Feature/tensors performance #497
@ -27,7 +27,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
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val newThis = broadcast[0]
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val newOther = broadcast[1]
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val resBuffer = DoubleArray(newThis.indices.linearSize) { i ->
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newThis.mutableBuffer.array()[i] + newOther.mutableBuffer.array()[i]
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newThis.mutableBuffer[i] + newOther.mutableBuffer[i]
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}
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return DoubleTensor(newThis.shape, resBuffer)
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}
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@ -35,8 +35,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
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override fun Tensor<Double>.plusAssign(arg: StructureND<Double>) {
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val newOther = broadcastTo(arg.tensor, tensor.shape)
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for (i in 0 until tensor.indices.linearSize) {
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tensor.mutableBuffer.array()[tensor.bufferStart + i] +=
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newOther.mutableBuffer.array()[tensor.bufferStart + i]
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tensor.mutableBuffer[tensor.bufferStart + i] +=
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newOther.mutableBuffer[tensor.bufferStart + i]
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}
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}
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@ -45,7 +45,7 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
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val newThis = broadcast[0]
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val newOther = broadcast[1]
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val resBuffer = DoubleArray(newThis.indices.linearSize) { i ->
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newThis.mutableBuffer.array()[i] - newOther.mutableBuffer.array()[i]
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newThis.mutableBuffer[i] - newOther.mutableBuffer[i]
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}
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return DoubleTensor(newThis.shape, resBuffer)
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}
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@ -53,8 +53,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
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override fun Tensor<Double>.minusAssign(arg: StructureND<Double>) {
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val newOther = broadcastTo(arg.tensor, tensor.shape)
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for (i in 0 until tensor.indices.linearSize) {
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tensor.mutableBuffer.array()[tensor.bufferStart + i] -=
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newOther.mutableBuffer.array()[tensor.bufferStart + i]
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tensor.mutableBuffer[tensor.bufferStart + i] -=
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newOther.mutableBuffer[tensor.bufferStart + i]
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}
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}
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@ -63,8 +63,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
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val newThis = broadcast[0]
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val newOther = broadcast[1]
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val resBuffer = DoubleArray(newThis.indices.linearSize) { i ->
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newThis.mutableBuffer.array()[newThis.bufferStart + i] *
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newOther.mutableBuffer.array()[newOther.bufferStart + i]
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newThis.mutableBuffer[newThis.bufferStart + i] *
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newOther.mutableBuffer[newOther.bufferStart + i]
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}
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return DoubleTensor(newThis.shape, resBuffer)
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}
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@ -72,8 +72,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
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override fun Tensor<Double>.timesAssign(arg: StructureND<Double>) {
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val newOther = broadcastTo(arg.tensor, tensor.shape)
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for (i in 0 until tensor.indices.linearSize) {
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tensor.mutableBuffer.array()[tensor.bufferStart + i] *=
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newOther.mutableBuffer.array()[tensor.bufferStart + i]
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tensor.mutableBuffer[tensor.bufferStart + i] *=
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newOther.mutableBuffer[tensor.bufferStart + i]
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}
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}
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@ -82,8 +82,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
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val newThis = broadcast[0]
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val newOther = broadcast[1]
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val resBuffer = DoubleArray(newThis.indices.linearSize) { i ->
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newThis.mutableBuffer.array()[newOther.bufferStart + i] /
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newOther.mutableBuffer.array()[newOther.bufferStart + i]
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newThis.mutableBuffer[newOther.bufferStart + i] /
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newOther.mutableBuffer[newOther.bufferStart + i]
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}
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return DoubleTensor(newThis.shape, resBuffer)
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}
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@ -91,8 +91,8 @@ public object BroadcastDoubleTensorAlgebra : DoubleTensorAlgebra() {
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override fun Tensor<Double>.divAssign(arg: StructureND<Double>) {
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val newOther = broadcastTo(arg.tensor, tensor.shape)
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for (i in 0 until tensor.indices.linearSize) {
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tensor.mutableBuffer.array()[tensor.bufferStart + i] /=
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newOther.mutableBuffer.array()[tensor.bufferStart + i]
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tensor.mutableBuffer[tensor.bufferStart + i] /=
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newOther.mutableBuffer[tensor.bufferStart + i]
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}
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}
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}
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@ -89,7 +89,7 @@ public open class DoubleTensorAlgebra :
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}
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override fun StructureND<Double>.valueOrNull(): Double? = if (tensor.shape contentEquals intArrayOf(1))
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tensor.mutableBuffer.array()[tensor.bufferStart] else null
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tensor.mutableBuffer[tensor.bufferStart] else null
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override fun StructureND<Double>.value(): Double = valueOrNull()
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?: throw IllegalArgumentException("The tensor shape is $shape, but value method is allowed only for shape [1]")
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@ -208,7 +208,7 @@ public open class DoubleTensorAlgebra :
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override fun Double.plus(arg: StructureND<Double>): DoubleTensor {
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val resBuffer = DoubleArray(arg.tensor.numElements) { i ->
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arg.tensor.mutableBuffer.array()[arg.tensor.bufferStart + i] + this
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arg.tensor.mutableBuffer[arg.tensor.bufferStart + i] + this
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}
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return DoubleTensor(arg.shape, resBuffer)
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}
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@ -218,35 +218,35 @@ public open class DoubleTensorAlgebra :
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override fun StructureND<Double>.plus(arg: StructureND<Double>): DoubleTensor {
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checkShapesCompatible(tensor, arg.tensor)
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val resBuffer = DoubleArray(tensor.numElements) { i ->
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tensor.mutableBuffer.array()[i] + arg.tensor.mutableBuffer.array()[i]
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tensor.mutableBuffer[i] + arg.tensor.mutableBuffer[i]
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}
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return DoubleTensor(tensor.shape, resBuffer)
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}
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override fun Tensor<Double>.plusAssign(value: Double) {
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for (i in 0 until tensor.numElements) {
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tensor.mutableBuffer.array()[tensor.bufferStart + i] += value
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tensor.mutableBuffer[tensor.bufferStart + i] += value
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}
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}
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override fun Tensor<Double>.plusAssign(arg: StructureND<Double>) {
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checkShapesCompatible(tensor, arg.tensor)
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for (i in 0 until tensor.numElements) {
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tensor.mutableBuffer.array()[tensor.bufferStart + i] +=
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arg.tensor.mutableBuffer.array()[tensor.bufferStart + i]
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tensor.mutableBuffer[tensor.bufferStart + i] +=
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arg.tensor.mutableBuffer[tensor.bufferStart + i]
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}
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}
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override fun Double.minus(arg: StructureND<Double>): DoubleTensor {
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val resBuffer = DoubleArray(arg.tensor.numElements) { i ->
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this - arg.tensor.mutableBuffer.array()[arg.tensor.bufferStart + i]
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this - arg.tensor.mutableBuffer[arg.tensor.bufferStart + i]
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}
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return DoubleTensor(arg.shape, resBuffer)
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}
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override fun StructureND<Double>.minus(arg: Double): DoubleTensor {
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val resBuffer = DoubleArray(tensor.numElements) { i ->
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tensor.mutableBuffer.array()[tensor.bufferStart + i] - arg
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tensor.mutableBuffer[tensor.bufferStart + i] - arg
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}
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return DoubleTensor(tensor.shape, resBuffer)
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}
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@ -254,28 +254,28 @@ public open class DoubleTensorAlgebra :
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override fun StructureND<Double>.minus(arg: StructureND<Double>): DoubleTensor {
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checkShapesCompatible(tensor, arg)
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val resBuffer = DoubleArray(tensor.numElements) { i ->
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tensor.mutableBuffer.array()[i] - arg.tensor.mutableBuffer.array()[i]
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tensor.mutableBuffer[i] - arg.tensor.mutableBuffer[i]
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}
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return DoubleTensor(tensor.shape, resBuffer)
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}
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override fun Tensor<Double>.minusAssign(value: Double) {
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for (i in 0 until tensor.numElements) {
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tensor.mutableBuffer.array()[tensor.bufferStart + i] -= value
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tensor.mutableBuffer[tensor.bufferStart + i] -= value
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}
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}
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override fun Tensor<Double>.minusAssign(arg: StructureND<Double>) {
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checkShapesCompatible(tensor, arg)
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for (i in 0 until tensor.numElements) {
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tensor.mutableBuffer.array()[tensor.bufferStart + i] -=
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arg.tensor.mutableBuffer.array()[tensor.bufferStart + i]
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tensor.mutableBuffer[tensor.bufferStart + i] -=
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arg.tensor.mutableBuffer[tensor.bufferStart + i]
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}
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}
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override fun Double.times(arg: StructureND<Double>): DoubleTensor {
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val resBuffer = DoubleArray(arg.tensor.numElements) { i ->
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arg.tensor.mutableBuffer.array()[arg.tensor.bufferStart + i] * this
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arg.tensor.mutableBuffer[arg.tensor.bufferStart + i] * this
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}
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return DoubleTensor(arg.shape, resBuffer)
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}
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@ -285,36 +285,36 @@ public open class DoubleTensorAlgebra :
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override fun StructureND<Double>.times(arg: StructureND<Double>): DoubleTensor {
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checkShapesCompatible(tensor, arg)
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val resBuffer = DoubleArray(tensor.numElements) { i ->
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tensor.mutableBuffer.array()[tensor.bufferStart + i] *
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arg.tensor.mutableBuffer.array()[arg.tensor.bufferStart + i]
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tensor.mutableBuffer[tensor.bufferStart + i] *
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arg.tensor.mutableBuffer[arg.tensor.bufferStart + i]
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}
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return DoubleTensor(tensor.shape, resBuffer)
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}
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override fun Tensor<Double>.timesAssign(value: Double) {
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for (i in 0 until tensor.numElements) {
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tensor.mutableBuffer.array()[tensor.bufferStart + i] *= value
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tensor.mutableBuffer[tensor.bufferStart + i] *= value
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}
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}
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override fun Tensor<Double>.timesAssign(arg: StructureND<Double>) {
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checkShapesCompatible(tensor, arg)
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for (i in 0 until tensor.numElements) {
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tensor.mutableBuffer.array()[tensor.bufferStart + i] *=
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arg.tensor.mutableBuffer.array()[tensor.bufferStart + i]
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tensor.mutableBuffer[tensor.bufferStart + i] *=
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arg.tensor.mutableBuffer[tensor.bufferStart + i]
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}
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}
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override fun Double.div(arg: StructureND<Double>): DoubleTensor {
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val resBuffer = DoubleArray(arg.tensor.numElements) { i ->
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this / arg.tensor.mutableBuffer.array()[arg.tensor.bufferStart + i]
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this / arg.tensor.mutableBuffer[arg.tensor.bufferStart + i]
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}
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return DoubleTensor(arg.shape, resBuffer)
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}
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override fun StructureND<Double>.div(arg: Double): DoubleTensor {
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val resBuffer = DoubleArray(tensor.numElements) { i ->
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tensor.mutableBuffer.array()[tensor.bufferStart + i] / arg
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tensor.mutableBuffer[tensor.bufferStart + i] / arg
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}
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return DoubleTensor(shape, resBuffer)
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}
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@ -322,29 +322,29 @@ public open class DoubleTensorAlgebra :
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override fun StructureND<Double>.div(arg: StructureND<Double>): DoubleTensor {
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checkShapesCompatible(tensor, arg)
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val resBuffer = DoubleArray(tensor.numElements) { i ->
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tensor.mutableBuffer.array()[arg.tensor.bufferStart + i] /
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arg.tensor.mutableBuffer.array()[arg.tensor.bufferStart + i]
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tensor.mutableBuffer[arg.tensor.bufferStart + i] /
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arg.tensor.mutableBuffer[arg.tensor.bufferStart + i]
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}
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return DoubleTensor(tensor.shape, resBuffer)
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}
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override fun Tensor<Double>.divAssign(value: Double) {
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for (i in 0 until tensor.numElements) {
