fix

README.md

@@ -22,11 +22,11 @@ It is the average of the precision scores computer after each relevant document
 >>> my_new_module = evaluate.load("map")
 >>> references= [json.dumps({"q_1":{"d_1":1, "d_2":2} }), 
              json.dumps({"q_2":{"d_2":1, "d_3":2, "d_5":3}})] 
->>> predictions = [json.dumps({"q_1": { "d_1": 0.9, "d_2": 0.8}}),
+>>> predictions = [json.dumps({"q_1": { "d_1": 0.8, "d_2": 0.9}}),
          json.dumps({"q_2": {"d_2": 0.9, "d_1": 0.8, "d_5": 0.7, "d_3": 0.3}})]
 >>> results = my_new_module.compute(references=references, predictions=predictions)
 >>> print(results)
-{'map': 0.902777}
+{'map': 1.0}
 ```
 ### Inputs
 - **predictions:** a list of dictionaries where each dictionary consists of document relevancy scores produced by the model for a given query. One dictionary per query. The dictionaries should be converted to string. 

map.py

@@ -54,11 +54,11 @@ Examples:
     >>> my_new_module = evaluate.load("map")
     >>> references= [json.dumps({"q_1":{"d_1":1, "d_2":2} }), 
              json.dumps({"q_2":{"d_2":1, "d_3":2, "d_5":3}})] 
-    >>> predictions = [json.dumps({"q_1": { "d_1": 0.9, "d_2": 0.8}}),
+    >>> predictions = [json.dumps({"q_1": { "d_1": 0.8, "d_2": 0.9}}),
          json.dumps({"q_2": {"d_2": 0.9, "d_1": 0.8, "d_5": 0.7, "d_3": 0.3}})]
     >>> results = my_new_module.compute(references=references, predictions=predictions)
     >>> print(results)
-    {'map': 0.902777}
+    {'recall': 1.0}
 """
 
 @evaluate.utils.file_utils.add_start_docstrings(_DESCRIPTION, _KWARGS_DESCRIPTION)
@@ -74,7 +74,7 @@ class map(evaluate.Metric):
             features=datasets.Features({
                 'predictions':  datasets.Value("string"),
                 'references':  datasets.Value("string"),
-                'k': datasets.Value("int", default=None)    
+                'k': datasets.Value("int")    
             }),
             # Homepage of the module for documentation
             reference_urls=["https://amenra.github.io/ranx/"]