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shift_applicator.py
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# -------------------------------------------------
# IMPORTS
# -------------------------------------------------
from data_utils import *
# -------------------------------------------------
# SHIFT APPLICATOR
# -------------------------------------------------
def apply_shift(X_te_orig, y_te_orig, shift, orig_dims, datset):
X_te_1 = None
y_te_1 = None
if shift == 'rand':
print('Randomized')
X_te_1 = X_te_orig.copy()
y_te_1 = y_te_orig.copy()
elif shift == 'large_gn_shift_1.0':
print('Large GN shift')
normalization = 255.0
X_te_1, _ = gaussian_noise_subset(X_te_orig, 100.0, normalization=normalization, delta_total=1.0)
y_te_1 = y_te_orig.copy()
elif shift == 'medium_gn_shift_1.0':
print('Medium GN Shift')
normalization = 255.0
X_te_1, _ = gaussian_noise_subset(X_te_orig, 10.0, normalization=normalization, delta_total=1.0)
y_te_1 = y_te_orig.copy()
elif shift == 'small_gn_shift_1.0':
print('Small GN Shift')
normalization = 255.0
X_te_1, _ = gaussian_noise_subset(X_te_orig, 1.0, normalization=normalization, delta_total=1.0)
y_te_1 = y_te_orig.copy()
elif shift == 'large_gn_shift_0.5':
print('Large GN shift')
normalization = 255.0
X_te_1, _ = gaussian_noise_subset(X_te_orig, 100.0, normalization=normalization, delta_total=0.5)
y_te_1 = y_te_orig.copy()
elif shift == 'medium_gn_shift_0.5':
print('Medium GN Shift')
normalization = 255.0
X_te_1, _ = gaussian_noise_subset(X_te_orig, 10.0, normalization=normalization, delta_total=0.5)
y_te_1 = y_te_orig.copy()
elif shift == 'small_gn_shift_0.5':
print('Small GN Shift')
normalization = 255.0
X_te_1, _ = gaussian_noise_subset(X_te_orig, 1.0, normalization=normalization, delta_total=0.5)
y_te_1 = y_te_orig.copy()
elif shift == 'large_gn_shift_0.1':
print('Large GN shift')
normalization = 255.0
X_te_1, _ = gaussian_noise_subset(X_te_orig, 100.0, normalization=normalization, delta_total=0.1)
y_te_1 = y_te_orig.copy()
elif shift == 'medium_gn_shift_0.1':
print('Medium GN Shift')
normalization = 255.0
X_te_1, _ = gaussian_noise_subset(X_te_orig, 10.0, normalization=normalization, delta_total=0.1)
y_te_1 = y_te_orig.copy()
elif shift == 'small_gn_shift_0.1':
print('Small GN Shift')
normalization = 255.0
X_te_1, _ = gaussian_noise_subset(X_te_orig, 1.0, normalization=normalization, delta_total=0.1)
y_te_1 = y_te_orig.copy()
elif shift == 'adversarial_shift_1.0':
print('Large adversarial shift')
adv_samples, true_labels = adversarial_samples(datset)
X_te_1, y_te_1, _ = data_subset(X_te_orig, y_te_orig, adv_samples, true_labels, delta=1.0)
elif shift == 'adversarial_shift_0.5':
print('Medium adversarial Shift')
adv_samples, true_labels = adversarial_samples(datset)
X_te_1, y_te_1, _ = data_subset(X_te_orig, y_te_orig, adv_samples, true_labels, delta=0.5)
elif shift == 'adversarial_shift_0.1':
print('Small adversarial Shift')
adv_samples, true_labels = adversarial_samples(datset)
X_te_1, y_te_1, _ = data_subset(X_te_orig, y_te_orig, adv_samples, true_labels, delta=0.1)
elif shift == 'ko_shift_0.1':
print('Small knockout shift')
X_te_1, y_te_1 = knockout_shift(X_te_orig, y_te_orig, 0, 0.1)
elif shift == 'ko_shift_0.5':
print('Medium knockout shift')
X_te_1, y_te_1 = knockout_shift(X_te_orig, y_te_orig, 0, 0.5)
elif shift == 'ko_shift_1.0':
print('Large knockout shift')
