KMP library for tensors #300
@ -32,7 +32,7 @@ public interface LinearOpsTensorAlgebra<T, TensorType : TensorStructure<T>> :
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public fun TensorType.lu(): Pair<TensorType, IntTensor>
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public fun TensorType.lu(): Pair<TensorType, IntTensor>
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//https://pytorch.org/docs/stable/generated/torch.lu_unpack.html
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//https://pytorch.org/docs/stable/generated/torch.lu_unpack.html
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public fun luPivot(aLU: TensorType, pivots: IntTensor): Triple<TensorType, TensorType, TensorType>
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public fun luPivot(lu: TensorType, pivots: IntTensor): Triple<TensorType, TensorType, TensorType>
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//https://pytorch.org/docs/stable/linalg.html#torch.linalg.svd
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//https://pytorch.org/docs/stable/linalg.html#torch.linalg.svd
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public fun TensorType.svd(): Triple<TensorType, TensorType, TensorType>
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public fun TensorType.svd(): Triple<TensorType, TensorType, TensorType>
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@ -144,5 +144,7 @@ public class RealAnalyticTensorAlgebra:
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TODO("Not yet implemented")
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TODO("Not yet implemented")
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}
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}
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}
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}
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public inline fun <R> RealAnalyticTensorAlgebra(block: RealTensorAlgebra.() -> R): R =
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RealAnalyticTensorAlgebra().block()
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@ -1,6 +1,7 @@
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package space.kscience.kmath.tensors
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package space.kscience.kmath.tensors
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import space.kscience.kmath.structures.array
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import space.kscience.kmath.structures.toDoubleArray
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import space.kscience.kmath.structures.toIntArray
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public class RealLinearOpsTensorAlgebra :
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public class RealLinearOpsTensorAlgebra :
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LinearOpsTensorAlgebra<Double, RealTensor>,
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LinearOpsTensorAlgebra<Double, RealTensor>,
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@ -80,7 +81,7 @@ public class RealLinearOpsTensorAlgebra :
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// todo checks
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// todo checks
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val n = lu.shape[0]
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val n = lu.shape[0]
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val p = lu.zeroesLike()
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val p = lu.zeroesLike()
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pivots.buffer.array.forEachIndexed { i, pivot ->
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pivots.buffer.toIntArray().forEachIndexed { i, pivot ->
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p[i, pivot] = 1.0
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p[i, pivot] = 1.0
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}
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}
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val l = lu.zeroesLike()
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val l = lu.zeroesLike()
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@ -130,4 +131,4 @@ public class RealLinearOpsTensorAlgebra :
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}
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}
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public inline fun <R> RealLinearOpsTensorAlgebra(block: RealTensorAlgebra.() -> R): R =
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public inline fun <R> RealLinearOpsTensorAlgebra(block: RealTensorAlgebra.() -> R): R =
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RealTensorAlgebra().block()
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RealLinearOpsTensorAlgebra().block()
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@ -1,6 +1,6 @@
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package space.kscience.kmath.tensors
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package space.kscience.kmath.tensors
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import space.kscience.kmath.structures.array
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import space.kscience.kmath.structures.toDoubleArray
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public open class RealTensorAlgebra : TensorPartialDivisionAlgebra<Double, RealTensor> {
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public open class RealTensorAlgebra : TensorPartialDivisionAlgebra<Double, RealTensor> {
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@ -9,7 +9,7 @@ public open class RealTensorAlgebra : TensorPartialDivisionAlgebra<Double, RealT
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check(this.shape contentEquals intArrayOf(1)) {
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check(this.shape contentEquals intArrayOf(1)) {
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"Inconsistent value for tensor of shape ${shape.toList()}"
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"Inconsistent value for tensor of shape ${shape.toList()}"
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}
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}
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return this.buffer.array[0]
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return this.buffer.toDoubleArray()[0]
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}
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}
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override fun zeros(shape: IntArray): RealTensor {
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override fun zeros(shape: IntArray): RealTensor {
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@ -32,13 +32,13 @@ public open class RealTensorAlgebra : TensorPartialDivisionAlgebra<Double, RealT
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override fun RealTensor.copy(): RealTensor {
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override fun RealTensor.copy(): RealTensor {
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// should be rework as soon as copy() method for NDBuffer will be available
