kmath-core/src/commonMain/kotlin/space/kscience/kmath/tensors/BufferedTensor.kt

@@ -1,32 +1,34 @@
 package space.kscience.kmath.tensors
 
-import space.kscience.kmath.nd.MutableNDBuffer
 import space.kscience.kmath.structures.*
 
 
 public open class BufferedTensor<T>(
     override val shape: IntArray,
-    buffer: MutableBuffer<T>
+    public val buffer: MutableBuffer<T>,
-) :
+    internal val bufferStart: Int
-    TensorStructure<T>,
+) : TensorStructure<T>
-    MutableNDBuffer<T>(
+{
-        TensorStrides(shape),
+    public val strides: TensorStrides
-        buffer
+        get() = TensorStrides(shape)
-    ) {
 
+    override fun get(index: IntArray): T = buffer[bufferStart + strides.offset(index)]
 
-    public operator fun get(i: Int, j: Int): T {
+    override fun set(index: IntArray, value: T) {
-        check(this.dimension == 2) { "Not matrix" }
+        buffer[bufferStart + strides.offset(index)] = value
-        return this[intArrayOf(i, j)]
     }
 
-    public operator fun set(i: Int, j: Int, value: T): Unit {
+    override fun elements(): Sequence<Pair<IntArray, T>> = strides.indices().map {
-        check(this.dimension == 2) { "Not matrix" }
+        it to this[it]
-        this[intArrayOf(i, j)] = value
     }
 
+    override fun equals(other: Any?): Boolean = false
+
+    override fun hashCode(): Int = 0
+
 }
 
+/*
 //todo make generator mb nextMatrixIndex?
 public class InnerMatrix<T>(private val tensor: BufferedTensor<T>){
     private var offset: Int = 0
@@ -75,25 +77,29 @@ public class InnerVector<T>(private val tensor: BufferedTensor<T>){
         offset += step
     }
 }
-
-
 //todo default buffer = arrayOf(0)???
+ */
+
 public class IntTensor(
     shape: IntArray,
-    buffer: IntArray
+    buffer: IntArray,
-) : BufferedTensor<Int>(shape, IntBuffer(buffer))
+    offset: Int = 0
+) : BufferedTensor<Int>(shape, IntBuffer(buffer), offset)
 
 public class LongTensor(
     shape: IntArray,
-    buffer: LongArray
+    buffer: LongArray,
-) : BufferedTensor<Long>(shape, LongBuffer(buffer))
+    offset: Int = 0
+) : BufferedTensor<Long>(shape, LongBuffer(buffer), offset)
 
 public class FloatTensor(
     shape: IntArray,
-    buffer: FloatArray
+    buffer: FloatArray,
-) : BufferedTensor<Float>(shape, FloatBuffer(buffer))
+    offset: Int = 0
+) : BufferedTensor<Float>(shape, FloatBuffer(buffer), offset)
 
 public class DoubleTensor(
     shape: IntArray,
-    buffer: DoubleArray
+    buffer: DoubleArray,
-) : BufferedTensor<Double>(shape, RealBuffer(buffer))
+    offset: Int = 0
+) : BufferedTensor<Double>(shape, RealBuffer(buffer), offset)

kmath-core/src/commonMain/kotlin/space/kscience/kmath/tensors/DoubleLinearOpsTensorAlgebra.kt

@@ -9,6 +9,7 @@ public class DoubleLinearOpsTensorAlgebra :
     }
 
     override fun DoubleTensor.lu(): Pair<DoubleTensor, IntTensor> {
+        /*
         // todo checks
         val luTensor = this.copy()
         val lu = InnerMatrix(luTensor)
@@ -69,11 +70,13 @@ public class DoubleLinearOpsTensorAlgebra :
             pivot.makeStep()
         }
 
