From 27751411a5970cec8321bf96567f10367a315c36 Mon Sep 17 00:00:00 2001
From: "Harle, Antoine (Contracteur)" <Antoine.Harle@Teledyne.com>
Date: Mon, 25 Nov 2019 12:14:58 -0500
Subject: [PATCH] Test Brutus skip res deja obtenu

---
 higher/test_dataug.py | 14 +++++++++-----
 1 file changed, 9 insertions(+), 5 deletions(-)

diff --git a/higher/test_dataug.py b/higher/test_dataug.py
index d4d391e..5b82b0f 100644
--- a/higher/test_dataug.py
+++ b/higher/test_dataug.py
@@ -74,11 +74,11 @@ if __name__ == "__main__":
     print('-'*9)
     '''
     #### Augmented Model ####
-    '''
+    #'''
     t0 = time.process_time()
     tf_dict = {k: TF.TF_dict[k] for k in tf_names}
     #tf_dict = TF.TF_dict
-    aug_model = Augmented_model(Data_augV5(TF_dict=tf_dict, N_TF=1, mix_dist=0.0, fixed_prob=False, fixed_mag=True, shared_mag=True), LeNet(3,10)).to(device)
+    aug_model = Augmented_model(Data_augV5(TF_dict=tf_dict, N_TF=1, mix_dist=0.0, fixed_prob=True, fixed_mag=False, shared_mag=False), LeNet(3,10)).to(device)
     #aug_model = Augmented_model(Data_augV5(TF_dict=tf_dict, N_TF=2, mix_dist=0.5, fixed_mag=True, shared_mag=True), WideResNet(num_classes=10, wrn_size=160)).to(device)
     print(str(aug_model), 'on', device_name)
     #run_simple_dataug(inner_it=n_inner_iter, epochs=epochs)
@@ -98,7 +98,7 @@ if __name__ == "__main__":
 
     print('Execution Time : %.00f '%(time.process_time() - t0))
     print('-'*9)
-    '''
+    #'''
     #### TF tests ####
     #'''
     res_folder="res/brutus-tests/"
@@ -110,6 +110,7 @@ if __name__ == "__main__":
     TF_nb = [len(tf_dict)] #range(10,len(TF.TF_dict)+1) #[len(TF.TF_dict)]
     N_seq_TF= [1, 2, 3, 4]
     mag_setup = [(True,True), (False, False)]
+    #prob_setup = [True, False]
     nb_run= 3
     
     try:
@@ -124,11 +125,14 @@ if __name__ == "__main__":
                 for dist in dist_mix:
                     #for i in TF_nb:
                     for m_setup in mag_setup:
+                        #for p_setup in prob_setup:
                         for run in range(nb_run):
+                            if n_inner_iter == 0 and (m_setup!=(True,True) or p_setup!=True): continue #Autres setup inutiles sans meta-opti
+                            if n_inner_iter ==1 and (n_tf==1 or n_tf==2): continue #Deja resultats
                             #keys = list(TF.TF_dict.keys())[0:i]
                             #ntf_dict = {k: TF.TF_dict[k] for k in keys}
 
-                            aug_model = Augmented_model(Data_augV5(TF_dict=tf_dict, N_TF=n_tf, mix_dist=dist, fixed_mag=m_setup[0], shared_mag=m_setup[1]), LeNet(3,10)).to(device)
+                            aug_model = Augmented_model(Data_augV5(TF_dict=tf_dict, N_TF=n_tf, mix_dist=dist, fixed_prob=False, fixed_mag=m_setup[0], shared_mag=m_setup[1]), 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=20, loss_patience=None)
@@ -137,7 +141,7 @@ if __name__ == "__main__":
                             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 (s?):", out["Time"][0], "+/-", out["Time"][1])
+                            print(str(aug_model),": acc", out["Accuracy"], "in :", out["Time"][0], "+/-", out["Time"][1])
                             filename = "{}-{}epochs(dataug:{})-{}in_it-{}".format(str(aug_model),epochs,dataug_epoch_start,n_inner_iter,run)
                             with open(res_folder+"log/%s.json" % filename, "w+") as f:
                                 json.dump(out, f, indent=True)