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src/inspect_evals/_registry.py

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@@ -19,14 +19,14 @@
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from .class_eval import class_eval
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from .commonsense_qa import commonsense_qa
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from .cybench import cybench
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from .docvqa import docvqa
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from .cybermetric import (
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cybermetric_80,
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cybermetric_500,
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cybermetric_2000,
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cybermetric_10000,
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)
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from .cyberseceval_2 import interpreter_abuse, prompt_injection, vulnerability_exploit
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from .docvqa import docvqa
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from .drop import drop
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from .ds1000 import ds1000
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from .gaia import gaia, gaia_level1, gaia_level2, gaia_level3

src/inspect_evals/docvqa/docvqa.py

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@@ -61,7 +61,9 @@ def _best_normalized_levenshtein_similiarity(
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completion: str, ground_truths: list[str], threshold: float
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) -> float:
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"""
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Compute the Average Normalized Levenshtein Similarity (ANLS) as defined in equation (1) of
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Compute a best normalized Levenshtein similiarity, an input into the Average Normalized Levenshtein Similiarity (ANLS)
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The Average Normalized Levenshtein Similarity (ANLS) is defined in equation (1) of
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https://arxiv.org/pdf/1907.00490.pdf
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Note that the "average" is computed by the accuracy metric -- not here. This function computes

tests/docvqa/test_docvqa.py

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from inspect_evals.docvqa.docvqa import (
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_levenshtein_distance as levenshtein,
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_best_normalized_levenshtein_similiarity as best,
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)
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from inspect_evals.docvqa.docvqa import (
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_levenshtein_distance as levenshtein,
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)
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def test_levenshtein():

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