code: def sliced_gan():
    
    hparams = common_hparams.basic_params1()
    hparams.optimizer = "adam"
    hparams.learning_rate_constant = 0.0002
    hparams.learning_rate_warmup_steps = 500
    hparams.learning_rate_schedule = "constant * linear_warmup"
    hparams.label_smoothing = 0.0
    hparams.batch_size = 128
    hparams.hidden_size = 128
    hparams.initializer = "uniform_unit_scaling"
    hparams.initializer_gain = 1.0
    hparams.weight_decay = 1e-6
    hparams.kernel_height = 4
    hparams.kernel_width = 4
    hparams.bottleneck_bits = 128
    hparams.add_hparam("discriminator_batchnorm", True)
    hparams.add_hparam("num_sliced_vecs", 4096)
    return hparams
docs: Basic parameters for a vanilla_gan.