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Inconsistency in TCAV: Order of experimental sets #909
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@carlomarxdk , thank you for pointing out to this issue. There was a bug related to the ordering of returned tcav scores. I'll send out the fix soon. |
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Summary: Fixes TCAV concept ordering bug reported in this issue: pytorch#909 The original implementation wasn't sorting the concepts correctly in the output. I changed so that the ordering is based on the input concept ordering in the experimental set. Differential Revision: D35302278 fbshipit-source-id: 61fab8e24db586af514356d83843ab1bd4d026e3
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Summary: Pull Request resolved: #915 Fixes TCAV concept ordering bug reported in this issue: #909 The original implementation wasn't sorting the concepts correctly in the output. I changed so that the ordering is based on the input concept ordering in the experimental set. Reviewed By: vivekmig Differential Revision: D35302278 fbshipit-source-id: 82657184f42d9841a5adf56ef103150be5ef6146
@carlomarxdk, we just merged, #915. Let us know if this helps to address the issue |
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🐛 Bug
Ordering of concepts in the
experemental_sets
drastically changes the output ofinterpret
(e.g. it is not consistent)To reproduce:
Steps to reproduce:
interpret
If you change the order of
experemental_sets
:experimental_set_zig_dot = [[zigzagged_concept, dotted_concept, stripes_concept]]
orexperimental_set_zig_dot = [[dotted_concept, stripes_concept, zigzagged_concept]]
you get absolutely different results. In first case, indeed zigzagged concept has the largest magnitude score; however, in the second case, the dotted concept is going to have the highest magnitude score.Expected behaviour
I would expect that the change of the ordering would give same results.
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