public void VectorRotate()
{
const int blockCount = 1;
var a = _cpu.CreateVector(4, i => i + 1).AsIndexable();
using (var gpuA = _cuda.CreateVector(a)) {
a.RotateInPlace(blockCount);
gpuA.RotateInPlace(blockCount);
FloatingPointHelper.AssertEqual(gpuA.AsIndexable(), a.AsIndexable());
}
}
public void VectorRotate2()
{
Load();
const int blockCount = 2;
var a = _cpu.CreateVector(8, i => i + 1).AsIndexable();
using var gpuA = _cuda.CreateVector(a);
a.RotateInPlace(blockCount);
gpuA.RotateInPlace(blockCount);
FloatingPointHelper.AssertEqual(gpuA.AsIndexable(), a.AsIndexable());
Cleanup();
}
void _Transpose(int rows, int columns)
{
var a = _cpu.CreateMatrix(rows, columns, (j, k) => k).AsIndexable();
var aT = a.Transpose();
IIndexableMatrix gpuResults;
using (var gpuA = _cuda.CreateMatrix(a))
using (var gpuAT = gpuA.Transpose())
gpuResults = gpuAT.AsIndexable();
FloatingPointHelper.AssertEqual(gpuResults, aT.AsIndexable());
}
public void MatrixGetRowSegment()
{
var a = _cpu.CreateMatrix(12, 18, (x, y) => x * 2 + y).AsIndexable();
var r = a.GetRowSegment(1, 2, 5).AsIndexable();
IIndexableVector gpuResults;
using (var gpuA = _cuda.CreateMatrix(a)) {
gpuResults = gpuA.GetRowSegment(1, 2, 5).AsIndexable();
}
FloatingPointHelper.AssertEqual(r, gpuResults);
}
public void MatrixGetColumnSegment()
{
var a = _cpu.CreateMatrix(9, 8, (x, y) => (x + 1) * (y + 1)).AsIndexable();
var r = a.GetColumnSegment(1, 2, 5).AsIndexable();
IIndexableVector gpuResults;
using (var gpuA = _cuda.CreateMatrix(a)) {
gpuResults = gpuA.GetColumnSegment(1, 2, 5).AsIndexable();
}
FloatingPointHelper.AssertEqual(r, gpuResults);
}
public void VectorL1Norm()
{
Load();
var distribution = new Normal(0, 5);
var a = _cpu.CreateVector(5000, i => Convert.ToSingle(distribution.Sample())).AsIndexable();
var v1 = a.L1Norm();
float v2;
using (var gpuA = _cuda.CreateVector(a))
v2 = gpuA.L1Norm();
FloatingPointHelper.AssertEqual(v1, v2);
Cleanup();
}
public void VectorAverage()
{
Load();
var distribution = new Normal(0, 5);
var a = _cpu.CreateVector(5000, i => Convert.ToSingle(distribution.Sample())).AsIndexable();
var average = a.Average();
float average2;
using (var gpuA = _cuda.CreateVector(a))
average2 = gpuA.Average();
FloatingPointHelper.AssertEqual(average, average2, 7);
Cleanup();
}
public void VectorReverse()
{
var distribution = new Normal(0, 5);
var a = _cpu.CreateVector(128, i => (float)distribution.Sample()).AsIndexable();
var cpuResult = a.Reverse().AsIndexable();
IIndexableVector result;
using (var gpuA = _cuda.CreateVector(a)) {
var gpuResult = gpuA.Reverse();
result = gpuResult.AsIndexable();
}
FloatingPointHelper.AssertEqual(result, cpuResult);
}
public void VectorStdDev()
{
Load();
var distribution = new Normal(0, 5);
var a = _cpu.CreateVector(5000, i => Convert.ToSingle(distribution.Sample())).AsIndexable();
var stdDev = a.StdDev(null);
float stdDev2;
using (var gpuA = _cuda.CreateVector(a))
