def create_vae_diffusers_config():
    """
    Creates a config for the diffusers based on the config of the LDM model.
    """
    block_out_channels = [VAE_PARAMS_CH * mult for mult in VAE_PARAMS_CH_MULT]
    down_block_types = ["DownEncoderBlock2D"] * len(block_out_channels)
    up_block_types = ["UpDecoderBlock2D"] * len(block_out_channels)

    config = dict(
        sample_size=VAE_PARAMS_RESOLUTION,
        in_channels=VAE_PARAMS_IN_CHANNELS,
        out_channels=VAE_PARAMS_OUT_CH,
        down_block_types=tuple(down_block_types),
        up_block_types=tuple(up_block_types),
        block_out_channels=tuple(block_out_channels),
        latent_channels=VAE_PARAMS_Z_CHANNELS,
        layers_per_block=VAE_PARAMS_NUM_RES_BLOCKS,
    )
    return config

    Creates a config for the diffusers based on the config of the LDM model.
    
scripts/train_kohya/utils/model_utils.py