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// should be rework as soon as copy() method for NDBuffer will be available
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return RealTensor(this.shape, this.buffer.array.copyOf())
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return RealTensor(this.shape, this.buffer.toDoubleArray().copyOf())
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}
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}
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override fun Double.plus(other: RealTensor): RealTensor {
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override fun Double.plus(other: RealTensor): RealTensor {
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val resBuffer = DoubleArray(other.buffer.size) { i ->
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val resBuffer = DoubleArray(other.buffer.size) { i ->
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other.buffer.array[i] + this
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other.buffer.toDoubleArray()[i] + this
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}
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}
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return RealTensor(other.shape, resBuffer)
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return RealTensor(other.shape, resBuffer)
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}
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}
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@ -50,34 +50,34 @@ public open class RealTensorAlgebra : TensorPartialDivisionAlgebra<Double, RealT
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val newThis = broadcast[0]
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val newThis = broadcast[0]
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val newOther = broadcast[1]
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val newOther = broadcast[1]
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val resBuffer = DoubleArray(newThis.buffer.size) { i ->
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val resBuffer = DoubleArray(newThis.buffer.size) { i ->
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newThis.buffer.array[i] + newOther.buffer.array[i]
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newThis.buffer.toDoubleArray()[i] + newOther.buffer.toDoubleArray()[i]
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}
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}
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return RealTensor(newThis.shape, resBuffer)
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return RealTensor(newThis.shape, resBuffer)
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}
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}
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override fun RealTensor.plusAssign(value: Double) {
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override fun RealTensor.plusAssign(value: Double) {
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for (i in this.buffer.array.indices) {
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for (i in this.buffer.toDoubleArray().indices) {
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this.buffer.array[i] += value
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this.buffer.toDoubleArray()[i] += value
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}
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}
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}
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}
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override fun RealTensor.plusAssign(other: RealTensor) {
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override fun RealTensor.plusAssign(other: RealTensor) {
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//todo should be change with broadcasting
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//todo should be change with broadcasting
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for (i in this.buffer.array.indices) {
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for (i in this.buffer.toDoubleArray().indices) {
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this.buffer.array[i] += other.buffer.array[i]
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this.buffer.toDoubleArray()[i] += other.buffer.toDoubleArray()[i]
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}
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}
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}
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}
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override fun Double.minus(other: RealTensor): RealTensor {
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override fun Double.minus(other: RealTensor): RealTensor {
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val resBuffer = DoubleArray(other.buffer.size) { i ->
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val resBuffer = DoubleArray(other.buffer.size) { i ->
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this - other.buffer.array[i]
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this - other.buffer.toDoubleArray()[i]
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}
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}
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return RealTensor(other.shape, resBuffer)
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return RealTensor(other.shape, resBuffer)
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}
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}
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override fun RealTensor.minus(value: Double): RealTensor {
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override fun RealTensor.minus(value: Double): RealTensor {
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val resBuffer = DoubleArray(this.buffer.size) { i ->
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val resBuffer = DoubleArray(this.buffer.size) { i ->
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this.buffer.array[i] - value
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this.buffer.toDoubleArray()[i] - value
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}
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}
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return RealTensor(this.shape, resBuffer)
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return RealTensor(this.shape, resBuffer)
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}
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}
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@ -87,14 +87,14 @@ public open class RealTensorAlgebra : TensorPartialDivisionAlgebra<Double, RealT
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val newThis = broadcast[0]
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val newThis = broadcast[0]
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val newOther = broadcast[1]
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val newOther = broadcast[1]
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val resBuffer = DoubleArray(newThis.buffer.size) { i ->
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val resBuffer = DoubleArray(newThis.buffer.size) { i ->