-        return Pair(luTensor, pivotsTensor)
+        return Pair(luTensor, pivotsTensor)*/
+
+        TODO("Andrei, first we need to view and get(Int)")
     }
 
     override fun luPivot(lu: DoubleTensor, pivots: IntTensor): Triple<DoubleTensor, DoubleTensor, DoubleTensor> {
-
+        /*
         // todo checks
         val n = lu.shape[0]
         val p = lu.zeroesLike()
@@ -97,7 +100,8 @@ public class DoubleLinearOpsTensorAlgebra :
             }
         }
 
-        return Triple(p, l, u)
+        return Triple(p, l, u)*/
+        TODO("Andrei, first we need implement get(Int)")
     }
 
     override fun DoubleTensor.cholesky(): DoubleTensor {

kmath-core/src/commonMain/kotlin/space/kscience/kmath/tensors/DoubleTensorAlgebra.kt

@@ -7,11 +7,11 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, Dou
         check(this.shape contentEquals intArrayOf(1)) {
             "Inconsistent value for tensor of shape ${shape.toList()}"
         }
-        return this.buffer.unsafeToDoubleArray()[0]
+        return this.buffer.unsafeToDoubleArray()[this.bufferStart]
     }
 
     override fun DoubleTensor.get(i: Int): DoubleTensor {
-        TODO("Not yet implemented")
+        TODO("TOP PRIORITY")
     }
 
     override fun zeros(shape: IntArray): DoubleTensor {
@@ -20,7 +20,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, Dou
 
     override fun DoubleTensor.zeroesLike(): DoubleTensor {
         val shape = this.shape
-        val buffer = DoubleArray(this.buffer.size) { 0.0 }
+        val buffer = DoubleArray(this.strides.linearSize) { 0.0 }
         return DoubleTensor(shape, buffer)
     }
 
@@ -31,6 +31,7 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, Dou
     override fun DoubleTensor.onesLike(): DoubleTensor {
         TODO("Not yet implemented")
     }
+
     override fun eye(n: Int): DoubleTensor {
         val shape = intArrayOf(n, n)
         val buffer = DoubleArray(n * n) { 0.0 }
@@ -42,14 +43,13 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, Dou
     }
 
     override fun DoubleTensor.copy(): DoubleTensor {
-        // should be rework as soon as copy() method for NDBuffer will be available
+        return DoubleTensor(this.shape, this.buffer.unsafeToDoubleArray().copyOf(), this.bufferStart)
-        return DoubleTensor(this.shape, this.buffer.unsafeToDoubleArray().copyOf())
     }
 
 
     override fun Double.plus(other: DoubleTensor): DoubleTensor {
-        val resBuffer = DoubleArray(other.buffer.size) { i ->
+        val resBuffer = DoubleArray(other.strides.linearSize) { i ->
-            other.buffer.unsafeToDoubleArray()[i] + this
+            other.buffer.unsafeToDoubleArray()[other.bufferStart + i] + this
         }
         return DoubleTensor(other.shape, resBuffer)
     }
@@ -60,35 +60,36 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, Dou
         val broadcast = broadcastTensors(this, other)
         val newThis = broadcast[0]
         val newOther = broadcast[1]
-        val resBuffer = DoubleArray(newThis.buffer.size) { i ->
+        val resBuffer = DoubleArray(newThis.strides.linearSize) { i ->
             newThis.buffer.unsafeToDoubleArray()[i] + newOther.buffer.unsafeToDoubleArray()[i]
         }
         return DoubleTensor(newThis.shape, resBuffer)
     }
 
     override fun DoubleTensor.plusAssign(value: Double) {
-        for (i in this.buffer.unsafeToDoubleArray().indices) {
+        for (i in 0 until this.strides.linearSize) {
-            this.buffer.unsafeToDoubleArray()[i] += value
+            this.buffer.unsafeToDoubleArray()[this.bufferStart + i] += value
         }
     }
 
