For now, removing output of all notebook cells

cpp/include/cuvs/cluster/kmeans.hpp

@@ -403,17 +403,12 @@ void predict(raft::resources const& handle,
  * @param[in]     params           Parameters for KMeans model.
  * @param[in]     X                New data to predict.
  *                                 [dim = n_samples x n_features]
- * @param[in]     sample_weight    Optional weights for each observation in X.
- *                                 [len = n_samples]
  * @param[in]     centroids        Cluster centroids. The data must be in
  *                                 row-major format.
  *                                 [dim = n_clusters x n_features]
- * @param[in]     normalize_weight True if the weights should be normalized
  * @param[out]    labels           Index of the cluster each sample in X
  *                                 belongs to.
  *                                 [len = n_samples]
- * @param[out]    inertia          Sum of squared distances of samples to
- *                                 their closest cluster center.
  */
 void predict(const raft::resources& handle,
              cuvs::cluster::kmeans::balanced_params const& params,

docs/source/working_with_ann_indexes_c.rst

@@ -18,6 +18,8 @@ Building an index
     cuvsCagraIndex_t index;
 
     DLManagedTensor *dataset;
+
+    // populate tensor with data
     load_dataset(dataset);
 
     cuvsResourcesCreate(&res);
@@ -34,6 +36,33 @@ Building an index
 Searching an index
 ------------------
 
+.. code-block:: c
+
+    #include <cuvs/neighbors/cagra.h>
+
+    cuvsResources_t res;
+    cuvsCagraSearchParams_t search_params;
+    cuvsCagraIndex_t index;
+
+    // ... build index ...
+
+    DLManagedTensor *queries;
+
+    DLManagedTensor *neighbors;
+    DLManagedTensor *distances;
+
+    // populate tensor with data
+    load_queries(queries);
+
+    cuvsResourcesCreate(&res);
+    cuvsCagraSearchParamsCreate(&index_params);
+
+    cuvsCagraSearch(res, search_params, index, queries, neighbors, distances);
+
+    cuvsCagraIndexDestroy(index);
+    cuvsCagraIndexParamsDestroy(index_params);
+    cuvsResourcesDestroy(res);
+
 
 Serializing an index
 --------------------

docs/source/working_with_ann_indexes_cpp.rst

@@ -23,13 +23,29 @@ Building an index
     auto index = cagra::build(res, index_params, dataset);
 
 
-
 Searching an index
 ------------------
 
+.. code-block:: c++
+
+    #include <cuvs/neighbors/cagra.hpp>
+
+    using namespace cuvs::neighbors;
+    cagra::index index;
+
+    // ... build index ...
+
+    raft::device_matrix_view<float> queries = load_queries();
+    raft::device_matrix_view<uint32_t> neighbors = make_device_matrix_view<uint32_t>(n_queries, k);
+    raft::device_matrix_view<float> distances = make_device_matrix_view<float>(n_queries, k);
+    raft::device_resources res;
+
+    cagra::search_params search_params;
+
+    cagra::search(res, search_params, index, queries, neighbors, distances);
 
-CPU/GPU interoperability
-------------------------
 
 Serializing an index
---------------------
+--------------------
+
+

docs/source/working_with_ann_indexes_python.rst

@@ -22,9 +22,19 @@ Building an index
 Searching an index
 ------------------
 
+.. code-block:: python
+
+    from cuvs.neighbors import cagra
+
+    queries = load_queries()
+
+    search_params = cagra.SearchParams()
+
+    index = // ... build index ...
+
+    neighbors, distances = cagra.search(search_params, index, queries, k)
+
 
-CPU/GPU interoperability
-------------------------
 
 Serializing an index
 --------------------