Allow checkpoint merger to merge pix2pix models in the same way that it...

    tertiary_model_info = sd_models.checkpoints_list[tertiary_model_name] if theta_func1 else None

    result_is_inpainting_model = False

    result_is_pix2pix_model = False

    if theta_func2:

        shared.state.textinfo = f"Loading B"

                if a.shape[1] == 4 and b.shape[1] == 9:

                    raise RuntimeError("When merging inpainting model with a normal one, A must be the inpainting model.")

                if a.shape[1] == 8 and b.shape[1] == 4:#If we have an InstructPix2Pix model...

                    print("Detected possible merge of instruct model with non-instruct model.")

                    theta_0[key][:, 0:4, :, :] = theta_func2(a[:, 0:4, :, :], b, multiplier)#Merge only the vectors the models have in common.  Otherwise we get an error due to dimension mismatch.

                    result_is_pix2pix_model = True

                else:

                    assert a.shape[1] == 9 and b.shape[1] == 4, f"Bad dimensions for merged layer {key}: A={a.shape}, B={b.shape}"

                    theta_0[key][:, 0:4, :, :] = theta_func2(a[:, 0:4, :, :], b, multiplier)

                    result_is_inpainting_model = True

            else:

    filename = filename_generator() if custom_name == '' else custom_name

    filename += ".inpainting" if result_is_inpainting_model else ""

    filename += ".pix2pix" if result_is_pix2pix_model else ""

    filename += "." + checkpoint_format

    output_modelname = os.path.join(ckpt_dir, filename)