updates

examples/model_compress/model_prune_torch.py

@@ -59,7 +59,7 @@
         'pruner_class': L1FilterPruner,
         'config_list': [{
             'sparsity': 0.5,
-            'op_types': ['default'],
+            'op_types': ['Conv2d'],
             'op_names': ['feature.0', 'feature.24', 'feature.27', 'feature.30', 'feature.34', 'feature.37']
         }]
     },
@@ -69,7 +69,7 @@
         'pruner_class': ActivationMeanRankFilterPruner,
         'config_list': [{
             'sparsity': 0.5,
-            'op_types': ['default'],
+            'op_types': ['Conv2d'],
             'op_names': ['feature.0', 'feature.24', 'feature.27', 'feature.30', 'feature.34', 'feature.37']
         }]
     },

test/nni_test/nnitest/validators.py

@@ -35,8 +35,8 @@ def check_metrics(self, nni_source_dir, **kwargs):
             assert len(trial_final_result) == 1, 'there should be 1 final result'
             assert trial_final_result[0] == expected_metrics['final_result']
             # encode dict/number into json string to compare them in set
-            assert set([json.dumps(x) for x in trial_intermediate_result]) \
-                == set([json.dumps(x) for x in expected_metrics['intermediate_result']])
+            assert set([json.dumps(x, sort_keys=True) for x in trial_intermediate_result]) \
+                == set([json.dumps(x, sort_keys=True) for x in expected_metrics['intermediate_result']])
 
     def get_metric_results(self, metrics):
         intermediate_result = {}