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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
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3 changed files with 135 additions and 11 deletions
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96
kmath-core/src/commonMain/kotlin/space/kscience/kmath/tensors/RealTensorAlgebra.kt
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@ -2,7 +2,9 @@ package space.kscience.kmath.tensors
import space.kscience.kmath.nd.MutableNDBuffer
import space.kscience.kmath.structures.RealBuffer
import space.kscience.kmath.structures.ValueFlag
import space.kscience.kmath.structures.array
import kotlin.math.max
public class RealTensor(
@ -54,27 +56,85 @@ public class RealTensorAlgebra : TensorPartialDivisionAlgebra<Double, RealTensor
TODO("Not yet implemented")
}
override fun broadcastShapes(vararg shapes: IntArray): IntArray {
var totalDim = 0
for (shape in shapes) {
totalDim = max(totalDim, shape.size)
}
val totalShape = IntArray(totalDim) {0}
for (shape in shapes) {
for (i in shape.indices) {
val curDim = shape[i]
val offset = totalDim - shape.size
totalShape[i + offset] = max(totalShape[i + offset], curDim)
}
}
for (shape in shapes) {
for (i in shape.indices) {
val curDim = shape[i]
val offset = totalDim - shape.size
if (curDim != 1 && totalShape[i + offset] != curDim) {
throw IllegalArgumentException("Shapes are not compatible and cannot be broadcast")
}
}
}
return totalShape
}
override fun broadcastTensors(vararg tensors: RealTensor): List<RealTensor> {
val totalShape = broadcastShapes(*(tensors.map { it.shape }).toTypedArray())
val n = totalShape.reduce{ acc, i -> acc * i }
val res = ArrayList<RealTensor>(0)
for (tensor in tensors) {
val resTensor = RealTensor(totalShape, DoubleArray(n))
for (linearIndex in 0 until n) {
val totalMultiIndex = resTensor.strides.index(linearIndex)
val curMultiIndex = tensor.shape.copyOf()
val offset = totalMultiIndex.size - curMultiIndex.size
for (i in curMultiIndex.indices) {
if (curMultiIndex[i] != 1) {
curMultiIndex[i] = totalMultiIndex[i + offset]
} else {
curMultiIndex[i] = 0
}
}
val curLinearIndex = tensor.strides.offset(curMultiIndex)
resTensor.buffer.array[linearIndex] = tensor.buffer.array[curLinearIndex]
}
res.add(resTensor)
}
return res
}
override fun Double.plus(other: RealTensor): RealTensor {
//todo should be change with broadcasting
val resBuffer = DoubleArray(other.buffer.size) { i ->
other.buffer.array[i] + this
}
return RealTensor(other.shape, resBuffer)
}
//todo should be change with broadcasting
override fun RealTensor.plus(value: Double): RealTensor = value + this
override fun RealTensor.plus(other: RealTensor): RealTensor {
//todo should be change with broadcasting
val resBuffer = DoubleArray(this.buffer.size) { i ->
this.buffer.array[i] + other.buffer.array[i]
val broadcast = broadcastTensors(this, other)
val newThis = broadcast[0]
val newOther = broadcast[1]
val resBuffer = DoubleArray(newThis.buffer.size) { i ->
newThis.buffer.array[i] + newOther.buffer.array[i]
}
return RealTensor(this.shape, resBuffer)
return RealTensor(newThis.shape, resBuffer)
}
override fun RealTensor.plusAssign(value: Double) {
//todo should be change with broadcasting
for (i in this.buffer.array.indices) {
this.buffer.array[i] += value
}
@ -88,19 +148,33 @@ public class RealTensorAlgebra : TensorPartialDivisionAlgebra<Double, RealTensor
}
override fun Double.minus(other: RealTensor): RealTensor {
TODO("Alya")
val resBuffer = DoubleArray(other.buffer.size) { i ->
this - other.buffer.array[i]
}
return RealTensor(other.shape, resBuffer)
}
override fun RealTensor.minus(value: Double): RealTensor {
TODO("Alya")
val resBuffer = DoubleArray(this.buffer.size) { i ->
