AntoineH/smart_augmentation
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Changement permission fichiers + Simplification utilisation Augmented_dataset

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Harle, Antoine (Contracteur) 2019-12-04 14:48:11 -05:00
parent adaac437b6
commit b26fbcd2a2
619 changed files with 41 additions and 13049 deletions
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13
higher/train_utils.py Normal file → Executable file
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@ -47,7 +47,7 @@ def compute_vaLoss(model, dl_it, dl):
return F.cross_entropy(model(xs), ys)
def train_classic(model, epochs=1):
def train_classic(model, epochs=1, print_freq=1):
device = next(model.parameters()).device
#opt = torch.optim.Adam(model.parameters(), lr=1e-3)
optim = torch.optim.SGD(model.parameters(), lr=1e-2, momentum=0.9)
@ -80,6 +80,15 @@ def train_classic(model, epochs=1):
val_loss = F.cross_entropy(model(xs_val), ys_val)
accuracy, _ =test(model)
model.train()
#### Print ####
if(print_freq and epoch%print_freq==0):
print('-'*9)
print('Epoch : %d/%d'%(epoch,epochs))
print('Time : %.00f'%(tf - t0))
print('Train loss :',loss.item(), '/ val loss', val_loss.item())
print('Accuracy :', accuracy)
#### Log ####
data={
"epoch": epoch,
@ -619,7 +628,7 @@ def run_dist_dataugV2(model, epochs=1, inner_it=0, dataug_epoch_start=0, print_f
if epoch>50:
meta_opt.step()
model['data_aug'].adjust_param(soft=False) #Contrainte sum(proba)=1
#model['data_aug'].next_TF_set()
#model['data_aug'].next_TF_set()
fmodel = higher.patch.monkeypatch(model, device=None, copy_initial_weights=True)
diffopt = higher.optim.get_diff_optim(inner_opt, model.parameters(),fmodel=fmodel, track_higher_grads=high_grad_track)