AntoineH/smart_augmentation
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Ajout option Weight decay / Nesterov sur inner opt

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Harle, Antoine (Contracteur) 2020-02-10 16:32:59 -05:00
parent 65e67addf6
commit 383f63c7b8
3 changed files with 26 additions and 12 deletions
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20
higher/smart_aug/test_dataug.py
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@ -77,12 +77,12 @@ 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':{
@ -93,16 +93,18 @@ if __name__ == "__main__":
'optim': 'SGD',
'lr':1e-2, #1e-2
'momentum':0.9, #0.9
'decay':0.0001,
'nesterov':True,
}
}
#Models
model = LeNet(3,10)
#model = LeNet(3,10)
#model = ResNet(num_classes=10)
#import torchvision.models as models
import torchvision.models as models
#model=models.resnet18()
model_name = str(model) #'wide_resnet50_2' #'resnet18' #str(model)
#model = getattr(models.resnet, model_name)(pretrained=False)
model_name = 'resnet50' #'wide_resnet50_2' #'resnet18' #str(model)
model = getattr(models.resnet, model_name)(pretrained=False)
#### Classic ####
if 'classic' in tasks:
@ -111,7 +113,7 @@ if __name__ == "__main__":
print("{} on {} for {} epochs".format(model_name, device_name, epochs))
log= train_classic(model=model, opt_param=optim_param, epochs=epochs, print_freq=1)
log= train_classic(model=model, opt_param=optim_param, epochs=epochs, print_freq=10)
#log= train_classic_higher(model=model, epochs=epochs)
exec_time=time.perf_counter() - t0
@ -161,7 +163,7 @@ if __name__ == "__main__":
inner_it=n_inner_iter,
dataug_epoch_start=dataug_epoch_start,
opt_param=optim_param,
print_freq=1,
print_freq=10,
unsup_loss=1,
hp_opt=False,
save_sample_freq=None)