Пример #1
0
def d_r1_loss(real_pred, real_img):
    with conv2d_gradfix.no_weight_gradients():
        grad_real, = autograd.grad(
            outputs=real_pred.sum(), inputs=real_img, create_graph=True
        )
    grad_penalty = grad_real.pow(2).reshape(grad_real.shape[0], -1).sum(1).mean()

    return grad_penalty
def d_r1_loss(real_pred, real_img, args):
    if args.useConvdFix==True:
        print("I entered")
        from op import conv2d_gradfix
        with conv2d_gradfix.no_weight_gradients():
            grad_real, = autograd.grad(
                outputs=real_pred.sum(), inputs=real_img, create_graph=True
            )
    else:
        grad_real, = autograd.grad(
            outputs=real_pred.sum(), inputs=real_img, create_graph=True
        )
    grad_penalty = grad_real.pow(2).reshape(grad_real.shape[0], -1).sum(1).mean()

    return grad_penalty