diff --git a/higher/smart_aug/benchmark.py b/higher/smart_aug/benchmark.py
index fcaa90f..d71baa4 100644
--- a/higher/smart_aug/benchmark.py
+++ b/higher/smart_aug/benchmark.py
@@ -14,7 +14,7 @@ optim_param={
     },
     'Inner':{
         'optim': 'SGD',
-        'lr':1e-1, #1e-2
+        'lr':1e-1, #1e-2 #1e-1 for ResNet
         'momentum':0.9, #0.9
     }
 }
@@ -58,6 +58,8 @@ tf_names = [
     #'Random',
     #'RandBlend'
 ]
+tf_dict = {k: TF.TF_dict[k] for k in tf_names}
+
 
 device = torch.device('cuda')
 
@@ -75,9 +77,8 @@ np.random.seed(0)
 ##########################################
 if __name__ == "__main__":
 
-
-    tf_dict = {k: TF.TF_dict[k] for k in tf_names}
-
+    ### Benchmark ###
+    '''
     for model_type in model_list.keys():
             for model_name in model_list[model_type]:
                 model = getattr(model_type, model_name)(pretrained=False)
@@ -124,14 +125,15 @@ if __name__ == "__main__":
 
                 print('Execution Time : %.00f '%(exec_time))
                 print('-'*9)
+    
+    '''
 
+    ### HP Search ###
     inner_its = [1]
     dist_mix = [0.0, 0.5, 0.8, 1.0]
     dataug_epoch_starts= [0]
-    tf_dict = {k: TF.TF_dict[k] for k in tf_names}
-    TF_nb = [len(tf_dict)] #range(10,len(TF.TF_dict)+1) #[len(TF.TF_dict)]
-    N_seq_TF= [4, 3, 2]
-    mag_setup = [(True,True), (False, False)] #(Fixed, Shared)
+    N_seq_TF= [2, 3, 4]
+    mag_setup = [(True,True), (False, False)] #(FxSh, Independant)
     #prob_setup = [True, False]
     nb_run= 3
     
@@ -149,12 +151,10 @@ if __name__ == "__main__":
                         #for p_setup in prob_setup:
                         p_setup=False
                         for run in range(nb_run):
-                            if (n_inner_iter == 0 and (m_setup!=(True,True) and p_setup!=True)) or (p_setup and dist!=0.0): continue #Autres setup inutiles sans meta-opti
-                            #keys = list(TF.TF_dict.keys())[0:i]
-                            #ntf_dict = {k: TF.TF_dict[k] for k in keys}
 
                             t0 = time.process_time()
 
+                            model = getattr(model_list.keys()[0], 'resnet18')(pretrained=False)
                             model = Higher_model(model) #run_dist_dataugV3
                             aug_model = Augmented_model(Data_augV5(TF_dict=tf_dict, N_TF=n_tf, mix_dist=dist, fixed_prob=p_setup, fixed_mag=m_setup[0], shared_mag=m_setup[1]), model).to(device)
                             #aug_model = Augmented_model(RandAug(TF_dict=tf_dict, N_TF=2), model).to(device)
@@ -183,10 +183,6 @@ if __name__ == "__main__":
                                     print('Log :\"',f.name, '\" saved !')
                                 except:
                                     print("Failed to save logs :",f.name)
-                            try:
-                                plot_resV2(log, fig_name="../res/"+filename, param_names=aug_model.TF_names())
-                            except:
-                                print("Failed to plot res")
 
                             print('Execution Time : %.00f '%(exec_time))
                             print('-'*9)