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Test MobileNet Brutus

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Harle, Antoine (Contracteur) 2019-12-06 14:19:05 -05:00
parent d68034eec1
commit 240ec5e581
2 changed files with 13 additions and 12 deletions
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24
higher/test_brutus.py
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@ -35,18 +35,21 @@ if __name__ == "__main__":
n_inner_iter = 1 n_inner_iter = 1
epochs = 100 epochs = 150
dataug_epoch_start=0 dataug_epoch_start=0
#model = LeNet(3,10)
model = MobileNetV2(num_classes=10)
#model = WideResNet(num_classes=10, wrn_size=32)
tf_dict = {k: TF.TF_dict[k] for k in tf_names} tf_dict = {k: TF.TF_dict[k] for k in tf_names}
t0 = time.process_time() t0 = time.process_time()
aug_model = Augmented_model(Data_augV5(TF_dict=tf_dict, N_TF=3, mix_dist=0.0, fixed_prob=False, fixed_mag=False, shared_mag=False), WideResNet(num_classes=10, wrn_size=32)).to(device) aug_model = Augmented_model(Data_augV5(TF_dict=tf_dict, N_TF=3, mix_dist=0.0, fixed_prob=True, fixed_mag=True, shared_mag=True), model).to(device)
#aug_model = Augmented_model(RandAug(TF_dict=tf_dict, N_TF=2), WideResNet(num_classes=10, wrn_size=32)).to(device)
print(str(aug_model), 'on', device_name) print("{} on {} for {} epochs - {} inner_it".format(str(aug_model), device_name, epochs, n_inner_iter))
#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, KLdiv=True, 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=None, loss_patience=None)
exec_time=time.process_time() - t0 exec_time=time.process_time() - t0
#### ####
@ -60,11 +63,10 @@ if __name__ == "__main__":
#### ####
t0 = time.process_time() t0 = time.process_time()
#aug_model = Augmented_model(Data_augV5(TF_dict=tf_dict, N_TF=3, mix_dist=0.0, fixed_prob=False, fixed_mag=False, shared_mag=False), WideResNet(num_classes=10, wrn_size=32)).to(device) aug_model = Augmented_model(RandAug(TF_dict=tf_dict, N_TF=2), model).to(device)
aug_model = Augmented_model(RandAug(TF_dict=tf_dict, N_TF=2), WideResNet(num_classes=10, wrn_size=32)).to(device)
print(str(aug_model), 'on', device_name) print("{} on {} for {} epochs - {} inner_it".format(str(aug_model), device_name, epochs, n_inner_iter))
#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, KLdiv=True, 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=None, loss_patience=None)
exec_time=time.process_time() - t0 exec_time=time.process_time() - t0
#### ####

1
higher/test_dataug.py
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@ -149,7 +149,6 @@ if __name__ == "__main__":
#aug_model = Augmented_model(RandAug(TF_dict=tf_dict, N_TF=2), 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)) print("{} on {} for {} epochs - {} inner_it".format(str(aug_model), device_name, epochs, n_inner_iter))
#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, KLdiv=True, 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=10, KLdiv=True, loss_patience=None)
exec_time=time.process_time() - t0 exec_time=time.process_time() - t0