img = base_img.copy().reshape(1,WIDTH,HEIGHT,3).astype('float32')

step=0.001
for i in range(100):
    loss_value, grad_values = eval_loss_and_grads(img)
    img -= step * grad_values

img2 = img.copy().reshape(WIDTH,HEIGHT,3)
img2 = np.clip(img2*255, 0, 255).astype('uint8')
plt.imshow(img2)
plt.axis('off')
plt.show()
