option to pad prompt/neg prompt to be same length

    timer.record("scripts callbacks")

    with devices.autocast(), torch.no_grad():

        sd_model.cond_stage_model_empty_prompt = sd_model.cond_stage_model([""])

    timer.record("calculate empty prompt")

    print(f"Model loaded in {timer.summary()}.")

    return sd_model

            x_in = x_in[:-batch_size]

            sigma_in = sigma_in[:-batch_size]

        # TODO add infotext entry

        if shared.opts.pad_cond_uncond and tensor.shape[1] != uncond.shape[1]:

            empty = shared.sd_model.cond_stage_model_empty_prompt

            num_repeats = (tensor.shape[1] - uncond.shape[1]) // empty.shape[1]

            if num_repeats < 0:

                tensor = torch.cat([tensor, empty.repeat((tensor.shape[0], -num_repeats, 1))], axis=1)

            elif num_repeats > 0:

                uncond = torch.cat([uncond, empty.repeat((uncond.shape[0], num_repeats, 1))], axis=1)

        if tensor.shape[1] == uncond.shape[1] or skip_uncond:

            if is_edit_model:

                cond_in = torch.cat([tensor, uncond, uncond])

    "token_merging_ratio": OptionInfo(0.0, "Token merging ratio", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}).link("PR", "https://github.com/AUTOMATIC1111/stable-diffusion-webui/pull/9256").info("0=disable, higher=faster"),

    "token_merging_ratio_img2img": OptionInfo(0.0, "Token merging ratio for img2img", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}).info("only applies if non-zero and overrides above"),

    "token_merging_ratio_hr": OptionInfo(0.0, "Token merging ratio for high-res pass", gr.Slider, {"minimum": 0.0, "maximum": 0.9, "step": 0.1}).info("only applies if non-zero and overrides above"),

    "pad_cond_uncond": OptionInfo(False, "Pad prompt/negative prompt to be same length").info("improves performance when prompt and negative prompt have different lengths; changes seeds"),

}))

options_templates.update(options_section(('compatibility', "Compatibility"), {