refactor

rapidsai · Jun 25, 2024 · 88278d3 · 88278d3
1 parent 5a4861a
commit 88278d3
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Showing 4 changed files with 20 additions and 22 deletions.
diff --git a/cpp/src/metrics/pairwise_distance_dice.cu b/cpp/src/metrics/pairwise_distance_dice.cu
@@ -1,6 +1,5 @@
-
 /*
- * Copyright (c) 2021-2024, NVIDIA CORPORATION.
+ * Copyright (c) 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.

diff --git a/cpp/src/metrics/pairwise_distance_dice.cuh b/cpp/src/metrics/pairwise_distance_dice.cuh
@@ -1,6 +1,5 @@
-
 /*
- * Copyright (c) 2021-2024, NVIDIA CORPORATION.
+ * Copyright (c) 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.

diff --git a/python/cuml/manifold/umap_utils.pyx b/python/cuml/manifold/umap_utils.pyx
@@ -135,30 +135,31 @@ def find_ab_params(spread, min_dist):
 
 
 metric_parsing = {
-    "l2": DistanceType.L2SqrtUnexpanded,
-    "euclidean": DistanceType.L2SqrtUnexpanded,
-    "sqeuclidean": DistanceType.L2Unexpanded,
-    "cityblock": DistanceType.L1,
-    "l1": DistanceType.L1,
-    "manhattan": DistanceType.L1,
-    "taxicab": DistanceType.L1,
-    "minkowski": DistanceType.LpUnexpanded,
+    "canberra": DistanceType.Canberra,
     "chebyshev": DistanceType.Linf,
-    "linf": DistanceType.Linf,
+    "cityblock": DistanceType.L1,
     "cosine": DistanceType.CosineExpanded,
     "correlation": DistanceType.CorrelationExpanded,
-    "hellinger": DistanceType.HellingerExpanded,
+    "dice": DistanceType.DiceExpanded,
+    "euclidean": DistanceType.L2SqrtUnexpanded,
     "hamming": DistanceType.HammingUnexpanded,
+    "hellinger": DistanceType.HellingerExpanded,
     "jaccard": DistanceType.JaccardExpanded,
-    "canberra": DistanceType.Canberra,
-    "dice": DistanceType.DiceExpanded,
+    "l1": DistanceType.L1,
+    "l2": DistanceType.L2SqrtUnexpanded,
+    "linf": DistanceType.Linf,
+    "manhattan": DistanceType.L1,
+    "minkowski": DistanceType.LpUnexpanded,
+    "sqeuclidean": DistanceType.L2Unexpanded,
+    "taxicab": DistanceType.L1,
 }
 
 
 DENSE_SUPPORTED_METRICS = [
     DistanceType.Canberra,
     DistanceType.CorrelationExpanded,
     DistanceType.CosineExpanded,
+    DistanceType.DiceExpanded,
     DistanceType.HammingUnexpanded,
     DistanceType.HellingerExpanded,
     # DistanceType.JaccardExpanded,  # not supported
@@ -167,14 +168,14 @@ DENSE_SUPPORTED_METRICS = [
     DistanceType.L2Unexpanded,
     DistanceType.Linf,
     DistanceType.LpUnexpanded,
-    DistanceType.DiceExpanded,
 ]
 
 
 SPARSE_SUPPORTED_METRICS = [
     DistanceType.Canberra,
     DistanceType.CorrelationExpanded,
     DistanceType.CosineExpanded,
+    DistanceType.DiceExpanded,
     DistanceType.HammingUnexpanded,
     DistanceType.HellingerExpanded,
     DistanceType.JaccardExpanded,
@@ -183,5 +184,4 @@ SPARSE_SUPPORTED_METRICS = [
     DistanceType.L2Unexpanded,
     DistanceType.Linf,
     DistanceType.LpUnexpanded,
-    DistanceType.DiceExpanded,
 ]
diff --git a/python/cuml/metrics/pairwise_distances.pyx b/python/cuml/metrics/pairwise_distances.pyx
@@ -81,7 +81,7 @@ PAIRWISE_DISTANCE_METRICS = {
     "kldivergence": DistanceType.KLDivergence,
     "russellrao": DistanceType.RusselRaoExpanded,
     "nan_euclidean": DistanceType.L2Expanded,
-    "dice": DistanceType.DiceExpanded
+    "dice": DistanceType.DiceExpanded,
 }
 
 PAIRWISE_DISTANCE_SPARSE_METRICS = {
@@ -98,7 +98,7 @@ PAIRWISE_DISTANCE_SPARSE_METRICS = {
     "jaccard": DistanceType.JaccardExpanded,
     "hellinger": DistanceType.HellingerExpanded,
     "chebyshev": DistanceType.Linf,
-    "dice": DistanceType.DiceExpanded
+    "dice": DistanceType.DiceExpanded,
 }
 
 
@@ -345,7 +345,7 @@ def pairwise_distances(X, Y=None, metric="euclidean", handle=None,
     if metric in ['nan_euclidean']:
         return nan_euclidean_distances(X, Y, **kwds)
 
-    if metric in ['russellrao', 'dice'] and not np.all(X.data == 1.):
+    if metric in {'russellrao', 'dice'} and not np.all(X.data == 1.):
         warnings.warn("X was converted to boolean for metric {}"
                       .format(metric))
         X = np.where(X != 0., 1.0, 0.0)
@@ -368,7 +368,7 @@ def pairwise_distances(X, Y=None, metric="euclidean", handle=None,
         if (n_samples_x == 1 or n_features_x == 1):
             input_order = "K"
 
-        if metric in ['russellrao', 'dice'] and not np.all(Y.data == 1.):
+        if metric in {'russellrao', 'dice'} and not np.all(Y.data == 1.):
             warnings.warn("Y was converted to boolean for metric {}"
                           .format(metric))
             Y = np.where(Y != 0., 1.0, 0.0)