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newThis.buffer.array[i] - newOther.buffer.array[i]
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newThis.buffer.toDoubleArray()[i] - newOther.buffer.toDoubleArray()[i]
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}
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}
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return RealTensor(newThis.shape, resBuffer)
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return RealTensor(newThis.shape, resBuffer)
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}
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}
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override fun RealTensor.minusAssign(value: Double) {
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override fun RealTensor.minusAssign(value: Double) {
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for (i in this.buffer.array.indices) {
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for (i in this.buffer.toDoubleArray().indices) {
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this.buffer.array[i] -= value
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this.buffer.toDoubleArray()[i] -= value
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}
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}
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}
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}
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@ -105,7 +105,7 @@ public open class RealTensorAlgebra : TensorPartialDivisionAlgebra<Double, RealT
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override fun Double.times(other: RealTensor): RealTensor {
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override fun Double.times(other: RealTensor): RealTensor {
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//todo should be change with broadcasting
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//todo should be change with broadcasting
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val resBuffer = DoubleArray(other.buffer.size) { i ->
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val resBuffer = DoubleArray(other.buffer.size) { i ->
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other.buffer.array[i] * this
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other.buffer.toDoubleArray()[i] * this
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}
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}
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return RealTensor(other.shape, resBuffer)
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return RealTensor(other.shape, resBuffer)
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}
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}
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@ -116,28 +116,28 @@ public open class RealTensorAlgebra : TensorPartialDivisionAlgebra<Double, RealT
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override fun RealTensor.times(other: RealTensor): RealTensor {
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override fun RealTensor.times(other: RealTensor): RealTensor {
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//todo should be change with broadcasting
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//todo should be change with broadcasting
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val resBuffer = DoubleArray(this.buffer.size) { i ->
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val resBuffer = DoubleArray(this.buffer.size) { i ->
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this.buffer.array[i] * other.buffer.array[i]
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this.buffer.toDoubleArray()[i] * other.buffer.toDoubleArray()[i]
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}
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}
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return RealTensor(this.shape, resBuffer)
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return RealTensor(this.shape, resBuffer)
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}
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}
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override fun RealTensor.timesAssign(value: Double) {
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override fun RealTensor.timesAssign(value: Double) {
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//todo should be change with broadcasting
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//todo should be change with broadcasting
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for (i in this.buffer.array.indices) {
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for (i in this.buffer.toDoubleArray().indices) {
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this.buffer.array[i] *= value
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this.buffer.toDoubleArray()[i] *= value
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}
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}
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}
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}
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override fun RealTensor.timesAssign(other: RealTensor) {
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override fun RealTensor.timesAssign(other: RealTensor) {
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//todo should be change with broadcasting
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//todo should be change with broadcasting
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for (i in this.buffer.array.indices) {
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for (i in this.buffer.toDoubleArray().indices) {
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this.buffer.array[i] *= other.buffer.array[i]
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this.buffer.toDoubleArray()[i] *= other.buffer.toDoubleArray()[i]
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}
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}
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}
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}
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override fun RealTensor.unaryMinus(): RealTensor {
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override fun RealTensor.unaryMinus(): RealTensor {
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val resBuffer = DoubleArray(this.buffer.size) { i ->
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val resBuffer = DoubleArray(this.buffer.size) { i ->
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this.buffer.array[i].unaryMinus()
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this.buffer.toDoubleArray()[i].unaryMinus()
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}
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}
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return RealTensor(this.shape, resBuffer)
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return RealTensor(this.shape, resBuffer)
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}
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}