     override fun DoubleTensor.plusAssign(other: DoubleTensor) {
         //todo should be change with broadcasting
-        for (i in this.buffer.unsafeToDoubleArray().indices) {
+        for (i in 0 until this.strides.linearSize) {
-            this.buffer.unsafeToDoubleArray()[i] += other.buffer.unsafeToDoubleArray()[i]
+            this.buffer.unsafeToDoubleArray()[this.bufferStart + i] +=
+                other.buffer.unsafeToDoubleArray()[this.bufferStart + i]
         }
     }
 
     override fun Double.minus(other: DoubleTensor): DoubleTensor {
-        val resBuffer = DoubleArray(other.buffer.size) { i ->
+        val resBuffer = DoubleArray(other.strides.linearSize) { i ->
-            this - other.buffer.unsafeToDoubleArray()[i]
+            this - other.buffer.unsafeToDoubleArray()[other.bufferStart + i]
         }
         return DoubleTensor(other.shape, resBuffer)
     }
 
     override fun DoubleTensor.minus(value: Double): DoubleTensor {
-        val resBuffer = DoubleArray(this.buffer.size) { i ->
+        val resBuffer = DoubleArray(this.strides.linearSize) { i ->
-            this.buffer.unsafeToDoubleArray()[i] - value
+            this.buffer.unsafeToDoubleArray()[this.bufferStart + i] - value
         }
         return DoubleTensor(this.shape, resBuffer)
     }
@@ -97,15 +98,15 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, Dou
         val broadcast = broadcastTensors(this, other)
         val newThis = broadcast[0]
         val newOther = broadcast[1]
-        val resBuffer = DoubleArray(newThis.buffer.size) { i ->
+        val resBuffer = DoubleArray(newThis.strides.linearSize) { i ->
             newThis.buffer.unsafeToDoubleArray()[i] - newOther.buffer.unsafeToDoubleArray()[i]
         }
         return DoubleTensor(newThis.shape, resBuffer)
     }
 
     override fun DoubleTensor.minusAssign(value: Double) {
-        for (i in this.buffer.unsafeToDoubleArray().indices) {
+        for (i in 0 until this.strides.linearSize) {
-            this.buffer.unsafeToDoubleArray()[i] -= value
+            this.buffer.unsafeToDoubleArray()[this.bufferStart + i] -= value
         }
     }
 
@@ -115,8 +116,8 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, Dou
 
     override fun Double.times(other: DoubleTensor): DoubleTensor {
         //todo should be change with broadcasting
-        val resBuffer = DoubleArray(other.buffer.size) { i ->
+        val resBuffer = DoubleArray(other.strides.linearSize) { i ->
-            other.buffer.unsafeToDoubleArray()[i] * this
+            other.buffer.unsafeToDoubleArray()[other.bufferStart + i] * this
         }
         return DoubleTensor(other.shape, resBuffer)
     }
@@ -126,36 +127,38 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, Dou
 
     override fun DoubleTensor.times(other: DoubleTensor): DoubleTensor {
         //todo should be change with broadcasting
-        val resBuffer = DoubleArray(this.buffer.size) { i ->
+        val resBuffer = DoubleArray(this.strides.linearSize) { i ->
-            this.buffer.unsafeToDoubleArray()[i] * other.buffer.unsafeToDoubleArray()[i]
+            this.buffer.unsafeToDoubleArray()[other.bufferStart + i] *
+                    other.buffer.unsafeToDoubleArray()[other.bufferStart + i]
         }
         return DoubleTensor(this.shape, resBuffer)
     }
 
     override fun DoubleTensor.timesAssign(value: Double) {
         //todo should be change with broadcasting
-        for (i in this.buffer.unsafeToDoubleArray().indices) {
+        for (i in 0 until this.strides.linearSize) {
-            this.buffer.unsafeToDoubleArray()[i] *= value
+            this.buffer.unsafeToDoubleArray()[this.bufferStart + i] *= value
         }
     }
 
