return dict

metrics/crps/crps.py

@@ -61,14 +61,17 @@
 Examples:
 
     >>> crps_metric = evaluate.load("crps")
-    >>> predictions = np.array([0.1, 0.2, 0.3, 0.4, 0.5])
+    >>> predictions = np.array([[0.1, 0.2, 0.3, 0.4, 0.5]])
     >>> references = np.array([0.3])
     >>> results = crps_metric.compute(predictions=predictions, references=references)
     >>> print(results)
-    {'mase': 0.18333333333333335}
-
-
+    {'crps': 1.9999999254941967}
 
+    >>> crps_metric = evaluate.load("crps", "multilist")
+    >>> predictions = [[[0, 2, 4]], [[-1, 2, 5]], [[8, -5, 6]]]
+    >>> references = [[0.5], [-1], [7]]
+    >>> print(results)
+    {'crps': 3.0522875816993467}
 """
 
 
@@ -126,9 +129,9 @@ def _compute(
             )
 
         if multioutput == "raw_values":
-            return weighted_quantile_loss
+            return {"crps": weighted_quantile_loss}
         elif multioutput == "uniform_average":
-            return np.average(weighted_quantile_loss)
+            return {"crps": np.average(weighted_quantile_loss)}
         else:
             raise ValueError(
                 "The multioutput parameter should be one of the following: "