forked from kscience/kmath
Add multik dot for tensors
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@ -3,9 +3,14 @@
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* Use of this source code is governed by the Apache 2.0 license that can be found in the LICENSE file.
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*/
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@file:Suppress("unused")
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package space.kscience.kmath.multik
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import org.jetbrains.kotlinx.multik.api.Multik
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import org.jetbrains.kotlinx.multik.api.linalg.dot
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import org.jetbrains.kotlinx.multik.api.mk
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import org.jetbrains.kotlinx.multik.api.ndarrayOf
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import org.jetbrains.kotlinx.multik.api.zeros
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import org.jetbrains.kotlinx.multik.ndarray.data.*
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import org.jetbrains.kotlinx.multik.ndarray.operations.*
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@ -30,8 +35,20 @@ public value class MultikTensor<T>(public val array: MutableMultiArray<T, DN>) :
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}
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}
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private fun <T, D : Dimension> MultiArray<T, D>.asD1Array(): D1Array<T> {
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if (this is NDArray<T, D>)
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return this.asD1Array()
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else throw ClassCastException("Cannot cast MultiArray to NDArray.")
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}
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public class MultikTensorAlgebra<T> internal constructor(
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private fun <T, D : Dimension> MultiArray<T, D>.asD2Array(): D2Array<T> {
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if (this is NDArray<T, D>)
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return this.asD2Array()
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else throw ClassCastException("Cannot cast MultiArray to NDArray.")
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}
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public class MultikTensorAlgebra<T : Number> internal constructor(
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public val type: DataType,
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public val elementAlgebra: Ring<T>,
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public val comparator: Comparator<T>
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@ -162,8 +179,17 @@ public class MultikTensorAlgebra<T> internal constructor(
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override fun Tensor<T>.viewAs(other: Tensor<T>): MultikTensor<T> = view(other.shape)
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override fun Tensor<T>.dot(other: Tensor<T>): MultikTensor<T> {
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TODO("Not yet implemented")
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override fun Tensor<T>.dot(other: Tensor<T>): MultikTensor<T> =
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if (this.shape.size == 1 && other.shape.size == 1) {
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Multik.ndarrayOf(
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asMultik().array.asD1Array() dot other.asMultik().array.asD1Array()
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).asDNArray().wrap()
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} else if (this.shape.size == 2 && other.shape.size == 2) {
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(asMultik().array.asD2Array() dot other.asMultik().array.asD2Array()).asDNArray().wrap()
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} else if(this.shape.size == 2 && other.shape.size == 1) {
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(asMultik().array.asD2Array() dot other.asMultik().array.asD1Array()).asDNArray().wrap()
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} else {
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TODO("Not implemented for broadcasting")
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}
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override fun diagonalEmbedding(diagonalEntries: Tensor<T>, offset: Int, dim1: Int, dim2: Int): MultikTensor<T> {
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