public void Solve()
{
ColumnWiseMatrix A = GetInvertibleMatrix(128);
DeviceManager.CheckDeviceSanity();
var _A = A.GetMatrix <float>();
ColumnWiseMatrix B = GetInvertibleMatrix(128, 2345);
DeviceManager.CheckDeviceSanity();
var _B = B.GetMatrix <float>();
A.Solve(B);
DeviceManager.CheckDeviceSanity();
var _x = B.Get <float>();
var BSanity = A.Multiply(B);
var _BSanity = BSanity.GetMatrix <float>();
for (int i = 0; i < A.nRows; ++i)
{
for (int j = 0; j < A.nCols; ++j)
{
double expected = _B[i, j];
Assert.IsTrue(Math.Abs(_BSanity[i, j] - expected) <= 5e-5);
}
}
}
public void Invert()
{
ColumnWiseMatrix A = GetInvertibleMatrix(128);
DeviceManager.CheckDeviceSanity();
ColumnWiseMatrix AMinus1 = new ColumnWiseMatrix(A);
AMinus1.Invert();
DeviceManager.CheckDeviceSanity();
var eye = A.Multiply(AMinus1);
var _eye = eye.GetMatrix <float>();
var _A = A.GetMatrix <float>();
var _AMinus1 = AMinus1.GetMatrix <float>();
for (int i = 0; i < A.nRows; ++i)
{
for (int j = 0; j < A.nCols; ++j)
{
double expected = i == j ? 1.0 : 0.0;
Assert.IsTrue(Math.Abs(_eye[i, j] - expected) <= 5e-5);
}
}
}
public void Dot()
{
ColumnWiseMatrix m1 = new ColumnWiseMatrix(10, 10, 1.2345f);
DeviceManager.CheckDeviceSanity();
var _m1 = m1.GetMatrix <float>();
Vector v1 = new Vector(10, 9.8765f);
DeviceManager.CheckDeviceSanity();
var _v1 = v1.Get <float>();
var v2 = m1 * v1;
DeviceManager.CheckDeviceSanity();
var _v2 = v2.Get <float>();
for (int i = 0; i < m1.nRows; ++i)
{
double m1v1 = 0.0;
for (int j = 0; j < m1.nCols; ++j)
{
m1v1 += _m1[i, j] * _v1[j];
}
Assert.IsTrue(Math.Abs(m1v1 - _v2[i]) <= 5e-5);
}
}
public void Multiply()
{
ColumnWiseMatrix m1 = new ColumnWiseMatrix(10, 10, 1.2345f);
DeviceManager.CheckDeviceSanity();
var _m1 = m1.GetMatrix <float>();
ColumnWiseMatrix m2 = new ColumnWiseMatrix(10, 10, 9.8765f);
DeviceManager.CheckDeviceSanity();
var _m2 = m2.GetMatrix <float>();
var m3 = m1 * m2;
DeviceManager.CheckDeviceSanity();
var _m3 = m3.GetMatrix <float>();
for (int i = 0; i < m1.nRows; ++i)
{
for (int j = 0; j < m1.nCols; ++j)
{
double m1m2 = 0.0;
for (int k = 0; k < m1.nCols; ++k)
{
m1m2 += _m1[i, k] * _m2[k, j];
}
Assert.IsTrue(Math.Abs(m1m2 - _m3[i, j]) <= 5e-5);
}
}
}
private void Compress <T>(ColumnWiseMatrix denseMatrix) where T : struct, IEquatable <T>, IFormattable
{
var hostDenseMatrix = denseMatrix.GetMatrix <T>();
List <T> nonZeroValues = new List <T>();
List <int> nonZeroColumnIndices = new List <int>();
List <int> nNonZeroRows = new List <int>();
int nNonZeros = 0;
for (int i = 0; i < denseMatrix.nRows; i++)
{
for (int j = 0; j < denseMatrix.nCols; j++)
{
if (Math.Abs(Convert.ToDouble(hostDenseMatrix[i, j])) > 1e-7)
{
nNonZeros++;
nonZeroValues.Add(hostDenseMatrix[i, j]);
nonZeroColumnIndices.Add(j);
}
}
nNonZeroRows.Add(nNonZeros);
}
Buffer.size = (uint)nNonZeros;
values = new Vector(nonZeroValues.Count, memorySpace, mathDomain);
