Fix RandomCentroidsInitialisation to safely handle cases where zero clusters are requested for a weight interval.

PiperOrigin-RevId: 925483764

Author: ratgr

tensorflow_model_optimization/python/core/clustering/keras/clustering_centroids.py

@@ -212,7 +212,6 @@ class LinearCentroidsInitialisation(AbstractCentroidsInitialisation):
   def _calculate_centroids_for_interval(self, weight_interval,
                                         number_of_clusters_for_interval):
     if tf.math.less_equal(number_of_clusters_for_interval, 0):
-      # Return an empty array of centroids
       return tf.constant([])
 
     weight_min = tf.reduce_min(weight_interval)
@@ -247,6 +246,10 @@ class RandomCentroidsInitialisation(AbstractCentroidsInitialisation):
 
   def _calculate_centroids_for_interval(self, weight_interval,
                                         number_of_clusters_for_interval):
+    if tf.math.less_equal(number_of_clusters_for_interval, 0):
+      # Return an empty array of centroids
+      return tf.constant([])
+
     weight_min = tf.reduce_min(weight_interval)
     weight_max = tf.reduce_max(weight_interval)
     cluster_centroids = tf.random.uniform(

tensorflow_model_optimization/python/core/clustering/keras/clustering_centroids_test.py

@@ -192,6 +192,7 @@ def testDensityBasedClusterCentroidsWithSparsityPreservation(
   @parameterized.parameters(
       ([0., 1., 2., 3., 4., 5., 6., 7., 8., 9., 10.], 5),
       ([0., 1., 2., 3., 3.1, 3.2, 3.3, 3.4, 3.5], 3),
+      ([1.0, 2.0, 3.0], 3),
       ([-3., -2., -1., 0., 1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.], 6))
   def testRandomClusterCentroidsWithSparsityPreservation(
       self, weights, number_of_clusters):