.kmath.operations.RealField
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import kotlin.random.Random
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import kotlin.system.measureTimeMillis
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internal class ExpressionsInterpretersBenchmark {
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private val algebra: Field<Double> = RealField
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fun functionalExpression() {
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val expr = algebra.expressionInField {
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variable("x") * const(2.0) + const(2.0) / variable("x") - const(16.0)
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}
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invokeAndSum(expr)
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}
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fun mstExpression() {
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val expr = algebra.mstInField {
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symbol("x") * number(2.0) + number(2.0) / symbol("x") - number(16.0)
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}
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invokeAndSum(expr)
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}
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fun asmExpression() {
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val expr = algebra.mstInField {
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symbol("x") * number(2.0) + number(2.0) / symbol("x") - number(16.0)
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}.compile()
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invokeAndSum(expr)
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}
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private fun invokeAndSum(expr: Expression<Double>) {
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val random = Random(0)
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var sum = 0.0
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repeat(1000000) {
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sum += expr("x" to random.nextDouble())
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}
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println(sum)
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}
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}
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/**
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* This benchmark compares basically evaluation of simple function with MstExpression interpreter, ASM backend and
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* core FunctionalExpressions API.
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*
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* The expected rating is:
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*
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* 1. ASM.
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* 2. MST.
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* 3. FE.
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*/
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fun main() {
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val benchmark = ExpressionsInterpretersBenchmark()
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val fe = measureTimeMillis {
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benchmark.functionalExpression()
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}
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println("fe=$fe")
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val mst = measureTimeMillis {
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benchmark.mstExpression()
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}
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println("mst=$mst")
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val asm = measureTimeMillis {
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benchmark.asmExpression()
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}
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println("asm=$asm")
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}
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@ -0,0 +1,22 @@
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package kscience.kmath.ast
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import edu.umontreal.kotlingrad.experimental.DoublePrecision
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import kscience.kmath.asm.compile
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import kscience.kmath.ast.kotlingrad.mst
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import kscience.kmath.ast.kotlingrad.sfun
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import kscience.kmath.ast.kotlingrad.svar
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import kscience.kmath.expressions.invoke
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import kscience.kmath.operations.RealField
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/**
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* In this example, x^2-4*x-44 function is differentiated with Kotlin∇, and the autodiff result is compared with
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* valid derivative.
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*/
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fun main() {
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val proto = DoublePrecision.prototype
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val x by MstAlgebra.symbol("x").svar(proto)
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val quadratic = "x^2-4*x-44".parseMath().sfun(proto)
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val actualDerivative = MstExpression(RealField, quadratic.d(x).mst()).compile()
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val expectedDerivative = MstExpression(RealField, "2*x-4".parseMath()).compile()
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assert(actualDerivative("x" to 123.0) == expectedDerivative("x" to 123.0))
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}
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