Crash when fit-ing fluid.robustscale~

Not exactly sure which part of the chain crashed, but when running the patch from this thread I got an insta crash with a bunch of fluid.stuff~ in the crash report.

fit crash.zip (41.3 KB)

Crash 2.

I suspect it may have to do with a lot of similar values in some columns (I was accidentally filling some with of the same samples. Crash seems excessive though.

crash2.zip (35.6 KB)

Indeed, things shouldn’t crash. fluid.buftranspose~ isn’t a thing – the crash report suggests that this when you’re fitting UMAP, yes?

lol whoops. It’d be even more surprising if that’s what threw up the error/crash then.

It’s a chain of processings (robustscale, standardize, umap (not in that order)). I haven’t isolated which step got really unhappy with things.

Here’s a standalone (messy) patch that should be able to reproduce it.


----------begin_max5_patcher----------
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-----------end_max5_patcher-----------

It doesn’t crash here, nor does it when I play with that bit of the original patch (as this is part of the other thread with ideas soon to appear…) - with your dataset, you could dump and check the range of robustscale. If you have a range of 0 somewhere that might explain (although it should be a nan not a crash) but that would help me to try to reproduce… (this one is my baby so bugs will be mine to sort)

Ok, it’s crashing at the fluid.umap~ part of the process. And the above crashes 100% of the time for me (Max 8.1.10 on Mojave).

This is the dump from the fluid.standardize~ that precedes it:

{
	"cols" : 76,
	"mean" : [ 7.965324878692627, 6.34978199005127, 0.109411269426346, 3.640201330184937, 3.647148370742798, 2.734099388122559, 1.402488827705383, 0.879556834697723, -0.622007608413696, -0.605379939079285, -0.768397152423859, 0.479116082191467, -1.547172784805298, 0.38996085524559, 0.487382978200912, -0.293511301279068, 0.692659854888916, 0.957192003726959, 1.174737095832825, 1.944554448127747, 9.699933052062988, 3.075112581253052, 2.243796586990356, 3.341866970062256, 2.072341680526733, 2.690227270126343, 1.691849231719971, 0.766773581504822, 1.496001124382019, 2.629327535629272, 1.869652390480042, 0.928587436676025, 1.948891520500183, 0.85331267118454, 1.451759338378906, 0.899518847465515, 1.337938904762268, 0.846606969833374, 5.909136772155762, -12.476437568664551, -4.028169631958008, -0.86164516210556, -1.91784679889679, -0.371667802333832, -1.240033745765686, -1.288015842437744, -1.883055686950684, -3.112740278244019, -5.615152835845947, -2.459360837936401, -3.480255126953125, -3.047985315322876, -0.970938861370087, -2.883966207504272, -1.063496351242065, 0.017220882698894, 0.022983815521002, 11.086114883422852, 17.778562545776367, 4.671655178070068, 6.054550647735596, 8.707236289978027, 5.346875190734863, 7.329411506652832, 3.904704570770264, -0.020018428564072, 1.251005053520203, 3.355345726013184, 3.189550876617432, -0.409507095813751, 2.904553890228271, 1.697600722312927, 1.718255877494812, 2.053926706314087, 3.814908742904663, 2.515552282333374 ],
	"std" : [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ]
}

Obviously that’d bad data, but nothing to crash over.

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We have a sturdier version here, can you forward me the dataset you feed it so I can check it is sorted before doing a bug report?

Chock full of nans.

nans.json.zip (1.2 KB)

nans are sorted, I know that, but what you dumped was full of 0s…

That was the fit.

I’m basically just dump-ing/write-ing what’s in that patch I posted above.

ok now I’m confused. You try to UMAP loads of NaNs? There was an old report stating it was crashing and that was sorted (waiting for alpha09) but at the moment I cannot reproduce. Let’s park this until release.

I’m not trying to UMAP NaNs. Because I put a typo in a version of my test patch I accidentally created a dataset with the same entry over and over, which then got sent through the processing chain from the LTEp patch. My real patch wasn’t crashing, though presumably it would if it had the same exact entry over and over.

but since NaNs don’t crash in the new version, this bug is the same as the previous one. that is what I was saying

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