diskann-benchmark 0.51.0

DiskANN is a fast approximate nearest neighbor search library for high dimensional data
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/*
 * Copyright (c) Microsoft Corporation.
 * Licensed under the MIT license.
 */

pub(crate) mod disk;
pub(crate) mod exhaustive;
pub(crate) mod filters;
pub(crate) mod graph_index;
pub(crate) mod save_and_load;

pub(crate) fn register_inputs(
    registry: &mut diskann_benchmark_runner::registry::Inputs,
) -> anyhow::Result<()> {
    graph_index::register_inputs(registry)?;
    exhaustive::register_inputs(registry)?;
    disk::register_inputs(registry)?;
    filters::register_inputs(registry)?;
    Ok(())
}

/// Construct an example input of type `Self`.
pub(crate) trait Example {
    fn example() -> Self;
}

// NOTE: The input registration and dispatching isn't prefect. It uses a pattern (like
// the use of `'static` on the benchmark types) as a byproduct of older ways of doing
// benchmark selection.
//
// In the future, these can be migrated to reduce this legacy cruft.
macro_rules! as_input {
    ($T:ty) => {
        impl diskann_benchmark_runner::Input for $T {
            fn tag() -> &'static str {
                <$T>::tag()
            }

            fn try_deserialize(
                serialized: &serde_json::Value,
                checker: &mut diskann_benchmark_runner::Checker,
            ) -> anyhow::Result<diskann_benchmark_runner::Any> {
                checker.any(<$T as serde::Deserialize>::deserialize(serialized)?)
            }

            fn example() -> anyhow::Result<serde_json::Value> {
                Ok(serde_json::to_value(
                    <$T as $crate::inputs::Example>::example(),
                )?)
            }
        }
    };
}

use as_input;