values.ReadFrom(nonZeroValues, nonZeroValues.Count);
this.nonZeroColumnIndices = new Vector(nonZeroColumnIndices.Count, memorySpace, MathDomain.Int);
this.nonZeroColumnIndices.ReadFrom(nonZeroColumnIndices, nonZeroColumnIndices.Count);
this.nNonZeroRows = new Vector(nNonZeroRows.Count, memorySpace, MathDomain.Int);
this.nNonZeroRows.ReadFrom(nNonZeroRows, nNonZeroRows.Count);
}
public void ColumnWiseArgAbsoluteMinMax()
{
ColumnWiseMatrix A = ColumnWiseMatrix.LinSpace(128, 64, -1, 1);
var _A = A.GetMatrix <float>();
var min = A.ColumnWiseAbsoluteMinimumIndex().GetRaw <int>();
var max = A.ColumnWiseAbsoluteMaximumIndex().GetRaw <int>();
int[] _min = new int[A.nCols];
int[] _max = new int[A.nCols];
for (int j = 0; j < A.nCols; j++)
{
_min[j] = _A.Column(j).AbsoluteMinimumIndex();
_max[j] = _A.Column(j).AbsoluteMaximumIndex();
Assert.AreEqual(min[j] - 1, _min[j]);
Assert.AreEqual(max[j] - 1, _max[j]);
}
}
public void AddMatrix()
{
ColumnWiseMatrix m1 = ColumnWiseMatrix.LinSpace(100, 20, -1.0, 1.0);
DeviceManager.CheckDeviceSanity();
var _m1 = m1.GetMatrix <float>();
ColumnWiseMatrix m2 = ColumnWiseMatrix.RandomGaussian(m1.nRows, m1.nCols, 1234);
DeviceManager.CheckDeviceSanity();
var _m2 = m2.GetMatrix <float>();
var m3 = m1 + m2;
DeviceManager.CheckDeviceSanity();
var _m3 = m3.GetMatrix <float>();
for (int i = 0; i < m1.nRows; ++i)
{
for (int j = 0; j < m1.nCols; ++j)
{
Assert.IsTrue(Math.Abs(_m3[i, j] - _m1[i, j] - _m2[i, j]) <= 3e-7, String.Format("i({0}) j({1}) err({2})", i, j, Math.Abs(_m3[i, j] - _m1[i, j] - _m2[i, j])));
}
}
var m4 = ColumnWiseMatrix.Add(m1, m2, alpha: 2.0);
DeviceManager.CheckDeviceSanity();
var _m4 = m4.GetMatrix <float>();
for (int i = 0; i < m1.nRows; ++i)
{
for (int j = 0; j < m1.nCols; ++j)
{
Assert.IsTrue(Math.Abs(_m4[i, j] - _m1[i, j] - 2.0 * _m2[i, j]) <= 5e-7, String.Format("i({0}) j({1}) err({2})", i, j, Math.Abs(_m4[i, j] - _m1[i, j] - 2.0 * _m2[i, j])));
}
}
}
public void Multiply()
{
int[] _NonZeroCols = new int[] { 0, 1, 1, 3, 2, 3, 4, 5 };
Vector gpuNonZeroCols = new Vector(_NonZeroCols);
int[] _NonZeroRows = new int[] { 0, 2, 4, 7, 8 };
Vector gpuNonZeroRows = new Vector(_NonZeroRows);
CompressedSparseRowMatrix m1 = new CompressedSparseRowMatrix(4, 6, gpuNonZeroCols, gpuNonZeroRows, 1.2345f, MathDomain.Float);
DeviceManager.CheckDeviceSanity();
var _m1 = m1.GetMatrix <float>();
ColumnWiseMatrix m2 = new ColumnWiseMatrix(6, 8, 9.8765f, MemorySpace.Device, MathDomain.Float);
DeviceManager.CheckDeviceSanity();
var _m2 = m2.GetMatrix <float>();
var m3 = m1 * m2;
DeviceManager.CheckDeviceSanity();
var _m3 = m3.GetMatrix <float>();
for (int i = 0; i < m1.nRows; ++i)
{
for (int j = 0; j < m2.nCols; ++j)
{
double m1m2 = 0.0;
for (int k = 0; k < m1.nCols; ++k)
{
m1m2 += _m1[i, k] * _m2[k, j];
}
Assert.IsTrue(Math.Abs(m1m2 - _m3[i, j]) <= 5e-5);
}
}
}