Tests influence nb TF

higher/dataug.py

@@ -316,6 +316,8 @@ class Data_augV3(nn.Module): #Echantillonage uniforme/Mixte
 class Data_augV4(nn.Module): #Transformations avec mask
     def __init__(self, TF_dict=TF.TF_dict, N_TF=1, mix_dist=0.0):
         super(Data_augV4, self).__init__()
+        assert len(TF_dict)>0
+        
         self._data_augmentation = True
 
         #self._TF_matrix={}

higher/test_dataug.py

@@ -696,7 +696,7 @@ def run_dist_dataugV2(model, epochs=1, inner_it=0, dataug_epoch_start=0, print_f
             model.augment(mode=True)
             if inner_it != 0: high_grad_track = True
 
-    print("Copy ", countcopy)
+    #print("Copy ", countcopy)
     return log
 
 ##########################################
@@ -728,7 +728,7 @@ if __name__ == "__main__":
     print('-'*9)
     '''
     #### Augmented Model ####
-    #'''
+    '''
     aug_model = Augmented_model(Data_augV4(TF_dict=TF.TF_dict, mix_dist=0.0), LeNet(3,10)).to(device)
     print(str(aug_model), 'on', device_name)
     #run_simple_dataug(inner_it=n_inner_iter, epochs=epochs)
@@ -744,7 +744,43 @@ if __name__ == "__main__":
         json.dump(out, f, indent=True)
         print('Log :\"',f.name, '\" saved !')
     print('-'*9)
-    #'''
+    '''
+    ## TF number tests ##
+    res_folder="res/TF_nb_tests/"
+    epochs= 200
+    inner_its = [0, 10]
+    dataug_epoch_starts= [0, -1]
+    max_TF_nb = len(TF.TF_dict)
+    
+    try:
+        os.mkdir(res_folder)
+        os.mkdir(res_folder+"log/")
+    except FileExistsError:
+        pass
+
+    for n_inner_iter in inner_its:
+        print("---Starting inner_it", n_inner_iter,"---")
+        for dataug_epoch_start in dataug_epoch_starts:
+            print("---Starting dataug", dataug_epoch_start,"---")
+            for i in range(1,max_TF_nb):
+                keys = list(TF.TF_dict.keys())[0:i]
+                ntf_dict = {k: TF.TF_dict[k] for k in keys}
+
+                aug_model = Augmented_model(Data_augV4(TF_dict=ntf_dict, mix_dist=0.0), LeNet(3,10)).to(device)
+                print(str(aug_model), 'on', device_name)
+                #run_simple_dataug(inner_it=n_inner_iter, epochs=epochs)
+                log= run_dist_dataugV2(model=aug_model, epochs=epochs, inner_it=n_inner_iter, dataug_epoch_start=dataug_epoch_start, print_freq=1, loss_patience=10)
+
+                ####
+                plot_res(log, fig_name=res_folder+"{}-{} epochs (dataug:{})- {} in_it".format(str(aug_model),epochs,dataug_epoch_start,n_inner_iter))
+                print('-'*9)
+                times = [x["time"] for x in log]
+                out = {"Accuracy": max([x["acc"] for x in log]), "Time": (np.mean(times),np.std(times)), "Device": device_name, "Param_names": aug_model.TF_names(), "Log": log}
+                print(str(aug_model),": acc", out["Accuracy"], "in (ms):", out["Time"][0], "+/-", out["Time"][1])
+                with open(res_folder+"log/%s.json" % "{}-{} epochs (dataug:{})- {} in_it".format(str(aug_model),epochs,dataug_epoch_start,n_inner_iter), "w+") as f:
+                    json.dump(out, f, indent=True)
+                    print('Log :\"',f.name, '\" saved !')
+                print('-'*9)
 
     #### Comparison ####
     '''
@@ -757,8 +793,8 @@ if __name__ == "__main__":
         #"res/log/Aug_mod(Data_augV4(Mix 0,5-3 TF)-LeNet)-100 epochs (dataug:0)- 1 in_it.json",
         #"res/log/Aug_mod(Data_augV4(Mix 0.5-3 TF)-LeNet)-100 epochs (dataug:50)- 10 in_it.json",
         #"res/log/Aug_mod(Data_augV4(Uniform-3 TF)-LeNet)-100 epochs (dataug:0)- 10 in_it.json",
-        "res/log/Aug_mod(Data_augV4(Uniform-10 TF)-LeNet)-100 epochs (dataug:50)- 10 in_it.json",
+        #"res/log/Aug_mod(Data_augV4(Uniform-10 TF)-LeNet)-100 epochs (dataug:50)- 10 in_it.json",
-        "res/log/Aug_mod(Data_augV4(Uniform-10 TF)-LeNet)-100 epochs (dataug:50)- 0 in_it.json",
+        #"res/log/Aug_mod(Data_augV4(Uniform-10 TF)-LeNet)-100 epochs (dataug:50)- 0 in_it.json",
     ]
     plot_compare(filenames=files, fig_name="res/compare")
     '''

higher/utils.py

@@ -43,6 +43,7 @@ def plot_res(log, fig_name='res'):
 
     fig_name = fig_name.replace('.',',')
     plt.savefig(fig_name)
+    plt.close()
 
 def plot_compare(filenames, fig_name='res'):
 
@@ -82,6 +83,7 @@ def plot_compare(filenames, fig_name='res'):
     fig_name = fig_name.replace('.',',')
 
     plt.savefig(fig_name, bbox_inches='tight')
+    plt.close()
 
 def viz_sample_data(imgs, labels, fig_name='data_sample'):
 
@@ -97,6 +99,7 @@ def viz_sample_data(imgs, labels, fig_name='data_sample'):
         plt.xlabel(labels[i].item())
 
     plt.savefig(fig_name)
+    plt.close()
 
 def model_copy(src,dst, patch_copy=True, copy_grad=True):
     #model=copy.deepcopy(fmodel) #Pas approprie, on ne souhaite que les poids/grad (pas tout fmodel et ses etats)