AntoineH/smart_augmentation
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Ajout des B_TF + chgt mag initiale

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Harle, Antoine (Contracteur) 2019-11-22 11:22:57 -05:00
parent 758d6e9b78
commit 12ff3ee115
3 changed files with 29 additions and 17 deletions
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34
higher/test_dataug.py
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@ -6,21 +6,27 @@ from train_utils import *
tf_names = [
## Geometric TF ##
'Identity',
#'FlipUD',
'FlipUD',
'FlipLR',
'Rotate',
#'TranslateX',
#'TranslateY',
'TranslateX',
'TranslateY',
'ShearX',
'ShearY',
#'BRotate',
#'BTranslateX',
#'BTranslateY',
#'BShearX',
#'BShearY',
## Color TF (Expect image in the range of [0, 1]) ##
'Contrast',
'Color',
'Brightness',
'Sharpness',
'Posterize',
#'Solarize', #=>Image entre [0,1] #Pas opti pour des batch
'Solarize', #=>Image entre [0,1] #Pas opti pour des batch
#Non fonctionnel
#'Auto_Contrast', #Pas opti pour des batch (Super lent)
@ -37,7 +43,7 @@ else:
##########################################
if __name__ == "__main__":
n_inner_iter = 0
n_inner_iter = 10
epochs = 100
dataug_epoch_start=0
@ -68,11 +74,11 @@ if __name__ == "__main__":
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=2, mix_dist=0.5, 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_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)
log= run_dist_dataugV2(model=aug_model, epochs=epochs, inner_it=n_inner_iter, dataug_epoch_start=dataug_epoch_start, print_freq=10, loss_patience=None)
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=None)
####
print('-'*9)
@ -91,16 +97,16 @@ if __name__ == "__main__":
'''
#### TF tests ####
#'''
res_folder="res/good_TF_tests/"
epochs= 100
inner_its = [0, 10]
dist_mix = [0.0, 0.5]
res_folder="res/brutus-tests/"
epochs= 150
inner_its = [0, 1, 10]
dist_mix = [0.0, 0.5, 1]
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= [1]#[1, 2, 3, 4]
mag_setup = [(True,True)]#[(True,True), (False,True), (False, False)]
nb_run= 1
N_seq_TF= [1, 2, 3, 4]
mag_setup = [(True,True), (False,True), (False, False)]
nb_run= 3
try:
os.mkdir(res_folder)