public void WriteAndReadDoubleTensorViaDiskFile()
{
const int size = 10;
var file = new DiskFile("test20.dat", "rwb");
Assert.NotNull(file);
Assert.True(file.CanWrite);
var tensor0 = new DoubleTensor(size);
for (var i = 0; i < size; ++i)
{
tensor0[i] = (double)i;
}
file.WriteTensor(tensor0);
Assert.Equal(size * sizeof(double), file.Position);
file.Seek(0);
var tensor1 = new DoubleTensor(size);
var rd = file.ReadTensor(tensor1);
Assert.Equal(rd, size);
Assert.Equal(size * sizeof(double), file.Position);
for (var i = 0; i < rd; ++i)
{
Assert.Equal(tensor1[i], tensor1[i]);
}
file.Close();
Assert.False(file.IsOpen);
}
public void DoubleTensorArcTrigonometrics()
{
var x1 = DoubleTensor.Range(0.0f, 0.99f, 0.05f);
Assert.IsNotNull(x1);
Assert.AreEqual(1, x1.Shape.Length);
var xsin = x1.Asin();
Assert.AreEqual(x1.Shape.Length, xsin.Shape.Length);
Assert.AreEqual(x1.Shape[0], xsin.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.IsTrue(BasicTensorAPI.IsApproximatelyEqual(Math.Asin(x1[i]), (double)xsin[i]));
}
var xcos = x1.Acos();
Assert.AreEqual(x1.Shape.Length, xcos.Shape.Length);
Assert.AreEqual(x1.Shape[0], xcos.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.IsTrue(BasicTensorAPI.IsApproximatelyEqual(Math.Acos(x1[i]), (double)xcos[i]));
}
var xtan = x1.Atan();
Assert.AreEqual(x1.Shape.Length, xtan.Shape.Length);
Assert.AreEqual(x1.Shape[0], xtan.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.IsTrue(BasicTensorAPI.IsApproximatelyEqual(Math.Atan(x1[i]), (double)xtan[i]));
}
}
public void DiagDouble()
{
var x1 = new DoubleTensor(9);
for (var i = 0; i < x1.Shape[0]; ++i)
{
x1[i] = i + 1;
}
x1.Resize2d(3, 3);
var diag0 = x1.Diagonal(0);
var diag1 = x1.Diagonal(1);
Assert.AreEqual(1, diag0.Shape.Length);
Assert.AreEqual(3, diag0.Shape[0]);
Assert.AreEqual(1, diag1.Shape.Length);
Assert.AreEqual(2, diag1.Shape[0]);
Assert.AreEqual(1, diag0[0]);
Assert.AreEqual(5, diag0[1]);
Assert.AreEqual(9, diag0[2]);
Assert.AreEqual(2, diag1[0]);
Assert.AreEqual(6, diag1[1]);
}
public void DoubleTensorHyperbolics()
{
var x1 = DoubleTensor.Range(2f, 15f, 1f);
Assert.IsNotNull(x1);
Assert.AreEqual(1, x1.Shape.Length);
var xsin = x1.Sinh();
Assert.AreEqual(x1.Shape.Length, xsin.Shape.Length);
Assert.AreEqual(x1.Shape[0], xsin.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.IsTrue(BasicTensorAPI.IsApproximatelyEqual(Math.Sinh(x1[i]), (double)xsin[i]));
}
var xcos = x1.Cosh();
Assert.AreEqual(x1.Shape.Length, xcos.Shape.Length);
Assert.AreEqual(x1.Shape[0], xcos.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.IsTrue(BasicTensorAPI.IsApproximatelyEqual(Math.Cosh(x1[i]), (double)xcos[i]));
}
var xtan = x1.Tanh();
Assert.AreEqual(x1.Shape.Length, xtan.Shape.Length);
Assert.AreEqual(x1.Shape[0], xtan.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.IsTrue(BasicTensorAPI.IsApproximatelyEqual(Math.Tanh(x1[i]), (double)xtan[i]));
}
}
public void DoubleTensorTrigonometrics()
{
var x1 = DoubleTensor.Range(2f, 15f, 1f);
Assert.NotNull(x1);
Assert.True(1 == x1.Shape.Length);
var xsin = x1.Sin();
Assert.Equal(x1.Shape.Length, xsin.Shape.Length);
Assert.Equal(x1.Shape[0], xsin.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.True(BasicTensorAPI.IsApproximatelyEqual(Math.Sin(x1[i]), (double)xsin[i]));
