From face60824da043f2f684acbb0891052217472f4b Mon Sep 17 00:00:00 2001 From: Roland Grinis Date: Tue, 13 Jul 2021 13:08:00 +0100 Subject: [PATCH] testing copying --- .../space/kscience/kmath/noa/algebras.kt | 16 ++++---- .../space/kscience/kmath/noa/TestTensor.kt | 40 +++++++++++++++++++ .../space/kscience/kmath/noa/TestUtils.kt | 4 +- 3 files changed, 49 insertions(+), 11 deletions(-) create mode 100644 kmath-noa/src/test/kotlin/space/kscience/kmath/noa/TestTensor.kt diff --git a/kmath-noa/src/main/kotlin/space/kscience/kmath/noa/algebras.kt b/kmath-noa/src/main/kotlin/space/kscience/kmath/noa/algebras.kt index baf4b99f9..94a2a0192 100644 --- a/kmath-noa/src/main/kotlin/space/kscience/kmath/noa/algebras.kt +++ b/kmath-noa/src/main/kotlin/space/kscience/kmath/noa/algebras.kt @@ -36,14 +36,14 @@ protected constructor(protected val scope: NoaScope) : override fun Tensor.value(): T = tensor.item() - public abstract fun randDiscrete(low: Long, high: Long, shape: IntArray, device: Device): TensorType + public abstract fun randDiscrete(low: Long, high: Long, shape: IntArray, device: Device = Device.CPU): TensorType @PerformancePitfall public abstract fun Tensor.copyToArray(): PrimitiveArray - public abstract fun copyFromArray(array: PrimitiveArray, shape: IntArray, device: Device): TensorType + public abstract fun copyFromArray(array: PrimitiveArray, shape: IntArray, device: Device = Device.CPU): TensorType - public abstract fun full(value: T, shape: IntArray, device: Device): TensorType + public abstract fun full(value: T, shape: IntArray, device: Device = Device.CPU): TensorType override operator fun Tensor.times(other: Tensor): TensorType { return wrap(JNoa.timesTensor(tensor.tensorHandle, other.tensor.tensorHandle)) @@ -136,10 +136,10 @@ protected constructor(protected val scope: NoaScope) : public fun Tensor.copy(): TensorType = wrap(JNoa.copyTensor(tensor.tensorHandle)) - public fun Tensor.copyToDevice(device: Device): TensorType = + public fun Tensor.copyToDevice(device: Device = Device.CPU): TensorType = wrap(JNoa.copyToDevice(tensor.tensorHandle, device.toInt())) - public abstract fun loadJitModule(path: String, device: Device): NoaJitModule + public abstract fun loadJitModule(path: String, device: Device = Device.CPU): NoaJitModule public fun NoaJitModule.forward(parameters: Tensor): TensorType = wrap(JNoa.forwardPass(jitModuleHandle, parameters.tensor.tensorHandle)) @@ -193,9 +193,9 @@ protected constructor(scope: NoaScope) : override fun Tensor.variance(dim: Int, keepDim: Boolean): TensorType = wrap(JNoa.varDimTensor(tensor.tensorHandle, dim, keepDim)) - public abstract fun randNormal(shape: IntArray, device: Device): TensorType + public abstract fun randNormal(shape: IntArray, device: Device = Device.CPU): TensorType - public abstract fun randUniform(shape: IntArray, device: Device): TensorType + public abstract fun randUniform(shape: IntArray, device: Device = Device.CPU): TensorType public fun Tensor.randUniform(): TensorType = wrap(JNoa.randLike(tensor.tensorHandle)) @@ -301,7 +301,7 @@ protected constructor(scope: NoaScope) : return Pair(wrap(S), wrap(V)) } - public fun TensorType.autoGradient(variable: TensorType, retainGraph: Boolean): TensorType = + public fun TensorType.autoGradient(variable: TensorType, retainGraph: Boolean = false): TensorType = wrap(JNoa.autoGradTensor(tensorHandle, variable.tensorHandle, retainGraph)) public fun TensorType.autoHessian(variable: TensorType): TensorType = diff --git a/kmath-noa/src/test/kotlin/space/kscience/kmath/noa/TestTensor.kt b/kmath-noa/src/test/kotlin/space/kscience/kmath/noa/TestTensor.kt new file mode 100644 index 000000000..a02c2a5fb --- /dev/null +++ b/kmath-noa/src/test/kotlin/space/kscience/kmath/noa/TestTensor.kt @@ -0,0 +1,40 @@ +/* + * Copyright 2018-2021 KMath contributors. + * Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file. + */ + +package space.kscience.kmath.noa + +import kotlin.test.Test +import kotlin.test.assertEquals +import kotlin.test.assertTrue + + +internal fun NoaFloat.testingCopying(device: Device = Device.CPU): Unit { + val array = (1..24).map { 10f * it * it }.toFloatArray() + val shape = intArrayOf(2, 3, 4) + val tensor = copyFromArray(array, shape = shape, device = device) + val copyOfTensor = tensor.copy() + tensor[intArrayOf(1, 2, 3)] = 0.1f + assertTrue(copyOfTensor.copyToArray() contentEquals array) + assertEquals(0.1f, tensor[intArrayOf(1, 2, 3)]) + if(device != Device.CPU){ + val normalCpu = randNormal(intArrayOf(2, 3)) + val normalGpu = normalCpu.copyToDevice(device) + assertTrue(normalCpu.copyToArray() contentEquals normalGpu.copyToArray()) + + val uniformGpu = randUniform(intArrayOf(3,2),device) + val uniformCpu = uniformGpu.copyToDevice(Device.CPU) + assertTrue(uniformGpu.copyToArray() contentEquals uniformCpu.copyToArray()) + } +} + + +class TestTensor { + @Test + fun testCopying(): Unit = NoaFloat { + withCuda { device -> + testingCopying(device) + } + }!! +} \ No newline at end of file diff --git a/kmath-noa/src/test/kotlin/space/kscience/kmath/noa/TestUtils.kt b/kmath-noa/src/test/kotlin/space/kscience/kmath/noa/TestUtils.kt index 21fe71f9c..ac82b9425 100644 --- a/kmath-noa/src/test/kotlin/space/kscience/kmath/noa/TestUtils.kt +++ b/kmath-noa/src/test/kotlin/space/kscience/kmath/noa/TestUtils.kt @@ -46,7 +46,7 @@ class TestUtils { } @Test - fun testSetNumThreads(){ + fun testSetNumThreads() { val numThreads = 2 setNumThreads(numThreads) assertEquals(numThreads, getNumThreads()) @@ -59,6 +59,4 @@ class TestUtils { } }!! - - }