Debug score K

README.md

@@ -88,11 +88,11 @@ Given n samples, the value of the Vendi Score ranges between 1 and n, with highe
 
 ```
 >>> import numpy as np
->>> vendiscore = evaluate.load("danf0/vendiscore")
+>>> vendiscore = evaluate.load("danf0/vendiscore", "int")
 >>> samples = [0, 0, 10, 10, 20, 20]
 >>> k = lambda a, b: np.exp(-np.abs(a - b))
 >>> vendiscore.compute(samples=samples, k=k)
-2.9999
+{"VS": 2.9999...}
 ```
 
 If you already have precomputed a similarity matrix:

vendiscore.py

@@ -145,6 +145,7 @@ class VendiScore(evaluate.Metric):
         device="cpu",
     ):
         if score_K:
+            print(samples)
             vs = vendi.score_K(np.array(samples), normalize=normalize)
         elif score_dual:
             vs = vendi.score_dual(np.array(samples), normalize=normalize)