make /temp_util to temporarily store stuff while refactoring is happening

test/MetaAugment/test_ucb_learner.py

+import MetaAugment.autoaugment_learners as aal
+import MetaAugment.child_networks as cn
+import torch
+import torchvision
+import torchvision.datasets as datasets
+
+import random
+
+
+def test_ucb_learner():
+    policies = UCB1_JC.generate_policies(num_policies, num_sub_policies)
+        q_values, best_q_values = UCB1_JC.run_UCB1(
+                                                policies,
+                                                batch_size, 
+                                                learning_rate, 
+                                                ds, 
+                                                toy_size, 
+                                                max_epochs, 
+                                                early_stop_num, 
+                                                iterations, 
+                                                IsLeNet, 
+                                                ds_name
+                                                )     
+        best_q_values = np.array(best_q_values)
+    pass
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