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@ -158,14 +158,14 @@ public open class RealTensorAlgebra : TensorPartialDivisionAlgebra<Double, RealT
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newMultiIndex[i] = newMultiIndex[j].also { newMultiIndex[j] = newMultiIndex[i] }
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newMultiIndex[i] = newMultiIndex[j].also { newMultiIndex[j] = newMultiIndex[i] }
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val linearIndex = resTensor.strides.offset(newMultiIndex)
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val linearIndex = resTensor.strides.offset(newMultiIndex)
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resTensor.buffer.array[linearIndex] = this.buffer.array[offset]
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resTensor.buffer.toDoubleArray()[linearIndex] = this.buffer.toDoubleArray()[offset]
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}
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}
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return resTensor
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return resTensor
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}
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}
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override fun RealTensor.view(shape: IntArray): RealTensor {
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override fun RealTensor.view(shape: IntArray): RealTensor {
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return RealTensor(shape, this.buffer.array)
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return RealTensor(shape, this.buffer.toDoubleArray())
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}
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}
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override fun RealTensor.viewAs(other: RealTensor): RealTensor {
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override fun RealTensor.viewAs(other: RealTensor): RealTensor {
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@ -1,6 +1,6 @@
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package space.kscience.kmath.tensors
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package space.kscience.kmath.tensors
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import space.kscience.kmath.structures.array
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import space.kscience.kmath.structures.toDoubleArray
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import kotlin.math.max
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import kotlin.math.max
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@ -55,7 +55,7 @@ internal inline fun broadcastTensors(vararg tensors: RealTensor): List<RealTenso
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}
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}
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val curLinearIndex = tensor.strides.offset(curMultiIndex)
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val curLinearIndex = tensor.strides.offset(curMultiIndex)
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resTensor.buffer.array[linearIndex] = tensor.buffer.array[curLinearIndex]
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resTensor.buffer.toDoubleArray()[linearIndex] = tensor.buffer.toDoubleArray()[curLinearIndex]
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}
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}
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res.add(resTensor)
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res.add(resTensor)
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}
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}
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@ -1,7 +1,7 @@
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package space.kscience.kmath.tensors
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package space.kscience.kmath.tensors
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import space.kscience.kmath.structures.array
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import space.kscience.kmath.structures.toDoubleArray
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import kotlin.test.Test
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import kotlin.test.Test
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import kotlin.test.assertEquals
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import kotlin.test.assertEquals
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import kotlin.test.assertTrue
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import kotlin.test.assertTrue
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@ -19,6 +19,6 @@ class TestRealTensor {
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fun stridesTest(){
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fun stridesTest(){
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val tensor = RealTensor(intArrayOf(2,2), doubleArrayOf(3.5,5.8,58.4,2.4))
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val tensor = RealTensor(intArrayOf(2,2), doubleArrayOf(3.5,5.8,58.4,2.4))
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assertEquals(tensor[intArrayOf(0,1)], 5.8)
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assertEquals(tensor[intArrayOf(0,1)], 5.8)
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assertTrue(tensor.elements().map{ it.second }.toList().toDoubleArray() contentEquals tensor.buffer.array)
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assertTrue(tensor.elements().map{ it.second }.toList().toDoubleArray() contentEquals tensor.buffer.toDoubleArray())
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}
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}
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}
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}
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@ -1,6 +1,6 @@
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package space.kscience.kmath.tensors
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package space.kscience.kmath.tensors
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import space.kscience.kmath.structures.array
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import space.kscience.kmath.structures.toDoubleArray
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import kotlin.test.Test
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import kotlin.test.Test
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import kotlin.test.assertTrue
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import kotlin.test.assertTrue
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@ -10,7 +10,7 @@ class TestRealTensorAlgebra {
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fun doublePlus() = RealTensorAlgebra {
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fun doublePlus() = RealTensorAlgebra {
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val tensor = RealTensor(intArrayOf(2), doubleArrayOf(1.0, 2.0))
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val tensor = RealTensor(intArrayOf(2), doubleArrayOf(1.0, 2.0))
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val res = 10.0 + tensor
