threshold = 0.7
perturbed_pixes = np.random.uniform(size=noisy_x_train.shape) > threshold
noisy_x_train = noisy_x_train + np.random.uniform(size=noisy_x_train.shape)*255*perturbed_pixes
noisy_x_train = noisy_x_train.clip(0,255)
perturbed_pixes = np.random.uniform(size=noisy_x_test.shape) > threshold
noisy_x_test = noisy_x_test + np.random.uniform(size=noisy_x_test.shape)*255*perturbed_pixes
noisy_x_test = noisy_x_test.clip(0,255)
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