AntoineH/smart_augmentation
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MaJ example simple + Suppression Nesterov momentum

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Harle, Antoine (Contracteur) 2020-02-17 17:32:54 -05:00
parent b170af076f
commit d53b385c43
4 changed files with 22 additions and 129 deletions
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45
higher/smart_aug/benchmark.py
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@ -19,7 +19,7 @@ optim_param={
'lr':1e-1, #1e-2/1e-1 (ResNet)
'momentum':0.9, #0.9
'decay':0.0005, #0.0005
'nesterov':True,
'nesterov':False, #False (True: Bad behavior w/ Data_aug)
'scheduler':'cosine', #None, 'cosine', 'multiStep', 'exponential'
}
}
@ -30,44 +30,6 @@ epochs= 200
dataug_epoch_start=0
nb_run= 3
# Use available TF (see transformations.py)
'''
tf_names = [
## Geometric TF ##
'Identity',
'FlipUD',
'FlipLR',
'Rotate',
'TranslateX',
'TranslateY',
'ShearX',
'ShearY',
## 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
## Bad Tranformations ##
# Bad Geometric TF #
#'BShearX',
#'BShearY',
#'BTranslateX-',
#'BTranslateX-',
#'BTranslateY',
#'BTranslateY-',
#'BadContrast',
#'BadBrightness',
#'Random',
#'RandBlend'
]
tf_dict = {k: TF.TF_dict[k] for k in tf_names}
'''
tf_config='../config/base_tf_config.json'
TF_loader=TF_loader()
tf_dict, tf_ignore_mag =TF_loader.load_TF_dict(tf_config)
@ -91,7 +53,7 @@ if __name__ == "__main__":
### Benchmark ###
#'''
n_inner_iter = 1
dist_mix = [0.5]#[0.5, 1.0]
dist_mix = [0.5, 1.0]
N_seq_TF= [3, 4]
mag_setup = [(False, False)] #[(True, True), (False, False)] #(FxSh, Independant)
@ -117,7 +79,8 @@ if __name__ == "__main__":
mix_dist=dist,
fixed_prob=False,
fixed_mag=m_setup[0],
shared_mag=m_setup[1]),
shared_mag=m_setup[1],
TF_ignore_mag=tf_ignore_mag),
model).to(device)
else:
aug_model = Augmented_model(RandAug(TF_dict=tf_dict, N_TF=n_tf), model).to(device)