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fix(token_classification): prevent IndexError in issues_from_scores on empty or all-below threshold scores - #1343
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…n empty or all-below threshold scores Resolves cleanlab#1338 - Bounds-check cutoff < len(ranking) before evaluating scores[ranking[cutoff]] to avoid IndexError when all scores are below threshold or input is empty - Convert sentence_scores with np.asarray to support array, list, and pandas Series inputs cleanly - Add regression unit tests in test_token_classification.py covering all-below, single-below, empty, and pandas Series inputs
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Summary
Fixes #1338
In \cleanlab.token_classification.rank.issues_from_scores, when \ oken_scores\ is not provided, the while loop:
\\python
while sentence_scores[ranking[cutoff]] < threshold and cutoff < len(ranking):
cutoff += 1
\
evaluated the array index \sentence_scores[ranking[cutoff]]\ before evaluating the bounds check \cutoff < len(ranking).
When all sentence scores fall below \ hreshold\ (or when given an empty sequence []\ or a single element below threshold), \cutoff\ increments to \len(ranking)\ and the next condition check indexed out of bounds, raising \IndexError.
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