forked from kscience/kmath
inheritance is back
This commit is contained in:
Roland Grinis
parent
e6e117f694
commit
6d5e4a5776
@ -14,7 +14,7 @@ import space.kscience.kmath.tensors.api.TensorAlgebra
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import space.kscience.kmath.tensors.core.TensorLinearStructure
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public sealed class NoaAlgebra<T, TensorType : NoaTensor<T>>
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public sealed class NoaAlgebra<T, PrimitiveArray, TensorType : NoaTensor<T>>
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protected constructor(protected val scope: NoaScope) :
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TensorAlgebra<T> {
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@ -36,6 +36,15 @@ protected constructor(protected val scope: NoaScope) :
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override fun Tensor<T>.value(): T = tensor.item()
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public abstract fun randDiscrete(low: Long, high: Long, shape: IntArray, device: Device): TensorType
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@PerformancePitfall
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public abstract fun Tensor<T>.copyToArray(): PrimitiveArray
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public abstract fun copyFromArray(array: PrimitiveArray, shape: IntArray, device: Device): TensorType
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public abstract fun full(value: T, shape: IntArray, device: Device): TensorType
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override operator fun Tensor<T>.times(other: Tensor<T>): TensorType {
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return wrap(JNoa.timesTensor(tensor.tensorHandle, other.tensor.tensorHandle))
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}
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@ -132,9 +141,9 @@ protected constructor(protected val scope: NoaScope) :
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}
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public sealed class NoaPartialDivisionAlgebra<T, TensorType : NoaTensor<T>>
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public sealed class NoaPartialDivisionAlgebra<T, PrimitiveArray, TensorType : NoaTensor<T>>
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protected constructor(scope: NoaScope) :
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NoaAlgebra<T, TensorType>(scope),
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NoaAlgebra<T, PrimitiveArray, TensorType>(scope),
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LinearOpsTensorAlgebra<T>,
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AnalyticTensorAlgebra<T> {
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@ -161,6 +170,10 @@ protected constructor(scope: NoaScope) :
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override fun Tensor<T>.variance(dim: Int, keepDim: Boolean): TensorType =
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wrap(JNoa.varDimTensor(tensor.tensorHandle, dim, keepDim))
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public abstract fun randNormal(shape: IntArray, device: Device): TensorType
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public abstract fun randUniform(shape: IntArray, device: Device): TensorType
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public fun Tensor<T>.randUniform(): TensorType =
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wrap(JNoa.randLike(tensor.tensorHandle))
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@ -278,7 +291,7 @@ protected constructor(scope: NoaScope) :
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public sealed class NoaDoubleAlgebra
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protected constructor(scope: NoaScope) :
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NoaPartialDivisionAlgebra<Double, NoaDoubleTensor>(scope) {
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NoaPartialDivisionAlgebra<Double, DoubleArray, NoaDoubleTensor>(scope) {
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private fun Tensor<Double>.castHelper(): NoaDoubleTensor =
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copyFromArray(
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@ -296,19 +309,19 @@ protected constructor(scope: NoaScope) :
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NoaDoubleTensor(scope = scope, tensorHandle = tensorHandle)
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@PerformancePitfall
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public fun Tensor<Double>.copyToArray(): DoubleArray =
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override fun Tensor<Double>.copyToArray(): DoubleArray =
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tensor.elements().map { it.second }.toList().toDoubleArray()
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public fun copyFromArray(array: DoubleArray, shape: IntArray, device: Device): NoaDoubleTensor =
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override fun copyFromArray(array: DoubleArray, shape: IntArray, device: Device): NoaDoubleTensor =
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wrap(JNoa.fromBlobDouble(array, shape, device.toInt()))
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public fun randNormalDouble(shape: IntArray, device: Device): NoaDoubleTensor =
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override fun randNormal(shape: IntArray, device: Device): NoaDoubleTensor =
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wrap(JNoa.randnDouble(shape, device.toInt()))
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public fun randUniformDouble(shape: IntArray, device: Device): NoaDoubleTensor =
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override fun randUniform(shape: IntArray, device: Device): NoaDoubleTensor =
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wrap(JNoa.randDouble(shape, device.toInt()))
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public fun randDiscreteDouble(low: Long, high: Long, shape: IntArray, device: Device): NoaDoubleTensor =
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override fun randDiscrete(low: Long, high: Long, shape: IntArray, device: Device): NoaDoubleTensor =
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wrap(JNoa.randintDouble(low, high, shape, device.toInt()))
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override operator fun Double.plus(other: Tensor<Double>): NoaDoubleTensor =
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@ -347,14 +360,14 @@ protected constructor(scope: NoaScope) :
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override fun Tensor<Double>.divAssign(value: Double): Unit =
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tensor.timesAssign(1 / value)
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public fun full(value: Double, shape: IntArray, device: Device): NoaDoubleTensor =
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override fun full(value: Double, shape: IntArray, device: Device): NoaDoubleTensor =
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wrap(JNoa.fullDouble(value, shape, device.toInt()))
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}
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public sealed class NoaFloatAlgebra
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protected constructor(scope: NoaScope) :
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NoaPartialDivisionAlgebra<Float, NoaFloatTensor>(scope) {
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NoaPartialDivisionAlgebra<Float, FloatArray, NoaFloatTensor>(scope) {
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private fun Tensor<Float>.castHelper(): NoaFloatTensor =
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copyFromArray(
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@ -372,19 +385,19 @@ protected constructor(scope: NoaScope) :
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NoaFloatTensor(scope = scope, tensorHandle = tensorHandle)
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@PerformancePitfall
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public fun Tensor<Float>.copyToArray(): FloatArray =
