AntoineH/smart_augmentation
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Benchmark pour HP search

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Harle, Antoine (Contracteur) 2020-01-30 12:07:46 -05:00
parent 8f89eb0e0a
commit bf29d4fb6d
1 changed files with 11 additions and 15 deletions
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26
higher/smart_aug/benchmark.py
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@ -14,7 +14,7 @@ optim_param={
}, },
'Inner':{ 'Inner':{
'optim': 'SGD', 'optim': 'SGD',
'lr':1e-1, #1e-2 'lr':1e-1, #1e-2 #1e-1 for ResNet
'momentum':0.9, #0.9 'momentum':0.9, #0.9
} }
} }
@ -58,6 +58,8 @@ tf_names = [
#'Random', #'Random',
#'RandBlend' #'RandBlend'
] ]
tf_dict = {k: TF.TF_dict[k] for k in tf_names}
device = torch.device('cuda') device = torch.device('cuda')
@ -75,9 +77,8 @@ np.random.seed(0)
########################################## ##########################################
if __name__ == "__main__": if __name__ == "__main__":
### Benchmark ###
tf_dict = {k: TF.TF_dict[k] for k in tf_names} '''
for model_type in model_list.keys(): for model_type in model_list.keys():
for model_name in model_list[model_type]: for model_name in model_list[model_type]:
model = getattr(model_type, model_name)(pretrained=False) model = getattr(model_type, model_name)(pretrained=False)
@ -125,13 +126,14 @@ if __name__ == "__main__":
print('Execution Time : %.00f '%(exec_time)) print('Execution Time : %.00f '%(exec_time))
print('-'*9) print('-'*9)
'''
### HP Search ###
inner_its = [1] inner_its = [1]
dist_mix = [0.0, 0.5, 0.8, 1.0] dist_mix = [0.0, 0.5, 0.8, 1.0]
dataug_epoch_starts= [0] dataug_epoch_starts= [0]
tf_dict = {k: TF.TF_dict[k] for k in tf_names} N_seq_TF= [2, 3, 4]
TF_nb = [len(tf_dict)] #range(10,len(TF.TF_dict)+1) #[len(TF.TF_dict)] mag_setup = [(True,True), (False, False)] #(FxSh, Independant)
N_seq_TF= [4, 3, 2]
mag_setup = [(True,True), (False, False)] #(Fixed, Shared)
#prob_setup = [True, False] #prob_setup = [True, False]
nb_run= 3 nb_run= 3
@ -149,12 +151,10 @@ if __name__ == "__main__":
#for p_setup in prob_setup: #for p_setup in prob_setup:
p_setup=False p_setup=False
for run in range(nb_run): for run in range(nb_run):
if (n_inner_iter == 0 and (m_setup!=(True,True) and p_setup!=True)) or (p_setup and dist!=0.0): continue #Autres setup inutiles sans meta-opti
#keys = list(TF.TF_dict.keys())[0:i]
#ntf_dict = {k: TF.TF_dict[k] for k in keys}
t0 = time.process_time() t0 = time.process_time()
model = getattr(model_list.keys()[0], 'resnet18')(pretrained=False)
model = Higher_model(model) #run_dist_dataugV3 model = Higher_model(model) #run_dist_dataugV3
aug_model = Augmented_model(Data_augV5(TF_dict=tf_dict, N_TF=n_tf, mix_dist=dist, fixed_prob=p_setup, fixed_mag=m_setup[0], shared_mag=m_setup[1]), model).to(device) aug_model = Augmented_model(Data_augV5(TF_dict=tf_dict, N_TF=n_tf, mix_dist=dist, fixed_prob=p_setup, fixed_mag=m_setup[0], shared_mag=m_setup[1]), model).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), model).to(device)
@ -183,10 +183,6 @@ if __name__ == "__main__":
print('Log :\"',f.name, '\" saved !') print('Log :\"',f.name, '\" saved !')
except: except:
print("Failed to save logs :",f.name) 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('Execution Time : %.00f '%(exec_time))
print('-'*9) print('-'*9)