void TestMmGen(DeviceType device)
{
{
var x1 = FloatTensor.Ones(new long[] { 1, 2 }, deviceType: device);
var x2 = FloatTensor.Ones(new long[] { 2, 1 }, deviceType: device);
var y = x1.Mm(x2).ToDevice(DeviceType.CPU);
var ydata = y.Data <float>();
Assert.Equal(2.0f, ydata[0]);
}
//System.Runtime.InteropServices.ExternalException : addmm for CUDA tensors only supports floating - point types.Try converting the tensors with.float() at C:\w\b\windows\pytorch\aten\src\THC / generic / THCTensorMathBlas.cu:453
if (device == DeviceType.CPU)
{
var x1 = LongTensor.Ones(new long[] { 1, 2 }, deviceType: device);
var x2 = LongTensor.Ones(new long[] { 2, 1 }, deviceType: device);
var y = x1.Mm(x2).ToDevice(DeviceType.CPU);
var ydata = y.Data <long>();
Assert.Equal(2L, ydata[0]);
}
}
public void WriteAndReadLongTensorViaDiskFile()
{
const int size = 10;
var file = new DiskFile("test1E.dat", "rwb");
Assert.NotNull(file);
Assert.True(file.CanWrite);
var tensor0 = new LongTensor(size);
for (var i = 0; i < size; ++i)
{
tensor0[i] = (long)i;
}
file.WriteTensor(tensor0);
Assert.Equal(size * sizeof(long), file.Position);
file.Seek(0);
var tensor1 = new LongTensor(size);
var rd = file.ReadTensor(tensor1);
Assert.Equal(rd, size);
Assert.Equal(size * sizeof(long), file.Position);
for (var i = 0; i < rd; ++i)
{
Assert.Equal(tensor1[i], tensor1[i]);
}
file.Close();
Assert.False(file.IsOpen);
}
public void CreateLongTensorOnes()
{
var shape = new long[] { 2, 2 };
TorchTensor t = LongTensor.Ones(shape);
Assert.Equal(shape, t.Shape);
Assert.Equal((long)1, t[0, 0].DataItem <int>());
Assert.Equal((long)1, t[1, 1].DataItem <int>());
}
public void TestSparse()
{
using (var i = LongTensor.From(new long[] { 0, 1, 1, 2, 0, 2 }, new long[] { 2, 3 }))
using (var v = FloatTensor.From(new float[] { 3, 4, 5 }, new long[] { 3 }))
{
var sparse = FloatTensor.Sparse(i, v, new long[] { 2, 3 });
Assert.True(sparse.IsSparse);
Assert.False(i.IsSparse);
Assert.False(v.IsSparse);
Assert.Equal(sparse.SparseIndices.Data <long>().ToArray(), new long[] { 0, 1, 1, 2, 0, 2 });
Assert.Equal(sparse.SparseValues.Data <float>().ToArray(), new float[] { 3, 4, 5 });
}
}
public void RandomTest()
{
var res = FloatTensor.Random(new long[] { 2 });
Assert.Equal(new long[] { 2 }, res.Shape);
var res1 = ShortTensor.RandomIntegers(10, new long[] { 200 });
Assert.Equal(new long[] { 200 }, res1.Shape);
var res2 = IntTensor.RandomIntegers(10, new long[] { 200 });
Assert.Equal(new long[] { 200 }, res2.Shape);
var res3 = LongTensor.RandomIntegers(10, new long[] { 200 });
Assert.Equal(new long[] { 200 }, res3.Shape);
var res4 = ByteTensor.RandomIntegers(10, new long[] { 200 });
Assert.Equal(new long[] { 200 }, res4.Shape);
var res5 = SByteTensor.RandomIntegers(10, new long[] { 200 });
Assert.Equal(new long[] { 200 }, res5.Shape);
var res6 = HalfTensor.RandomIntegers(10, new long[] { 200 });
Assert.Equal(new long[] { 200 }, res6.Shape);
//var res7 = ComplexHalfTensor.RandomIntegers(10, new long[] { 200 });
//Assert.Equal(new long[] { 200 }, res7.Shape);
//var res8 = ComplexFloatTensor.RandomIntegers(10, new long[] { 200 });
//Assert.Equal(new long[] { 200 }, res8.Shape);
//var res9 = ComplexDoubleTensor.RandomIntegers(10, new long[] { 200 });
//Assert.Equal(new long[] { 200 }, res9.Shape);
}
/// <summary>
/// Write longs to the file from the given long tensor.
/// </summary>
/// <param name="tensor">A tensor containing data to be written to the file.</param>
/// <returns>The number of longs written.</returns>
public long WriteTensor(LongTensor tensor)
{
return(THFile_writeLongRaw(this.handle, tensor.Data, tensor.NumElements));
}
/// <summary>
/// Read longs from the file into the given long tensor.
/// </summary>
/// <param name="tensor">A tensor to place the data in after reading it from the file.</param>
/// <returns>The number of longs read.</returns>
public long ReadTensor(LongTensor tensor)
{
return(THFile_readLongRaw(this.handle, tensor.Data, tensor.NumElements));
}