code: def grad_to_image(gradient):
      
      gradient = gradient - gradient.min()
      gradient /= gradient.max()
      gradient = np.uint8(gradient * 255).transpose(1, 2, 0)
      gradient = gradient[..., ::-1]
      return gradient
docs: Convert gradients of image obtained using `get_image_grad`
      into image. This shows parts of the image that is most strongly activating
      the output neurons.