}
var xcos = x1.Cos();
Assert.Equal(x1.Shape.Length, xcos.Shape.Length);
Assert.Equal(x1.Shape[0], xcos.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.True(BasicTensorAPI.IsApproximatelyEqual(Math.Cos(x1[i]), (double)xcos[i]));
}
var xtan = x1.Tan();
Assert.Equal(x1.Shape.Length, xtan.Shape.Length);
Assert.Equal(x1.Shape[0], xtan.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.True(BasicTensorAPI.IsApproximatelyEqual(Math.Tan(x1[i]), (double)xtan[i]));
}
}
public void DoubleTensorPower()
{
var x1 = DoubleTensor.Range(2f, 15f, 1f);
Assert.IsNotNull(x1);
Assert.AreEqual(1, x1.Shape.Length);
var x2 = x1.Pow(2.0f);
Assert.AreEqual(x1.Shape.Length, x2.Shape.Length);
Assert.AreEqual(x1.Shape[0], x2.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.IsTrue(BasicTensorAPI.IsApproximatelyEqual(Math.Pow(x1[i], 2.0f), x2[i]));
}
var x3 = x1.TPow(2.0f);
Assert.AreEqual(x1.Shape.Length, x3.Shape.Length);
Assert.AreEqual(x1.Shape[0], x3.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.IsTrue(BasicTensorAPI.IsApproximatelyEqual(Math.Pow(2.0f, x1[i]), x3[i]));
}
}
public void TestMemoryDisposalOnes()
{
for (int i = 0; i < 1024; i++)
{
var x = DoubleTensor.Ones(new long[] { 1024, 1024 });
x.Dispose();
}
}
public void RangeDouble()
{
var x1 = DoubleTensor.Range(0f, 100f, 1f);
for (int i = 0; i < x1.Shape[0]; ++i)
{
Assert.AreEqual(i, x1[i]);
}
}
public void TestMemoryDisposalZeros()
{
for (int i = 0; i < 1024; i++)
{
var x = DoubleTensor.Zeros(new long[] { 1024, 1024 });
x.Dispose();
//System.GC.Collect();
}
}
public void SignDouble()
{
var x1 = DoubleTensor.Range(-15f, 15f, 1f);
var x2 = x1.Sign();
for (var i = 0; i < x2.Shape[0]; ++i)
{
var sign = (x1[i] < 0) ? -1 : (x1[i] == 0) ? 0 : 1;
Assert.AreEqual(sign, x2[i]);
}
}
public void TestMemoryDisposalScalarTensors()
{
for (int i = 0; i < 5; i++)
{
for (int j = 0; j < 1000 * 100; j++)
{
var x = DoubleTensor.From(i * j * 3.1415);
x.Dispose();
}
//System.GC.Collect();
}
}
public void CreateDoubleTensorFromRange()
{
var x1 = DoubleTensor.Range(0f, 150f, 5f);
Assert.IsNotNull(x1);
Assert.AreEqual(1, x1.Shape.Length);
float start = 0f;
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.AreEqual(start + 5f * i, x1[i]);
}
}
public void ReshapeDoubleTensor()
{
var x2 = new DoubleTensor(200);
Assert.AreEqual(1, x2.Shape.Length);
Assert.AreEqual(200, x2.Shape[0]);
for (var i = 0; i < x2.Shape[0]; ++i)
{
x2[i] = i * 47.11f;
}
x2.Resize2d(10, 20);
Assert.AreEqual(2, x2.Shape.Length);
Assert.AreEqual(10, x2.Shape[0]);
Assert.AreEqual(20, x2.Shape[1]);
x2.Resize3d(4, 25, 2);
Assert.AreEqual(3, x2.Shape.Length);
Assert.AreEqual(4, x2.Shape[0]);
Assert.AreEqual(25, x2.Shape[1]);
Assert.AreEqual(2, x2.Shape[2]);
x2.Resize4d(4, 5, 5, 2);
Assert.AreEqual(4, x2.Shape.Length);
Assert.AreEqual(4, x2.Shape[0]);
Assert.AreEqual(5, x2.Shape[1]);
Assert.AreEqual(5, x2.Shape[2]);
Assert.AreEqual(2, x2.Shape[3]);
x2.Resize5d(2, 2, 5, 5, 2);
Assert.AreEqual(5, x2.Shape.Length);
Assert.AreEqual(2, x2.Shape[0]);
Assert.AreEqual(2, x2.Shape[1]);
Assert.AreEqual(5, x2.Shape[2]);
Assert.AreEqual(5, x2.Shape[3]);
Assert.AreEqual(2, x2.Shape[4]);
// Check that the values are retained across resizings.
x2.Resize1d(200);
Assert.AreEqual(1, x2.Shape.Length);
Assert.AreEqual(200, x2.Shape[0]);
for (var i = 0; i < x2.Shape[0]; ++i)
{
Assert.AreEqual(i * 47.11f, x2[i]);
}
}
public void CreateDoubleTensor()
{
var x1 = new DoubleTensor(10);
var x2 = new DoubleTensor(10, 20);
var x1Shape = x1.Shape;
var x2Shape = x2.Shape;
Assert.AreEqual(1, x1Shape.Length);
Assert.AreEqual(2, x2Shape.Length);
Assert.AreEqual(10, x1Shape[0]);
Assert.AreEqual(10, x2Shape[0]);
Assert.AreEqual(20, x2Shape[1]);
}
public void DoubleTensorLog2()
{
var x1 = DoubleTensor.Range(2f, 100f, 1f);
Assert.NotNull(x1);
Assert.True(1 == x1.Shape.Length);
var x2 = x1.Log2();
Assert.Equal(x1.Shape.Length, x2.Shape.Length);
Assert.Equal(x1.Shape[0], x2.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.True(BasicTensorAPI.IsApproximatelyEqual(Math.Log(x1[i], 2.0), (double)x2[i]));
}
}
public void DoubleTensorExp()
{
var x1 = DoubleTensor.Range(2f, 15f, 1f);
Assert.IsNotNull(x1);
Assert.AreEqual(1, x1.Shape.Length);
var x2 = x1.Exp();
Assert.AreEqual(x1.Shape.Length, x2.Shape.Length);
Assert.AreEqual(x1.Shape[0], x2.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.IsTrue(BasicTensorAPI.IsApproximatelyEqual(Math.Exp(x1[i]), (double)x2[i]));
}
}
public void TestSaveLoadTensorDouble()
{
var file = ".saveload.double.ts";
if (File.Exists(file))
{
File.Delete(file);
}
var tensor = DoubleTensor.Ones(new long[] { 5, 6 });
tensor.Save(file);
var tensorLoaded = TorchTensor.Load(file);
File.Delete(file);
Assert.NotNull(tensorLoaded);
Assert.Equal(tensorLoaded.Type, tensor.Type);
Assert.Equal(tensorLoaded, tensor);
}
public void IdentityDouble()
{
var x1 = DoubleTensor.Eye(10, 10);
for (int i = 0; i < 10; ++i)
{
for (int j = 0; j < 10; ++j)
{
if (i == j)
{
Assert.AreEqual(1, x1[i, j]);
}
else
{
Assert.AreEqual(0, x1[i, j]);
}
}
}
}
public void CreateDoubleTensorLike()
{
var x1 = new DoubleTensor(200, 200);
var x2 = x1.OnesLike();
var x3 = x1.ZerosLike();
Assert.IsNotNull(x1);
Assert.IsNotNull(x2);
Assert.IsNotNull(x3);
Assert.AreEqual(x1.Shape.Length, x2.Shape.Length);
Assert.AreEqual(x1.Shape.Length, x3.Shape.Length);
x2.Resize1d(200 * 200);
x3.Resize1d(200 * 200);
for (var i = 0; i < x2.Shape[0]; ++i)
{
Assert.AreEqual(1, x2[i]);
Assert.AreEqual(0, x3[i]);
}
}
public void ConcatenateDouble()
{
var x1 = new DoubleTensor(9);
var x2 = new DoubleTensor(9);
for (var i = 0; i < x1.Shape[0]; ++i)
{
x1[i] = i + 1;
x2[i] = i + 1 + x1.Shape[0];
}
var x3 = x1.Concatenate(x2, 0);
Assert.AreEqual(1, x3.Shape.Length);
Assert.AreEqual(18, x3.Shape[0]);
for (var i = 0; i < x3.Shape[0]; ++i)
{
Assert.AreEqual(i + 1, x3[i]);
}
}
/// <summary>
/// Read doubles from the file into the given double tensor.
/// </summary>
/// <param name="tensor">A tensor to place the data in after reading it from the file.</param>
/// <returns>The number of doubles read.</returns>
public long ReadTensor(DoubleTensor tensor)
{
return(THFile_readDoubleRaw(this.handle, tensor.Data, tensor.NumElements));
}
public void DoubleTensorUnaries()
{
var x1 = DoubleTensor.Range(2f, 15f, 1f);
Assert.IsNotNull(x1);
Assert.AreEqual(1, x1.Shape.Length);
var xsqrt = x1.Sqrt();
Assert.AreEqual(x1.Shape.Length, xsqrt.Shape.Length);
Assert.AreEqual(x1.Shape[0], xsqrt.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.IsTrue(BasicTensorAPI.IsApproximatelyEqual(Math.Sqrt(x1[i]), (double)xsqrt[i]));
}
x1 = DoubleTensor.Range(-15f, 15f, .1f);
var xceil = x1.Ceil();
Assert.AreEqual(x1.Shape.Length, xceil.Shape.Length);
Assert.AreEqual(x1.Shape[0], xceil.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.IsTrue(BasicTensorAPI.IsApproximatelyEqual(Math.Ceiling(x1[i]), (double)xceil[i]));
}
var xfloor = x1.Floor();
Assert.AreEqual(x1.Shape.Length, xfloor.Shape.Length);
Assert.AreEqual(x1.Shape[0], xfloor.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.IsTrue(BasicTensorAPI.IsApproximatelyEqual(Math.Floor(x1[i]), (double)xfloor[i]));
}
var xabs = x1.Abs();
Assert.AreEqual(x1.Shape.Length, xabs.Shape.Length);
Assert.AreEqual(x1.Shape[0], xabs.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.IsTrue(BasicTensorAPI.IsApproximatelyEqual(Math.Abs(x1[i]), (double)xabs[i]));
}
var xneg = x1.neg();
Assert.AreEqual(x1.Shape.Length, xneg.Shape.Length);
Assert.AreEqual(x1.Shape[0], xneg.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Assert.IsTrue(BasicTensorAPI.IsApproximatelyEqual(-x1[i], (double)xneg[i]));
}
#if false
// DISABLED: libtorch appears to round away from zero for N.5, which means that comparing
// against Math.Round() will fail.
x1 = DoubleTensor.Range(0f, 15f, .1f);
var xrnd = x1.Round();
Assert.AreEqual(x1.Shape.Length, xrnd.Shape.Length);
Assert.AreEqual(x1.Shape[0], xrnd.Shape[0]);
for (var i = 0; i < x1.Shape[0]; ++i)
{
Console.WriteLine($"{x1[i]}, {Math.Round(x1[i])}, {(double)xrnd[i]}");
Assert.IsTrue(BasicTensorAPI.IsApproximatelyEqual(Math.Round(x1[i]), (double)xrnd[i]));
}
#endif
}
/// <summary>
/// Write doubles to the file from the given double tensor.
/// </summary>
/// <param name="tensor">A tensor containing data to be written to the file.</param>
/// <returns>The number of doubles written.</returns>
public long WriteTensor(DoubleTensor tensor)
{
return(THFile_writeDoubleRaw(this.handle, tensor.Data, tensor.NumElements));
}
