def neural_style_loss(style, combination, num_channels, img_width, img_height):
    assert K.ndim(style) == 3
    assert K.ndim(combination) == 3
    S = gram_matrix(style)
    C = gram_matrix(combination)
    size = img_width * img_height
    return K.sum(K.square(C - S)) / (4. * (num_channels ** 2) * (size ** 2))
dataset/ETHPy150Open awentzonline/image-analogies/image_analogy/losses/neural_style.py/neural_style_loss/swapped operands of `-`