do not use range_test results for tuning

server/website/website/tasks/async_tasks.py

@@ -448,6 +448,9 @@ def train_ddpg(train_ddpg_input):
     params = JSONUtil.loads(session.hyperparameters)
     session_results = Result.objects.filter(session=session,
                                             creation_time__lt=result.creation_time)
+    for i, result in enumerate(session_results):
+        if 'range_test' in result.metric_data.name:
+            session_results.pop(i)
     target_data = {}
     target_data['newest_result_id'] = result_id
 

server/website/website/utils.py

@@ -153,6 +153,8 @@ class DataUtil(object):
         rowlabels = np.empty(len(results), dtype=int)
 
         for i, result in enumerate(results):
+            if 'range_test' in result.metric_data.name:
+                continue
             param_data = JSONUtil.loads(result.knob_data.data)
             if len(param_data) != len(knob_labels):
                 raise Exception(

server/website/website/views.py

@@ -645,7 +645,7 @@ def handle_result_files(session, files, execution_times=None):
         if 'status' in summary and summary['status'] == "range_test":
             # The metric should not be used for learning because the driver did not run workload
             # We tag the metric as invalid, so later they will be set to the worst result
-            metric_data.name = metric_data.name + '*'
+            metric_data.name = 'range_test_' + metric_data.name + '*'
             metric_data.save()
 
         # Create a new workload if this one does not already exist