code: def imagetransformer_base_12l_8h_big():
    
    hparams = imagetransformer_sep_channels_8l_8h()
    hparams.filter_size = 1024
    hparams.num_decoder_layers = 12
    hparams.batch_size = 1
    hparams.hidden_size = 512
    hparams.learning_rate_warmup_steps = 4000
    hparams.sampling_method = "random"
    hparams.beam_size = 1
    hparams.block_width = 256
    return hparams
docs: big 1d model for conditional image generation.