AntoineH/smart_augmentation
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Antoine Harlé 2024-08-20 11:53:35 +02:00 • committed by AntoineH
parent 03ffd7fe05
commit b89dac9084
185 changed files with 16668 additions and 484 deletions
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42
higher/smart_aug/benchmark.py
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@ -7,19 +7,22 @@ from train_utils import *
from transformations import TF_loader
import torchvision.models as models
from LeNet import *
#model_list={models.resnet: ['resnet18', 'resnet50','wide_resnet50_2']} #lr=0.1
model_list={models.resnet: ['resnet18']}
model_list={models.resnet: ['wide_resnet50_2']}
optim_param={
'Meta':{
'optim':'Adam',
'lr':1e-2, #1e-2
'lr':5e-3, #1e-2
'epoch_start': 2, #0 / 2 (Resnet?)
'reg_factor': 0.001,
'scheduler': None, #None, 'multiStep'
},
'Inner':{
'optim': 'SGD',
'lr':1e-1, #1e-2/1e-1 (ResNet)
'lr':1e-2, #1e-2/1e-1 (ResNet)
'momentum':0.9, #0.9
'decay':0.0005, #0.0005
'nesterov':False, #False (True: Bad behavior w/ Data_aug)
@ -28,16 +31,17 @@ optim_param={
}
res_folder="../res/benchmark/CIFAR10/"
#res_folder="../res/benchmark/MNIST/"
#res_folder="../res/HPsearch/"
epochs= 200
dataug_epoch_start=0
nb_run= 1
nb_run= 3
tf_config='../config/wide_tf_config.json' #'../config/wide_tf_config.json'#'../config/base_tf_config.json'
tf_config='../config/bad_tf_config.json' #'../config/wide_tf_config.json'#'../config/base_tf_config.json'
TF_loader=TF_loader()
tf_dict, tf_ignore_mag =TF_loader.load_TF_dict(tf_config)
device = torch.device('cuda')
device = torch.device('cuda:1')
if device == torch.device('cpu'):
device_name = 'CPU'
@ -54,8 +58,8 @@ np.random.seed(0)
if __name__ == "__main__":
### Benchmark ###
#'''
inner_its = [3]
'''
inner_its = [0]
dist_mix = [0.5]
N_seq_TF= [3]
mag_setup = [(False, False)] #[(True, True), (False, False)] #(FxSh, Independant)
@ -74,6 +78,8 @@ if __name__ == "__main__":
t0 = time.perf_counter()
model = getattr(model_type, model_name)(pretrained=False, num_classes=len(dl_train.dataset.classes))
#model_name = 'LeNet'
#model = LeNet(3,10)
model = Higher_model(model, model_name) #run_dist_dataugV3
if n_inner_iter!=0:
@ -122,12 +128,17 @@ if __name__ == "__main__":
print('Log :\"',f.name, '\" saved !')
except:
print("Failed to save logs :",f.name)
try:
plot_resV2(log, fig_name=res_folder+filename, param_names=aug_model.TF_names())
except:
print("Failed to plot res")
print(sys.exc_info()[1])
print('Execution Time : %.00f '%(exec_time))
print('-'*9)
#'''
### Benchmark - RandAugment/Vanilla ###
'''
### Benchmark - RandAugment/Vanilla ###
#'''
for model_type in model_list.keys():
for model_name in model_list[model_type]:
for run in range(nb_run):
@ -155,7 +166,7 @@ if __name__ == "__main__":
#"Rand_Aug": rand_aug,
"Log": log}
print(model_name,": acc", out["Accuracy"], "in:", out["Time"][0], "+/-", out["Time"][1])
filename = "{}-{} epochs -{}".format(model_name,epochs, run)
filename = "{}-{} epochs -{}-basicDA".format(model_name,epochs, run)
#print("RandAugment-",model_name,": acc", out["Accuracy"], "in:", out["Time"][0], "+/-", out["Time"][1])
#filename = "RandAugment(N{}-M{:.2f})-{}-{} epochs -{}".format(rand_aug['N'],rand_aug['M'],model_name,epochs, run)
with open(res_folder+"log/%s.json" % filename, "w+") as f:
@ -166,11 +177,14 @@ if __name__ == "__main__":
print("Failed to save logs :",f.name)
print(sys.exc_info()[1])
#plot_resV2(log, fig_name=res_folder+filename)
try:
plot_resV2(log, fig_name=res_folder+filename, param_names=aug_model.TF_names())
except:
print("Failed to plot res")
print(sys.exc_info()[1])
print('Execution Time : %.00f '%(exec_time))
print('-'*9)
'''
#'''
### HP Search ###
'''
from LeNet import *