AntoineH/smart_augmentation
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Ajout fonctionnalitees apprentissage parametre optimisateur + mix dist

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Harle, Antoine (Contracteur) 2020-01-16 16:38:15 -05:00
parent 75901b69b4
commit cd4b0405b9
3 changed files with 70 additions and 37 deletions
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27
higher/test_dataug.py
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@ -67,7 +67,7 @@ if __name__ == "__main__":
'aug_model'
}
n_inner_iter = 1
epochs = 15
epochs = 150
dataug_epoch_start=0
optim_param={
'Meta':{
@ -81,9 +81,10 @@ if __name__ == "__main__":
}
}
#model = LeNet(3,10)
model = LeNet(3,10)
#model = ResNet(num_classes=10)
#Lents
#model = MobileNetV2(num_classes=10)
model = ResNet(num_classes=10)
#model = WideResNet(num_classes=10, wrn_size=32)
model = Higher_model(model) #run_dist_dataugV3
@ -94,8 +95,8 @@ if __name__ == "__main__":
model = model.to(device)
print("{} on {} for {} epochs".format(str(model), device_name, epochs))
#log= train_classic(model=model, opt_param=optim_param, epochs=epochs, print_freq=10)
log= train_classic_higher(model=model, epochs=epochs)
log= train_classic(model=model, opt_param=optim_param, epochs=epochs, print_freq=1)
#log= train_classic_higher(model=model, epochs=epochs)
exec_time=time.process_time() - t0
####
@ -181,6 +182,7 @@ if __name__ == "__main__":
opt_param=optim_param,
print_freq=1,
KLdiv=True,
hp_opt=True,
loss_patience=None)
exec_time=time.process_time() - t0
@ -189,12 +191,17 @@ if __name__ == "__main__":
times = [x["time"] for x in log]
out = {"Accuracy": max([x["acc"] for x in log]), "Time": (np.mean(times),np.std(times), exec_time), 'Optimizer': optim_param, "Device": device_name, "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)#+"demi_mag"
filename = "{}-{} epochs (dataug:{})- {} in_it".format(str(aug_model),epochs,dataug_epoch_start,n_inner_iter)+"-opt_hp"
with open("res/log/%s.json" % filename, "w+") as f:
json.dump(out, f, indent=True)
print('Log :\"',f.name, '\" saved !')
plot_resV2(log, fig_name="res/"+filename, param_names=aug_model.TF_names())
try:
json.dump(out, f, indent=True)
print('Log :\"',f.name, '\" saved !')
except:
print("Failed to save logs :",f.name)
try:
plot_resV2(log, fig_name="res/"+filename, param_names=aug_model.TF_names())
except:
print("Failed to plot res")
print('Execution Time : %.00f '%(exec_time))
print('-'*9)