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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:

def add_noise(weights, other_weights):
    '''add noise to the layer.
    '''
    w_range = np.ptp(other_weights.flatten())
    noise_range = NOISE_RATIO * w_range
    noise = np.random.uniform(-noise_range / 2.0, noise_range / 2.0, weights.shape)
    return np.add(noise, weights)