AntoineH/smart_augmentation
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Cross Validation splits + New mesure process time (train utils)

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Harle, Antoine (Contracteur) 2020-02-03 15:08:22 -05:00
parent bce882de38
commit 385bc9977c
3 changed files with 51 additions and 30 deletions
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34
higher/smart_aug/test_dataug.py
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@ -13,19 +13,19 @@ tf_names = [
'Identity',
'FlipUD',
'FlipLR',
#'Rotate',
#'TranslateX',
#'TranslateY',
#'ShearX',
#'ShearY',
'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
'Contrast',
'Color',
'Brightness',
'Sharpness',
'Posterize',
'Solarize', #=>Image entre [0,1] #Pas opti pour des batch
#Color TF (Common mag scale)
#'+Contrast',
@ -74,12 +74,12 @@ if __name__ == "__main__":
#Task to perform
tasks={
'classic',
#'aug_model'
#'classic',
'aug_model'
}
#Parameters
n_inner_iter = 1
epochs = 2
epochs = 150
dataug_epoch_start=0
optim_param={
'Meta':{
@ -147,7 +147,7 @@ if __name__ == "__main__":
tf_dict = {k: TF.TF_dict[k] for k in tf_names}
model = Higher_model(model, model_name) #run_dist_dataugV3
aug_model = Augmented_model(Data_augV5(TF_dict=tf_dict, N_TF=2, mix_dist=0.8, fixed_prob=False, fixed_mag=False, shared_mag=False), model).to(device)
aug_model = Augmented_model(Data_augV5(TF_dict=tf_dict, N_TF=3, mix_dist=0.8, fixed_prob=False, fixed_mag=False, shared_mag=False), model).to(device)
#aug_model = Augmented_model(RandAug(TF_dict=tf_dict, N_TF=2), model).to(device)
print("{} on {} for {} epochs - {} inner_it".format(str(aug_model), device_name, epochs, n_inner_iter))
@ -156,7 +156,7 @@ if __name__ == "__main__":
inner_it=n_inner_iter,
dataug_epoch_start=dataug_epoch_start,
opt_param=optim_param,
print_freq=1,
print_freq=20,
unsup_loss=1,
hp_opt=False,
save_sample_freq=None)
@ -174,7 +174,7 @@ if __name__ == "__main__":
"Param_names": aug_model.TF_names(),
"Log": log}
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)
filename = "{}-{} epochs (dataug:{})- {} in_it".format(str(aug_model),epochs,dataug_epoch_start,n_inner_iter)+"(CV)"
with open("../res/log/%s.json" % filename, "w+") as f:
try:
json.dump(out, f, indent=True)