stdDev2 = gpuA.StdDev(null);
FloatingPointHelper.AssertEqual(stdDev, stdDev2);
Cleanup();
}
public void VectorSqrt()
{
var a = _cpu.CreateVector(10, i => i * 2).AsIndexable();
var b = a.Sqrt().AsIndexable();
IIndexableVector gpuResults;
using (var gpuA = _cuda.CreateVector(a))
using (var gpuB = gpuA.Sqrt()) {
gpuResults = gpuB.AsIndexable();
}
FloatingPointHelper.AssertEqual(b, gpuResults);
}
public void MatrixRowL2Norm()
{
var a = _cpu.CreateMatrix(6, 3, (x, y) => x * 2 + y).AsIndexable();
var r = a.RowL2Norm().AsIndexable();
IIndexableVector gpuResults;
using (var gpuA = _cuda.CreateMatrix(a))
using (var norm = gpuA.RowL2Norm()) {
gpuResults = norm.AsIndexable();
}
FloatingPointHelper.AssertEqual(r, gpuResults);
}
public void MatrixDiagonal()
{
var a = _cpu.CreateMatrix(6, 6, (x, y) => x * 2 + y).AsIndexable();
var d = a.Diagonal().AsIndexable();
IIndexableVector gpuResults;
using (var gpuA = _cuda.CreateMatrix(a))
using (var diagonal = gpuA.Diagonal()) {
gpuResults = diagonal.AsIndexable();
}
FloatingPointHelper.AssertEqual(d, gpuResults);
}
public void TestManhattanDistance()
{
var distribution = new Normal(0, 5);
var vectors = Enumerable.Range(0, 10).Select(i => _cpu.CreateVector(100, j => Convert.ToSingle(distribution.Sample())).AsIndexable()).ToList();
var compareTo = Enumerable.Range(0, 20).Select(i => _cpu.CreateVector(100, j => Convert.ToSingle(distribution.Sample())).AsIndexable()).ToList();
var distances = _cpu.CalculateDistances(vectors, compareTo, DistanceMetric.Manhattan);
var gpuVectors = vectors.Select(v => _cuda.CreateVector(v)).ToList();
var gpuCompareTo = compareTo.Select(v => _cuda.CreateVector(v)).ToList();
var gpuDistances = _cuda.CalculateDistances(gpuVectors, gpuCompareTo, DistanceMetric.Manhattan);
FloatingPointHelper.AssertEqual(distances.AsIndexable(), gpuDistances.AsIndexable());
}
public void MatrixColumnSums()
{
var a = _cpu.CreateMatrix(2, 5, (j, k) => k).AsIndexable();
var colSums = a.ColumnSums().AsIndexable();
IIndexableVector gpuResults;
using (var gpuA = _cuda.CreateMatrix(a))
using (var gpuColSums = gpuA.ColumnSums())
gpuResults = gpuColSums.AsIndexable();
FloatingPointHelper.AssertEqual(gpuResults, colSums);
}
public void VectorColumnMatrix()
{
var a = _cpu.CreateVector(5, i => i).AsIndexable();
var matrix = a.ReshapeAsColumnMatrix().AsIndexable();
IIndexableMatrix gpuResults;
using (var gpuA = _cuda.CreateVector(a))
using (var gpuB = gpuA.ReshapeAsColumnMatrix())
gpuResults = gpuB.AsIndexable();
FloatingPointHelper.AssertEqual(matrix, gpuResults);
}
public void TensorIm2Col()
{
var normalDistribution = new Normal(0, 1);
using (var cpuTensor = _cpu.Create3DTensor(Enumerable.Range(0, 3).Select(i => _cpu.CreateMatrix(4, 4, (j, k) => Convert.ToSingle(normalDistribution.Sample()))).ToList()))
using (var gpuTensor = _cuda.Create3DTensor(cpuTensor.AsIndexable()))
using (var cpuMatrix = cpuTensor.Im2Col(2, 2, 2))
