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altavir/diff #494

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altavir merged 71 commits from altavir/diff into commandertvis/diff 2022-07-16 09:58:44 +03:00
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benchmarks/src/jvmMain/kotlin/space/kscience/kmath/benchmarks/DotBenchmark.kt
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@ -15,10 +15,8 @@ import space.kscience.kmath.linear.invoke
import space.kscience.kmath.linear.linearSpace import space.kscience.kmath.linear.linearSpace
import space.kscience.kmath.multik.multikAlgebra import space.kscience.kmath.multik.multikAlgebra
import space.kscience.kmath.operations.DoubleField import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.invoke
import space.kscience.kmath.structures.Buffer import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.tensorflow.produceWithTF import space.kscience.kmath.tensorflow.produceWithTF
import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
import space.kscience.kmath.tensors.core.tensorAlgebra import space.kscience.kmath.tensors.core.tensorAlgebra
import kotlin.random.Random import kotlin.random.Random
@ -36,9 +34,6 @@ internal class DotBenchmark {
random.nextDouble() random.nextDouble()
} }
val tensor1 = DoubleTensorAlgebra.randomNormal(shape = intArrayOf(dim, dim), 12224)
val tensor2 = DoubleTensorAlgebra.randomNormal(shape = intArrayOf(dim, dim), 12225)
val cmMatrix1 = CMLinearSpace { matrix1.toCM() } val cmMatrix1 = CMLinearSpace { matrix1.toCM() }
val cmMatrix2 = CMLinearSpace { matrix2.toCM() } val cmMatrix2 = CMLinearSpace { matrix2.toCM() }
@ -51,7 +46,7 @@ internal class DotBenchmark {
fun tfDot(blackhole: Blackhole) { fun tfDot(blackhole: Blackhole) {
blackhole.consume( blackhole.consume(
DoubleField.produceWithTF { DoubleField.produceWithTF {
tensor1 dot tensor2 matrix1 dot matrix1
} }
) )
} }
@ -95,9 +90,4 @@ internal class DotBenchmark {
fun doubleDot(blackhole: Blackhole) = with(DoubleField.linearSpace) { fun doubleDot(blackhole: Blackhole) = with(DoubleField.linearSpace) {
blackhole.consume(matrix1 dot matrix2) blackhole.consume(matrix1 dot matrix2)
} }
@Benchmark
fun doubleTensorDot(blackhole: Blackhole) = DoubleTensorAlgebra.invoke {
blackhole.consume(tensor1 dot tensor2)
}
} }