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After creating a TCAV instance, when one calls the .interpret() method, the yielded dictionary of scores don't follow the order of the experimental sets given in input. This creates confusion.
To Reproduce
Steps to reproduce the behavior:
Define some experimental sets. In my case I had 25 pairs of "base concept - random concept j" for j = 0, .. 24 for every base concept. The order is: base concept 0 - random concept 0, base concept 0 - random concept 1, ... base concept 0 - random concept 24, base concept 1 - random concept 0, base concept 1 - random concept 1, .. etc
🐛 Bug
After creating a TCAV instance, when one calls the .interpret() method, the yielded dictionary of scores don't follow the order of the experimental sets given in input. This creates confusion.
To Reproduce
Steps to reproduce the behavior:
scores = mytcav.interpret(inputs=input_class, experimental_sets=experimental_set_rand, target=target_id,)
Expected behavior
The keys of the scores' dictionary should follow the order of the experimental sets given in input.
conda
,pip
, source): condaThe text was updated successfully, but these errors were encountered: