Correcting inputs

path_planning_evaluate.py

@@ -53,7 +53,7 @@ Returns:
 Examples:
 
     >>> my_new_module = evaluate.load("rfr2003/path_planning_evaluate")
-    >>> results = my_new_module.compute(predictions=['[(0,0), (0,1), (1,1)]', '[(0,0), (1,0), (1,1)]', '[(0,0), (1,0), (1,1), (0,1)]', '(0,0'], golds=[[(0,0), (0,1), (1,1)], [(0,0), (0,1), (1,1)], [(0,0), (0,1)], []], obstacles=[[(1,0)], [(1,0)], [], []], ends=[[(1,1)], [(1,1)], [(0,1)], [(0,1)]], n=[2, 2, 2, 2])
+    >>> results = my_new_module.compute(generations=['[(0,0), (0,1), (1,1)]', '[(0,0), (1,0), (1,1)]', '[(0,0), (1,0), (1,1), (0,1)]', '(0,0'], golds=[[(0,0), (0,1), (1,1)], [(0,0), (0,1), (1,1)], [(0,0), (0,1)], []], obstacles=[[(1,0)], [(1,0)], [], []], ends=[[(1,1)], [(1,1)], [(0,1)], [(0,1)]], n=[2, 2, 2, 2])
     >>> print(results)
     {'compliance_ratio': 0.75, 'success_ratio': 0.6666666666666666,'optimal_ratio': 0.3333333333333333, 'feasible_ratio': 0.6666666666666666, 'distance': 0, 'unreachable_acc': 1.0}
 """
@@ -75,8 +75,8 @@ class Path_Planning_evaluate(evaluate.Metric):
             features=datasets.Features({
                 'generations': datasets.Value('string'),
                 'golds': datasets.Sequence(datasets.Sequence(datasets.Value('int64'))),
-                'obstacles': datasets.Sequence(datasets.Sequence(datasets.Value('int64'))),
-                'ends': datasets.Sequence(datasets.Sequence(datasets.Value('int64'))),
+                'obstacles': datasets.Sequence(datasets.Value('int64')),
+                'ends': datasets.Sequence(datasets.Value('int64')),
                 'n': datasets.Sequence(datasets.Value('int64')),
             }),
         )