general {

    base_exp_dir = ./outs/

    recording = [

        ./,

        ./models

    ]

}

dataset {

    data_dir = data/

    data_name = carnew1w_norm.npz

}

dataset2 {

    data_dir = data/

    data_name = carnew1w_norm.npz

}

train {

    learning_rate = 0.001

    maxiter = 10000

    warm_up_end = 1000

    eval_num_points = 100000

    batch_size = 5000

    save_freq = 5000

    val_freq = 5000

    report_freq = 1000

    igr_weight = 0.1

    mask_weight = 0.0

    labmda_non_mfd = 100

    labmda_mfd = 0.4

    labmda_adl = 0.01

    labmda_scc = 0.01

}

model {

    sdf_network {

        d_out = 1

        d_in = 3

        d_hidden = 256

        n_layers = 8

        skip_in = [4]

        multires = 0

        bias = 0.5

        scale = 1.0

        geometric_init = True

        weight_norm = True

    }

        discriminator {

    }

}