using (var gpuMatrix = gpuTensor.Im2Col(2, 2, 2)) {
var cpu = cpuMatrix.AsIndexable();
var gpu = gpuMatrix.AsIndexable();
FloatingPointHelper.AssertEqual(cpu, gpu);
}
}
public void MatrixPow()
{
var a = _cpu.CreateMatrix(6, 3, (x, y) => x * 2 + y).AsIndexable();
const float OPERAND = 2.5f;
var r = a.Pow(OPERAND).AsIndexable();
IIndexableMatrix gpuResults;
using (var gpuA = _cuda.CreateMatrix(a))
using (var pow = gpuA.Pow(OPERAND)) {
gpuResults = pow.AsIndexable();
}
FloatingPointHelper.AssertEqual(r, gpuResults);
}
public void MatrixL1Regularisation()
{
var a = _cpu.CreateMatrix(6, 3, (x, y) => x * 2 + y).AsIndexable();
const float OPERAND = 2f;
IIndexableMatrix gpuResults;
using (var gpuA = _cuda.CreateMatrix(a)) {
gpuA.L1Regularisation(OPERAND);
gpuResults = gpuA.AsIndexable();
}
a.L1Regularisation(OPERAND);
FloatingPointHelper.AssertEqual(a, gpuResults);
}
public void MatrixClear()
{
var a = _cpu.CreateMatrix(15, 23, (j, k) => k + 1).AsIndexable();
IIndexableMatrix gpuResults;
using (var gpuA = _cuda.CreateMatrix(a)) {
gpuA.Clear();
gpuResults = gpuA.AsIndexable();
}
a.Clear();
FloatingPointHelper.AssertEqual(gpuResults, a);
}
public void MatrixNewMatrixFromColumns()
{
var cols = new[] { 1, 2, 9 };
var a = _cpu.CreateMatrix(12, 13, (j, k) => (k + 1) * (j + 1)).AsIndexable();
var results = a.GetNewMatrixFromColumns(cols).AsIndexable();
IIndexableMatrix gpuResults;
using (var gpuA = _cuda.CreateMatrix(a))
using (var m = gpuA.GetNewMatrixFromColumns(cols))
gpuResults = m.AsIndexable();
FloatingPointHelper.AssertEqual(gpuResults, results);
}
public void MatrixLeakyRELUDerivative()
{
var normalDistribution = new Normal(0, 1);
var a = _cpu.CreateMatrix(3, 7, (j, k) => Convert.ToSingle(normalDistribution.Sample())).AsIndexable();
var b = a.LeakyReluDerivative().AsIndexable();
IIndexableMatrix gpuResults;
using (var gpuA = _cuda.CreateMatrix(a))
using (var relu = gpuA.LeakyReluDerivative())
gpuResults = relu.AsIndexable();
FloatingPointHelper.AssertEqual(gpuResults, b);
}
public void MatrixRow()
{
const int INDEX = 11;
var a = _cpu.CreateMatrix(20, 50, (j, k) => k * j).AsIndexable();
var row = a.Row(INDEX).AsIndexable();
IIndexableVector gpuResults;
using (var gpuA = _cuda.CreateMatrix(a))
using (var gpuRow = gpuA.Row(INDEX))
gpuResults = gpuRow.AsIndexable();
FloatingPointHelper.AssertEqual(gpuResults, row);
}
public void VectorSigmoid()
{
var a = _cpu.CreateVector(1000, i => i).AsIndexable();
var results = a.Sigmoid().AsIndexable();
IIndexableVector gpuResults;
using (var gpuA = _cuda.CreateVector(a))
using (var gpuB = gpuA.Sigmoid()) {
gpuResults = gpuB.AsIndexable();
}
FloatingPointHelper.AssertEqual(results, gpuResults);
}
public void MatrixToVector()
{
var matrix = _cpu.CreateMatrix(3, 4, (x, y) => (x + 1) * (y + 1)).AsIndexable();
var vector = matrix.ReshapeAsVector();
var matrix2 = vector.ReshapeAsMatrix(3, 4);
FloatingPointHelper.AssertEqual(matrix.AsIndexable(), matrix2.AsIndexable());
