with tf.Session() as sess:
    # Initialize image
    sess.run(tf.global_variables_initializer())
    sess.run(layers['input'].assign(generate_noise_image()))

    for epoch in range(epochs):
      epoch_loss, epoch_content_loss, epoch_style_loss, _ = sess.run([J_total,J_content,J_style,optimizer])

      if (epoch+1) % 100 == 0:
        generated_image = sess.run(layers['input'])
        generated_image = save_image(generated_image,prefix + '_' + str(epoch+1) + '.jpg')
        print('Loss after epoch %d: \nT: %f, \nC: %f, \nS: %f'%(epoch,epoch_loss,epoch_content_loss,epoch_style_loss))
        generated_image = cv2.cvtColor(generated_image, cv2.COLOR_RGB2BGR)
        cv2_imshow(generated_image)