code: def imagetransformer_base_10l_8h_big_uncond_dr03_dan_64_2d():
    
    hparams = image_transformer2d_base()
    hparams.unconditional = True
    hparams.hidden_size = 512
    hparams.batch_size = 1
    hparams.img_len = 64
    hparams.num_heads = 8
    hparams.filter_size = 2048
    hparams.batch_size = 1
    hparams.max_length = 3075
    hparams.max_length = 14000
    hparams.layer_preprocess_sequence = "none"
    hparams.layer_postprocess_sequence = "dan"
    hparams.layer_prepostprocess_dropout = 0.1
    hparams.dec_attention_type = cia.AttentionType.LOCAL_2D
    hparams.query_shape = (16, 16)
    hparams.memory_flange = (8, 8)
    return hparams
docs: big 1d model for unconditional generation on imagenet.