optimizer.step(closure)
Performs a single optimization step (parameter update).
Parameters: closure (callable) – A closure that reevaluates the model and returns the loss. Optional for most optimizers.

def closure():
    # correct the values of updated input image
    input_img.data.clamp_(0, 1)

    optimizer.zero_grad()
    model(input_img)
    style_score = 0
    content_score = 0

    for sl in style_losses:
        style_score += sl.loss
    for cl in content_losses:
        content_score += cl.loss

    style_score *= style_weight
    content_score *= content_weight

    loss = style_score + content_score
    loss.backward()

    run[0] += 1
    if run[0] % 50 == 0:
        print("run {}:".format(run))
        print('Style Loss : {:4f} Content Loss: {:4f}'.format(
            style_score.item(), content_score.item()))
        print()

    return style_score + content_score

optimizer.step(closure)