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tensor.mutableBuffer.array()[tensor.bufferStart + i] /= value
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tensor.mutableBuffer[tensor.bufferStart + i] /= value
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}
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}
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override fun Tensor<Double>.divAssign(arg: StructureND<Double>) {
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checkShapesCompatible(tensor, arg)
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for (i in 0 until tensor.numElements) {
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tensor.mutableBuffer.array()[tensor.bufferStart + i] /=
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arg.tensor.mutableBuffer.array()[tensor.bufferStart + i]
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tensor.mutableBuffer[tensor.bufferStart + i] /=
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arg.tensor.mutableBuffer[tensor.bufferStart + i]
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}
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}
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override fun StructureND<Double>.unaryMinus(): DoubleTensor {
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val resBuffer = DoubleArray(tensor.numElements) { i ->
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tensor.mutableBuffer.array()[tensor.bufferStart + i].unaryMinus()
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tensor.mutableBuffer[tensor.bufferStart + i].unaryMinus()
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}
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return DoubleTensor(tensor.shape, resBuffer)
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}
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@ -367,8 +367,8 @@ public open class DoubleTensorAlgebra :
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newMultiIndex[ii] = newMultiIndex[jj].also { newMultiIndex[jj] = newMultiIndex[ii] }
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val linearIndex = resTensor.indices.offset(newMultiIndex)
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resTensor.mutableBuffer.array()[linearIndex] =
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tensor.mutableBuffer.array()[tensor.bufferStart + offset]
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resTensor.mutableBuffer[linearIndex] =
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tensor.mutableBuffer[tensor.bufferStart + offset]
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}
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return resTensor
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}
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@ -958,18 +958,21 @@ public open class DoubleTensorAlgebra :
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var eigenvalueStart = 0
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var eigenvectorStart = 0
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val eigenvaluesBuffer = eigenvalues.mutableBuffer
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val eigenvectorsBuffer = eigenvectors.mutableBuffer
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for (matrix in tensor.matrixSequence()) {
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val matrix2D = matrix.as2D()
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val (d, v) = matrix2D.jacobiHelper(maxIteration, epsilon)
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for (i in 0 until matrix2D.rowNum) {
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for (j in 0 until matrix2D.colNum) {
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eigenvectors.mutableBuffer.array()[eigenvectorStart + i * matrix2D.rowNum + j] = v[i, j]
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eigenvectorsBuffer[eigenvectorStart + i * matrix2D.rowNum + j] = v[i, j]
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}
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}
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for (i in 0 until matrix2D.rowNum) {
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eigenvalues.mutableBuffer.array()[eigenvalueStart + i] = d[i]
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eigenvaluesBuffer[eigenvalueStart + i] = d[i]
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}
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eigenvalueStart += this.shape.last()
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@ -992,11 +995,11 @@ public open class DoubleTensorAlgebra :
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// assume that buffered tensor is square matrix
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operator fun BufferedTensor<Double>.get(i: Int, j: Int): Double {
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return this.mutableBuffer.array()[bufferStart + i * this.shape[0] + j]
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return this.mutableBuffer[bufferStart + i * this.shape[0] + j]
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}
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operator fun BufferedTensor<Double>.set(i: Int, j: Int, value: Double) {
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this.mutableBuffer.array()[bufferStart + i * this.shape[0] + j] = value
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this.mutableBuffer[bufferStart + i * this.shape[0] + j] = value
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}
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fun maxOffDiagonal(matrix: BufferedTensor<Double>): Double {
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@ -156,9 +156,12 @@ internal class TestDoubleLinearOpsTensorAlgebra {
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val res = svd1d(tensor2)
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val resBuffer = res.mutableBuffer
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val resStart = res.bufferStart
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assertTrue(res.shape contentEquals intArrayOf(2))
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assertTrue { abs(abs(res.mutableBuffer.array()[res.bufferStart]) - 0.386) < 0.01 }
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assertTrue { abs(abs(res.mutableBuffer.array()[res.bufferStart + 1]) - 0.922) < 0.01 }
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assertTrue { abs(abs(resBuffer[resStart]) - 0.386) < 0.01 }
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assertTrue { abs(abs(resBuffer[resStart + 1]) - 0.922) < 0.01 }
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}
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@Test
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Loading…
Reference in New Issue
Block a user