Adding distance types back

cpp/include/raft/distance/distance_types.hpp

@@ -0,0 +1,108 @@
+/*
+ * Copyright (c) 2021-2024, NVIDIA CORPORATION.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#pragma once
+
+namespace raft {
+namespace distance {
+
+/** enum to tell how to compute distance */
+enum DistanceType : unsigned short {
+
+  /** evaluate as dist_ij = sum(x_ik^2) + sum(y_ij)^2 - 2*sum(x_ik * y_jk) */
+  L2Expanded = 0,
+  /** same as above, but inside the epilogue, perform square root operation */
+  L2SqrtExpanded = 1,
+  /** cosine distance */
+  CosineExpanded = 2,
+  /** L1 distance */
+  L1 = 3,
+  /** evaluate as dist_ij += (x_ik - y-jk)^2 */
+  L2Unexpanded = 4,
+  /** same as above, but inside the epilogue, perform square root operation */
+  L2SqrtUnexpanded = 5,
+  /** basic inner product **/
+  InnerProduct = 6,
+  /** Chebyshev (Linf) distance **/
+  Linf = 7,
+  /** Canberra distance **/
+  Canberra = 8,
+  /** Generalized Minkowski distance **/
+  LpUnexpanded = 9,
+  /** Correlation distance **/
+  CorrelationExpanded = 10,
+  /** Jaccard distance **/
+  JaccardExpanded = 11,
+  /** Hellinger distance **/
+  HellingerExpanded = 12,
+  /** Haversine distance **/
+  Haversine = 13,
+  /** Bray-Curtis distance **/
+  BrayCurtis = 14,
+  /** Jensen-Shannon distance**/
+  JensenShannon = 15,
+  /** Hamming distance **/
+  HammingUnexpanded = 16,
+  /** KLDivergence **/
+  KLDivergence = 17,
+  /** RusselRao **/
+  RusselRaoExpanded = 18,
+  /** Dice-Sorensen distance **/
+  DiceExpanded = 19,
+  /** Precomputed (special value) **/
+  Precomputed = 100
+};
+
+/**
+ * Whether minimal distance corresponds to similar elements (using the given metric).
+ */
+inline bool is_min_close(DistanceType metric)
+{
+  bool select_min;
+  switch (metric) {
+    case DistanceType::InnerProduct:
+      // Similarity metrics have the opposite meaning, i.e. nearest neighbors are those with larger
+      // similarity (See the same logic at cpp/include/raft/sparse/spatial/detail/knn.cuh:362
+      // {perform_k_selection})
+      select_min = false;
+      break;
+    default: select_min = true;
+  }
+  return select_min;
+}
+
+namespace kernels {
+enum KernelType { LINEAR, POLYNOMIAL, RBF, TANH };
+
+/**
+ * Parameters for kernel matrices.
+ * The following kernels are implemented:
+ * - LINEAR \f[ K(x_1,x_2) = <x_1,x_2>, \f] where \f$< , >\f$ is the dot product
+ * - POLYNOMIAL \f[ K(x_1, x_2) = (\gamma <x_1,x_2> + \mathrm{coef0})^\mathrm{degree} \f]
+ * - RBF \f[ K(x_1, x_2) = \exp(- \gamma |x_1-x_2|^2) \f]
+ * - TANH \f[ K(x_1, x_2) = \tanh(\gamma <x_1,x_2> + \mathrm{coef0}) \f]
+ */
+struct KernelParams {
+  // Kernel function parameters
+  KernelType kernel;  //!< Type of the kernel function
+  int degree;         //!< Degree of polynomial kernel (ignored by others)
+  double gamma;       //!< multiplier in the
+  double coef0;       //!< additive constant in poly and tanh kernels
+};
+}  // end namespace kernels
+
+};  // namespace distance
+};  // end namespace raft