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override fun Tensor<Float>.copyToArray(): FloatArray =
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tensor.elements().map { it.second }.toList().toFloatArray()
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public fun copyFromArray(array: FloatArray, shape: IntArray, device: Device): NoaFloatTensor =
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override fun copyFromArray(array: FloatArray, shape: IntArray, device: Device): NoaFloatTensor =
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wrap(JNoa.fromBlobFloat(array, shape, device.toInt()))
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public fun randNormalFloat(shape: IntArray, device: Device): NoaFloatTensor =
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override fun randNormal(shape: IntArray, device: Device): NoaFloatTensor =
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wrap(JNoa.randnFloat(shape, device.toInt()))
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public fun randUniformFloat(shape: IntArray, device: Device): NoaFloatTensor =
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override fun randUniform(shape: IntArray, device: Device): NoaFloatTensor =
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wrap(JNoa.randFloat(shape, device.toInt()))
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public fun randDiscreteFloat(low: Long, high: Long, shape: IntArray, device: Device): NoaFloatTensor =
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override fun randDiscrete(low: Long, high: Long, shape: IntArray, device: Device): NoaFloatTensor =
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wrap(JNoa.randintFloat(low, high, shape, device.toInt()))
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override operator fun Float.plus(other: Tensor<Float>): NoaFloatTensor =
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@ -423,14 +436,14 @@ protected constructor(scope: NoaScope) :
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override fun Tensor<Float>.divAssign(value: Float): Unit =
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tensor.timesAssign(1 / value)
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public fun full(value: Float, shape: IntArray, device: Device): NoaFloatTensor =
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override fun full(value: Float, shape: IntArray, device: Device): NoaFloatTensor =
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wrap(JNoa.fullFloat(value, shape, device.toInt()))
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}
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public sealed class NoaLongAlgebra
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protected constructor(scope: NoaScope) :
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NoaAlgebra<Long, NoaLongTensor>(scope) {
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NoaAlgebra<Long, LongArray, NoaLongTensor>(scope) {
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private fun Tensor<Long>.castHelper(): NoaLongTensor =
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copyFromArray(
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@ -448,13 +461,13 @@ protected constructor(scope: NoaScope) :
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NoaLongTensor(scope = scope, tensorHandle = tensorHandle)
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@PerformancePitfall
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public fun Tensor<Long>.copyToArray(): LongArray =
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override fun Tensor<Long>.copyToArray(): LongArray =
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tensor.elements().map { it.second }.toList().toLongArray()
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public fun copyFromArray(array: LongArray, shape: IntArray, device: Device): NoaLongTensor =
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override fun copyFromArray(array: LongArray, shape: IntArray, device: Device): NoaLongTensor =
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wrap(JNoa.fromBlobLong(array, shape, device.toInt()))
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public fun randDiscreteLong(low: Long, high: Long, shape: IntArray, device: Device): NoaLongTensor =
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override fun randDiscrete(low: Long, high: Long, shape: IntArray, device: Device): NoaLongTensor =
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wrap(JNoa.randintLong(low, high, shape, device.toInt()))
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override operator fun Long.plus(other: Tensor<Long>): NoaLongTensor =
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@ -484,14 +497,14 @@ protected constructor(scope: NoaScope) :
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override fun Tensor<Long>.timesAssign(value: Long): Unit =
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JNoa.timesLongAssign(value, tensor.tensorHandle)
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public fun full(value: Long, shape: IntArray, device: Device): NoaLongTensor =
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override fun full(value: Long, shape: IntArray, device: Device): NoaLongTensor =
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wrap(JNoa.fullLong(value, shape, device.toInt()))
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}
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public sealed class NoaIntAlgebra
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protected constructor(scope: NoaScope) :
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NoaAlgebra<Int, NoaIntTensor>(scope) {
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NoaAlgebra<Int, IntArray, NoaIntTensor>(scope) {
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private fun Tensor<Int>.castHelper(): NoaIntTensor =
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copyFromArray(
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@ -509,13 +522,13 @@ protected constructor(scope: NoaScope) :
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NoaIntTensor(scope = scope, tensorHandle = tensorHandle)
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@PerformancePitfall
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public fun Tensor<Int>.copyToArray(): IntArray =
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override fun Tensor<Int>.copyToArray(): IntArray =
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tensor.elements().map { it.second }.toList().toIntArray()
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public fun copyFromArray(array: IntArray, shape: IntArray, device: Device): NoaIntTensor =
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override fun copyFromArray(array: IntArray, shape: IntArray, device: Device): NoaIntTensor =
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wrap(JNoa.fromBlobInt(array, shape, device.toInt()))
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public fun randDiscreteInt(low: Long, high: Long, shape: IntArray, device: Device): NoaIntTensor =
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override fun randDiscrete(low: Long, high: Long, shape: IntArray, device: Device): NoaIntTensor =
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wrap(JNoa.randintInt(low, high, shape, device.toInt()))
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override operator fun Int.plus(other: Tensor<Int>): NoaIntTensor =
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@ -545,7 +558,7 @@ protected constructor(scope: NoaScope) :
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override fun Tensor<Int>.timesAssign(value: Int): Unit =
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JNoa.timesIntAssign(value, tensor.tensorHandle)
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public fun full(value: Int, shape: IntArray, device: Device): NoaIntTensor =
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override fun full(value: Int, shape: IntArray, device: Device): NoaIntTensor =
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wrap(JNoa.fullInt(value, shape, device.toInt()))
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}
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