using (var gpuMatrix = _cuda.CreateMatrix(matrix.AsIndexable()))
using (var gpuVector = gpuMatrix.ReshapeAsVector())
using (var gpuMatrix2 = gpuVector.ReshapeAsMatrix(3, 4)) {
FloatingPointHelper.AssertEqual(gpuMatrix.AsIndexable(), gpuMatrix2.AsIndexable());
}
}
public void VectorAddScalar()
{
var a = _cpu.CreateVector(1000, i => i).AsIndexable();
IIndexableVector gpuResults;
using (var gpuA = _cuda.CreateVector(a)) {
gpuA.Add(0.5f);
gpuResults = gpuA.AsIndexable();
}
a.Add(0.5f);
FloatingPointHelper.AssertEqual(a, gpuResults);
}
public void MatrixSoftmaxActivation()
{
var normalDistribution = new Normal(0, 1);
var a = _cpu.CreateMatrix(3, 7, (j, k) => Convert.ToSingle(normalDistribution.Sample())).AsIndexable();
var b = a.SoftmaxActivation().AsIndexable();
IIndexableMatrix gpuResults;
using (var gpuA = _cuda.CreateMatrix(a))
using (var softmax = gpuA.SoftmaxActivation())
gpuResults = softmax.AsIndexable();
FloatingPointHelper.AssertEqual(gpuResults, b);
}
public void MatrixTransposeAndMultiplication2()
{
var a = _cpu.CreateMatrix(2, 6, (j, k) => k).AsIndexable();
var b = _cpu.CreateMatrix(2, 5, (j, k) => j).AsIndexable();
var cpuResults = a.TransposeThisAndMultiply(b);
IIndexableMatrix gpuResults;
using (var gpuA = _cuda.CreateMatrix(a))
using (var gpuB = _cuda.CreateMatrix(b))
using (var gpuC = gpuA.TransposeThisAndMultiply(gpuB))
gpuResults = gpuC.AsIndexable();
FloatingPointHelper.AssertEqual(gpuResults, cpuResults.AsIndexable());
}
public void VectorMinMax()
{
Load();
var distribution = new Normal(0, 5);
var a = _cpu.CreateVector(5000, i => Convert.ToSingle(distribution.Sample())).AsIndexable();
var minMax = a.GetMinMax();
(float Min, float Max)minMax2;
using (var gpuA = _cuda.CreateVector(a))
minMax2 = gpuA.GetMinMax();
FloatingPointHelper.AssertEqual(minMax.Min, minMax2.Min);
FloatingPointHelper.AssertEqual(minMax.Max, minMax2.Max);
Cleanup();
}
public void TensorCreateFromMatrix()
{
const int DEPTH = 3, ROWS = 4, COLUMNS = 4;
var cpuTensor = _cpu.Create3DTensor(Enumerable.Range(0, DEPTH).Select(i => _cpu.CreateMatrix(ROWS, COLUMNS, (j, k) => (i + 1) * (j + 1) * (k + 1))).ToList());
var cpuMatrix = cpuTensor.ConvertToMatrix();
var cpuTensor2 = cpuMatrix.ConvertTo3DTensor(ROWS, COLUMNS);
FloatingPointHelper.AssertEqual(cpuTensor.AsIndexable(), cpuTensor2.AsIndexable());
using (var gpuMatrix = _cuda.CreateMatrix(cpuMatrix.AsIndexable()))
using (var gpuTensor2 = gpuMatrix.ConvertTo3DTensor(ROWS, COLUMNS)) {
FloatingPointHelper.AssertEqual(cpuTensor.AsIndexable(), gpuTensor2.AsIndexable());
}
}
public void MatrixColumn()
{
const int INDEX = 7;
var a = _cpu.CreateMatrix(13, 17, (j, k) => (j + 1) * (k + 1)).AsIndexable();
var row = a.Column(INDEX).AsIndexable();
IIndexableVector gpuResults;
using (var gpuA = _cuda.CreateMatrix(a))
using (var gpuCol = gpuA.Column(INDEX))
gpuResults = gpuCol.AsIndexable();
FloatingPointHelper.AssertEqual(gpuResults, row);
}