X_te_1, y_te_1 = knockout_shift(X_te_orig, y_te_orig, 0, 1.0)
elif shift == 'small_img_shift_0.1':
print('Small image shift')
X_te_1, _ = image_generator(X_te_orig, orig_dims, 10, 0.05, 0.05, 0.1, 0.1, False, False, delta=0.1)
y_te_1 = y_te_orig.copy()
elif shift == 'small_img_shift_0.5':
print('Small image shift')
X_te_1, _ = image_generator(X_te_orig, orig_dims, 10, 0.05, 0.05, 0.1, 0.1, False, False, delta=0.5)
y_te_1 = y_te_orig.copy()
elif shift == 'small_img_shift_1.0':
print('Small image shift')
X_te_1, _ = image_generator(X_te_orig, orig_dims, 10, 0.05, 0.05, 0.1, 0.1, False, False, delta=1.0)
y_te_1 = y_te_orig.copy()
elif shift == 'medium_img_shift_0.1':
print('Medium image shift')
X_te_1, _ = image_generator(X_te_orig, orig_dims, 40, 0.2, 0.2, 0.2, 0.2, True, False, delta=0.1)
y_te_1 = y_te_orig.copy()
elif shift == 'medium_img_shift_0.5':
print('Medium image shift')
X_te_1, _ = image_generator(X_te_orig, orig_dims, 40, 0.2, 0.2, 0.2, 0.2, True, False, delta=0.5)
y_te_1 = y_te_orig.copy()
elif shift == 'medium_img_shift_1.0':
print('Medium image shift')
X_te_1, _ = image_generator(X_te_orig, orig_dims, 40, 0.2, 0.2, 0.2, 0.2, True, False, delta=1.0)
y_te_1 = y_te_orig.copy()
elif shift == 'large_img_shift_0.1':
print('Large image shift')
X_te_1, _ = image_generator(X_te_orig, orig_dims, 90, 0.4, 0.4, 0.3, 0.4, True, True, delta=0.1)
y_te_1 = y_te_orig.copy()
elif shift == 'large_img_shift_0.5':
print('Large image shift')
X_te_1, _ = image_generator(X_te_orig, orig_dims, 90, 0.4, 0.4, 0.3, 0.4, True, True, delta=0.5)
y_te_1 = y_te_orig.copy()
elif shift == 'large_img_shift_1.0':
print('Large image shift')
X_te_1, _ = image_generator(X_te_orig, orig_dims, 90, 0.4, 0.4, 0.3, 0.4, True, True, delta=1.0)
y_te_1 = y_te_orig.copy()
elif shift == 'medium_img_shift_0.5+ko_shift_0.1':
print('Medium image shift + knockout shift')
X_te_1, _ = image_generator(X_te_orig, orig_dims, 40, 0.2, 0.2, 0.2, 0.2, True, False, delta=0.5)
y_te_1 = y_te_orig.copy()
X_te_1, y_te_1 = knockout_shift(X_te_1, y_te_1, 0, 0.1)
elif shift == 'medium_img_shift_0.5+ko_shift_0.5':
print('Medium image shift + knockout shift')
X_te_1, _ = image_generator(X_te_orig, orig_dims, 40, 0.2, 0.2, 0.2, 0.2, True, False, delta=0.5)
y_te_1 = y_te_orig.copy()
X_te_1, y_te_1 = knockout_shift(X_te_1, y_te_1, 0, 0.5)
elif shift == 'medium_img_shift_0.5+ko_shift_1.0':
print('Medium image shift + knockout shift')
X_te_1, _ = image_generator(X_te_orig, orig_dims, 40, 0.2, 0.2, 0.2, 0.2, True, False, delta=0.5)
y_te_1 = y_te_orig.copy()
X_te_1, y_te_1 = knockout_shift(X_te_1, y_te_1, 0, 1.0)
elif shift == 'only_zero_shift+medium_img_shift_0.1':
print('Only zero shift + Medium image shift')
X_te_1, y_te_1 = only_one_shift(X_te_orig, y_te_orig, 0)
X_te_1, _ = image_generator(X_te_1, orig_dims, 40, 0.2, 0.2, 0.2, 0.2, True, False, delta=0.1)
elif shift == 'only_zero_shift+medium_img_shift_0.5':
print('Only zero shift + Medium image shift')
X_te_1, y_te_1 = only_one_shift(X_te_orig, y_te_orig, 0)
X_te_1, _ = image_generator(X_te_1, orig_dims, 40, 0.2, 0.2, 0.2, 0.2, True, False, delta=0.5)
elif shift == 'only_zero_shift+medium_img_shift_1.0':
print('Only zero shift + Medium image shift')
X_te_1, y_te_1 = only_one_shift(X_te_orig, y_te_orig, 0)
X_te_1, _ = image_generator(X_te_1, orig_dims, 40, 0.2, 0.2, 0.2, 0.2, True, False, delta=1.0)
return (X_te_1, y_te_1)