small necesary changes in evo_learner

MetaAugment/autoaugment_learners/autoaugment.py

@@ -238,8 +238,6 @@ class AutoAugment(torch.nn.Module):
             if probs[i] <= p:
                 op_meta = self._augmentation_space(10, F.get_image_size(img))
                 magnitudes, signed = op_meta[op_name]
-                print("magnitude_id: ", magnitude_id)
-                print("magnitudes[magnitude_id]: ", magnitudes[magnitude_id])
                 magnitude = float(magnitudes[magnitude_id].item()) if magnitude_id is not None else 0.0
                 if signed and signs[i] == 0:
                     magnitude *= -1.0

MetaAugment/autoaugment_learners/evo_learner.py

@@ -297,7 +297,7 @@ class evo_learner(aa_learner):
                     full_policy = self.get_single_policy_cov(test_x)[0]
 
 
-            fit_val = self.test_autoaugment_policy(full_policy,child_network_architecture,train_dataset,test_dataset) #) /
+            fit_val = self._test_autoaugment_policy(full_policy,child_network_architecture,train_dataset,test_dataset) #) /
                       #  + self.test_autoaugment_policy(full_policy, train_dataset, test_dataset)) / 2
 
             self.policy_result.append([full_policy, fit_val])