code: def imagetransformer2d_base_8l_8_64_64by64():
      """hparams fo 12 layer big 2d model for imagenet 64x64."""
      hparams = image_transformer2d_base()
      hparams.num_heads = 8
      hparams.hidden_size = 512
      hparams.filter_size = 2048
      hparams.num_decoder_layers = 8
      hparams.batch_size = 1
      hparams.layer_prepostprocess_dropout = 0.1
      hparams.query_shape = (8, 64)
      hparams.memory_flange = (4, 32)
      hparams.unconditional = int(False)
      hparams.max_length = 14000
      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 9 for calling a global function with example usage: imagetransformer2d_base_8l_8_64_64by64() and returns: hparams