Wrapper function to generate GPU nearest neighbour parameters

Usage

params_nn_gpu(
  dist_metric = c("euclidean", "cosine"),
  n_list = NULL,
  n_probes = NULL,
  node_degree_final = NULL,
  k_build = NULL,
  n_tree = NULL,
  delta = 0.001,
  rho = NULL,
  beam_width = NULL,
  max_beam_iters = NULL,
  n_entry_points = NULL,
  extract_knn = FALSE
)

Arguments

dist_metric: String. The distance metric to use. One of c("euclidean", "cosine"). Defaults to "euclidean".
n_list: Integer or NULL. IVF GPU: Number of clusters to use. If NULL, will default to sqrt(n). Defaults to NULL.
n_probes: Integer or NULL. IVF GPU: Number of clusters to probe. If NULL, will default to sqrt(n_list). Defaults to NULL.
node_degree_final: Integer or NULL. Final node degree of the CAGRA navigational graph. If NULL, defaults to 30 on the Rust side. Defaults to NULL.
k_build: Integer or NULL. Number of k-neighbours during the NNDescent build phase before CAGRA pruning. If NULL, defaults to 1.5 * node_degree_final on the Rust side. (Cannot be smaller than node_degree_final) Defaults to NULL.
n_tree: Integer or NULL. CAGRA GPU: Number of trees for graph build. Automatically if NULL. Defaults to NULL.
delta: Numeric. CAGRA GPU: Early termination parameter for NN descent. Defaults to 0.001.
rho: Numeric or NULL. CAGRA GPU: Sample rate parameter for NN descent. Defaults to NULL.
beam_width: Integer or NULL. CAGRA GPU: Beam width for beam search. If not provided will be set to max(c(k, node_degree_final, 16L)) * 2. Defaults to NULL.
max_beam_iters: Integer or NULL. CAGRA GPU: Maximum number of beam search iterations. If not provided, defaults to 3 * beam_width. Defaults to NULL.
n_entry_points: Integer or NULL. CAGRA GPU: Number of entry points for beam search. If not provided, defaults to 8L. Defaults to NULL.
extract_knn: Boolean. CAGRA GPU: Skip the beam search and take the graph the NNDescent left it. Faster, slightly lower recall. Ignored by the other two searches. Defaults to FALSE.

Value

A named list with the following elements:

dist_metric - String. The distance metric to use. One of c("euclidean", "cosine"). Defaults to "euclidean".
n_list - Integer or NULL. IVF GPU: Number of clusters to use. If NULL, will default to sqrt(n). Defaults to NULL.
n_probes - Integer or NULL. IVF GPU: Number of clusters to probe. If NULL, will default to sqrt(n_list). Defaults to NULL.
node_degree_final - Integer or NULL. Final node degree of the CAGRA navigational graph. If NULL, defaults to 30 on the Rust side. Defaults to NULL.
k_build - Integer or NULL. Number of k-neighbours during the NNDescent build phase before CAGRA pruning. If NULL, defaults to 1.5 * node_degree_final on the Rust side. (Cannot be smaller than node_degree_final) Defaults to NULL.
n_tree - Integer or NULL. CAGRA GPU: Number of trees for graph build. Automatically if NULL. Defaults to NULL.
delta - Numeric. CAGRA GPU: Early termination parameter for NN descent. Defaults to 0.001.
rho - Numeric or NULL. CAGRA GPU: Sample rate parameter for NN descent. Defaults to NULL.
beam_width - Integer or NULL. CAGRA GPU: Beam width for beam search. If not provided will be set to max(c(k, node_degree_final, 16L)) * 2. Defaults to NULL.
max_beam_iters - Integer or NULL. CAGRA GPU: Maximum number of beam search iterations. If not provided, defaults to 3 * beam_width. Defaults to NULL.
n_entry_points - Integer or NULL. CAGRA GPU: Number of entry points for beam search. If not provided, defaults to 8L. Defaults to NULL.
extract_knn - Boolean. CAGRA GPU: Skip the beam search and take the graph the NNDescent left it. Faster, slightly lower recall. Ignored by the other two searches. Defaults to FALSE.