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Fix HFFT tests to use complex input tensors #1533

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Fix HFFT tests to use complex input tensors #1533

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95d6d4d
Fix HFFT tests to use complex input tensors
alinpahontu2912 Feb 16, 2026
ff3c8d9
Fix Float32HFFTN test to call hfftn instead of hfft2
alinpahontu2912 Feb 17, 2026
f3bab3e
Address PR comments: Remove redundant tests and rename others
alinpahontu2912 Feb 19, 2026
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56 changes: 15 additions & 41 deletions test/TorchSharpTest/TestTorchTensor.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -6938,32 +6938,6 @@ public void Float64FFT()
Assert.Equal(ScalarType.ComplexFloat64, inverted.dtype);
}

[Fact]
[TestOf(nameof(fft.hfft))]
public void Float32HFFT()
{
var input = torch.arange(4);
var output = fft.hfft(input);
Assert.Equal(6, output.shape[0]);
Assert.Equal(ScalarType.Float32, output.dtype);

var inverted = fft.ifft(output);
Assert.Equal(ScalarType.ComplexFloat32, inverted.dtype);
}

[Fact]
[TestOf(nameof(fft.hfft))]
public void Float64HFFT()
{
var input = torch.arange(4, float64);
var output = fft.hfft(input);
Assert.Equal(6, output.shape[0]);
Assert.Equal(ScalarType.Float64, output.dtype);

var inverted = fft.ifft(output);
Assert.Equal(ScalarType.ComplexFloat64, inverted.dtype);
}

[Fact]
[TestOf(nameof(fft.rfft))]
public void Float32RFFT()
Expand Down Expand Up @@ -7201,12 +7175,12 @@ public void Float64RFFTN()

[Fact]
[TestOf(nameof(fft.hfft2))]
public void Float32HFFT2()
public void ComplexFloat32HFFT2()
{
var input = torch.rand(new long[] { 5, 5, 5, 5 });
var input = torch.rand(new long[] { 5, 5, 5, 5 }, complex64);
var output = fft.hfft2(input);
Assert.Equal(new long[] { 5, 5, 5, 8 }, output.shape);
Assert.Equal(input.dtype, output.dtype);
Assert.Equal(ScalarType.Float32, output.dtype);

var inverted = fft.ihfft2(output);
Assert.Equal(new long[] { 5, 5, 5, 5 }, inverted.shape);
Expand All @@ -7215,44 +7189,44 @@ public void Float32HFFT2()

[Fact]
[TestOf(nameof(fft.hfft2))]
public void Float64HFFT2()
public void ComplexFloat64HFFT2()
{
var input = torch.rand(new long[] { 5, 5, 5, 5 }, float64);
var input = torch.rand(new long[] { 5, 5, 5, 5 }, complex128);
var output = fft.hfft2(input);
Assert.Equal(new long[] { 5, 5, 5, 8 }, output.shape);
Assert.Equal(input.dtype, output.dtype);
Assert.Equal(ScalarType.Float64, output.dtype);

var inverted = fft.ihfft2(output);
Assert.Equal(new long[] { 5, 5, 5, 5 }, inverted.shape);
Assert.Equal(ScalarType.ComplexFloat64, inverted.dtype);
}

[Fact]
[TestOf(nameof(fft.hfft2))]
public void Float32HFFTN()
[TestOf(nameof(fft.hfftn))]
public void ComplexFloat32HFFTN()
{
var input = torch.rand(new long[] { 5, 5, 5, 5 });
var output = fft.hfft2(input);
var input = torch.rand(new long[] { 5, 5, 5, 5 }, complex64);
var output = fft.hfftn(input);
Assert.Equal(new long[] { 5, 5, 5, 8 }, output.shape);
Assert.Equal(input.dtype, output.dtype);
Assert.Equal(ScalarType.Float32, output.dtype);

var inverted = fft.ihfft2(output);
var inverted = fft.ihfftn(output);
Assert.Equal(new long[] { 5, 5, 5, 5 }, inverted.shape);
Assert.Equal(ScalarType.ComplexFloat32, inverted.dtype);
}

[Fact(Skip = "Fails on all Release builds.")]
[TestOf(nameof(fft.hfftn))]
public void Float64HFFTN()
public void ComplexFloat64HFFTN()
{
if (!RuntimeInformation.IsOSPlatform(OSPlatform.Windows) && !RuntimeInformation.IsOSPlatform(OSPlatform.OSX)) {

// TODO: Something in this test makes if fail on Windows / Release and MacOS / Release

var input = torch.rand(new long[] { 5, 5, 5, 5 }, float64);
var input = torch.rand(new long[] { 5, 5, 5, 5 }, complex128);
var output = fft.hfftn(input);
Assert.Equal(new long[] { 5, 5, 5, 8 }, output.shape);
Assert.Equal(input.dtype, output.dtype);
Assert.Equal(ScalarType.Float64, output.dtype);

var inverted = fft.ihfftn(output);
Assert.Equal(new long[] { 5, 5, 5, 5 }, inverted.shape);
Expand Down
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