Drop duplicate test from DorBenchmark

This commit is contained in:
Ivan Kylchik 2022-02-20 02:55:37 +03:00
parent dda6602ed4
commit a621dd7c5b

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@ -15,10 +15,8 @@ import space.kscience.kmath.linear.invoke
import space.kscience.kmath.linear.linearSpace
import space.kscience.kmath.multik.multikAlgebra
import space.kscience.kmath.operations.DoubleField
import space.kscience.kmath.operations.invoke
import space.kscience.kmath.structures.Buffer
import space.kscience.kmath.tensorflow.produceWithTF
import space.kscience.kmath.tensors.core.DoubleTensorAlgebra
import space.kscience.kmath.tensors.core.tensorAlgebra
import kotlin.random.Random
@ -36,9 +34,6 @@ internal class DotBenchmark {
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 cmMatrix2 = CMLinearSpace { matrix2.toCM() }
@ -48,10 +43,10 @@ internal class DotBenchmark {
@Benchmark
fun tfDot(blackhole: Blackhole){
fun tfDot(blackhole: Blackhole) {
blackhole.consume(
DoubleField.produceWithTF {
tensor1 dot tensor2
matrix1 dot matrix1
}
)
}
@ -95,9 +90,4 @@ internal class DotBenchmark {
fun doubleDot(blackhole: Blackhole) = with(DoubleField.linearSpace) {
blackhole.consume(matrix1 dot matrix2)
}
@Benchmark
fun doubleTensorDot(blackhole: Blackhole) = DoubleTensorAlgebra.invoke {
blackhole.consume(tensor1 dot tensor2)
}
}