AntoineH/smart_augmentation
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Test Brutus skip res deja obtenu

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Harle, Antoine (Contracteur) 2019-11-25 12:14:58 -05:00
parent b3b607c011
commit 27751411a5
1 changed files with 9 additions and 5 deletions
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14
higher/test_dataug.py
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@ -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)