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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 get_mean_masked_features_distance(mean_features_0, mean_features_1, mean_masks_0, mean_masks_1, n_features_per_channel=None, ):
 """Compute the distance between the mean masked features."""


    assert n_features_per_channel > 0

    mu_0 = mean_features_0.ravel()
    mu_1 = mean_features_1.ravel()

    omeg_0 = mean_masks_0
    omeg_1 = mean_masks_1

    omeg_0 = np.repeat(omeg_0, n_features_per_channel)
    omeg_1 = np.repeat(omeg_1, n_features_per_channel)

    d_0 = mu_0 * omeg_0
    d_1 = mu_1 * omeg_1

    return np.linalg.norm(d_0 - d_1)