forked from kscience/kmath
Testing linear structure
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@ -3,19 +3,17 @@ package space.kscience.kmath.tensors
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// https://proofwiki.org/wiki/Definition:Algebra_over_Ring
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// https://proofwiki.org/wiki/Definition:Algebra_over_Ring
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public interface TensorAlgebra<T, TensorType : TensorStructure<T>> {
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public interface TensorAlgebra<T, TensorType : TensorStructure<T>> {
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//https://pytorch.org/docs/stable/generated/torch.full.html
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public fun full(value: T, shape: IntArray): TensorType
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//https://pytorch.org/docs/stable/generated/torch.full_like.html#torch.full_like
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public fun TensorType.fullLike(value: T): TensorType
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public fun zeros(shape: IntArray): TensorType
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public fun zeros(shape: IntArray): TensorType
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public fun TensorType.zeroesLike(): TensorType // mb it shouldn't be tensor but algebra method (like in numpy/torch) ?
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public fun TensorType.zeroesLike(): TensorType // mb it shouldn't be tensor but algebra method (like in numpy/torch) ?
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public fun ones(shape: IntArray): TensorType
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public fun ones(shape: IntArray): TensorType
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public fun TensorType.onesLike(): TensorType
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public fun TensorType.onesLike(): TensorType
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//https://pytorch.org/docs/stable/generated/torch.full.html
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public fun full(shape: IntArray, value: T): TensorType
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//https://pytorch.org/docs/stable/generated/torch.full_like.html#torch.full_like
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public fun TensorType.fullLike(value: T): TensorType
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//https://pytorch.org/docs/stable/generated/torch.eye.html
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//https://pytorch.org/docs/stable/generated/torch.eye.html
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public fun eye(n: Int): TensorType
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public fun eye(n: Int): TensorType
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@ -20,23 +20,25 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, Dou
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return DoubleTensor(newShape, this.buffer.array(), newStart)
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return DoubleTensor(newShape, this.buffer.array(), newStart)
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}
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}
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override fun zeros(shape: IntArray): DoubleTensor {
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override fun full(value: Double, shape: IntArray): DoubleTensor {
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TODO("Not yet implemented")
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checkEmptyShape(shape)
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}
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val buffer = DoubleArray(shape.reduce(Int::times)) { value }
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override fun DoubleTensor.zeroesLike(): DoubleTensor {
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val shape = this.shape
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val buffer = DoubleArray(this.strides.linearSize) { 0.0 }
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return DoubleTensor(shape, buffer)
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return DoubleTensor(shape, buffer)
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}
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}
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override fun ones(shape: IntArray): DoubleTensor {
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override fun DoubleTensor.fullLike(value: Double): DoubleTensor {
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TODO("Not yet implemented")
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val shape = this.shape
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val buffer = DoubleArray(this.strides.linearSize) { value }
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return DoubleTensor(shape, buffer)
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}
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}
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override fun DoubleTensor.onesLike(): DoubleTensor {
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override fun zeros(shape: IntArray): DoubleTensor = full(0.0, shape)
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TODO("Not yet implemented")
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}
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override fun DoubleTensor.zeroesLike(): DoubleTensor = this.fullLike(0.0)
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override fun ones(shape: IntArray): DoubleTensor = full(1.0, shape)
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override fun DoubleTensor.onesLike(): DoubleTensor = this.fullLike(1.0)
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override fun eye(n: Int): DoubleTensor {
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override fun eye(n: Int): DoubleTensor {
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val shape = intArrayOf(n, n)
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val shape = intArrayOf(n, n)
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@ -225,15 +227,6 @@ public open class DoubleTensorAlgebra : TensorPartialDivisionAlgebra<Double, Dou
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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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override fun full(shape: IntArray, value: Double): DoubleTensor {
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TODO("Not yet implemented")
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}
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override fun DoubleTensor.fullLike(value: Double): DoubleTensor {
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TODO("Not yet implemented")
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}
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override fun DoubleTensor.sum(dim: Int, keepDim: Boolean): DoubleTensor {
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override fun DoubleTensor.sum(dim: Int, keepDim: Boolean): DoubleTensor {
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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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@ -47,4 +47,36 @@ class TestDoubleTensorAlgebra {
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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.array() 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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fun linearStructure() = DoubleTensorAlgebra {
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val shape = intArrayOf(3)
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val tensorA = full(value = -4.5, shape = shape)
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val tensorB = full(value = 10.9, shape = shape)
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val tensorC = full(value = 789.3, shape = shape)
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val tensorD = full(value = -72.9, shape = shape)
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val tensorE = full(value = 553.1, shape = shape)
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val result = 15.8 * tensorA - 1.5 * tensorB * (-tensorD) + 0.02 * tensorC / tensorE - 39.4
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val expected = fromArray(
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shape,
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(1..3).map {
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15.8 * (-4.5) - 1.5 * 10.9 * 72.9 + 0.02 * 789.3 / 553.1 - 39.4
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}.toDoubleArray()
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)
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val assignResult = zeros(shape)
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tensorA *= 15.8
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tensorB *= 1.5
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tensorB *= -tensorD
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tensorC *= 0.02
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tensorC /= tensorE
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assignResult += tensorA
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assignResult -= tensorB
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assignResult += tensorC
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assignResult += -39.4
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assertTrue(expected.buffer.array() contentEquals result.buffer.array())
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assertTrue(expected.buffer.array() contentEquals assignResult.buffer.array())
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}
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}
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}
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