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KMP library for tensors #300

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grinisrit merged 215 commits from feature/tensor-algebra into dev 2021-05-08 09:48:04 +03:00
Conversation 1 Commits 215 Files Changed 40 +11 -21
5 changed files with 11 additions and 21 deletions
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3
kmath-core/api/kmath-core.api
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@ -792,7 +792,6 @@ public final class space/kscience/kmath/nd/DefaultStrides : space/kscience/kmath
public fun getStrides ()[I public fun getStrides ()[I
public fun hashCode ()I public fun hashCode ()I
public fun index (I)[I public fun index (I)[I
public fun offset ([I)I
} }
public final class space/kscience/kmath/nd/DefaultStrides$Companion { public final class space/kscience/kmath/nd/DefaultStrides$Companion {
@ -934,7 +933,7 @@ public abstract interface class space/kscience/kmath/nd/Strides {
public abstract fun getStrides ()[I public abstract fun getStrides ()[I
public abstract fun index (I)[I public abstract fun index (I)[I
public fun indices ()Lkotlin/sequences/Sequence; public fun indices ()Lkotlin/sequences/Sequence;
public abstract fun offset ([I)I public fun offset ([I)I
} }
public abstract interface class space/kscience/kmath/nd/Structure1D : space/kscience/kmath/nd/StructureND, space/kscience/kmath/structures/Buffer { public abstract interface class space/kscience/kmath/nd/Structure1D : space/kscience/kmath/nd/StructureND, space/kscience/kmath/structures/Buffer {

10
kmath-core/src/commonMain/kotlin/space/kscience/kmath/nd/StructureND.kt
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@ -189,7 +189,10 @@ public interface Strides {
/** /**
* Get linear index from multidimensional index * Get linear index from multidimensional index
*/ */
public fun offset(index: IntArray): Int public fun offset(index: IntArray): Int = index.mapIndexed { i, value ->
if (value < 0 || value >= shape[i]) throw IndexOutOfBoundsException("Index $value out of shape bounds: (0,${this.shape[i]})")
value * strides[i]
}.sum()
/** /**
* Get multidimensional from linear * Get multidimensional from linear
@ -233,11 +236,6 @@ public class DefaultStrides private constructor(override val shape: IntArray) :
}.toList().toIntArray() }.toList().toIntArray()
} }
override fun offset(index: IntArray): Int = index.mapIndexed { i, value ->
if (value < 0 || value >= shape[i]) throw IndexOutOfBoundsException("Index $value out of shape bounds: (0,${this.shape[i]})")
value * strides[i]
}.sum()
override fun index(offset: Int): IntArray { override fun index(offset: Int): IntArray {
val res = IntArray(shape.size) val res = IntArray(shape.size)
var current = offset var current = offset

5
kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/algebras/TensorLinearStructure.kt
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@ -68,8 +68,6 @@ public class TensorLinearStructure(override val shape: IntArray) : Strides
override val strides: IntArray override val strides: IntArray
get() = stridesFromShape(shape) get() = stridesFromShape(shape)
override fun offset(index: IntArray): Int = offsetFromIndex(index, shape, strides)
override fun index(offset: Int): IntArray = override fun index(offset: Int): IntArray =
indexFromOffset(offset, strides, shape.size) indexFromOffset(offset, strides, shape.size)
@ -82,7 +80,4 @@ public class TensorLinearStructure(override val shape: IntArray) : Strides
public val dim: Int public val dim: Int
get() = shape.size get() = shape.size
override fun indices(): Sequence<IntArray> = (0 until linearSize).asSequence().map {
index(it)
}
} }

13
kmath-tensors/src/commonMain/kotlin/space/kscience/kmath/tensors/core/broadcastUtils.kt
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@ -75,14 +75,13 @@ internal fun broadcastTensors(vararg tensors: DoubleTensor): List<DoubleTensor>
val totalShape = broadcastShapes(*(tensors.map { it.shape }).toTypedArray()) val totalShape = broadcastShapes(*(tensors.map { it.shape }).toTypedArray())
val n = totalShape.reduce { acc, i -> acc * i } val n = totalShape.reduce { acc, i -> acc * i }
val res = ArrayList<DoubleTensor>(0) return buildList {
for (tensor in tensors) { for (tensor in tensors) {
val resTensor = DoubleTensor(totalShape, DoubleArray(n)) val resTensor = DoubleTensor(totalShape, DoubleArray(n))
multiIndexBroadCasting(tensor, resTensor, n) multiIndexBroadCasting(tensor, resTensor, n)
res.add(resTensor) add(resTensor)
}
} }
return res
} }
internal fun broadcastOuterTensors(vararg tensors: DoubleTensor): List<DoubleTensor> { internal fun broadcastOuterTensors(vararg tensors: DoubleTensor): List<DoubleTensor> {

1
kmath-tensors/src/commonTest/kotlin/space/kscience/kmath/tensors/core/TestDoubleTensorAlgebra.kt
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@ -170,7 +170,6 @@ internal class TestDoubleTensorAlgebra {
val tensor1 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0)) val tensor1 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
val tensor2 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0)) val tensor2 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
val tensor3 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 5.0)) val tensor3 = fromArray(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 5.0))
val tensor4 = fromArray(intArrayOf(6, 1), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
assertTrue(tensor1 eq tensor1) assertTrue(tensor1 eq tensor1)
assertTrue(tensor1 eq tensor2) assertTrue(tensor1 eq tensor2)