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You know that you're trying to write to the "same position" twice, for example [1, 2]. Unfortunatly (or fortunatly, depending on the point of view) that doesn't work.
But you can use np.add.at which according to the docs "For addition ufunc, this method is equivalent to a[indices] += b, except that results are accumulated for elements that are indexed more than once.":
This is a BUG
the output is -5
I find that
train
is not equal totrain2
when there are some duplicate tuples intmp
. Is there something wrong in numpy slicing.The text was updated successfully, but these errors were encountered: