[FIX] fix skip_test default value

examples/dataset_image_workflow/workflow.py

@@ -77,7 +77,7 @@ class ImageDatasetWorkflow:
 
         logger.info("Total Item: %d" % (len(self.image_market)))
 
-    def image_example(self, rebuild=False, skip_test=True):
+    def image_example(self, rebuild=False, skip_test=False):
         np.random.seed(1)
         random.seed(1)
         self.n_labeled_list = [100, 200, 500, 1000, 2000, 4000]
@@ -112,7 +112,9 @@ class ImageDatasetWorkflow:
                 test_dataset = TensorDataset(test_x, test_y)
 
                 user_stat_spec = generate_stat_spec(type="image", X=test_x, whitening=False)
-                user_info = BaseUserInfo(semantic_spec=self.user_semantic, stat_info={user_stat_spec.type: user_stat_spec})
+                user_info = BaseUserInfo(
+                    semantic_spec=self.user_semantic, stat_info={user_stat_spec.type: user_stat_spec}
+                )
                 logger.info("Searching Market for user: %d" % (i))
 
                 search_result = self.image_market.search_learnware(user_info)
@@ -195,7 +197,9 @@ class ImageDatasetWorkflow:
                         _, user_model_acc = evaluate(model, test_dataset, distribution=True)
                         user_model_score_list.append(user_model_acc)
 
-                        reuse_pruning = EnsemblePruningReuser(learnware_list=mixture_learnware_list, mode="classification")
+                        reuse_pruning = EnsemblePruningReuser(
+                            learnware_list=mixture_learnware_list, mode="classification"
+                        )
                         reuse_pruning.fit(x_train, y_train)
                         _, pruning_acc = evaluate(reuse_pruning, test_dataset, distribution=False)
                         reuse_pruning_score_list.append(pruning_acc)