     override fun DoubleTensor.timesAssign(other: DoubleTensor) {
         //todo should be change with broadcasting
-        for (i in this.buffer.unsafeToDoubleArray().indices) {
+        for (i in 0 until this.strides.linearSize) {
-            this.buffer.unsafeToDoubleArray()[i] *= other.buffer.unsafeToDoubleArray()[i]
+            this.buffer.unsafeToDoubleArray()[this.bufferStart + i] *=
+                other.buffer.unsafeToDoubleArray()[this.bufferStart + i]
         }
     }
 
     override fun DoubleTensor.unaryMinus(): DoubleTensor {
-        val resBuffer = DoubleArray(this.buffer.size) { i ->
+        val resBuffer = DoubleArray(this.strides.linearSize) { i ->
-            this.buffer.unsafeToDoubleArray()[i].unaryMinus()
+            this.buffer.unsafeToDoubleArray()[this.bufferStart + i].unaryMinus()
         }
         return DoubleTensor(this.shape, resBuffer)
     }
 
     override fun DoubleTensor.transpose(i: Int, j: Int): DoubleTensor {
         checkTranspose(this.dimension, i, j)
-        val n = this.buffer.size
+        val n = this.strides.linearSize
         val resBuffer = DoubleArray(n)
 
         val resShape = this.shape.copyOf()
@@ -169,14 +172,16 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, Dou
             newMultiIndex[i] = newMultiIndex[j].also { newMultiIndex[j] = newMultiIndex[i] }
 
             val linearIndex = resTensor.strides.offset(newMultiIndex)
-            resTensor.buffer.unsafeToDoubleArray()[linearIndex] = this.buffer.unsafeToDoubleArray()[offset]
+            resTensor.buffer.unsafeToDoubleArray()[linearIndex] =
+                this.buffer.unsafeToDoubleArray()[this.bufferStart + offset]
         }
         return resTensor
     }
 
 
     override fun DoubleTensor.view(shape: IntArray): DoubleTensor {
-        return DoubleTensor(shape, this.buffer.unsafeToDoubleArray())
+        checkView(this, shape)
+        return DoubleTensor(shape, this.buffer.unsafeToDoubleArray(), this.bufferStart)
     }
 
     override fun DoubleTensor.viewAs(other: DoubleTensor): DoubleTensor {

kmath-core/src/commonMain/kotlin/space/kscience/kmath/tensors/utils.kt

@@ -55,7 +55,8 @@ internal inline fun broadcastTensors(vararg tensors: DoubleTensor): List<DoubleT
             }
 
             val curLinearIndex = tensor.strides.offset(curMultiIndex)
-            resTensor.buffer.unsafeToDoubleArray()[linearIndex] = tensor.buffer.unsafeToDoubleArray()[curLinearIndex]
+            resTensor.buffer.unsafeToDoubleArray()[linearIndex] =
+                tensor.buffer.unsafeToDoubleArray()[tensor.bufferStart + curLinearIndex]
         }
         res.add(resTensor)
     }

kmath-core/src/commonTest/kotlin/space/kscience/kmath/tensors/TestDoubleTensor.kt

@@ -6,7 +6,7 @@ import kotlin.test.Test
 import kotlin.test.assertEquals
 import kotlin.test.assertTrue
 
-class TestRealTensor {
+class TestDoubleTensor {
 
     @Test
     fun valueTest() = DoubleTensorAlgebra {

kmath-core/src/commonTest/kotlin/space/kscience/kmath/tensors/TestDoubleTensorAlgebra.kt

@@ -4,7 +4,7 @@ package space.kscience.kmath.tensors
 import kotlin.test.Test
 import kotlin.test.assertTrue
 
-class TestRealTensorAlgebra {
+class TestDoubleTensorAlgebra {
 
     @Test
     fun doublePlus() = DoubleTensorAlgebra {