Refactor GMM TUs to use gmm_matrix.json

cpp/CMakeLists.txt

@@ -1380,6 +1380,12 @@ if(NOT BUILD_CPU_ONLY)
     OUTPUT_FILE_FORMAT
       "${CMAKE_CURRENT_BINARY_DIR}/src/neighbors/ivf_pq/detail/ivf_pq_transform_inst_data_@data_abbrev@_index_@index_abbrev@.cu"
   )
+  generate_inst_matrix(
+    gmm_inst_files
+    MATRIX_JSON_FILE "${CMAKE_CURRENT_SOURCE_DIR}/src/cluster/gmm_matrix.json"
+    INPUT_FILE "${CMAKE_CURRENT_SOURCE_DIR}/src/cluster/gmm_inst.cu.in"
+    OUTPUT_FILE_FORMAT "${CMAKE_CURRENT_BINARY_DIR}/src/cluster/gmm_inst_data_@data_abbrev@.cu"
+  )
   generate_inst_matrix(
     nn_descent_inst_files
     MATRIX_JSON_FILE "${CMAKE_CURRENT_SOURCE_DIR}/src/neighbors/nn_descent_matrix.json"
@@ -1415,8 +1421,7 @@ if(NOT BUILD_CPU_ONLY)
     cuvs_objs OBJECT
     src/cluster/detail/minClusterDistanceCompute.cu
     src/cluster/agglomerative.cu
-    src/cluster/gmm_double.cu
-    src/cluster/gmm_float.cu
+    ${gmm_inst_files}
     src/cluster/kmeans_cluster_cost.cu
     src/cluster/kmeans_fit_double.cu
     src/cluster/kmeans_fit_float.cu

cpp/src/cluster/gmm.cuh

@@ -5,7 +5,7 @@
 
 #pragma once
 
-#include "gmm_impl.cuh"
+#include "detail/gmm_impl.cuh"
 
 #include <cuvs/cluster/gmm.hpp>
 

cpp/src/cluster/gmm_inst.cu.in

@@ -0,0 +1,80 @@
+/*
+ * SPDX-FileCopyrightText: Copyright (c) 2026, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
+ * SPDX-License-Identifier: Apache-2.0
+ */
+
+#include <cluster/gmm.cuh>
+
+#include <cuvs/cluster/gmm.hpp>
+
+namespace {
+
+using data_t = @data_type@;
+
+}  // namespace
+
+namespace cuvs::cluster::gmm {
+
+void fit(raft::resources const& handle,
+         const params& params,
+         raft::device_matrix_view<const data_t, int64_t> X,
+         raft::device_vector_view<data_t, int64_t> weights,
+         raft::device_matrix_view<data_t, int64_t> means,
+         raft::device_vector_view<data_t, int64_t> covariances,
+         raft::device_vector_view<data_t, int64_t> precisions_chol,
+         raft::device_vector_view<data_t, int64_t> precisions,
+         raft::device_vector_view<int, int64_t> labels,
+         raft::host_scalar_view<data_t> lower_bound,
+         raft::host_scalar_view<int> n_iter,
+         raft::host_scalar_view<bool> converged,
+         bool warm_start)
+{
+  fit<data_t>(handle,
+              params,
+              X,
+              weights,
+              means,
+              covariances,
+              precisions_chol,
+              precisions,
+              labels,
+              lower_bound,
+              n_iter,
+              converged,
+              warm_start);
+}
+
+void predict(raft::resources const& handle,
+             const params& params,
+             raft::device_matrix_view<const data_t, int64_t> X,
+             raft::device_vector_view<const data_t, int64_t> weights,
+             raft::device_matrix_view<const data_t, int64_t> means,
+             raft::device_vector_view<const data_t, int64_t> precisions_chol,
+             raft::device_vector_view<int, int64_t> labels)
+{
+  predict<data_t>(handle, params, X, weights, means, precisions_chol, labels);
+}
+
+void predict_proba(raft::resources const& handle,
+                   const params& params,
+                   raft::device_matrix_view<const data_t, int64_t> X,
+                   raft::device_vector_view<const data_t, int64_t> weights,
+                   raft::device_matrix_view<const data_t, int64_t> means,
+                   raft::device_vector_view<const data_t, int64_t> precisions_chol,
+                   raft::device_matrix_view<data_t, int64_t> resp)
+{
+  predict_proba<data_t>(handle, params, X, weights, means, precisions_chol, resp);
+}
+
+void score_samples(raft::resources const& handle,
+                   const params& params,
+                   raft::device_matrix_view<const data_t, int64_t> X,
+                   raft::device_vector_view<const data_t, int64_t> weights,
+                   raft::device_matrix_view<const data_t, int64_t> means,
+                   raft::device_vector_view<const data_t, int64_t> precisions_chol,
+                   raft::device_vector_view<data_t, int64_t> log_prob_norm)
+{
+  score_samples<data_t>(handle, params, X, weights, means, precisions_chol, log_prob_norm);
+}
+
+}  // namespace cuvs::cluster::gmm

cpp/src/cluster/gmm_matrix.json

@@ -0,0 +1,12 @@
+{
+  "_data": [
+    {
+      "data_type": "float",
+      "data_abbrev": "f"
+    },
+    {
+      "data_type": "double",
+      "data_abbrev": "d"
+    }
+  ]
+}