def bt(self, loader='test_loader'):
print("Benign training")
self.args['robust_training'] = False
ac = AdversarialCompression(self.args)
model = ac.get_full_model()
ac.print_metrics(model, loader=loader, unmask_metrics=True)
def gtc(self, loader='test_loader'):
# no adversarial robustness
self.args['robust_training'] = False
self.args['orthogonality'] = False
self.args['spectral_normalization'] = False
self.args['ortho_lambda'] = 0
# some noise corruption
self.args['gaussian_training'] = True
assert self.args['train_corruption_strength'] in [1, 2, 3, 4, 5]
# assert some compression
assert self.args['gamma_lambda'] != 0
# no noise removal
self.args['noise_removal'] = False
ac = AdversarialCompression(self.args)
model = ac.get_small_model()
ac.print_metrics(model, type='small', loader=loader)
def atc(self):
# only adversarial robustness
self.args['robust_training'] = True
self.args['orthogonality'] = False
self.args['spectral_normalization'] = False
self.args['ortho_lambda'] = 0
# no noise corruption
self.args['gaussian_training'] = False
self.args['train_corruption_strength'] = 1
self.args['test_corruption'] = 'none'
self.args['test_corruption_strength'] = 1
# assert some compression
assert self.args['gamma_lambda'] != 0
# no noise removal
self.args['noise_removal'] = False
ac = AdversarialCompression(self.args)
model = ac.get_small_model()
ac.print_metrics(model, type='small')
def at(self, loader='test_loader'):
# no adversarial robustness
self.args['robust_training'] = True
self.args['orthogonality'] = False
self.args['spectral_normalization'] = False
self.args['ortho_lambda'] = 0
# no noise corruption
self.args['gaussian_training'] = False
self.args['train_corruption_strength'] = 1
self.args['test_corruption'] = 'none'
self.args['test_corruption_strength'] = 1
# no compression
self.args['gamma_lambda'] = 0
# no noise removal
self.args['noise_removal'] = False
ac = AdversarialCompression(self.args)
model = ac.get_full_model()
ac.print_metrics(model,loader=loader)
def train(self, loader='test_loader'):
ac = AdversarialCompression(self.args)
model = ac.get_full_model()
ac.print_metrics(model, loader=loader, unmask_metrics=False)