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val res = 10.0 + tensor
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assertTrue(res.buffer.array contentEquals doubleArrayOf(11.0,12.0))
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assertTrue(res.buffer.toDoubleArray() contentEquals doubleArrayOf(11.0,12.0))
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}
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}
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@Test
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@Test
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@ -18,7 +18,7 @@ class TestRealTensorAlgebra {
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val tensor = RealTensor(intArrayOf(1), doubleArrayOf(0.0))
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val tensor = RealTensor(intArrayOf(1), doubleArrayOf(0.0))
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val res = tensor.transpose(0, 0)
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val res = tensor.transpose(0, 0)
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assertTrue(res.buffer.array contentEquals doubleArrayOf(0.0))
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assertTrue(res.buffer.toDoubleArray() contentEquals doubleArrayOf(0.0))
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assertTrue(res.shape contentEquals intArrayOf(1))
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assertTrue(res.shape contentEquals intArrayOf(1))
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}
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}
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@ -27,7 +27,7 @@ class TestRealTensorAlgebra {
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val tensor = RealTensor(intArrayOf(3, 2), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
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val tensor = RealTensor(intArrayOf(3, 2), doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
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val res = tensor.transpose(1, 0)
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val res = tensor.transpose(1, 0)
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assertTrue(res.buffer.array contentEquals doubleArrayOf(1.0, 3.0, 5.0, 2.0, 4.0, 6.0))
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assertTrue(res.buffer.toDoubleArray() contentEquals doubleArrayOf(1.0, 3.0, 5.0, 2.0, 4.0, 6.0))
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assertTrue(res.shape contentEquals intArrayOf(2, 3))
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assertTrue(res.shape contentEquals intArrayOf(2, 3))
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}
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}
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@ -42,9 +42,9 @@ class TestRealTensorAlgebra {
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assertTrue(res02.shape contentEquals intArrayOf(3, 2, 1))
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assertTrue(res02.shape contentEquals intArrayOf(3, 2, 1))
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assertTrue(res12.shape contentEquals intArrayOf(1, 3, 2))
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assertTrue(res12.shape contentEquals intArrayOf(1, 3, 2))
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assertTrue(res01.buffer.array contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
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assertTrue(res01.buffer.toDoubleArray() contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
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assertTrue(res02.buffer.array contentEquals doubleArrayOf(1.0, 4.0, 2.0, 5.0, 3.0, 6.0))
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assertTrue(res02.buffer.toDoubleArray() contentEquals doubleArrayOf(1.0, 4.0, 2.0, 5.0, 3.0, 6.0))
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assertTrue(res12.buffer.array contentEquals doubleArrayOf(1.0, 4.0, 2.0, 5.0, 3.0, 6.0))
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assertTrue(res12.buffer.toDoubleArray() contentEquals doubleArrayOf(1.0, 4.0, 2.0, 5.0, 3.0, 6.0))
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}
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}
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@Test
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@Test
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@ -70,9 +70,9 @@ class TestRealTensorAlgebra {
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assertTrue(res[1].shape contentEquals intArrayOf(1, 2, 3))
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assertTrue(res[1].shape contentEquals intArrayOf(1, 2, 3))
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assertTrue(res[2].shape contentEquals intArrayOf(1, 2, 3))
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assertTrue(res[2].shape contentEquals intArrayOf(1, 2, 3))
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assertTrue(res[0].buffer.array contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
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assertTrue(res[0].buffer.toDoubleArray() contentEquals doubleArrayOf(1.0, 2.0, 3.0, 4.0, 5.0, 6.0))
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assertTrue(res[1].buffer.array contentEquals doubleArrayOf(10.0, 20.0, 30.0, 10.0, 20.0, 30.0))
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assertTrue(res[1].buffer.toDoubleArray() contentEquals doubleArrayOf(10.0, 20.0, 30.0, 10.0, 20.0, 30.0))
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assertTrue(res[2].buffer.array contentEquals doubleArrayOf(500.0, 500.0, 500.0, 500.0, 500.0, 500.0))
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assertTrue(res[2].buffer.toDoubleArray() contentEquals doubleArrayOf(500.0, 500.0, 500.0, 500.0, 500.0, 500.0))
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}
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}
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@Test
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@Test
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@ -82,14 +82,14 @@ class TestRealTensorAlgebra {
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val tensor3 = RealTensor(intArrayOf(1, 1, 1), doubleArrayOf(500.0))
|
val tensor3 = RealTensor(intArrayOf(1, 1, 1), doubleArrayOf(500.0))
|
||||||
|
|
||||||
assertTrue((tensor2 - tensor1).shape contentEquals intArrayOf(2, 3))
|
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((tensor2 - tensor1).buffer.toDoubleArray() 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).shape contentEquals intArrayOf(1, 2, 3))
|
||||||
assertTrue((tensor3 - tensor1).buffer.array
|
assertTrue((tensor3 - tensor1).buffer.toDoubleArray()
|
||||||
contentEquals doubleArrayOf(499.0, 498.0, 497.0, 496.0, 495.0, 494.0))
|
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).shape contentEquals intArrayOf(1, 1, 3))
|
||||||
assertTrue((tensor3 - tensor2).buffer.array contentEquals doubleArrayOf(490.0, 480.0, 470.0))
|
assertTrue((tensor3 - tensor2).buffer.toDoubleArray() contentEquals doubleArrayOf(490.0, 480.0, 470.0))
|
||||||
}
|
}
|
||||||
|
|
||||||
}
|
}
|
Loading…
Reference in New Issue
Block a user