this.buffer.array[i] - value
}
return RealTensor(this.shape, resBuffer)
}
override fun RealTensor.minus(other: RealTensor): RealTensor {
TODO("Alya")
val broadcast = broadcastTensors(this, other)
val newThis = broadcast[0]
val newOther = broadcast[1]
val resBuffer = DoubleArray(newThis.buffer.size) { i ->
newThis.buffer.array[i] - newOther.buffer.array[i]
}
return RealTensor(newThis.shape, resBuffer)
}
override fun RealTensor.minusAssign(value: Double) {
TODO("Alya")
for (i in this.buffer.array.indices) {
this.buffer.array[i] -= value
}
}
override fun RealTensor.minusAssign(other: RealTensor) {

3
kmath-core/src/commonMain/kotlin/space/kscience/kmath/tensors/TensorAlgebra.kt
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@ -13,6 +13,9 @@ public interface TensorAlgebra<T, TensorType : TensorStructure<T>> {
public fun TensorType.copy(): TensorType
public fun broadcastShapes(vararg shapes: IntArray): IntArray
public fun broadcastTensors(vararg tensors: RealTensor): List<TensorType>
public operator fun T.plus(other: TensorType): TensorType
public operator fun TensorType.plus(value: T): TensorType
public operator fun TensorType.plus(other: TensorType): TensorType

47
kmath-core/src/commonTest/kotlin/space/kscience/kmath/tensors/TestRealTensorAlgebra.kt
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@ -2,6 +2,8 @@ package space.kscience.kmath.tensors
import space.kscience.kmath.structures.array
import kotlin.test.Test
import kotlin.test.assertFails
import kotlin.test.assertFailsWith
import kotlin.test.assertTrue
class TestRealTensorAlgebra {
@ -64,4 +66,49 @@ class TestRealTensorAlgebra {
assertTrue(tensor.buffer.array contentEquals doubleArrayOf(1.0, 4.0, 2.0, 5.0, 3.0, 6.0))
assertTrue(tensor.shape contentEquals intArrayOf(3, 2))
}
@Test
fun broadcastShapes() = RealTensorAlgebra {
assertTrue(this.broadcastShapes(
intArrayOf(2, 3), intArrayOf(1, 3), intArrayOf(1, 1, 1)
) contentEquals intArrayOf(1, 2, 3))
assertTrue(this.broadcastShapes(
intArrayOf(6, 7), intArrayOf(5, 6, 1), intArrayOf(7,), intArrayOf(5, 1, 7)
) contentEquals intArrayOf(5, 6, 7))
}
@Test
fun broadcastTensors() = RealTensorAlgebra {
val tensor1 = RealTensor(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
val tensor2 = RealTensor(intArrayOf(1, 3), doubleArrayOf(10.0, 20.0, 30.0))
val tensor3 = RealTensor(intArrayOf(1, 1, 1), doubleArrayOf(500.0))
val res = this.broadcastTensors(tensor1, tensor2, tensor3)
assertTrue(res[0].shape contentEquals intArrayOf(1, 2, 3))
assertTrue(res[1].shape contentEquals intArrayOf(1, 2, 3))
assertTrue(res[2].shape contentEquals intArrayOf(1, 2, 3))
assertTrue(res[0].buffer.array contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
assertTrue(res[1].buffer.array contentEquals doubleArrayOf(10.0, 20.0, 30.0, 10.0, 20.0, 30.0))
assertTrue(res[2].buffer.array contentEquals doubleArrayOf(500.0, 500.0, 500.0, 500.0, 500.0, 500.0))
}
@Test
fun minusTensor() = RealTensorAlgebra {
val tensor1 = RealTensor(intArrayOf(2, 3), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
val tensor2 = RealTensor(intArrayOf(1, 3), doubleArrayOf(10.0, 20.0, 30.0))
val tensor3 = RealTensor(intArrayOf(1, 1, 1), doubleArrayOf(500.0))
assertTrue((tensor2 - tensor1).shape contentEquals intArrayOf(2, 3))
assertTrue((tensor2 - tensor1).buffer.array contentEquals doubleArrayOf(9.0, 18.0, 27.0, 6.0, 15.0, 24.0))
assertTrue((tensor3 - tensor1).shape contentEquals intArrayOf(1, 2, 3))
assertTrue((tensor3 - tensor1).buffer.array
contentEquals doubleArrayOf(499.0, 498.0, 497.0, 496.0, 495.0, 494.0))
assertTrue((tensor3 - tensor2).shape contentEquals intArrayOf(1, 1, 3))
assertTrue((tensor3 - tensor2).buffer.array contentEquals doubleArrayOf(490.0, 480.0, 470.0))
}
}