Coerce tensorboard metrics into numpy arrays #21504
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As of [Numpy 2.4.0](https://numpy.org/doc/stable/release/2.4.0-notes.html#raise-typeerror-on-attempt-to-convert-array-with-ndim-0-to-scalar), converting an 0-dimensional array to a scalar is now a TypeError, following the expiration of a lengthy deprecation period. This change detects the situation and adjusts the types accordingly before passing them to tensorboard.
pganssle-google
requested review from
ethanwharris,
justusschock,
lantiga,
tchaton and
williamFalcon
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Codecov Report❌ Patch coverage is Additional details and impacted files@@ Coverage Diff @@
## master #21504 +/- ##
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- Coverage 87% 87% -0%
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Files 270 270
Lines 24067 24075 +8
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+ Hits 20863 20869 +6
- Misses 3204 3206 +2 |
| if isinstance(v, (int, float, np.number)): | ||
| v = np.array(v) | ||
| elif isinstance(v, np.ndarray) and v.ndim > 0 and v.size == 1: | ||
| v = np.array(v.item()) |
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| if isinstance(v, (int, float, np.number)): | |
| v = np.array(v) | |
| elif isinstance(v, np.ndarray) and v.ndim > 0 and v.size == 1: | |
| v = np.array(v.item()) | |
| if isinstance(v, (np.number)) or isinstance(v, np.ndarray) and v.ndim > 0 and v.size == 1: | |
| v = float(v.item()) |
Why are we converting them into np.array? Is there any additional benefit?
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When I skipped that part the tests failed, at least for me.
TBH, this whole thing is a bug in tensorboardX. tensorboardX does some inappropriate conversion with scalars which hits the deprecated-now-removed code path. IIRC, if you don't coerce to a numpy array with the right shape before passing it to tensorboardX, it does it anyway, it just does it incorrectly.
So I guess it's up to you how much you want to have code here to work around a bug upstream. In practical terms it means this part of the library is not compatible with numpy 2.4 until tensorboardX is fixed, which may never happen, and even if it does, it will require a more recent version of tensorboardX to work properly. But from a purity perspective, this isn't actually your bug 😅
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What does this PR do?
As of Numpy 2.4.0, converting an 0-dimensional array to a scalar is now a TypeError, following the expiration of a lengthy deprecation period.
This change detects the situation and adjusts the types accordingly before passing them to tensorboard.
Fixes #21503
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📚 Documentation preview 📚: https://pytorch-lightning--21504.org.readthedocs.build/en/21504/