Add centered FFT example to fftshift docs #51223
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💊 CI failures summary and remediationsAs of commit a35097b (more details on the Dr. CI page):
🚧 1 fixed upstream failure:These were probably caused by upstream breakages that were already fixed.
Please rebase on the
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| >>> torch.fftshift(f) | ||
| tensor([-0.5000, -0.2500, 0.0000, 0.2500]) | ||
| >>> torch.fft.fftshift(f) | ||
| tensor([-0.5000, -0.2500, 0.0000, 0.2500]) |
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Found these discrepancies from running the doctests manually. So, it seems fft doctests aren't being run in CI.
torch/fft/__init__.py
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| @@ -865,6 +865,10 @@ | |||
| Reorders n-dimensional FFT data, as provided by :func:`~torch.fft.fftn`, to have | |||
| negative frequency terms first. | |||
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| This performs a periodic shift of n-dimensional data such that the origin | |||
| ``(0, ..., 0)`` is moved to the center of the tensor. Specifically, | |||
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Suggestion:
"Specifically, ..." -> "Specifically, to ..." to make the second sentence parallel to the first.
torch/fft/__init__.py
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| >>> fft_centered = torch.fft.fftshift(fft_uncentered) | ||
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| The inverse transform, from centered Fourier space back to centered spatial | ||
| data, is simply applying the inverse shifts in reverse order: |
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Suggestion: "is simply applying" -> "can be performed by applying"
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I made a couple suggestions for your review @peterbell10. If they're helpful, great, and if not no worries. Just ping me when you'd like this merged.
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@mruberry I've added your suggestions. |
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@mruberry has imported this pull request. If you are a Facebook employee, you can view this diff on Phabricator.
Closes #51022