code: def imagetransformer_base_10l_8h_big_uncond_dr03_dan_64_2d():
      """big 1d model for unconditional generation on imagenet."""
      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
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import numpy
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.layers import common_image_attention
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import modalities
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import t2t_model
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 8 for calling a global function with example usage: imagetransformer_base_10l_8h_big_uncond_dr03_dan_64_2d() and returns: hparams