dense_vector/track.py [12:29]:
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def extract_vector_operations_count(knn_result):
    vector_operations_count = 0
    profile = knn_result["profile"]
    for shard in profile["shards"]:
        assert len(shard["dfs"]["knn"]) == 1
        knn_search = shard["dfs"]["knn"][0]
        if "vector_operations_count" in knn_search:
            vector_operations_count += knn_search["vector_operations_count"]
    return vector_operations_count


def compute_percentile(data: List[Any], percentile):
    size = len(data)
    if size <= 0:
        return None
    sorted_data = sorted(data)
    index = int(round(percentile * size / 100)) - 1
    return sorted_data[max(min(index, size - 1), 0)]
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msmarco-v2-vector/track.py [16:33]:
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def extract_vector_operations_count(knn_result):
    vector_operations_count = 0
    profile = knn_result["profile"]
    for shard in profile["shards"]:
        assert len(shard["dfs"]["knn"]) == 1
        knn_search = shard["dfs"]["knn"][0]
        if "vector_operations_count" in knn_search:
            vector_operations_count += knn_search["vector_operations_count"]
    return vector_operations_count


def compute_percentile(data: List[Any], percentile):
    size = len(data)
    if size <= 0:
        return None
    sorted_data = sorted(data)
    index = int(round(percentile * size / 100)) - 1
    return sorted_data[max(min(index, size - 1), 0)]
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