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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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d4358ed
Fix HFFT tests to use complex input tensors
alinpahontu2912 Feb 16, 2026
ef4e90f
Fix Float32HFFTN test to call hfftn instead of hfft2
alinpahontu2912 Feb 17, 2026
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30 changes: 15 additions & 15 deletions test/TorchSharpTest/TestTorchTensor.cs
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Original file line number Diff line number Diff line change
Expand Up @@ -6881,25 +6881,25 @@ public void Float64FFT()
[TestOf(nameof(fft.hfft))]
public void Float32HFFT()
{
var input = torch.arange(4);
var input = torch.arange(4, complex64);
var output = fft.hfft(input);
Assert.Equal(6, output.shape[0]);
Assert.Equal(ScalarType.Float32, output.dtype);

var inverted = fft.ifft(output);
var inverted = fft.ihfft(output);
Assert.Equal(ScalarType.ComplexFloat32, inverted.dtype);
Comment on lines +6884 to 6890
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Copilot AI Feb 17, 2026

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Float32HFFT now uses complex input and is functionally identical to the existing ComplexFloat32HFFT test (and similarly Float64HFFT duplicates ComplexFloat64HFFT later in this file). This introduces redundant coverage and makes the intent of the “Float32/Float64” naming unclear. Consider removing the duplicate tests or renaming/adjusting them so each case covers a distinct scenario (e.g., only keep the Complex* variants, or have one set validate round-trip/value behavior).

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}

[Fact]
[TestOf(nameof(fft.hfft))]
public void Float64HFFT()
{
var input = torch.arange(4, float64);
var input = torch.arange(4, complex128);
var output = fft.hfft(input);
Assert.Equal(6, output.shape[0]);
Assert.Equal(ScalarType.Float64, output.dtype);

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

Expand Down Expand Up @@ -7142,10 +7142,10 @@ public void Float64RFFTN()
[TestOf(nameof(fft.hfft2))]
public void Float32HFFT2()
{
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 @@ -7156,26 +7156,26 @@ public void Float32HFFT2()
[TestOf(nameof(fft.hfft2))]
public void Float64HFFT2()
{
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))]
[TestOf(nameof(fft.hfftn))]
public void Float32HFFTN()
{
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);
Comment on lines 7145 to 7174
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Copilot AI Feb 17, 2026

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These tests (Float32HFFT2/Float64HFFT2/Float32HFFTN/Float64HFFTN) now pass complex inputs (complex64/complex128). In this file, other FFT tests use the “Float32/Float64” prefix to indicate the input dtype (e.g., Float32FFT2, Float32RFFTN). To avoid confusion, consider renaming these to reflect the complex input type (or otherwise aligning the naming scheme).

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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);
}
Expand All @@ -7188,10 +7188,10 @@ public void Float64HFFTN()

// 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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