add cheap VAE approximation coeffs for SDXL

def cheap_approximation(sample):

    # https://discuss.huggingface.co/t/decoding-latents-to-rgb-without-upscaling/23204/2

    coefs = torch.tensor([

    if shared.sd_model.is_sdxl:

        coeffs = [

            [ 0.3448,  0.4168,  0.4395],

            [-0.1953, -0.0290,  0.0250],

            [ 0.1074,  0.0886, -0.0163],

            [-0.3730, -0.2499, -0.2088],

        ]

    else:

        coeffs = [

            [ 0.298,  0.207,  0.208],

            [ 0.187,  0.286,  0.173],

            [-0.158,  0.189,  0.264],

            [-0.184, -0.271, -0.473],

    ]).to(sample.device)

        ]

    coefs = torch.tensor(coeffs).to(sample.device)

    x_sample = torch.einsum("lxy,lr -> rxy", sample, coefs)